uuid
int64 0
6k
| title
stringlengths 8
285
| abstract
stringlengths 22
4.43k
|
|---|---|---|
5,500 | Association between Berlin questionnaire index and blood pressure, organ damage and metabolic profilein a general population | We evaluated the relationships between Berlin questionnaire (BQ) scores, hypertension and other metabolic variables in 598 subjects (age: 65.8 ± 10 years, mean ± SD) enrolled in the PAMELA (Pressioni Arteriose Monitorate E Loro Associazioni) study representative of the general population, treated or untreated with antihypertensive drugs. Two hundred and eleven subjects (35%) had a positive BQ with two or more positive categories of the inquiry. Compared to those without sleep disorders these subjects showed a greater male prevalence (55.9%), worse serum cholesterol, triglycerides and glucose profile, greater body mass index (BMI) (28.9 ± 4.9 vs. 24.9 ± 3.4 kg/m2 ), higher office (and to a lesser extent 24-h) BP and HR values, higher serum creatinine values and greater rate of echocardiographic left ventricular (LV) hypertrophy (25% vs. 13%). These differences were not detected when the data analysis was restricted to treated hypertensive patients. Thus, BQ scores allow to identify among subjects belonging to a general population those with elevated BP, organ damage and altered metabolic. When antihypertensive drug treatment is present, however, the approach fails to detect differences between groups with low or high BQ index. |
5,501 | The Role of Gut Microbiota and Trimethylamine N-oxide in Cardiovascular Diseases | Changes in the intestinal flora and its metabolites have been associated with cardiovascular disease (CVD). Short-chain fatty acids, bile acids, and especially trimethylamine N-oxide (TMAO), an endothelial toxic factor produced by gut microbiota from phosphatidylcholine in meat, have been identified to be closely related to endothelial cell dysfunction as well as tightly affiliated with CVD, the two main types being coronary artery disease (CAD) and coronary microvascular disease (CMVD). We discuss how changes in the gut flora and the metabolite TMAO contribute to the development of CAD and CMVD. The above insight might serve as a stepping stone for novel CAD and CMVD diagnostics and therapies centered on microbiota. |
5,502 | Global Metabonomic and Proteomic Analysis of Human Conjunctival Epithelial Cells (IOBA-NHC) in Response to Hyperosmotic Stress | "Dry eye" is a multifactorial inflammatory disease affecting the ocular surface. Tear hyperosmolarity in dry eye contributes to inflammation and cell damage. Recent research efforts on dry eye have been directed toward biomarker discovery for diagnosis, response to treatment, and disease mechanisms. This study employed a spontaneously immortalized normal human conjunctival cell line, IOBA-NHC, as a model to investigate hyperosmotic stress-induced changes of metabolites and proteins. Global and targeted metabonomic analyses as well as proteomic analysis were performed on IOBA-NHC cells incubated in serum-free media at 280 (control), 380, and 480 mOsm for 24 h. Twenty-one metabolites and seventy-six iTRAQ-identified proteins showed significant changes under at least one hyperosmotic stress treatment as compared with controls. SWATH-based proteomic analysis further confirmed the involvement of inflammatory pathways such as prostaglandin 2 synthesis in IOBA-NHC cells under hyperosmotic stress. This study is the first to identify glycerophosphocholine synthesis and O-linked β-N-acetylglucosamine glycosylation as key activated pathways in ocular surface cells under hyperosmotic stress. These findings extend the current knowledge in metabolite markers of dry eye and provide potential therapeutic targets for its treatment. |
5,503 | Long umbilical cord and its mysterious demeanour: A case report | True knots in the umbilical cord are rare, affecting approximately 1% of all pregnancies. The diagnosis may be missed antenatally during routine ultrasonography. Many known predisposing factors are associated with true knotting. In the majority of cases, it has no bearing on foetal outcome, but may rarely be linked to intra-uterine foetal death. |
5,504 | INFLUENCE OF STRUCTURED TEACHING ENVIRONMENT ON LEARNING ATTITUDE AND ACHIEVEMENT IN ART TEACHING | From Europe, America, and Asia, artistic ability is a part of national competitiveness has been constantly emphasised in today globalised society. Artistic ability and cognition of foreign culture are not only the important direction of strategic thinking, but also the basis of today economic and industrial competition. This study takes a university in Zhejiang as the research object. This study adopted experimental research, there being a total of 212 students from the university are selected; and the experimental teaching study was proceeded for 16 weeks (3 h a week and a total of 48 h). Research results are: (1) Structured learning environments affect learning attitudes; (2) Structured learning environments affect learning outcomes; (3) Learning attitude has a significant positive impact on learning outcomes. The results can help students to: improve their motivation for learning, enhance their active learning attitude, and develop the ability and attitude of independent learning. |
5,505 | Functional magnetic resonance imaging, deep learning, and Alzheimer's disease: A systematic review | Alzheimer's disease (AD) is currently diagnosed using a mixture of psychological tests and clinical observations. However, these diagnoses are not perfect, and additional diagnostic tools (e.g., MRI) can help improve our understanding of AD as well as our ability to detect the disease. Accordingly, a large amount of research has been invested into innovative diagnostic methods for AD. Functional MRI (fMRI) is a form of neuroimaging technology that has been used to diagnose AD; however, fMRI is incredibly noisy, complex, and thus lacks clinical use. Nonetheless, recent innovations in deep learning technology could enable the simplified and streamlined analysis of fMRI. Deep learning is a form of artificial intelligence that uses computer algorithms based on human neural networks to solve complex problems. For example, in fMRI research, deep learning models can automatically denoise images and classify AD by detecting patterns in participants' brain scans. In this systematic review, we investigate how fMRI (specifically resting-state fMRI) and deep learning methods are used to diagnose AD. In turn, we outline the common deep neural network, preprocessing, and classification methods used in the literature. We also discuss the accuracy, strengths, limitations, and future direction of fMRI deep learning methods. In turn, we aim to summarize the current field for new researchers, suggest specific areas for future research, and highlight the potential of fMRI to aid AD diagnoses. |
5,506 | Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks | State-of-the-art object detection networks depend on region proposal algorithms to hypothesize object locations. Advances like SPPnet [1] and Fast R-CNN [2] have reduced the running time of these detection networks, exposing region proposal computation as a bottleneck. In this work, we introduce a Region Proposal Network (RPN) that shares full-image convolutional features with the detection network, thus enabling nearly cost-free region proposals. An RPN is a fully convolutional network that simultaneously predicts object bounds and objectness scores at each position. The RPN is trained end-to-end to generate high-quality region proposals, which are used by Fast R-CNN for detection. We further merge RPN and Fast R-CNN into a single network by sharing their convolutional features-using the recently popular terminology of neural networks with 'attention' mechanisms, the RPN component tells the unified network where to look. For the very deep VGG-16 model [3], our detection system has a frame rate of 5 fps (including all steps) on a GPU, while achieving state-of-the-art object detection accuracy on PASCAL VOC 2007, 2012, and MS COCO datasets with only 300 proposals per image. In ILSVRC and COCO 2015 competitions, Faster R-CNN and RPN are the foundations of the 1st-place winning entries in several tracks. Code has been made publicly available. |
5,507 | Pan-Sharpening Based on Transformer With Redundancy Reduction | Pan-sharpening methods based on deep neural network (DNN) have produced the state-of-the-art results. However, the common information in the panchromatic (PAN) image and the low spatial resolution multispectral (LRMS) image is not sufficiently explored. As PAN and LRMS images are collected from the same scene, there exists some common information among them, in addition to their respective unique information. The direct concatenation of extracted features leads to some redundancy in the feature space. To reduce the redundancy among features and exploit the global information in source images, we proposed a novel pan-sharpening method by combining the convolution neural network and transformer. Specifically, PAN and LRMS images are encoded as unique features and common features by the subnetworks consisting of convolution blocks and transformer blocks. Then, the common features are averaged and combined with unique features from source images for the reconstruction of the fused image. To extract accurate common features, the equality constraint is imposed on them. Experimental results show that the proposed method outperforms the state-of-the-art methods on both reduced-scale and full-scale datasets. The source code is available at https://github.com/RSMagneto/TRRNet. |
5,508 | Ox40-Cre-mediated deletion of BRD4 reveals an unexpected phenotype of hair follicle stem cells in alopecia | BRD4 is a bromodomain extraterminal domain family member and functions primarily as a chromatin reader regulating genes involved in cell-fate decisions. Here, we bred Brd4fl/fl Ox40-Cre mice in which Brd4 was conditionally deleted in OX40-expressing cells to examine the role of BRD4 in regulating immune responses. We found that the Brd4fl/fl Ox40-Cre mice developed profound alopecia and dermatitis, while other organs and tissues were not affected. Surprisingly, lineage-tracing experiments using the Rosa26fl/fl-Yfp mice identified a subset of hair follicle stem cells (HFSCs) that constitutively express OX40, and deletion of Brd4 specifically in such HFSCs resulted in cell death and a complete loss of skin hair growth. We also found that death of HFSCs triggered massive activation of the intradermal γδ T cells, which induced epidermal hyperplasia and dermatitis by producing the inflammatory cytokine IL-17. Interestingly, deletion of Brd4 in Foxp3+ Tregs, which also constitutively express OX40, compromised their suppressive functions, and this, in turn, contributed to the enhanced activation of γδ T cells, as well as the severity of dermatitis and hair follicle destruction. Thus, our data demonstrate an unexpected role of BRD4 in regulating skin follicle stem cells and skin inflammation. |
5,509 | Monocular 3D Object Detection With Sequential Feature Association and Depth Hint Augmentation | Monocular 3D object detection, with the aim of predicting the geometric properties of on-road objects, is a promising research topic for the intelligent perception systems of autonomous driving. Most state-of-the-art methods follow a keypoint-based paradigm, where the keypoints of objects are predicted and employed as the basis for regressing the other geometric properties. In this work, a unified network named as FADNet is presented to address the task of monocular 3D object detection. In contrast to previous keypoint-based methods, we propose to divide the output modalities into different groups according to the estimation difficulty of object properties. Different groups are treated differently and sequentially associated by a convolutional Gated Recurrent Unit. Another contribution of this work is the strategy of depth hint augmentation. To provide characterized depth patterns as hints for depth estimation, a dedicated depth hint module is designed to generate row-wise features named as depth hints, which are explicitly supervised in a bin-wise manner. The contributions of this work are validated by conducting experiments and ablation study on the KITTI benchmark. Without utilizing depth priors, post optimization, or other refinement modules, our network performs competitively against state-of-the-art methods while maintaining a decent running speed. |
5,510 | Ferroelectric Thin Films for Oxide Electronics | Ferroelectric materials have set in motion numerous ultralow-energyconsuming device concepts that can be integrated into state-of-the-art complementary metal-oxide-semiconductor technology. Their nonvolatile, spontaneous electric polarization makes them promising candidates to control functionalities at the nanoscale with energy-efficient electric fields only. In this spotlight article, we start with a brief introduction to ferroelectric materials, the challenges involving the design of thin films and review the state-of-the-art of their integration into various electronic applications. Revolutionary in situ and operando diagnostic tools allowing the monitoring of the technology-relevant polarization state during the material design, or its operation will be detailed. Concepts such as chiral states in ferroelectrics and neuromorphic-type switching will be addressed to provide a comprehensive view on the evolution of ferroelectric states for the next generation of low-energy-consuming electronics. Finally, we discuss the most recent developments in the field, including the emergence of ferroelectricity at the nanoscale and in two-dimensional systems. |
5,511 | Image-to-Images Translation for Multi-Task Organ Segmentation and Bone Suppression in Chest X-Ray Radiography | Chest X-ray radiography is one of the earliest medical imaging technologies and remains one of the most widely-used for diagnosis, screening, and treatment follow up of diseases related to lungs and heart. The literature in this field of research reports many interesting studies dealing with the challenging tasks of bone suppression and organ segmentation but performed separately, limiting any learning that comes with the consolidation of parameters that could optimize both processes. This study, and for the first time, introduces a multitask deep learning model that generates simultaneously the bone-suppressed image and the organ-segmented image, enhancing the accuracy of tasks, minimizing the number of parameters needed by the model and optimizing the processing time, all by exploiting the interplay between the network parameters to benefit the performance of both tasks. The architectural design of this model, which relies on a conditional generative adversarial network, reveals the process on how the well-established pix2pix network (image-to-image network) is modified to fit the need for multitasking and extending it to the new image-to-images architecture. The developed source code of this multitask model is shared publicly on Github as the first attempt for providing the two-task pix2pix extension, a supervised/paired/aligned/registered image-to-images translation which would be useful in many multitask applications. Dilated convolutions are also used to improve the results through a more effective receptive field assessment. The comparison with state-of-the-art algorithms along with ablation study and a demonstration video (1) are provided to evaluate the efficacy and gauge the merits of the proposed approach. (1) https://youtu.be/J8Uth26_7rQhttps://youtu.be/J8Uth26_7rQ |
5,512 | Pseudomonas aeruginosa Antivirulence Strategies: Targeting the Type III Secretion System | The Pseudomonas aeruginosa type III secretion system (T3SS) is a complex molecular machine that delivers toxic proteins from the bacterial cytoplasm directly into host cells. This apparatus spans the inner and outer membrane and employs a needle-like structure that penetrates through the eucaryotic cell membrane into the host cell cytosol. The expression of the P. aeruginosa T3SS is highly regulated by environmental signals including low calcium and host cell contact. P. aeruginosa strains with mutations in T3SS genes are less pathogenic, suggesting that the T3SS is a virulence mechanism. Given that P. aeruginosa is naturally antibiotic resistant and multidrug resistant isolates are rapidly emerging, new antibiotics to target P. aeruginosa are needed. Furthermore, even if new antibiotics were to be developed, the timeline between when an antibiotic is released and resistance development is relatively short. Therefore, the concept of targeting virulence factors has garnered attention. So-called "antivirulence" approaches do not kill the microbe but instead focus on rendering it harmless and therefore unable to cause damage. Since these therapies target a particular system or pathway, the normal microbiome is unlikely to be affected and there is less concern about the spread to other microbes. Finally, and most importantly, since any antivirulence drug does not kill the microbe, there should be less selective pressure to develop resistance to these inhibitors. The P. aeruginosa T3SS has been well studied due to its importance for pathogenesis in numerous human and animal infections. Thus, many P. aeruginosa T3SS inhibitors have been described as potential antivirulence therapeutics, some of which have progressed to clinical trials. |
