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4,500 | Clemastine in remyelination and protection of neurons and skeletal muscle after spinal cord injury | Spinal cord injuries affect nearly five to ten individuals per million every year. Spinal cord injury causes damage to the nerves, muscles, and the tissue surrounding the spinal cord. Depending on the severity, spinal injuries are linked to degeneration of axons and myelin, resulting in neuronal impairment and skeletal muscle weakness and atrophy. The protection of neurons and promotion of myelin regeneration during spinal cord injury is important for recovery of function following spinal cord injury. Current treatments have little to no effect on spinal cord injury and neurogenic muscle loss. Clemastine, an Food and Drug Administration-approved antihistamine drug, reduces inflammation, protects cells, promotes remyelination, and preserves myelin integrity. Recent clinical evidence suggests that clemastine can decrease the loss of axons after spinal cord injury, stimulating the differentiation of oligodendrocyte progenitor cells into mature oligodendrocytes that are capable of myelination. While clemastine can aid not only in the remyelination and preservation of myelin sheath integrity, it also protects neurons. However, its role in neurogenic muscle loss remains unclear. This review discusses the pathophysiology of spinal cord injury, and the role of clemastine in the protection of neurons, myelin, and axons as well as attenuation of skeletal muscle loss following spinal cord injury. |
4,501 | The mouse allantois: new insights at the embryonic-extraembryonic interface | During the early development of Placentalia, a distinctive projection emerges at the posterior embryonic-extraembryonic interface of the conceptus; its fingerlike shape presages maturation into the placental umbilical cord, whose major role is to shuttle fetal blood to and from the chorion for exchange with the mother during pregnancy. Until recently, the biology of the cord's vital vascular anlage, called the body stalk/allantois in humans and simply the allantois in rodents, has been largely unknown. Here, new insights into the development of the mouse allantois are featured, from its origin and mechanism of arterial patterning through its union with the chorion. Key to generating the allantois and its critical functions are the primitive streak and visceral endoderm, which together are sufficient to create the entire fetal-placental connection. Their newly discovered roles at the embryonic-extraembryonic interface challenge conventional wisdom, including the physical limits of the primitive streak, its function as sole purveyor of mesoderm in the mouse, potency of visceral endoderm, and the putative role of the allantois in the germ line. With this working model of allantois development, understanding a plethora of hitherto poorly understood orphan diseases in humans is now within reach. This article is part of the theme issue 'Extraembryonic tissues: exploring concepts, definitions and functions across the animal kingdom'. |
4,502 | Pelvic Organ Segmentation Using Distinctive Curve Guided Fully Convolutional Networks | Accurate segmentation of pelvic organs (i.e., prostate, bladder, and rectum) from CT image is crucial for effective prostate cancer radiotherapy. However, it is a challenging task due to: 1) low soft tissue contrast in CT images and 2) large shape and appearance variations of pelvic organs. In this paper, we employ a two-stage deep learning-based method, with a novel distinctive curve-guided fully convolutional network (FCN), to solve the aforementioned challenges. Specifically, the first stage is for fast and robust organ detection in the raw CT images. It is designed as a coarse segmentation network to provide region proposals for three pelvic organs. The second stage is for fine segmentation of each organ, based on the region proposal results. To better identify those indistinguishable pelvic organ boundaries, a novel morphological representation, namely, distinctive curve, is also introduced to help better conduct the precise segmentation. To implement this, in this second stage, a multi-task FCN is initially utilized to learn the distinctive curve and the segmentation map separately and then combine these two tasks to produce accurate segmentation map. The final segmentation results of all three pelvic organs are generated by a weighted max-voting strategy. We have conducted exhaustive-experiments on a large and diverse pelvic CT data set for evaluating our proposed method. The experimental results demonstrate that our proposed method is accurate and robust for this challenging segmentation task, by also outperforming the state-of-the-art segmentation methods. |
4,503 | Multigene synergism increases the isoflavone and proanthocyanidin contents of Medicago truncatula | Isoflavones and proanthocyanidins (PAs), which are flavonoid derivatives, possess many health benefits and play important roles in forage-based livestock production. However, the foliage of Medicago species accumulates limited levels of both isoflavones and PAs. In this study, biosynthesis of isoflavone and PA in Medicago truncatula was enhanced via synergy between soya bean isoflavone synthase (IFS1); two upstream enzymes, chalcone synthase (CHS) and chalcone isomerase (CHI); and the endogenous flavanone 3-hydroxylase (F3H). Constitutive expression of GmIFS1 alone resulted in ectopic accumulation of the isoflavone daidzein and large increases in the levels of the isoflavones formononetin, genistein and biochanin A in the leaves. Furthermore, coexpression of GmIFS1 with GmCHS7 and GmCHI1A generally increased the available flux to flavonoid biosynthesis and resulted in elevated isoflavone, flavone and PA contents. In addition, down-regulation of MtF3H combined with coexpression of GmIFS1, GmCHS7 and GmCHI1A led to the highest isoflavone levels (up to 2 μmol/g fresh weight in total). Taken together, our results demonstrate that multigene synergism is a powerful means to enhance the biosynthesis of particular flavonoids and can be more broadly applied to the metabolic engineering of forage species. |
4,504 | Fatigue of drillstring: State of the art | Failure due to fatigue is a very costly problem in oil and gas industry. Many investigators have previously addressed this problem, but its frequency of occurrence is still excessive. Torque and tension can be correctly predicted but computations of fatigue duration are still approximate. Regarding the fatigue failure of drillstring, this paper summarizes the state of the art. Prediction and calculation of fatigue duration are stated, including both historic of the simplified approach based oil Miner's rule and a Jew elements of the fracture mechanics theory. Existing inspection methods, their limitations and father recommendations are provided. Moreover, the fatigue tests are performed when human life and environment may be at risk. The loading conditions, the test frequency, the number and the size of test specimens are given. Environmental effects such as corrosion are recalled. Prevention and inhibitors are mentioned. Last chapter focuses on enhancement of drillstring Drillpipes geometry improvement, connections re-design, steel properties such as toughness, tool-joints hardfacing and inspection of drillpipes are discussed. |
4,505 | Effects of drought stress and plant cultivar type on demographic characteristics of the rose-grain aphid, Metopolophium dirhodum (Hemiptera: Aphididae) | Drought is a substantial threat to cereal production under global climatic change scenarios, albeit its aftermath on arthropod pests is yet contentious. To address this issue, demographic characteristics of Metopolophium dirhodum (Walker, 1849) (Hemiptera: Aphididae) were studied on one drought-susceptible wheat cultivar and one drought-tolerant wheat cultivar under different water treatments. Some physiological and biochemical features of wheat cultivars including leaf soluble sugar and proline contents and antioxidant enzymes activities were also investigated. Significant differences occurred in the developmental period, survival, and fecundity of M. dirhodum between wheat cultivars under various water treatments. The impact of intermediate and severe water stress on M. dirhodum was neutral and negative for the tolerant cultivar and negative for the water-susceptible cultivar, respectively. Under severe water stress, on both wheat cultivars, the aphids had low net reproductive rates and finite and intrinsic rates of increase in comparison with those reared on unstressed plants. In total, drought resulted in lower growth of population and reduced survival of aphids. Hence, in the context of projected climatic changes, acute water deficiency could probably result in reducing the abundance and menace of outburst of M. dirhodum. However, it should be noted that the potential likelihood of M. dirhodum eruptions can be drastically affected by the degree of drought intensity and host plant cultivar. |
4,506 | Resting state network dynamic reconfiguration and neuropsychological functioning in temporal lobe epilepsy: An HD-EEG investigation | Temporal lobe epilepsy (TLE) is nowadays considered a network disorder impacting several cognitive domains. In this work we investigated dynamic network reconfiguration differences in patients with unilateral TLE compared to a healthy control group, focusing on two connectivity indices: flexibility and integration. We apply these indices for the first time to high-density EEG source-based functional connectivity. We observed that patients with TLE exhibited significantly lower flexibility than healthy controls in the Control, Default Mode and Attentive Dorsal networks, expressed in the delta, theta and alpha bands. In addition, patients with TLE displayed greater integration values across the majority of the resting state networks, especially in the delta, theta and gamma bands. Relevantly, a higher integration index in the Control, Attentive Dorsal and Visual networks in the delta band was correlated with lower performance in visual attention and executive functions. Moreover, a greater integration index in the gamma band of the Control, Somatomotor and Temporoparietal networks was related to lower long-term memory performance. These results suggest that patients with TLE display dysregulated network reconfiguration, with lower flexibility in the brain areas related to cognitive control and attention, together with excessive inter-network communication (integration index). Finally, the correlation between network integration and the reduced cognitive performance suggests a potential mechanism underlying specific alterations in neuropsychological profile of patients with TLE. |
4,507 | Using recursive ART network to construction domain ontology based on term frequency and inverse document frequency | Ontology describes data about data and offers a group of glossaries with a definition that encompasses them in their entire. It not only transfers syntax of words but also accurately transfers semantic data between human users and the network. Hence, the usefulness of the semantic web depends on whether the domain ontology can be constructed effectively and correctly. In this paper we propose an automated method to construct the domain ontology. First, we collected domain-related web pages from the Internet. Secondly, we use the HTML tag labels to choose meaningful terms from the web pages. Next, we use these terms to construct the domain ontology by calculating a TF-IDF to find the weight of terms, using a recursive ART network (Adaptive Resonance Theory Network) to cluster terms. Each group of terms will find a candidate keyword for ontology construction. Boolean operations locate individual keywords in a hierarchy. Finally, the system outputs an ontology in a Jena package using an RDF format. The primary experiment indicates that our method is useful for domain ontology creation. (c) 2006 Elsevier Ltd. All rights reserved. |
4,508 | 3D Forward and Back-Projection for X-Ray CT Using Separable Footprints | Iterative methods for 3D image reconstruction have the potential to improve image quality over conventional filtered back projection (FBP) in X-ray computed tomography (CT). However, the computation burden of 3D cone-beam forward and back-projectors is one of the greatest challenges facing practical adoption of iterative methods for X-ray CT. Moreover, projector accuracy is also important for iterative methods. This paper describes two new separable footprint (SF) projector methods that approximate the voxel footprint functions as 2D separable functions. Because of the separability of these footprint functions, calculating their integrals over a detector cell is greatly simplified and can be implemented efficiently. The SF-TR projector uses trapezoid functions in the transaxial direction and rectangular functions in the axial direction, whereas the SF-TT projector uses trapezoid functions in both directions. Simulations and experiments showed that both SF projector methods are more accurate than the distance-driven (DD) projector, which is a current state-of-the-art method in the field. The SF-TT projector is more accurate than the SF-TR projector for rays associated with large cone angles. The SF-TR projector has similar computation speed with the DD projector and the SF-TT projector is about two times slower. |
4,509 | Challenges and Opportunities of Using a National Database to Evaluate Racial/Ethnic Disparities and Breastfeeding Effects on Sudden Unexpected Infant Death | Background: Sudden unexpected infant death (SUID) rates remain higher in American Indian/Alaska Native (AI/AN) and non-Hispanic Black (NHB) infants than other demographic groups. Racial disparities are also evident in breastfeeding, which is associated with reduced risk of SUID. Objective: To assess the relationship between racial/ethnic disparities in SUID and breastfeeding beyond the newborn period using U.S. nationally reported public databases. Methods: Data were extracted from Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research (WONDER) and the National Immunization Surveys (NISs) 2009-2017. WONDER data were restricted to full-term infants and sorted by death year, race/ethnicity, and other characteristics. NIS breastfeeding data included ever breastfed, breastfed at 6 months, and exclusive breastfeeding at 3 and 6 months. Breastfeeding rates and mortality data were aggregated based on race/ethnicity, and mortality rates were analyzed by weighted (number of births) multivariable linear regression. Results: SUID rates were highest among NHB and AI/AN infants who also had the lowest breastfeeding rates. When breastfeeding and race/ethnicity were included in the analyses, race/ethnicity confounded the relationship between breastfeeding and SUID. When race was excluded, ever breastfeeding and any breastfeeding at 6 months were associated with significantly decreased SUID rates. Conclusion: Race/ethnicity confounded the relationship between breastfeeding and SUID. Analysis was limited because individual SUID rates were available for maternal/birth characteristics but not for breastfeeding. Our study showed a need for adding additional data points to other national databases to better understand the role that breastfeeding plays in the racial/ethnic disparities in SUID. |
4,510 | Impacts of COVID-19 on the home food environment and eating related behaviors of families with young children based on food security status | This mixed-methods study endeavored to expand the current understanding of how early pandemic related disruptions impacted the home food environment and parent feeding practices of families with young children. Data for this study are taken from the Kids EAT! Study, a racially/ethnically diverse cohort of families with 2-5 year old children. Individual interviews were conducted by phone and video conference with mothers (n = 25) during August/September of 2020 and were coded using a hybrid deductive/inductive analysis approach. Parents also reported on their family's food insecurity status enabling qualitative findings to be stratified by family-level food security status. Two overarching themes were identified related to how families in this sample describe the COVID-19 pandemic's impact on their home food environment. Themes included 1) Impacts on obtaining food for one's family, and 2) Specific changes in parent feeding practices. Findings indicated variation within each theme by family food security status. Overall, families experiencing food insecurity more frequently discussed using various coping strategies, including stocking up, rationing food, and use of supplemental food resources, to overcome challenges associated with obtaining food brought on by COVID-19. Families with food insecurity also reported having more time for home cooked meals and more frequently discussed enforcing less structure (timing of meal, place) related to meals/snacks consumed at home during the pandemic. The impacts of the COVID-19 persist, ranging from ongoing economic challenges, inconsistent access to childcare for families, and the emergence of new, more contagious, variants. With this, interventions to address food insecurity amongst families with young children should consider how to optimize the home food environment and promote healthful parent feeding practices within the families they serve in the face of an evolving public health crisis. |
