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2,600 | Welder's Anthrax: A Tale of 2 Cases | Bacillus anthracis has traditionally been considered the etiologic agent of anthrax. However, anthrax-like illness has been documented in welders and other metal workers infected with Bacillus cereus group spp. harboring pXO1 virulence genes that produce anthrax toxins. We present 2 recent cases of severe pneumonia in welders with B. cereus group infections and discuss potential risk factors for infection and treatment options, including antitoxin. |
2,601 | Improvements on deinterleaving of radar pulses in dynamically varying signal environments | An electronic support system receiver which is a passive receiver picks up an interleaved stream of pulses and extracts their pulse parameters. These parameters are sent to a deinterleaving subsystem which sorts them and forms pulse cells that each are assumed to belong to a specific emitter. In this paper, we develop a method for this task of deinterleaving of radar pulse sequences. For this aim, a novel pulse amplitude tracking algorithm is proposed for dynamically varying signal environments wherein radar parameters can change abruptly. This method particularly works for air-to-air engagements where pulse amplitude distortion due to channel effects can be considered negligible. Simulation results show that the proposed algorithm incorporated with a clustering algorithm improves deinterleaving of radar emitters that have agile pulse parameters such as airborne radars. (C) 2017 Elsevier Inc. All rights reserved. |
2,602 | Tumor Microenvironment-Adaptive Nanoplatform Synergistically Enhances Cascaded Chemodynamic Therapy | Chemodynamic therapy (CDT), a noninvasive strategy, has emerged as a promising alternative to conventional chemotherapy for treating tumors. However, its therapeutic effect is limited by the amount of H2O2, pH value, the hypoxic environment of tumors, and it has suboptimal tumor-targeting ability. In this study, tumor cell membrane-camouflaged mesoporous Fe3O4 nanoparticles loaded with perfluoropentane (PFP) and glucose oxidase (GOx) are used as a tumor microenvironment-adaptive nanoplatform (M-mFeP@O2-G), which synergistically enhances the antitumor effect of CDT. Mesoporous Fe3O4 nanoparticles are selected as inducers for photothermal and Fenton reactions and as nanocarriers. GOx depletes glucose within tumor cells for starving the cells, while producing H2O2 for subsequent ·OH generation. Moreover, PFP, which can carry O2, relieves hypoxia in tumor cells and provides O2 for the cascade reaction. Finally, the nanoparticles are camouflaged with osteosarcoma cell membranes, endowing the nanoparticles with homologous targeting and immune escape abilities. Both in vivo and in vitro evaluations reveal high synergistic therapeutic efficacy of M-mFeP@O2-G, with a desirable tumor-inhibition rate (90.50%), which indicates the great potential of this platform for clinical treating cancer. |
2,603 | Learning to Hash With Optimized Anchor Embedding for Scalable Retrieval | Sparse representation and image hashing are powerful tools for data representation and image retrieval respectively. The combinations of these two tools for scalable image retrieval, i.e., sparse hashing (SH) methods, have been proposed in recent years and the preliminary results are promising. The core of those methods is a scheme that can efficiently embed the (high-dimensional) image features into a low-dimensional Hamming space, while preserving the similarity between features. Existing SH methods mostly focus on finding better sparse representations of images in the hash space. We argue that the anchor set utilized in sparse representation is also crucial, which was unfortunately underestimated by the prior art. To this end, we propose a novel SH method that optimizes the integration of the anchors, such that the features can be better embedded and binarized, termed as Sparse Hashing with Optimized Anchor Embedding. The central idea is to push the anchors far from the axis while preserving their relative positions so as to generate similar hashcodes for neighboring features. We formulate this idea as an orthogonality constrained maximization problem and an efficient and novel optimization framework is systematically exploited. Extensive experiments on five benchmark image data sets demonstrate that our method outperforms several state-of-the-art related methods. |
2,604 | Consistency of Eye Coloration Across Different Relationship Partners | Studies have indicated that people are attracted to partners who resemble themselves or their parents, in terms of physical traits including eye color. We might anticipate this inclination to be relatively stable, giving rise to a sequential selection of similar partners who then represent an individual's "type". We tested this idea by examining whether people's sequential partners resembled each other at the level of eye color. We gathered details of the eye colors of the partners of participants (N = 579) across their adult romantic history (N = 3250 relationships), in three samples, comprising two samples which made use of self-reports from predominantly UK-based participants, and one which made use of publicly available information about celebrity relationship histories. Recorded partner eye colors comprised black (N = 39 partners), dark brown (N = 884), light brown (N = 393), hazel (N = 224), blue (N = 936), blue green (N = 245), grey (N = 34), and green (N = 229). We calculated the proportion of identical eye colors within each participant's relationship history, and compared that to 100,000 random permutations of our dataset, using t-tests to investigate if the eye color of partners across an individual's relationship history was biased relative to chance (i.e., if there was greater consistency, represented by higher calculated proportions of identical eye colors, in the original dataset than in the permutations). To account for possible eye color reporting errors and ethnic group matching, we ran the analyses restricted to White participants and to high-confidence eye color data; we then ran the analyses again in relation to the complete dataset. We found some limited evidence for some consistency of eye color across people's relationship histories in some of the samples only when using the complete dataset. We discuss the issues of small effect sizes, partner-report bias, and ethnic group matching in investigating partner consistency across time. |
2,605 | Investigating Physiopathological Roles for Sirtuins in a Mouse Model | Sirtuins are identified as NAD+-dependent class III histone deacetylases (HDAC) and are involved in a variety of cellular activities, including energy metabolism, DNA repair, epigenetics, gene expression, cell proliferation, differentiation, and survival. Using genetically modified model organisms, sirtuins are proved to be one of the most conserved aging-regulatory and longevity-promoting genes/pathways among species. Of the seven sirtuins, SIRT7 is the only sirtuin that localizes in the nucleolus. SIRT7 senses endogenous and environmental stress to maintain physiological homeostasis. Sirt7 deficient and transgenic mice provide a useful tool to understand the mechanisms of aging and related pathologies. In this chapter, we summarized the most widely applied methods to understand the physiopathological function of SIRT7 in mice. |
2,606 | Fundamentals of HDX-MS | Hydrogen deuterium exchange mass spectrometry (HDX-MS) is becoming part of the standard repertoire of techniques used by molecular biologists to investigate protein structure and dynamics. This is partly due to the increased use of automation in all stages of the technique and its versatility of application-many proteins that present challenges with techniques such as X-ray crystallography and cryoelectron microscopy are amenable to investigation with HDX-MS. The present review is aimed at scientists who are curious about the technique, and how it may aid their research. It describes the fundamental basis of solvent exchange, the basics of a standard HDX-MS experiment, as well as highlighting emerging novel experimental advances, which point to where the field is heading. |
2,607 | Molecular hydrogen positively influences lateral root formation by regulating hydrogen peroxide signaling | Although a previous study discovered that exogenous molecular hydrogen (H2) supplied with hydrogen-rich water (HRW) can mediate lateral root (LR) development, whether or how endogenous H2 influences LR formation is still elusive. In this report, mimicking the induction responses in tomato seedlings achieved by HRW or exogenous hydrogen peroxide (H2O2; a positive control), transgenic Arabidopsis that overexpressed the hydrogenase1 gene (CrHYD1) from Chlamydomonas reinhardtii not only stimulated endogenous hydrogen peroxide (H2O2) production, but also markedly promoted LR formation. Above H2 and H2O2 responses were abolished by the removal of endogenous H2O2. Moreover, the changes in transcriptional patterns of representative cell cycle genes and auxin signaling-related genes during LR development in both tomato and transgenic Arabidopsis thaliana matched with above phenotypes. The alternations in the levels of GUS transcripts driven by the CYCB1 promoter and expression of PIN1 protein further indicated that H2O2 synthesis was tightly linked to LR formation achieved by endogenous H2, and cell cycle regulation and auxin-dependent pathway might be their targets. There results might provide a reference for molecular mechanism underlying the regulation of root morphogenesis by H2. |
2,608 | Efficient Scheduling for the Massive Random Access Gaussian Channel | This article investigates the massive random access Gaussian channel with a focus on small payloads. For this problem, grant-based schemes have been regarded as inefficient due to the necessity of large feedbacks and the use of inefficient scheduling request methods. This articles attempts to answer whether grant-based schemes can be competitive against state-ot-art grantless schemes and worthy of further investigation. In order to compare these schemes fairly, a novel model is proposed, and, under this model, a novel grant-based scheme is proposed. The scheme uses Ordentlich and Polyanskiy's grantless method to transmit small coordination indices in order to perform the scheduling request, which allows both the request from the users to be efficient and the feedback to be small. We also present improvements to the Ordentlich and Polyanskiy's scheme, allowing it to transmit information through the choice of sub-block, as well as to handle collisions of the same message, significantly improving the method for very small messages. Simulation results show that, if a small feedback is allowed, the proposed scheme performs closely to the state-of-art while using simpler coding schemes, suggesting that novel grant-based schemes should not be dismissed as a potential solution to the massive random access problem. |
2,609 | A Novel SCA-Based Method for Beamforming Optimization in IRS/RIS-Assisted MU-MISO Downlink | In this letter, we consider the fundamental problem of jointly designing the transmit beamformers and the phase shifts of the intelligent reflecting surface (IRS)/reconfigurable intelligent surface (RIS) to minimize the transmit power, subject to quality-of-service constraints at individual users in an IRS-assisted multiuser multiple-input single-output downlink communication system. In particular, we propose a new successive convex approximation based second-order cone programming approach in which all the optimization variables are simultaneously updated in each iteration. Our proposed scheme achieves superior performance compared to state-of-the-art benchmark solutions. In addition, the complexity of the proposed scheme is O(N-s(3.5)), while that of state-of-the-art benchmark schemes is O(N-s(7)), where Ns denotes the number of reflecting elements at the IRS. |
2,610 | Expression and Crystallization of HDAC6 Tandem Catalytic Domains | Histone deacetylase 6 (HDAC6) is an atypical lysine deacetylase with tandem catalytic domains and an ubiquitin-binding zinc finger domain. HDAC6 is involved in various biological processes, such as cell motility or stress responses, and has been implicated in pathologies ranging from cancer to neurodegeneration. Due to this broad range of functions, there has been considerable interest in developing HDAC6-specific small molecule inhibitors, several of which are already available. The crystal structure of the tandem catalytic domains of zebrafish HDAC6 has revealed an arrangement with twofold symmetry and extensive surface interaction between the catalytic domains. Further dissection of the biochemical properties of HDAC6 and the development of novel inhibitors will benefit from being able to routinely express high-quality protein. We present here our optimized protocol for expression and crystallization of the zebrafish tandem catalytic domains. |
2,611 | Perspective-SIFT: An efficient tool for low-altitude remote sensing image registration | This paper presents an automated image registration approach that is robust to perspective distortions. State-of-the-art method affine-SIFT uses affine transform to simulate various viewpoints to increase the robustness of registration. However, affine transformation does not follow the process by which real-world images are formed. To solve this problem, we propose a perspective scale invariant feature transform (PSIFT) that uses homographic transformation to simulate perspective distortion. As for ASIFT, PSIFT is based on the scale invariant feature transform (SIFT) and has a two-resolution scheme, namely a low-resolution phase and a high-resolution phase. The low-resolution phase of PSIFT simulates several image views following a perspective transformation by varying two camera axis orientation parameters. Given those simulated images, SIFT is then used to extract features and find matches among them. In the high-resolution phase, the perspective transformations which lead the largest number of matches in the low-resolution stage are selected to generate SIFT features on the original images. Experimental results obtained on three categories of low-altitude remote sensing images and Morel-Yu's dataset show that PSIFT outperforms significantly the state-of-the-art ASIFT, SIFT, Random Ferns, Harris-Affine, MSER and Hessian Affine, especially when images suffer severe perspective distortion. (C) 2013 Elsevier B.V. All rights reserved. |
2,612 | Phase-Transition-Cycle-Induced Recrystallization of FAPbI3 Film in An Open Environment Toward Excellent Photodetectors with High Reproducibility | Perovskite is an attractive building block for future optoelectronic applications. However, the strict fabrication conditions of perovskite devices impede the transformation of lab techniques into commercial applications. Here, a facile annealing-free posttreatment is proposed to reconstruct the perovskite film to obtain high-performance photodetectors with an optimized production rate. With posttreatment by methylamine thiocyanate, the prefabricated formamidinium-lead triiodide (FAPbI3 ) film will undergo a recrystallization process consisting of a repeating phase-transition-cycle (PTC) between the black and yellow phases of FAPbI3 , which improves the crystal quality and eliminates defects. As a result, some casually prepared or even decomposed perovskite films can be reconstructed, and the dispersion degree of the device performance based on the posttreatment method decreases by ≈21% compared to the traditional antisolvent method. This facile and annealing-free posttreatment will be an attractive method for the future industrial production of perovskite devices. |
2,613 | The Predictive Utility of Trauma Subtypes in the Assessment of Mental Health Outcomes for Persons Resettled as Refugees | Pre-migration trauma, a psychological risk factor for refugees, is often measured using cumulative indices. However, recent research suggests that trauma subtypes, rather than cumulative trauma, may better predict psychological outcomes. This study investigated the predictive utility of trauma subtypes in the assessment of refugee mental health. Multiple regression was used to determine whether cumulative trauma or trauma subtypes explained more variance in depression, anxiety, and post-traumatic stress disorder (PTSD) symptom scores in 70 Syrian and Iraqi refugees. Subtype models performed better than cumulative trauma models for PTSD (cumulative R2 = 0.138; subtype R2 = 0.32), anxiety (cumulative R2 = 0.061; subtype R2 = 0.246), and depression (cumulative R2 = 0.041; subtype R2 = 0.184). Victimization was the only subtype significantly associated with PTSD (p < 0.001; r2 = 0.210), anxiety (p < 0.001; r2 = 0.162), and depression (p = 0.002; r2 = 0.140). Cumulative trauma was predictive of PTSD symptoms only (p = 0.003; r2 = 0.125). Trauma subtypes were more informative than cumulative trauma, indicating their utility for improving predictive efforts in research and clinical contexts. |