5,513 | A review of enhanced municipal wastewater treatment through energy savings and carbon recovery to reduce discharge and CO2 footprint | Municipal wastewater treatment that mainly performed by conventional activated sludge (CAS) process faces the challenge of intensive aeration-associated energy consumption for oxidation of organics and ammonium, contributing to significant directly/indirectly greenhouse gas (GHG) emissions from energy use, which hinders the achievement of carbon neutral, the top priority mission in the coming decades to cope with the global climate change. Therefore, this article aimed to offer a comprehensive analysis of recently developed biological treatment processes with the focus on reducing discharge and CO2 footprint. The biotechnologies including "Zero Carbon", "Low Carbon", "Carbon Capture and Utilization" are discussed, it suggested that, by integrating these processes with energy-saving and carbon recovery, the challenges faced in current wastewater treatment plants can be overcome, and a carbon-neutral even be possible. Future research should investigate the integration of these methods and improve anammox contribution as well as minimize organics lost under different scales. |
5,514 | DyNNamic: Dynamically Reshaping, High Data-Reuse Accelerator for Compact DNNs | Convolutional layers dominate the computation and energy costs of Deep Neural Network (DNN) inference. Recent algorithmic works attempt to reduce these bottlenecks via compact DNN structures and model compression. Likewise, state-of-the-art accelerator designs leverage spatiotemporal characteristics of convolutional layers to reduce data movement overhead and improve throughput. Although both are independently effective at reducing latency and energy costs, combining these approaches does not guarantee cumulative improvements due to inefficient mapping. This inefficiency can be attributed to (1) inflexibility of underlying hardware and (2) inherent reduction of data-reuse opportunities of compact DNN structures. To address these issues, we propose a dynamically reshaping, high data-reuse PE array accelerator, namely DyNNamic. DyNNamic leverages kernel-wise filter decomposition to partition the convolution operation into two compact stages: Shared Kernels Convolution (SKC) and Weighted Accumulation (WA). Because both stages have vastly different dimensions, DyNNamic reshapes its PE array to effectively map the algorithm to the architecture. The architecture then exploits data-reuse opportunities created by the SKC stage, further reducing data movement with negligible overhead. We evaluate our approach on various representative networks and compare against state-of-the-art accelerators. On average, DyNNamic outperforms DianNao by 8.4x and 12.3x in terms of inference energy and latency, respectively. |
5,515 | Efficient cascading of multi-domain image Gaussian noise filters | Image denoising is a well explored but still an active research topic. The focus is usually on achieving higher numerical quality which is theoretically interesting, however, often the factor of computation cost is not considered. Our idea is to employ different image Gaussian noise filters to construct an effective image denoiser, where the deficiency of each filter is compensated with others, while a wide variation of quality versus speed can be achieved. We integrate filters using different cascaded forms and show that if two filters use uncorrelated features, their cascaded form provides a higher quality than each separately. We start with easy-to-implement filters employing pixel- and frequency-domain with different kernel size to construct a fast yet high-quality multi-domain denoiser. Then, we propose more complex denoisers by integrating our cascaded multi-domain denoiser to other state-of-the-art denoising methods. Simulations show that the quality of proposed multi-domain denoiser is significantly higher than its building-blocks. We also show that the proposed multi-domain denoiser can be integrated to state-of-the-art denoisers to from a more effective denoiser, while adding negligible complexity. |
5,516 | Reciprocal associations between affective decision-making and mental health in adolescence | Poor affective decision-making has been shown to associate cross-sectionally with poor mental health in clinical populations. However, evidence from general population samples is scarce. Moreover, whether decision-making is prospectively linked to mental health in youth in the general population and whether such associations are reciprocal have yet to be examined. The present study examined bidirectional associations between various aspects of affective decision-making and emotional and behavioural problems at ages 11 and 14 years in 13,366 members of the Millennium Cohort Study. Decision-making (delay aversion, deliberation time, quality of decision-making, risk adjustment, risk-taking) and emotional (emotional symptoms, peer problems) and behavioural (conduct problems, hyperactivity/inattention) problems were measured using the Cambridge Gambling Task and the Strengths and Difficulties Questionnaire, respectively. Results of cross-lagged panel models adjusted for confounding revealed a negative reciprocal association between hyperactivity and quality of decision-making but also positive reciprocal associations between conduct problems and delay aversion, and between peer problems and deliberation time. Emotional problems and peer problems predicted a decrease in risk-taking, conduct problems predicted an increase in risk-taking, and hyperactivity predicted an increase in delay aversion and deliberation time. Furthermore, hyperactivity and conduct problems predicted less risk adjustment, and risk adjustment predicted fewer peer problems. The results suggest that behavioural problems are prospectively linked to greater risk-taking and lower risk adjustment in adolescence. Moreover, adolescents with behavioural problems tend to make poorer decisions and be more delay-averse, but also poorer quality of decision-making and increased delay aversion are associated with more behavioural problems over time. |
5,517 | WAVE: designing a heuristics-based three-way breadth-first search on GPUs | Breadth-first search (BFS) is a building block for improving the performance of many iterative graph algorithms. In addition to conventional BFS (push), a novel method that traverses a graph in the reverse direction (pull) has emerged and gained popularity because of its enhanced processing performance. Several frameworks have recently used a hybrid approach known as direction-optimizing BFS, which utilizes both directions. However, these frameworks are mostly interested in optimizing the procedure in each direction, instead of designing sophisticated methods for determining the appropriate direction between push and pull at each iteration. Owing to the lack of in-depth discussion on this decision, state-of-the-art direction optimizing BFS algorithms cannot demonstrate their comprehensive performance despite improvements in the design of each direction because they select ineffective directions at each iteration. We identified that the current frameworks suffer from high computational overheads for their decisions and make decisions that are overfitted to several graph datasets used for tuning their direction selection process. Based on observations from state-of-the-art limitations, we designed a direction-optimizing method for BFS called WAVE. WAVE minimizes the computational overhead to near zero and makes more appropriate direction selection decisions than the state-of-the-art heuristics based on the characteristics extracted from the input graph dataset. In our experiments on 20 graph benchmarks, WAVE achieved speedups of up to 4.95x, 5.79x, 46.49x, and 149.67x over Enterprise, Gunrock, Tigr, and CuSha, respectively. |
5,518 | CRITERIA OF MUSEUM COLOUR AND LUMINOUS ENVIRONMENT CONCEPT SELECTION | The article formulates the criteria of selection of the colour and luminous concept in museums of different profiles with focus on visitors of exhibition halls. The amount of light and the quality of illumination solution are important parameters affecting preservation of pieces of art, perception of museum environment, and capability to research any exhibit. Showcase illumination requires not only meeting exhibit lighting standards, but also balancing showcase illumination with general hall lighting. If daylighting is present, the problem becomes more complicated: it is necessary to select illuminance and luminance levels, locations of showcases and exhibits in them. For demonstration and convenient perception of paintings, it is important to create a comfortable illumination solution, to fill the space with light, to select appropriate contrast. Cultural heritage of Russia is huge, and, naturally, no exhibition may consist of exhibits of the same light resistance category. Annual luminous exposure may help find a solution for lighting design in this case. Light and shadow are inseparable, that combination gives a perspective of volume and texture of a piece of art. But shadow may distort exhibit perception therefore it is necessary to work with it. Another complication and, at the same time, a limitless area for creativity is using and/or limiting daylighting. Lighting design depends on the goals and objectives of a project. |
5,519 | Time-frequency feature extraction for classification of episodic memory | This paper investigates the extraction of time-frequency (TF) features for classification of electroencephalography (EEG) signals and episodic memory. We propose a model based on the definition of locally stationary processes (LSPs), estimate the model parameters, and derive a mean square error (MSE) optimal Wigner-Ville spectrum (WVS) estimator for the signals. The estimator is compared with state-of-the-art TF representations: the spectrogram, the Welch method, the classically estimated WVS, and the Morlet wavelet scalogram. First, we evaluate the MSE of each spectrum estimate with respect to the true WVS for simulated data, where it is shown that the LSP-inference MSE optimal estimator clearly outperforms other methods. Then, we use the different TF representations to extract the features which feed a neural network classifier and compare the classification accuracies for simulated datasets. Finally, we provide an example of real data application on EEG signals measured during a visual memory encoding task, where the classification accuracy is evaluated as in the simulation study. The results show consistent improvement in classification accuracy by using the features extracted from the proposed LSP-inference MSE optimal estimator, compared to the use of state-of-the-art methods, both for simulated datasets and for the real data example. |
5,520 | Combined Federated and Split Learning in Edge Computing for Ubiquitous Intelligence in Internet of Things: State-of-the-Art and Future Directions | Federated learning (FL) and split learning (SL) are two emerging collaborative learning methods that may greatly facilitate ubiquitous intelligence in the Internet of Things (IoT). Federated learning enables machine learning (ML) models locally trained using private data to be aggregated into a global model. Split learning allows different portions of an ML model to be collaboratively trained on different workers in a learning framework. Federated learning and split learning, each have unique advantages and respective limitations, may complement each other toward ubiquitous intelligence in IoT. Therefore, the combination of federated learning and split learning recently became an active research area attracting extensive interest. In this article, we review the latest developments in federated learning and split learning and present a survey on the state-of-the-art technologies for combining these two learning methods in an edge computing-based IoT environment. We also identify some open problems and discuss possible directions for future research in this area with the hope of arousing the research community's interest in this emerging field. |
5,521 | Synthesis of a Bifunctional Cross-Bridged Chelating Agent, Peptide Conjugation, and Comparison of 68 Ga Labeling and Complex Stability Characteristics with Established Chelators | [68 Ga]Ga3+ can be introduced into receptor-specific peptidic carriers via different chelators to obtain radiotracers for Positron Emission Tomography imaging and the chosen chelating agent considerably influences the in vivo pharmacokinetics of the corresponding radiopeptides. A chelator that should be a valuable alternative to established chelating agents for 68 Ga-radiolabeling of peptides would be a backbone-functionalized variant of the chelator CB-DO2A. Here, the bifunctional cross-bridged chelating agent CB-DO2A-GA was developed and compared to the established chelators DOTA, NODA-GA and DOTA-GA. For this purpose, CB-DO2A-GA(tBu)2 was introduced into the peptide Tyr3 -octreotate (TATE) and in direct comparison to the corresponding DOTA-, NODA-GA-, and DOTA-GA-modified TATE analogs, CB-DO2A-GA-TATE required harsher reaction conditions for 68 Ga-incorporation. Regarding the hydrophilicity profile of the resulting radiopeptides, a decrease in hydrophilicity from [68 Ga]Ga-DOTA-GA-TATE (logD(7.4) of -4.11±0.11) to [68 Ga]Ga-CB-DO2A-GA-TATE (-3.02±0.08) was observed. Assessing the stability against metabolic degradation and complex challenge, [68 Ga]Ga-CB-DO2A-GA demonstrated a very high kinetic inertness, exceeding that of [68 Ga]Ga-DOTA-GA. Therefore, CB-DO2A-GA is a valuable alternative to established chelating agents for 68 Ga-radiolabeling of peptides, especially when the formation of a very stable, positively charged 68 Ga-complex is pursued. |
5,522 | A Boosted Multi-Task Model for Pedestrian Detection With Occlusion Handling | Pedestrian detection is a challenging problem in computer vision, and has achieved impressive progress in recent years. However, the current state-of-the-art methods suffer from significant performance decline with increasing occlusion level of pedestrians. A common approach for occlusion handling is to train a set of occlusion-specific detectors and merge their results directly, but these detectors are trained independently and the relationship among them is ignored. In this paper, we consider pedestrian detection in different occlusion levels as different but related problems, and propose a boosted multi-task model to jointly consider their relatedness and differences. The proposed model adopts multi-task learning algorithm to map pedestrians in different occlusion levels to a common space, where all models corresponding to different occlusion levels are constrained to share a common set of features, and a boosted detector is then constructed to distinguish pedestrians from background. The proposed approach is evaluated on three challenging pedestrian detection data sets, including Caltech, TUD-Brussels, and INRIA, and achieves superior performances against state of the art in the literature on different occlusion-specific test sets. |
5,523 | Bag-of-Frequencies: A Descriptor of Pulmonary Nodules in Computed Tomography Images | We present a novel descriptor for the characterization of pulmonary nodules in computed tomography (CT) images. The descriptor encodes information on nodule morphology and has scale-invariant and rotation-invariant properties. Information on nodule morphology is captured by sampling intensity profiles along circular patterns on spherical surfaces centered on the nodule, in a multi-scale fashion. Each intensity profile is interpreted as a periodic signal, where the Fourier transform is applied, obtaining a spectrum. A library of spectra is created and labeled via unsupervised clustering, obtaining a Bag-of-Frequencies, which is used to assign each spectra a label. The descriptor is obtained as the histogram of labels along all the spheres. Additional contributions are a technique to estimate the nodule size, based on the sampling strategy, as well as a technique to choose the most informative plane to cut a 2-D view of the nodule in the 3-D image. We evaluate the descriptor on several nodule morphology classification problems, namely discrimination of nodules versus vascular structures and characterization of spiculation. We validate the descriptor on data from European screening trials NELSON and DLCST and we compare it with state-of-the-art approaches for 3-D shape description in medical imaging and computer vision, namely SPHARM and 3-D SIFT, outperforming them in all the considered experiments. |
