uuid
int64 0
6k
| title
stringlengths 8
285
| abstract
stringlengths 22
4.43k
|
|---|---|---|
4,000 | Low-Rank Modeling of Local k-Space Neighborhoods (LORAKS) for Constrained MRI | Recent theoretical results on low-rank matrix reconstruction have inspired significant interest in low-rank modeling of MRI images. Existing approaches have focused on higher-dimensional scenarios with data available from multiple channels, timepoints, or image contrasts. The present work demonstrates that single-channel, single-contrast, single-timepoint k-space data can also be mapped to low-rank matrices when the image has limited spatial support or slowly varying phase. Based on this, we develop a novel and flexible framework for constrained image reconstruction that uses low-rank matrix modeling of local k-space neighborhoods (LORAKS). A new regularization penalty and corresponding algorithm for promoting low-rank are also introduced. The potential of LORAKS is demonstrated with simulated and experimental data for a range of denoising and sparse-sampling applications. LORAKS is also compared against state-of-the-art methods like homodyne reconstruction, l(1)-norm minimization, and total variation minimization, and is demonstrated to have distinct features and advantages. In addition, while calibration-based support and phase constraints are commonly used in existing methods, the LORAKS framework enables calibrationless use of these constraints. |
4,001 | Thermoresponsive Random Poly(ether urethanes) with Tailorable LCSTs for Anticancer Drug Delivery | A new class of thermoresponsive random polyurethanes is successfully synthesized and characterized. Poly(ethylene glycol) diol (Mn = 1500 Da) and 2,2-dimethylolpropionic acid are reacted with isophorone diisocyanate in the presence of methane sulfonic acid catalyst. It is found that these polyurethanes are thermoresponsive in aqueous media and manifest a lower critical solution temperature (LCST) that can be easily tuned from 30 °C to 70 °C by increasing the poly(ethylene glycol) content. Their sharp LCST transitions make these random polyurethanes ideal candidates for stimuli-responsive drug delivery applications. To that end, the ability of these systems to efficiently sequester doxorubicin (up to 36 wt%) by means of a sonication/dialysis method is successfully demonstrated. Additionally, it is also demonstrated that accelerated doxorubicin release kinetics from the nanoparticles can be attained above the LCST. |
4,002 | Eco-Capabilities as a Pathway to Wellbeing and Sustainability | Eco-Capabilities is an AHRC funded project situated at the intersection of three issues: a concern with children's wellbeing; their disconnect with the environment; and a lack of engagement with arts in school curricula. It builds on Amartya Sen's work on human capabilities as a proxy for wellbeing, developing the term eco-capabilities to describe how children define what they feel they need to live a fully good human life through environmental sustainability, social justice and future economic wellbeing. A total of 101 children aged 7-10 from schools in highly deprived areas participated in eight full days of arts in nature practice. The study drew on arts based research methods, participatory observations, interviews and focus groups with artists, teachers and children. Findings suggest that arts in nature practice contributed towards eight (eco-)capabilities: autonomy; bodily integrity and safety; individuality; mental and emotional wellbeing; relationality: human/nonhuman relations; senses and imagination; and spirituality. This was facilitated through four pedagogical elements: extended and repeated arts in nature sessions; embodiment and engaging children affectively through the senses; 'slowliness', which envelops children with time and space to (re)connect; and thoughtful practice, which facilitates emotional expression. We suggest that, through these elements, arts in nature practice supports children's wellbeing, and guides them towards a more entangled relationship with nature and a clearer understanding of themselves as part of it, thereby motivating them to take better care of it. |
4,003 | Acceleration of Bi-Objective Optimization of Data-Parallel Applications for Performance and Energy on Heterogeneous Hybrid Platforms | Accelerating the bi-objective optimization of applications for performance and energy is crucial to achieving energy efficiency objectives and meeting quality-of-service requirements in modern high-performance computing platforms and cloud computing infrastructures. In this work, we highlight the crucial challenges to accelerate model-based methods proposed for the bi-objective optimization of data parallel applications for performance and energy that employ workload distribution between the executing processors as the decision variable. The methods solve unconstrained bi-objective optimization problems and take input, the processors' performance and energy profiles in the form of discrete functions of workload size, and output Pareto-optimal solutions (workload distributions), minimizing the execution time and the total energy consumption of computations during the parallel execution of the application. One of the challenges is the fast computation of Pareto-optimal solutions. We then formulate the bi-objective optimization problem of data-parallel applications for performance and energy through workload distribution on a cluster of p identical hybrid nodes, each containing h heterogeneous processors. The state-of-the-art algorithm for solving the problem is sequential and takes exorbitant execution times to find Pareto-optimal solutions for even moderate numbers of processors. We propose two algorithms that address this shortcoming. The first algorithm is an exact sequential algorithm that is more efficient and amenable to parallelization and achieves a complexity reduction of O(m x h) over the state-of-the-art sequential algorithm where m is the cardinality of the input discrete execution time and dynamic energy functions. The second algorithm is a parallel algorithm executed by q identical parallel processes that reduces the complexity of our proposed sequential algorithm by O(q). It, therefore, achieves a complexity reduction of O(m x h x q) over the state-of-the-art sequential algorithm. Finally, we experimentally analyze the practical efficacy of our proposed algorithms for two data-parallel applications, matrix multiplication and fast Fourier transform, on a heterogeneous hybrid node containing an Intel Haswell multicore CPU, an Nvidia k40c GPU, and an Nvidia P100 GPU and simulations of clusters of such hybrid nodes. The experiments demonstrate that our proposed algorithms provide tremendous speedups over state-of-the-art solutions. |
4,004 | Human health risk estimation of antibiotics transferred from wastewater and soil to crops | Antibiotics enter into agricultural land, via manure application or wastewater irrigation. The practices of using untreated wastewater in the agricultural system help in the bioaccumulation of antibiotics in vegetables and other crops. Exposure to the bioaccumulated antibiotics poses serious health risks to ecosystem and human. In this study, the prevalence of two fluoroquinolones (levofloxacin and ciprofloxacin), their bioaccumulation in five crops (Daucus carota L., Pisum sativum L., Raphanus raphanistrum L., Lactuca sativa L., Spinacia oleracea L.), and associated human health risks were investigated. Lettuce showed highest bioaccumulation of levofloxacin (LEV) (12.66 μg kg-1) and carrot showed high bioaccumulation of ciprofloxacin (CIP) (13.01 μg kg-1). In roots, bioconcentration factor (BCFroot) was observed to be relatively high in radish (LEV 0.24-0.43, CIP 0.32-0.49) and observed to be lower in spinach (LEV 0.05-0.13, CIP 0.12-0.19). The translocation factor (TF) for LEV and CIP was generally >1 for all five crops under all treatment. The final transfer and distribution of LEV and CIP in the edible parts of the crops were as follows: leaves > shoots > roots for both antibiotics. Risk quotient of both LEV and CIP in current study is found to be in between 0.018 and 0.557 and shows a medium risk (0.1 to 1) to human health due the discharge of untreated wastewater into the fields. However, our study reports that both antibiotics do accumulate in the edible plant parts; therefore, it poses potential risks to human health. |
4,005 | Localization and Segmentation of 3D Intervertebral Discs in MR Images by Data Driven Estimation | This paper addresses the problem of fully-automatic localization and segmentation of 3D intervertebral discs (IVDs) from MR images. Our method contains two steps, where we first localize the center of each IVD, and then segment IVDs by classifying image pixels around each disc center as foreground (disc) or background. The disc localization is done by estimating the image displacements from a set of randomly sampled 3D image patches to the disc center. The image displacements are estimated by jointly optimizing the training and test displacement values in a data-driven way, where we take into consideration both the training data and the geometric constraint on the test image. After the disc centers are localized, we segment the discs by classifying image pixels around disc centers as background or foreground. The classification is done in a similar data-driven approach as we used for localization, but in this segmentation case we are aiming to estimate the foreground/background probability of each pixel instead of the image displacements. In addition, an extra neighborhood smooth constraint is introduced to enforce the local smoothness of the label field. Our method is validated on 3D T2-weighted turbo spin echo MR images of 35 patients from two different studies. Experiments show that compared to state of the art, our method achieves better or comparable results. Specifically, we achieve for localization a mean error of 1.6-2.0 mm, and for segmentation a mean Dice metric of 85%-88% and a mean surface distance of 1.3-1.4 mm. |
4,006 | Mediastinal Lymph Node Detection and Segmentation Using Deep Learning | Automatic lymph node (LN) segmentation and detection for cancer staging are critical. In clinical practice, computed tomography (CT) and positron emission tomography (PET) imaging detect abnormal LNs. Despite its low contrast and variety in nodal size and form, LN segmentation remains a challenging task. Deep convolutional neural networks frequently segment items in medical photographs. Most state-of-the-art techniques destroy image's resolution through pooling and convolution. As a result, the models provide unsatisfactory results. Keeping the issues in mind, a well-established deep learning technique UNet++ was modified using bilinear interpolation and total generalized variation (TGV) based upsampling strategy to segment and detect mediastinal lymph nodes. The modified UNet++ maintains texture discontinuities, selects noisy areas, searches appropriate balance points through backpropagation, and recreates image resolution. Collecting CT image data from TCIA, 5-patients, and ELCAP public dataset, a dataset was prepared with the help of experienced medical experts. The UNet++ was trained using those datasets, and three different data combinations were utilized for testing. Utilizing the proposed approach, the model achieved 94.8% accuracy, 91.9% Jaccard, 94.1% recall, and 93.1% precision on COMBO_3. The performance was measured on different datasets and compared with state-of-the-art approaches. The UNet++ model with hybridized strategy performed better than others. |
4,007 | Deep salient-Gaussian Fisher vector encoding of the spatio-temporal trajectory structures for person re-identification | In this paper, we propose a deep spatio-temporal appearance (DSTA) descriptor for person re-identification (re-ID). The proposed descriptor is based on the deep Fisher vector (FV) encoding of the trajectory spatio-temporal structures. These have the advantage of robustly handling the misalignment in the pedestrian tracklets. The deep encoding exploits the richness of the spatio-temporal structural information around the trajectories. This is achieved by hierarchically encoding the trajectory structures leveraging a larger tracklet neighborhood scale when moving from one layer to the next one. In order to eliminate the noisy background located around the pedestrian and model the uniqueness of its identity, the deep FV encoder is further enriched towards the deep Salient-Gaussian weighted FV (deepSGFV) encoder by integrating the pedestrian Gaussian and saliency templates in the encoding process, respectively. The proposed descriptor produces competitive accuracy with respect to state-of-the art methods and especially the deep CNN ones without necessitating either pre-training or data augmentation on four challenging pedestrian video datasets: PRID2011, i-LIDS-VID, Mars and LPW. The further combination of DSTA with deep CNN boosts the current state-of-the-art methods and demonstrates their complementarity. |
4,008 | The impact of age on the morphology of the 12th thoracic vertebral endplates | The current article explores the aging effects on the overall morphology of the endplates of the 12th thoracic vertebra (T12), while screening for sex differences. It further evaluates the suitability of T12 for estimating age-at-death in bioarcheaological contexts. We captured the morphology of the vertebral endplates, including the formation of osteophytes, in a novel continuous quantitative manner using digital photography. 168 Greek adults from the Athens Collection were used for modeling the aging effects and another 107 individuals from two Danish archaeological assemblages for evaluation. Regression analysis is based on generalized additive models for correlating age-at-death and morphological variation. Our proposed measurement method is highly reliable (R>0.98) and the main differences observed between sexes are size related. Aging has considerable effect on the endplate morphology of the T12 with the total area of the endplate, the area of the epiphyseal rim, and the shape irregularities of the endplate's external boundary being mostly affected. Multivariate regression shows that aging effects account up to 46% of the observed variation, although with differential expression between sexes. Correct age prediction on archaeological remains reached 33% with a prominent tendency for overestimation. The morphology of the T12 endplates is influenced by age and it can provide some insight with respect to the age-at-death of unidentified individuals, especially when other skeletal age markers are unavailable. Our proposed method provides an age-estimation framework for bioarchaeological settings, especially for estimating broader age ranges, such as discriminating between young and old adults. |
4,009 | Hybrid Physics-Based Adaptive Kalman Filter State Estimation Framework | State-of-the art physics-model based dynamic state estimation generally relies on the assumption that the system's transition matrix is always correct, the one that relates the states in two different time instants, which might not hold always on real-life applications. Further, while making such assumptions, state-of-the-art dynamic state estimation models become unable to discriminate among different types of anomalies, as measurement gross errors and sudden load changes, and thus automatically leads the state estimator framework to inaccuracy. Towards the solution of this important challenge, in this work, a hybrid adaptive dynamic state estimator framework is presented. Based on the Kalman Filter formulation, measurement innovation analytical-based tests are presented and integrated into the state estimator framework. Gross measurement errors and sudden load changes are automatically detected, identified, and corrected, providing continuous updating of the state estimator. Towards such, the asymmetry index applied to the measurement innovation is introduced, as an anomaly discrimination method, which assesses the physics-model-based dynamic state estimation process in different piece-wise stationary levels. Comparative tests with the state-of-the-art are presented, considering the IEEE 14, IEEE 30, and IEEE 118 test systems. Easy-to-implement-model, without hard-to-design parameters, build-on the classical Kalman Filter solution, highlights potential aspects towards real-life applications. |
4,010 | Partial Regret After Gender Affirmation Surgery of a 35-Year-Old Taiwanese Transgender Woman | Gender-affirming surgery (GAS) is often sought after to alleviate the distress of those who suffer from gender dysphoria (GD). While many studies have shown that a significant percentage of people benefit from this procedure, a number of individuals later regret their decision of undergoing surgery. Studies have illustrated what regret depicts, categorizing regret based on intensity, persistency, and sources, in the hopes to prevent an unwanted irreversible intervention. Here, an in-depth interview with a 35-year-old transwoman from Taiwan who underwent feminizing GAS at the age of 31 illustrates her unique cultural upbringing and the course of her regret. Her experience best matches the characteristics of true regret and major regret based on the classifications of Pfäfflin and Wiepjes, respectively, indicating that she expected GAS to be the solution to her personal acceptance issue, but, in retrospect, regretted the diagnosis and treatment as her problems were not solved and worsened to the extent of secondary dysphoria. This case report hopes to shed light on the complexity of GD and regret after GAS, while encouraging the pre-surgical evaluation of psychological comorbidities and post-surgical psychotherapy, and ensuring that patients are informed and give full consent. In addition, more elaborate, long-term, large-scale qualitative research, especially within more conservative cultural settings, is needed. |