4,511 | Time-Aware Multivariate Nearest Neighbor Regression Methods for Traffic Flow Prediction | Traffic flow prediction is a fundamental functionality of intelligent transportation systems. After presenting the state of the art, we focus on nearest neighbor regression methods, which are data-driven algorithms that are effective yet simple to implement. We try to strengthen their efficacy in two ways that are little explored in literature, i.e., by adopting a multivariate approach and by adding awareness of the time of the day. The combination of these two refinements, which represents a novelty, leads to the definition of a new class of methods that we call time-aware multivariate nearest neighbor regression (TaM-NNR) algorithms. To assess this class, we have used publicly available traffic data from a California highway. Computational results show the effectiveness of such algorithms in comparison with state-of-the-art parametric and non-parametric methods. In particular, they consistently perform better than their corresponding standard univariate versions. These facts highlight the importance of context elements in traffic prediction. The ideas presented here may be further investigated considering more context elements (e.g., weather conditions), more complex road topologies (e.g., urban networks), and different types of prediction methods. |
4,512 | The phylogenetic position of the giant devil ray Mobula mobular (Bonnaterre, 1788) (Myliobatiformes, Myliobatidae) inferred from the mitochondrial genome | The giant devil ray, Mobula mobular, is a member of one of the most distinct groups of cartilaginous fishes, the Mobulidae (manta and devil rays), and is the only mobulid assessed as Endangered due its restricted distribution, high bycatch mortality and suspected population decline. The complete mitochondrial genome is 18 913 base pairs in length and comprises 2 rRNAs, 13 protein-coding genes, 22 tRNAs and 2 non-coding regions. Comparison with the partial mitogenome of M. japanica suggests a sister-cryptic species complex and two different taxonomic units. However, the limited divergence within the species (>99.9% genetic identity) may be the result of a geographically and numerically restricted population of M. mobular within the Mediterranean Sea. |
4,513 | Infrared Small Target Detection via Non-Convex Rank Approximation Minimization Joint l(2,1) Norm | To improve the detection ability of infrared small targets in complex backgrounds, a novel method based on non-convex rank approximation minimization joint l(2,1) norm (NRAM) was proposed. Due to the defects of the nuclear norm and l(1) norm, the state-of-the-art infrared image-patch (IPI) model usually leaves background residuals in the target image. To fix this problem, a non-convex, tighter rank surrogate and weighted l(1) norm are instead utilized, which can suppress the background better while preserving the target efficiently. Considering that many state-of-the-art methods are still unable to fully suppress sparse strong edges, the structured l(2,1) norm was introduced to wipe out the strong residuals. Furthermore, with the help of exploiting the structured norm and tighter rank surrogate, the proposed model was more robust when facing various complex or blurry scenes. To solve this non-convex model, an efficient optimization algorithm based on alternating direction method of multipliers (ADMM) plus difference of convex (DC) programming was designed. Extensive experimental results illustrate that the proposed method not only shows superiority in background suppression and target enhancement, but also reduces the computational complexity compared with other baselines. |
4,514 | Placenta segmentation in ultrasound imaging: Addressing sources of uncertainty and limited field-of-view | Automatic segmentation of the placenta in fetal ultrasound (US) is challenging due to the (i) high diversity of placenta appearance, (ii) the restricted quality in US resulting in highly variable reference annotations, and (iii) the limited field-of-view of US prohibiting whole placenta assessment at late gestation. In this work, we address these three challenges with a multi-task learning approach that combines the classification of placental location (e.g., anterior, posterior) and semantic placenta segmentation in a single convolutional neural network. Through the classification task the model can learn from larger and more diverse datasets while improving the accuracy of the segmentation task in particular in limited training set conditions. With this approach we investigate the variability in annotations from multiple raters and show that our automatic segmentations (Dice of 0.86 for anterior and 0.83 for posterior placentas) achieve human-level performance as compared to intra- and inter-observer variability. Lastly, our approach can deliver whole placenta segmentation using a multi-view US acquisition pipeline consisting of three stages: multi-probe image acquisition, image fusion and image segmentation. This results in high quality segmentation of larger structures such as the placenta in US with reduced image artifacts which are beyond the field-of-view of single probes. |
4,515 | Fibre optics: Forty years later | This paper presents a brief overview of the state of the art in fibre optics and its main applications: optical fibre communications, fibre lasers and fibre sensors for various physical property measurements. The future of fibre optics and the status of this important area of the modern technology in Russia are discussed. |
4,516 | Hemiparesis Revealing a Unique Neurological Hemophagocytic Lymphohistiocytosis in a Patient With Griscelli Syndrome Type 2 | Griscelli syndrome (GS) is a rare genetic disorder that encompasses three different subtypes (GS type 1 (GS1), GS type 2 (GS2), and GS type 3 (GS3)), in which isolated neurological manifestations without immune system implications are typically seen in GS1, while neurological involvements in GS2 should be attributed to the macrophage and lymphocyte invasion of the central nervous system (CNS), under associated hemophagocytic lymphohistiocytosis (HLH). The presence of the clinical, biological, and hematologic features of HLH help explain the neurological defects that GS2 patients unusually present. In our case report, however, we attempt to highlight an uncommon presentation of GS2 involving a hemiparesis, along which we did not have any clinical or biological features of HLH. We also collect and evaluate similar published cases that feature this problem of explaining the neurological manifestations among GS2 patients. |
4,517 | Over-reliance on English hinders cognitive science | English is the dominant language in the study of human cognition and behavior: the individuals studied by cognitive scientists, as well as most of the scientists themselves, are frequently English speakers. However, English differs from other languages in ways that have consequences for the whole of the cognitive sciences, reaching far beyond the study of language itself. Here, we review an emerging body of evidence that highlights how the particular characteristics of English and the linguistic habits of English speakers bias the field by both warping research programs (e.g., overemphasizing features and mechanisms present in English over others) and overgeneralizing observations from English speakers' behaviors, brains, and cognition to our entire species. We propose mitigating strategies that could help avoid some of these pitfalls. |
4,518 | Bilateral spontaneous salivary otorrhoea: Case report and a review of the literature | Spontaneous salivary otorrhoea is an extremely rare clinical entity. Most of the times, salivary otorrhoea results from various forms of trauma. It has also been attributed to the patent foramen of Huschke, and fissures of Santorini. Here, we present a rare case of an 8 year old child presenting with salivary discharge from both the ears. The diagnosis was established on the basis of biochemical and radiological investigations. The patient was managed by surgical exploration and ligation of the fistulous tract. |
4,519 | Energy disaggregation using variational autoencoders | Non-intrusive load monitoring (NILM) is a technique that uses a single sensor to measure the total power consumption of a building. Using an energy disaggregation method, the consumption of individual appli-ances can be estimated from the aggregate measurement. Recent disaggregation algorithms have signif-icantly improved the performance of NILM systems. However, the generalization capability of these methods to different houses as well as the disaggregation of multi-state appliances are still major chal-lenges. In this paper we address these issues and propose an energy disaggregation approach based on the variational autoencoders framework. The probabilistic encoder makes this approach an efficient model for encoding information relevant to the reconstruction of the target appliance consumption. In particular, the proposed model accurately generates more complex load profiles, thus improving the power signal reconstruction of multi-state appliances. Moreover, its regularized latent space improves the generalization capabilities of the model across different houses. The proposed model is compared to state-of-the-art NILM approaches on the UK-DALE and REFIT datasets, and yields competitive results. The mean absolute error reduces by 18% on average across all appliances compared to the state-of-the -art. The F1-Score increases by more than 11%, showing improvements for the detection of the target appliance in the aggregate measurement. (c) 2021 Elsevier B.V. All rights reserved. |
4,520 | Cardiac innervations in diabetes mellitus-Anatomical evidence of neuropathy | The extensive innervations of the heart include a complex network of sympathetic, parasympathetic, and sensory nerves connected in loops that serve to regulate cardiac output. Metabolic dysfunction in diabetes affects many different organ systems, including the cardiovascular system; it causes cardiac arrhythmias, silent myocardial ischemia, and sudden cardiac death, among others. These conditions are associated with damage to the nerves that innervate the heart, cardiac autonomic neuropathy (CAN), which is caused by various pathophysiological mechanisms. In this review, the main facts about the anatomy of cardiac innervations and the current knowledge of CAN, its pathophysiological mechanisms, and its diagnostic approach are discussed. In addition, anatomical evidence for CAN from human and animal studies has been summarized. |
4,521 | Polyphenols: a route from bioavailability to bioactivity addressing potential health benefits to tackle human chronic diseases | Chronic pathologies or non-communicable diseases (NCDs) include cardiovascular diseases, metabolic syndrome, neurological diseases, respiratory disorders and cancer. They are the leading global cause of human mortality and morbidity. Given their chronic nature, NCDs represent a growing social and economic burden, hence urging the need for ameliorating the existing preventive strategies, and for finding novel tackling therapies. NCDs are highly correlated with unhealthy lifestyle habits (such as high-fat and high-glucose diet, or sedentary life). In general, lifestyle approaches that might improve these habits, including dietary consumption of fresh vegetables, fruits and fibers, may contrast NCD symptoms and prolong life expectancy of affected people. Polyphenols (PPLs) are plant-derived molecules with demonstrated biological activities in humans, which include: radical scavenging and anti-oxidant activities, capability to modulate inflammation, as well as human enzymes, and even to bind nuclear receptors. For these reasons, PPLs are currently tested, both preclinically and clinically, as dietary adjuvants for the prevention and treatment of NCDs. In this review, we describe the human metabolism and bioactivity of PPLs. Also, we report what is currently known about PPLs interaction with gastro-intestinal enzymes and gut microbiota, which allows their biotransformation in many different metabolites with several biological functions. The systemic bioactivity of PPLs and the newly available PPL-delivery nanosystems are also described in detail. Finally, the up-to-date clinical studies assessing both safety and efficacy of dietary PPLs in individuals with different NCDs are hereby reported. Overall, the clinical results support the notion that PPLs from fruits, vegetables, but also from leaves or seeds extracts, are safe and show significant positive results in ameliorating symptoms and improving the whole quality of life of people with NCDs. |
4,522 | Mixed Dimensional ZnO/WSe2 Piezo-gated Transistor with Active Millinewton Force Sensing | This work demonstrates a mixed-dimensional piezoelectric-gated transistor in the microscale that could be used as a millinewton force sensor. The force-sensing transistor consists of 1D piezoelectric zinc oxide (ZnO) nanorods (NRs) as the gate control and multilayer tungsten diselenide (WSe2) as the transistor channel. The applied mechanical force on piezoelectric NRs can induce a drain-source current change (ΔIds) on the WSe2 channel. The different doping types of the WSe2 channel have been found to lead to different directions of ΔIds. The pressure from the calibration weight of 5 g has been observed to result in an ∼30% Ids change for ZnO NRs on the p-type doped WSe2 device and an ∼-10% Ids change for the device with an n-type doped WSe2. The outcome of this work would be useful for applications in future human-machine interfaces and smart biomedical tools. |
4,523 | Gradient-Based Illumination Description for Image Forgery Detection | The goal of blind image forensics is to determine authenticity and origin of an image without using an explicitly embedded security scheme. Most existing forensic methods can roughly be grouped into statistical and physics-based approaches. Statistical methods can oftentimes be fully automated, and achieve impressive results on current state-of-the-art benchmarks. Physics-based methods explain image inconsistencies using an analytic model, and are more robust to common image processing operations such as resizing or recompression. In this work, we propose a physics-based forensic descriptor to characterize 2-D lighting environments of objects. The key idea is that the integral over a gradient field of an object indicates the direction of incident light in the image plane. In contrast to prior 2-D lighting methods, the proposed method is remarkably robust to changes in object color and variations in user input, as it operates on the whole object area instead of object contours. Furthermore, we show that the proposed method is unaffected by image resizing or compression, which makes it possible to analyze images that are impossible to analyze with current state-of-the-art statistical methods. |
4,524 | Techno-economic analysis of single-stage and temperature-phase anaerobic co-digestion of sewage sludge, wine vinasse, and poultry manure | Anaerobic co-digestion (AcoD) is a mature and consolidated waste management technology that can transform agro-industrial by-products into biogas and digestate. This study conducted a techno-economic assessment of bioenergy and agricultural fertilizer production from AcoD of sewage sludge, wine vinasse, and poultry manure. In this case study, three configurations were investigated: i) Scenario 1, AcoD in thermophilic temperature; ii) Scenario 2, AcoD in mesophilic temperature; and iii) Scenario 3, AcoD in a temperature phase (TPAD) system, where the digestate produced in the first reactor (thermophilic) feeds the second reactor (mesophilic). The process was designed to manage 24,022 m³ wine vinasse y-1, 24,022 m³ sewage sludge y-1, and 480 m³ poultry manure y-1. The major cost was the fixed capital investment for the single-stage (320,981 USD) and TPAD processes (379,698 USD). The TPAD process produced the highest electricity (1058.99 MWh y-1) and heat (4765.47 GJ y-1) with the lowest cost of manufacturing for electricity (84.99 USD MWh-1), heat (0.019 USD MJ-1), and fertilizer (30.91 USD t-1). Regarding the profitability indicators, the highest net present value (509,011 USD) and the lowest payback time (4.24 y) were achieved for Scenario 3. In conclusion, TPAD is a profitable and sustainable waste-to-energy management technology that can be applied in a circular economy framework to recover bioenergy and fertilizer, contributing to decreasing the carbon footprint of the agri-food sector. |