2,614 | Cultural Sustainability of US Cities: The Scaling of Non-Profit Arts Footprint with Population | The functional characteristics of urban systems vary predictably with Metropolitan Statistical Area (MSA) population, with certain metrics increasing apace with population (e.g., housing stock), some increasing faster than population (e.g., wealth), and others increasing slower than population (infrastructure elements). Culture has been designated the fourth pillar of sustainability. The population-dependent scaling of operating revenue, work space, and number of employees was investigated for almost 3000 arts organizations in the US, both in aggregate and by arts discipline (music, theater, visual and design arts, dance, and museums). Unlike general measures of creativity, the three measures of economic footprint did not scale supra-linearly with the population of metropolitan areas. Rather, operating revenue scaled linearly (e.g., like amenities), and work space and employee number scaled sub-linearly (e.g., like infrastructure). The cost of living, proxied by housing costs, increased with MSA population, though not as rapidly as did arts organization operating revenue, indicating a degree of uncoupling. The generally higher educational attainment of adults in larger cities, coupled with the growth of the education-dependent arts patronage, suggest a funding focus on less populous (50,000-1,000,000), as well as on under-performing, cities. |
2,615 | Suspect face retrieval system using multicriteria decision process and deep learning | The identification and apprehending of suspects by law enforcement authorities rely heavily on facial sketches. The sketch artist creates sketches based on the witnesses' memories. Sketch artists are few and limited in their availability. It is also evident that as time passes, the eyewitness forgets many of the important details, which can be expensive in time-sensitive investigations. The sketch was used to obtain the suspect's image through the state-of-the-art sketch-photo retrieval model, which missed the relevance of time sensitivity. A linguistic description-based suspect face image retrieval approach is presented in this study. In the proposed approach, the facial attribute-value pair is extracted from eyewitness descriptions. Facial attribute saliency is also studied in this work and validated with the Fuzzy Analytic Hierarchy Process (FAHP) model. A weighted score is computed to retrieve the suspect face images. The effectiveness of the proposed method is assessed by comparing it to existing linguistic sketch-based retrieval methods as well as the sketch to photo retrieval models. As compared to state-of-the-art approaches, experimental results give an accuracy of 94.98%. |
2,616 | Inter-domain routing for communication networks using Hierarchical Hopfield Neural Networks | This paper presents the Hierarchical Hopfield Neural Networks (HHNN). HHNN is a novel Hopfield Neural Network (HNN) approach. HHNN is composed of a hierarchy of self-sufficient HNNs, aiming to reduce the neural network structure and mitigate convergence problems. The HNNN composition depends on the applied problem. In this paper, the problem approached is the inter-domain routing for communication networks. Thus, the hierarchy of HNNs mimics the structure of communication networks (domains, nodes, and links). The proof of concept and the comparison between HNNN with the state-of-art HNN occurs using an implementation of them in the Java programming language. Besides, the performance analysis of the HHNN runs on a parallel hardware platform, using VHDL to develop it. The results have demonstrated a reduction of 93.75% and 99.98% in the number of neurons and connections to build the neural network, respectively. Furthermore, the mean time to achieve convergence of HHNN is rough 1.52% of the total time needed by the current state-of-art HNN approach. It is also less susceptible to early convergence problems when used in communications networks with a large number of nodes. Last, but not least, the VHDL implementation shows that convergence time of HHNN is comparable to routing algorithms used in practical applications. |
2,617 | Analysis and optimization of coplanar RLC lines for GSI global interconnection | Compact physical models are derived for the delay and crosstalk of on-chip coplanar transmission lines, which are used in state-of-the-art high-speed microprocessors. These lines are mainly used for long global interconnects that are relatively thick and wide and have prominent inductive effects. The models are then used to optimize the design of coplanar global interconnects. |
2,618 | Computer-aided diagnosis of mammographic masses based on a supervised content-based image retrieval approach | In this work, the incorporation of content-based image retrieval (CBIR) into computer aided diagnosis (CADx) is investigated, in order to contribute to the decision-making process of radiologists in the characterization of mammographic masses. The proposed scheme comprises two stages: A margin-specific supervised CBIR stage that retrieves images from reference cases along with a decision stage that is based on the retrieved items. The feature set utilized exploits state-of-the-art features along with a newly proposed texture descriptor, namely mHOG, targeted to capturing margin and core specific mass properties. Performance evaluation considers the CBIR and diagnosis stages separately and is addressed by using standard measures on an enhanced version of the widely adopted digital database for screening mammography (DDSM). The proposed scheme achieved improved performance of CADx of masses in X-ray mammography experimentally compared to the state-of-the-art. (C) 2017 Elsevier Ltd. All rights reserved. |
2,619 | Brainnetome atlas of preadolescent children based on anatomical connectivity profiles | During the preadolescent period, when the cerebral thickness, curvature, and myelin are constantly changing, the brain's regionalization patterns underwent persistent development, contributing to the continuous improvements of various higher cognitive functions. Using a brain atlas to study the development of these functions has attracted much attention. However, the brains of children do not always have the same topological patterns as those of adults. Therefore, age-specific brain mapping is particularly important, serving as a basic and indispensable tool to study the normal development of children. In this study, we took advantage of longitudinal data to create the brain atlas specifically for preadolescent children. The resulting human Child Brainnetome Atlas, with 188 cortical and 36 subcortical subregions, provides a precise period-specific and cross-validated version of the brain atlas that is more appropriate for adoption in the preadolescent period. In addition, we compared and illustrated for regions with different topological patterns in the child and adult atlases, providing a topologically consistent reference for subsequent research studying child and adolescent development. |
2,620 | Closing the HIV Treatment Gap for Adolescents in Windhoek, Namibia: A Retrospective Analysis of Predictors of Viral Non-Suppression | Windhoek joined the Fast-Track Cities Initiative in 2017 to optimize HIV service delivery for adolescents, promoting adherence and sustaining viral suppression. Recent surveys and programmatic data show that the treatment gap remains greatest among children and adolescents living with HIV. A retrospective cohort analysis of adolescents living with HIV (ALHIV) receiving antiretroviral therapy (ART) at Windhoek healthcare facilities was conducted. Routine clinical data were extracted from the electronic Patient Monitoring System (ePMS). The SPSS statistical package was used to determine viral non-suppression and perform inferential statistics. 695 ALHIV were analysed with median age of 16 years (IQR = 13-18). Viral non-suppression at 1000 copies/mL threshold was 12%. Viral non-suppression was associated with age at ART initiation, duration on ART, current ART regimen and WHO Clinical Stage. In multivariate analysis, longer duration on ART was a protective factor for viral non-suppression (13-24 months vs. >24 months: aOR = 8.92, 95% CI 2.60-30.61), while being on third line regimen (vs. first line) was protective against viral non-suppression (aOR = 0.11, 95% CI 0.03-0.49). A significant treatment gap is evident for ALHIV with high viral non-suppression levels. Interventions are required to counter treatment fatigue to keep adolescents engaged in ART, and timely switching to rescue regimens for failing adolescents. |
2,621 | Pyramid Fully Convolutional Network for Hyperspectral and Multispectral Image Fusion | Low spatial resolution hyperspectral (LRHS) and high spatial resolution multispectral (HRMS) image fusion has been recognized as an important technology for enhancing the spatial resolution of LRHS image. Recent advances in convolutional neural network have improved the performance of state-of-the-art fusion methods. However, it is still a challenging problem to effectively explore the spatial information of HRMS image. In this paper, we propose a pyramid fully convolutional network made up of an encoder sub-network and a pyramid fusion sub-network to address this issue. Specifically, the encoder sub-network aims to encode the LRHS image into a latent image. Then, this latent image, together with a HRMS image pyramid input, is used to progressively reconstruct the high spatial resolution hyperspectral image in a global-to-local manner. Furthermore, to sharpen the blurry predictions easily obtained by the standard l(2) loss, we introduce the gradient difference loss as a regularization term. We evaluate the proposed method on three datasets acquired by three different satellite sensors. Experimental results demonstrate that the proposed method achieves better performance than several state-of-the-art methods. |
2,622 | Advancing a causal role of type 2 diabetes and its components in developing macro- and microvascular complications via genetic studies | The role of diabetes in developing microvascular and macrovascular complications has been subject to extensive research. Despite multiple observational and genetic studies, the causal inference of diabetes (and associated risk factors) on those complications remains incomplete. In this review, we focused on type 2 diabetes, as the major form of diabetes, and investigated the evidence of causality provided by observational and genetic studies. We found that genetic studies based on Mendelian randomization provided consistent evidence of causal inference of type 2 diabetes on macrovascular complications; however, the evidence for causal inference on microvascular complications has been somewhat limited. We also noted high BMI could be causal for several diabetes complications, notable given high BMI is commonly upstream of type 2 diabetes and the recent calls to target weight loss more aggressively. We emphasize the need for further studies to identify type 2 diabetes components that mostly drive the risk of those complications. Even so, the genetic evidence summarized broadly concurs with the need for a multifactorial risk reduction approach in type 2 diabetes, including addressing excess adiposity. |
2,623 | Eye drop delivery of pigment epithelium-derived factor-34 promotes retinal ganglion cell neuroprotection and axon regeneration | Axotomised retinal ganglion cells (RGCs) die rapidly by apoptosis and fail to regenerate because of the limited availability of neurotrophic factors and a lack of axogenic stimuli. However, we have recently showed that pigment epithelium-derived factor (PEDF) promotes RGC survival and axon regeneration after optic nerve crush injury. PEDF has multiple fragments of the native peptide that are neuroprotective, anti-angiogenic and anti-inflammatory. Here we investigated the neuroprotective and axogenic properties of a fragment of PEDF, PEDF-34, in retinal neurons in vitro and when delivered by intravitreal injection and eye drops in vivo. We found that PEDF-34 was 43% more neuroprotective and 52% more neuritogenic than PEDF-44 in vitro. Moreover, in vivo, intravitreal delivery of 1.88nM PEDF-34 was 71% RGC neuroprotective at 21days after optic nerve crush compared to intact controls, whilst daily eye drops containing 1.88nM PEDF-34 promoted 87% RGC survival. After topical eye drop delivery, PEDF-34 was detected in the vitreous body within 30min and attained physiologically relevant concentrations in the retina by 4h peaking at 1.4±0.05nM by 14days. In eye drop- compared to intravitreal-treated PEDF-34 animals, 55% more RGC axons regenerated 250μm beyond the optic nerve lesion. We conclude that daily topical eye drop application of PEDF-34 is superior to weekly intravitreal injections in promoting RGC survival and axon regeneration through both direct effects on retinal neurons and indirect effects on other retinal cells. |
2,624 | Robust CP Tensor Factorization With Skew Noise | The low-rank tensor factorization (LRTF) technique has received increasing popularity in data science, especially in computer vision applications. Many robust LRTF models have been presented recently. However, none of them take the skewness of data into account. This letter proposes a novel LRTF model for skew data analysis by modeling noise as a Mixture of Asymmetric Laplacians (MoAL). The numerical experiments show that the new model MoAL-LRTF outperforms several state-of-the-art counterparts. The codes for all the experiments are available at https://xsxjtu.github.io/Projects/MoAL/main.html. |
2,625 | Effect of curcumin on lipid profile, fibrosis, and apoptosis in liver tissue in abemaciclib-administered rats | Abemaciclib (ABEM) is an important antitumor agent for breast cancer treatment. However, the side-effects of ABEM are unclear in the liver. This study investigated the protective effect of curcumin (CURC) on liver damage caused by ABEM. The rats were divided into five groups with eight animals in each group; Control, DMSO (150 µL for per rats), CURC, 30 mg/kg/day), ABE (26 mg/kg/day), and ABE + CURC (26 mg/kg/day ABE, 30 mg/kg/day) groups. Injections were administered daily for 28 days. The levels of AST, LDH, HDL, LDL, triglyceride, and total cholesterol in serum, and hepatic tissue fibrosis, caspase-3, Bax, and TNF-α expression were higher in the ABE group compared to the control group (p < 0.05). Also, these parameters in the ABEM + CURC group were lower than in the ABE group (p < 0.05). The results showed that ABE administration could cause liver damage and increase fibrosis in the liver. In addition, it was shown that co-administration of CURC with ABE could suppress the levels of AST, LDH, HDL, LDL, triglyceride, and total cholesterol in serum, and fibrosis, caspase-3, Bax, and TNF-α expressions in the liver. These data are the first in the literature. Therefore, the administration of CURC following ABE may be a therapeutic agent in preventing liver damage. |
2,626 | Spatial Multiomics of Lipids, N-Glycans, and Tryptic Peptides on a Single FFPE Tissue Section | Mass spectrometry imaging (MSI) is an emerging technology that is capable of mapping various biomolecules within their native spatial context, and performing spatial multiomics on formalin-fixed paraffin-embedded (FFPE) tissues may further increase the molecular characterization of pathological states. Here we present a novel workflow which enables the sequential MSI of lipids, N-glycans, and tryptic peptides on a single FFPE tissue section and highlight the enhanced molecular characterization that is offered by combining the multiple spatial omics data sets. In murine brain and clear cell renal cell carcinoma (ccRCC) tissue, the three molecular levels provided complementary information and characterized different histological regions. Moreover, when the spatial omics data was integrated, the different histopathological regions of the ccRCC tissue could be better discriminated with respect to the imaging data set of any single omics class. Taken together, these promising findings demonstrate the capability to more comprehensively map the molecular complexity within pathological tissue. |