5,524 | Efficient Compressed Sensing SENSE pMRI Reconstruction With Joint Sparsity Promotion | The theory and techniques of compressed sensing (CS) have shown their potential as a breakthrough in accelerating k-space data acquisition for parallel magnetic resonance imaging (pMRI). However, the performance of CS reconstruction models in pMRI has not been fully maximized, and CS recovery guarantees for pMRI are largely absent. To improve reconstruction accuracy from parsimonious amounts of k-space data while maintaining flexibility, a new CS SENSitivity Encoding (SENSE) pMRI reconstruction framework promoting joint sparsity (JS) across channels (JS CS SENSE) is proposed in this paper. The recovery guarantee derived for the proposed JS CS SENSE model is demonstrated to be better than that of the conventional CS SENSE model and similar to that of the coil-by-coil CS model. The flexibility of the new model is better than the coil-by-coil CS model and the same as that of CS SENSE. For fast image reconstruction and fair comparisons, all the introduced CS-based constrained optimization problems are solved with split Bregman, variable splitting, and combined-variable splitting techniques. For the JS CS SENSE model in particular, these techniques lead to an efficient algorithm. Numerical experiments show that the reconstruction accuracy is significantly improved by JS CS SENSE compared with the conventional CS SENSE. In addition, an accurate residual-JS regularized sensitivity estimation model is also proposed and extended to calibration-less (CaL) JS CS SENSE. Numerical results show that CaL JS CS SENSE outperforms other state-of-the-art CS-based calibration-less methods in particular for reconstructing non-piecewise constant images. |
5,525 | Do functional and phylogenetic nestedness follow the same mechanisms as taxonomic nestedness? Evidence from amphibians in the largest archipelago of China | Nested subset pattern (nestedness) has been raised to explain the distribution of species on islands and habitat fragments for over 60 years. However, previous studies on nestedness focused on species richness and composition and overlooked the role of species traits and phylogeny in generating and explaining nestedness. To address this gap, we sampled amphibians on 37 land-bridge islands in the largest archipelago of China, the Zhoushan Archipelago, to explore nestedness as well as the underlying causal processes through three facets of diversity, that is, taxonomic, functional and phylogenetic diversity. The taxonomic nestedness was measured through organizing the species incidence matrix to achieve a maximum value, while the functional and phylogenetic nestedness were quantified by incorporating the similarity of species in terms of their ecological traits and phylogeny. We also obtained six island characteristics and seven species traits as predictors of nestedness. Amphibian metacommunities were significantly nested in these three facets of diversity. When relating different predictors to nestedness, island area, habitat diversity and species traits were highly correlated with taxonomic nestedness. Moreover, island area and habitat diversity significantly influenced functional and phylogenetic nestedness. Therefore, the results support the selective extinction and habitat nestedness hypotheses. Interestingly, although we did not observe significant influences of island isolation on taxonomic nestedness, functional and phylogenetic diversities were significantly higher than expected when matrices were ordered by increasing distance to mainland. The result suggests that there are more functionally and phylogenetically diverse species on less-isolated islands, reflecting a selective colonization process overlooked by the traditional analysis of taxonomic nestedness. Although the three facets of nestedness and underlying processes were largely congruent, we detected the distance-related functional and phylogenetic nestedness for amphibian assemblages. Therefore, we highlight that a framework that simultaneously considers taxonomic, functional and phylogenetic nestedness can contribute to a complementary understanding of nestedness processes. In addition, it also improves our ability to conserve insular biodiversity from different perspectives. |
5,526 | Normalization and de-noising of single-cell Hi-C data with BandNorm and scVI-3D | Single-cell high-throughput chromatin conformation capture methodologies (scHi-C) enable profiling of long-range genomic interactions. However, data from these technologies are prone to technical noise and biases that hinder downstream analysis. We develop a normalization approach, BandNorm, and a deep generative modeling framework, scVI-3D, to account for scHi-C specific biases. In benchmarking experiments, BandNorm yields leading performances in a time and memory efficient manner for cell-type separation, identification of interacting loci, and recovery of cell-type relationships, while scVI-3D exhibits advantages for rare cell types and under high sparsity scenarios. Application of BandNorm coupled with gene-associating domain analysis reveals scRNA-seq validated sub-cell type identification. |
5,527 | A prediction-based lossless image compression procedure using dimension reduction and Huffman coding | Advanced therapeutic imaging innovation produces an immense amount of information, predominantly from processed tomography and other imaging modalities. This causes a significant challenge when storing them on a local personal computer or communicating them over cyberspace. Therefore, a proficient image compression system is fundamentally required. From this perspective, this paper proposes a lossless image compression procedure by reducing image dimension and using a prediction technique. In the proposed strategy, the column dimension of a grey-scale image is first reduced and then the prediction errors are encoded using Huffman coding. The decoding process is carried out in the reverse direction. The proposed method is executed and applied to several bench-marked images. The performance of this proposed algorithm is assessed and compared with the state-of-the-art techniques based on several assessment criteria, such as average code length (ACL), compression ratio (CR), encoding time, decoding time, efficiency, peak signal to noise ratio (PSNR) and normalised correlation (NC). The proposed algorithm also demonstrates an improvement in the average code length compared with the state-of-the-art techniques. |
5,528 | Gearbox Fault Diagnosis Based on Selective Integrated Soft Competitive Learning Fuzzy Adaptive Resonance Theory | In this work, a soft competitive learning fuzzy adaptive resonance theory (SFART) diagnosis model based on multifeature domain selection for the single symptom domain and the single-target model is proposed. In order to solve the problem that the performance of traditional fuzzy ART (FART) is affected by the order of sample input, the similarity criterion of YU norm is introduced into the fuzzy ART network. In the meanwhile, the lateral inhibition theory is introduced to solve the wasteful problem of fuzzy ART mode node. By combining YU norm and lateral inhibition theory with fuzzy ART network, a soft competitive learning ART neural network diagnosis model that allows multiple mode nodes to learn simultaneously is designed. The feature parameters are extracted from the perspectives of time domain, frequency domain, time series model, wavelet analysis, and wavelet packet energy spectrum analysis, respectively. To further improve the diagnostic accuracy, the selective weighted majority voting method is integrated into the diagnosis model. Finally, the selected feature parameters are inputted to the integrated model to complete the fault classification and diagnosis. Finally, the proposed method is verified with a gearbox fault diagnosis test. |
5,529 | Experimental Guidelines to Image Transient Single-Molecule Events Using Graphene Liquid Cell Electron Microscopy | In quest of the holy grail to "see" how individual molecules interact in liquid environments, single-molecule imaging methods now include liquid-phase electron microscopy, whose resolution can be nanometers in space and several frames per second in time using an ordinary electron microscope that is routinely available to many researchers. However, with the current state of the art, protocols that sound similar to those described in the literature lead to outcomes that can differ. The key challenge is to achieve sample contrast under a safe electron dose within a frame rate adequate to capture the molecular process. Here, we present such examples from different systems─synthetic polymer, lipid assembly, DNA-enzyme─in which we have done this using graphene liquid cells. We describe detailed experimental procedures and share empirical experience for conducting successful experiments, starting from fabrication of a graphene liquid cell, to identification of high-quality liquid pockets from desirable shapes and sizes, to effective searching for target sample pockets under electron microscopy, and to discrimination of sample molecules and molecular processes of interest. These experimental tips can assist others who wish to make use of this method. |
5,530 | Noise Resistant Fusion for Multi-Exposure Sensors | A noise resistant image fusion scheme for multiexposure sensors using color dissimilarity (for motion detection and removal), median and noise maps (to refine weights for noise removal) is proposed. A well-exposed image is obtained as a result of weighted average of multi-exposure source images. Higher valued weights are assigned to pixels containing low values of noises, high values of color dissimilarity, and median maps. Quantitative and qualitative comparison reveals superiority of the proposed scheme as compared with the current state-of-the-art multi-exposure fusion schemes. |
5,531 | Racial Prejudice Predicts Police Militarization | In the United States, police are becoming increasingly militarized. Whereas the racialized nature of police militarization has been documented, the relationship between racial prejudice and police militarization is less understood. We assessed the link between racial prejudice against Black and Native Americans and police militarization at individual and regional levels. Study 1 (N = 765) recruited a nationally representative sample of White Americans and found a positive association between racial prejudice and support for police militarization. Study 2 (N = 3,129,343) sourced regional aggregates of prejudice among White Americans from Project Implicit and policing data from the Defense Logistics Agency and found that police departments in states higher in prejudice acquired greater amounts of militarized equipment. Together, these studies demonstrate that, in terms of attitudes and policies, racial prejudice predicts police militarization. |
5,532 | Developing Wellbeing Through a Randomised Controlled Trial of a Martial Arts Based Intervention: An Alternative to the Anti-Bullying Approach | Anti-bullying policies and interventions are the main approach addressing bullying behaviours in Australian schools. However, the evidence supporting these approaches is inconsistent and its theoretical underpinning may be problematic. The current study examined the effects of a martial arts based psycho-social intervention on participants' ratings of resilience and self-efficacy, delivered as a randomised controlled trial to 283 secondary school students. Results found a consistent pattern for strengths-based wellbeing outcomes. All measures relating to resilience and self-efficacy improved for the intervention group, whereas results declined for the control group. These findings suggest that a martial arts based psycho-social intervention may be an efficacious method of improving wellbeing outcomes including resilience and self-efficacy. The study proposes utilising alternatives to the anti-bullying approach and that interventions should be aimed towards helping individuals develop strengths and cope more effectively, which has specific relevance to bullying and more generalised importance to positive mental health. |
5,533 | An Efficient FPGA Design of Residue-to-Binary Converter for the Moduli Set {2n+1, 2n-1} | In this paper, we propose a novel reverse converter for the moduli set {2n + 1, 2n, 2n - 1}. First, we simplify the Chinese Remainder Theorem in order to obtain a reverse converter that uses mod-(2n - 1) operations. Next, we present a low complexity implementation that does not require the explicit use of modulo operation in the conversion process and we prove that theoretically speaking it outperforms state of the art equivalent converters. We also implemented the proposed converter and the best equivalent state of the art converters on Xilinx Spartan 3 field-programmable gate array. The results indicate that, on average, our proposal is about 14%, 21%, and 8% better in terms of conversion time, area cost, and power consumption, respectively. |
5,534 | Management of Latent Tuberculosis Infection in Saudi Arabia: Knowledge and Perceptions Among Healthcare Workers | Background Tuberculosis (TB) continues to pose a serious threat to public health despite great efforts. For many years, management and screening for active TB cases have been the main focus of TB control programs. Latent TB is a stage where TB can be prevented and controlled. Therefore, designing a comprehensive TB control program that includes latent tuberculosis infection (LTBI) management diseases is needed to be implemented among the healthcare workers (HCWs) who have been found to be at a higher risk for active TB compared to the general population. The objective of the study The objective of the study is to assess the knowledge and perceptions of LTBI among HCWs. In addition to estimating the prevalence of LTBI among HCWs using closed-end questions in a self-administered questionnaire. Subjects and methods Through a cross-sectional study and non-random sampling technique, 324 (84%) healthcare workers who met the inclusion criteria completed and submitted the electronic questionnaire. Results Among all participants, the study reported a good knowledge about LTBI; however, a third of HCWs had poor knowledge about the difference between LTBI and active TB. Eighteen percent of participants were diagnosed with LTBI, and two-thirds accepted the treatment. Of all participants who started the treatment, 55% completed the treatment course. The compliance rate was high among young HCWs and physicians who had a short course of LTB treatment regimen. Conclusion The study reported a low acceptance and completion rate of LTBI therapy among HCWs. Low knowledge about some clinical facts of LTBI, the long duration of treatment, and being the treatment optional in Saudi health institutes were all barriers to accepting and completing the treatment of LTBI. All of these factors need to be addressed to increase the compliance rate to LTBI treatment. |
5,535 | Budo in Physical Recreation as a Form of Rapprochement to Nature | Martial arts, or budo in Japanese, are practiced recreationally on a global scale. Is there a relation between the regular practice/training of various fighting arts and the attitude of these people towards the natural world? Does budo educate in this direction? Representatives of various fighting arts (n = 145) were examined using a diagnostic survey. It was found that the attitude of the respondents to nature and ecology was positive for the majority of the respondents (almost 74%). This applied to both men and women and was not determined by the level of education. The type of martial art or combat sport practiced did not differentiate this attitude. |
5,536 | Lymph Node Metastasis Prediction From Whole Slide Images With Transformer-Guided Multiinstance Learning and Knowledge Transfer | The gold standard for diagnosing lymph node metastasis of papillary thyroid carcinoma is to analyze the whole slide histopathological images (WSIs). Due to the large size of WSIs, recent computer-aided diagnosis approaches adopt the multi-instance learning (MIL) strategy and the key part is how to effectively aggregate the information of different instances (patches). In this paper, a novel transformer-guided framework is proposed to predict lymph node metastasis from WSIs, where we incorporate the transformer mechanism to improve the accuracy from three different aspects. First, we propose an effective transformer-based module for discriminative patch feature extraction, including a lightweight feature extractor with a pruned transformer (Tiny-ViT) and a clustering-based instance selection scheme. Next, we propose a new Transformer-MIL module to capture the relationship of different discriminative patches with sparse distribution on WSIs and better nonlinearly aggregate patch-level features into the slide-level prediction. Considering that the slide-level annotation is relatively limited to training a robust Transformer-MIL, we utilize the pathological relationship between the primary tumor and its lymph node metastasis and develop an effective attention-based mutual knowledge distillation (AMKD) paradigm. Experimental results on our collected WSI dataset demonstrate the efficiency of the proposed Transformer-MIL and attention-based knowledge distillation. Our method outperforms the state-of-the-art methods by over 2.72% in AUC (area under the curve). |
5,537 | Workforce reconfiguration strategies in manufacturing systems: a state of the art | This paper provides a literature review and an analysis of the studies related to workforce reconfiguration strategies as a part of workforce planning for various production environments. The survey demonstrates that these strategies play a crucial role in the resilience and flexibility of manufacturing systems since they help industrial companies to quickly adapt to frequent changes in demand both in terms of volume and product mix. Five strategies are considered: the use ofutility,temporary,walking,cross-trainedworkers, andbucket brigades. They are analysed in the context of mixed and multi-model manual assembly lines, dedicated, cellular, flexible, and reconfigurable manufacturing systems. The review shows that most of the researches on these reconfiguration strategies focus on multi- or mixed-model assembly lines. At the same time, few studies consider workers team reconfiguration in flexible and reconfigurable manufacturing systems. Finally, this paper reveals several promising research directions in workforce reconfiguration planning, namely, the use of both machine and workforce reconfigurations, consideration of the ergonomic aspects, the combination of multiple workforce reconfiguration strategies, the study of workforce reconfiguration in human-robot collaborative systems, and the use of new technologies in human-machine industrial environments. |