4,525 | High-resolution mapping reveals hotspots and sex-biased recombination in Populus trichocarpa | Fine-scale meiotic recombination is fundamental to the outcome of natural and artificial selection. Here, dense genetic mapping and haplotype reconstruction were used to estimate recombination for a full factorial Populus trichocarpa cross of 7 males and 7 females. Genomes of the resulting 49 full-sib families (N = 829 offspring) were resequenced, and high-fidelity biallelic SNP/INDELs and pedigree information were used to ascertain allelic phase and impute progeny genotypes to recover gametic haplotypes. The 14 parental genetic maps contained 1,820 SNP/INDELs on average that covered 376.7 Mb of physical length across 19 chromosomes. Comparison of parental and progeny haplotypes allowed fine-scale demarcation of cross-over regions, where 38,846 cross-over events in 1,658 gametes were observed. Cross-over events were positively associated with gene density and negatively associated with GC content and long-terminal repeats. One of the most striking findings was higher rates of cross-overs in males in 8 out of 19 chromosomes. Regions with elevated male cross-over rates had lower gene density and GC content than windows showing no sex bias. High-resolution analysis identified 67 candidate cross-over hotspots spread throughout the genome. DNA sequence motifs enriched in these regions showed striking similarity to those of maize, Arabidopsis, and wheat. These findings, and recombination estimates, will be useful for ongoing efforts to accelerate domestication of this and other biomass feedstocks, as well as future studies investigating broader questions related to evolutionary history, perennial development, phenology, wood formation, vegetative propagation, and dioecy that cannot be studied using annual plant model systems. |
4,526 | Learning Document Embeddings Along With Their Uncertainties | Majority of the text modeling techniques yield only point-estimates of document embeddings and lack in capturing the uncertainty of the estimates. These uncertainties give a notion of how well the embeddings represent a document. We present Bayesian subspace multinomial model (Bayesian SMM), a generative log-linear model that learns to represent documents in the form of Gaussian distributions, thereby encoding the uncertainty in its covariance. Additionally, in the proposed Bayesian SMM, we address a commonly encountered problem of intractability that appears during variational inference in mixed-logit models. We also present a generative Gaussian linear classifier for topic identification that exploits the uncertainty in document embeddings. Our intrinsic evaluation using perplexity measure shows that the proposed Bayesian SMM fits the unseen test data better as compared to the state-of-the-art neural variational document model on (Fisher) speech and (20Newsgroups) text corpora. Our topic identification experiments show that the proposed systems are robust to over-fitting on unseen test data. The topic ID results show that the proposed model outperforms state-of-the-art unsupervised topic models and achieve comparable results to the state-of-the-art fully supervised discriminative models. |
4,527 | Justice, Equity, Diversity, and Inclusion Curriculum Within an Introductory Bioengineering Course | Curriculum initiatives that provide the societal context of engineering practice can contribute to justice, equity, diversity, and inclusion (JEDI) within the profession, as well as within the communities served by engineers. JEDI curriculum can foster diversity and inclusion by acknowledging and addressing social justice issues, providing a safe and inclusive space for students' voices to be heard, and advancing a productive dialogue within their institution of higher learning. Furthermore, such curriculum initiatives can empower students with the theoretical frameworks, analytical tools, and knowledge base to recognize and address ethical challenges and opportunities related to justice, equity, diversity, and inclusion in their field. This Teaching Tips paper offers a description of a pilot program to incorporate JEDI material within a core bioengineering course modeled on evidence-based curriculum programs to embed ethics within technical courses. The author and collaborators sought to achieve two aims with the JEDI-focused material: (1) for students to learn how justice, equity, diversity, and inclusion intersect with bioengineering practice through an interdisciplinary lens of history, philosophy, sociology and anthropology which provide strong scholarly frameworks and theoretical foundations and (2) for students to participate in and foster an inclusive environment within their own educational institution through effectively communicating about these topics with each other. At the conclusion of the semester, a student survey indicated an overwhelmingly positive reception of the material. This paper will discuss the interdisciplinary curriculum development initiative, how the learning objectives were addressed by the specific lesson plans, and challenges to be addressed to create a sustainable educational model for the program. |
4,528 | Complex Deep Neural Networks from Large Scale Virtual IMU Data for Effective Human Activity Recognition Using Wearables | Supervised training of human activity recognition (HAR) systems based on body-worn inertial measurement units (IMUs) is often constrained by the typically rather small amounts of labeled sample data. Systems like IMUTube have been introduced that employ cross-modality transfer approaches to convert videos of activities of interest into virtual IMU data. We demonstrate for the first time how such large-scale virtual IMU datasets can be used to train HAR systems that are substantially more complex than the state-of-the-art. Complexity is thereby represented by the number of model parameters that can be trained robustly. Our models contain components that are dedicated to capture the essentials of IMU data as they are of relevance for activity recognition, which increased the number of trainable parameters by a factor of 1100 compared to state-of-the-art model architectures. We evaluate the new model architecture on the challenging task of analyzing free-weight gym exercises, specifically on classifying 13 dumbbell execises. We have collected around 41 h of virtual IMU data using IMUTube from exercise videos available from YouTube. The proposed model is trained with the large amount of virtual IMU data and calibrated with a mere 36 min of real IMU data. The trained model was evaluated on a real IMU dataset and we demonstrate the substantial performance improvements of 20% absolute F1 score compared to the state-of-the-art convolutional models in HAR. |
4,529 | VoxelMorph: A Learning Framework for Deformable Medical Image Registration | We present VoxelMorph, a fast learning-based framework for deformable, pairwise medical image registration. Traditional registration methods optimize an objective function for each pair of images, which can be time-consuming for large datasets or rich deformation models. In contrast to this approach and building on recent learning-based methods, we formulate registration as a function that maps an input image pair to a deformation field that aligns these images. We parameterize the function via a convolutional neural network and optimize the parameters of the neural network on a set of images. Given a new pair of scans, VoxelMorph rapidly computes a deformation field by directly evaluating the function. In this paper, we explore two different training strategies. In the first (unsupervised) setting, we train the model to maximize standard image matching objective functions that are based on the image intensities. In the second setting, we leverage auxiliary segmentations available in the training data. We demonstrate that the unsupervised model's accuracy is comparable to the state-of-the-art methods while operating orders of magnitude faster. We also show that VoxelMorph trained with auxiliary data improves registration accuracy at test time and evaluate the effect of training set size on registration. Our method promises to speed up medical image analysis and processing pipelines while facilitating novel directions in learning-based registration and its applications. Our code is freely available at https://github.com/voxelmorph/voxelmorph. |
4,530 | Design of radiation-hardened memory cell by polar design for space applications | This paper proposed a radiation-hardened memory cell (RHMC12T) by polar design for space applications. The proposed cell has the following advantages: (1) it can tolerate all single-node upset and partial double-node upset based on combining radiation hardened by polar design technology together with reasonable layout topology; (2) comparing with the state-of-the-art radiation hardened SRAM cells, simulation results show the proposed RHMC12T cell has lower write access time, higher wordline write trip voltage, larger static noise margin, and larger critical charge. And Monte Carlo simulation results have shown that RHMC12T has good robustness; (3) electrical quality metric is widely used to evaluate the overall performance of SRAM cells. And RHMC12T has the largest EQM compared with the state-of-the-art radiation hardened SRAM cells, which suggests the proposed RHMC12T exhibits good circuit performance (including write/read access time, static noise margin et al.) as well as good radiation resistance performance with sacrificing a large area overhead. |
4,531 | GAN computers generate arts? A survey on visual arts, music, and literary text generation using generative adversarial network | Art is the lie that enables us to realize the truth. - Pablo Picasso. For centuries, humans have dedicated themselves to producing arts to convey their imagination. The advancement in technology and deep learning in particular, has caught the attention of many researchers trying to investigate whether art generation is possible by computers and algorithms. Using generative adversarial networks (GANs), applications such as synthesizing photorealistic human faces and generating captions automatically from images were realized. This survey takes a comprehensive look at the recent works using GANs for generating visual arts, music, and literary text. A performance comparison and description of the various GAN architecture are also presented. Finally, some of the key challenges in GAN-based art generation are highlighted along with recommendations for future work. |
4,532 | Cannabinoid Photochemistry: An Underexplored Opportunity | Photochemistry is a powerful synthetic tool resulting in the construction of unique substances. Remarkably, photochemistry has been relatively underexplored in the cannabinoid area and represents a valuable opportunity for further discovery. |
4,533 | Hybrid SFNet Model for Bone Fracture Detection and Classification Using ML/DL | An expert performs bone fracture diagnosis using an X-ray image manually, which is a time-consuming process. The development of machine learning (ML), as well as deep learning (DL), has set a new path in medical image diagnosis. In this study, we proposed a novel multi-scale feature fusion of a convolution neural network (CNN) and an improved canny edge algorithm that segregate fracture and healthy bone image. The hybrid scale fracture network (SFNet) is a novel two-scale sequential DL model. This model is highly efficient for bone fracture diagnosis and takes less computation time compared to other state-of-the-art deep CNN models. The innovation behind this research is that it works with an improved canny edge algorithm to obtain edges in the images that localize the fracture region. After that, grey images and their corresponding canny edge images are fed to the proposed hybrid SFNet for training and evaluation. Furthermore, the performance is also compared with the state-of-the-art deep CNN models on a bone image dataset. Our results showed that SFNet with canny (SFNet + canny) achieved the highest accuracy, F1-score and recall of 99.12%, 99% and 100%, respectively, for bone fracture diagnosis. It showed that using a canny edge algorithm improves the performance of CNN. |
4,534 | Breaking (Global) Barriers in Parallel Stochastic Optimization With Wait-Avoiding Group Averaging | Deep learning at scale is dominated by communication time. Distributing samples across nodes usually yields the best performance, but poses scaling challenges due to global information dissemination and load imbalance across uneven sample lengths. State-of-the-art decentralized optimizers mitigate the problem, but require more iterations to achieve the same accuracy as their globally-communicating counterparts. We present Wait-Avoiding Group Model Averaging (WAGMA) SGD, a wait-avoiding stochastic optimizer that reduces global communication via subgroup weight exchange. The key insight is a combination of algorithmic changes to the averaging scheme and the use of a group allreduce operation. We prove the convergence of WAGMA-SGD, and empirically show that it retains convergence rates similar to Allreduce-SGD. For evaluation, we train ResNet-50 on ImageNet; Transformer for machine translation; and deep reinforcement learning for navigation at scale. Compared with state-of-the-art decentralized SGD variants, WAGMA-SGD significantly improves training throughput (e.g., 2.1x on 1,024 GPUs for reinforcement learning), and achieves the fastest time-to-solution (e.g., the highest score using the shortest training time for Transformer). |
4,535 | LineGAN: An image colourisation method combined with a line art network | The work on grayscale image colourisation has been significantly improved. Currently, learning-based methods have achieved some great colourisation effects, but existing colour edge bleeding, especially when colourful cartoon characters. In this paper, we focus on the colourisation of cartoon characters from a series in an adversarial environment with a line art network, whose name is LineGAN. LineGAN learns the corresponding colour mapping from datasets, improving the accuracy of image colourisation. Our methods limit the colour boundary overflow by adding a line art frame in the generator. Extensive experiment results on cartoon image colourisation tasks demonstrate that the proposed method can achieve effective results. |
4,536 | The Generalized Log-Ratio Transformation: Learning Shape and Adjacency Priors for Simultaneous Thigh Muscle Segmentation | We present a novel probabilistic shape representation that implicitly includes prior anatomical volume and adjacency information, termed the generalized log-ratio (GLR) representation. We demonstrate the usefulness of this representation in the task of thigh muscle segmentation. Analysis of the shapes and sizes of thigh muscles can lead to a better understanding of the effects of chronic obstructive pulmonary disease (COPD), which often results in skeletal muscle weakness in lower limbs. However, segmenting these muscles from one another is difficult due to a lack of distinctive features and inter-muscular boundaries that are difficult to detect. We overcome these difficulties by building a shape model in the space of GLR representations. We remove pose variability from the model by employing a presegmentation-based alignment scheme. We also design a rotationally invariant random forest boundary detector that learns common appearances of the interface between muscles from training data. We combine the shape model and the boundary detector into a fully automatic globally optimal segmentation technique. Our segmentation technique produces a probabilistic segmentation that can be used to generate uncertainty information, which can be used to aid subsequent analysis. Our experiments on challenging 3D magnetic resonance imaging data sets show that the use of the GLR representation improves the segmentation accuracy, and yields an average Dice similarity coefficient of 0.808 +/- 0.074, comparable to other state-of-the-art thigh segmentation techniques. |
4,537 | Human actions recognition: an approach based on stable motion boundary fields | Automatic video action recognition have been a long-standing problem in computer vision. To obtain a scalable solution for actions recognition, it is important to have efficient visual representation of motions. In this paper, we propose a new visual representation for actions based in the body motion boundaries. The first step, a set of optical flow frames highlighting the principal motions in the poses is substracted. Then, the motion boundaries are computed from the previous optical flow frames. Maximum Stable Extremal Regions are then applied to motion boundaries maps in order to obtain Motion Stable Shape (MSS) features. Local descriptors were computed based on each detected MSS to capture motion patterns. To predict the classes of the different human actions, we have represented different descriptors with a bag-of-words (BOW) model and for classification, we use a non-linear support vector machine. We have performed a set of experiments on different datasets: Weizmann, KTH, UCF sport, UCF50 and Hollywood to prove the efficiency of our developed model. The achieved results improve the state-of-the-art on the KTH and Weizmann datasets and are comparable to state-of-the-art for UCF sport and UCF50 datasets. |