4,011 | Ageing behaviour and analytical pyrolysis characterisation of diterpenic resins used as art materials: Manila copal and sandarac | Artificial indoor and outdoor exposure conditions have been applied in order to investigate the photo-ageing behaviour of two natural resins once used as art materials. Copals and sandarac consist of free labdane diterpenoids and of a highly cross-linked fraction of polycommunic acid. To determine the nature and the composition of the cross-linked fraction, pyrolysis is required. Thermally assisted hydrolysis and methylation, coupled with gas chromatography-mass spectrometry (THM-GOMS), has been used to identify the acidic compounds. Many secondary pyrolysis products have been recognised and distinguished from the original resin components. Further details on the composition and ageing behaviour of Manila copal and sandarac have been obtained from Fourier transform infrared spectroscopy (FTIR), size exclusion chromatography (SEC) and direct temperature-resolved mass spectrometry (DTMS). During ageing, cross-linking and cleavage reactions were found to affect largely the chemical structure of the two resins, together with minor degradation processes such as isomerisation, defunctionalisation and oxidation. (C) 2003 Elsevier Science B.V. All rights reserved. |
4,012 | Endophilin A2 protects against renal fibrosis by targeting TGF-β/Smad signaling | Renal fibrosis underlies all forms of end-stage kidney disease. Endophilin A2 (EndoA2) plays a role in nephrotic syndrome; however, its effect on renal fibrosis remains unknown. Here, we demonstrate that EndoA2 protects against kidney interstitial fibrosis via the transforming growth factor-β (TGF-β)/Smad signaling pathway. Mouse kidneys with fibrosis or kidney biopsy specimens from patients with fibrotic nephropathy had lower levels of EndoA2 protein expression than that in kidneys without fibrosis. In vivo overexpression of EndoA2 with the endophilin A2 transgene (EndoA2Tg ) notably prevented renal fibrosis, decreased the protein expression of profibrotic molecules, suppressed tubular injury, and reduced apoptotic tubular cells in the obstructed kidney cortex of mice with unilateral ureteral obstruction (UUO). In vivo and in vitro overexpression of EndoA2 markedly inhibited UUO- or TGF-β1-induced phosphorylation of Smad2/3 and tubular epithelial cells dedifferentiation. Furthermore, EndoA2 was co-immunoprecipitated with the type II TGF-β receptor (TβRII), thus inhibiting the binding of the type I TGF-β receptor (TβRI) to TβRII. These findings indicate that EndoA2 mitigates renal fibrosis, at least partially, via modulating the TGF-β/Smad signaling. Targeting EndoA2 may be a new potential therapeutic strategy for treatment of renal fibrosis. |
4,013 | 2-Methoxyjuglone, a Promising Bioactive Compound for Pharmaceutical and Agricultural Purposes: A Review | 2-Methoxyjuglone, a member of the 1,4-naphthoquinone family, was first obtained through semi-synthesis based on 2-hydroxyjuglone as the precursor in 1966. It has been isolated and identified from different plant species of the Juglandaceae, Sterculiaceae, and Proteaceae families. 2-Methoxyjuglone has been demonstrated to possess a wide range of biological activities, including antitumor, antifungal, and antibacterial activities; in addition, it has been shown to poison fish and inhibit seed germination. These properties make 2-methoxyjuglone a promising bioactive compound for pharmaceutical and agricultural purposes. This review article provides an overview of the current research progress on 2-methoxyjuglone for the first time, with a primary focus on the plant sources, extraction, identification, synthesis, and biological activities associated with this compound for further development. |
4,014 | N-acetylcysteine prevents stress-induced anxiety behavior in zebrafish | Despite the recent advances in understanding the pathophysiology of anxiety disorders, the pharmacological treatments currently available are limited in efficacy and induce serious side effects. A possible strategy to achieve clinical benefits is drug repurposing, i.e., discovery of novel applications for old drugs, bringing new treatment options to the market and to the patients who need them. N-acetylcysteine (NAC), a commonly used mucolytic and paracetamol antidote, has emerged as a promising molecule for the treatment of several neuropsychiatric disorders. The mechanism of action of this drug is complex, and involves modulation of antioxidant, inflammatory, neurotrophic and glutamate pathways. Here we evaluated the effects of NAC on behavioral parameters relevant to anxiety in zebrafish. NAC did not alter behavioral parameters in the novel tank test, prevented the anxiety-like behaviors induced by an acute stressor (net chasing), and increased the time zebrafish spent in the lit side in the light/dark test. These data may indicate that NAC presents an anti-stress effect, with the potential to prevent stress-induced psychiatric disorders such as anxiety and depression. The considerable homology between mammalian and zebrafish genomes invests the current data with translational validity for the further clinical trials needed to substantiate the use of NAC in anxiety disorders. |
4,015 | Self-Attentive Spatial Adaptive Normalization for Cross-Modality Domain Adaptation | Despite the successes of deep neural networks on many challenging vision tasks, they often fail to generalize to new test domains that are not distributed identically to the training data. The domain adaptation becomes more challenging for cross-modality medical data with a notable domain shift. Given that specific annotated imaging modalities may not be accessible nor complete. Our proposed solution is based on the cross-modality synthesis of medical images to reduce the costly annotation burden by radiologists and bridge the domain gap in radiological images. We present a novel approach for image-to-image translation in medical images, capable of supervised or unsupervised (unpaired image data) setups. Built upon adversarial training, we propose a learnable self-attentive spatial normalization of the deep convolutional generator network's intermediate activations. Unlike previous attention-based image-to-image translation approaches, which are either domain-specific or require distortion of the source domain's structures, we unearth the importance of the auxiliary semantic information to handle the geometric changes and preserve anatomical structures during image translation. We achieve superior results for cross-modality segmentation between unpaired MRI and CT data for multi-modality whole heart and multi-modal brain tumor MRI (T1/T2) datasets compared to the state-of-the-art methods. We also observe encouraging results in cross-modality conversion for paired MRI and CT images on a brain dataset. Furthermore, a detailed analysis of the cross-modality image translation, thorough ablation studies confirm our proposed method's efficacy. |
4,016 | Family Physician Racial Identity: An Analysis of "Other" Race Selection and Implications for Future Data Collection | Family physicians who report their race as "Other" in a single best option question find the existing categories and forced choice of one category to be problematic. Our analysis of open-text responses in the "Other" race category supports a modification in the way these data are collected to provide more accurate and meaningful ways to understand the workforce and move toward more diverse, equitable, and inclusive policies in family medicine. |
4,017 | Effect of protein supplementation on ruminal parameters and microbial community fingerprint of Nellore steers fed tropical forages | In tropical regions, protein supplementation is a common practice in dairy and beef farming. However, the effect of highly degradable protein in ruminal fermentation and microbial community composition has not yet been investigated in a systematic manner. In this work, we aimed to investigate the impact of casein supplementation on volatile fatty acids (VFA) production, specific activity of deamination (SAD), ammonia concentration and bacterial and archaeal community composition. The experimental design was a 4×4 Latin square balanced for residual effects, with four animals (average initial weight of 280±10 kg) and four experimental periods, each with duration of 29 days. The diet comprised Tifton 85 (Cynodon sp.) hay with an average CP content of 9.8%, on a dry matter basis. Animals received basal forage (control) or infusions of pure casein (230 g) administered direct into the rumen, abomasum or divided (50 : 50 ratio) in the rumen/abomasum. There was no differences (P>0.05) in ruminal pH and microbial protein concentration between supplemented v. non-supplemented animals. However, in steers receiving ruminal infusion of casein the SAD and ruminal ammonia concentration increased 33% and 76%, respectively, compared with the control. The total concentration of VFA increased (P0.05) in species richness and diversity of γ-proteobacteria, firmicutes and archaea between non-supplemented Nellore steers and steers receiving casein supplementation in the rumen. However, species richness and the Shannon-Wiener index were lower (P<0.05) for the phylum bacteroidetes in steers supplemented with casein in the rumen compared with non-supplemented animals. Venn diagrams indicated that the number of unique bands varied considerably among individual animals and was usually higher in number for non-supplemented steers compared with supplemented animals. These results add new knowledge about the effects of ruminal and postruminal protein supplementation on metabolic activities of rumen microbes and the composition of bacterial and archaeal communities in the rumen of steers. |
4,018 | Motor networks in children with autism spectrum disorder: a systematic review on EEG studies | Motor disturbance and altered motor networks are commonly reported in individuals with autism spectrum disorder (ASD). It has been suggested that electroencephalogram (EEG) can be used to provide exquisite temporal resolution for understanding motor control processes in ASD. However, the variability of study design and EEG approaches can impact our interpretation. Here, we conducted a systematic review on recent 11 EEG studies that involve motor observation and/or execution tasks and evaluated how these findings help us understand motor difficulties in ASD. Three behavior paradigms with different EEG analytic methods were demonstrated. The main findings were quite mixed: children with ASD did not always show disrupted neuronal activity during motor observation. Additionally, they might have intact ability for movement execution but have more difficulties in neuronal modulation during movement preparation. We would like to promote discussions on how methodological selections of behavioral tasks and data analytic approaches impact our interpretation of motor deficits in ASD. Future EEG research addressing the inconsistency across methodological approaches is necessary to help us understand neurophysiological mechanism of motor abnormalities in ASD. |
4,019 | A pyramid multi-level face descriptor: application to kinship verification | Texture descriptors such as Local Binary Pattern (LBP), Local Phase Quantization (LPQ), and Histogram of Oriented Gradients (HOG) have been widely used for face image analysis. This work introduces a novel framework for image-based kinship verification able to efficiently combine local and global facial information extracted from diverse descriptors. The proposed scheme relies on two main points: (1) we model the face images using a Pyramid Multi-level (PML) representation where local descriptors are extracted from several blocks at different resolution scales; (2) we compute the covariance (second-order statistics) between diverse local features characterizing each individual block in the PML representation. This gives rise to a face descriptor with two interesting properties: (i) thanks to the PML representation, scales and face parts are explicitly encoded in the final descriptor without having to detect the facial landmarks; (ii) the covariance descriptor encodes spatial features of any type allowing the integration of several state-of-the-art texture and color features. Experiments conducted on three public kinship databases show that the proposed descriptor can outperform many state-of-the-art kinship verification algorithms and descriptors including those that are based on deep Convolutional Neural Nets. |
4,020 | 3-D Consistent and Robust Segmentation of Cardiac Images by Deep Learning With Spatial Propagation | We propose a method based on deep learning to perform cardiac segmentation on short axis Magnetic resonance imaging stacks iteratively from the top slice (around the base) to the bottom slice (around the apex). At each iteration, a novel variant of the U-net is applied to propagate the segmentation of a slice to the adjacent slice below it. In other words, the prediction of a segmentation of a slice is dependent upon the already existing segmentation of an adjacent slice. The 3-D consistency is hence explicitly enforced. The method is trained on a large database of 3078 cases from the U.K. Biobank. It is then tested on the 756 different cases from the U.K. Biobank and three other state-of-the-art cohorts (ACDC with 100 cases, Sunnybrook with 30 cases, and RVSC with 16 cases). Results comparable or even better than the state of the art in terms of distance measures are achieved. They also emphasize the assets of our method, namely, enhanced spatial consistency (currently neither considered nor achieved by the state of the art), and the generalization ability to unseen cases even from other databases. |
4,021 | MRI Upsampling Using Feature-Based Nonlocal Means Approach | In magnetic resonance imaging (MRI), spatial resolution is limited by several factors such as acquisition time, short physiological phenomena, and organ motion. The acquired image usually has higher resolution in two dimensions (the acquisition plane) in comparison with the third dimension, resulting in highly anisotropic voxel size. Interpolation of these low resolution (LR) images using standard techniques, such as linear or spline interpolation, results in distorted edges in the planes perpendicular to the acquisition plane. This poses limitation on conducting quantitative analyses of LR images, particularly on their voxel-wise analysis and registration. We have proposed a new non-local means feature- based technique that uses structural information of a high resolution (HR) image with a different contrast and interpolates the LR image. In this approach, the similarity between voxels is estimated using a feature vector that characterizes the laminar pattern of the brain structures, resulting in a more accurate similarity measure in comparison with conventional patch-based approach. This technique can be applied to LR images with both anisotropic and isotropic voxel sizes. Experimental results conducted on brain MRI scans of patients with brain tumors, multiple sclerosis, epilepsy, as well as schizophrenic patients and normal controls show that the proposed method is more accurate, requires fewer computations, and thus is significantly faster than a previous state-of-the-art patch-based technique. We also show how the proposed method may be used to upsample regions of interest drawn on LR images. |
4,022 | List-Mode PET Motion Correction Using Markerless Head Tracking: Proof-of-Concept With Scans of Human Subject | A custom designed markerless tracking system was demonstrated to be applicable for positron emission tomography (PET) brain imaging. Precise head motion registration is crucial for accurate motion correction (MC) in PET imaging. State-of-the-art tracking systems applied with PET brain imaging rely on markers attached to the patient's head. The marker attachment is the main weakness of these systems. A healthy volunteer participating in a cigarette smoking study to image dopamine release was scanned twice for 2 h with C-11-racolopride on the high resolution research tomograph (HRRT) PET scanner. Head motion was independently measured, with a commercial marker-based device and the proposed vision-based system. A list-mode event-by-event reconstruction algorithm using the detected motion was applied. A phantom study with hand-controlled continuous random motion was obtained. Motion was time-varying with long drift motions of up to 18 mm and regular step-wise motion of 1-6 mm. The evaluated measures were significantly better for motion-corrected images compared to no MC. The demonstrated system agreed with a commercial integrated system. Motion-corrected images were improved in contrast recovery of small structures. |