5,538 | Simplified Model Analysis of Self-Excited Oscillation and Its Suppression in a High-Voltage Common Package for Si-IGBT and SiC-MOS | This paper presents the analysis of a simplified model for the design of a module structure that avoids the risk of self-excitedoscillation(SE-Osc). A necessaryand sufficient simplifiedmodel that can extract the critical oscillation mode is proposed based on a comparison of several simplifying steps. The differential equation of the simplified model is solved, and the solution is plotted in the frequency domain to analyze the oscillatory conditions. The simplified model is verified via a time-domain full-model simulation modeled by 3-D electromagnetic simulation and solved by finite-element simulation. Measurements of test modules show consistent oscillatory conditions and frequency. SE-Osc modes are eliminated by reducing the inductance connected to the emitter and increasing the inductance connectedto the collector. Increasing the ratio ofCCE toCGC increases the risk of self-exciting oscillation. Suppressions of SE-Osc from a common package design with state-ofthe- art Si-insulatedgate bipolar transistors (IGBTs) presenting small feedback capacitance, SiC-MOS, and hybrids of state-of-art Si-IGBTs and SiC-Schottky barrier diodes are verified. |
5,539 | Evo-devo perspectives on cancer | The integration of evolutionary and developmental approaches into the field of evolutionary developmental biology has opened new areas of inquiry- from understanding the evolution of development and its underlying genetic and molecular mechanisms to addressing the role of development in evolution. For the last several decades, the terms 'evolution' and 'development' have been increasingly linked to cancer, in many different frameworks and contexts. This mini-review, as part of a special issue on Evolutionary Developmental Biology, discusses the main areas in cancer research that have been addressed through the lenses of both evolutionary and developmental biology, though not always fully or explicitly integrated in an evo-devo framework. First, it briefly introduces the current views on carcinogenesis that invoke evolutionary and/or developmental perspectives. Then, it discusses the main mechanisms proposed to have specifically evolved to suppress cancer during the evolution of multicellularity. Lastly, it considers whether the evolution of multicellularity and development was shaped by the threat of cancer (a cancer-evo-devo perspective), and/or whether the evolution of developmental programs and life history traits can shape cancer resistance/risk in various lineages (an evo-devo-cancer perspective). A proper evolutionary developmental framework for cancer, both as a disease and in terms of its natural history (in the context of the evolution of multicellularity and development as well as life history traits), could bridge the currently disparate evolutionary and developmental perspectives and uncover aspects that will provide new insights for cancer prevention and treatment. |
5,540 | Speeded up detection of squared fiducial markers | Squared planar markers have become a popular method for pose estimation in applications such as autonomous robots, unmanned vehicles and virtual trainers. The markers allow estimating the position of a monocular camera with minimal cost, high robustness, and speed. One only needs to create markers with a regular printer, place them in the desired environment so as to cover the working area, and then registering their location from a set of images. Nevertheless, marker detection is a time-consuming process, especially as the image dimensions grows. Modern cameras are able to acquire high resolutions images, but fiducial marker systems are not adapted in terms of computing speed. This paper proposes a multi-scale strategy for speeding up marker detection in video sequences by wisely selecting the most appropriate scale for detection, identification and corner estimation. The experiments conducted show that the proposed approach outperforms the state-of-the-art methods without sacrificing accuracy or robustness. Our method is up to 40 times faster than the state-of-the-art method, achieving over 1000 fps in 4 K images without any parallelization. (C) 2018 Elsevier B.V. All rights reserved. |
5,541 | A Novel Adaptive Parameter Search Elastic Net Method for Fluorescent Molecular Tomography | Fluorescence molecular tomography (FMT) is a new type of medical imaging technology that can quantitatively reconstruct the three-dimensional distribution of fluorescent probes in vivo. Traditional Lp norm regularization techniques used in FMT reconstruction often face problems such as over-sparseness, over-smoothness, spatial discontinuity, and poor robustness. To address these problems, this paper proposes an adaptive parameter search elastic net (APSEN) method that is based on elastic net regularization, using weight parameters to combine the L1 and L2 norms. For the selection of elastic net weight parameters, this approach introduces the L0 norm of valid reconstruction results and the L2 norm of the residual vector, which are used to adjust the weight parameters adaptively. To verify the proposed method, a series of numerical simulation experiments were performed using digital mice with tumors as experimental subjects, and in vivo experiments of liver tumors were also conducted. The results showed that, compared with the state-of-the-art methods with different light source sizes or distances, Gaussian noise of 5%-25%, and the brute-force parameter search method, the APSEN method has better location accuracy, spatial resolution, fluorescence yield recovery ability, morphological characteristics, and robustness. Furthermore, the in vivo experiments demonstrated the applicability of APSEN for FMT. |
5,542 | Drug-induced immune-mediated thrombocytopenia in the intensive care unit | A 62-year-old woman with prosthetic mitral valve was admitted for explant of an infected prosthetic knee. Perioperatively, she was bridged with heparin and started on empiric vancomycin and piperacillin-tazobactam. Platelet counts dropped precipitously within 2 days reaching a nadir of 6000/μL, without any bleeding. Decline persisted despite substituting heparin with bivalirudin. Antiplatelet factor 4 and anti-PLA1 antigen were negative. Schistocytes were absent. Antibiotics were substituted with daptomycin for suspected drug-induced thrombocytopenia. Pulse dose of intravenous immunoglobulin was initiated with rapid normalization of platelet count. She tested positive for IgG antiplatelet antibodies to vancomycin and piperacillin-tazobactam thereby confirming the diagnosis. Drug-induced immune-mediated thrombocytopenia is an underrecognized cause of thrombocytopenia in the intensive care units. Clinicians should be cognizant of this entity, and a definitive diagnosis should be sought if feasible. |
5,543 | No-Reference Video Quality Assessment Based on Visual Memory Modeling | Objective video quality assessment plays an important role in a variety of video processing applications such as video compression, transmission, visualization, and display. This paper proposes a no-reference video quality assessment model based on visual memory understanding. Inspired by the findings of neuroscience researchers, who argue there is a large overlap between the active human brain area when performing video quality assessment and saliency detection tasks, saliency maps are employed here to assist the quality assessment. To this end, we first generate the saliency maps using CLBP (Complete Local Binary Patterns) features of the residual frames. Then, a model of visual memory is created from the statistics of saliency maps. This is followed by learning the video quality from the visual memory, saliency, and frame features through a support vector regression pipeline. The experimental results on the state-of-the-art LIVE and SJTU video datasets indicate that the proposed no-reference video quality assessment algorithm is effective and performs statistically better than several other state-of-the-art approaches. |
5,544 | Comparative exploration of the morphological plasticity of Trichodina centrostrigeata (Peritrichia: Mobilida), ectoparasite from the gills of two tilapia species (Oreochromis niloticus and O. mossambicus) in a global context | Trichodina centrostrigeata Basson, Van As et Paperna, 1983 from Oreochromis mossambicus (Peters) and O. niloticus (Linnaeus) from different host populations from Argentina, Mexico and South Africa was reviewed. Although T. centrostrigeata has a distinct denticle structure that makes morphological taxonomic inferences uncomplicated, variation of the denticles within and among individuals and populations were still observed. While traditional taxonomy of mobilines is heavily reliant on morphometrics, and recently even more so on molecular analysis, this paper proposes the use of geometric morphometry, specifically elliptical Fourier analysis, to address morphological conflicts that arise when comparing different populations. By applying this technique, combined with traditional taxonomy, it was found that T. centrostrigeata in this study can be grouped into two separate morphotypes, the first (type a) from aquaculture farms in Argentina and Mexico and the second (type b) from a natural habitat in Glen Alpine Dam, South Africa. This study supports the validity of geometric morphometry as an additional technique to distinguish not only between species but also evolutionary plasticity of the same species from different localities and habitats. |
5,545 | Transcriptome profiles associated with resilience and susceptibility to single prolonged stress in the locus coeruleus and nucleus accumbens in male sprague-dawley rats | Although most people are subjected to traumatic stress at least once in their lifetime, only a subset develop long-lasting, stress-triggered neuropsychiatric disorders, such as PTSD. Here we examined different transcriptome profiles within the locus coeruleus (LC) and nucleus accumbens (NAc) that may contribute to stress susceptibility. Sprague Dawley male rats were exposed to the single prolonged stress (SPS) model for PTSD. Two weeks later they were tested for their anxiety/avoidance behavior on the Elevated Plus Maze (EPM) and were divided into high and low anxiety-like subgroups. RNA (n = 5 per group) was subsequently isolated from LC and NAc and subjected to RNAseq. Transcriptome analysis was used to identify differentially-expressed genes (DEGs) which differed by at least 50 % with significance of 0.01. The LC had more than six times the number of DEGs than the NAc. Only one DEG was regulated similarly in both locations. Many of the DEGs in the LC were associated with morphological changes, including regulation of actin cytoskeleton, growth factor activity, regulation of cell size, brain development and memory, with KEGG pathway of regulation of actin cytoskeleton. The DEGs in the NAc were primarily related to DNA repair and synthesis, and differential regulation of cytokine production. The analysis identified MTPN (myotrophin) and NR3C1 (glucocorticoid receptor) as important upstream regulators of stress susceptibility in the LC. Overall the study provides new insight into molecular pathways in the LC and NAc that are associated with anxiety-like behavior triggered by stress susceptibility or resilience. |
5,546 | Mental Health Benefits of Breastfeeding: A Literature Review | Pregnancy is typically viewed as a time of emotional well-being for prospective mothers, but for some, this period can negatively impact mental health. However, the relationship between postpartum mental health and breastfeeding is not clearly understood. Considering that many health authorities recommend breastfeeding, clearly defining this relationship is important. This review aims to illustrate the effects that breastfeeding has on the mental health of postpartum mothers. An extensive computerized search was performed through databases of PubMed, CINAHL, and Medline. All studies conducted to determine the effects of breastfeeding on mental health were screened and included in this review. Search terms related to breastfeeding, postpartum, and mental health were used. This review on breastfeeding and postpartum depression (PPD) begins by discussing the correlation between lactation and the maternal stress response. Another component discussed is the duration of breastfeeding and its importance in limiting PPD symptoms. The review then shifts to focus more on the psychological aspects of breastfeeding, notably on changes to the sleep-wake cycle and mother-infant interactions. The final part of the review emphasizes the danger that early breastfeeding cessation imposes on a mother's mental health, portraying how prenatal and early-onset postpartum depression may lead to early breastfeeding cessation. This composite collection of studies clarifies the importance of breastfeeding in reducing the incidence and severity of maternal postpartum depression. |
5,547 | A Rare Case of HIV-Induced Neutropenia Resulting in Haemophilus influenzae Septic Oligoarthritis: A Case-Based Literature Review | Septic arthritis is a medical emergency that rarely occurs without direct trauma to a joint, compromise or trauma to the synovium, or internal hematogenous seeding from bacteremia. Infection of a single joint space is a cause for concern, and infection of multiple joints is even more rare and concerning. Human immunodeficiency virus (HIV) renders patients particularly susceptible to encapsulated bacteria as it compromises opsonization, humoral immunity, as well as neutrophil function. Neutrophils play an important role in preventing and fighting off infections of the synovium, and it is well documented that compromised neutrophil function can result in this peculiar infection. HIV is popularly acknowledged for its suppression of the lymphoid division of the immune system, particularly CD4 T-cells suppression. However, HIV's effects on myeloid cells are largely overlooked in medical academia, specifically with respect to neutrophil dysfunction. We will explore a case where compromised neutrophil function results in rare infiltration of Haemophilus influenzae resulting in polyarticular septic arthritis. |
5,548 | Seismic Considerations for the Art Deco Interwar Reinforced-Concrete Buildings of Napier, New Zealand | Following the devastating 1931 Hawke's Bay earthquake, buildings in Napier and surrounding areas in the Hawke's Bay region were rebuilt in a comparatively homogenous structural and architectural style comprising the region's famous Art Deco stock. These interwar buildings are most often composed of reinforced concrete two-way space frames, and although they have comparatively ductile detailing for their date of construction, are often expected to be brittle, earthquake-prone buildings in preliminary seismic assessments. Furthermore, the likelihood of global collapse of an RC building during a design-level earthquake became an issue warranting particular attention following the collapse of multiple RC buildings in the February 22, 2011 Christchurch earthquake. Those who value the architectural heritage and future use of these iconic Art Deco buildings-including building owners, tenants, and city officials, among others-must consider how they can be best preserved and utilized functionally given the especially pressing implications of relevant safety, regulatory, and economic factors. This study was intended to provide information on the seismic hazard, geometric weaknesses, collapse hazards, material properties, structural detailing, empirically based vulnerability, and recommended analysis approaches particular to Art Deco buildings in Hawke's Bay as a resource for professional structural engineers tasked with seismic assessments and retrofit designs for these buildings. The observed satisfactory performance of similar low-rise, ostensibly brittle RC buildings in other earthquakes and the examination of the structural redundancy and expected column drift capacities in these buildings, led to the conclusion that the seismic capacity of these buildings is generally underrated in simple, force-based assessments. (C) 2014 American Society of Civil Engineers. |