2,627 | Deep and shallow fast embedded capsule networks: going faster with capsules | Capsule Networks (CapsNets) is a great approach for understanding data in the field of computer vision. CapsNets allow a deeper understanding of images compared to the traditional Convolutional Neural Networks. The first test for CapsNet was in digits recognition on the 'MNIST' dataset, where it successfully achieved high accuracy. CapsNets are reliable at deciphering overlapping digits. Deep Capsule Networks achieved state-of-the-art accuracy in CIFAR10 which isn't achieved by shallow capsule networks. Despite all these accomplishments, Deep Capsule Networks are very slow due to the 'Dynamic Routing' algorithm. In this paper, Fast Embedded Capsule Network and Deep Fast Embedded Capsule Network are introduced, representing novel capsule network architectures that uses 1D convolution based dynamic routing with a fast element-wise multiplication transformation process. These architectures not only compete with the state-of-the-art methods in terms of accuracy in the capsule domain, but also excels in terms of speed, and reduced complexity. This is shown by the 58% reduction in the number of trainable parameters and 64% reduction in the average epoch time in the training process. Experimental results shows excellent and verified properties. |
2,628 | Kalman-Based Real-Time Functional Decomposition for the Spectral Calibration in Swept Source Optical Coherence Tomography | This paper presents a real-time functional decomposition adaptive algorithm for the optimal sampling of the interferometric signal in Swept-Source Optical Coherence Tomography imaging systems, which completely eliminates the input signal dependent nonlinearities that are problematic in current state-of-the-art OCT realizations that use interpolation and resampling. The proposed adaptive calibration algorithm uses the Kalman approach to estimate the wavenumber index parameter k from the Mach-Zender Interferometer signal which is then applied to an adaptive level crossing sampler to generate a sampling clock that k-linearizes the data on real-time during the sampling process. Such a system implements an artifact-free realization of the technology removing the need for classical interpolation and resampling. The new real-time linearization scheme has the additional capability of increasing the imaging acquisition speed by 10X while providing robustness to noise, properties that are demonstrated through mathematical analysis and simulation results throughout the paper. |
2,629 | On Establishing Edge Adaptive Grid for Bilevel Image Data Hiding | We propose, in this paper, a novel edge-adaptive data hiding method for authenticating binary host images. Through establishing a dense edge-adaptive grid (EAG) along the object contours, we use a simple binary image to show that EAG more efficiently selects good data carrying pixel locations (DCPL) associated with "l-shaped" patterns than block-based methods. Our method employs a dynamic system structure with the redesigned fundamental content adaptive processes (CAP) switch to iteratively trace new contour segments and to search for new DCPLs. By maintaining and updating a location status map, a protective mechanism is proposed to preserve the context of each CAP and their corresponding outcomes. We prove that our method is robust against the interferences caused by close-by contours, image noises, and invariantly selects the same sequence of DCPLs for an arbitrary binary host image and its various marked versions. Comparison shows that our method achieves a good tradeoff between large payload and minimal visual distortion as compared with several classic prior arts for diverse types of binary host images. Moreover, our method well supports state-of-the-art hybrid authentication that integrates data hiding and modern cryptographic techniques. |
2,630 | Tissue Sealants for Facial Rhytidectomy: A Systematic Review and Meta-Analysis of Randomized Controlled Trials | Background: The aging face can be surgically treated with a face-lift (rhytidectomy); however, bleeding and hematoma are complications that surgeons seek to prevent. Objective: To compare the drainage volume and rate of hematoma in studies of rhytidectomy among those having tissue sealants and those without. Methods: This systematic review and meta-analysis was prospectively registered in PROSPERO (CRD42022325404). We included randomized controlled trials (RCTs) that the enrolled participants undergoing rhytidectomy and used tissue sealants as the intervention. We calculated the mean and standard deviation for the drainage volume; risk ratios (RRs) were used for hematoma incidents. Results: Seven RCTs were included. The drainage volume was significantly lower in the tissue sealant group than in the control group (mean difference [MD]: -11.01, confidence interval [95% CI]: -18.39 to -3.63, p < 0.00001). As for hematomas, the incidence was also lower in the tissue sealant group (RR: 0.29, 95% CI: 0.08-0.99, p = 0.05). Conclusion: This study suggests that tissue sealants can be effective in reducing drainage volume and hematoma in face-lift; however, autologous and homologous tissue sealants can be further compared in future RCTs. |
2,631 | Heterologous expression of Arabidopsis pattern recognition receptor RLP23 increases broad-spectrum resistance in poplar to fungal pathogens | The pattern recognition receptor AtRLP23 from Arabidopsis thaliana recognizes the epitopes (nlp24s) of necrosis and ethylene-inducing peptide 1-like proteins (NLPs) and triggers pattern-triggered immunity (PTI). Here, we established methods for studying the early events of PTI in the hybrid poplar cultivar Shanxin (Populus davidiana × Populus bolleana) in response to the flagellin epitope. We confirmed that wild-type Shanxin cannot generate PTI responses on nlp24 treatment. Four NLP homologues were characterized from two common fungal pathogens of Shanxin, namely Marssonina brunnea f. sp. monogermtubi (MbMo) and Elsinoë australis (Ea), which cause black leaf spot and anthracnose disease, respectively, and the nlp24s of three of them could be responded to by Nicotiana benthamiana leaves expressing AtRLP23. We then created AtRLP23 transgenic Shanxin lines and confirmed that the heterologous expression of AtRLP23 conferred on transgenic Shanxin the ability to respond to one nlp24 of each fungal pathogen. Consistently, infection assays with MbMo or Ea showed obviously lower levels of disease symptoms and significantly inhibited the growth of fungi on the transgenic poplar compared with that in wild-type poplar. Overall, our results indicated that the heterologous expression of AtRLP23 allowed transgenic Shanxin to generate a PTI response to nlp24s, resulting in increased broad-spectrum fungal disease resistance. |
2,632 | Giant ventral hernia following left ventricular assist device bridge to heart transplantation | Ventral hernias following left ventricular assist device (LVAD) placement are rare. With the improvement in technology, and miniaturization of devices associated with intrapericardial placement, these complications have largely been abolished. The mere presence of a large ventral hernia should not exclude recipients from being candidates for orthotopic heart transplantation. |
2,633 | Low Complexity Generic VLSI Architecture Design Methodology for Nth Root and Nth Power Computations | In this paper, we propose a low complexity architecture design methodology for fixed point root and power computations. The state of the art approaches perform the root and power computations based on the natural logarithm-exponential relation using Hyperbolic COordinate Rotation DIgital Computer (CORDIC). In this paper, any root and power computations have been performed using binary logarithm-binary inverse logarithm relation. The designs are modeled using VHDL for fixed point numbers and synthesized under the TSMC 40 -nm CMOS technology @ 1 GHz frequency. The synthesis results shows that the proposed N-th root computation saves 19.38% on chip area and 15.86% power consumption when compared with the state of the art architecture for root computation without compromising the computational accuracy. Similarly, the proposed N-th power computation saves 38% on chip area, 35.67% power consumption when compared with the state of the art power computation with out loss in accuracy. The proposed root and power computation designs save 8 clock cycle latency when compared with the state of the art implementations. |
2,634 | Content-Noise Complementary Learning for Medical Image Denoising | Medical imaging denoising faces great challenges, yet is in great demand. With its distinctive characteristics, medical imaging denoising in the image domain requires innovative deep learning strategies. In this study, we propose a simple yet effective strategy, the content-noise complementary learning (CNCL) strategy, in which two deep learning predictors are used to learn the respective content and noise of the image dataset complementarily. A medical image denoising pipeline based on the CNCL strategy is presented, and is implemented as a generative adversarial network, where various representative networks (including U-Net, DnCNN, and SRDenseNet) are investigated as the predictors. The performance of these implemented models has been validated on medical imaging datasets including CT, MR, and PET. The results show that this strategy outperforms state-of-the-art denoising algorithms in terms of visual quality and quantitative metrics, and the strategy demonstrates a robust generalization capability. These findings validate that this simple yet effective strategy demonstrates promising potential for medical image denoising tasks, which could exert a clinical impact in the future. Code is available at: https://github.com/gengmufeng/CNCL-denoising. |
2,635 | Enhancing online english language and literature classrooms: effective and practical teaching strategies | This paper examines key effective and practical online strategies for teaching and learning literature subjects in online education. The present study also explores the leading concepts and principles of e- teaching strategies and extends to address the way to adopt literary lesson plans to various types of college students, determine subject descriptions, class activities, assignments, assessments, and expectations with students, and build rapport and communication with the students. This article discusses how to enjoy appropriate online media, channels, platforms, and e-pedagogical tools to help the learners and support the college curriculum in literary subjects e.g. poetry, fiction, and drama. The results show that online pedagogues portray and guide interactive literary texts and skills to the students, educators, and course designers and can facilitate instructional methods in learning the English language and literature online. |
2,636 | A Human Visual System Inspired No-Reference Image Quality Assessment Method Based on Local Feature Descriptors | Objective quality assessment of natural images plays a key role in many fields related to imaging and sensor technology. Thus, this paper intends to introduce an innovative quality-aware feature extraction method for no-reference image quality assessment (NR-IQA). To be more specific, a various sequence of HVS inspired filters were applied to the color channels of an input image to enhance those statistical regularities in the image to which the human visual system is sensitive. From the obtained feature maps, the statistics of a wide range of local feature descriptors were extracted to compile quality-aware features since they treat images from the human visual system's point of view. To prove the efficiency of the proposed method, it was compared to 16 state-of-the-art NR-IQA techniques on five large benchmark databases, i.e., CLIVE, KonIQ-10k, SPAQ, TID2013, and KADID-10k. It was demonstrated that the proposed method is superior to the state-of-the-art in terms of three different performance indices. |
2,637 | BioWolf: A Sub-10-mW 8-Channel Advanced Brain-Computer Interface Platform With a Nine-Core Processor and BLE Connectivity | Advancements in digital signal processing (DSP) and machine learning techniques have boosted the popularity of brain-computer interfaces (BCIs), where electroencephalography is a widely accepted method to enable intuitive human-machine interaction. Nevertheless, the evolution of such interfaces is currently hampered by the unavailability of embedded platforms capable of delivering the required computational power at high energy efficiency and allowing for a small and unobtrusive form factor. To fill this gap, we developed BioWolf, a highly wearable (40mm 20 mm 2 mm) BCI platform based on Mr. Wolf, a parallel ultra low power system-on-chip featuring nine RISC-V cores with DSP-oriented instruction set extensions. BioWolf also integrates a commercial 8-channel medical-grade analog-to-digital converter, and an ARM-Cortex M4 microcontroller unit (MCU) with bluetooth low-energy connectivity. To demonstrate the capabilities of the system, we implemented and tested a BCI featuring canonical correlation analysis (CCA) of steady-state visual evoked potentials. The system achieves an average information transfer rate of 1.46 b/s (aligned with the state-of-the-art of bench-top systems). Thanks to the reduced power envelope of the digital computational platform, which consumes less than the analog front-end, the total power budget is just 6.31mW, providing up to 38h operation (65mAh battery). To our knowledge, our design is the first to explore the significant energy boost of a parallel MCU with respect to single-core MCUs for CCA-based BCI. |
2,638 | High-Power Lensless THz Imaging of Hidden Objects | The potential of pulsed THz radiation for time-of-flight imaging applications is well recognized. However, advances in this field are currently severely limited by the low average power of ultrafast THz sources. Typically, this results in impractically long acquisition times and a loss in resolution and contrast. These limitations make imaging of the objects in real-life scenarios impossible. Here, conclusively, the potential of state-of-the-art high-average power THz time-domain spectrometer (TDS), driven by a 100-W class, one-box ultrafast oscillator for imaging applications is shown by demonstrating lensless THz imaging in reflection mode of a dielectric sample with low reflectivity. Images obtained with our home-built 20-mW average power THz-TDS system show a significant contrast enhancement compared to a state-of-the-art commercial THz-TDS with less than 200 mu W of average power. Our unique setup even allows us to obtain images of such an object with high-contrast hidden inside a medium-density fiberboard (MDF) box. This opens the door to THz time-of-flight imaging of concealed objects of unknown shape and orientation in various real-life scenarios which were so far impossible to realize. |