4,023 | 3-D fabrication using electrical discharge-milling: an overview | The electrical discharge machining (EDM) process has predominantly gained considerable impetus in the varieties of high-tech areas for impeccable machining of complex microfeatures in ultra-hard and exotic materials. The development of computer numerical control (CNC) of machine tools has permitted to explore the capabilities of the EDM process for the fabrication of three-dimensional (3-D) micro/macro features employing the controlled movement of the simpler tools in all three axes (x-, y- and z-axes) in addition to the high-speed rotation about its axis. This variant of the EDM process, which entails a simple cylindrical/rectangular/square cross-section tool to accomplish the intended shape by following the programmed instructions is termed as electrical discharge-milling (ED-Milling) operation. In this review article, an endeavor has been made to present the state-of-the-art research that has been accomplished in ED-Milling and the allied EDM processes for 3-D machining. The article reviews the comparative study of majorly available micro-fabrication techniques, different means of complex 3-D fabrication using spark erosion phenomena, machining performance enhancement methods, material aspects, tool wear analysis and sustainable dielectrics in the ED-Milling. Critical assessment and prospects in the respective areas of research in ED-Milling are recommended. |
4,024 | Protection of farmed camels (Camelus Dromedarius): Welfare problems and legislative perspective | In the last years animal welfare has assumed an increasing interest in our society, influencing legislation to enact many provisions aimed at the protection of animals. Along with increased consumer awareness of the need to maintain ethically acceptable conditions of raised animals, scientists too have begun to investigate the conditions of animal welfare, the tools for its evaluation and for its improvement. Although there are many advances in knowledge, much remains to be investigated concerning many species considered "minor", that is, camels and dromedaries. Dromedaries, recently, have attracted the interest of some breeders following the results of studies concerning the nutritional and therapeutic properties of their products - milk in particular - that make them ideal for some particular categories of consumers, such as diabetics, obesity sufferers, lactose-intolerant subjects, menopausal women and so on. Considering their use in dairy husbandry, dromedaries are reared under intensive and/or semi-intensive systems with the resulting emergence of specific needs, which should be fulfilled in order to have appropriate welfare. This paper's purpose is to give practical elements in order to find out dromedary welfare standards, promoting a comprehensive set of regulations on welfare, care and protection of this animal. |
4,025 | CRISPR Gene Editing of Hematopoietic Stem and Progenitor Cells | Genetic editing of hematopoietic stem and progenitor cells can be employed to understand gene-function relationships underlying hematopoietic cell biology, leading to new therapeutic approaches to treat disease. The ability to collect, purify, and manipulate primary cells outside the body permits testing of many different gene editing approaches. RNA-guided nucleases, such as CRISPR, have revolutionized gene editing based simply on Watson-Crick base-pairing, employed to direct activity to specific genomic loci. Given the ease and affordability of synthetic, custom RNA guides, testing of precision edits or large random pools in high-throughput screening studies is now widely available. With the ever-growing number of CRISPR nucleases being discovered or engineered, researchers now have a plethora of options for directed genomic change, including single base edits, nicks or double-stranded DNA cuts with blunt or staggered ends, as well as the ability to target CRISPR to other cellular oligonucleotides such as RNA or mitochondrial DNA. Except for single base editing strategies, precise rewriting of larger segments of the genetic code requires delivery of an additional component, templated DNA oligonucleotide(s) encoding the desired changes flanked by homologous sequences that permit recombination at or near the site of CRISPR activity. Altogether, the ever-growing CRISPR gene editing toolkit is an invaluable resource. This chapter outlines available technologies and the strategies for applying CRISPR-based editing in hematopoietic stem and progenitor cells. |
4,026 | Sn Dopants with Synergistic Oxygen Vacancies Boost CO2 Electroreduction on CuO Nanosheets to CO at Low Overpotential | Using the electrochemical CO2 reduction reaction (CO2RR) with Cu-based electrocatalysts to achieve carbon-neutral cycles remains a significant challenge because of its low selectivity and poor stability. Modulating the surface electron distribution by defects engineering or doping can effectively improve CO2RR performance. Herein, we synthesize the electrocatalyst of Vo-CuO(Sn) nanosheets containing oxygen vacancies and Sn dopants for application in CO2RR-to-CO. Density functional theory calculations confirm that the incorporation of oxygen vacancies and Sn atoms substantially reduces the energy barrier for *COOH and *CO intermediate formation, which results in the high efficiency, low overpotential, and superior stability of the CO2RR to CO conversion. This electrocatalyst possesses a high Faraday efficiency (FE) of 99.9% for CO at a low overpotential of 420 mV and a partial current density of up to 35.22 mA cm-2 at -1.03 V versus reversible hydrogen electrode (RHE). The FECO of Vo-CuO(Sn) could retain over 95% within a wide potential area from -0.48 to -0.93 V versus RHE. Moreover, we obtain long-term stability for more than 180 h with only a slight decay in its activity. Therefore, this work provides an effective route for designing environmentally friendly electrocatalysts to improve the selectivity and stability of the CO2RR to CO conversion. |
4,027 | Adaptive algorithm for spreading factor selection in LoRaWAN networks with multiple gateways | Recently, LoRaWAN has been considered a promising technology for large-scale IoT applications owing to its ability to achieve low power and long range communications. However, LoRaWAN is limited using Aloha random access scheme. When in dense scenarios, such scheme leads to a high number of collisions, thus severely impacts the reliability and scalability of LoRaWAN. In this paper, we investigate the impact of scalability and densification of nodes and gateways on the system reliability taking into account the capture effect. We propose an optimization problem to derive the node distribution at different spreading factors (SF) in LoRaWAN networks with multiple gateways. We then introduce an adaptive algorithm that enables to easily implement SF optimization by adjusting the signal-to-noise ratio thresholds. Moreover, the performance of the proposed algorithm is compared with the performance of legacy LoRaWAN and relevant algorithms from the state-of-the-art. Simulation results show that the proposed algorithm significantly outperforms the state-of-the-art algorithms, and improves the throughput and packet delivery ratio of the network. |
4,028 | In vivo EPR tooth dosimetry for triage after a radiation event involving large populations | The management of radiation injuries following a catastrophic event where large numbers of people may have been exposed to life-threatening doses of ionizing radiation will rely critically on the availability and use of suitable biodosimetry methods. In vivo electron paramagnetic resonance (EPR) tooth dosimetry has a number of valuable and unique characteristics and capabilities that may help enable effective triage. We have produced a prototype of a deployable EPR tooth dosimeter and tested it in several in vitro and in vivo studies to characterize the performance and utility at the state of the art. This report focuses on recent advances in the technology, which strengthen the evidence that in vivo EPR tooth dosimetry can provide practical, accurate, and rapid measurements in the context of its intended use to help triage victims in the event of an improvised nuclear device. These advances provide evidence that the signal is stable, accurate to within 0.5 Gy, and can be successfully carried out in vivo. The stability over time of the radiation-induced EPR signal from whole teeth was measured to confirm its long-term stability and better characterize signal behavior in the hours following irradiation. Dosimetry measurements were taken for five pairs of natural human upper central incisors mounted within a simple anatomic mouth model that demonstrates the ability to achieve 0.5 Gy standard error of inverse dose prediction. An assessment of the use of intact upper incisors for dose estimation and screening was performed with volunteer subjects who have not been exposed to significant levels of ionizing radiation and patients who have undergone total body irradiation as part of bone marrow transplant procedures. Based on these and previous evaluations of the performance and use of the in vivo tooth dosimetry system, it is concluded that this system could be a very valuable resource to aid in the management of a massive radiological event. |
4,029 | Rendezvous Cost-Aware Opportunistic Routing in Heterogeneous Duty-Cycled Wireless Sensor Networks | This paper analyzes the packet transmission cost in asynchronous heterogeneous duty-cycled wireless sensor network systems (WSNs). We discover limitations of conventional opportunistic routing protocols when they are applied to asynchronous heterogeneous duty-cycled WSNs. The key reason is that the conventional opportunistic routing protocols overlook the rendezvous cost in calculating the packet transmission cost. To solve the above issue, we introduce a novel routing metric, expected transmission cost (ETC), which is designed with the rendezvous cost-aware. The proposed metric, ETC, appropriately captures the packet transmitting cost in heterogeneous duty-cycled WSN environments by incorporating the estimation for both expected communication as well as rendezvous cost. We then design an efficient ETC-based opportunistic routing protocol (EoR) which selects the best forwarding candidates with the least packet transmission cost to reduce the actual energy consumption of sensors in packet transmission. We conduct comprehensive testbed experiments and simulations with Telosb motes for the performance evaluation of EoR in comparison with the state-of-the-art routing protocols. Obtained experimental results indicate that EoR achieves significant improvements in terms of packet latency, delivery ratio, and energy efficiency, in comparison with the state-of-the-art protocols. |
4,030 | Impact of wildfire on granite outcrops in archaeological sites surrounded by different types of vegetation | The lack of scientific information about the effects of wildfire on prehistoric structures and rock art, such as dolmens and petroglyphs, impedes the development of conservation guidelines. In this study, the impact of a recent wildfire (late 2017) on granite outcrops in the San Salvador de Coruxo archaeological site (Vigo, SW Galicia) was evaluated. Samples of the same type of granite were obtained from three sites characterised by different types of vegetation ( natural scrub, native deciduous oak and non- native pine-eucalypt forest) in order to determine how the vegetation influences the fire-caused damage to the rock. Three subsamples were taken from each of the granite samples at depths of 1 cm(-3) cm to study how fire affects the rock at depth. In all sites, the temperature reached at the granite surface was below 380 degrees C. No mineralogical changes due to fire exposure were detected, and no physical changes that could be attributed to the effect of the fire on the fissure system of the granite were identified. However, aesthetic colour changes due to the deposition of organic and charred matter, which even penetrated the fissures, were detected. The existence of lignin-derived compounds, lipids and carbohydrates in the samples from the oakwood site indicates greater resistance to fire effects in this type of vegetation than in the other two types. Although preliminary, these findings suggest that oakwoods could act as protective belts around archaeological sites by reducing the wildfire severity, because of their greater resistance to being burnt, and that they could buffer the damaging effects of fire in natural areas where parietal art is found. (C) 2020 Elsevier B.V. All rights reserved. |
4,031 | Learning semantic ambiguities for zero-shot learning | Zero-shot learning (ZSL) aims at recognizing classes for which no visual sample is available at training time. To address this issue, one can rely on a semantic description of each class. A typical ZSL model learns a mapping between the visual samples of seen classes and the corresponding semantic descriptions, in order to do the same on unseen classes at test time. State of the art approaches rely on generative models that synthesize visual features from the prototype of a class, such that a classifier can then be learned in a supervised manner. However, these approaches are usually biased towards seen classes whose visual instances are the only one that can be matched to a given class prototype. We propose a regularization method that can be applied to any conditional generative-based ZSL method, by leveraging only the semantic class prototypes. It learns to synthesize discriminative features for possible semantic description that are not available at training time, that is the unseen ones. The approach is evaluated for ZSL and GZSL on four datasets commonly used in the literature, either in inductive or transductive settings, with results on-par or above state of the art approaches. The code is available at https://github.com/hanouticelina/lsa-zsl. |
4,032 | Intranasal immunization with HRSV prefusion F protein and CpG adjuvant elicits robust protective effects in mice | Human respiratory syncytial virus (HRSV) is a leading cause of lower respiratory tract infections in elderly individuals and young children/infants and can cause bronchiolitis and even death. There is no licensed HRSV vaccine. An ideal vaccine should induce high titers of neutralizing antibodies and a Th1-biased immune response. In this study, we used EXPI293 cells to express the fusion (F) protein with a prefusion conformation (PrF) and compared the safety and efficacy of intranasal immunization with PrF in combination with two mucosal adjuvants (CpG ODN and liposomes) in mice. After two intranasal administrations, mice in the PrF + CpG group produced high titers of neutralizing antibodies (4961) and a Th1-biased immune response compared with the PrF + Lipo group. The lung viral load of mice in the PrF + CpG group was significantly reduced (3.5 log) compared with that in the adjuvant control group, and the survival rate was 100 %, while the survival rate of mice in the PrF + Lipo group was only 67 %. At the same time, this immunization strategy reduced the pathological damage to the lungs in mice. In conclusion, the combination of PrF and CpG adjuvant is immunogenic, elicits a Th1 type immune response, and completely protects mice from a lethal HRSV challenge. It is worthy of further evaluation as an HRSV vaccine in clinical trials. Clinical trial registration. This study was not related to human participation or experimentation. |
4,033 | Antiretroviral therapy adherence strategies used by patients of a large HIV clinic in Lesotho | A high degree of adherence to antiretroviral therapy (ART) in patients infected with human immunodeficiency virus (HIV) is necessary for long term treatment effects. This study explores the role of timing of ART intake, the information patients received from health workers, local adherence patterns, barriers to and facilitators of ART among 28 HIV-positive adults at the Senkatana HIV Clinic in Maseru, Lesotho. This qualitative, semi-structured interview study was carried out during February and March of 2011 and responses were analyzed inspired by the Grounded Theory method. Results were then compared and discussed between the authors and the main themes that emerged were categorized. The majority of the respondents reported having missed one or more doses of medicine in the past and it was a widespread belief among patients that they were required to skip the dose of ART if they were "late". The main barriers to adherence were interruptions of daily routines or leaving the house without sufficient medicine. The use of mobile phone alarms, phone clocks and support from family and friends were major facilitators of adherence. None of the patients reported to have been counseled on family support or the use of mobile phones as helpful methods in maintaining or improving adherence to ART. Being on-time with ART was emphasized during counseling by health workers. In conclusion, patients should be advised to take the dose as soon as they remember instead of skipping the dose completely when they are late. Mobile phones and family support could be subjects to focus on during future counseling particularly with the growing numbers of mobile phones in Africa and the current focus on telemedicine. |