5,549 | A Comprehensive State-of-the-Art Survey on the Transmission Network Expansion Planning Optimization Algorithms | Long term planning in power transmission network expansion provides a well ordered and profitable extension of power equipment and facilities to meet the expected electric energy demand with an allowable degree of reliability. However, high quality and improved reliability in energy supply have to be balanced with the available funds. The need to expand transmission network can never be over emphasized. Transmission Network Expansion Planning (TNEP) is a periodical measure that must be carried out due to dynamic societies that attract extra energy demands. It is highly important to minimize the network reinforcement and operational costs while satisfying the increase in demand imposed by technical and economic conditions over the planning horizon. Several optimization algorithms for TNEP problems have been developed and applied over the past decades. This paper presents a comprehensive state-of-the-art survey on the TNEP optimization algorithms. The approach of this paper is in the area of highlights of the various available TNEP algorithms, their applications, viability, computational complexities and drawbacks, which can aid in the identifications of the proper methods that can yield an optimal solution to TNEP problem. |
5,550 | Dynamic Complexity Measures for Use in Complexity-Based System Design | Difficulty predicting system behaviors introduces a certain level of complexity to a system design. The INCOSE systems engineering handbook indicates that system complexity is one of the seven key challenges influencing development when engineering a system of systems. The scope of this paper is first to survey systems engineering relevant definitions of complexity for latter application to the complexity evaluation framework. The literature search also includes state-of-the-art works on system complexity measurement. Before proposing new techniques, the current complexity-based system, and interface measurement and design techniques are explored. As the state-of-the-art only includes static/ structural complexity quantification, entropy-based measures for dynamic complexity quantification are proposed. A sample system is evaluated using the proposed dynamic complexity measures and the results are discussed. The methods proposed herein provide a first step in the path to an enhanced system/ interface complexity evaluation framework using dynamic complexity measures. |
5,551 | Single-Channel and Multi-Channel Sinusoidal Audio Coding Using Compressed Sensing | Compressed sensing (CS) samples signals at a much lower rate than the Nyquist rate if they are sparse in some basis. In this paper, the CS methodology is applied to sinusoidally modeled audio signals. As this model is sparse by definition in the frequency domain (being equal to the sum of a small number of sinusoids), we investigate whether CS can be used to encode audio signals at low bitrates. In contrast to encoding the sinusoidal parameters (amplitude, frequency, phase) as current state-of-the-art methods do, we propose encoding few randomly selected samples of the time-domain description of the sinusoidal component (per signal segment). The potential of applying compressed sensing both to single-channel and multi-channel audio coding is examined. The listening test results are encouraging, indicating that the proposed approach can achieve comparable performance to that of state-of-the-art methods. Given that CS can lead to novel coding systems where the sampling and compression operations are combined into one low-complexity step, the proposed methodology can be considered as an important step towards applying the CS framework to audio coding applications. |
5,552 | Design Optimization Considering Guiding Template Feasibility and Redundant Via Insertion for Directed Self-Assembly | While multiple patterning lithography suffers from considerable and increasing mask manufacturing cost, next generation lithography technologies are urgently required for sub-10 nm technology nodes, where directed self-assembly (DSA) is one of the most promising candidates for contact/via layer fabrication. In addition, redundant via insertion is regarded as an important step in the circuit design flow to improve circuit reliability and yield. In this paper, we propose to adopt wire perturbation to further enhance via manufacturability and redundant via insertion rates. In addition, an improved DSA-compliant and redundant via-aware routing graph model is proposed and a systematic via graph update approach is developed to facilitate the implementation of the router. Experimental results demonstrate that compared with a state-of-the-art work, our wire perturbation approach can averagely increase inserted redundant vias by 6% and reduce unmanufacturable vias by 23% with only 0.9% wirelength overhead, and our routing graph model achieves the same performance as the one proposed in a state-of-the-art work and is much more efficient. |
5,553 | Collaborative Convolution Operators for Real-Time Coarse-to-Fine Tracking | Discriminative correlation filter (DCF) has attracted enormous popularity among the tracking community. Standard DCF based trackers easily achieve real-time tracking speed but significantly suffer from the boundary effects. Recently, spatially regularized or constrained correlation filters tackle the problem of boundary effects at the sacrifice of the closed-form element-wise solution. In this paper, we cope with boundary effects from a novel perspective and present a coarse-to-fine tracking (CTFT) framework which breaks the task of visual tracking into two stages. In the first stage, CTFT locates the target coarsely with a deep convolution operator in a large search area. In the second stage, CTFT performs a fine-grained search of the target with a shallow convolution operator around the initial location in the first stage. With this two-stage tracking framework, CTFT holds a large target search area and maintains the efficient element-wise solution of standard DCF. Compared with state-of-the-art deep trackers, CTFT makes a good balance between computational efficiency and accuracy. Extensive experimental results on OTB2013 and OTB2015 demonstrate that CTFT maintains real-time performance at an average tracking speed of 35.8 fps and achieves favorable performance against state-of-the-art trackers. |
5,554 | Improvement of Stability for Small Molecule Organic Solar Cells by Suppressing the Trap Mediated Recombination | To understand the degradation mechanism of organic solar cells (OSCs), the charge dynamics of conventional and inverted planar heterojunction OSCs based on boron subthalocyanine chloride (SubPc) and fullerene (C60) with identical buffers during the air exposure were investigated. The results of light intensity dependent open circuit voltage show that the bimolecular recombination is dominated in the fresh devices, regardless of the device structure. The appearance of transient peak in photocurrent after turn-on and the light intensity independent turn-off traces in transient photocurrent suggest that the rapid degradation of conventional device is due to the energy loss originated from the aggravated trap mediated recombination. In contrast, the half-lifetime of inverted device is ∼25 times longer than the conventional one. The improvement of stability is ascribed to the decrease of the trap generation possibility and the suppression of trap mediated recombination in the case of inverted structure, where the penetration of oxygen and water through buffer layer is avoided. |
5,555 | Domain Transformation-Based Efficient Cost Aggregation for Local Stereo Matching | Binocular stereo matching is one of the most important algorithms in the field of computer vision. Adaptive support-weight approaches, the current state-of-the-art local methods, produce results comparable to those generated by global methods. However, excessive time consumption is the main problem of these algorithms since the computational complexity is proportionally related to the support window size. In this paper, we present a novel cost aggregation method inspired by domain transformation, a recently proposed dimensionality reduction technique. This transformation enables the aggregation of 2-D cost data to be performed using a sequence of 1-D filters, which lowers computation and memory costs compared to conventional 2-D filters. Experiments show that the proposed method outperforms the state-of-the-art local methods in terms of computational performance, since its computational complexity is independent of the input parameters. Furthermore, according to the experimental results with the Middlebury dataset and real-world images, our algorithm is currently one of the most accurate and efficient local algorithms. |
5,556 | Advances in hydrostatic leveling with the NPH6, and suggestions for further enhancements | This paper reviews the state-of-the-art of hydrostatic leveling and tilt measurement, with an emphasis on the Pellissier H5, and the National Radio Astronomy Observatory NPH6. Details of the NPH6 design are described, experimental results are discussed, suggestions are made for further enhancements, and additional potential applications are offered. (c) 2004 Elsevier Inc. All rights reserved. |
5,557 | The Effect of Obstructive Sleep Apnea on Sleep-dependent Emotional Memory Consolidation | Rationale: A growing body of evidence suggests that sleep is critical for the adaptive processing and consolidation of emotional information into long-term memory. Previous research has indicated that emotional components of scenes particularly benefit from sleep in healthy groups, yet sleep-dependent emotional memory processes remain unexplored in clinical cohorts, including those with obstructive sleep apnea (OSA). This line of research is important as it will add to the understanding of how disrupted sleep in OSA contributes to both impaired cognition and emotion dysregulation. Objectives: To test the hypothesis that individuals with OSA will have impaired sleep-dependent memory consolidation, with the greatest impact being on memory for emotional content. Methods: In this study, a group of newly diagnosed patients with OSA (n = 26; 10 female; average age, 42.5 years) and a matched group of healthy control subjects (n = 24; 13 female; average age, 37 years) were enrolled in the study at Beth Israel Deaconess Medical Center. Participants encoded scenes with negative or neutral foreground objects placed on neutral backgrounds before a night of polysomnographically recorded sleep. In the morning, they completed a recognition test in which old and new scene objects and backgrounds, presented separately and one at a time, were judged as old, new, or similar compared with what had been previously viewed. Results: Patients with OSA had a deficit in recognition memory for the scenes. Overall recognition (the ability to recognize old items as either old or similar) was impaired across all scene elements, both negative and neutral objects and backgrounds, whereas specific recognition (correctly identifying old items as old) was impaired only for negative objects. Across all participants, successful overall recognition correlated positively with sleep efficiency and rapid eye movement (REM) sleep, whereas successful specific memory recognition correlated only with REM sleep. Conclusions: Our findings indicate that fragmented sleep and reduced REM sleep, both hallmarks of OSA, are associated with disruptions in general memory impairment and veridical memory for emotional content, which could alter emotional regulation and contribute to comorbid emotional distress in OSA. |
5,558 | Implementation of Tele-Intensive Care Unit Services During the COVID-19 Pandemic: A Systematic Literature Review and Updated Experience from Shandong Province | Background: While the use of telemedicine had been expanding before the initial outbreak of COVID-19, the pandemic has dramatically accelerated its implementation and expanded its usage in many hospitals. Tele-intensive care unit (ICU) is a specialized type of telemedicine that adapts available technologies to the unique needs of critically ill patients. We published an editorial in 2020 describing our initial experiences of Tele-ICU application in Shandong Province. Here, we update our insights gained over the past 2 years, and we provide a systematic review of the literature to compare our perspectives with those from other institutions. Methods: We performed a systematic literature review of publications describing the use of telemedicine in an ICU setting during COVID-19. The PubMed database was searched for studies published after January 1, 2020, which offered detailed descriptions of tele-ICU usage. Extracted data included details regarding tele-ICU technologies, descriptions of the institution, usage cases, assessments of tele-ICU effectiveness, and site-reported opinions (e.g., advantages, disadvantages). Results: We screened 162 studies resulting from the PubMed literature search, along with one expert recommendation. Of the 112 full-text articles retrieved, 11 were selected for inclusion in this qualitative summary. All were retrospective descriptions of tele-ICU experiences at a single site. Some pairs of included articles reported results from the same institution, with seven unique sites being described. Three sites employed centralized models of tele-ICU, while four allowed staff to participate from distant locations. Five sites collected user-reported feedback regarding tele-ICU. While the advantages and disadvantages described rarely overlapped directly between sites, many reported positive opinions of tele-ICU use overall. Conclusions: The potential applications of tele-ICU technologies vary widely, making them highly adaptable to the needs of individual institutions. Tele-ICU has proven invaluable to some hospitals during COVID-19 due to its effectiveness at aiding patient care while mitigating risk to health care workers. |
5,559 | A Partially-Learned Algorithm for Joint Photo-acoustic Reconstruction and Segmentation | In an inhomogeneously illuminated photoacoustic image, important information like vascular geometry is not readily available, when only the initial pressure is reconstructed. To obtain the desired information, algorithms for image segmentation are often applied as a post-processing step. In this article, we propose to jointly acquire the photoacoustic reconstruction and segmentation, by modifying a recently developed partially learned algorithm based on a convolutional neural network. We investigate the stability of the algorithm against changes in initial pressures and photoacoustic system settings. These insights are used to develop an algorithm that is robust to input and system settings. Our approach can easily be applied to other imaging modalities and can be modified to perform other high-level tasks different from segmentation. The method is validated on challenging synthetic and experimental photoacoustic tomography data in limited angle and limited view scenarios. It is computationally less expensive than classical iterative methods and enables higher quality reconstructions and segmentations than the state-of-the-art learned and non-learned methods. |
5,560 | Antibiotics administration alleviates the high fat diet-induced obesity through altering the lipid metabolism in young mice | Currently, there is a global trend of rapid increase in obesity, especially among adolescents. The antibiotics cocktails (ABX) therapy is commonly used as an adjunctive treatment for gut microbiota related diseases, including obesity. However, the effects of broad-spectrum antibiotics alone on young obese hosts have rarely been reported. In the present study, the 3-week-old C57BL/6J male mice fed a high-fat diet (HFD) were intragastric administration with ampicillin, vancomycin, metronidazole or neomycin for 30 days. The lipid metabolites in plasma were assessed by biochemical assay kits, and genes related to lipid metabolite in the white adipose were assessed by qPCR. To further analyze the underlying mechanisms, the expression of genes related to lipid metabolism, inflammatory reactions and oxidative stress in the liver were determined by qPCR assay. In addition, the expression of oxidative damage-associated proteins in the liver were detected by western blot. The results showed that oral antibiotics exposure could reduce body weight and fat index in HFD-fed mice, concurrent with the increase of white adipose lipolysis genes and the decrease of hepatic lipogenic genes. Furthermore, antibiotics treatment could clearly reverse the HFD-induced elevation of oxidative damage-related proteins in the liver. Together, these findings will provide valuable clues into the effects of antibiotics on obesity. |