2,639 | Bioefficacy of isolated compound l-isoleucine, N-allyloxycarbonyl-, and dodecyl ester from entomopathogenic actinobacteria Actinokineospora fastidiosa against agricultural insect pests, human vector mosquitoes, and antioxidant activities | Spodoptera litura and Helicoverpa armigera are polyphagous pests of agricultural crops in the Asian tropics since these pests have been responsible for massive crop and carry economic losses and low commodity production. At the same time, mosquitoes are vectors for numerous dreadful diseases, which is the most important group of insect for their public health concern. Using synthetic insecticides to control the pests can lead to contamination of land surface and groundwater and impact beneficial soil organisms and nontarget species. Applications of bioactive compounds are received considerable attention across the world as alternatives to synthetic insecticides. In the current study, actinobacterial secondary metabolite was isolated from Actinokineospora fastidiosa for the first time. The effect of actinobacterial metabolite (l-isoleucine, N-allyloxycarbonyl-, and dodecyl ester) was assessed on agricultural pest S. litura and H. armigera, mosquito vectors larvae Ae. aegypti, An. stephensi, and Cx. quinquefasciatus. The bioactive fraction was characterized through UV, FTIR, and NMR analysis. GC-MS analyses reveal the existence of a bioactive compound with a respective retention time of 19.740 responsible for larvicidal activity. The bioefficacy of the l-isoleucine, N-allyloxycarbonyl-, and dodecyl ester showed high antifeedant activity on S. litura (80.80%) and H. armigera (84.49%); and larvicidal activity on S. litura (82.77%) and H. armigera (88.00%) at 25 μg/mL concentration, respectively. The effective LC50 values were 8.07 μg/mL (F = 2.487, r2 = 0.988, P ≤ 0.05) on S. litura and 7.53 μg/mL (F = 123.25, r2 = 0.951, P ≤ 0.05) on H. armigera. The mosquito larvicidal effect of isolated compounds l-isoleucine, N-allyloxycarbonyl-, and dodecyl ester treated against Ae. aegypti, An. stephensi, and Cx. quinquefasciatus the obtained percentage mortality was 96.66, 83.24, 64.52, 50.00, and 40.00% against Ae. aegypti; 100.00, 86.22, 73.81, 65.37, and 56.24% against An. stephensi; 100.00, 90.00, 76.24, 68.75, and 56.23% against Cx. quinquefasciatus. The mosquito larvae of Ae. aegypti obtained LC50 value was 13.25 μg/mL, F = 28.50, r2 = 0.90; on An. stephensi was 10.19 μg/mL, F = 15.55, r2 = 0.83, and Cx. quinquefasciatus was 9.68 μg/mL, F = 20.00, r2 = 0.87. Furthermore, l-isoleucine-, N-allyloxycarbonyl-, and dodecyl ester-treated larvae produced significant pupicidal activity on S. litura (62.71%) and H. armigera (66.50%) at 25 μg/mL, along with increased larval and pupal duration as compared to control group. Treated larvae revealed obliteration in the midgut epithelial cells and destruction of microvilli was noticed as compared to the control. The isolated compounds l-isoleucine, N-allyloxycarbonyl-, and dodecyl ester did not produce any significant mortality on zebrafish embryos in all tested concentrations on biosafety observation. The potential microbial isolated molecule may fit well in IPM programs. Since the risk to human health, the environment, etc. is unknown. |
2,640 | Automated Skin Lesion Segmentation Via an Adaptive Dual Attention Module | We present a convolutional neural network (CNN) equipped with a novel and efficient adaptive dual attention module (ADAM) for automated skin lesion segmentation from dermoscopic images, which is an essential yet challenging step for the development of a computer-assisted skin disease diagnosis system. The proposed ADAM has three compelling characteristics. First, we integrate two global context modeling mechanisms into the ADAM, one aiming at capturing the boundary continuity of skin lesion by global average pooling while the other dealing with the shape irregularity by pixel-wise correlation. In this regard, our network, thanks to the proposed ADAM, is capable of extracting more comprehensive and discriminative features for recognizing the boundary of skin lesions. Second, the proposed ADAM supports multi-scale resolution fusion, and hence can capture multi-scale features to further improve the segmentation accuracy. Third, as we harness a spatial information weighting method in the proposed network, our method can reduce a lot of redundancies compared with traditional CNNs. The proposed network is implemented based on a dual encoder architecture, which is able to enlarge the receptive field without greatly increasing the network parameters. In addition, we assign different dilation rates to different ADAMs so that it can adaptively capture distinguishing features according to the size of a lesion. We extensively evaluate the proposed method on both ISBI2017 and ISIC2018 datasets and the experimental results demonstrate that, without using network ensemble schemes, our method is capable of achieving better segmentation performance than state-of-the-art deep learning models, particularly those equipped with attention mechanisms. |
2,641 | Factors Associated with Antiretroviral Therapy Toxicity Out-Comes in Patients with and without Hypertension | Background: Negative effects of antiretroviral therapy (ART) drugs on HIV/AIDS patients are one of the major health issues in the therapeutic treatment of this communicable disease. This holds particularly for people living with HIV (PLHIV) who might have a non-communicable disease (like hypertension), which also requires a lifetime treatment. In this study, we investigated the association between hypertension and other possible factors on ART toxicity markers in patients with hypertension, compared to those without hypertension. Methods: This retrospective longitudinal study reviewed chronic patient files of 525 patients (of which 222 were hypertensive) who satisfied the inclusion criteria and were on ART at a hospital in central Eswatini. Specific levels of estimated glomerular filtration (eGFR), alanine aminotransferase (ALT) and aspartate aminotransferase (AST) were used as drug toxicity markers. To analyze the longitudinal data between the exposure of interest and outcome variables, a Generalized Estimated Equation method was employed. Results: Participants with hypertension had decreased eGFR compared to those without hypertension (beta = -2.22; p-value = 0.03). There was no significant association between ALT, AST and hypertension (p-value = 0.34 and 0.20, respectively). Factors that were found to have a significant association with ART toxicity markers included age, sex, ART duration, hypertension treatment and time of study. The eGFR was found to be significantly increasing over the study period (p-value < 0.001) for all participants. The significance was consistent in both hypertensive and non-hypertensive participants independently (p-value = 0.002 and <0.001, respectively). The overall trends of ALT and AST over time were also significant (p-value = 0.003 and <0.001, respectively). Conclusions: Patients with hypertension had decreased eGFR, and there was a significant association of eGFR with time of the study. Special attention, therefore, to monitor calamities which are indicated by a decrease of eGFR (like renal impairment) should be given in PLHIV on ART with hypertension, especially more so if they were on ART for longer time. |
2,642 | Improved Zn bioavailability by its enhanced colocalization and speciation with S in wheat grain tissues after N addition | Zinc bioavailability with the presence of other elements in wheat grains might be affected by fertilizers. A long-term field experiment was conducted to examine effects of N fertilizer on Zn bioavailability in wheat grain tissues, with changes in the concentrations, distribution, and speciation of Zn as well as P and sulfur S via synchrotron-based technology. Results showed that addition of N fertilizer was associated with changes in Zn concentrations and distributions in grain tissues, especially in the crease region and endosperm. Simultaneously, N addition enhanced Zn-S colocalization in the crease region and endosperm and lowered the P/Zn ratio and Zn-P colocalization. Addition of N fertilizer with P increased Zn-cysteine (9.2%) and decreased Zn-phytate (47.3%) in the crease region, leading to potentially higher grain Zn bioavailability. Thus, addition of N fertilizer improved concentrations and bioavailability of Zn, by coordinating the relationships among Zn, P and S within wheat grains. |
2,643 | The immune response in the CNS in Theiler's virus induced demyelinating disease switches from an early adaptive response to a chronic innate-like response | Theiler's murine encephalomyelitis virus-induced demyelinating disease (TMEV-IDD) is an important model of the progressive disability caused by irreversible CNS tissue injury, and provides an example of how a CNS pathogen can cause inflammation, demyelination, and neuronal damage. We were interested in which molecules, especially inflammatory mediators, might be upregulated in the CNS throughout TMEV-IDD. We quantitated by a real-time RT-PCR multi-gene system the expression of a pathway-focused panel of genes at 30 and 165 days post infection, characterizing both the early inflammatory and the late neurodegenerative stages of TMEV-IDD. Also, we measured 32 cytokines/chemokines by multiplex Luminex analysis in CSF specimens from early and late TMEV-IDD as well as sham-treated mice. Results indicate that, in the later stage of TMEV-IDD, activation of the innate immune response is most prominent: TLRs, type I IFN response genes, and innate immunity-associated cytokines were highly expressed in late TMEV-IDD compared to sham (p ≤ 0.0001) and early TMEV-IDD (p < 0.05). Conversely, several molecular mediators of adaptive immune response were highly expressed in early TMEV-IDD (all p ≤ 0.001). Protein detection in the CSF was broadly concordant with mRNA abundance of the corresponding gene measured by real-time RT-PCR in the spinal cord, since several cytokines/chemokines were increased in the CSF of TMEV-IDD mice. Results show a clear shift from adaptive to innate immunity from early to late TMEV-IDD, indicating that adaptive and innate immune pathways are likely involved in the development and progression of the disease to different extents. CSF provides an optimal source of biomarkers of CNS neuroinflammation. |
2,644 | CLID: A Chunk-Level Intent Detection Framework for Multiple Intent Spoken Language Understanding | Multi-intent spoken language understanding (SLU) that can handle an utterance containing multiple intents is more practical and attracts increasing attention. However, existing state-of-the-art models are either too coarse-grained (Utterance-level) or too fine-grained (Token-level) in intent detection, and thus may fail to recognize the intent transition point and the correct intents in an utterance. In this paper, we propose a Chunk-Level Intent Detection (CLID) framework, where we introduce a sliding window-based self-attention (SWSA) scheme for regional chunk intent detection. Based on the SWSA, an auxiliary task is introduced to identify the intent transition point in an utterance and obtain sub-utterances with a single intent. The intent of each sub-utterance is then predicted by assembling the intent predictions of the chunks (in a sliding window manner) within it. We conduct experiments on two public datasets, MixATIS and MixSNIPS, and the results show that our model achieves state-of-the-art performance. |
2,645 | Super-Resolution via Image-Adapted Denoising CNNs: Incorporating External and Internal Learning | While deep neural networks exhibit state-of-the-art results in the task of image super-resolution (SR) with a fixed known acquisition process (e.g., a bicubic downscaling kernel), they experience a huge performance loss when the real observation model mismatches the one used in training. Recently, two different techniques suggested to mitigate this deficiency, i.e., enjoy the advantages of deep learning without being restricted by the training phase. The first one follows the plug-and-play (P&P) approach that solves general inverse problems (e.g., SR) by using Gaussian denoisers for handling the prior term in model-based optimization schemes. The second builds on internal recurrence of information inside a single image, and trains a super-resolver network at test time on examples synthesized from the low-resolution image. Our letter incorporates these two independent strategies, enjoying the impressive generalization capabilities of deep learning, captured by the first, and further improving it through internal learning at test time. First, we apply a recent P&P strategy to SR. Then, we show how it may become image-adaptive in test time. This technique outperforms the above two strategies on popular datasets and gives better results than other state-of-the-art methods in practical cases where the observation model is inexact or unknown in advance. |
2,646 | Digital Health Solutions to Reduce the Burden of Atherosclerotic Cardiovascular Disease Proposed by the CARRIER Consortium | Digital health is a promising tool to support people with an elevated risk for atherosclerotic cardiovascular disease (ASCVD) and patients with an established disease to improve cardiovascular outcomes. Many digital health initiatives have been developed and employed. However, barriers to their large-scale implementation have remained. This paper focuses on these barriers and presents solutions as proposed by the Dutch CARRIER (ie, Coronary ARtery disease: Risk estimations and Interventions for prevention and EaRly detection) consortium. We will focus in 4 sections on the following: (1) the development process of an eHealth solution that will include design thinking and cocreation with relevant stakeholders; (2) the modeling approach for two clinical prediction models (CPMs) to identify people at risk of developing ASCVD and to guide interventions; (3) description of a federated data infrastructure to train the CPMs and to provide the eHealth solution with relevant data; and (4) discussion of an ethical and legal framework for responsible data handling in health care. The Dutch CARRIER consortium consists of a collaboration between experts in the fields of eHealth development, ASCVD, public health, big data, as well as ethics and law. The consortium focuses on reducing the burden of ASCVD. We believe the future of health care is data driven and supported by digital health. Therefore, we hope that our research will not only facilitate CARRIER consortium but may also facilitate other future health care initiatives. |
2,647 | Sexualization of Children or Human Rights? Attitudes Toward Addressing Sexual-Orientation Diversity in School | Lesbian, gay, and bisexual (LGB) adolescents are more likely to experience mental health problems than their heterosexual peers because they are victimized more often or fear discrimination. Governmental plans to improve this situation by addressing sexual diversity in German schools have been accompanied by public resistance and misinformation, e.g., that they aim to sexualize children. The present study assessed how widespread negative attitudes toward such plans really are and how they can be explained. A random sample of 2,013 German residents was surveyed by phone. Only 10% opposed promoting acceptance of LGB in school. Approval of such plans was predominantly predicted by respondents' beliefs about sexual orientation and the plans' aim, and only marginally by societal values. Respondents who knew that the plans' aim was to promote acceptance of LGB and not to sexualize children and that children with same-sex parents are just as well off as those with heterosexual parents showed higher approval, whereas respondents who believed that homosexuality is affected by socialization showed higher opposition. |
2,648 | Plasma-Assisted Reforming of Methane | Methane (CH4 ) is inexpensive, high in heating value, relatively low in carbon footprint compared to coal, and thus a promising energy resource. However, the locations of natural gas production sites are typically far from industrial areas. Therefore, transportation is needed, which could considerably increase the sale price of natural gas. Thus, the development of distributed, clean, affordable processes for the efficient conversion of CH4 has increasingly attracted people's attention. Among them are plasma technology with the advantages of mild operating conditions, low space need, and quick generation of energetic and chemically active species, which allows the reaction to occur far from the thermodynamic equilibrium and at a reasonable cost. Significant progress in plasma-assisted reforming of methane (PARM) is achieved and reviewed in this paper from the perspectives of reactor development, thermal and nonthermal PARM routes, and catalysis. The factors affecting the conversion of reactants and the selectivity of products are studied. The findings from the past works and the insight into the existing challenges in this work should benefit the further development of reactors, high-performance catalysts, and PARM routes. |
2,649 | Ultrasensitive nanomechanical photonic sensor based on horizontal slot-waveguide resonator | A novel integrated nanomechanical optical sensor with ultrahigh sensitivity is presented. The photonic device consists of a silicon-based disk resonator formed by a horizontal slot-waveguide acting as a circular cantilever. The overall sensitivity results from the product of the sensitivities of the slot-waveguide and the disk resonator. Calculations indicate a sensitivity as high as 33 nm(-1), which is four orders of magnitude larger than that of state-of-the-art microcantilever sensors. |