4,034 | Genome report: chromosome-level draft assemblies of the snow leopard, African leopard, and tiger (Panthera uncia, Panthera pardus pardus, and Panthera tigris) | The big cats (genus Panthera) represent some of the most popular and charismatic species on the planet. Although some reference genomes are available for this clade, few are at the chromosome level, inhibiting high-resolution genomic studies. We assembled genomes from 3 members of the genus, the tiger (Panthera tigris), the snow leopard (Panthera uncia), and the African leopard (Panthera pardus pardus), at chromosome or near-chromosome level. We used a combination of short- and long-read technologies, as well as proximity ligation data from Hi-C technology, to achieve high continuity and contiguity for each individual. We hope that these genomes will aid in further evolutionary and conservation research of this iconic group of mammals. |
4,035 | The Factory of Blood Production: Hematopoietic Stem Cells | Hematopoietic stem cells (HSCs) support the lifelong production of hundreds of billions of blood cells per day. This unique, incredible ability of HSCs also creates an incredible therapeutic potential for patients. To advance this potential, effective methods to study HSCs are continually evolving. This chapter summarizes the variety of protocols and techniques covered in this book used to evaluate HSCs - modification, characterization, interaction with their niche, and in vivo function. |
4,036 | In Situ Separator Modification with an N-Rich Conjugated Microporous Polymer for the Effective Suppression of Polysulfide Shuttle and Li Dendrite Growth | Lithium-sulfur (Li-S) batteries are very promising high-energy-density electrochemical energy storage devices, but suffer from serious Li polysulfide (LiPS) shuttle and uncontrollable Li dendrite growth. Here, we show in situ polyolefin separator modification with an N-rich conjugated microporous polymer (NCMP) for advanced Li-S battery. In situ polymerization generates an ultrathin NCMP coating on the whole external surface and the internal surface of the separator, which is substantially different from the conventional approaches with thick coatings only on the external surface. The NCMP coating with abundant N-containing groups (-NH2 and -N═), uniform nanopores (12.294 Å), and π-conjugated structure can simultaneously inhibit LiPS shuttle and regulate uniform nucleation and growth of Li dendrites. Consequently, the NCMP-based separator endows the Li-S battery with significantly enhanced cycling stability at high S loading (5.4 mg cm-2), lean electrolyte (E/S = 6.3 μL mg-1), and limited Li excess (50 μm). |
4,037 | A Genome-Wide CRISPR-Cas9 Loss-of-Function Screening to Identify Host Restriction Factors Modulating Oncolytic Virotherapy | Oncolytic virotherapy represents an efficient immunotherapeutic approach for cancer treatment. Oncolytic viruses (OVs) promote antitumor responses through tumor-selective cell lysis and immune system activation. However, some tumor cell lines and primary tumors display resistance to therapy. Here we describe a protocol to identify novel host factors responsible for tumor resistance to oncolysis using an unbiased genome-wide CRISPR-Cas9 loss-of-function screening. Cas9-expressing tumor cells are transduced with a library of pooled single-guide RNA (sgRNA)-expressing lentiviruses that target all human genes to obtain a cell population where each cell is knocked out for a single gene. Upon OV infection, resistant cells survive, while sensitive cells die. The relative abundance of each genome-integrated sgRNA is measured by next-generation sequencing (NGS) in resistant and control cells. This protocol is amenable to uncover host factors involved in the resistance to different OVs in multiple tumor models. |
4,038 | Energy- and time-efficient matrix multiplication on FPGAs | We develop new algorithms and architectures for matrix multiplication on configurable devices. These have reduced energy dissipation and latency compared with the state-of-the-art field-programmable gate array (FPGA)-based designs. By profiling well-known designs, we identify "energy hot spots," which are responsible for most of the energy dissipation. Based on this, we develop algorithms and architectures that offer tradeoffs among the number of I/O ports, the number of registers, and the number of PEs. To avoid time-consuming low-level simulations for energy profiling and performance prediction of many alternate designs, we derive functions to represent the impact of algorithm design choices on the system-wide energy dissipation, area, and latency. These functions are used to either optimize the energy performance or provide tradeoffs for a family of candidate algorithms and architectures. For selected designs, we perform extensive low-level simulations using state-of-the-art tools and target FPGA devices. We show a design space for matrix multiplication on FPGAs that results in tradeoffs; among energy, area, and latency. For example, our designs improve the energy performance of state-of-the-art FPGA-based designs by 29%-51% without any increase in the area-latency product. The latency of our designs is reduced one-third to one-fifteenth while area is increased 1.9-9.4 times. In terms of comprehensive metrics such as Energy-Area-Time, our designs exhibit superior performance compared with the state-of-the-art by 50%-79%. |
4,039 | A comparison of 3D shape retrieval methods based on a large-scale benchmark supporting multimodal queries | Large-scale 3D shape retrieval has become an important research direction in content-based 3D shape retrieval. To promote this research area, two Shape Retrieval Contest (SHREC) tracks on large scale comprehensive and sketch-based 3D model retrieval have been organized by us in 2014. Both tracks were based on a unified large-scale benchmark that supports multimodal queries (3D models and sketches). This benchmark contains 13680 sketches and 8987 3D models, divided into 171 distinct classes. It was compiled to be a superset of existing benchmarks and presents a new challenge to retrieval methods as it comprises generic models as well as domain-specific model types. Twelve and six distinct 3D shape retrieval methods have competed with each other in these two contests, respectively. To measure and compare the performance of the participating and other promising Query-by-Model or Query-by-Sketch 3D shape retrieval methods and to solicit state-of-the-art approaches, we perform a more comprehensive comparison of twenty-six (eighteen originally participating algorithms and eight additional state-of-the-art or new) retrieval methods by evaluating them on the common benchmark. The benchmark, results, and evaluation tools are publicly available at our websites (C) 2014 Elsevier Inc. All rights reserved. |
4,040 | Learning Mesh Representations via Binary Space Partitioning Tree Networks | Polygonal meshes are ubiquitous, but have only played a relatively minor role in the deep learning revolution. State-of-the-art neural generative models for 3D shapes learn implicit functions and generate meshes via expensive iso-surfacing. We overcome these challenges by employing a classical spatial data structure from computer graphics, Binary Space Partitioning (BSP), to facilitate 3D learning. The core operation of BSP involves recursive subdivision of 3D space to obtain convex sets. By exploiting this property, we devise BSP-Net, a network that learns to represent a 3D shape via convex decomposition without supervision. The network is trained to reconstruct a shape using a set of convexes obtained from a BSP-tree built over a set of planes, where the planes and convexes are both defined by learned network weights. BSP-Net directly outputs polygonal meshes from the inferred convexes. The generated meshes are watertight, compact (i.e., low-poly), and well suited to represent sharp geometry. We show that the reconstruction quality by BSP-Net is competitive with those from state-of-the-art methods while using much fewer primitives.We also explore variations to BSP-Net including using a more generic decoder for reconstruction, more general primitives than planes, as well as training a generative model with variational auto-encoders. |
4,041 | An Improved Weighted Nuclear Norm Minimization Method for Image Denoising | Patch-based low rank matrix approximation has shown great potential in image denoising. Among state-of-the-art methods in this topic, the weighted nuclear norm minimization (WNNM) has been attracting significant attention due to its competitive denoising performance. For each local patch in an image, the WNNM method groups nonlocal similar patches by block matching to formulate a low-rank matrix. However, the WNNM often chooses irrelevant patches such that it may lose fine details of the image, resulting in undesirable artifacts in the final reconstruction. In this regards, this paper aims to provide a denoising algorithm which further improves the performance of the WNNM method. For this purpose, we develop a new nonlocal similarity measure by exploiting both pixel intensities and gradients and present a filter that enhances edge information in a patch to improve the performance of low rank approximation. The experimental results on widely used test images demonstrate that the proposed denoising algorithm performs better than other state-of-the-art denoising algorithms in terms of PSNR and SSIM indices as well as visual quality. |
4,042 | Bilateral atraumatic femoral neck fractures resulting from transient osteoporosis of the hip | A woman in her mid-30s presented to the orthopaedic team, unable to mobilise, shortly after her caesarean section. On questioning, she reported 10 weeks of atraumatic right hip pain. A radiograph revealed a displaced right subcapital neck of femur fracture. An MRI confirmed this, as well as identifying a minimally displaced left subcapital neck of femur fracture. She underwent a right total hip replacement and internal fixation of the left hip. A dual energy X-ray absorptiometry (DEXA) scan showed severe osteoporosis, and a diagnosis of transient osteoporosis of the hip was made. She was seen by the bone metabolism team and given calcium and vitamin D medication. Although atraumatic hip fractures are rare in young patients, disproportionate or persisting hip pain in pregnant patients should raise the index of suspicion and prompt further investigation in the form of an MRI. This will allow timely management of hip fractures and improve patient outcomes. |
4,043 | Development of a Linear Piezoelectric Microactuator Inspired by the Hollowing Art | Microactuators have been playing crucial roles in micromachine technologies because of their small sizes and light weights. The piezoelectric actuation is one of the most important driving methods to perform the motion output with miniature structures. The rotary piezoelectric microactuators are relatively mature, whereas the linear ones need to be further developed. Inspired by the hollowing art, a novel linear piezoelectric microactuator with miniature dimensions of 7.4 mm x 7.4 mm x 10 mm is proposed, which is designed to be an integrated hollow structure without a guide rail and can achieve bidirectional standing-wave drive. The bidirectional motions are achieved by the same first-order bending vibrations of two pairs of thin-walled beams, respectively, which are conducive to the consistency of the forward and backward motions indicate that the maximum velocity, resolution, and maximum thrust force achieved in the forward motion are 19.06 mm/s, 0.3 mu m, and 17.45 mN, respectively, whereas those in the backward motion are 16.92 mm/s, 0.45 mu m, and 15.28 mN, respectively. The design inspired by the hollowing art has the potential to be an effective and alternative solution for the development of linear piezoelectric microactuators. |
4,044 | State of the art of advanced solar control devices for buildings | This paper deals with the state of the art of advanced solar control devices for buildings, with the comparative evaluation of solar-control systems and with guidelines for the development of new solar control systems. It includes multifunctional systems with building integrated photovoltaic (BIPV) and/or building integrated solar thermal (BIST) energy conversion. In order to facilitate and to structure the understanding of solar control systems two multidimensional spaces are introduced: the design space and the evaluation space. The design space contains the design parameters which are to be selected by the designer when solar control devices are to be chosen for specific buildings or when new systems are to be developed, such us the color of the slat of a venetian blind or the fraction of holes (direct transmittance) of a fabric for a roller blind. The evaluation space contains the performance parameters or evaluation criteria, which indicate the design's ability to satisfy the functional and aesthetic requirements, such us passive solar gain control or visual comfort. All the design parameters and evaluation criteria are explained in detail in the paper. A chapter with examples of advanced solar control systems completes the overview of the state of the art of solar control systems. (C) 2017 The Author. Published by Elsevier Ltd. |
4,045 | High-Quality Real-Time Video Stabilization Using Trajectory Smoothing and Mesh-Based Warping | Some state-of-the-art video stabilization methods can achieve quite good visual effect, but they always cost a lot of time. On the other hand, current real-time video stabilization methods cannot generate satisfactory results. In this paper, we propose a novel trajectory-based video stabilization method which can generate high-quality results in real time. Our method runs very fast, because many techniques are proposed for acceleration. In the trajectory smoothing step, trajectories are extracted, pre-processed, and smoothed. A video splitting algorithm is proposed for pre-processing, and binomial filtering is used for smoothing. Both of them are simple and fast. In the frame warping step, we calculate a spatially varying warp that is directed by a grid mesh for each frame. Instead of solving time consuming global optimization problems, the transformation matrix of each grid is calculated using nearby trajectories in our method, leading to very high speed. We implement our method and run it on a variety of videos. Experiments show that while the stabilization effect is comparable with state-of-the-art methods, our algorithm can run in real time. |
4,046 | Millimeter-Wave Imaging With Accelerated Super-Resolution Range Migration Algorithm | Millimeter-wave imaging systems are increasingly used in human screening at checkpoints, in linear or multi-input multi-output (MIMO) array modes. Rather than pressing intrinsic system requirements to improve image quality, it seems more economical to appeal to some specific approaches, for example, super-resolution (SR) techniques. In this paper, as a variation of SR, coherence factor (CF) is incorporated in the framework of the range migration algorithm (RMA), termed CF-RMA for short. As a critical part of CF, the double integral in the wavenumber domain is approximated by a single integral in the sense of the point-matching method, resulting in a particular formulation to carry on another independent RMA program. Being computationally efficient, the proposed method is shown to be effective in suppressing sidelobes and background noise. The resolution (as gauged by the width of the main lobe of the point spread function) is enhanced as well. A structural similarity (SSIM) index is employed to quantify the image quality enhancement with respect to state-of-the-art SR approaches. In terms of computation load, the new approach is shown to be much more efficient than state-of-the-art SR approaches. |
4,047 | Techno-economic comparison of membrane distillation and MVC in a zero liquid discharge application | Membrane distillation (MD) is a thermally driven membrane process for the separation of vapour from a liquid stream through a hydrophobic, microporous membrane. However, a commercial breakthrough on a large scale has not been achieved so far. Specific developments on MD technology are required to adapt the technology for applications in which its properties can potentially outshine state of the art technologies such as standard evaporation. In order to drive these developments in a focused manner, firstly it must be shown that MD can be economically attractive in comparison to state of the art systems. Thus, this work presents a technological design and economic analysis for AGMD and v-AGMD for application in a zero liquid discharge (ZLD) process chain and compares it to the costs of mechanical vapour compression (MVC) for the same application. The results show that MD can potentially be similar to 40% more cost effective than MVC for a system capacity of 100 m(3)/day feed water, and up to similar to 75% more cost effective if the MD is driven with free waste heat. |