5,561 | Host-microbiota interactions play a crucial role in oyster adaptation to rising seawater temperature in summer | Climate change, represented by rising and fluctuating temperature, induces systematic changes in marine organisms and in their bacterial symbionts. However, the role of host-microbiota interactions in the host's response to rising temperature and the underlying mechanisms are incompletely understood in marine organisms. Here, the symbiotic intestinal microbiota and transcriptional responses between diploid and triploid oysters that displayed susceptible and resistant performance under the stress of rising temperature during a summer mortality event were compared to investigate the host-microbiota interactions. The rising and fluctuating temperatures triggered an earlier onset and higher mortality in susceptible oysters (46.7%) than in resistant oysters (17.3%). Correlation analysis between microbial properties and environmental factors showed temperature was strongly correlated with indices of α-diversity and the abundance of top 10 phyla, indicating that temperature significantly shaped the intestinal microbiota of oysters. The microbiota structure of resistant oysters exhibited more rapid changes in composition and diversity compared to susceptible oysters before peak mortality, indicating that resistant oysters possessed a stronger ability to regulate their symbiotic microbiota. Meanwhile, linear discriminant analysis effect size (LefSe) analysis found that the probiotics Verrucomicrobiales and Clostridiales were highly enriched in resistant oysters, and that potential pathogens Betaproteobacteriales and Acidobacteriales were enriched in susceptible oysters. These results implied that the symbiotic microbiota played a significant role in the oysters' adaptation to rising temperature. Accompanying the decrease in unfavorable bacteria before peak mortality, genes related to phagocytosis and lysozymes were upregulated and the xenobiotics elimination pathway was exclusively expressed in resistant oysters, demonstrating the validity of these immunological functions in controlling proliferation of pathogens driven by rising temperature. Compromised immunological functions might lead to proliferation of pathogens in susceptible oysters. This study might uncover a conserved mechanism of adaptation to rising temperature in marine invertebrates from the perspective of interactions between host and symbiotic microbiota. |
5,562 | Fully Connected Generative Adversarial Network for Human Activity Recognition | Conditional Generative Adversarial Networks (CGAN) have shown great promise in generating synthetic data for sensor-based activity recognition. However, one key issue concerning existing CGAN is the design of the network architecture that affects sample quality. This study proposes an effective CGAN architecture that synthesizes higher quality samples than state-of-the-art CGAN architectures. This is achieved by combining convolutional layers with multiple fully connected networks in the generator's input and discriminator's output of the CGAN. We show the effectiveness of the proposed approach using elderly data for sensor-based activity recognition. Visual evaluation, similarity measure, and usability evaluation are used to assess the quality of generated samples by the proposed approach and validate its performance in activity recognition. In comparison to the state-of-the-art CGAN, the visual evaluation and similarity measure demonstrate that the proposed models' synthetic data more accurately represents actual data and creates more variations in each synthetic data than the state-of-the-art approach respectively. The experimental stages of the usability evaluation, on the other hand, show a performance gain of 2.5%, 2.5%, 3.1%, and 4.4% over the state-of-the-art CGAN when using synthetic samples by the proposed architecture. |
5,563 | A survey on secure multipath routing protocols in WSNs | Routing protocols in wireless sensor networks (WSN) have been substantially investigated by researches. Most state-of-the-art surveys have focused on reviewing the different routing schemes that have been proposed for WSN and classifying them based on the network's type and protocol's operation. Security aspects in routing protocols have not been given enough attention, since most of the routing protocols in WSNs have not been designed with security requirements in mind. However, taking into consideration that WSN applications need to support critical infrastructures (i.e., military, healthcare, environmental, etc.), security becomes an issue. And since these infrastructures are highly depended on the availability of resources, focus has especially been given to support a secure, resilient and reliable environment, with multipath routing being one of the added functionalities. The need for security in sensitive WSN application has lead researchers to design secure multipath routing protocols from the beginning or design security extensions for existing protocols. This paper surveys the current state-of-the-art of secure multipath routing protocols in WSNs, classifies the protocols in categories according to their security-related operational objectives, defines a new threat model in the routing procedure and identifies open research issues in the area. (C) 2010 Elsevier B.V. All rights reserved. |
5,564 | Fairness and Efficiency in Stochastic Buffer-Aided Relay-Assisted MEC | This letter studies hierarchical Mobile Edge Computing (MEC) with multiple sources, multiple buffer-aided relays, and one Higher-level computing Node (HN). The relays may or may not have computation resources and therefore, they randomly decide to process the received tasks or to offload them to the HN. We consider the delay in the transmission and computation buffers, and propose a novel Fairness and Efficiency Cost Function (FECF) as the weighted sum of the maximum Average Response Time (ART) and the overall system ART. We formulate a novel problem to minimize the FECF while keeping the system queues stable, by jointly optimizing the offloading probabilities at the relays and the capacities of the virtual machines at the HN. We prove that the problem is a multi-convex optimization problem and propose an effective solution method by alternating optimization. Simulation results demonstrate the effectiveness of the different variants of the proposed scheme in the scenarios with server-less and server-empowered relays and provide important insights regarding the fairness and efficiency in terms of the ART. |
5,565 | Uncertainty Class Activation Map (U-CAM) Using Gradient Certainty Method | Understanding and explaining deep learning models is an imperative task. Towards this, we propose a method that obtains gradient-based certainty estimates that also provide visual attention maps. Particularly, we solve for visual question answering task. We incorporate modern probabilistic deep learning methods that we further improve by using the gradients for these estimates. These have two-fold benefits: a) improvement in obtaining the certainty estimates that correlate better with misclassified samples and b) improved attention maps that provide state-of-the-art results in terms of correlation with human attention regions. The improved attention maps result in consistent improvement for various methods for visual question answering. Therefore, the proposed technique can be thought of as a tool for obtaining improved certainty estimates and explanations for deep learning models. We provide detailed empirical analysis for the visual question answering task on all standard benchmarks and comparison with state of the art methods. |
5,566 | ASPD-Net: Self-aligned part mask for improving text-based person re-identification with adversarial representation learning | Text-based person re-identification aims to retrieve images of the corresponding person from a large visual database according to a natural language description. When it comes to visual local information extraction, most of the state-of-the-art methods adopt either a strict uniform strategy which can be too rough to catch local details properly, or pre-processing with external cues which may suffer from the deviations of the pre-trained model and the large computation consumption. In this paper, we proposed an Adversarial Self -aligned Part Detecting Network (ASPD-Net) model which extracts and combines multi-granular visual and textual features. A novel Self-aligned Part Mask Module was presented to autonomously learn the information of human body parts, and obtain visual local features in a soft-attention manner by using K Self-aligned Part Mask Detectors. Regarding the main model branches as a generator, a discriminator is employed to determine whether the representation vector comes from the visual modality or the textual modality. With Adversarial Loss training, ASPD-Net can learn more robust representations, as long as it successfully tricks the discriminator. Experimental results demonstrate that the proposed ASPD-Net outperforms the previous methods and achieves the state-of-the-art performance on the CUHK-PEDES and RSTPReid datasets. |
5,567 | Psychological Well-Being of Prospective Counselors from the Faith-Based Educational Institution in the COVID-19 Outbreak | This study aims to analyze the Psychological Well-Being among prospective counselors from the Faith-Based Educational Institution during the COVID-19 pandemic. The approach of this study was quantitative with a descriptive method. The Psychological Well-Being among prospective counselors is at a high classification level, namely 84%. The components of Psychological Well-Being that are above the total average score are Positive Relationship with Other People and components of Self-Growth. |
5,568 | Complete mitochondrial genome sequence of Chestnut-flanked white-eye (Zosterops erythropleurus) | The Chestnut-flanked white-eye (Zosterops erythropleurus) is a species of family Zosteropidae, which is distributed widely in the world. In the present study, the complete mitochondrial genome sequence of Chestnut-flanked white-eye was determined. It has a total length of 17 811 bp, and contains 13 protein-coding genes, 22 tRNA genes, 2 ribosome RNA genes and 2 control regions. The total base composition was 30.2% for A, 31.0% for C, 14.2% for G and 24.6% for T. The phylogenetic tree of Chestnut-flanked white-eye and 13 other species belonging to the order Passeriformes was built. The molecular data presented here will be useful to study the evolutionary relationships and genetic diversity of Chestnut-flanked white-eye. |
5,569 | CATtalk: An IoT-Based Interactive Art Development Platform | Interactive art has been significant advanced by the Internet of Things (IoT) and cyber physical interaction technologies, which enables the participants to engage with the art devices. Several tools and platforms have been proposed to create the art devices. However, the interactive artworks are typically developed with these art devices in ad hoc approaches, and the artists need to spend significant programming efforts to integrate the art devices. This paper proposes CATtalk, a platform to create and maintain interactive artworks. The novel idea is to treat all art devices in an interactive artwork as IoT devices that can be transparently reused by reconfiguration in CATtalk. Therefore, the artworks developed independently by individual artists can be quickly integrated to create new interactive applications. Through CATtalk's no-code and low-code mechanisms, the artists can manipulate CATtalk with little or no programing efforts. CATtalk offers a built-in mechanism so that any person in the audience can play with an interactive artwork with his/her smartphone. We also conduct analytic analysis, simulation and measurements to ensure that the interactive art performance in cross-country remote stages are not affected by the communications delays. In our measurements, the average local and remote communication delays are about 0.01 and 0.05 seconds, respectively. If the art performance is designed such that the average delay between two actions of a local (remote) performer is longer than 0.1 seconds, then the probability of out-of-sequence actions is less than 0.01%. That is, the local dancer should perform slower than the remote dancer. Such delay analysis for remote interactive art performance has not been conducted in the literature. |
5,570 | Digital design and manufacturing on the cloud: A review of software and services | In recent years, industrial nations around the globe have invested heavily in new technologies, software, and services to advance digital design and manufacturing using cyber-physical systems, data analytics, and high-performance computing. Many of these initiatives, such as cloud-based design and manufacturing, fall under the umbrella of what has become known as Industry 4.0 or Industrial Internet and are often hailed as pillars of a new industrial revolution. While an increasing number of companies are developing or already offer commercial cloud-based software packages and services for digital design and manufacturing, little work has been reported on providing a review of the state of the art of these commercial software and services as well as identifying research gaps in this field. The objective of this paper is to present a state-of-the-art review of digital design and manufacturing software and services that are currently available on the cloud. The focus of this paper is on assessing to what extent engineering design, engineering analysis, manufacturing, and production across all phases of the product development lifecycles can already be performed based on the software and services accessed through the cloud. In addition, the key capabilities and benefits of these software packages and services are discussed. Based on the assessment of the core features of commercial software and services, it can be concluded that almost all phases of product realization can be conducted through digital design and manufacturing software and services on the cloud. Finally, existing research gaps and related challenges to overcome are identified. The state-of-the-art review serves to provide a technology guide for decision makers in their efforts to select suitable cloud-based software and services as alternatives to existing in-house resources as well as to recommend new research areas. |
5,571 | Minimizing flowtime in a flowshop scheduling problem with a biased random-key genetic algorithm | In this paper, we advance the state of the art for solving the Permutation Flowshop Scheduling Problem with total flowtime minimization. For this purpose, we propose a Biased Random-Key Genetic Algorithm (BRKGA) introducing on it a new feature called shaking. With the shaking, instead to full reset the population to escape from local optima, the shaking procedure perturbs all individuals from the elite set and resets the remaining population. We compare results for the standard and the shaking BRKGA with results from the Iterated Greedy Search, the Iterated Local Search, and a commercial mixed integer programming solver, in 120 traditional instances. For all algorithms, we use warm start solutions produced by the state-of-the-art Beam-Search procedure. Computational experiments show the efficiency of proposed BRKGA, in addition to identify lower and upper bounds, as well as some optimal values, among the solutions. (C) 2019 Elsevier Ltd. All rights reserved. |
5,572 | Agro-pastoral rituals and shaman dances of Dahongyan rock painting, Guizhou, Southwestern China, new investigations | Guizhou was for a long time the wildest and the most enclave province of South China, its ethnographic, historical, archaeological and prehistoric researches are recent, especially that of the rock paintings (Wang and Luo, 1989; Cao, 2004; He, 2006; Yu, 2009). Dahongyan, or the Great Red Cliff, is the first rock art locality known in the Province. The research program is conducted by Cao Bo, vice-director of the Guizhou Provincial Culture Relics and Archaeology Institute. In 2012, a cooperation has developed with the Mountain Resources Institute, Academy of Sciences of Guizhou, and the Department of Prehistory of the Natural Museum of Natural History, Paris, France. The first description of the rock paintings has been presented at the IFRAO (International Federation of Rock Art Organizations) world Congress in July 2014, at Guiyang (Cao et al., 2014). The meeting was co-organized with the People's Government of Guiyang Municipality and the Rock Art Research Association of China (RARAC). The preliminary studies of some frescoes put in light ritual shamanic practices from agro-pastoral peoples before rice cultivation, in relation with animal spirits symbolized by the buffalo and the python. Three scenes are described with new observations and interpreted in the historical context of ethnic minorities and their cultural traditions devoid of written language. They have been named "The shaman dance", "The dance lesson" and "The meeting". |
5,573 | Two tree-based methods for the waterfall | The waterfall transform is a hierarchical segmentation technique based on the watershed transform from the field of mathematical morphology. Watershed-based techniques are useful in numerous fields ranging from image segmentation to cell-and-portal generation for games. The waterfall helps mitigate the problem of over-segmentation that commonly occurs when applying the basic watershed transform. It can also be used as a core part of a method for constructing image partition forests, a tree-based, multiscale representation of an image. The best existing method for the waterfall is fast and effective, but our experience has been that it is not as straightforward to implement as might be desired. Furthermore, it does not deal consistently with the issue of non-minimal plateaux. This paper therefore proposes two new tree-based methods for the waterfall. Both are easier to implement than the existing state-of-the-art, and in our implementations, both were faster by a constant factor. The Simplified Waterfall (SW) method focuses on simplicity and ease of implementation; the Balanced Waterfall (BW) method focuses on robust handling of non-minimal plateaux. We perform experiments on both 2D and 3D images to contrast the new methods with each other and with the existing state-of-the-art, and show that both achieve a noticeable speed-up whilst producing similar results. (C) 2014 Elsevier Ltd. All rights reserved. |