2,650 | Medical Image Segmentation With Deep Atlas Prior | Organ segmentation from medical images is one of the most important pre-processing steps in computer-aided diagnosis, but it is a challenging task because of limited annotated data, low-contrast and non-homogenous textures. Compared with natural images, organs in the medical images have obvious anatomical prior knowledge (e.g., organ shape and position), which can be used to improve the segmentation accuracy. In this paper, we propose a novel segmentation framework which integrates the medical image anatomical prior through loss into the deep learning models. The proposed prior loss function is based on probabilistic atlas, which is called as deep atlas prior (DAP). It includes prior location and shape information of organs, which are important prior information for accurate organ segmentation. Further, we combine the proposed deep atlas prior loss with the conventional likelihood losses such as Dice loss and focal loss into an adaptive Bayesian loss in a Bayesian framework, which consists of a prior and a likelihood. The adaptive Bayesian loss dynamically adjusts the ratio of the DAP loss and the likelihood loss in the training epoch for better learning. The proposed loss function is universal and can be combined with a wide variety of existing deep segmentation models to further enhance their performance. We verify the significance of our proposed framework with some state-of-the-art models, including fully-supervised and semi-supervised segmentation models on a public dataset (ISBI LiTS 2017 Challenge) for liver segmentation and a private dataset for spleen segmentation. |
2,651 | Cumulative dual-branch network framework for long-tailed multi-class classification | The long-tailed data distribution problem (i.e., a few classes account for majority data, while most classes account for minority data) is widespread in large-scale and real-world datasets, and it poses a huge challenge to the computer vision field. Existing methods of long-tailed classification mainly focus on re-sampling, re-weighting, and transfer learning. Although class imbalance learning can yield better long-tailed classification performance, the feature representative ability of the feature extraction network is damaged to a certain extent. To deal with these issues, the present work proposes a novel cumulative dual-branch network framework (CDBNF), which takes into account the class imbalance learning and feature representation learning at the same time by the dual-branch network architecture. In CDBNF, the class imbalance learning branch greatly improves the classification performance of tail classes, while the few-shot learning branch enhances the feature representative ability. Furthermore, a cumulative learning strategy (CLS) is proposed in CDBNF to make it pay more attention to the tail classes gradually in the training process. The effectiveness and practicability of the proposed CDBNF are verified by the four benchmark datasets. Experimental results show that the classification performance of CDBNF is superior to other state-of-the-art methods, while the intra-class feature variance is smaller than other state-of-the-art methods. |
2,652 | Write Pattern Format Algorithm for Reliable NAND-Based SSDs | This brief presents and evaluates a pre-coding algorithm to reduce power consumption and improve data retention in NAND-based solid-state drives. Compared to the state-of-the-art asymmetric coding and stripe pattern elimination algorithm, the proposed write pattern format algorithm (WPFA) achieves better data retention while consuming less power. The hardware for WPFA is simpler and requires less circuitry. The performance of WPFA is evaluated by both computer simulations and field-programmable gate array implementation. |
2,653 | Endpoints for geroscience clinical trials: health outcomes, biomarkers, and biologic age | Treatments that target fundamental processes of aging are expected to delay several aging-related conditions simultaneously. Testing the efficacy of these treatments for potential anti-aging benefits will require clinical trials with endpoints that reflect the potential benefits of slowing processes of aging. There are several potential types of endpoints to capture the benefits of slowing a process of aging, and a consensus is needed to standardize and compare the results of these trials and to guide the analysis of observational data to support trial planning. Using biomarkers instead of clinical outcomes would substantially reduce the size and the duration of clinical trials. This requires validation of surrogate markers showing that treatment induced change in the marker reliably predicts the magnitude of change in the clinical outcome. The surrogate marker must also reflect the biological mechanism for the effect of treatment on the clinical outcome. "Biological age" is a superficially attractive marker for such trials. However, it is essential to establish that treatment induced change in biological age reliably predict the magnitude of benefits in the clinical outcome. Reaching consensus on clinical outcomes for geroscience trials and then validating potential surrogate biomarkers requires time, effort, and coordination that will be worthwhile to develop surrogate outcomes that can be trusted to efficiently test the value of many anti-aging treatments under development. |
2,654 | Online Design of Optimal Precoders for High Dimensional Signal Detection | In this paper, we propose a novel methodology to design optimal precoders for distributed detection of high-dimensional signals. We consider a wireless sensor network (WSN) that consists of multiple sensors that are spatially distributed in a region of interest and a fusion center (FC). The sensors observe an unknown high-dimensional signal and forward their observations to the FCafter precoding. The sensors collect data over both temporal and spatial domains. The FC performs a binary hypothesis test based on the data received fromthe sensors over noisy channels. In this setup, we present a technique to design optimal online linear precoding strategies with transmit power constraints. We show analytically that the error exponents achieved by the proposed precoders are independent of the signal dimension. In contrast, the error exponents of the state-of-the-art precoding strategies deteriorate with the increase in signal dimension. We verify our analysis via numerical simulations and show that the proposed precoders achieve better detection performance compared to those of other state-of-the-art techniques known in the literature. |
2,655 | Theory Integration for Examining Health Care Discrimination among Minoritized Older Adults with Chronic Illness | Prevalence of chronic illnesses, including type 2 diabetes (T2DM), is increasing disproportionately among Latinx adults in the United States. Health care inequities such as health care discrimination contribute to the disparities in this population. Academic and clinical nurses must address health care discrimination from a strong theoretical framework. In this article, we integrate the minority stress theory and ecosocial theory of disease distribution to offer a whole-person model that identifies the concepts most relevant to Latinx older adults who function at multiple levels of intersectionality. This paper uses T2DM as an exemplar of chronic illness. The integrated model depicts possible pathways of physiological and psychological embodiment of lived experiences of minoritized older persons managing chronic illness who are living in a society deeply embedded with structural racism and oppression. This model may guide future research aimed at elucidating the social and structural determinants that impact health-related outcomes among Latinx older adults. |
2,656 | Unveiling the "Proton Lubricant" Chemistry in Aqueous Zinc-MoS2 Batteries | Proton insertion chemistry in aqueous zinc-ion batteries (AZIBs) is becoming a research hotspot owing to its fast kinetics and additional capacities. However, H+ storage mechanism has not been deciphered in the popular MoS2 -based AZIBs. Herein, we innovatively prepared a MoS2 /poly(3,4-ethylenedioxythiophene) (MoS2 /PEDOT) hybrid, where the intercalated PEDOT not only increases the interlayer spacing (from 0.62 to 1.29 nm) and electronic conductivity of MoS2 , but also activates the proton insertion chemistry. Thus, highly efficient and reversible H+ /Zn2+ co-insertion/extraction behaviors are demonstrated for the first time in aqueous Zn-MoS2 batteries. More intriguingly, the co-inserted protons can act as lubricants to effectively shield the electrostatic interactions between MoS2 /PEDOT host and divalent Zn2+ , enabling the accelerated ion-diffusion kinetics and exceptional rate performance. This work proposes a new concept of "proton lubricant" driving Zn2+ transport and broadens the horizons of Zn-MoS2 batteries. |
2,657 | Consensus Head Acceleration Measurement Practices (CHAMP): Study Design and Statistical Analysis | Head impact measurement devices enable opportunities to collect impact data directly from humans to study topics like concussion biomechanics, head impact exposure and its effects, and concussion risk reduction techniques in sports when paired with other relevant data. With recent advances in head impact measurement devices and cost-effective price points, more and more investigators are using them to study brain health questions. However, as the field's literature grows, the variance in study quality is apparent. This brief paper aims to provide a high-level set of key considerations for the design and analysis of head impact measurement studies that can help avoid flaws introduced by sampling biases, false data, missing data, and confounding factors. We discuss key points through four overarching themes: study design, operational management, data quality, and data analysis. |
2,658 | DYNAMIC PLANNING AND DESIGN OF URBAN WATERFRONT LANDSCAPE BASED ON TIME SCALE | With the acceleration of the process of city and industrialization, human beings are facing greater challenges in landscaping activities aimed at environmental transformation and ecological protection. Urban architecture and landscape environment art are a complex. With the rapid development of social civilization, urban landscape environment art becomes more and more important. This paper makes a preliminary study on the related issues of urban waterfront landscape dynamic planning and design, introduces the specific conception of urban waterfront landscape dynamic planning and design from three aspects: spatial scale, time scale and plant arrangement, and shows the specific form of urban waterfront landscape planning and design. This paper puts forward the idea of landscape dynamic planning and overall planning of urban waterfront, and achieves the purpose of sustainable utilization by rationally developing urban waterfront. |
2,659 | Attribution Analysis of Foodborne Disease Outbreaks Related to Meat and Meat Products in China, 2002-2017 | This study aimed to understand the epidemiological characteristics of foodborne disease outbreaks related to meat and meat products in China from 2002 to 2017. Data collected from the National Foodborne Diseases Surveillance System and searched databases were analyzed. From 2002 to 2017, China reported 2815 outbreaks caused by foodborne diseases related to meat and meat products, resulting in 52,122 illnesses and 25,361 hospitalizations, and 96 deaths. Outbreaks were markedly seasonal and concentrated from May to September, accounting for 66.93%. Outbreaks were concentrated mainly in China's eastern coastal and southern regions. Unidimensional attribution analysis revealed that livestock meat was the most commonly implicated food category causing the outbreaks, accounting for 28.67%. Bacteria were the most common pathogenic cause of outbreaks, accounting for 51.94%. Clostridium botulinum was the most common pathogenic cause of death, accounting for 34.38%. Improper processing was the most common contributing factor, accounting for 27.89%. Households were the most common food preparation location causing the outbreak, accounting for 34.39%. Two-dimensional and multidimensional attribution analysis found that Salmonella contamination occurred in different locations and regions, mainly caused by various contributing factors and improper processing. Nitrite poisoning is caused by improper processing in households in East China. Bacterial causes were the commonest agents associated with foodborne diseases related to meat and meat products, and improving the safety and quality of meat and meat product should be a priority. |
2,660 | Fast interactive stereo image segmentation | The paper presents an approach to cutting out the same target object from a pair of stereo images interactively. With this approach, a user labels parts of the object and background in either of the images with strokes. The approach generates a segmentation result immediately. In case it is not satisfying, the result can be improved by interactively drawing more strokes, or using an alternative interaction way called adding corresponding points, which is first presented in this paper. The proposed segmentation approach is capable of providing feedback fast after each interaction. The fast computation is performed in the framework of graph cut. First, the labeled parts are used to learn foreground and background color models. Next, an energy function is built by formulating the similarities between unlabeled pixels and the foreground/background color models, color difference between neighbor pixels, and stereo correspondences obtained by SIFT feature matching. At last, graph cut is utilized to find the optimum of the energy function and obtain a segmentation result. Different from state-of-the-art methods, our segmentation approach formulates sparse correspondences rather than dense matches as stereo constraints in the energy function. Experimental results demonstrate that our method is faster in computation. In the meanwhile, it generates comparable results with state-of-the-art methods. |
2,661 | Modulation Classification via Gibbs Sampling Based on a Latent Dirichlet Bayesian Network | A novel Bayesian modulation classification scheme is proposed for a single-antenna system over frequency-selective fading channels. The method is based on Gibbs sampling as applied to a latent Dirichlet Bayesian network (BN). The use of the proposed latent Dirichlet BN provides a systematic solution to the convergence problem encountered by the conventional Gibbs sampling approach for modulation classification. The method generalizes, and is shown to improve upon, the state of the art. |
2,662 | Nonlinear Load Harmonic Mitigation Strategies in Microgrids: State of the Art | A generational shift has led to the evolution of distributed generation (DG) and microgrids. The loads connected in a microgrid can be both linear and nonlinear. Nonlinear loads deteriorate the power quality by drawing harmonic currents. Drawing of nonlinear currents will make the voltage waveform nonsinusoidal, which may prove harmful for other loads connected to the system. Previously, passive and active filters were used to mitigate harmonics, but they are expensive and bulky. The state of the art is to exploit multifunctional capabilities of inverter-interfaced DGs to deal with the power quality issues. This article presents the typical sources of generation of the harmonics, their deleterious effects, available standards, and detection techniques. Harmonic mitigation strategies for both grid-connected and islanded microgrids have been discussed in detail. The aim is to review and categorize the various strategies adopted by authors in recent times to mitigate harmonics and bring out the research gaps so that further avenues can be explored in this area. |
2,663 | Real-time video stabilization via camera path correction and its applications to augmented reality on edge devices | With the rapid development of edge devices such as mobile phones, in the past decade, many videos have appeared on the professional video website and they are easy to retrieve. However, most of the videos captured by mobile cameras are jittery, and even motion blurred. These low-quality videos may affect the experience of users. Thus, the problem that how to eliminate the jittery issues, and make unstable video became stable one is very urgent. To enhance the stability of low-quality video, in this paper, we propose a novel method for video stabilization. The proposed method is called SimpleStab, and consists of motion estimation, trajectory smoothing, and compositing image. The SimpleStab is not only able to process offline videos but also can deal with live video streaming due to the novel architecture. We conduct a comprehensive experiment on the benchmarking dataset and make comparison with the state-of-the-art approaches. Experimental results show that the performance of SimpleStab is superior to the state-of-the-art methods. |