4,538 | A meta-evolutionary selection of constituents in ensemble differential evolution algorithm | A Meta-evolutionary Selection of Constituents in Ensemble DE (MeSCEDE) framework is proposed in this paper to automate the design of high-level multi-population ensemble Differential Evolution (DE) algorithms. The automated design of high-level multi-population ensemble DE algorithms involves both automated selection of constituent DE algorithms for the ensemble and automated configuration of ensemble related parameters. Grammatical Evolution has been used as the meta-evolutionary algorithm in MeSCEDE to search the space of design choices so as to evolve effective ensemble design(s) for given problem(s). The simulation experiments carried out in this paper involve applying MeSCEDE to evolve ensemble DE designs for solving 30-dimensional CEC'17 benchmark functions. The effectiveness of the evolved designs are validated on 30 and 50-dimensional CEC'14 functions as well as on 22 real-world problem instances from CEC'11 benchmark suite. The MeSCEDE evolved designs have exhibited a competitive performance against state-of-the-art ensemble DE algorithms. In addition, the potential of MeSCEDE has been demonstrated against irace, a state-of-the-art algorithm configurator. All simulation experiments reiterate the potential of MeSCEDE towards evolving effective and robust ensemble DE designs. |
4,539 | Enhanced Passive GNSS-Based Radar Imaging Based on Coherent Integrated Multi-Satellite Signals | Weak reflected signal is one of the main problems in a recent developing remote sensing tool-passive GNSS-based radar (GNSS radar). To address this issue, an enhanced GNSS radar imaging scheme on the basis of coherently integrating multiple satellites is proposed. In the proposed scheme, to avoid direct signal interference at surveillance antenna, the satellites that used as transmission of opportunity are in backscattering geometry model. To coherently accumulate echo signal magnitudes of the scene center in the targeted sensing region illuminated by the selected satellites, after performing the paralleled range compressions, a coordinates alignment operator is performed to the respective range domains, in which, pseudorandom noise (PRN) code phases are aligned. Thereafter, the coordinates aligned range compressed signals of the selected satellites are coherently integrated along azimuth domain so that imaging gain is improved and azimuth processing can be accomplished in only one state operation. The theoretical analysis and field proof-of-concept experimental results indicate that compared to both conventional bistatic imaging scheme and the state-of-the-art multi-image fusion scheme, the proposed scheme can provide a higher imaging gain; compared to the state-of-the-art multi-image fusion scheme, the proposed scheme has a less computational complexity and faster algorithm speed. |
4,540 | RandShift: An Energy-Efficient Fault-Tolerant Method in Secure Nonvolatile Main Memory | In this article, we present a simple, yet energy- and area-efficient method for tolerating the stuck-at faults caused by an endurance issue in secure-resistive main memories. In the proposed method, by employing the random characteristics of the encrypted data encoded by the Advanced Encryption Standard (AES) as well as a rotational shift operation, a large number of memory locations with stuck-at faults could be employed for correctly storing the data. Due to the simple hardware implementation of the proposed method, its energy consumption is considerably smaller than that of other recently proposed methods. The technique may be employed along with other error correction methods, including the error correction code (ECC) and the error correction pointer (ECP). To assess the efficacy of the proposed method, it is implemented in a phase-change memory (PCM)based main memory system and compared with three error tolerating methods. The results reveal that for a stuck-at fault occurrence rate of 10(-2) and with the uncorrected bit error rate of 2 x 10(-3), the proposed method achieves 82% energy reduction compared to the state-of-the-art method. More generally, using a simulation analysis technique, we show that the fault coverage of the proposed method is similar to that of the state-of-the-art method. |
4,541 | A state of the art system for managing time data in manual assembly | Valid time data, a prerequisite for the efficient use of manufacturing resources, directly influence planning and control quality. However, access to time data that capture real shop-floor operations in general and manual operations in particular is often assumed by both academics and practitioners. This has led to a mismatch between reality and the data found in systems for production planning and control, causing operational inefficiencies and negatively affecting decision-making in manufacturing companies. This article addresses the importance of updated and valid time data in planning and controlling production and considers how they relate to manufacturing system performance and improvement. The focus is on how to determine, utilise, and sustain valid time data for manual assembly operations through integrating enterprise information systems. The article builds on a case study performed at a large manufacturing enterprise that operates a state of the art system for managing time data in manual assembly. Findings from the case study reveal how standalone system applications can be integrated with the organisational functions of an enterprise to achieve updated and valid operation times. |
4,542 | ETHICS OF EXHIBITION SPACE LIGHTING IN ART MUSEUMS | Exhibition lighting is one of the most important subjects in terms of forming of an image of the entire museum as well as of perception of particular exhibits. This article reviews aspects of art museum lighting, presents examples of interaction of light and fine art pieces, and gives a perspective on possible methods of picture lighting accounting for nuances of the subject and the state of a painting. We will try to describe the main aspects and principles of work with paintings. |
4,543 | Bayesian compressive sensing for cluster structured sparse signals | In traditional framework of compressive sensing (CS), only sparse prior on the property of signals in time or frequency domain is adopted to guarantee the exact inverse recovery. Other than sparse prior, structures on the sparse pattern of the signal have also been used as an additional prior, called model-based compressive sensing, such as clustered structure and tree structure on wavelet coefficients. In this paper, the cluster structured sparse signals are investigated. Under the framework of Bayesian compressive sensing, a hierarchical Bayesian model is employed to model both the sparse prior and cluster prior, then Markov Chain Monte Carlo (MCMC) sampling is implemented for the inference. unlike the state-of-the-art algorithms which are also taking into account the cluster prior, the proposed algorithm solves the inverse problem automatically prior information on the number of clusters and the size of each cluster is unknown. The experimental results show that the proposed algorithm outperforms many state-of-the-art algorithms. (C) 2011 Elsevier B.V. All rights reserved. |
4,544 | Cyber Insurance Against Cyberattacks on Electric Vehicle Charging Stations | Cyberattacks in the energy sector are commonplace. Load-altering cyberattacks launched via the manipulations of high-wattage appliances and assets are particularly alarming, as they are not continuously monitored by electric power utilities. Public Electric Vehicle Charging Stations (EVCSs) are among such high-wattage assets. Even EVCSs monitored by the electric power utilities and protected by state-of-the-art defense mechanisms are vulnerable to cyberattacks. Such cyberattacks cause financial losses to the EVCSs. In this paper, we propose cyber insurance for EVCSs to hedge the economic loss due to such cyberattacks and develop a data-driven cyber insurance design model for public EVCSs. Under mild modeling assumptions, we derive an optimal cyber insurance premium. Then, we ensure the robustness of this optimal premium and investigate the risk of insuring the EVCSs using a suitable risk assessment metric (Conditional Value-at-Risk). A case study with data from EVCSs in Manhattan, New York illustrates our results. Our results demonstrate that risk assessment is crucial for designing insurance premiums. Furthermore, the premium increases in proportion to the loss coverage offered for the EVCSs. This work informs the stakeholders involved in the roll-out and operation of public EVCSs about the benefits of cyber insurance and suggests that insurance premiums can be reduced by deploying state-of-the-art defense mechanisms. |
4,545 | Dietary zero-dimensional fullerene supplementation improves the meat quality, lipid metabolism, muscle fiber characteristics, and antioxidative status in finishing pigs | With the increasing demand for high-quality pork, more nutritional substances have been studied for the regulation of meat quality. Zero-dimensional fullerenes (C60) can modulate the biological behavior of a variety of cell lines and animals. In this study, we report the biological effects of C60 on finishing pigs at different concentrations. A total of 24 barrows (Duroc × Large White × Landrace), with an average body weight of 21.01 ± 0.98 kg, were divided into 3 groups and each treated daily with C60 (100 or 200 mg per kg feed) or a control diet until the end of the experiment. Our results showed that dietary C60 supplementation improved flesh color, marbling scores, and flavor amino acid contents of longissimus dorsi (LD) of growing-finishing pigs (P < 0.05). C60 improved meat quality by regulating lipid metabolism and muscle fiber morphology by mediating the expression of genes, L-lactic dehydrogenase (LDH), myosin heavy chain (MyHC) IIa, MyHCIIb, peroxisome proliferator-activated receptor γ (PPARγ), and fatty acid transport protein 1 (FATP1) (P < 0.05). Moreover, C60 substantially promoted the mRNA expression of antioxidant enzyme genes (P < 0.05), which also contributed to improving meat quality. These findings have important implications for the application of C60 in the livestock industry, especially for improving the meat quality of fattening pigs. |
4,546 | Complicating cure: How Australian criminal law shapes imagined post-hepatitis C futures | In recent years, highly tolerable and effective drugs have emerged promising a radical new 'post-hepatitis C' world. Optimism about medical cure potentially overlooks discrimination and stigma associated with hepatitis C and injecting drug use. Legal frameworks are especially relevant to hepatitis futures, since the law has the potential to reinforce or alleviate stigma and discrimination. This article explores how hepatitis C figures in Australian criminal law and with what potential effects. Drawing on Bruno Latour's work on legal veridiction, Alison Kafer's work on futurity and disability and case law data collected for a major study on hepatitis C and post-cure lives, we explore how the criminal law handles hepatitis C in the age of cure. We find that law complicates cure, constituting hepatitis C as disabling despite the advent of effective cures. The law steadfastly maintains its own approach to disease, disability and illness, untouched by medical and scientific developments, in ways that might complicate straightforwardly linear imaginaries of cure, transformation and progress of the kind that dominate biomedicine. We explore the implications of these tensions between law and medicine. |
4,547 | Differential 3D Facial Recognition: Adding 3D to Your State-of-the-Art 2D Method | Active illumination is a prominent complement to enhance 2D face recognition and make it more robust, e.g., to spoofing attacks and low-light conditions. In the present work we show that it is possible to adopt active illumination to enhance state-of-the-art 2D face recognition approaches with 3D features, while bypassing the complicated task of 3D reconstruction. The key idea is to project over the test face a high spatial frequency pattern, which allows us to simultaneously recover real 3D information plus a standard 2D facial image. Therefore, state-of-the-art 2D face recognition solution can be transparently applied, while from the high frequency component of the input image, complementary 3D facial features are extracted. Experimental results on ND-2006 dataset show that the proposed ideas can significantly boost face recognition performance and dramatically improve the robustness to spoofing attacks. |
4,548 | Methods for Successful Aging: An Aesthetics-Oriented Perspective Derived from Richard Shusterman's Somaesthetics | This study explored Richard Shusterman's somaesthetics to understand the rationale for his view on enhancing the body experience of older adults and increasing their participation in art; it also examined methods or successful aging to enhance the theoretical foundation for educational gerontology. Accordingly, the research objectives were to (1) analyze the definition of successful aging; (2) clarify the role of body experience and participation in art in promoting successful aging among older adults; (3) explore and discuss Shusterman's somaesthetics; and (4) explore methods for successful aging derived from Shusterman's somaesthetics. This study mainly explored educational philosophy by collecting, reading, analyzing, logically reviewing, and interpreting the literature on this topic. During this exploration, methods for successful aging were reviewed. The findings are as follows: (1) shifting focus of successful aging to the bodies of older adults; (2) cultivating the body consciousness of older adults enables them to understand themselves and pursue virtue, happiness, and justice; (3) popular art can be integrated to promote the aesthetic ability of older adults and encourage their physical participation in the aesthetic process; (4) older adult education should cultivate the somaesthetic sensitivity of older adults; (5) older adult education should incorporate the physical training of older adults to help them enhance their self-cultivation and care for their body, cultivate virtue, and live a better life; and (6) older adult education should integrate the body and mind of older adults. |
4,549 | Urban flood impact assessment: A state-of-the-art review | Flooding can cause major disruptions in cities, and lead to significant impacts on people, the economy and on the environment. These impacts may be exacerbated by climate and socio-economic changes. Resilience thinking has become an important way for city planners and decision makers to manage flood risks. Despite different definitions of resilience, a consistent theme is that flood resilient cities are impacted less by extreme flood events. Therefore, flood risk professionals and planners need to understand flood impacts to build flood resilient cities. This paper presents a state-of-the-art literature review on flood impact assessment in urban areas, detailing their application, and their limitations. It describes both techniques for dealing with individual categories of impacts, as well as methodologies for integrating them. The paper will also identify future avenues for progress in improving the techniques. |
4,550 | A Single-MOSFET Analog High Resolution-Targeted (SMART) Multiplier for Machine Learning Classification | Mixed-signal machine-learning classification has recently been demonstrated as an efficient alternative for classification with power expensive digital circuits. In this paper, a single-MOSFET analog multiplier is proposed for classifying high-dimensional input data into multi-class output space with less power and higher accuracy than state-of-the-art mixed-signal linear classifiers. A high-resolution (i.e., multi-bit) multiplication is facilitated within a single-MOSFET by feeding the features and feature weights into, respectively, the body and gate inputs. High-resolution classifier that considers the decisions of the individual predictors is designed at 180nm technology node and operates at 100MHz in near/subthreshold region. To evaluate the performance of the classifier, a reduced MNIST dataset is generated by downsampling the MNIST digit images from 784 features to 48 features. The system is simulated across a wide range of PVT variations, exhibiting average accuracy of 92% (2% improvement over state-of-the-art), energy consumption of 67.3 pJ per classification (over 8 times lower than state-of-the-art classifiers), area of 27,570 mu m(2) per binary classifier, and a stable response under PVT variations. Finally, to provide ground for future work on ultra-low-power deep and convolutional networks, scalability and robustness of the proposed multiplier is evaluated with a convolutional neural network on CIFAR-10. Similar classification accuracy with digital and SMART hardware has been observed. All the code and simulation files are available at an online public GitHub repository, https://github.com/faridken/SMART-Multiplier-for-ML. |