5,574 | Synthesized pansharpening using curvelet transform and adaptive neuro-fuzzy inference system | Image fusion is an important technique in remote sensing to improve visual interpretation and classification. Pansharpening is the procedure of fusing panchromatic (PAN) and multispectral images to produce high spatial and spectral resolution images. Synthesized pansharpening is performed on Linear Imaging Self-Scanning Sensor III and Advanced Wide Field Sensor data, which are freely available and provided by the National Remote Sensing Center. The Adaptive Neuro-Fuzzy Inference System (ANFIS) in multiscale transform domain for multisensor image fusion application is evaluated. The state-of-the-art method has been evaluated by various quality metrics. The computational cost of ANFIS with wavelet, contourlet, shearlet, and curvelet transform is investigated. This study proves that curvelet with ANFIS-based fusion technique outperformed state-of-the-art techniques. The application will be used to incorporate the missing spectral information in the high spatial resolution PAN image to identify objects, highlighting the regions clearly. (C) 2019 Society of Photo-Optical Instrumentation Engineers (SPIE) |
5,575 | A paleolimnological context of ecological vulnerability for the freshwater ecosystems of Sable Island National Park Reserve, Canada | Protected areas require long-term monitoring to understand the influence and extent of ecosystem stress to inform management and conservation decisions. As long-term data are not always available, paleolimnological methods offer a way of extending our knowledge of past environmental conditions necessary to use as context for remediation. Here, we examine four sediment cores and additional surface sediments from 14 ponds located on Sable Island National Park Reserve Canada (SINPR), where long-term ecological changes and vulnerability to disturbance are not well defined. We develop a paleolimnological approach to assessing environmental vulnerability through the use of biological indicators (Diptera: Chironomidae), where shifts in the environment are inferred by shifts in chironomid assemblages over time. Analysis of surface sediments show four distinct assemblage types reflecting four different habitat conditions; primarily represented by the presence of Glyptotendipes, Chironomus, Microtendipes, and Dicrotendipes. Differences in habitat conditions through time based on these results are then compared to biostratigraphic analysis of sediment cores from four of the ponds. We found that two ponds had large shifts in chironomids assemblages that were associated with changes in habitat over time, while two others that were not as exposed to the influence of erosion and influx of sand dunes did not. Our findings established a baseline of historical change in SINPR, broadening the scope of long-term monitoring, which is essential for defining goals for management and conservation of the ecological integrity of Sable Island. |
5,576 | Extrachromosomal circular DNA: Current status and future prospects | Extrachromosomal circular DNA (eccDNA) is a double-stranded DNA molecule found in various organisms, including humans. In the past few decades, the research on eccDNA has mainly focused on cancers and their associated diseases. Advancements in modern omics technologies have reinvigorated research on eccDNA and shed light on the role of these molecules in a range of diseases and normal cell phenotypes. In this review, we first summarize the formation of eccDNA and its modes of action in eukaryotic cells. We then outline eccDNA as a disease biomarker and reveal its regulatory mechanism. We finally discuss the future prospects of eccDNA, including basic research and clinical application. Thus, with the deepening of understanding and exploration of eccDNAs, they hold great promise in future biomedical research and clinical translational application. |
5,577 | Artificial intelligence-based creative thinking skill analysis model using human-computer interaction in art design teaching | Due to the rapid growth of network technology, its openness and sharing capabilities and interaction have helped change the art education model for the better. Increased science has been presented to students who spend a lot of time utilizing technology. They similarly did greater mathematical abilities. IT has a good effect on student learning must be included in classroom education. Art education must shift from a teacher-centred to a student-centred approach, and students' passive reception of knowledge must be altered. Students' academic enthusiasm and awareness must be fostered, and their ability to locate knowledge resources must be enhanced. Using pedagogical content knowledge (PCK) in visual art education as a benchmark and this study examines art teachers' PCK proficiency in this area. Social learning theory is applied in the art education curriculum through observational learning based on the Artificial Intelligence-based Creative Thinking Skills Analysis Model (AI-CTSAM). An analytical hierarchy process (AHP) and a grey clustering-based performance analysis model are established to enhance AI's effectiveness in art instruction. Most of the methods to assess clustering performance exist in two types in which one is irrelevant actions requiring labels of foundation truth. Examples are Adjusted Rand, Fowlkes-Mallows, Mutual information scores, Homogeneity, Completeness, and V measurements. Model-based cluster analysis is a new classification approach for investigating population heterogeneity utilizing a limited multivariate mixture. Students can describe, analyze, interpret, and evaluate artwork through the visual art education curriculum. |
5,578 | Scholarship on urban Africa's water crisis narratives: the state of the art | Water crises present a global water governance challenge. To date, scholarship has tended to focus on technological and policy-based solutions, while ignoring the influence of narratives on public buy-in during such crises. Africa is expected to become hotter and drier in future, while its cities experience high levels of informal population growth and inequality. These factors combine to make African cities particularly vulnerable to times of water stress. The aim in this paper is to investigate the state of the 'art' on narratives framing domestic water use in African cities during periods of acute water stress and 'crises', using a systematic literature review of peer-reviewed academic journal articles. The findings revealed a small population of recently published papers that engage critically with state-generated narratives framing the crisis, limited to case studies on Cape Town and Windhoek. We recommend, however, a greater critical engagement with the anti-establishment narratives that can flourish during periods of acute water stress, and tend to be inflammatory and divisive in nature. |
5,579 | A statistical framework for few-shot action recognition | Along with the exponential growth of online video creation platforms such as Tik Tok and Instagram, state of the art research involving quick and effective action/gesture recognition remains crucial. This work addresses the challenge of classifying short video clips, using a domain-specific feature design approach, capable of performing significantly well using as little as one training example per action. The method is based on Gunner Farneback's dense optical flow (GF-OF) estimation strategy, Gaussian mixture models, and information divergence. We first aim to obtain accurate representations of the human movements/actions by clustering the results given by GF-OF using K-means method of vector quantization. We then proceed by representing the result of one instance of each action by a Gaussian mixture model. Furthermore, using Kullback-Leibler divergence (KL-divergence), we attempt to find similarities between the trained actions and the ones in the test videos. Classification is done by matching each test video to the trained action with the highest similarity (a.k.a lowest KL-divergence). We have performed experiments on the KTH and Weizmann Human Action datasets using One-Shot and K-Shot learning approaches, and the results reveal the discriminative nature of our proposed methodology in comparison with state-of-the-art techniques. |
5,580 | Case report: Langerhans cell histiocytosis of the temporal bone in children: Challenging diagnosis of a rare disease with some pitfalls | A 4-year-old girl was admitted to hospital with disturbance of balance. After being questioned, parents remembered an otitis with effusion 3 months earlier. CT-scans revealed destruction of both temporal bones. Initial biopsy showed granulomatous, necrotic inflammation, which led to comprehensive differential diagnoses. A second tissue sample confirmed Langerhans cell histiocytosis. |
5,581 | The Essential Role of Water Molecules in the Reaction Mechanism of Protein O-Fucosyltransferase 2 | Protein O-fucosyltransferase 2 (PoFUT2) is an inverting glycosyltransferase (GT) that fucosylates thrombospondin repeats (TSRs) from group 1 and 2. PoFUT2 recognizes a large and diverse number of TSRs through a dynamic network of water-mediated interactions. By X-ray structural studies of C. elegans PoFUT2 complexed to a TSR of group 2, we demonstrate that this GT recognizes similarly the 3D structure of TSRs from both groups 1 and 2. Its active site is highly exposed to the solvent, suggesting that water molecules might also play an essential role in the fucosylation mechanism. We applied QM/MM methods using human PoFUT2 as a model, and found that HsPoFUT2 follows a classical SN 2 reaction mechanism in which water molecules contribute to a great extent in facilitating the release of the leaving pyrophosphate unit, causing the H transfer from the acceptor nucleophile (Thr/Ser) to the catalytic base, which is the last event in the reaction. This demonstrates the importance of water molecules not only in recognition of the ligands but also in catalysis. |
5,582 | SAR Time-Series Despeckling via Nonlocal Total Variation Regularized Robust PCA | Through the development of synthetic aperture radar (SAR) technology, it is now possible to observe dynamic processes on the earth with fine temporal resolution by forming SAR time series. Nonetheless, such sequential images remain difficult to interpret due to the speckle effect. Despeckling them is further complicated by outliers caused by abrupt changes in weather conditions or the appearance of objects. In spite of the fact that many state-of-the-art methods can achieve excellent filtering performances over stable areas, they often result in artifacts in those areas where outliers existed at the time of acquisition. To simultaneously mitigate the speckle noise and extract outliers, we propose a novel SAR time-series despeckling method based on nonlocal total variation (TV) regularized robust principle component analysis (RPCA), which is termed SAR-NL-TVRPCA. By comparing it to other state-of-the-art methods, the effectiveness of its despeckling has been validated in real data experiments. Furthermore, the extracted outliers can provide insights into abrupt changes occurring throughout the observation period, which provides byproducts for further analysis. |
5,583 | Resilient operation of DC microgrid against FDI attack: A GRU based framework | DC microgrid is the most susceptible to cyber-attacks as the communication channel is involved for the imple-mentation of the secondary controller. Accordingly, the false data are injected into the transmitted data (i.e., DC bus voltage) and it may lead to deteriorating the system performance. To address these issues, the gated recurrent unit (GRU) based mechanism is presented to eliminate the false data injection (FDI) attack for the resilient operation of the DC microgrid. The presented GRU-based framework is divided into two parts: 1) estimation strategy: an offline-trained GRU based network is employed herein for online evaluation of the actual DC bus voltage, and 2) mitigation strategy: GRU based trained network is exploited herein with an amalgamation of the proportional-integral (PI) controller to counteract the malicious cyber-attack. The presented GRU-based framework has several advantages such as ease of implementation and computationally efficient, unlike state -of-art methods. The sensitivity analysis is investigated herein to validate the effectiveness of the presented GRU-based framework over state-of-art techniques. Simulation results show satisfactory performance under manifold operating scenarios such as bias injection attack and time-varying attack. In addition, the quantitative and qualitative comparative performances are performed herein to demonstrate the efficacy of the presented framework. |
5,584 | Kernel-Matching Pursuits With Arbitrary Loss Functions | The purpose of this research is to develop a classifier capable of state-of-the-art performance in both computational efficiency and generalization ability while allowing the algorithm designer to choose arbitrary loss functions as appropriate for a give problem domain. This is critical in applications involving heavily imbalanced, noisy, or non-Gaussian distributed data. To achieve this goal, a kernel-matching pursuit (KMP) framework is formulated where the objective is margin maximization rather than the standard error minimization. This approach enables excellent performance and computational savings in the presence of large, imbalanced training data sets and facilitates the development of two general algorithms. These algorithms support the use of arbitrary loss functions allowing the algorithm designer to control the degree to which outliers are penalized and the manner in which non-Gaussian distributed data is handled. Example loss functions are provided and algorithm performance is illustrated in two groups of experimental results. The first group demonstrates that the proposed algorithms perform equivalent to several state-of-the-art machine learning algorithms on well-published, balanced data. The second group of results illustrates superior performance by the proposed algorithms on imbalanced, non-Gaussian data achieved by employing loss functions appropriate for the data characteristics and problem domain. |
5,585 | Symbolism of the ibex motif in Negev rock art | The male ibex is the dominant zoomorphic motif in rock art of the Negev desert, Israel. It recurs in thousands of petroglyphs, either alone or in association with several recurring images; commonly with dogs or other predators but also with hunters. These associations occur in all chronological phases of Negev rock art, implying that they had an enduring symbolic significance. Here we address only some aspects of ibex iconography, focusing on its association with dogs, hunters and astral symbols. We discuss the possible meaning of these associations with regard to the ritual hunting of ibex and connection to deities associated with rainfall, seasonal cycles and celestial constellations. (C) 2016 Elsevier Ltd. All rights reserved. |
5,586 | Optical band gap enhancements of chemically synthesized α-Ni(OH)2 nanoparticles by a novel technique: Precipitator molarity variation | Nickel hydroxide nanoparticles (NHNPs) are extremely important semiconducting materials for applications in energy storage and energy harvesting devices. This study uses a novel variation in molarity of the sodium hydroxide (NaOH) precipitator solution to enhance the direct optical band gap in the NHNPs chemically synthesized by using nickel nitrate hexahydrate (Ni(NO3 )2 ·6H2 O) as the precursor. The simple, energy benign chemical precipitation route involved the usage of 1 M (Ni(NO3 )2 ·6H2 O) solutions as the precursor and 0.4 M, 0.6 M, and 0.8 M NaOH solutions as the precipitator solutions. The simple variation in precipitator molarity induces an increase in pH from about 6.9 to 7.5 of the reactant solution. As the molarity of the precursor solution does not change, the change in pH of the reactant solution is equivalent to the change in the pH of the precipitator solution. The NHNPs characterized by X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), dynamic light scattering (DLS), Fourier-transform infrared (FTIR) and ultraviolet-visible (UV-vis) techniques confirm a reduction of the nanocrystallite size from about 6.8 to 4.5 nm with a concomitant enhancement in the direct optical band gap energy from about 2.64 to 2.74 eV. The possible mechanisms that could be operative behind obtaining microstructurally tuned (MT)-NHNPs and band gap engineering (BGE) of the MT-NHNPs are discussed from both theoretical and physical process perspectives. Further, the implications of these novel results for possible future applications are briefly touched upon. The reported results might be useful to assess the material as an active electrode to improve the performance of batteries. |
5,587 | Software Frameworks for SDR | This paper describes the state of the art in software frameworks for executing Software Defined Radio (SDR) components. These frameworks are catalyzing drastic changes in signal processing by enabling software engineers and signal processing engineers to work in tandem on core challenges, such as effectively processing large amounts of data in real-time on limited hardware resources. In addition to a historical perspective of this area, we showcase the REDHAWK framework as an example of a modern SDR framework which provides many facilities for distributed SDR deployment. |