2,664 | Prototype of a pigments color chart for the digital conservation of ancient murals | Digital imaging has become a very important technique in the conservation of cultural art relics because it can nondestructively acquire the color and spectral image of cultural art relics for different applications. Imaging accuracy is one of the key factors in digital protection of cultural art relics. In order to improve the color and spectral accuracy for digital imaging of cultural art relics, the idea of making the specific color charts for different kinds of artworks is presented. Taking ancient Chinese Dunhuang murals as the specific object of study, a prototype pigments color chart of the Dunhuang murals (DCC), containing a six-step grayscale and 30 colored pigment samples, is made to investigate its pigment types and painting techniques. Under the premise of considering the difference in the number of samples in color charts, the DCC is tested and compared with the classic and widely used standard Macbeth colorchecker (CC) in two aspects: color correction for RGB imaging and spectral reconstruction for spectral imaging. The results show that the prototype pigments color chart is more effective and exhibits superior performance to the CC in both aspects for digital conservation of the Dunhuang murals. (C) 2017 SPIE and IS&T |
2,665 | Single-Antenna Coherent Detection of Collided FM0 RFID Signals | This work derives and evaluates single-antenna detection schemes for collided radio frequency identification (RFID) signals, i.e. simultaneous transmission of two RFID tags, following FM0 (biphase-space) encoding. In sharp contrast to prior art, the proposed detection algorithms take explicitly into account the FM0 encoding characteristics, including its inherent memory. The detection algorithms are derived when error at either or only one out of two tags is considered. It is shown that careful design of one-bit-memory two-tag detection can improve bit-error-rate (BER) performance by 3dB, compared to its memoryless counterpart, on par with existing art for single-tag detection. Furthermore, this work calculates the total tag population inventory delay, i.e. how much time is saved when two-tag detection is utilized, as opposed to conventional, single-tag methods. It is found that two-tag detection could lead to significant inventory time reduction (in some cases on the order of 40%) for basic framed-Aloha access schemes. Analytic calculation of inventory time is confirmed by simulation. This work could augment detection software of existing commercial RFID readers, including single-antenna portable versions, without major modification of their RF front ends. |
2,666 | Remove Cosine Window From Correlation Filter-Based Visual Trackers: When and How | Correlation filters (CFs) have been continuously advancing the state-of-the-art tracking performance and have been extensively studied in the recent few years. Nonetheless, the existing CF trackers adopt a cosine window to spatially reweight base image to alleviate boundary discontinuity. However, cosine window emphasizes more on the central regions of base image and has the risk of contaminating negative training samples during model learning. On the other hand, spatial regularization deployed in many recent CF trackers plays a similar role as cosine window by enforcing spatial penalty on CF coefficients. Therefore, we in this paper investigate the feasibility to remove cosine window from CF trackers with spatial regularization. When simply removing cosine window, CF with spatial regularization still suffers from small degree of boundary discontinuity. To tackle this issue, binary and Gaussian shaped mask functions are further introduced for eliminating boundary discontinuity while reweighting the estimation error of each training sample, and can be incorporated with multiple CF trackers with spatial regularization. In comparison to the baseline methods with cosine window, our methods are effective in handling boundary discontinuity and sample contamination, thereby benefiting tracking performance. Extensive experiments on four benchmarks show that our methods perform favorably against the state-of-the-art trackers using either handcrafted or deep CNN features. |
2,667 | Driver attention prediction based on convolution and transformers | In recent years, studying how drivers allocate their attention while driving is critical in achieving human-like cognitive ability for autonomous vehicles. And it has been an active topic in the community of human-machine augmented intelligence for self-driving. However, existing state-of-the-art methods for driver attention prediction are mainly built upon convolutional neural network (CNN) with local receptive field which has a limitation to capture the long-range dependencies. In this work, we propose a novel Attention prediction method based on CNN and Transformer which is termed as ACT-Net. In particular, CNN and Transformer are combined as a block which is further stacked to form the deep model. Through this design, both local and long-range dependencies are captured that both are crucial for driver attention prediction. Exhaustive comparison experiments over other state-of-the-art techniques conducted on widely used dataset of BDD-A and private collected data on BDD-X validate the effectiveness of the proposed ACT-Net. |
2,668 | PSW statistical LSB image steganalysis | Steganography is the art and science of producing covert communications by concealing secret messages in apparently innocent media, while steganalysis is the art and science of detecting the existence of these. This manuscript proposes a novel blind statistical steganalysis technique to detect Least Significant Bit (LSB) flipping image steganography. It shows that the technique has a number of major advantages. First, a novel method of pixel color correlativity analysis in Pixel Similarity Weight (PSW). Second, filtering out image pixels according to their statistically detected suspiciousness, thereby excluding neutral pixels from the steganalysis process. Third, ranking suspicious pixels according to their statistically detected suspiciousness and determining the influence of such pixels based on the level of detected anomalies. Fourth, the capability to classify and analyze pixels in three pixel classes of flat, smooth and edgy, thereby enhancing the sensitivity of the steganalysis. Fifth, achieving an extremely high efficiency level of 98.049% in detecting 0.25bpp stego images with only a single dimension analysis. |
2,669 | Paradoxical self-sustained dynamics emerge from orchestrated excitatory and inhibitory homeostatic plasticity rules | Self-sustained neural activity maintained through local recurrent connections is of fundamental importance to cortical function. Converging theoretical and experimental evidence indicates that cortical circuits generating self-sustained dynamics operate in an inhibition-stabilized regime. Theoretical work has established that four sets of weights (WE←E, WE←I, WI←E, and WI←I) must obey specific relationships to produce inhibition-stabilized dynamics, but it is not known how the brain can appropriately set the values of all four weight classes in an unsupervised manner to be in the inhibition-stabilized regime. We prove that standard homeostatic plasticity rules are generally unable to generate inhibition-stabilized dynamics and that their instability is caused by a signature property of inhibition-stabilized networks: the paradoxical effect. In contrast, we show that a family of "cross-homeostatic" rules overcome the paradoxical effect and robustly lead to the emergence of stable dynamics. This work provides a model of how-beginning from a silent network-self-sustained inhibition-stabilized dynamics can emerge from learning rules governing all four synaptic weight classes in an orchestrated manner. |
2,670 | Exploring Malaysian Physicians' Intention to Discriminate Against Gay, Bisexual, and Other Men Who Have Sex with Men Patients | Purpose: Gay, bisexual, and other men who have sex with men (MSM) experience high levels of stigma and discrimination. Minimizing the stigma and discrimination is critical to fostering an inclusive environment for care and optimizing health outcomes. This study aimed at exploring the factors related to physicians' intention to discriminate against MSM in Malaysia. Methods: Physicians (N = 542) from two university-affiliated hospitals in Kuala Lumpur, Malaysia, completed an online cross-sectional survey between January and March 2016. Measures included sociodemographic and clinical characteristics, intention to discriminate against MSM, and several stigma-related constructs. Bivariate and multivariable linear regressions were used to evaluate independent correlates of discrimination intent against MSM. Results: Physicians' intention to discriminate against MSM was low (mean [M] = 1.9, standard deviation [SD] = 0.7), but most physicians (70.6%) had a mean score greater than 1.0, indicating that most physicians expressed some degree of intention to discriminate against MSM. A minority of physicians (10.7%), however, had a score of 3.0 or higher, revealing some physicians holding a moderate to high level of discrimination intent toward MSM. The multivariable model demonstrated that physicians who expressed greater prejudice (B = 0.30, p < 0.01), had more MSM-related shame (B = 0.19, p < 0.01), and fear about MSM (B = 0.31, p < 0.01) were more likely to have the intention to discriminate against MSM. Conclusion: Stigma-related constructs including prejudice, MSM-related shame, and fear were independently correlated with increases in a physician's intention to discriminate against MSM. Therefore, implementing interventions to reduce physicians' stigma toward MSM may promote equitable and stigma-free access to health care. |
2,671 | A patent analysis on advanced biohydrogen technology development and commercialisation: Scope and competitiveness | The need of developing renewable energy to reduce the impact on the global environment and climate change of the increasing industrial development has fostered the use of biological processes to produce biofuel from biohydrogen. The present work made a patent analysis of advanced hydrogen production techniques comparing it with similar prior art in China, Japan, the Republic of Korea, the European Union and the United States (U.S.) The aims were to find the scope, competitiveness of prior art, as well as the technology trend on biohydrogen production methods. The patents value was assessed its geographic scope and competitiveness indicators such as green image, low cost, energy efficiency and equipment design. It was found that most of the hydrogen production methods and associated technologies are developed by academic institutions, however their patents are reduced to a local level, and few are patented at international level, which reduces their competitiveness. The China (P.R.C.) is the biggest patent contributor worldwide in terms of hydrogen production methods by academic institutions. Japan is a huge patent contributor, in terms of methods aiming rear-end products application of hydrogen by private companies. The biggest amount of prior art found that the most popular methods of pretreatment and dark fermentation produced coincide with the time of energetic crisis and the green movement to find alternative fuels. Finally, patent analysis of this study can help to discern the current technology trend and to develop the next generation of biohydrogen processes and associated technologies. Copyright (C) 2011, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved. |
2,672 | An Efficient Visibility Enhancement Algorithm for Road Scenes Captured by Intelligent Transportation Systems | The visibility of images of outdoor road scenes will generally become degraded when captured during inclement weather conditions. Drivers often turn on the headlights of their vehicles and streetlights are often activated, resulting in localized light sources in images capturing road scenes in these conditions. Additionally, sandstorms are also weather events that are commonly encountered when driving in some regions. In sandstorms, atmospheric sand has a propensity to irregularly absorb specific portions of a spectrum, thereby causing color-shift problems in the captured image. Traditional state-of-the-art restoration techniques are unable to effectively cope with these hazy road images that feature localized light sources or color-shift problems. In response, we present a novel and effective haze removal approach to remedy problems caused by localized light sources and color shifts, which thereby achieves superior restoration results for single hazy images. The performance of the proposed method has been proven through quantitative and qualitative evaluations. Experimental results demonstrate that the proposed haze removal technique can more effectively recover scene radiance while demanding fewer computational costs than traditional state-of-the-art haze removal techniques. |
2,673 | Locally Structured On-Chip Optofluidic Hollow-Core Light Cages for Single Nanoparticle Tracking | Nanoparticle tracking analysis (NTA) is a widely used methodology to investigate nanoscale systems at the single species level. Here, we introduce the locally structured on-chip optofluidic hollow-core light cage, as a novel platform for waveguide-assisted NTA. This hollow waveguide guides light by the antiresonant effect in a sparse array of dielectric strands and includes a local modification to realize aberration-free tracking of individual nano-objects, defining a novel on-chip solution with properties specifically tailored for NTA. The key features of our system are (i) well-controlled nano-object illumination through the waveguide mode, (ii) diffraction-limited and aberration-free imaging at the observation site, and (iii) a high level of integration, achieved by on-chip interfacing to fibers. The present study covers all aspects relevant for NTA including design, simulation, implementation via 3D nanoprinting, and optical characterization. The capabilities of the approach to precisely characterize practically relevant nanosystems have been demonstrated by measuring the solvency-induced collapse of a nanoparticle system which includes polymer brush-based shells that react to changes in the liquid environment. Our study unlocks the advantages of the light cage approach in the context of NTA, suggesting its application in various areas such as bioanalytics, life science, environmental science, or nanoscale material science in general. |
2,674 | More Robust and Reliable Optimized Energy Conversion Facilitated through Electric Machines, Power Electronics and Drives, and Their Control: State-of-the-Art and Trends | According to the special section entitled 'Robust design and analysis of electric machines and drives', to be published in IEEE Transactions on Energy Conversion, the authors present an introduction to tolerance analysis, robust optimization, and measures to improve the reliability of electric machines, power electronics and drives, and their robust control in general. A comprehensive review of modeling uncertainties and evaluating robustness and reliability based measures is presented. In addition, techniques facilitating solving dedicated optimization scenarios are introduced. The most recent research activities will be illustrated. The article thus enables to easily catch up with the state-of-the-art in these fields and to take notice of ongoing and future work. |