4,551 | Trends in American scientists' political donations and implications for trust in science | Scientists in the United States are more politically liberal than the general population. This fact has fed charges of political bias. To learn more about scientists' political behavior, we analyze publicly available Federal Election Commission data. We find that scientists who donate to federal candidates and parties are far more likely to support Democrats than Republicans, with less than 10 percent of donations going to Republicans in recent years. The same pattern holds true for employees of the academic sector generally, and for scientists employed in the energy sector. This was not always the case: Before 2000, political contributions were more evenly divided between Democrats and Republicans. We argue that these observed changes are more readily explained by changes in Republican Party attitudes toward science than by changes in American scientists. We reason that greater public involvement by centrist and conservative scientists could help increase trust in science among Republicans. |
4,552 | Development of an automated reconfigurable robotic airplane fuselage panel final assembly system using state-of-the-art automation technologies | Airspace companies regularly incorporate state-of-the-art automation technologies into their aircraft assembly systems to reduce lead times and manufacturing costs and improve product quality in their assembly plants. Rapid advances in assembly automation, robotics, material handling, measurement in the assembly processes, and systematic design methodologies require constant consideration of new applications and technologies in assembly systems' design studies for airplane structures such as fuselage panels. Such a design study is performed in this study to enable the formation of an automated, reconfigurable and robotic fuselage panel final assembly system. The authors' extensive review of the literature and catalogs reveals that stringer positioning robots, 3D projection devices for fastener position controls on the panels, reconfigurable fixtures for holding the panels, mobile refill friction stir spot joining robots to assemble clips to frames, robotic measurement systems, and modular crane for material handling can be used as state-of-the-art automation technologies in an automated and reconfigurable fuselage panel final assembly system. The proposed automated, reconfigurable, and robotic fuselage panel final assembly system provides an increase in its performance of adaptation level to the changes in the panel types, customers' order quantities, and suppliers' and customers' delivery dates. |
4,553 | Performance Evaluation of Full Search Equivalent Pattern Matching Algorithms | Pattern matching is widely used in signal processing, computer vision, and image and video processing. Full search equivalent algorithms accelerate the pattern matching process and, in the meantime, yield exactly the same result as the full search. This paper proposes an analysis and comparison of state-of-the-art algorithms for full search equivalent pattern matching. Our intention is that the data sets and tests used in our evaluation will be a benchmark for testing future pattern matching algorithms, and that the analysis concerning state-of-the-art algorithms could inspire new fast algorithms. We also propose extensions of the evaluated algorithms and show that they outperform the original formulations. |
4,554 | Multichannel magnetogastrogram: a clinical marker for pediatric chronic nausea | Chronic nausea is a widespread functional disease in children with numerous comorbidities. High-resolution electrogastrogram (HR-EGG) has shown sufficient sensitivity as a noninvasive clinical marker to objectively detect distinct gastric slow wave properties in children with functional nausea. We hypothesized that the increased precision of magnetogastrogram (MGG) slow wave recordings could provide supplementary information not evident on HR-EGG. We evaluated simultaneous pre- and postprandial MGG and HR-EGG recordings in pediatric patients with chronic nausea and healthy asymptomatic subjects, while also measuring nausea intensity and nausea severity. We found significant reductions in postprandial dominant frequency and normogastric power, and higher levels of postprandial bradygastric power in patients with nausea in both MGG and HR-EGG. MGG also detected significantly lower preprandial normogastric power in patients. A significant difference in the mean preprandial gastric slow wave propagation direction was observed in patients as compared with controls in both MGG (control: 180 ± 61°, patient: 34 ±72°; P < 0.05) and HR-EGG (control: 240 ± 39°, patient: 180 ± 46°; P < 0.05). Patients also showed a significant change in the mean slow wave direction between pre- and postprandial periods in MGG (P < 0.05). No statistical differences were observed in propagation speed between healthy subjects and patients in either MGG or HR-EGG pre/postprandial periods. The use of MGG and/or HR-EGG represents an opportunity to assess noninvasively the effects of chronic nausea on gastric slow wave activity. MGG data may offer the opportunity for further refinement of the more portable and economical HR-EGG in future machine-learning approaches for functional nausea.NEW & NOTEWORTHY Pediatric chronic nausea is a difficult-to-measure subjective complaint that requires objective diagnosis, clinical assessment, and individualized treatment plans. Our study demonstrates that multichannel MGG used in conjunction with custom HR-EGG detects key pathological signatures of functional nausea in children. This quantifiable measure may allow more personalized diagnosis and treatment in addition to minimizing the cost and potential radiation associated with current diagnostic approaches. |
4,555 | An Iterative Receiver for OFDM With Sparsity-Based Parametric Channel Estimation | In this paper, we design a receiver that iteratively passes soft information between the channel estimation and data decoding stages. The receiver incorporates sparsity-based parametric channel estimation. State-of-the-art sparsity-based iterative receivers simplify the channel estimation problem by restricting the multipath delays to a grid. Our receiver does not impose such a restriction. As a result, it does not suffer from the leakage effect, which destroys sparsity. Communication at near capacity rates in high SNR requires a large modulation order. Due to the close proximity of modulation symbols in such systems, the grid-based approximation is of insufficient accuracy. We show numerically that a state-of-the-art iterative receiver with grid-based sparse channel estimation exhibits a bit-error-rate floor in the high SNR regime. On the contrary, our receiver performs very close to the perfect channel state information bound for all SNR values. We also demonstrate both theoretically and numerically that parametric channel estimation works well in dense channels, i.e., when the number of multipath components is large and each individual component cannot be resolved. |
4,556 | MobileFAN: Transferring deep hidden representation for face alignment | Facial landmark detection is a crucial prerequisite for many face analysis applications. Deep learning-based methods currently dominate the approach of addressing the facial landmark detection. However, such works generally introduce a large number of parameters, resulting in high memory cost. In this paper, we aim for a lightweight as well as effective solution to facial landmark detection. To this end, we propose an effective lightweight model, namely Mobile Face Alignment Network (MobileFAN), using a simple backbone MobileNetV2 as the encoder and three deconvolutional layers as the decoder. The proposed MobileFAN, with only 8% of the model size and lower computational cost, achieves superior or equivalent performance compared with state-of-the-art models. Moreover, by transferring the geometric structural information of a face graph from a large complex model to our proposed MobileFAN through feature-aligned distillation and feature-similarity distillation, the performance of MobileFAN is further improved in effectiveness and efficiency for face alignment. Extensive experiment results on three challenging facial landmark estimation benchmarks including COFW, 300W and WFLW show the superiority of our proposed MobileFAN against state-of-the-art methods. (C) 2019 Elsevier Ltd. All rights reserved. |
4,557 | Who cares? The grandmother kinship carers shouldering the burden within a gendered care economy | It is estimated that around half of all kinship carers in the UK are grandparents. International studies show that when broken down by gender, these carers are predominantly grandmothers. However, there is little research exploring the gender dimensions of kinship carers' experiences. Drawing on data from qualitative interviews with 27 grandparent kinship carers, this article highlights the gendered context in which the grandparents we spoke to found themselves. The grandparents - the majority of whom were grandmothers - described lives filled with multiple unpaid caring commitments and demands. We discuss the ways that gender norms, roles and stereotypes, alongside economic models and policies that invisiblise women's care work, shaped the experiences of the grandmothers who took part in our research. We argue that, despite their undeniable determination and commitment to love, nurture and care for their grandchildren in very difficult circumstances, and the money they are saving the state in doing so, grandmother kinship carers are penalized in multiple ways. Economically, emotionally, socially, physically and practically, grandmother kinship carers are unsupported and undervalued. We need a social, economic and cultural shift around the value of care and a redistribution of care work across genders. The situations of grandmother kinship carers need to be part of this shift, so that grandmothers who care for their grandchildren are no longer penalized, and all kinship carers are properly supported and valued. |
4,558 | Constraining the age of rock art by dating a rockfall event using sediment and rock-surface luminescence dating techniques | Optically stimulated luminescence (OSL) is used to determine the age of a rockfall event that removed part of the pictograph figures at the Great Gallery rock art panel in Canyonlands National Park, Utah, USA. Analyses from the outer millimeter of the buried surface of a rockfall boulder and quartz grains from the underlying sediment both provide consistent ages that also agree with an AMS radiocarbon age of a cottonwood leaf found immediately between the clast and underlying sediment. Measurement of the OSL signals as a function of depth into the surface of the boulder clearly shows that there is no detectable increase in the OSL signal to a depth of at least 3 mm suggesting that the OSL signal was fully reset to this depth before burial. Consistent OSL and radiocarbon ages for this rockfall event provide a minimum age of similar to 900 a for the Great Gallery, which is the type locality of Barrier Canyon Style rock art with a controversial and unknown origin. (C) 2012 Elsevier B.V. All rights reserved. |
4,559 | Solving Inverse Computational Imaging Problems Using Deep Pixel-Level Prior | Signal reconstruction is a challenging aspect of computational imaging as it often involves solving ill-posed inverse problems. Recently, deep feed-forward neural networks have led to state-of-the-art results in solving various inverse imaging problems. However, being task specific, these networks have to be learned for each inverse problem. On the other hand, a more flexible approach would be to learn a deep generative model once and then use it as a signal prior for solving various inverse problems. In this paper, we show that among the various state-of-the-art deep generative models, autoregressive models are especially suitable for our purpose for the following reasons. First, they explicitly model the pixel level dependencies and hence are capable of reconstructing low-level details, such as texture patterns and edges better. Second, they provide an explicit expression for the image prior, which can then he used for MAP-based inference along with the forward model. Third, they can model long range dependencies in images which make them ideal for handling global multiplexing as encountered in various compressive imaging systems. We demonstrate the efficacy of our proposed approach in solving three computational imaging problems: Single Pixel Camera, LiSens, and FlatCam. For both real and simulated cases, we obtain better reconstructions than the state-of-the-art methods in terms of perceptual and quantitative metrics. |
4,560 | An automated system for nucleic acid extraction from formalin-fixed paraffin-embedded samples using high intensity focused ultrasound technology | Formalin-fixed paraffin-embedded (FFPE) tissue samples are routinely used in prospective and retrospective studies. It is crucial to obtain high-quality nucleic acid (NA) from FFPE samples for downstream molecular analysis, such as quantitative polymerase chain reaction (PCR), Sanger sequencing, next-generation sequencing, and microarray, in both clinical diagnosis and basic research. The current NA extraction methods from FFPE samples using chemical solvent are tedious, environmentally unfriendly, and unamenable to automation or field deployment. We present a tool for NA extraction from FFPE samples using a high-intensity focused ultrasound (HIFU) technology. A cartridge strip containing reagents for FFPE sample deparaffinization and NA extraction and purification is operated by an automation tool consisting of a HIFU module, a liquid handling robot unit, and accessories including a thermal block and magnets. The HIFU module is a single concaved piezoelectric ceramic plate driven by a current-mode class-D power amplifier. Based on the ultrasonic cavitation effects, the HIFU module provides highly concentrated energy introducing paraffin emulsification and disintegration. The high quantity and quality of NA extracted using the reported system are evaluated by PCR and compared with the quantity and quality of NA extracted using the current standard methods. |
4,561 | RESEARCH ON ENVIRONMENTAL ART DESIGN BASED ON THE GUIDANCE OF ECOLOGICAL CONCEPTS | Based on the ecological concept, this article analyzed the environmental art design of Xuanzhou Ancient Town. It introduced the environmental art composition of Xuanzhou Ancient Town through the four aspects of geographical environment, economic industry, folk customs and traditional architecture. It was pointed out that because of the lack of unified development and management, there was currently a lack of overall planning for thc demolition and reconstruction of Xuanzhou Ancient Town's ancient buildings, the existing problems of the lack of protection of the ecological environment of ancient towns and the lack of complete public infrastructure. Finally, through the three aspects of design concept, design principle and design method, the environmental art design plan of Xuanzhou ancient town guided by ecological concept was proposed to protect the ancient buildings of Xuanzhou, protect the ecological environment of Xuanzhou ancient town, improve the artistry of the ancient town, and promote local travel industry development, thus pull the economic growth, realize the harmonious development of economic development and ecological protection, and achieve the effect of sustainable development. |
4,562 | A Novel Low Rank Smooth Flat-Field Correction Algorithm for Hyperspectral Microscopy Imaging | A flat-field correction method is proposed for multiple measured hyperspectral microscopy imaging in this paper. As the most crucial preprocessing process in quantitative microscopic analysis, flat-field correction solves the uneven illumination caused by vignetting in microscopic images, and guarantees the precision of spatial and spectral information in hyperspectral microscopic imaging. In order to carry out flat-field correction and extract uneven illumination among groups of hyperspectral microscopic data containing hundreds of bands simultaneously, two properties of vignetting have been exploited: i) low-rank property is reflected by little information contained in vignetting; ii) local smoothness can be observed as a gradual change in brightness of vignetting, which is typically equivalent to the sparseness in spatial frequency domain. Combining the two properties above, a novel Low Rank Smooth Flat-field Correction (LRSFC) model modified from common orthogonal basis extraction is proposed, while an optimization is solved based on alternating direction multiplier method (ADMM), obtaining a unique flat-field term with low-rank and smooth properties. Qualitative and quantitative experimental assessments indicate that LRSFC does not add extra cell texture to the extracted flat-field term, whose performance appears prior to other state-of-the-art flat-field correction methods. |