4,048 | Litter Detection with Deep Learning: A Comparative Study | Pollution in the form of litter in the natural environment is one of the great challenges of our times. Automated litter detection can help assess waste occurrences in the environment. Different machine learning solutions have been explored to develop litter detection tools, thereby supporting research, citizen science, and volunteer clean-up initiatives. However, to the best of our knowledge, no work has investigated the performance of state-of-the-art deep learning object detection approaches in the context of litter detection. In particular, no studies have focused on the assessment of those methods aiming their use in devices with low processing capabilities, e.g., mobile phones, typically employed in citizen science activities. In this paper, we fill this literature gap. We performed a comparative study involving state-of-the-art CNN architectures (e.g., Faster RCNN, Mask-RCNN, EfficientDet, RetinaNet and YOLO-v5), two litter image datasets and a smartphone. We also introduce a new dataset for litter detection, named PlastOPol, composed of 2418 images and 5300 annotations. The experimental results demonstrate that object detectors based on the YOLO family are promising for the construction of litter detection solutions, with superior performance in terms of detection accuracy, processing time, and memory footprint. |
4,049 | Medial Spheres for Shape Approximation | We study the problem of approximating a 3D solid with a union of overlapping spheres. In comparison with a state-of-the-art approach, our method offers more than an order of magnitude speedup and achieves a tighter approximation in terms of volume difference with the original solid while using fewer spheres. The spheres generated by our method are internal and tangent to the solid's boundary, which permits an exact error analysis, fast updates under local feature size preserving deformation, and conservative dilation. We show that our dilated spheres offer superior time and error performance in approximate separation distance tests than the state-of-the-art method for sphere set approximation for the class of (sigma, theta)-fat solids. We envision that our sphere-based approximation will also prove useful for a range of other applications, including shape matching and shape segmentation. |
4,050 | Characterization of the Catalytic and Nucleotide Binding Properties of the α-Kinase Domain of Dictyostelium Myosin-II Heavy Chain Kinase A | The α-kinases are a widely expressed family of serine/threonine protein kinases that exhibit no sequence identity with conventional eukaryotic protein kinases. In this report, we provide new information on the catalytic properties of the α-kinase domain of Dictyostelium myosin-II heavy chain kinase-A (termed A-CAT). Crystallization of A-CAT in the presence of MgATP yielded structures with AMP or adenosine in the catalytic cleft together with a phosphorylated Asp-766 residue. The results show that the β- and α-phosphoryl groups are transferred either directly or indirectly to the catalytically essential Asp-766. Biochemical assays confirmed that A-CAT hydrolyzed ATP, ADP, and AMP with kcat values of 1.9, 0.6, and 0.32 min(-1), respectively, and showed that A-CAT can use ADP to phosphorylate peptides and proteins. Binding assays using fluorescent 2'/3'-O-(N-methylanthraniloyl) analogs of ATP and ADP yielded Kd values for ATP, ADP, AMP, and adenosine of 20 ± 3, 60 ± 20, 160 ± 60, and 45 ± 15 μM, respectively. Site-directed mutagenesis showed that Glu-713, Leu-716, and Lys-645, all of which interact with the adenine base, were critical for nucleotide binding. Mutation of the highly conserved Gln-758, which chelates a nucleotide-associated Mg(2+) ion, eliminated catalytic activity, whereas loss of the highly conserved Lys-722 and Arg-592 decreased kcat values for kinase and ATPase activities by 3-6-fold. Mutation of Asp-663 impaired kinase activity to a much greater extent than ATPase, indicating a specific role in peptide substrate binding, whereas mutation of Gln-768 doubled ATPase activity, suggesting that it may act to exclude water from the active site. |
4,051 | A Large-Scale Database and a CNN Model for Attention-Based Glaucoma Detection | Glaucoma is one of the leading causes of irreversible vision loss. Many approaches have recently been proposed for automatic glaucoma detection based on fundus images. However, none of the existing approaches can efficiently remove high redundancy in fundus images for glaucoma detection, which may reduce the reliability and accuracy of glaucoma detection. To avoid this disadvantage, this paper proposes an attention-based convolutional neural network (CNN) for glaucoma detection, called AG-CNN. Specifically, we first establish a large-scale attention-based glaucoma (LAG) database, which includes 11 760 fundus images labeled as either positive glaucoma (4878) or negative glaucoma (6882). Among the 11 760 fundus images, the attention maps of 5824 images are further obtained from ophthalmologists through a simulated eye-tracking experiment. Then, a new structure of AG-CNN is designed, including an attention prediction subnet, a pathological area localization subnet, and a glaucoma classification subnet. The attention maps are predicted in the attention prediction subnet to highlight the salient regions for glaucoma detection, under a weakly supervised training manner. In contrast to other attention-based CNN methods, the features are also visualized as the localized pathological area, which are further added in our AG-CNN structure to enhance the glaucoma detection performance. Finally, the experiment results from testing over our LAG database and another public glaucoma database show that the proposed AG-CNN approach significantly advances the state-of-the-art in glaucoma detection. |
4,052 | A Krasnoselskii-Mann Algorithm With an Improved EM Preconditioner for PET Image Reconstruction | This paper presents a preconditioned Krasnoselskii-Mann (KM) algorithm with an improved EM preconditioner (IEM-PKMA) for higher-order total variation (HOTV) regularized positron emission tomography (PET) image reconstruction. The PET reconstruction problem can be formulated as a three-term convex optimization model consisting of the Kullback-Leibler (KL) fidelity term, a nonsmooth penalty term, and a nonnegative constraint term which is also nonsmooth. We develop an efficient KM algorithm for solving this optimization problem based on a fixed-point characterization of its solution, with a preconditioner and a momentum technique for accelerating convergence. By combining the EM precondtioner, a thresholding, and a good inexpensive estimate of the solution, we propose an improved EM preconditioner that can not only accelerate convergence but also avoid the reconstructed image being "stuck at zero." Numerical results in this paper show that the proposed IEM-PKMA outperforms existing state-of-the-art algorithms including, the optimization transfer descent algorithm and the preconditioned L-BFGS-B algorithm for the differentiable smoothed anisotropic total variation regularized model, the preconditioned alternating projection algorithm, and the alternating direction method of multipliers for the nondifferentiable HOTV regularized model. Encouraging initial experiments using clinical data are presented. |
4,053 | Local oppugnant color space extrema patterns for content based natural and texture image retrieval | This paper proposes a novel feature descriptor called local oppugnant color space extrema patterns (LOCSEP) for image indexing retrieval. The existing directional local extrema pattern (DLEP) extracts the directional edge information based on local extrema in 0 degrees, 45 degrees, 90 degrees, and 135 degrees directions in an image. The proposed method integrates the concepts of color and texture features. First, the color image is converted into RGB (red, green and blue) and HSV (hue, saturation and value) color spaces. Then oppugnant color spaces, RV, GV, BV are used for the extract of oppugnant DLEP features (LOCSEP). The performance of the proposed method is tested by conducting two experiments on benchmark databases viz. Corel-1K and MIT VisTex databases. The performance of the proposed method is compared with the state-of-the-art methods for image retrieval and face recognition applications in terms of average retrieval precision (ARP) and average retrieval rate (ARR). The results after being investigated show a significant improvement in terms of their evaluation measures as compared to state-of-the-art methods on respective databases. (C) 2014 Elsevier GmbH. All rights reserved. |
4,054 | Transfer Recurrent Feature Learning for Endomicroscopy Image Recognition | Probe-based confocal laser endomicroscopy (pCLE) is an emerging tool for epithelial cancer diagnosis, which enables in-vivo microscopic imaging during endoscopic procedures and facilitates the development of automatic recognition algorithms to identify the status of tissues. In this paper, we propose a transfer recurrent feature learning framework for classification tasks on pCLE videos. At the first stage, the discriminative feature of single pCLE frame is learned via generative adversarial networks based on both pCLE and histology modalities. At the second stage, we use recurrent neural networks to handle the varying length and irregular shape of pCLE mosaics taking the frame-based features as input. The experiments on real pCLE data sets demonstrate that our approach outperforms, with statistical significance, state-of-the-art approaches. A binary classification accuracy of 84.1% has been achieved. |
4,055 | Dual Attention Multi-Instance Deep Learning for Alzheimer's Disease Diagnosis With Structural MRI | Structural magnetic resonance imaging (sMRI) is widely used for the brain neurological disease diagnosis, which could reflect the variations of brain. However, due to the local brain atrophy, only a few regions in sMRI scans have obvious structural changes, which are highly correlative with pathological features. Hence, the key challenge of sMRI-based brain disease diagnosis is to enhance the identification of discriminative features. To address this issue, we propose a dual attention multi-instance deep learning network (DA-MIDL) for the early diagnosis of Alzheimer's disease (AD) and its prodromal stage mild cognitive impairment (MCI). Specifically, DA-MIDL consists of three primary components: 1) the Patch-Nets with spatial attention blocks for extracting discriminative features within each sMRI patch whilst enhancing the features of abnormally changed micro-structures in the cerebrum, 2) an attention multi-instance learning (MIL) pooling operation for balancing the relative contribution of each patch and yield a global different weighted representation for the whole brain structure, and 3) an attention-aware global classifier for further learning the integral features and making the AD-related classification decisions. Our proposed DA-MIDL model is evaluated on the baseline sMRI scans of 1689 subjects from two independent datasets (i.e., ADNI and AIBL). The experimental results show that our DA-MIDL model can identify discriminative pathological locations and achieve better classification performance in terms of accuracy and generalizability, compared with several state-of-the-art methods. |
4,056 | HRPose: Real-Time High-Resolution 6D Pose Estimation Network Using Knowledge Distillation | Real-time six degrees-of-freedom (6D) object pose estimation is essential for many real-world applications, such as robotic grasping and augmented reality. To achieve an accurate object pose estimation from RGB images in real-time, we propose an effective and lightweight model, namely high-resolution 6D pose estimation network (HRPose). We adopt the efficient and small HRNetV2-W18 as a feature extractor to reduce computational burdens while generating accurate 6D poses. With only 33% of the model size and lower computational costs, our HRPose achieves comparable performance compared with state-of-the-art models. Moreover, by transferring knowledge from a large model to our proposed HRPose through output and feature-similarity distillations, the performance of our HRPose is improved in effectiveness and efficiency. Numerical experiments on the widely-used benchmark LINEMOD demonstrate the superiority of our proposed HRPose against state-of-the-art methods. |
4,057 | [Second opinions and reference pathology] | Second opinions in pathology require expert knowledge for diagnosis in difficult cases and in Germany have a tradition that has grown into a network between primarily diagnostic care institutions and university-associated institutes of pathology that are active in research. The term reference pathology is not a designation for a class of institutes for pathology but rather indicates a function within prospective clinical trials with defined endpoints and a central pathology, which derives expert knowledge from this function. The thus generated collection of samples and expertise enable diagnostic support in difficult cases. Furthermore, research based on this tissue material might lead to the establishment of novel biomarkers and methods, which when transferred back for local application will enhance the overall diagnostic validity of pathological tissue analysis. Thus, for all institutes participating in the network second opinion and reference pathology provide considerable benefit. |
4,058 | Characterization and shelf stability of sweetened condensed milk formulated with different sucrose substitutes during storage | Sweetened condensed milk (SCM) is a value-added milk product with extended shelf life and high levels of nutrition. The high level of sucrose may lead to health problems. Many studies have focused on the reduction of sucrose but seldomly on different combination of sugar substitutes. This study aims to find an ideal sucrose substitution through physiochemical, microbiological and sensory properties of SCM under different storage times. The results demonstrated that substitution with 20% trehalose, 5% lactulose and 15% erythritol resulted in similar sensory and color as control group. The volatile flavor analysis showed that substitution with 30% trehalose, 5% lactulose and 5% polyols was the most similar and hexanoic acid was the symbolistic flavor. Sucrose replacement increased the antibacterial effect and Staphylococcus, Penicillium, Apiotrichum and Candida were widely present. Substitution with 30% trehalose, 5% lactulose and 5% polyols resulted in the most similar water activity, texture, aroma and microbial diversity. |
4,059 | Automatic Segmentation and Quantitative Analysis of the Articular Cartilages From Magnetic Resonance Images of the Knee | In this paper, we present a segmentation scheme that automatically and accurately segments all the cartilages from magnetic resonance (MR) images of nonpathological knees. Our scheme involves the automatic segmentation of the bones using a three-dimensional active shape model, the extraction of the expected bone-cartilage interface (BCI), and cartilage segmentation from the BCI using a deformable model that utilizes localization, patient specific tissue estimation and a model of the thickness variation. The accuracy of this scheme was experimentally validated using leave one out experiments on a database of fat suppressed spoiled gradient recall MR images. The scheme was compared to three state of the art approaches, tissue classification, a modified semi-automatic watershed algorithm and nonrigid registration (B-spline based free form deformation). Our scheme obtained an average Dice similarity coefficient (DSC) of (0.83, 0.83, 0.85) for the (patellar, tibial, femoral) cartilages, while (0.82, 0.81, 0.86) was obtained with a tissue classifier and (0.73, 0.79, 0.76) was obtained with nonrigid registration. The average DSC obtained for all the cartilages using a semi-automatic watershed algorithm (0.90) was slightly higher than our approach (0.89), however unlike this approach we segment each cartilage as a separate object. The effectiveness of our approach for quantitative analysis was evaluated using volume and thickness measures with a median volume difference error of (5.92, 4.65, 5.69) and absolute Laplacian thickness difference of (0.13, 0.24, 0.12) mm. |
4,060 | Building Extraction from Remote Sensing Images with Sparse Token Transformers | Deep learning methods have achieved considerable progress in remote sensing image building extraction. Most building extraction methods are based on Convolutional Neural Networks (CNN). Recently, vision transformers have provided a better perspective for modeling long-range context in images, but usually suffer from high computational complexity and memory usage. In this paper, we explored the potential of using transformers for efficient building extraction. We design an efficient dual-pathway transformer structure that learns the long-term dependency of tokens in both their spatial and channel dimensions and achieves state-of-the-art accuracy on benchmark building extraction datasets. Since single buildings in remote sensing images usually only occupy a very small part of the image pixels, we represent buildings as a set of "sparse " feature vectors in their feature space by introducing a new module called "sparse token sampler ". With such a design, the computational complexity in transformers can be greatly reduced over an order of magnitude. We refer to our method as Sparse Token Transformers (STT). Experiments conducted on the Wuhan University Aerial Building Dataset (WHU) and the Inria Aerial Image Labeling Dataset (INRIA) suggest the effectiveness and efficiency of our method. Compared with some widely used segmentation methods and some state-of-the-art building extraction methods, STT has achieved the best performance with low time cost. |