2,675 | Investigating Generalized Performance of Data-Constrained Supervised Machine Learning Models on Novel, Related Samples in Intrusion Detection | Recently proposed methods in intrusion detection are iterating on machine learning methods as a potential solution. These novel methods are validated on one or more datasets from a sparse collection of academic intrusion detection datasets. Their recognition as improvements to the state-of-the-art is largely dependent on whether they can demonstrate a reliable increase in classification metrics compared to similar works validated on the same datasets. Whether these increases are meaningful outside of the training/testing datasets is rarely asked and never investigated. This work aims to demonstrate that strong general performance does not typically follow from strong classification on the current intrusion detection datasets. Binary classification models from a range of algorithmic families are trained on the attack classes of CSE-CIC-IDS2018, a state-of-the-art intrusion detection dataset. After establishing baselines for each class at various points of data access, the same trained models are tasked with classifying samples from the corresponding attack classes in CIC-IDS2017, CIC-DoS2017 and CIC-DDoS2019. Contrary to what the baseline results would suggest, the models have rarely learned a generally applicable representation of their attack class. Stability and predictability of generalized model performance are central issues for all methods on all attack classes. Focusing only on the three best-in-class models in terms of interdataset generalization, reveals that for network-centric attack classes (brute force, denial of service and distributed denial of service), general representations can be learned with flat losses in classification performance (precision and recall) below 5%. Other attack classes vary in generalized performance from stark losses in recall (-35%) with intact precision (98+%) for botnets to total degradation of precision and moderate recall loss for Web attack and infiltration models. The core conclusion of this article is a warning to researchers in the field. Expecting results of proposed methods on the test sets of state-of-the-art intrusion detection datasets to translate to generalized performance is likely a serious overestimation. Four proposals to reduce this overestimation are set out as future work directions. |
2,676 | Comparative studies of soluble and immobilized Fe(III) heme-peptide complexes as alternative heterogeneous biocatalysts | Fe(III) heme is known to possess low catalytic activity when exposed to hydrogen peroxide and a reducing substrate. Efficient non-covalently linked Fe(III) heme-peptide complexes may represent suitable alternatives as a new group of green catalysts. Here, we evaluated a set of heme-peptide complexes by determination of their peroxidase-like activity and the kinetics of the catalytic conversion in both, the soluble and the immobilized state. We show the impact of peptide length on binding of the peptides to Fe(III) heme and the catalytic activity. Immobilization of the peptide onto a polymer support maintains the catalytic performance of the Fe(III) heme-peptide complex. This study thus opens up a new perspective with regard to the development of heterogeneous biocatalysts with a peroxidase-like activity. |
2,677 | Crude oil associated heavy metals (HMs) contamination in agricultural land: Understanding risk factors and changes in soil biological properties | Ecological and human risks of crude oil associated heavy metals (HMs) in the contaminated agricultural lands were evaluated employing different indices. The indices that were employed includes enrichment factor (EF), contamination factor (Cf),pollution load index (PLI), geo-accumulation index (Igeo), ecological risk index (ERI), contamination degree (Cd), Nemerow's pollution index (PN), exposure factor (ExF), hazard quotient (HQ) and hazard index (HI). Besides, the adverse effects of crude oil associated HMs on the soil biological properties were also analyzed. The results of Cf and EF were found consistent with each other showing the HMs in the decreasing order of contamination as Mn > Zn > Cr > Ni > Cu. The Igeo and ERI fall in the grade (Igeo>5) and (ERI ≥40) respectively. The results of PLI, Cd, PN and ExF values clearly indicate a high environmental risk of crude oil-associated HMs. The results of the human health risks assessment revealed the maximum level of HMs enters the body via ingestion. There were significant(p < 0.05) decreases (5.7-15.5 folds) in the activities of cellulase (0.194 ± 0.02-0.998 ± 0.1), phosphatase (0.173 ± 0.3-0.612 ± 1.5), catalase (0.328 ± 0.3-2.036 ± 1.5), urease (0.44 ± 0.3-1.80 ± 1.2), dehydrogenase (0.321 ± 0.2-0.776 ± 0.7),polyphenol oxidase (0.21 ± 0.5-0.89 ± 2.5)and peroxidase (0.13 ± 0.4-0.53 ± 1.03)in crude oil-contaminated soil. The Pearson's correlation confirmed the significant negative impact of HMs on the soil's biological properties. |
2,678 | Complete Neurologic Recovery of Cerebral Fat Embolism Syndrome in Sickle Cell Disease | Sickle cell disease is one of the most common inherited hemoglobinopathies diagnosed in the United States. Patients often present with severe anemia, pain crises, infections, and vaso-occlusive phenomena. Complications of these disorders can lead to significant debilitating morbidity and mortality. Fat embolism syndrome (FES) is a rare and devastating complication of sickle cell disease. It usually presents with a rapidly deteriorating clinical course, and the prognosis is dismal. We report a case of FES in a 19-year-old African American male with a history of sickle cell disease who presented with tonic-clonic seizures and was found to have multi-organ failure. FES was diagnosed 20 days from a presentation based on blood cytopenias and magnetic resonance imaging findings that were obscured at the initial presentation. We describe in this report, the patient's course from presentation until diagnosis and resolution. Our case is peculiar as the patient had a very good outcome without the need for red blood cell (RBC) exchange; instead, supportive treatment and simple RBC transfusions were enough to change the clinical course of this almost fatal syndrome. |
2,679 | Mesenteric Ischemia in Patients with Coronavirus 2019: A Scoping Review | Background: Coronavirus 2019 (COVID-19) is a systemic disease associated with severe gastrointestinal complications including life-threatening mesenteric ischemia. We sought to review and summarize the currently available literature on the presentation, management, and outcomes of mesenteric ischemia in patients with COVID-19. Patients and Methods: The PubMed database was searched to identify studies published between January 2020 and January 2021 that reported one or more adult (≥18 years) patients with COVID-19 who developed mesenteric ischemia during hospitalization. The demographic characteristics, clinical and imaging findings, management, and outcomes of patients from each study were extracted and summarized. Results: A total of 35 articles reporting on 61 patients with COVID-19 with mesenteric ischemia met the eligibility and were included in our study. The mean age was 60 (±15.9) years, and 53% of patients were male. Imaging findings of these patients included mesenteric arterial or venous thromboembolism, followed by signs of mesenteric ischemia. Sixty-seven percent of patients were taken to the operating room for an exploratory laparotomy and bowel resection and 21% were managed conservatively. The terminal ileum was the most commonly involved area of necrosis (26%). The mortality rate of patients with COVID-19 with mesenteric ischemia was 33%, and the most common cause of death was multiorgan failure or refractory septic shock. Twenty-seven percent of patients managed operatively died during the post-operative period. Conclusions: Mesenteric ischemia in patients with COVID-19 is a devastating complication associated with a high rate of morbidity and mortality. Further efforts should focus on developing strategies for early recognition and management. |
2,680 | Antimicrobial Shape Memory Polymer Hydrogels for Chronic Wound Dressings | Chronic wounds can remain open for several months and have high risks of amputation due to infection. Dressing materials to treat chronic wounds should be conformable for irregular wound geometries, maintain a moist wound bed, and reduce infection risks. To that end, we developed cytocompatible shape memory polyurethane-based poly(ethylene glycol) (PEG) hydrogels that allow facile delivery to the wound site. Plant-based phenolic acids were physically incorporated onto the hydrogel scaffolds to provide antimicrobial properties. These materials were tested to confirm their shape memory properties, cytocompatibility, and antibacterial properties. The incorporation of phenolic acids provides a new mechanism for tuning intermolecular bonding in the hydrogels and corollary mechanical and shape memory properties. Phenolic acid-containing hydrogels demonstrated an increased shape recovery ratio (1.35× higher than the control formulation), and materials with cytocompatibility >90% were identified. Antimicrobial properties were retained over 20 days in hydrogels with higher phenolic acid content. Phenolic acid retention and antimicrobial efficacy were dependent upon phenolic acid structures and interactions with the polymer backbone. This novel hydrogel system provides a platform for future development as a chronic wound dressing material that is easy to implant and reduces infection risks. |
2,681 | Efficient Implementation of Adaptive Interpolation Filters for Low Complexity Video Coding | This paper presents novel methods for implementing adaptive interpolation filtering techniques for video coding on 16-bit integer architectures. The proposed methods offer significant complexity reduction over the state-of-the-art, making, them especially valuable for resource constrained mobile multimedia devices, with high coding efficiency.(1) |
2,682 | Prehistoric charcoal drawings in the caves in the Slovak Republic, Central Europe: Successful radiocarbon dating by a micro-sample C-14 AMS | In Central Europe, only a few caves with ancient drawings on the walls are known. During the past years, simple lines and sketches made of charcoal or smearing traces from torches are found mainly in less accessible locations in some caves of the Slovak Karst. Previous attempts to date these findings were unsuccessful since the painted layers were too thin to allow sampling and enable routine AMS dating. Now the application of the small mass radiocarbon accelerator mass-spectrometry (AMS) technique developed at the Australian Nuclear Science and Technology Organisation (ANSTO) made possible successful C-14 determinations for a set of cave drawings and markings from the Slovak Karst. This research confirmed the prehistoric/protohistoric nature of the drawings/sketches in Uikova Diera, Silicka Ladnica, Ardovska and Domica Caves. Moreover, this research widens the scope for prehistoric rock art dating, one of the major constrains in rock art studies. |
2,683 | Bangla-BERT: Transformer-Based Efficient Model for Transfer Learning and Language Understanding | The advent of pre-trained language models has directed a new era of Natural Language Processing (NLP), enabling us to create powerful language models. Among these models, Transformer-based models like BERT have grown in popularity due to their cutting-edge effectiveness. However, these models heavily rely on resource-intensive languages, forcing other languages into multilingual models(mBERT). The two fundamental challenges with mBERT become significantly more challenging in a resource-constrained language like Bangla. It was trained on a limited and organized dataset and contained weights for all other languages. Besides, current research on other languages suggests that a language-specific BERT model will exceed multilingual ones. This paper introduces Bangla-BERT,a a monolingual BERT model for the Bangla language. Despite the limited data available for NLP tasks in Bangla, we perform pre-training on the largest Bangla language model dataset, BanglaLM, which we constructed using 40 GB of text data. Bangla-BERT achieves the highest results in all datasets and vastly improves the state-of-the-art performance in binary linguistic classification, multilabel extraction, and named entity recognition, outperforming multilingual BERT and other previous research. The pre-trained model is assessed against several non-contextual models such as Bangla fasttext and word2vec the downstream tasks. Finally, this model is evaluated by transfer learning based on hybrid deep learning models such as LSTM, CNN, and CRF in NER, and it is observed that Bangla-BERT outperforms state-of-the-art methods. The proposed Bangla-BERT model is assessed by using benchmark datasets, including Banfakenews, Sentiment Analysis on Bengali News Comments, and Cross-lingual Sentiment Analysis in Bengali. Finally, it is concluded that Bangla-BERT surpasses all prior state-of-the-art results by 3.52%, 2.2%, and 5.3%. |
2,684 | A Model of Population and Subject (MOPS) Intensities With Application to Multiple Sclerosis Lesion Segmentation | White matter (WM) lesions are thought to play an important role in multiple sclerosis (MS) disease burden. Recent work in the automated segmentation of white matter lesions from magnetic resonance imaging has utilized a model in which lesions are outliers in the distribution of tissue signal intensities across the entire brain of each patient. However, the sensitivity and specificity of lesion detection and segmentation with these approaches have been inadequate. In our analysis, we determined this is due to the substantial overlap between the whole brain signal intensity distribution of lesions and normal tissue. Inspired by the ability of experts to detect lesions based on their local signal intensity characteristics, we propose a new algorithm that achieves lesion and brain tissue segmentation through simultaneous estimation of a spatially global within-the-subject intensity distribution and a spatially local intensity distribution derived from a healthy reference population. We demonstrate that MS lesions can be segmented as outliers from this intensity model of population and subject. We carried out extensive experiments with both synthetic and clinical data, and compared the performance of our new algorithm to those of state-of-the art techniques. We found this new approach leads to a substantial improvement in the sensitivity and specificity of lesion detection and segmentation. |
2,685 | Evaluating Snow Bidirectional Reflectance of Models Using Multiangle Remote Sensing Data and Field Measurements | Because of the anisotropy of snow surface reflectance, it is essential to select a proper snow bidirectional reflectance model for extracting snow cover and inverting snow properties from remote sensing image, especially during the period of snow rapidly changed. In this letter, the ability of reproducing snow bidirectional reflectance by three semiempirical bidirectional reflectance distribution function (BRDF) models (Ross-Li, Roujean, and Raman-Pinty-Verstraete) and the asymptotic radiative transfer theory (ART) model was evaluated using the polarization and directionality of the earth reflectance (POLDER) data. In addition, the ART model was compared with the bicontinuous geometric optics (bic-GORT) model based on field measurements. The results indicated that the root mean square errors (RMSEs) are small and similar for all models during the stable-snow period. The physical models perform better than the semiempirical models in capturing the bidirectional signatures of snow during the periods of snow rapidly changed. The bic-GORT model achieves higher accuracy, while the ART model holds the advantages of simple and efficient to be used. |
2,686 | Context-Aware Guided Attention Based Cross-Feedback Dense Network for Hyperspectral Image Super-Resolution | Convolutional neural networks (CNNs) have shown impressive performance in computer vision due to their nonlinearity. Particularly, DenseNet (DN) that facilitates feature reuse in a feedforward (FF) manner has achieved state-of-the-art reconstruction accuracy for super-resolution (SR). However, most DN-based SR models transfer the features generated from each layer to all the subsequent layers, inevitably introducing redundancy, especially for high-dimensional hyperspectral (HS) images. To tackle this problem, we propose a two-branch cross-feedback dense network with context-aware guided attention (CFDcagaNet) for HS super-resolution (HSSR), which allows the network to learn the attention maps of high-level features and refine the low-level features in a feedback (FB) manner across two branches. Context-aware guided attention (CAGA) uses high-level posterior information to provide more faithful spatial-spectral guidance for low-level features, which enables CFDcagaNet to learn more effective spatial-spectral features at low levels and yield more effective spatial-spectral transfer in the network. Extensive experiments on widely used datasets demonstrate that the proposed method outperforms state-of-the-art methods in terms of both quantitative values and visual qualities. |