4,563 | Tumor-targeted miRNA nanomedicine for overcoming challenges in immunity and therapeutic resistance | miRNA are critical messengers in the tumor microenvironment (TME) that influence various processes leading to immune suppression, tumor progression, metastasis and resistance. Strategies to modulate miRNAs in the TME have important implications in overcoming these challenges. However, miR delivery to specific cells in the TME has been challenging. This review discusses nanomedicine strategies to achieve cell-specific delivery of miRNAs. The key goal of delivery is to activate the tumor immune landscape as well as to prevent chemotherapy resistance. Specifically, the use of hyaluronic acid-based nanoparticle miRNA delivery to the TME is discussed. The discussion is focused on miRNA-125b for reprogramming tumor-associated macrophages to overcome immunosuppression and miRNA-let-7b to overcome resistance to anticancer chemotherapeutics because both these miRNAs have been extensively evaluated for delivery with hyaluronic acid-based delivery systems. |
4,564 | "No Alcohol, No Risk. #FASD"- Twitter Activity on Alcohol and Pregnancy among Australian Organizations | Objective: Research has suggested that information communicated by public health and industry-funded organizations differ, as organizations linked to industry have tended to downplay risks with alcohol more broadly and pregnancy specifically. There is limited knowledge of how alcohol use in pregnancy and associated risks are communicated on social media in Australia. This study set out to describe communication of health risks associated with alcohol use during pregnancy on Twitter by Australian-based organizations and stakeholders. Methods: We searched for "alcohol" and "pregnancy", "pregnant", or "FASD" on Twitter accounts belonging to potentially relevant organizations, of which 17 had tweeted on the topic. Content analysis was undertaken on all tweets and summarized under eight themes. Results: A total of 347 tweets were identified, posted between 2010 and 2019 mainly by public health and disability nongovernmental organizations. Tweets generally focused on FASD, but other potential consequences of maternal alcohol use were infrequently mentioned and tended to be generic. We found infrequent mentions of direct advice around alcohol use during pregnancy and official guidelines. Overall, tweets reflected ongoing policy debates in Australia - including alcohol warning labeling, disability policy and increased activity was seen particularly before the second parliamentary inquiry into FASD. Conclusions: The limited number of tweets from relevant organizations over a nine-year period suggests focus has been on FASD while less discussion of alcohol use during pregnancy was evident. We identified an opportunity for more and consistent communication of trusted national health guidance. |
4,565 | Selection of Reference Genes for Normalization of qRT‒PCR Analysis in the Soybean Aphid Aphis glycines Matsumura (Hemiptera: Aphididae) | The soybean aphid Aphis glycines Matsumura is a predominant insect pest in Asia and North America and causes great losses to soybean. The release of genome data for A. glycines will facilitate gene function research in the future. However, suitable reference genes for A. glycines under various experimental conditions are scarce. To search for appropriate reference genes for A. glycines, nine candidate reference genes, including Act, α-Tub, β-Tub, RPS12, RPS18, RPL5, RPL27, EF1α, and Fer, were tested under six experimental conditions to evaluate their suitability for use in the normalization of qRT‒PCR data. Results showed that EF1α and RPS12 were optimal for the developmental stages of A. glycines, RPS18 and RPS12 were appropriate for wing dimorphism, β-Tub and RPS18 were suitable for different tissues and RPL5, and α-Tub could be used for normalization at different temperatures. β-Tub and EF1α could be proposed as reference genes for insecticide treatment, and RPL5 and RPS12 were found to be the most stable reference genes in different photoperiods. The results provide appropriate reference genes for analyzing gene expression in A. glycines and contribute to future research on the molecular physiology and biochemistry of A. glycines. |
4,566 | An effective genetic algorithm for the resource levelling problem with generalised precedence relations | Resource levelling aims to obtain a feasible schedule to minimise the resource usage fluctuations during project execution. It is of crucial importance in project scheduling to ensure the effective use of scarce and expensive renewable resources, and has been successfully applied to production environments, such as make-to-order and engineering-to-order systems. In real-life projects, general temporal relationships are often needed to model complex time-dependencies among activities. We develop a novel genetic algorithm (GA) for the resource levelling problem with generalised precedence relations. Our design and implementation of GA features an efficient schedule generation scheme, built upon a new encoding mechanism that combines the random key representation and the shift vector representation. A two-pass local search-based improvement procedure is devised and integrated into the GA to enhance the algorithmic performance. Our GA is able to obtain near optimal solutions with less than 2% optimality gap for small instances in fractions of a second. It outperforms or is competitive with the state-of-the-art algorithms for large benchmark instances with size up to 1000 activities. |
4,567 | Small and Slim Deep Convolutional Neural Network for Mobile Device | Recent development of deep convolutional neural networks (DCNN) devoted in creating a slim model for devices with lower specification such as embedded, mobile hardware, or microcomputer. Slim model can be achieved by minimizing computational complexity which theoretically will make processing time faster. Therefore, our focus is to build an architecture with minimum floating-point operation per second (FLOPs). In this work, we propose a small and slim architecture which later will be compared to state-of-the-art models. This architecture will be implemented into two models which are CustomNet and CustomNet2. Each of these models implements 3 convolutional blocks which reduce the computational complexity while maintains its accuracy and able to compete with state-of-the-art DCNN models. These models will be trained using ImageNet, CIFAR 10, CIFAR 100 and other datasets. The result will be compared based on accuracy, complexity, size, processing time, and trainable parameter. From the result, we found that one of our models which is CustomNet2, is better than MobileNet, MobileNet-v2, DenseNet, NASNetMobile in accuracy, trainable parameter, and complexity. For future implementation, this architecture can be adapted using region based DCNN for multiple object detection. |
4,568 | Efficient embedding and retrieval of information for high-resolution videos coded with HEVC | Steganography is the art of hiding information within a file. This work focuses on embedding such information in videos. In this scenario, it is critical to comply with the latest video standard, namely: the High Efficiency Video Coding (HEVC), which allows reducing the size of the file to be transmitted. In this paper we propose an HEVC-compliant method to hide and retrieve information in high-resolution videos. The procedure is based on modifying the luminance of certain blocks, not the HEVC encoder. Nevertheless, this must be carefully done, as the HEVC standard is a powerful attack in itself, since it compresses 50% the size of the video on average and the embedded information may disappear. Results show that it is possible to retrieve all the information while maintaining the quality of the video when using intra frames. Furthermore, the proposed flow has shown to be resilient to state-of-the-art steganalysis attacks. (C) 2019 Elsevier Ltd. All rights reserved. |
4,569 | Gut microbial ecology of Philippine gekkonids: ecoevolutionary effects on microbiome compositions | Given the rapidly changing landscapes of habitats across the globe, a sound understanding of host-associated microbial communities and the ecoevolutionary forces that shape them is needed to assess general organismal adaptability. Knowledge of the symbiotic endogenous microbiomes of most reptilian species worldwide remains limited. We sampled gut microbiomes of geckos spanning nine species and four genera in the Philippines to (i) provide baseline data on gut microbiota in these host species, (ii) test for significant associations between host phylogenetic relationships and observed microbial assemblages, potentially indicative of phylosymbiosis, and (iii) identify correlations between multiple ecoevolutionary factors (e.g. species identity, habitat tendencies, range extents, and maximum body sizes) and gut microbiomes in Philippine gekkonids. We recovered no significant association between interspecific host genetic distances and observed gut microbiomes, providing limited evidence for phylosymbiosis in this group. Philippine gekkonid microbiomes were associated most heavily with host species identity, though marked variation among conspecifics at distinct sampling sites indicates that host locality influences gut microbiomes as well. Interestingly, individuals grouped as widespread and microendemic regardless of host species identity displayed significant differences in alpha and beta diversity metrics examined, likely driven by differences in rare OTU presence between groups. These results provide much needed insight in host-associated microbiomes in wild reptiles and the ecoevolutionary forces that structure such communities. |
4,570 | Cobalt-Catalyzed Deaminative Amino- and Alkoxycarbonylation of Aryl Trialkylammonium Salts Promoted by Visible Light | Catalytic carbonylations of aryl electrophiles via C(sp2 )-N cleavage remains a significant challenge. Herein, we demonstrate an aminocarbonylation of aniline-derived trialkylammonium salts promoted by visible light with a simple cobalt catalyst. The reaction proceeds under mild conditions suitable for late-stage functionalization and is amenable to telescoped carbonylations directly from anilines. A range of alkylamines are successful partners, and alkoxycarbonylation is also demonstrated. Mechanistic studies and DFT calculations support a novel mechanism for catalytic carbonylations of aryl electrophiles involving a key visible light-induced carbonyl photodissociation. |
4,571 | Real-Time Vehicle Detection Using an Effective Region Proposal-Based Depth and 3-Channel Pattern | Traditional deep learning-based vehicle detection methods are often designed using a pyramid of filters with multiple scales and sizes; therefore, the processing time is slow due to the large number of scales used and because the classifier runs at all scales. Recently, a deep learning-based region proposal network was introduced to detect vehicles that only employ the network one time regardless of the size of the input image. In object detection, deep learning-based region proposal networks have achieved state-of-the-art performance in terms of accuracy. These systems achieve a very high accuracy under normal driving conditions; however, their performance decreases under difficult driving conditions such as in snow, rain, or fog. In addition, the current state-of-the-art system-based region proposal networks still fail to satisfy the real-time requirements of the driving assistant systems. More recently, the identification of local patterns has been shown to improve the performance of the traditional deep-learning systems; hence, this paper investigates local patterns in region proposal networks to improve their accuracy. Depth information is also investigated to improve the processing time of current region proposal networks. Our experimental results show that the proposed system obtains better performance than the state-of-the-art object region detection systems in terms of both accuracy and processing time. |
4,572 | Time-varying harmonics: Part II - Harmonic summation and propagation | This paper represents the second part of a two-part article reviewing the state of the art of probabilistic aspects of harmonics in electric power systems. It includes tools for calculating probabilities of rectangular and phasor components of individual as well as multiple harmonic sources. A procedure for determining the statistical distribution of voltages resulting from dispersed and random current sources is reviewed. Some applications of statistical representation of harmonics are also discussed. |
4,573 | Finding Stars From Fireworks: Improving Non-Cooperative Iris Tracking | We revisit the problem of iris tracking with RGB cameras, aiming to obtain iris contours from captured images of eyes. We find the reason that limits the performance of the state-of-the-art method in more general non-cooperative environments, which prohibits a wider adoption of this useful technique in practice. We believe that because the iris boundary could be inherently unclear and blocked, as its pixels occupy only an extremely limited percentage of those on the entire image of the eye, similar to the stars hidden in fireworks, we should not treat the boundary pixels as one class to conduct end-to-end recognition directly. Thus, we propose to learn features from iris and sclera regions first, and then leverage entropy to sketch the thin and sharp iris boundary pixels, where we can trace more precise parameterized iris contours. In this work, we also collect a new dataset by smartphone with 22 K images of eyes from video clips. We annotate a subset of 2 K images, so that label propagation can be applied to further enhance the system performance. Extensive experiments over both public and our own datasets show that our method outperforms the state-of-the-art method. The results also indicate that our method can improve the coarsely labeled data to enhance the iris contour's accuracy and support the downstream application better than the prior method. |
4,574 | Metal-Organic Framework-Derived Carbon as a Photoacoustic Modulator of Alzheimer's β-Amyloid Aggregate Structure | Photoacoustic materials emit acoustic waves into the surrounding by absorbing photon energy. In an aqueous environment, light-induced acoustic waves form cavitation bubbles by altering the localized pressure to trigger the phase transition of liquid water into vapor. In this study, we report photoacoustic dissociation of beta-amyloid (Aβ) aggregates, a hallmark of Alzheimer's disease, by metal-organic framework-derived carbon (MOFC). MOFC exhibits a near-infrared (NIR) light-responsive photoacoustic characteristic that possesses defect-rich and entangled graphitic layers that generate intense cavitation bubbles by absorbing tissue-penetrable NIR light. According to our video analysis, the photoacoustic cavitation by MOFC occurs within milliseconds in the water, which was controllable by NIR light dose. The photoacoustic cavitation successfully transforms robust, β-sheet-dominant neurotoxic Aβ aggregates into nontoxic debris by changing the asymmetric distribution of water molecules around the Aβ's amino acid residues. This work unveils the therapeutic potential of NIR-triggered photoacoustic cavitation as a modulator of the Aβ aggregate structure. |
4,575 | Australian pre-service primary teachers' knowledge, attitudes, and skills regarding stuttering | Purpose: Exploring Australian pre-service primary teachers' knowledge, attitudes, and classroom strategies regarding stuttering provides speech-language pathologists (SLPs) with information that can facilitate enhanced outcomes for school-aged children who stutter.Method: In this exploratory descriptive cross-sectional study, 51 final-year Bachelor of Education (Primary) students enrolled at an Australian university completed an online survey about stuttering.Result: Responses demonstrated positive and negative beliefs. Seventy-four per cent of pre-service teachers believed that stuttering has a psychological aetiology and that students who stutter are more likely to be shy or anxious. Participants agreed that their reactions and support offered would largely be based on their assumptions rather than knowledge.Conclusion: Pre-service primary teachers share similar misconceptions and unhelpful attitudes towards stuttering with previously evaluated populations. Implications for SLPs are discussed. |
4,576 | Photosensitisation and green egg yolks in laying hens caused by the feeding of ensiled alfalfa leaves | 1. The present study was carried out to determine the effects of feeding ensiled alfalfa leaves (ALS) as an alternative protein source to laying hens under the terms of an organic diet. Due to the occurrence of unexpected negative health effects and undesirable egg yolk pigmentation in the test groups the trial was prematurely stopped and further analysis was conducted to evaluate the responsible substances.2. Body weights of the test groups decreased significantly already in week 2 of the trial. Performance variables dropped. Olive green pigmented egg yolks were found in groups fed diets containing ALS. Severe comb necrosis occurred in the experimental group receiving the highest level of ALS (20%) combined with the option of free-range access and therefore natural light exposure.3. The noxious agent found in ALS, blood serum and egg yolk was the photosensitising chlorophyll derivate pheophorbid a (PPBa), deriving from a strong depletion of chlorophyll contained in the alfalfa leaves. PPBa caused the olive-green pigmentation found in yolks and led to photosensitivity in groups with the highest level of ALS in the diet in combination with light exposure.4. By aiming for high protein and amino acid levels, harvesting and processing have, unintentionally and initially unnoticed, led to a strong accumulation of phototoxic PPBa. From these results it is strongly advised not to include ensiled alfalfa leaves as a protein source in organic laying hen diets. |