4,061 | Insights into the mapping of green synthesis conditions for ZnO nanoparticles and their toxicokinetics | Research on ZnO nanoparticles (NPs) has broad medical applications. However, the green synthesis of ZnO NPs involves a wide range of properties requiring optimization. ZnO NPs show toxicity at lower doses. This toxicity is a function of NP properties and pharmacokinetics. Moreover, NP toxicity and pharmacokinetics are affected by the species type and age of the animals tested. Physiologically based pharmacokinetic (PBPK) modeling offers a mechanistic platform to scrutinize the colligative effect of the interplay between these factors, which reduces the need for in vivo studies. This review provides a guide to choosing green synthesis conditions that result in minimal toxicity using a mechanistic tool, namely PBPK modeling. |
4,062 | Identification of antigens recognized by salivary IgA using microbial protein microarrays | Secretory IgA plays an important role in the mucosal immune system for protection against pathogens. However, the antigens recognized by these antibodies have only been partially studied. We comprehensively investigated the antigens bound by salivary IgA in healthy adults using microbial protein microarrays. This confirmed that saliva contained IgA antibodies that bind to a variety of pathogenic microorganisms, including spike proteins of severe acute respiratory syndrome coronavirus 2, severe acute respiratory syndrome coronavirus, Middle East respiratory syndrome coronavirus, and other human coronavirus species. Also, many subtypes and strains of influenza virus were bound, regardless of the seasonal or vaccine strains. Salivary IgA also bound many serogroups and serovars of Escherichia coli and Salmonella. Taken together, these findings suggest that salivary IgA, which exhibits broad reactivity, is likely an essential element of the mucosal immune system at the forefront of defense against infection. |
4,063 | SNS-CF: Siamese Network with Spatially Semantic Correlation Features for Object Tracking | Recent advances in object tracking based on deep Siamese networks shifted the attention away from correlation filters. However, the Siamese network alone does not have as high accuracy as state-of-the-art correlation filter-based trackers, whereas correlation filter-based trackers alone have a frame update problem. In this paper, we present a Siamese network with spatially semantic correlation features (SNS-CF) for accurate, robust object tracking. To deal with various types of features spread in many regions of the input image frame, the proposed SNS-CF consists of-(1) a Siamese feature extractor, (2) a spatially semantic feature extractor, and (3) an adaptive correlation filter. To the best of authors knowledge, the proposed SNS-CF is the first attempt to fuse the Siamese network and the correlation filter to provide high frame rate, real-time visual tracking with a favorable tracking performance to the state-of-the-art methods in multiple benchmarks. |
4,064 | Prenatal heroin exposure alters brain morphology and connectivity in adolescent mice | The United States is experiencing a dramatic increase in maternal opioid misuse and, consequently, the number of individuals exposed to opioids in utero. Prenatal opioid exposure has both acute and long-lasting effects on health and wellbeing. Effects on the brain, often identified at school age, manifest as cognitive impairment, attention deficit, and reduced scholastic achievement. The neurobiological basis for these effects is poorly understood. Here, we examine how in utero exposure to heroin affects brain development into early adolescence in a mouse model. Pregnant C57BL/6J mice received escalating doses of heroin twice daily on gestational days 4-18. The brains of offspring were assessed on postnatal day 28 using 9.4 T diffusion MRI of postmortem specimens at 36 μm resolution. Whole-brain volumes and the volumes of 166 bilateral regions were compared between heroin-exposed and control offspring. We identified a reduction in whole-brain volume in heroin-exposed offspring and heroin-associated volume changes in 29 regions after standardizing for whole-brain volume. Regions with bilaterally reduced standardized volumes in heroin-exposed offspring relative to controls include the ectorhinal and insular cortices. Regions with bilaterally increased standardized volumes in heroin-exposed offspring relative to controls include the periaqueductal gray, septal region, striatum, and hypothalamus. Leveraging microscopic resolution diffusion tensor imaging and precise regional parcellation, we generated whole-brain structural MRI diffusion connectomes. Using a dimension reduction approach with multivariate analysis of variance to assess group differences in the connectome, we found that in utero heroin exposure altered structure-based connectivity of the left septal region and the region that acts as a hub for limbic regulatory actions. Consistent with clinical evidence, our findings suggest that prenatal opioid exposure may have effects on brain morphology, connectivity, and, consequently, function that persist into adolescence. This work expands our understanding of the risks associated with opioid misuse during pregnancy and identifies biomarkers that may facilitate diagnosis and treatment. |
4,065 | Rapidly Photocurable Solid-State Poly(ionic liquid) Ionogels For Thermally Robust and Flexible Electrochromic Devices | Formation of ionogels through in situ polymerization can effectively improve electrolyte processability; however, the curing process has been slow and oxygen-sensitive. Considering the low oxygen solubility of poly(ionic liquid)s (PILs), in situ polymerized ionogels are designed to realize excellent electrolytes. Herein, two in situ polymerized ionogels (PIL A & PIL B) are formulated, and they can be rapidly photocured within a minute. The ionogels are highly transparent, stretchable, and exhibit excellent physicochemical stability, including thermal, electrochemical, and air stability, allowing them to perform in various conditions. Benefitting from these properties, two high-performance electrochromic devices (ECDs) are assembled, with iron-centered coordination polymer (FeCP) and tungsten oxide (P-WO3 ) electrochromic materials, achieving high color contrast (45.2% and 56.4%), fast response time (1.5/1.9 and 1.7/6.4 s), and excellent cycling endurance (>90% retention over 3000 cycles). Attributed to the thermal robustness of the ionogels, the ECDs can also be operated over a wide temperature range (-20 to 100 °C). With the use of deformable substrates (e.g., ultrathin ITO glass), curved electrochromic eye protector and flexible electrochromic displays are realized, highlighting their potential use in futuristic wearables. |
4,066 | A case of left foot drop as initial symptom of granulomatosis with polyangiitis: Triggered by COVID-19 disease? | In Granulomatosis with polyangiitis (GPA), involvement of the peripheral nervous system is frequent but its occurrence as an initial presentation is unusual. This case highlights the importance of this occurrence to permit an early diagnosis. Moreover, GPA started after a coronavirus disease 2019 infection and could have been induced by this. |
4,067 | Unregulated LDL cholesterol uptake is detrimental to breast cancer cells | Tumor uptake of exogenous cholesterol has been associated with the proliferation of various cancers. Previously, we and others have shown that hypercholesterolemia promotes tumor growth and silencing of the LDL receptor (LDLR) in high LDLR-expressing tumors reduces growth. To advance understanding of how LDL uptake promotes tumor growth, LDLR expression was amplified in breast cancer cell lines with endogenously low LDLR expression. Murine (Mvt1) and human (MDA-MB-468) breast cancer cell lines were transduced to overexpress human LDLR (LDLROE). Successful transduction was confirmed by RNA and protein analysis. Fluorescence-labeled LDL uptake was increased in both Mvt1 and MDA-MD-468 LDLROE cells. The expression of the cholesterol-metabolizing genes, ABCA1 and ABCG1, was increased, while HMGCR was decreased in the MDA-MB-468 LDLROE cells. In contrast, Mvt1 LDLROE cells showed no differences in Abca1 and Abcg1 expression and increased Hmgcr expression. Using a Seahorse analyzer, Mvt1 LDLROE cells showed increased respiration (ATP-linked and maximal) relative to controls, while no statistically significant changes in respiration in MDA-MB-468 LDLROE cells were observed. Growth of LDLROE cells was reduced in culture and in hypercholesterolemic mice by two-fold. However, the expression of proliferation-associated markers (Ki67, PCNA and BrdU-label incorporation) was not decreased in the Mvt1 LDLROE tumors and cells. Caspase-3 cleavage, which is associated with apoptosis, was increased in both the Mvt1 and MDA-MB-468 LDLROE cells relative to controls, with the Mvt1 LDLROE cells also showing decreased phosphorylation of p44/42MAPK. Taken together, our work suggests that while additional LDL can promote tumor growth, unregulated and prolonged LDL uptake is detrimental. |
4,068 | Magnetic resonance imaging of rhino-orbito-cerebral mucormycosis: a pictorial review | Rhino-orbito-cerebral mucormycosis is a potentially fatal disease requiring early magnetic resonance imaging (MRI) for disease evaluation and timely detection of intracranial complications. Angio-invasive nature leading to necrosis and infarction is the hallmark of mucormycosis. The disease follows a fulminant course extending from the paranasal sinuses to involve the orbit, deep neck spaces, skull base, facial bones, and intracranial compartment. Loss of vision either due to direct extension into the orbit or optic nerve infarction adds to disease morbidity. Prompt MRI using dedicated sequences can help in assessing the exact disease extent including early osseous and intracranial changes, which aid in precise disease management. |
4,069 | Improving M-SBL for Joint Sparse Recovery Using a Subspace Penalty | A multiple measurement vector problem (MMV) is a generalization of the compressed sensing problem that addresses the recovery of a set of jointly sparse signal vectors. One of the important contributions of this paper is to show that the seemingly least related state-of-the-art MMV joint sparse recovery algorithms-the M-SBL (multiple sparse Bayesian learning) and subspace-based hybrid greedy algorithms-have a very important link. More specifically, we show that replacing the (.) term in the M-SBL by a rank surrogate that exploits the spark reduction property discovered in the subspace-based joint sparse recovery algorithms provides significant improvements. In particular, if we use the Schatten-quasi-norm as the corresponding rank surrogate, the global minimizer of the cost function in the proposed algorithm becomes identical to the true solution as. Furthermore, under regularity conditions, we show that convergence to a local minimizer is guaranteed using an alternating minimization algorithm that has closed form expressions for each of the minimization steps, which are convex. Numerical simulations under a variety of scenarios in terms of SNR and the condition number of the signal amplitude matrix show that the proposed algorithm consistently outperformed the M-SBL and other state-of-the art algorithms. |
4,070 | Interface Trap Density Metrology of State-of-the-Art Undoped Si n-FinFETs | The presence of interface states at the MOS interface is a well-known cause of device degradation. This is particularly true for ultrascaled FinFET geometries where the presence of a few traps can strongly influence the device behavior. Typical methods for interface trap density (D-it) measurements are not performed on ultimate devices but on custom-designed structures. We present the first set of methods that allow direct estimation of D-it in state-of-the-art FinFETs, addressing a critical industry need. |
4,071 | Maladaptive Laterality in Cortical Networks Related to Social Communication in Autism Spectrum Disorder | Neuroimaging studies of individuals with autism spectrum disorders (ASDs) consistently find an aberrant pattern of reduced laterality in brain networks that support functions related to social communication and language. However, it is unclear how the underlying functional organization of these brain networks is altered in ASD individuals. We tested four models of reduced laterality in a social communication network in 70 ASD individuals (14 females) and a control group of the same number of tightly matched typically developing (TD) individuals (19 females) using high-quality resting-state fMRI data and a method of measuring patterns of functional laterality across the brain. We found that a functionally defined social communication network exhibited the typical pattern of left laterality in both groups, whereas there was a significant increase in within- relative to across-hemisphere connectivity of homotopic regions in the right hemisphere in ASD individuals. Furthermore, greater within- relative to across-hemisphere connectivity in the left hemisphere was positively correlated with a measure of verbal ability in both groups, whereas greater within- relative to across-hemisphere connectivity in the right hemisphere in ASD, but not TD, individuals was negatively correlated with the same verbal measure. Crucially, these differences in patterns of laterality were not found in two other functional networks and were specifically correlated to a measure of verbal ability but not metrics of other core components of the ASD phenotype. These results suggest that previous reports of reduced laterality in social communication regions in ASD is because of the two hemispheres functioning more independently than seen in TD individuals, with the atypical right-hemisphere network component being maladaptive.SIGNIFICANCE STATEMENT A consistent neuroimaging finding in individuals with ASD is an aberrant pattern of reduced laterality of the brain networks that support functions related to social communication and language. We tested four models of reduced laterality in a social communication network in ASD individuals and a TD control group using high-quality resting-state fMRI data. Our results suggest that reduced laterality of social communication regions in ASD may be because of the two hemispheres functioning more independently than seen in TD individuals, with atypically greater within- than across-hemisphere connectivity in the right hemisphere being maladaptive. |
4,072 | SBERT-WK: A Sentence Embedding Method by Dissecting BERT-Based Word Models | Sentence embedding is an important research topic in natural language processing (NLP) since it can transfer knowledge to downstream tasks. Meanwhile, a contextualized word representation, called BERT, achieves the state-of-the-art performance in quite a few NLP tasks. Yet, it is an open problem to generate a high quality sentence representation from BERT-based word models. It was shown in previous study that different layers of BERT capture different linguistic properties. This allows us to fuse information across layers to find better sentence representations. In this work, we study the layer-wise pattern of the word representation of deep contextualized models. Then, we propose a new sentence embedding method by dissecting BERT-based word models through geometric analysis of the space spanned by the word representation. It is called the SBERT-WK method. No further training is required in SBERT-WK. We evaluate SBERT-WK on semantic textual similarity and downstream supervised tasks. Furthermore, ten sentence-level probing tasks are presented for detailed linguistic analysis. Experiments show that SBERT-WK achieves the state-of-the-art performance. Our codes are publicly available. |
4,073 | Museum Moving to Inpatients: Le Louvre a l'Hopital | Anxiety and depressive symptoms are common in hospitalized patients. Arts and cultural programs were reported to enhance their quality of life. The Le Louvre a l'hopital study presents a new approach in which the museum moves to the hospital by displaying and discussing artworks with patients interactively. Over one year, four large statues were disposed in the hospital gardens, 30 reprints of large painting were exhibited in the hospital hall, dining rooms, and circulations areas. A total of 83 small-group guided art discussions (90 min) were organized, which 451 patients attended. The 200 small-size reproductions of paintings placed in the patients' rooms were chosen based on their individual preferences. Decreased anxiety after the art sessions was reported by 160 of 201 patients (79.6%). Out of 451 patients, 406 (90%) said the art program had met their expectations, and 372 (82.4%) wished to continue the experience with caregivers (162 paramedics trained for art activity during 66 workshops). In conclusion, moving the museum to the hospital constitutes a valuable way to provide art activities for inpatients in large numbers, which may reduce hospital-related anxiety in many instances. |