5,588 | Anthropogenic influences on coastal environmental changes in the Mekong Delta: a study from Ben Tre Province, Southern Vietnam | Low-lying coastal environments are highly dynamic and sensitive to natural as well as anthropogenic perturbations. Climate change, sea level rise, storms and tsunamis are the natural phenomena that affect the deltaic coasts in Southeast Asia in general and Vietnam in particular. The effects of these phenomena can be exacerbated by human activities such as mangrove deforestation, aquaculture and infrastructure development. Conversely, the low-lying coastal areas are important in the economic development of Southeast Asian countries. In the Vietnamese Mekong Delta, coastal areas have been affected by a number of factors, such as climate change, sea level rise, aquaculture, pollution and tourism-related activities in recent decades. The present study investigated shoreline changes, expansion of aquaculture ponds, soil salinity changes and salinity intrusion in the river systems along the coastal areas of Ben Tre Province in the Vietnamese Mekong Delta between 1998 and 2020 using satellite imagery and field data. Variations in erosion and accretion were found to be not unique along the coast of Ben Tre. There was a rapid expansion of aquaculture ponds between 1998 and 2015 and a slight decline since then. Soil salinity has been increased between 1998 and 2020; it is seen from recent satellite data that soil is becoming more saline in the inland areas of Ben Tre. Saltwater intrusion into the rivers of Ben Tre is considered associated with El Niño-La Niña conditions. It is suggested that reforestation of abandoned shrimp ponds in Ben Tre by mangrove vegetation can be effective as a bioshield against coastal hazards, such as sea level rise and shoreline erosion. |
5,589 | On the Improved High-Frequency Linearity of Drain Extended MOS Devices | Based upon two-tone measurements, 5dB improvement in the linearity behavior of drain extended MOS (DeMOS) device is reported by novel drain engineering. The presented modification significantly improves the device saturation characteristic, ON resistance and transconductance without affecting the breakdown behavior. Formation of IMD sweet-spot by device design is shown and verified using DeMOS devices fabricated in state-of-the-art 28nm CMOS technology. Detailed analysis towards the achieved improvement is also given. |
5,590 | ART(2)ool: a model-driven framework to generate target code for robot handling tasks | Nowadays, robotic manipulation tasks are present in modern production industries, making robotics a decisive discipline in the industrial sector. Additionally, in a short period of time, handle robots will be also become essential in daily life. There is an increase in demand for applications for handle robots with software requirements such as reusability, flexibility, and adaptability. Unfortunately, the current lack of standardization of hardware and software platforms hinders the fulfillment of these requirements. Hence, it is necessary to define a methodology that provides guidelines to design, implement, and support at runtime of such types of applications. This work explores the advantages of Model Driven Engineering (MDE) in the design and development of tasks performed by handle robots. Concretely, the authors present the ART(2)ool (Arm based Robotic Tasks modeling Tool), a MDE framework, which is very useful for application domain experts, because it guides them along the design of the application functionality, abstracting from the emerging techniques. Besides, the proposed framework supports an automatic code generation by Mode to Text transformation techniques for component-based and ROS communication middleware, achieving the requirements mentioned previously. |
5,591 | Highly Stable 4.6 V LiCoO2 Cathodes for Rechargeable Li Batteries by Rubidium-Based Surface Modifications | Among extensively studied Li-ion cathode materials, LiCoO2 (LCO) remains dominant for portable electronic applications. Although its theoretical capacity (274 mAh g-1 ) cannot be achieved in Li cells, high capacity (≤240 mAh g-1 ) can be obtained by raising the charging voltage up to 4.6 V. Unfortunately, charging Li-LCO cells to high potentials induces surface and structural instabilities that result in rapid degradation of cells containing LCO cathodes. Yet, significant stabilization is achieved by surface coatings that promote formation of robust passivation films and prevent parasitic interactions between the electrolyte solutions and the cathodes particles. In the search for effective coatings, the authors propose RbAlF4 modified LCO particles. The coated LCO cathodes demonstrate enhanced capacity (>220 mAh g-1 ) and impressive retention of >80/77% after 500/300 cycles at 30/45 °C. A plausible mechanism that leads to the superior stability is proposed. Finally the authors demonstrate that the main reason for the degradation of 4.6 V cells is the instability of the anode side rather than the failure of the coated cathodes. |
5,592 | Louse flies holding on mammals' hair: Comparative functional morphology of specialized attachment devices of ectoparasites (Diptera: Hippoboscoidea) | Hippoboscidae and Nycteribiidae of the dipteran superfamily Hippoboscoidea are obligate ectoparasites, which feed on the blood of different mammals. Due to their limited flight capability, the attachment system on all tarsi is of great importance for a secure grasp onto their host and thus for their survival. In this study, the functional morphology of the attachment system of two hippoboscid species and two nycteribiid species was compared in their specificity to the host substrate. Based on data from scanning electron microscopy and confocal laser scanning microscopy, it was shown that the attachment systems of both Hippoboscidae and Nycteribiidae (Hippoboscoidea) differ greatly from that of other calyptrate flies and are uniform within the respective families. All studied species have an attachment system with two monodentate claws and two pulvilli. The claws and pulvilli of the Hippoboscidae are asymmetric, which is an adaptation to the fur of even-toed ungulates (Artiodactyla). The fur of these mammals possesses both, thinner woolen and thicker coat hair; thus, the asymmetry of the attachment system of the hippoboscid species enables a secure attachment to all surfaces of their hosts. The claws and pulvilli of the nyceribiid species do not show an asymmetry, since the fur of their bat (Chiroptera) hosts consists of hairs with the same thickness. The claws are important for the attachment to mammals' fur, because they enable a secure grip by mechanical interlocking of the hairs through the claws. Additionally, well-developed pulvilli are able to attach on thicker hairs of Artiodactyla or on smooth substrates such as the skin. |
5,593 | Sample-Adaptive GANs: Linking Global and Local Mappings for Cross-Modality MR Image Synthesis | Generative adversarial network (GAN) has been widely explored for cross-modality medical image synthesis. The existing GAN models usually adversarially learn a global sample space mapping from the source-modality to the target-modality and then indiscriminately apply this mapping to all samples in the whole space for prediction. However, due to the scarcity of training samples in contrast to the complicated nature of medical image synthesis, learning a single global sample space mapping that is "optimal" to all samples is very challenging, if not intractable. To address this issue, this paper proposes sample-adaptive GAN models, which not only cater for the global sample space mapping between the source- and the target-modalities but also explore the local space around each given sample to extract its unique characteristic. Specifically, the proposed sample-adaptive GANs decompose the entire learning model into two cooperative paths. The baseline path learns a common GAN model by fitting all the training samples as usual for the global sample space mapping. The new sample-adaptive path additionally models each sample by learning its relationship with its neighboring training samples and using the target-modality features of these training samples as auxiliary information for synthesis. Enhanced by this sample-adaptive path, the proposed sample-adaptive GANs are able to flexibly adjust themselves to different samples, and therefore optimize the synthesis performance. Our models have been verified on three cross-modality MR image synthesis tasks from two public datasets, and they significantly outperform the state-of-the-art methods in comparison. Moreover, the experiment also indicates that our sample-adaptive strategy could be utilized to improve various backbone GAN models. It complements the existing GANs models and can be readily integrated when needed. |
5,594 | Multi-Objective Memetic Search for Robust Motion and Distortion Correction in Diffusion MRI | Effective image-based artifact correction is an essential step in the analysis of diffusion MR images. Many current approaches are based on retrospective registration, which becomes challenging in the realm of high b-values and low signal-to-noise ratio, rendering the corresponding correction schemes more and more ineffective. We propose a novel registration scheme based on memetic search optimization that allows for simultaneous exploitation of different signal intensity relationships between the images, leading to more robust registration results. We demonstrate the increased robustness and efficacy of our method on simulated as well as in vivo datasets. In contrast to the state-of-art methods, the median target registration error (TRE) stayed below the voxel size even for high b-values (3000 s . mm(-2) and higher) and low SNR conditions. We also demonstrate the increased precision in diffusion-derived quantities by evaluating Neurite Orientation Dispersion and Density Imaging (NODDI) derived measures on a in vivo dataset with severe motion artifacts. These promising results will potentially inspire further studies on metaheuristic optimization in diffusion MRI artifact correction and image registration in general. |
5,595 | Multi-Slice Fusion for Sparse-View and Limited-Angle 4D CT Reconstruction | Inverse problems spanning four or more dimensions such as space, time andother independent parameters have become increasingly important. State-of-the-art 4D reconstruction methods use model based iterative reconstruction (MBIR), but depend critically on the quality of the prior modeling. Recently, plug-and-play (PnP) methods have been shown to he an effective way to incorporate advanced prior models using state-of-the-art denoising algorithms. However, state-of-the-art denoisers such as BM4D and deep convolutional neural networks (CNNs) are primarily available for 2D or 3D images and extending them to higher dimensions is difficult due to algorithmic complexity and the increased difficulty of effective training. In this paper, we present multi-slice fusion, a novel algorithm for 4D reconstruction, based on the fusion of multiple low-dimensional denoisers. Our approach uses multi-agent consensus equilibrium (MACE), an extension of plug-and-play, as a framework for integrating the multiple lower-dimensional models. We apply our method to 4D cone-beam X-ray CT reconstruction for non destructive evaluation (NDE) of samples that are dynamically moving during acquisition. We implement multi-slice fusion on distributed, heterogeneous clusters in order to reconstruct large 4D volumes in reasonable time and demonstrate the inherent parallelizable nature of the algorithm. We present simulated and real experimental results on sparse-view and limited-angle CT data to demonstrate that multi-slice fusion can substantially improve the quality of reconstructions relative to traditional methods, while also being practical to implement and train. |
5,596 | Automatic fire pixel detection using image processing: a comparative analysis of rule-based and machine learning-based methods | This paper presents a comparative analysis of state-of-the art image processing-based fire color detection rules and methods in the context of geometrical characteristics measurement of wildland fires. Two new rules and two new detection methods using an intelligent combination of the rules are presented, and their performances are compared with their counterparts. The benchmark is performed on approximately two hundred million fire pixels and seven hundred million non-fire pixels extracted from five hundred wildland images under diverse imaging conditions. The fire pixels are categorized according to fire color and existence of smoke; meanwhile, non-fire pixels are categorized according to the average intensity of the corresponding image. This characterization allows to analyze the performance of each rule by category. It is shown that the performances of the existing rules and methods from the literature are category dependent, and none of them is able to perform equally well on all categories. Meanwhile, a new proposed method based on machine learning techniques and using all the rules as features outperforms existing state-of-the-art techniques in the literature by performing almost equally well on different categories. Thus, this method, promises very interesting developments for the future of metrologic tools for fire detection in unstructured environments. |
5,597 | A quick pipeline for the isolation of 3D cell culture-derived extracellular vesicles | Recent advances in cell biology research regarding extracellular vesicles have highlighted an increasing demand to obtain 3D cell culture-derived EVs, because they are considered to more accurately represent EVs obtained in vivo. However, there is still a grave need for efficient and tunable methodologies to isolate EVs from 3D cell cultures. Using nanofibrillar cellulose (NFC) scaffold as a 3D cell culture matrix, we developed a pipeline of two different approaches for EV isolation from cancer spheroids. A batch method was created for delivering high EV yield at the end of the culture period, and a harvesting method was created to enable time-dependent collection of EVs to combine EV profiling with spheroid development. Both these methods were easy to set up, quick to perform, and they provided a high EV yield. When compared to scaffold-free 3D spheroid cultures on ultra-low affinity plates, the NFC method resulted in similar EV production/cell, but the NFC method was scalable and easier to perform resulting in high EV yields. In summary, we introduce here an NFC-based, innovative pipeline for acquiring EVs from 3D cancer spheroids, which can be tailored to support the needs of variable EV research objectives. |
5,598 | Naturally occurring pre-S mutations promote occult HBV infection by affecting pre-S2/S promoter activity | Occult hepatitis B virus (HBV) infection (OBI) has non-negligible clinical significance, but the mechanism of its occurrence remains unclear. Growing evidence suggests that mutations in the pre-S region of HBV genome may be associated with the occurrence of OBI. However, the role of pre-S mutations in OBI and its molecular mechanism was not fully understand. Here, the pre-S sequences from 307 OBI blood donors and 293 hepatitis B surface protein (HBsAg)-positive blood donors were obtained, and we observed a higher frequency of naturally occurring pre-S mutations in OBI donors infected with genotype B/C HBV than in HBsAg-positive donors, suggesting their potential positive role in OBI. In both genotype B and C, several pre-S mutants resulted in markedly reduced HBsAg production in vitro. In particular, the T68I, S78N and N98T mutants of genotype B were proven to significantly decrease the HBsAg synthesis by affecting the pre-S2/S promoter activity, and thereby promoting the occurrence of OBI. |
5,599 | On the Security and Privacy Challenges of Virtual Assistants | Since the purchase of Siri by Apple, and its release with the iPhone 4S in 2011, virtual assistants (VAs) have grown in number and popularity. The sophisticated natural language processing and speech recognition employed by VAs enables users to interact with them conversationally, almost as they would with another human. To service user voice requests, VAs transmit large amounts of data to their vendors; these data are processed and stored in the Cloud. The potential data security and privacy issues involved in this process provided the motivation to examine the current state of the art in VA research. In this study, we identify peer-reviewed literature that focuses on security and privacy concerns surrounding these assistants, including current trends in addressing how voice assistants are vulnerable to malicious attacks and worries that the VA is recording without the user's knowledge or consent. The findings show that not only are these worries manifold, but there is a gap in the current state of the art, and no current literature reviews on the topic exist. This review sheds light on future research directions, such as providing solutions to perform voice authentication without an external device, and the compliance of VAs with privacy regulations. |
Subsets and Splits
No saved queries yet
Save your SQL queries to embed, download, and access them later. Queries will appear here once saved.