4,577 | LIGHT FORMS IN URBAN ENVIRONMENT | The paper proposes a method for generalizing and understanding the achievements of modern lighting design by means of classifying light forms and their main features are specified. The variety of types and complexity of light forms are due to avant-garde experiments in the art of the early and mid-20th century and is consistent with the successive change in artistic styles. Advances in computer technology and programming have made it possible to combine lighting elements, visual, colour and optical effects in one form. The new lighting techniques were developed for illuminating the architectural environment, various buildings, structures and forms in the spaces of world exhibitions. In this paper, the following light forms of the urban environment are investigated: projection mapping, light-graphic, light-painting and installation, sculptural, media surfaces and media facades, structural and vertical, energy-saving and virtual. The classification of light forms makes it possible to identify their structure and image, their correspondence to different eras in art, to predict the possibility of their transformation in the perspective of modern visual creativity. |
4,578 | Changes to food intake and nutrition of female red-tailed phascogales (Phascogale calura) during late lactation | Reproduction and especially lactation are nutritionally costly for mammals. Maternal access to adequate and optimal nutrients is essential for fecundity, survival of offspring, and offspring growth rates. In eutherian species energy requirements during lactation can be heavily dependent on litter size and the body mass of the female. In marsupials litter size does not appear to affect nutritional requirements during lactation; however, studies of marsupial nutritional requirements during lactation are rare. Marsupials are distinct from eutherians as they give birth to young at a much more underdeveloped state and the majority of their investment into the growth of their offspring occurs postnatally. Nutritional requirements of adult female red-tailed phascogales (Phascogale calura) were measured to determine the differences between those lactating and not lactating. On average females that were lactating had maintenance energy requirements of 1728 ± 195 kJ kg(-0.75) d(-1), double that of non-lactating animals. There was no significant correlation between energy requirements and litter size among lactating female phascogales. Apparent absorption of macronutrients did not differ between lactating and non-lactating individuals. The study has shown that food needs to be increased by at least double during late lactation. Litter size appears to have no influence on maternal nutrient requirements when food is available ad libitum and offspring in smaller litters grow faster than those in larger litters. |
4,579 | Advances in nanotechnology-based carrier systems for targeted delivery of bioactive drug molecules with special emphasis on immunotherapy in drug resistant tuberculosis - a critical review | From the early sixteenth and seventeenth centuries to the present day of life, tuberculosis (TB) still is a global health threat with some new emergence of resistance. This type of emergence poses a vital challenge to control TB cases across the world. Mortality and morbidity rates are high due to this new face of TB. The newer nanotechnology-based drug-delivery approaches involving micro-metric and nano-metric carriers are much needed at this stage. These delivery systems would provide more advantages over conventional systems of treatment by producing enhanced therapeutic efficacy, uniform distribution of drug molecule to the target site, sustained and controlled release of drug molecules and lesser side effects. The main aim to develop these novel drug-delivery systems is to improve the patient compliance and reduce therapy time. This article reviews and elaborates the new concepts and drug-delivery approaches for the treatment of TB involving solid-lipid particulate drug-delivery systems (solid-lipid micro- and nanoparticles, nanostructured lipid carriers), vesicular drug-delivery systems (liposomes, niosomes and liposphere), emulsion-based drug-delivery systems (micro and nanoemulsion) and some other novel drug-delivery systems for the effective treatment of tuberculosis and role of immunomodulators as an adjuvant therapy for management of MDR-TB and XDR-TB. |
4,580 | Fish species composition, diversity, and migration in the Mekong Delta: a study in the Cua Tieu River, Vietnam | Southern Vietnam, particularly the Mekong Delta, is popular in inland fish species diversity. In this study, fish species diversity across six stations from the estuary to the upstream of Cua Tieu River, which is situated in the Tien Giang province in Southern Vietnam, has been studied from January 2018 to June 2020. Altogether, 2088 specimens were collected and classified, and these belonged to 115 species, 98 genera, and 54 families of 15 orders that were recognized and identified. The names of species, genera, families, and orders are cited. In the total of 115 species, the Perch-like order (Perciformes) is the most diverse group, with 50 species (consist of 43.48% of total species). The catfish order (Siluriformes) is the second-most diverse group, consisting of 19 species (16.52% of total species). The carp order (Cypriniformes) consists of 8 species (6.96%), and the herring order (Clupeiformes) consists of 7 species (6.09%). Three orders of fishes, needle fish order (Beloniformes), Spiny eel order (Synbranchiformes), and flounder order (Pleuronectiformes), consist of 6 species (5.22%), and other orders consist of 1-3 species (0.87-2.61%). Among the 115 species recorded, 4 species were classified as vulnerable (VU) in the Red Data Book of Viet Nam (2007) (which is 3.48% of the total species collected). These are Elops saurus, Anodontostoma chacunda, Datnioides polota, and Toxotes chatareus. According to the IUCN Red list (2020), 1 species is endangered (EN) (0.87%), 1 species is vulnerable (VU) (0.87%), 3 species of fish are near threatened (NT) (2.61%), 6 species are data deficient (DD) (5.22%), and 58 species are least concern (LC) (50.43%). The result also recorded 41 fish as migratory species (26 freshwater species and 15 marine species), which is 35.65% of total species collected. Some migratory species are important and endemic species of the Mekong River, such as Bagarius yarrelli, Boesemania microlepis, Yasuhikotakia modesta, Cyclocheilos enoplos, Pangasianodon hypophthalmus, Pangasius conchophilus, Pangasius krempfi, Pangasius pleurotaenia, Phalacronotus bleekeri. |
4,581 | Fluvoxamine prompts the antitumor immune effect via inhibiting the PD-L1 expression on mice-burdened colon tumor | A colon tumor, one of the digestive tract malignant tumors, is harmful to human health. A potential new treatment still deserves attention. The development of a new drug needs more resources, including time and expense. Therefore, the old drug with new targets has become a current research hotspot. Fluvoxamine, as an antidepressant, could play an effect on inhibiting 5-hydroxytryptamine reuptake. In the present research, the antitumor effects and possible mechanisms of fluvoxamine are validated. The results showed that fluvoxamine significantly suppressed the migration and proliferation of tumor cells, and increased the apoptosis in vitro. Additionally, fluvoxamine significantly delays tumor development, and prompts the apoptosis in tumor tissues of mice-burdened colon tumors in vivo. The tumor suppression might be related with that fluvoxamine inhibits the expression of phosphorylated signal transducer and activator of transcription 3, matrix metalloproteinase 2, and cleaved-caspase 3. Importantly, fluvoxamine significantly reduces the expression level of programmed cell death ligand 1. This could be a possible reason that treatment with fluvoxamine drives the infiltration of T lymphocytes and M1-type macrophages in tumor tissues. Taken together, this research suggests that fluvoxamine might be a promising drug to treat colon cancer by inhibiting the proliferation and migration, inducing apoptosis, and even increasing the immune response of antitumor. |
4,582 | Deep Neural Network Compression by In-Parallel Pruning-Quantization | Deep neural networks enable state-of-the-art accuracy on visual recognition tasks such as image classification and object detection. However, modern networks contain millions of learned connections, and the current trend is towards deeper and more densely connected architectures. This poses a challenge to the deployment of state-of-the-art networks on resource-constrained systems, such as smartphones or mobile robots. In general, a more efficient utilization of computation resources would assist in deployment scenarios from embedded platforms to computing clusters running ensembles of networks. In this paper, we propose a deep network compression algorithm that performs weight pruning and quantization jointly, and in parallel with fine-tuning. Our approach takes advantage of the complementary nature of pruning and quantization and recovers from premature pruning errors, which is not possible with two-stage approaches. In experiments on ImageNet, CLIP-Q (Compression Learning by In-Parallel Pruning-Quantization) improves the state-of-the-art in network compression on AlexNet, VGGNet, GoogLeNet, and ResNet. We additionally demonstrate that CLIP-Q is complementary to efficient network architecture design by compressing MobileNet and ShuffleNet, and that CLIP-Q generalizes beyond convolutional networks by compressing a memory network for visual question answering. |
4,583 | Image super-resolution via sparse representation over multiple learned dictionaries based on edge sharpness | A new algorithm for single-image super-resolution based on selective sparse representation over a set of coupled dictionary pairs is proposed. Patch sharpness measure for high- and low-resolution patch pairs defined via the magnitude of the gradient operator is shown to be approximately invariant to the patch resolution. This measure is employed in the training stage for clustering the training patch pairs and in the reconstruction stage for model selection. For each cluster, a pair of low- and high-resolution dictionaries is learned. In the reconstruction stage, the sharpness measure of a low-resolution patch is used to select the cluster it belongs to. The sparse coding coefficients of the patch over the selected low-resolution cluster dictionary are calculated. The underlying high-resolution patch is reconstructed by multiplying the high-resolution cluster dictionary with the calculated coefficients. The performance of the proposed algorithm is tested over a set of natural images. PSNR and SSIM results show that the proposed algorithm is competitive with the state-of-the-art super-resolution algorithms. In particular, it significantly out-performs the state-of-the-art algorithms for images with sharp edges and corners. Visual comparison results also support the quantitative results. |
4,584 | Weakly supervised codebook learning by iterative label propagation with graph quantization | Visual codebook serves as a fundamental component in many state-of-the-art visual search and object recognition systems. While most existing codebooks are built based solely on unsupervised patch quantization, there are few works exploited image labels to supervise its construction. The key challenge lies in the following: image labels are global, but patch supervision should be local. Such imbalanced supervision is beyond the scope of most existing supervised codebooks [9,10,12-15,29]. In this paper, we propose a weakly supervised codebook learning framework, which integrates image labels to supervise codebook building with two steps: the Label Propagation step propagates image labels into local patches by multiple instance learning and instance selection [20,21]. The Graph Quantization step integrates patch labels to build codebook using Mean Shift. Both steps are co-optimized in an Expectation Maximization framework: the E-phase selects the best patches that minimize the semantic distortions in quantization to propagate image labels; while the M-phase groups similar patches with related labels (modeled by WordNet [18]), which minimizes the visual distortions in quantization. In quantitative experiments, our codebook outperforms state-of-the-art unsupervised and supervised codebooks [1,10,11,25,29] using benchmark datasets. (C) 2012 Elsevier B.V. All rights reserved. |
4,585 | Competency-based medical education and the McNamara fallacy: Assessing the important or making the assessed important? | The McNamara fallacy refers to the tendency to focus on numbers, metrics, and quantifiable data while disregarding the meaningful qualitative aspects. The existence of such a fallacy in medical education is reviewed in this paper. Competency-based medical education (CBME) has been introduced in India with the goal of having Indian Medical Graduates competent in five different roles - Clinician, Communicator, Leader and member of the health care team, Professional, and Lifelong learner. If we only focus on numbers and structure to assess the competencies pertaining to these roles, we would be falling prey to the McNamara fallacy. To assess these roles in the real sense, we need to embrace the qualitative assessment methods and appreciate their value in competency-based education. This can be done by using various workplace-based assessments, choosing tools based on educational impact rather than psychometric properties, using narratives and descriptive evaluation, giving grades instead of marks, and improving the quality of the questions asked in various exams. There are challenges in adopting qualitative assessment starting with being able to move past the objective-subjective debate, to developing expertise in conducting and documenting such assessment, and adding the rigor of qualitative research methods to enhance its credibility. The perspective on assessment thus needs a paradigm shift - we need to assess the important rather than just making the assessed important; and this would be crucial for the success of the CBME curriculum. |
4,586 | Clinical Report Guided Retinal Microaneurysm Detection With Multi-Sieving Deep Learning | Timely detection and treatment of microaneurysms is a critical step to prevent the development of vision-threatening eye diseases such as diabetic retinopathy. However, detecting microaneurysms in fundus images is a highly challenging task due to the low image contrast, misleading cues of other red lesions, and the large variation of imaging conditions. Existing methods tend to fail in face of the large intra-class variation and small inter-class variations for microaneurysm detection in fundus images. Recently, hybrid text/image mining computer-aided diagnosis systems have emerged to offer a promise of bridging the semantic gap between images and diagnostic information. In this paper, we focus on developing an interleaved deep mining technique to cope intelligently with the unbalanced microaneurysm detection problem. Specifically, we present a clinical report guided multi-sieving convolutional neural network, which leverages a small amount of supervised information in clinical reports to identify the potential microaneurysm regions via the image-to-text mapping in the feature space. These potential microaneurysm regions are then interleaved with fundus image information for multi-sieving deep mining in a highly unbalanced classification problem. Critically, the clinical reports are employed to bridge the semantic gap between low-level image features and high-level diagnostic information. We build an efficient microaneurysm detection framework based on the hybrid text/image interleaving and validate its performance on challenging clinical data sets acquired from diabetic retinopathy patients. Extensive evaluations are carried out in terms of fundus detection and classification. Experimental results show that our framework achieves 99.7% precision and 87.8% recall, comparing favorably with the state-of-the-art algorithms. Integration of expert domain knowledge and image information demonstrates the feasibility of reducing the difficulty of training classifiers under extremely unbalanced data distributions. |
4,587 | TMP optimization using Multivariate analysis | A new thermo-mechanical pulp refiner installation was optimized for quality parameters. The mill was state of the art and, despite having the most modern process equipment, was not able to meet the quality requirements without undergoing a deliberate optimization effort. The quality improvement results were not obtained from a single solution but by incremental changes and methodical testing. A variety of techniques were used to achieve the results in a timely and cost-effective manner. |