4,074 | Making Aqueously Processed LiNi0.5Mn0.3Co0.2O2-Based Electrodes Competitive in Performance: Tailoring Distribution and Interconnection of Active and Inactive Electrode Materials through Paste Surfactants | Enabling aqueous processing of positive active materials to replace toxicologically critical N-methyl-2-pyrrolidone could significantly reduce the ecologic and economic footprint of lithium ion battery production. Processing additives are key to elevate the performance of aqueously processed electrodes beyond the state of the art. A mostly neglected factor during aqueous processing is electrostatic repulsion of active/inactive materials due to their zeta potentials, which can be compensated for by applying optimized amounts of surfactants like hexadecyltrimethylammonium bromide. The notably improved distribution and interconnection of active/inactive materials lead to superior rate capability and similar capacity retention during long-term cycling compared to state-of-the-art processing. |
4,075 | Mapping the Binding Energy of Layered Crystals to Macroscopic Observables | Van der Waals (vdW) integration of two dimensional (2D) crystals into functional heterostructures emerges as a powerful tool to design new materials with fine-tuned physical properties at an unprecedented precision. The intermolecular forces governing the assembly of vdW heterostructures are investigated by first-principles models, yet translating the outcome of these models to macroscopic observables in layered crystals is missing. Establishing this connection is, therefore, crucial for ultimately designing advanced materials of choice-tailoring the composition to functional device properties. Herein, components from both vdW and non-vdW forces are integrated to build a comprehensive framework that can quantitatively describe the dynamics of these forces in action. Specifically, it is shown that the optical band gap of layered crystals possesses a peculiar ionic character that works as a quantitative indicator of non-vdW forces. Using these two components, it is then described why only a narrow range of exfoliation energies for this class of materials is observed. These findings unlock the microscopic origin of universal binding energy in layered crystals and provide a general protocol to identify and synthesize new crystals to regulate vdW coupling in the next generation of heterostructures. |
4,076 | Efficient low-order system identification from low-quality step response data with rank-constrained optimization | In the presence of low-quality industrial process data, generic step response identification methods typically show unsatisfactory performance and heavily rely on manual intervention of technical personnel. This erects obvious obstacles for the advancement of intelligent manufacturing in process industries. To address these challenges, we propose a novel rank-constrained optimization approach to low-order system identification from step response data, which yields much more accurate and robust estimates than existing modeling methods. By exploiting the inherent low-rank structure of the Hankel matrix of ideal step response, parameters of a low-order process can be accurately recovered by solving a rank-constrained program, which effectively bypasses the two-step procedure in some state-of-the-art algorithms involving significant error accumulation. The alternating direction method of multipliers is adopted to effectively solve the nonconvex error minimization problem and circumvent poor local optima. Case studies on both numerical examples and industrial datasets demonstrate that, the proposed method not only gives much better modeling accuracy, but also secures reliable and robust estimates even for raw low-quality industrial data. This is particularly helpful for automated execution of the identification routine without human intervention, with success percentage over 99% that is remarkably higher than the state-of-the-art. |
4,077 | Role of the Chemical Environment beyond the Coordination Site: Structural Insight into Fe(III) Protoporphyrin Binding to Cysteine-Based Heme-Regulatory Protein Motifs | The importance of heme as a transient regulatory molecule has become a major focus in biochemical research. However, detailed information about the molecular basis of transient heme-protein interactions is still missing. We report an in-depth structural analysis of Fe(III) heme-peptide complexes by a combination of UV/Vis, resonance Raman, and 2D-NMR spectroscopic methods. The experiments reveal insights both into the coordination to the central iron ion and into the spatial arrangement of the amino acid sequences interacting with protoporphyrin IX. Cysteine-based peptides display different heme-binding behavior as a result of the existence of ordered, partially ordered, and disordered conformations in the heme-unbound state. Thus, the heme-binding mode is clearly the consequence of the nature and flexibility of the residues surrounding the iron ion coordinating cysteine. Our analysis reveals scenarios for transient binding of heme to heme-regulatory motifs in proteins and demonstrates that a thorough structural analysis is required to unravel how heme alters the structure and function of a particular protein. |
4,078 | Science-fiction literature as inspiration for social theorizing within sustainability research | As commonly accepted, the stakes of sustainable development (SD) are altogether highly serious, complex, and diverse, spanning from changing living standards to the very future of mankind. Although it has long been argued that such complexity warrants radical change in the way "good" knowledge is conceived of and produced, it appears that much of sustainability research including its grounding in social sciences has yet to extend beyond the institutionalized precepts of natural science with regard to validity and credibility. In this context, this paper argues that crucial insights can be developed by opening social sciences' theorizing process to undervalued forms of knowledge including art in general, and science-fiction literature in particular. To support this argument, current non-scientific productions of knowledge are reviewed in light of alternate conceptions of epistemological value. The potential of science fiction as thought experiments and inspiration for both problematizing and theory building in the social sciences is explored. In particular, certain science-fiction texts are thoroughly examined to illustrate how current problems pertaining to firm theories and management practice may be "discovered" (or made visible) only through science-fiction hindsight. Ultimately, the research shows how this hidden potential may be employed by social research to radically stimulate theoretical imagination and benefit sustainability research. (C) 2017 Elsevier Ltd. All rights reserved. |
4,079 | Energy management using non-intrusive load monitoring techniques - State-of-the-art and future research directions | In recent years, the development of smart sustainable cities has become the primary focus among urban planners and policy makers to make responsible use of resources, conserve the environment and improve the well-being of the society. Energy management is an integral part of the smart sustainable cities development programme which involves conscious and efficient use of available energy resources towards attaining sustainability and self-reliance on energy systems. Building sector is one of the key sectors that utilize more energy. Therefore, efforts are being made to monitor and manage energy consumption effectively in residential and commercial buildings. In recent years, non-intrusive load monitoring (NILM) technique has become a popular and emerging approach to monitor events (on/off) and energy consumption of appliances/electrical utilities in buildings using single energy meter. The information about the energy consumption at the appliance level would help consumers to understand their appliance usage behavior and take necessary steps for reducing energy consumption. In this paper, we present the comprehensive review of state-of-the-art algorithms that have been explored by the researchers towards developing an accurate NILM system for effective energy management. Finally, potential applications of NILM in different domains and its future research directions are discussed. |
4,080 | An Efficient Protocol of Queries for Large and Small Categories in RFID Systems | One of the most important problems for categorized radio-frequency identification systems is to find large categories and small categories. In this article, we propose a protocol that can find the large categories and the small categories quickly. The protocol uses multiple hash pairs to allocate as many tag categories as possible to distinct slots to estimate the sizes of the tag categories. Specifically, we optimize the parameters by minimizing the execution time of the protocol. Extensive simulation results demonstrate that the proposed protocol is superior to the state-of-the-art protocols. Particularly, when the length of single-one-geometric (SOG) string is 32 b, it reduces nearly 24% of the required execution time compared with the Top-k protocol and reduces 77% of the required execution time compared with the ART protocol. |
4,081 | Accurate Lungs Segmentation on CT Chest Images by Adaptive Appearance-Guided Shape Modeling | To accurately segment pathological and healthy lungs for reliable computer-aided disease diagnostics, a stack of chest CT scans is modeled as a sample of a spatially inhomogeneous joint 3D Markov-Gibbs random field (MGRF) of voxel-wise lung and chest CT image signals (intensities). The proposed learnable MGRF integrates two visual appearance sub-models with an adaptive lung shape submodel. The first-order appearance submodel accounts for both the original CT image and its Gaussian scale space (GSS) filtered version to specify local and global signal properties, respectively. Each empirical marginal probability distribution of signals is closely approximated with a linear combination of discrete Gaussians (LCDG), containing two positive dominant and multiple sign-alternate subordinate DGs. The approximation is separated into two LCDGs to describe individually the lungs and their background, i.e., all other chest tissues. The second-order appearance submodel quantifies conditional pairwise intensity dependencies in the nearest voxel 26-neighborhood in both the original and GSS-filtered images. The shape submodel is built for a set of training data and is adapted during segmentation using both the lung and chest appearances. The accuracy of the proposed segmentation framework is quantitatively assessed using two public databases (ISBI VES-SEL12 challenge and MICCAI LOLA11 challenge) and our own database with, respectively, 20, 55, and 30 CT images of various lung pathologies acquired with different scanners and protocols. Quantitative assessment of our framework in terms of Dice similarity coefficients, 95-percentile bidirectional Hausdorff distances, and percentage volume differences confirms the high accuracy of our model on both our database (98.4(+/- 1.0%,) 2.2(+/- 1.0) mm, 0.42(+/- 0.10)%) and the VESSEL12 database (99.0(+/- 0.5)%, 2.1(+/- 1.6) mm, 0.39(+/- 0.20)%), respectively. Similarly, the accuracy of our approach is further verified via a blind evaluation by the organizers of the LOLA11 competition, where an average overlap of 98.0% with the expert's segmentation is yielded on all 55 subjects with our framework being ranked first among all the state-of-the-art techniques compared. |
4,082 | H-Patches: A Benchmark and Evaluation of Handcrafted and Learned Local Descriptors | In this paper, a novel benchmark is introduced for evaluating local image descriptors. We demonstrate limitations of the commonly used datasets and evaluation protocols, that lead to ambiguities and contradictory results in the literature. Furthermore, these benchmarks are nearly saturated due to the recent improvements in local descriptors obtained by learning from large annotated datasets. To address these issues, we introduce a new large dataset suitable for training and testing modern descriptors, together with strictly defined evaluation protocols in several tasks such as matching, retrieval and verification. This allows for more realistic, thus more reliable comparisons in different application scenarios. We evaluate the performance of several state-of-the-art descriptors and analyse their properties. We show that a simple normalisation of traditional hand-crafted descriptors is able to boost their performance to the level of deep learning based descriptors once realistic benchmarks are considered. Additionally we specify a protocol for learning and evaluating using cross validation. We show that when training state-of-the-art descriptors on this dataset, the traditional verification task is almost entirely saturated. |
4,083 | Efficient dc-free RLL codes for optical recording | We will report on new dc-free runlength-limited codes (DCRLL) intended for the next generation of DVD. The efficiency of the newly developed DCRLL schemes is extremely close to the theoretical maximum, and as a result, significant density gains can be obtained with respect. to prior art coding schemes. With a newly developed DCRLL (d = 2) code we can achieve a 9% higher overall rate than that of DVD's EFMPlus. |
4,084 | Boom, Bust and Beyond: Arts and Sustainability in Calumet, Michigan | Cycles of boom and bust plague mining communities around the globe, and decades after the bust the skeletons of shrunken cities remain. This article evaluates strategies for how former mining communities cope and strive for sustainability in the decades well beyond the bust, using a case study of Calumet, Michigan. In 1910, Calumet was at the center of the mining industry in the Upper Peninsula of Michigan, but in the century since its peak, mining employment steadily declined until the last mine closed in 1968, and the population declined by over 80%. This paper explores challenges, opportunities, and progress toward sustainability associated with arts-related development in this context. Methods are mixed, including observation, interviews, document review, a survey, and secondary data analysis. We follow Flora and Flora's Community Capitals Framework to analyze progress toward sustainability. Despite key challenges associated with the shrunken city context (degraded tax base, overbuilt and aging infrastructure, diminished human capital, and a rather limited set of volunteers and political actors), we find the shrunken city also offers advantages for arts development, including low rents, less risk of gentrification, access to space, and political incentive. In Calumet, we see evidence of a spiraling up pattern toward social sustainability resulting from arts development; however impacts on environmental and economic sustainability are limited. |
4,085 | Use of free radial forearm and pronator quadratus muscle flap: Anatomical study and clinical application | The authors present an anatomical study and clinical experience with radial forearm flap (RFF) and pronator quadratus muscle (PQM) application in the reconstruction of various body areas. The aim was to describe the anatomical placement and proportions of the PQM, the anatomical location of the major arterial branch of the radial artery supplying the PQM, and the application of this knowledge in clinical practice. The anatomical study was based upon an analysis of 13 fresh adult cadaver upper extremities, of which nine were female and four male; both arms from the same donors were used in four cases. The study of the PQM was performed using a dye-containing intraarterial injection, standard macro- and micro-preparation techniques, and chemical digestion. The data on the PQM size in males and females, thickness of the radial artery branch (the principal artery nourishing the muscle), and its position were analysed. The radial artery branch nourishing the PQM was identified in all cadaveric specimens of the anatomical study. In addition, 12 patients underwent reconstructions of soft and bony tissue defects using a RFF + PQM (pedicled or free flap). The radial artery branch perfusing the PQM was identified in all cases. The flap was used for the management of defects of the head (seven cases), arm (three cases) and lower leg (two cases). The harvest site healed well in all cases and, with the exception of one case in which a partial necrosis of the flap was observed, all flaps remained viable, which demonstrated the safety of the method. |