2,687 | A Facile Structural Isomerization-Induced 3D Spatial D-A Interlocked Network for Achieving NIR-II Phototheranostic Agents | The performances of second near-infrared (NIR-II) organic phototheranostic agents (OPTAs) depend on both molecular structure and molecular packing when used as nanoparticles (NPs). Herein, we proposed a facile structural isomerization-induced 3D spatial donor (D)-acceptor (A) interlocked network for achieving NIR-II OPTAs. Two isomers, 4MNVDPP and 6MNVDPP were synthesized and formulated into NPs. 6MNVDPP, which has a larger electrostatic potential difference, exhibits a compact 3D spatial D-A interlocked network in the crystal form, while 4MNVDPP forms 2D D-D type J-aggregates. Thus, 6MNVDPP NPs show red-shifted NIR absorption and larger molar extinction coefficient than 4MNVDPP NPs. Thanks to the typical NIR-II emission, superior photothermal-stability, high photothermal conversion efficiency (89 %) and reactive oxygen species production capacity, 6MNVDPP NPs exhibit outstanding NIR-II tiny capillary vasculature/tumor imaging ability and synergistic photothermal/photodynamic anti-cancer effect in vivo. |
2,688 | ART artificial neural networks based adaptive phase selector | This paper introduces a new phase selector based on adaptive resonance theory (ART). Because conventional phase selector cannot adapt dynamically to the power system operating conditions, it presents different characters under different power system conditions. To overcome the disadvantage, an adaptive phase selector, which utilizes artificial neural network based on ART, is designed. ART based neural network (ARTNN) has some advantages such as no local extremum, quickly convergence and so on. Therefore, the proposed ARTNN based phase selector has better performances compared with other neural networks based phase selector, and the new selector can adapt dynamically to the varying power system operation conditions. Furthermore, the phase selector can be trained and learned on-line. A lot of EMTP simulations and experimental field data tests have illustrated the phase selector's correctness and effectiveness. (C) 2005 Elsevier B.V. All rights reserved. |
2,689 | A Video Steganalytic Approach Against Quantized Transform Coefficient-Based H.264 Steganography by Exploiting In-Loop Deblocking Filtering | This article presents a method for detection of H.264 steganographic algorithms that modulate quantized transform coefficients (QTCs) for data hiding. The in-loop deblocking filter specified in the H.264 standard is used for attenuating the discontinuities at coded block boundaries. However, our investigation indicates that the deblocking filtering process would probably be affected by QTC modification. Therefore, we suggest performing steganalysis by considering the influence of QTC modification on filtering decisions and filtering operations. In the filtering of luma block edges, for each luma sample, we try to obtain the cumulative amount of modification applied to it caused by filtering operations, and determine the frequency of the modification made to its sample value. Based on this, a 768-dimensional feature set is designed for training and classification. Extensive experiments were conducted under a range of setups to evaluate the effectiveness of the proposed method. The corresponding experimental results demonstrate that, compared with the prior art, our proposed method is generally capable of providing superior performance on detecting QTC modification in H.264 video, even at low embedding strengths. |
2,690 | POST-FILTERING WITH SURFACE ORIENTATION CONSTRAINTS FOR STEREO DENSE IMAGE MATCHING | Dense image matching (DIM) is a critical technique when computing accurate 3D geometric information for many photogrammetric applications. Most DIM methods adopt first-order regularisation priors for efficient matching, which often introduce stepped biases (also called fronto-parallel biases) into the matching results. To remove these biases and compute more accurate matching results, this paper proposes a novel post-filtering method by adjusting the surface orientation of each pixel in the matching process. The core algorithm formulates the post-filtering as the optimisation of a global energy function with second-order regularisation priors. A compromise solution of the energy function is computed by breaking the optimisation into a collection of sub-optimisations of each pixel in a local adaptive window. The proposed method was compared with several state-of-the-art post-filtering methods on indoor, aerial and satellite datasets. The comparisons demonstrate that the proposed method obtains the highest post-filtering accuracies on all datasets. |
2,691 | A Comparative Study of Improved Harmony Search Algorithm in Four Bar Mechanisms | There are problems that are difficult to solve through mathematical programming or by classical methods. These problems are called hard problems due to their high complexity or high dimension. On the other hand, mataheuristics intends to seek a better solution to a problem. The Improvement Harmony Search algorithm is proposed under modification of the bandwidth parameter increasing the quality of the exploitation of the solutions. That is why within the state of the art, are mentioned several versions of harmonic search. The state of the art is supports the fact that the algorithm belongs to the category of those who make modifications to its parameters. This research demonstrates the ability of ImHS to solve a problem of high complexity focused on solving four-bar mechanism designs, whose solutions imply high dimension and which are also classified as hard problems. The two problems that are solved in this investigation, are problems very attacked within the state of the art by various metaheuristics. A comparison is then made against previous solutions with traditional metaheuristics and other versions of harmony search algorithm. Finally, the effectiveness of performance is demonstrated, where proposed algorithm it exceeded five metaheuristic algorithms and five harmony search versions. An optimum is provided in an easy and useful way, the parametric statistics are improved and the number of feasible solutions is exceeded in NP-hard problems as in the case of problems with four-bar mechanisms. |
2,692 | Heritability of brain neurovascular coupling | The moment-to-moment variation of neurovascular coupling in the brain was determined by computing the moment-to-moment turnover of the blood-oxygen-level-dependent signal (TBOLD) at resting state. Here we show that 1) TBOLD is heritable, 2) its heritability estimates are highly correlated between left and right hemispheres, and 3) the degree of its heritability is determined, in part, by the anatomical proximity of the brain areas involved. We also show that the regional distribution of TBOLD in the cortex is significantly associated with that of the vesicular acetylcholine transporter. These findings establish that TBOLD as a key heritable measure of local cortical brain function captured by neurovascular coupling.NEW & NOTEWORTHY Here we show that the sample-to-sample turnover of the resting state fMRI blood-oxygen-level-dependent turnover (TBOLD) is heritable, the left and right hemisphere TBOLD heritabilities are highly correlated, and TBOLD heritability varies among cortical areas. Moreover, we documented that TBOLD is associated with the regional cortical distribution of the vesicular acetylcholine transporter. |
2,693 | Aesthetic art simulation for embroidery style | Different image styles play a significant role in the human vision. Image rendering methods with non-photorealistic rendering based can simulate different illustrations and increase its aesthetic appeal. Despite many kinds of methods have been put forward to obtain various styles, technical subtleties and stylistic potential of the embroidery simulation are litter attention. This paper offers a detailed review of the embroidery art style simulating approach from a 2D photograph, and performs an evaluation features for these tasks. The primary novelty of this method is that the stitch features are generated through an embroidery stroke model, and stitch stoke will be merged to source image. Therefore, it avoids irregular needling embroidery, and highlights the stereoscopic effect which is not revealed in other rendering methods. Firstly, we generate noise image through gray adaptive method to guide the embroidery lines produced. After that, an improved line integral convolution technique is presented to generate stitch strokes, and scattered noise is normalizing to a certain line based on Hough transform. Next, the paper focuses on the raised strokes, which are rendered and obtained through bulging process technique in this paper. Finally, we can exploit mergence strategy based on mapping method to produce embroidery art style. To demonstrate the performance of our proposed method, this paper compares its simulating results with the real embroidery work and measure of image MSSIM is also used to evaluate the simulation quality. In all cases, the experimental results show that the proposed method can achieve embroidery style stitch visual quality and rich the aesthetic expression. |
2,694 | A state-of-the-art survey of cloud manufacturing | Rapid development in cloud computing has made an impact on the manufacturing industry. Consequently, cloud manufacturing has been proposed and has become a hot topic in the past 3 years. Many technologies such as service-oriented architecture, resource virtualisation, service ontology and modelling, service composition and management, and product data integration have been used to build the architecture of cloud manufacturing platforms. In this article, the authors survey the state of the art in the area of cloud manufacturing, identify recent research directions, and discuss potential research opportunities. |
2,695 | Beta-naphthoflavone and doxorubicin synergistically enhance apoptosis in human lung cancer cells by inducing doxorubicin accumulation, mitochondrial ROS generation, and JNK pathway signaling | Doxorubicin is one of the most effective chemotherapeutic agents available for treating various cancers, including lung cancer-the leading cause of cancer death in both men and women. However, its clinical application has been impeded by severe adverse effects, notably cardiotoxicity. Development of cellular resistance to doxorubicin is another major obstacle that must be overcome for broader application of the drug. In the present study, we examined the therapeutic potential of beta-naphthoflavone (BNF), a synthetic derivative of a naturally occurring flavonoid, in combination with doxorubicin for the treatment of lung cancer. Among our novel observations were that BNF enhances the efficacy of doxorubicin by inducing doxorubicin accumulation, mitochondrial ROS generation, and JNK pathway signaling in lung cancer cells. These combined effects were also evident in many other cancer cell types. BNF further exhibited synergistic induction of apoptosis in lung cancer cells when combined with several other cancer drugs, including irinotecan, cisplatin, and 5-fluorouracil. Our results suggest that BNF can be developed as a promising adjuvant agent for enhancing the efficacy of doxorubicin. |
2,696 | 0.5 m Triboelectric Nanogenerator for Efficient Blue Energy Harvesting of All-Sea Areas | Triboelectric nanogenerators (TENGs) to harvest ocean wave blue energy is flourishing, yet the research horizon has been limited to centimeter-level TENG. Here, for the first time, a TENG shell is advanced for ocean energy harvesting to 0.5 m and an excellent frictional areal density of 1.03 cm-1 and economies of scale are obtained. The unique structure of the multi-arch shape is adopted to untie the difficulty of fully getting the extensive friction layer contact. An inside steel plate is vertically placed in the center of every TENG block, which can activate the TENG to achieve complete contact even at a tilt angle of 7 degrees. The proposed half-meter TENG (HM-TENG) has a broad response band from 0.1 to 2 Hz, a total transferred charge quantity up to 67.2 µC, and one single TENG can deliver an open-circuit voltage of 368 V. Coupled with the self-stabilizing and susceptible features the ellipsoid shell brings, the HM-TENG can readily accommodate itself to the all-weather, all-sea wave energy harvesting. Muchmore, the HM-TENG is also applied to RF signal transmitters. This work takes the first step toward near-meter-scale enclosures and provides a new direction for large-scale wave energy harvesting. |
2,697 | State-of-the-Art in Perception Technologies for Collaborative Robots | The developments in sensor technology, information processing, computer science, and artificial intelligence significantly improved robots' autonomy. Robots' external perception relies on sensing technology. Thus, capturing accurate sensor information is vital for ensuring robotic security and improving human-machine interaction performance. This paper classifies the main robotic sensors, describes multi-sensor information fusion and processing and contrasts the state-of-the-art sensor technologies for collaborative robots with other state-of-the-art technologies in related fields. In addition, this paper also introduces collaborative robots' perception applications of the state-of-the-art representative products, the new designs for collaborative robots, the interactive applications of the intelligent Kinect sensor with collaborative robots, and the important applications of collaborative robots in the medical fields. Through a deep analysis of relevant information, this paper aims to introduce the integration of the state-of-the-art sensor technologies and collaborative robots, with hoping of guiding significance for the applications of robot sensors. This paper finally emphasizes the sensors' impact on robot performance and discusses future research on sensor technologies in robotics. |
2,698 | Sparse filtered SIRT for electron tomography | Electron tomographic reconstruction is a method for obtaining a three-dimensional image of a specimen with a series of two dimensional microscope images taken from different viewing angles. Filtered backprojection, one of the most popular tomographic reconstruction methods, does not work well under the existence of image noises and missing wedges. This paper presents a new approach to largely mitigate the effect of noises and missing wedges. We propose a novel filtered backprojection that optimizes the filter of the backprojection operator in terms of a reconstruction error. This data-dependent filter adaptively chooses the spectral domains of signals and noises, suppressing the noise frequency bands, so it is very effective in denoising. We also propose the new filtered backprojection embedded within the simultaneous iterative reconstruction iteration for mitigating the effect of missing wedges. Our numerical study is presented to show the performance gain of the proposed approach over the state-of-the-art. (C) 2020 Elsevier Ltd. All rights reserved. |
2,699 | Utilizing a new self-centering hysteresis model to assess the seismic vulnerability of a long-span cable-stayed bridge equipped with SMA wire-based roller bearings | A novel shape memory alloy wires-based smart roller bearing (SMA-RBs) has been developed and its cyclic behavior under reverse cyclic loadings has been experimentally investigated. However, its efficacy and performance in enhancing the seismic performance of bridge structures have not been well understood and proven. A new self-centering hysteresis model for SMA-RBs has been proposed to properly simulate their hysteretic behavior, which has been experimentally validated through a pseudo-static test. A methodology is proposed to determine the four damage states of SMA-RB (i.e. slight, moderate, extensive, and collapse) considering the contribution of SMA wires. The smart SMA-RBs are utilized for a cable-stayed bridge in China. The vulnerability of two reference bridges, i.e. the floating system (FS) and rigid system (RS), and one isolated bridge equipped with SMA-RBs (SMA-RBS) are compared at component and system levels. The applicability of three commonly used intensity measures (IMs), i.e. PGA, PGV, and Sa(T1), are evaluated and PGV turns out to be the optimal IM for long-span cable-stayed bridge systems. Results show that incorporating SMA wires in roller bearings can decrease the failure probabilities of the bearing. The piers and towers with SMA-RBs lead to lower seismic fragility over the towers and piers in the reference bridges. The RS is the most vulnerable bridge whereas the SMA-RBS is the least vulnerable bridge among the four bridges. The SMA-RBS experience a much lower collapse damage probability compared to RS ad FS. |
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