4,588 | New Generation Hole Transporting Materials for Perovskite Solar Cells: Amide-Based Small-Molecules with Nonconjugated Backbones | State-of-the-art perovskite-based solar cells employ expensive, organic hole transporting materials (HTMs) such as Spiro-OMeTAD that, in turn, limits the commercialization of this promising technology. Herein an HTM (EDOT-Amide-TPA) is reported in which a functional amide-based backbone is introduced, which allows this material to be synthesized in a simple condensation reaction with an estimated cost of <$5 g(-1). When employed in perovskite solar cells, EDOT-Amide-TPA demonstrates stabilized power conversion efficiencies up to 20.0% and reproducibly outperforms Spiro-OMeTAD in direct comparisons. Time resolved microwave conductivity measurements indicate that the observed improvement originates from a faster hole injection rate from the perovskite to EDOT-Amide-TPA. Additionally, the devices exhibit an improved lifetime, which is assigned to the coordination of the amide bond to the Li-additive, offering a novel strategy to hamper the migration of additives. It is shown that, despite the lack of a conjugated backbone, the amide-based HTM can outperform state-of-the-art HTMs at a fraction of the cost, thereby providing a novel set of design strategies to develop new, low-cost HTMs. |
4,589 | Transcription factor DegU-mediated multi-pathway regulation on lichenysin biosynthesis in Bacillus licheniformis | Lichenysin, producted by Bacillus licheniformis, is an important cyclic lipopeptide biosurfactant, which has potential applications in oil exploitation, drug development, biological control of agriculture and bioremediation. While studies are lacking on metabolism regulation of lichenysin biosynthesis, which limits metabolic engineering and large-scale production of lichenysin. In this study, the yield of lichenysin was improved obviously by 13.6 folds to 2.18 ± 0.03 g/L in degU deletion strain (WX02△degU) compared with the wild-type strain (WX02) and completely inhibited in degU overexpressed strain (WX02/pHY-degU). We further proved that DegU, a transcription factor plays a significant role in multicellular behavior, is a key negative regulator of lichenysin synthesis lchA operon. But interestingly, lichenysin yield was still inhibited by overexpressing DegU in the promoter-substituted strain (WX02-PP43lch), in which promoter of lchA operon cannot be controlled by DegU. Thus, through 13C-metabolic flux analysis, we found that deletion of degU also enhanced glucose uptake, branched chain amino acid synthesis, and fatty acid synthesis, while decrease acetoin synthesis, which is beneficial for the supply of lichenysin precursors. Further experiments demonstrate that DegU regulates these pathways by binding to the promoter regions of related genes. Overall, we systematically investigated the multi-pathway regulation network mediated by DegU on lichenysin biosynthesis, which not only contributes to the further metabolic engineering for lichenysin high-production, but sheds light on studies of transcription factor regulation. |
4,590 | A novel multiple description coding scheme compatible with the JPEG2000 decoder | In this letter we propose a novel technique to generate rate-distortion optimized multiple descriptions of images, exploiting the rate-allocation strategy embedded in the JPEG2000 encoder. The proposed scheme can be applied to any encoding algorithm, given that the rate allocation is based on code-block truncation. The method yields excellent performance in terms of both central and side distortion, outperforming state-of-the art techniques. Moreover, the single description decoding is fully compatible with the JPEG2000 Part 1 decoder. |
4,591 | X-Net: A Binocular Summation Network for Foreground Segmentation | In foreground segmentation, it is challenging to construct an effective background model to learn the spatial-temporal representation of the background. Recently, deep learning-based background models (DBMs) with the capability of extracting high-level features have shown remarkable performance. However, the existing state-of-the-art DBMs deal with video segmentation as single-image segmentation and ignore temporal cues in video sequences. To exploit temporal data sufficiently, this paper proposes a multi-input multi-output (MIMO) DBM framework for the first time, which is partially inspired by the binocular summation effect in human eyes. Our framework is an X-shaped network which allows the DBM to track temporal changes in a video sequence. Moreover, each output branch of our model could receive visual signals from two similar input frames simultaneously like the binocular summation mechanism. In addition, our model can be trained end-to-end using only a few training examples without any post-processing. We evaluate our method on the largest dataset for change detection (CDnet 2014) and achieve the state-of-the-art performance by an average overall F-Measure of 0.9920. |
4,592 | Partially Linear Estimation With Application to Sparse Signal Recovery From Measurement Pairs | We address the problem of estimating a random vector X from two sets of measurements Y and Z, such that the estimator is linear in Y. We show that the partially linear minimum mean-square error (PLMMSE) estimator does not require knowing the joint distribution of X and Y in full, but rather only its second-order moments. This renders it of potential interest in various applications. We further show that the PLMMSE method is minimax-optimal among all estimators that solely depend on the second-order statistics X of Y and. We demonstrate our approach in the context of recovering a signal, which is sparse in a unitary dictionary, from noisy observations of it and of a filtered version. We show that in this setting PLMMSE estimation has a clear computational advantage, while its performance is comparable to state-of-the-art algorithms. We apply our approach both in static and in dynamic estimation applications. In the former category, we treat the problem of image enhancement from blurred/noisy image pairs. We show that PLMMSE estimation performs only slightly worse than state-of-the art algorithms, while running an order of magnitude faster. In the dynamic setting, we provide a recursive implementation of the estimator and demonstrate its utility in tracking maneuvering targets from position and acceleration measurements. |
4,593 | Culture media composition influences patient-derived organoid ability to predict therapeutic responses in gastrointestinal cancers | BACKGROUNDA patient-derived organoid (PDO) platform may serve as a promising tool for translational cancer research. In this study, we evaluated PDO's ability to predict clinical response to gastrointestinal (GI) cancers.METHODSWe generated PDOs from primary and metastatic lesions of patients with GI cancers, including pancreatic ductal adenocarcinoma, colorectal adenocarcinoma, and cholangiocarcinoma. We compared PDO response with the observed clinical response for donor patients to the same treatments.RESULTSWe report an approximately 80% concordance rate between PDO and donor tumor response. Importantly, we found a profound influence of culture media on PDO phenotype, where we showed a significant difference in response to standard-of-care chemotherapies, distinct morphologies, and transcriptomes between media within the same PDO cultures.CONCLUSIONWhile we demonstrate a high concordance rate between donor tumor and PDO, these studies also showed the important role of culture media when using PDOs to inform treatment selection and predict response across a spectrum of GI cancers.TRIAL REGISTRATIONNot applicable.FUNDINGThe Joan F. & Richard A. Abdoo Family Fund in Colorectal Cancer Research, GI Cancer program of the Mayo Clinic Cancer Center, Mayo Clinic SPORE in Pancreatic Cancer, Center of Individualized Medicine (Mayo Clinic), Department of Laboratory Medicine and Pathology (Mayo Clinic), Incyte Pharmaceuticals and Mayo Clinic Hepatobiliary SPORE, University of Minnesota-Mayo Clinic Partnership, and the Early Therapeutic program (Department of Oncology, Mayo Clinic). |
4,594 | Loss of Rai1 enhances hippocampal excitability and epileptogenesis in mouse models of Smith-Magenis syndrome | Hyperexcitability of brain circuits is a common feature of autism spectrum disorders (ASDs). Genetic deletion of a chromatin-binding protein, retinoic acid induced 1 (RAI1), causes Smith-Magenis syndrome (SMS). SMS is a syndromic ASD associated with intellectual disability, autistic features, maladaptive behaviors, overt seizures, and abnormal electroencephalogram (EEG) patterns. The molecular and neural mechanisms underlying abnormal brain activity in SMS remain unclear. Here we show that panneural Rai1 deletions in mice result in increased seizure susceptibility and prolonged hippocampal seizure duration in vivo and increased dentate gyrus population spikes ex vivo. Brain-wide mapping of neuronal activity pinpointed selective cell types within the limbic system, including the hippocampal dentate gyrus granule cells (dGCs) that are hyperactivated by chemoconvulsant administration or sensory experience in Rai1-deficient brains. Deletion of Rai1 from glutamatergic neurons, but not from gamma-aminobutyric acidergic (GABAergic) neurons, was responsible for increased seizure susceptibility. Deleting Rai1 from the Emx1Cre-lineage glutamatergic neurons resulted in abnormal dGC properties, including increased excitatory synaptic transmission and increased intrinsic excitability. Our work uncovers the mechanism of neuronal hyperexcitability in SMS by identifying Rai1 as a negative regulator of dGC intrinsic and synaptic excitability. |
4,595 | Communal visual histories to detect environmental change in northern areas: Examples of emerging North American and Eurasian practices | This article explores the pioneering potential of communal visual-optic histories which are recorded, painted, documented, or otherwise expressed. These materials provide collective meanings of an image or visual material within a specific cultural group. They potentially provide a new method for monitoring and documenting changes to ecosystem health and species distribution, which can effectively inform society and decision makers of Arctic change. These visual histories can be positioned in a continuum that extends from rock art to digital photography. They find their expressions in forms ranging from images to the oral recording of knowledge and operate on a given cultural context. For monitoring efforts in the changing boreal zone and Arctic, a respectful engagement with visual histories can reveal emerging aspects of change. The examples from North America and case studies from Eurasia in this article include Inuit sea ice observations, Yu'pik visual traditions of masks, fish die-offs in a sub-boreal catchment area, permafrost melt in the Siberian tundra and early, first detection of a scarabaeid beetle outbreak, a Southern species in the Skolt Sami area. The pros and cons of using these histories and their reliability are reviewed. |
4,596 | A Scalable Privacy-Preserving Multi-Agent Deep Reinforcement Learning Approach for Large-Scale Peer-to-Peer Transactive Energy Trading | Peer-to-peer (P2P) transactive energy trading has emerged as a promising paradigm towards maximizing the flexibility value of prosumers' distributed energy resources (DERs). Despite reinforcement learning constitutes a well-suited model-free and data-driven methodological framework to optimize prosumers' energy management decisions, its application to the large-scale coordinated management and P2P trading among multiple prosumers within an energy community is still challenging, due to the scalability, non-stationarity and privacy limitations of state-of-the-art multi-agent deep reinforcement learning (MADRL) approaches. This paper proposes a novel P2P transactive trading scheme based on the multi-actor-attention-critic (MAAC) algorithm, which addresses the above challenges individually. This method is complemented by a P2P trading platform that incentivizes prosumers to engage in local energy trading while also penalizes each prosumer's addition to rebound peaks. Case studies involving a real-world, large-scale scenario with 300 residential prosumers demonstrate that the proposed method significantly outperforms the state-of-the-art MADRL methods in reducing the community's cost and peak demand. |
4,597 | Recent Progress of Carbon Dots for Air Pollutants Detection and Photocatalytic Removal: Synthesis, Modifications, and Applications | Rapid industrialization has inevitably led to serious air pollution problems, thus it is urgent to develop detection and treatment technologies for qualitative and quantitative analysis and efficient removal of harmful pollutants. Notably, the employment of functional nanomaterials, in sensing and photocatalytic technologies, is promising to achieve efficient in situ detection and removal of gaseous pollutants. Among them, carbon dots (CDs) have shown significant potential due to their superior properties, such as controllable structures, easy surface modification, adjustable energy band, and excellent electron-transfer capacities. Moreover, their environmentally friendly preparation and efficient capture of solar energy provide a green option for sustainably addressing environmental problems. Here, recent advances in the rational design of CDs-based sensors and photocatalysts are highlighted. An overview of their applications in air pollutants detection and photocatalytic removal is presented, especially the diverse sensing and photocatalytic mechanisms of CDs are discussed. Finally, the challenges and perspectives are also provided, emphasizing the importance of synthetic mechanism investigation and rational design of structures. |
4,598 | Building Relationships between Museums and Schools: Reggio Emilia as a Bridge to Educate Children about Heritage | Schools and museums represent essential spaces for the development of learning and understanding of the world surrounding us through the arts and heritage. One of the things learned in the COVID crisis is that it is key to build bridges between schools and museums to support their educational activities, regardless of the possibility to access these spaces in person. School teachers and museum educators have the opportunity to develop a critical and creative citizenry by collaborating in the design of learning activities that can bring the museums to schools and schools to the museum by adopting the Reggio Emilia approach. The results of the study arise from a triangulation of data, as we contrasted the literature about the Reggio Emilia approach with the practices of museums that use such a philosophy and with the analysis of a series of interviews with experts in early childhood education and Reggio Emilia in order to identify a series of good practices, which we used to delineate recommendations to foster the adoption of this model and establish relationships between schools and museums, enhancing the opportunities to develop critical and creative thinking throughout activities and to understand the heritage and the arts, thus fostering citizenship from an early childhood. |
4,599 | Hybrid polymeric therapeutic microcarriers for thermoplasmonic-triggered release of resveratrol | Diabetic retinopathy (DR) is a severe ocular complication that causes retinal damage, being one of the leading causes of blindness globally, thus the development of new strategies to prevent and treat DR as well as other degenerative diseases is highly desired. This work is focused on the design and fabrication of an ingenious model of polymeric microcapsules (MC) for controlled drug delivery in human retina cells able to carry therapeutic resveratrol (RSV) molecules in tandem with active anisotropic gold bipyramidal nanoparticles (AuBPs) as efficient photothermal agents. Specifically, MC were developed via a Layer-by-Layer deposition technique, by successively adding oppositely charged polyelectrolytes on a RSV-conjugated calcium carbonate (CaCO3) core. For the monitorization and localization of the as-formed spherical fluorescent MC inside human retina pigmented epithelial (RPE) D407 cells, fluorescein isothiocyanate, a Food and Drug Administration approved fluorophore, was attached between the polyelectrolytes layers. High-performance liquid chromatography analysis revealed a loading efficiency of over 90% of RSV on the CaCO3 core and demonstrates its release upon NIR irradiation as a consequence of the thermoplasmonic effect of MC. The cytotoxicity of the RSV-carrying MC inside human retina cells was assessed by WST-1 assay. Finally, cellular internalization and localization of the MC inside living RPE cells were monitored via Conventional Fluorescence and Re-Scanning Confocal Fluorescence Microscopy. This research seeks to take use of the novel MC and implement them as potential intraocular RSV delivery vehicles for the therapy of DR. |
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