4,086 | Multi-modal graph reasoning for structured video text extraction | Structured video text information extraction is a crucial part of video understanding for exploring the structured text fields from different category-specific videos such as scores in basketball games or identities in news. Recent natural language models and text detectors have demonstrated state-of-the-art performance in video text detection and recognition. However, understanding text from unstructured video frames is challenging in practice due to a variety of video text and dynamic text layout changes. Limited work has focused on the solutions that efficiently extract structured information from the video text. In this paper, we address this task by modeling a multi-modal attention graph on the video text. Specifically, we encode both the visual and textual features of detected text regions as nodes of the graph; the spatial layout relationship of the text regions is modeled as edges of the graph. The structured information extraction is solved by iteratively propagating text region messages along graph edges and reasoning the structured categories of graph nodes. To promote the representation capacity of the graph, we further introduce a contrastive loss on the visual embeddings of the text regions in a self-supervised manner. In order to roundly evaluate our proposed method as well as boost future research, we release a new dataset collected and annotated from several standard NBA regular seasons and playoff match videos. Experimental results demonstrate the superior performance of the proposed method over several state-of-the-art methods. |
4,087 | Method to Design General RNS Reverse Converters for Extended Moduli Sets | In recent years, research on residue number systems (RNS) has targeted larger dynamic ranges (DRs) in order to further explore their inherent parallelism. In this brief, we start from the traditional three-moduli set {2(n), 2(n) - 1, 2(n) + 1}, with an equivalent 3n-bit DR; propose horizontal and vertical extensions to scale the DR; and improve the parallelism according to the requirements. This brief also introduces a method to design general reverse converters for extended moduli sets with the desired DRs, whereas the existing state of the art allows to achieve at most (8n + 1) bit. The experimental results suggest that the proposed moduli set extensions allow for larger and more balanced moduli sets, in comparison with the state of the art, resulting in an improvement of the overall RNS performance at the cost of a slower reverse conversion operation. |
4,088 | Design of an efficient Scalable Vector Graphics player for constrained devices | The mobile industry, and in particular the 3(rd) Generation Partnership Project (3GPP) Consortium, has selected the "Tiny" profile of the Scalable Vector Graphics (SVG) specification as a basis for the Rich Media format for mobile applications, leading the way to consumer electronics. Among the foreseen applications for SVG on constrained consumer electronics devices, maps, clip arts, animated cartoons and user interfaces are often cited. However, such devices are memory-constrained and have limited processing capabilities whereas vector graphics clip arts, animated cartoons or maps are described by large SVG documents. Such content may require heavy computations and important memory consumption, especially when applying models for animation and inheritance. In this paper, we present the design of a low-footprint and compulationally efficient player for large and animated SVG documents. We describe the structures of the scene objects which enable low memory consumption and the compositing and rendering algorithms enabling fast playback. Finally, we evaluate the limitations of our proposal and compare our results with publically available desktop SVG players. |
4,089 | Genetic programming for multibiometrics | Biometric systems suffer from some drawbacks: a biometric system can provide in general good performances except with some individuals as its performance depends highly on the quality of the capture ... One solution to solve some of these problems is to use multibiometrics where different biometric systems are combined together (multiple captures of the same biometric modality, multiple feature extraction algorithms, multiple biometric modalities ... ). In this paper, we are interested in score level fusion functions application (i.e., we use a multibiometric authentication scheme which accept or deny the claimant for using an application). In the state of the art, the weighted sum of scores (which is a linear classifier) and the use of an SVM (which is a non linear classifier) provided by different biometric systems provide one of the best performances. We present a new method based on the use of genetic programming giving similar or better performances (depending on the complexity of the database). We derive a score fusion function by assembling some classical primitives functions (+, *, -, ... ). We have validated the proposed method on three significant biometric benchmark datasets from the state of the art. (C) 2011 Elsevier Ltd. All rights reserved. |
4,090 | Up-sampling of YCbCr4:2:0 Image Exploiting Inter-color Correlation in RGB Domain | This paper introduces a practical inter-color up-sampling algorithm for images with decimated chrominance components. Most of the existing and emerging image and video compression coding standards such as JPEG, MPEG and H.26x families employ; YCbCr4:2:0 chrominance format. After reconstructing the YCbCr4:2:0 image at a decoder, one must up-sample the decoded chrominance signals by a factor of two in both horizontal and vertical directions to generate the YCbCr4:4:4 format image, which is eventually transformed to RGB color space especially for displaying the reconstructed image. Then, we focus on generating high-fidelity RGB image, (but not an intermediate YCbCr image), and propose an innovative up-sampling algorithm that exploits the RGB inter-channel cot-relation. This is based on the fact that the RGB inter-channel correlation is usually higher than the YCbCr inter-channel correlation. The simulation results show that the proposed method outperforms the state-of-the-art method and a bi-linear method with regard to the objective quality measures. In addition, the proposed algorithm is less expensive than the state-of-the-art technology in terms of the resource requirements. |
4,091 | Simplified Solutions for Activity Deposited on Moving Filter Media | Simplified numerical solutions for particulate activity viewed on moving filter continuous air monitors are developed. The monitor configurations include both rectangular window (RW) and circular window (CW) types. The solutions are demonstrated first for a set of basic airborne radioactivity cases, for a series of concentration pulses, and for indicating the effects of step changes in reactor coolant system (RCS) leakage for a pressurized water reactor. The method is also compared to cases from the prior art. These simplified solutions have additional benefits: They are easily adaptable to multiple radionuclides, they will accommodate collection and detection efficiencies that vary in known ways across the collection area, and they also ease the solution programming. |
4,092 | SensorFormer: Efficient Many-to-Many Sensor Calibration With Learnable Input Subsampling | Accurate calibration of low-cost environmental sensors is a prerequisite for their successful use in many monitoring applications. State-of-the-art calibration methods vary from simple linear regression to sophisticated deep models based on LSTMs and GRUs. The latter take past measurements to improve calibration accuracy. In this article, we argue that both recent past and close future measurements help to achieve accurate calibration, whereas accuracy improvements beyond the past come with a delay introduced by the occurrence of the future. We propose a generalized many-to-many calibration scheme called SensorFormer based on the successful Transformer model which takes both past and future raw measurements into account. We show that the proposed approach: 1) outperforms other methods by improving calibration accuracy by 16.5%-20.4% on public data sets and own field data and 2) can efficiently run on low-power microcontrollers with very limited computational and storage capabilities. The latter is achieved by a novel optimization technique based on learnable input subsampling taking advantage of the properties of typical sensor data. We manage to reduce the model size by 20%-33% and minimize the overall floating point operations per second (FLOPs) by 65% while maintaining superior accuracy than state-of-the-art methods. |
4,093 | Dating Iberian prehistoric rock art: Methods, sampling, data, limits and interpretations | Rock art dating has been one of the major challenges since its discovery and recognition. The methods have evolved through the last century, beginning with the study of superpositions and style until to the application of numeric methods since the 1990s. The aim of this paper is to evaluate and publish an up-to-date database of all of the numerical dates currently available for Iberian prehistoric rock art sites. For this purpose, the manuscript reviews all the methods applied so far to Iberian rock art discussing the limits, the sampling involved, and the problems affecting the results. After that, we present and discuss the most relevant results related to each cultural graphic tradition (Palaeolithic, Levantine, Schematic and Megalithic rock art) assessing their value and limitations. Finally, we reflect on the future of rock art dating: unfortunately most of the motifs are not dateble in numeric terms, meaning we still have to combine traditional with numerical methods; but also, we need to keep working on the problems affecting these methods to be able to create a more reliable chronological framework of use to address other issues such as group mobility, cultural networks, and reutilisation of symbolic elements, to name a few. |
4,094 | NASA's L-Band Digital Beamforming Synthetic Aperture Radar | The Digital Beamforming Synthetic Aperture Radar (DBSAR) is a state-of-the-art L-band radar that employs advanced radar technology and a customized data acquisition and real-time processor in order to enable multimode measurement techniques in a single radar platform. DBSAR serves as a test bed for the development, implementation, and testing of digital beamforming radar techniques applicable to Earth science and planetary measurements. DBSAR flew its first field campaign on board the National Aeronautics and Space Administration P3 aircraft in October 2008, demonstrating enabling techniques for scatterometry, synthetic aperture, and altimetry. |
4,095 | Automatic portrait oil painter: joint domain stylization for portrait images | Everyone has the dream of being in the center of famous art paintings, admired by numerous future generations. However, the dream came true at a huge cost of the painter's commission in old days. In our paper, another practical choice is provided for everyone to achieve that dream - an automatic portrait oil painter transferring some artistic styles from one single reference painting. To address this issue, we propose a joint-domain image stylization approach, particularly for portrait oil paintings. From the view of artistic appreciation, we analyze an amount of oil painting art works and summarize three critical factors to depict the figure, i.e. color, structure and texture. Based on this point, we separate and represent an artistic work into these three domains. Then, considering their intrinsic properties and following an art creation route, we propose the corresponding approaches to jointly model and transfer the features in these domains. First, a swatch-based color adjustment is proposed to recolor the tone of the input image based on semantic regions corresponding to the references. Second, the main structures of the input image is maintained by sparse reconstruction. Third, a coarse-to-fine texture synthesis is used to enhance the detail oil painting patterns. Extensive experimental results demonstrate that the proposed method achieves desirable results compared with state-of-the-art methods in not only transferring the styles from references but also keeping consistent contents with the given portrait. |
4,096 | Machine learning in lung transplantation: Where are we? | Lung transplantation has been accepted as a viable treatment for end-stage respiratory failure. While regression models continue to be a standard approach for attempting to predict patients' outcomes after lung transplantation, more sophisticated supervised machine learning (ML) techniques are being developed and show encouraging results. Transplant clinicians could utilize ML as a decision-support tool in a variety of situations (e.g. waiting list mortality, donor selection, immunosuppression, rejection prediction). Although for some topics ML is at an advanced stage of research (i.e. imaging and pathology) there are certain topics in lung transplantation that needs to be aware of the benefits it could provide. |
4,097 | Oxidative stress and DNA damage in earthworms induced by methyl tertiary-butyl ether in natural soils | Adverse effects of methyl tertiary-butyl ether (MTBE) have been noticed at different trophic levels by international researchers. However, there was unclear evidence about its effects on oxidative stress and DNA damage in earthworms. In this study, earthworms were cultivated in various doses of MTBE (0.0 mg/kg, 10.0 mg/kg, 30.0 mg/kg, and 60.0 mg/kg) contaminated agricultural soil for 7 days, 14 days, 21 days, and 28 days, respectively. The result showed that the reactive oxygen species (ROS) content of earthworms significantly increased in MTBE treatment groups compared to the control group. In MTBE treatment groups, the activities of superoxide dismutase, catalase, peroxidase, and glutathione S-transferase were significantly activated at the exposure of 7 days, which increased by 36.3-78.9%, 51.8-97.3%, 36.5-61.9%, and 12.0-54.8%, respectively. Then, the activities of these defense enzymes showed various changes following the changes in exposure times and MTBE concentrations. Especially in the 60.0 mg kg-1 group, both antioxidant enzymes and GST were still significantly activated at the exposure of 14 days and then significantly inhibited at the exposure of 28 days. The analysis of olive tail moment showed significant DNA damage in the 10.0 mg kg-1 group at the exposure of 28 days, and this damage in 30.0 mg/kg and 60.0 mg/kg groups was found at the exposure of 7 days. This result was consistent with the malondialdehyde accumulation in earthworms. Additionally, the analysis of IBRv2 showed the effects of MTBE treatments on earthworms in dose- and time-dependent manners. This study helps better to understand the effects of MTBE on soil invertebrate animals and provide theoretical support for soil protection in governing MTBE application. |
4,098 | Comparative analysis of building insulation material properties and performance | Building envelope insulation is crucial for an energy-efficient and comfortable indoor environment because the envelope accounts for 50-60% of total heat gain/loss in a building. Previous studies mostly used lifecycle cost as the criteria to select the optimum insulation materials with little or no consideration of embodied energy, emission, and summer overheating potential. This study presents a comparative analysis of building insulation materials properties (thermal, hygroscopic, acoustic, reaction to fire, environmental, and cost) and their performance in different climate zones and proposed an optimization framework. Insulation materials can be primarily categorized as conventional, state-of-the-art and sustainable. State-of-the-art insulation materials have the lowest thermal conductivity value amongst the three insulation types. However, their life cycle cost is higher compared to the other types. Sustainable insulation materials could be useful to delay and minimize indoor peak temperature and reduce overheating risk during the hot summer period. The analysis also showed that building walls with comparatively lower thermal resistance are more cost-effective for the cooling dominated region, but walls with higher thermal resistance are more cost-effective in heating-dominated regions. However, highly insulated and airtight houses may also lead to increased overheating risk and peak cooling demand during a hot summer period. In addition, hygroscopic, acoustic, and fire retardancy properties of insulation materials are critical to control indoor relative humidity in a humid region, to maintain a minimum noise level in a zone, and to reduce fire destruction. Hence, the optimization should include four criteria 1) Energy, 2) Environment, 3) Economic, and 4) Comfort. |
4,099 | Prenatal evaluation of atelencephaly | Atelencephaly is a rare lethal congenital brain malformation characterized by underdevelopment of the prosencephalon and is often accompanied by the facial features seen in some cases of holoprosencephaly, such as cyclopia. We report a case of atelencephaly in the fetus with characteristic ultrasound findings. In addition, we report the findings on fetal MRI, which have not been previously described in the literature. |
Subsets and Splits
No saved queries yet
Save your SQL queries to embed, download, and access them later. Queries will appear here once saved.