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2,200 | Does plantar skin abrasion affect cutaneous mechanosensation? | In humans, plantar cutaneous mechanoreceptors provide critical input signals for postural control during walking and running. Because these receptors are located within the dermis, the mechanical properties of the overlying epidermis likely affect the transmission of external stimuli. Epidermal layers are highly adaptable and can form hard and thick protective calluses, but their effects on plantar sensitivity are currently disputed. Some research has shown no effect of epidermal properties on sensitivity to vibrations, whereas other research suggests that vibration and touch sensitivity diminishes with a thicker and harder epidermis. To address this conflict, we conducted an intervention study where 26 participants underwent a callus abrasion while an age-matched control group (n = 16) received no treatment. Skin hardness and thickness as well as vibration perception thresholds and touch sensitivity thresholds were collected before and after the intervention. The Callus abrasion significantly decreased skin properties. The intervention group exhibited no change in vibration sensitivity but had significantly better touch sensitivity. We argue that touch sensitivity was impeded by calluses because hard skin disperses the monofilament's standardized pressure used to stimulate the mechanoreceptors over a larger area, decreasing indentation depth and therefore stimulus intensity. However, vibration sensitivity was unaffected because the vibrating probe was adjusted to reach specific indentation depths, and thus stimulus intensity was not affected by skin properties. Since objects underfoot necessarily indent plantar skin during weight-bearing, calluses should not affect mechanosensation during standing, walking, or running. |
2,201 | Parallel graph traversal for FPGA | This paper presents a multi-channel memory based architecture for parallel processing of large-scale graph traversal for field-programmable gate array (FPGA). By designing a multi-channel memory subsystem with two DRAM modules and two SRAM chips and developing an optimized pipelining structure for the processing elements, we achieve superior performance to that of a state-of-the-art highly optimized BFS implementations using the same type of FPGA. |
2,202 | State-of-the-art performance in text-independent speaker verification through open-source software | This paper illustrates an evolution in state-of-the-art speaker verification by highlighting the contribution from newly developed techniques. Starting from a baseline system based on Gaussian mixture models that reached state-of-the-art performances during the NIST'04 SRE, final systems with new intersession compensation techniques show a relative gain of around 50%. This work highlights that a key element in recent improvements is still the classical maximum a posteriori (MAP) adaptation, while the latest compensation methods have a crucial impact on overall performances. Nuisance attribute projection (NAP) and factor analysis (FA) are examined and shown to provide significant improvements. For FA, a new symmetrical scoring (SFA) approach is proposed. We also show further improvement with an original combination between a support vector machine and SFA. This work is undertaken through the open-source ALIZE toolkit. |
2,203 | Removal of Penicillin G from aqueous medium by PPI@SBA-15/ZIF-8 super adsorbent: Adsorption isotherm, thermodynamic, and kinetic studies | In the present paper, synthesis of SBA-15 nanoparticles was carried out from tetraethyl orthosilicate (TEOS) precursor using the sol-gel process. After being combined with Poly propylene imine, and ZIF-8 they were employed for the removal of Penicillin G. The synthesized combination morphology was assessed using nitrogen adsorption and desorption (BET), Fourier transform infrared (FTIR) spectroscopy, and X-ray powder diffraction (XRD). The parameters affecting Penicillin G removal, including pH, amount of adsorbent, time of contact, temperature, and concentration, were optimized, and the optimum levels of the mentioned variables were reported to be pH = 3, 0.03 g, 90 min, 25 °C, and 100 ppm, respectively. In addition, application of Freundlich, Langmuir, Dubinin-Radushkevhch, and Tempkin models and pseudo-first-order and pseudo-second-order adsorption synthetic equations aimed at determining the type of adsorbent isotherm. The results showed that the best fitting of Langmuir (R2 = 0.9944, qm = 400 mg/g) for adsorption isotherm and pseudo-second-order model (R2 = 0.9905) for kinetics studies. Furthermore, data of Gibbs free energy and enthalpy demonstrated an exothermic and spontaneous process in the research. |
2,204 | Minimal Solvers for Rectifying From Radially-Distorted Conjugate Translations | This paper introduces minimal solvers that jointly solve for radial lens undistortion and affine-rectification using local features extracted from the image of coplanar translated and reflected scene texture, which is common in man-made environments. The proposed solvers accommodate different types of local features and sampling strategies, and three of the proposed variants require just one feature correspondence. State-of-the-art techniques from algebraic geometry are used to simplify the formulation of the solvers. The generated solvers are stable, small and fast. Synthetic and real-image experiments show that the proposed solvers have superior robustness to noise compared to the state of the art. The solvers are integrated with an automated system for rectifying imaged scene planes from coplanar repeated texture. Accurate rectifications on challenging imagery taken with narrow to wide field-of-view lenses demonstrate the applicability of the proposed solvers. |
2,205 | Unilateral absence of pulmonary artery with absent pulmonary valve in tetralogy of Fallot | The incidence of absent pulmonary valve (APV) in tetralogy of Fallot is 2.4 to 6.3%. About 1-3% of the patients with tetralogy of Fallot will have unilateral absence of pulmonary artery (UAPA). However, coexistence of APV with tetralogy of Fallot (TOF) and UAPA is extremely rare. This rare subset can present in two forms. In one group, the main pulmonary artery continues as either left or right pulmonary artery (UAPA) and there is true absence of contralateral pulmonary artery. The second group is termed as unilateral anomalous origin of pulmonary artery (UAOPA), in which the contralateral lung is supplied either by patent ductus arteriosus or a collateral from the aorta. There are a limited number of these cases in the literature. We present a rare case of TOF with APV and UAPA managed using a different surgical technique. Also, we have done contemporary literature review. |
2,206 | The User Experience of an Immersive and Interactive Wall Exergame in Older Adults | Exergames are promising options for modulating the effects of aging on physical and cognitive functions. A new-generation immersive and interactive wall exergame (I2WE) has emerged in recent years, offering users freedom of movement as well as greater and varied interactions with other players, the environment, and the system than traditional games (e.g., Wii™, Kinect). These features could improve the user experience (UX) and thus the engagement and benefits of the intervention for older people. The purpose of this study was to determine whether this kind of exergame could be an effective tool for multidomain training for the elderly. An exploratory study was conducted with 38 healthy older adults who tested a single exergame session to evaluate the UX and the perceived enjoyment, as well as the session's workload and intensity. The results show that I2WE generates moderate-to-high physical intensity, following recommendations for older people, while the perceived exertion is lower. Moreover, it creates a positive UX that correlates with high perceived enjoyment while producing a suitable session's workload. I2WE appears to be an effective tool to promote physical activity while concurrently stimulating cognition in older adults. The intrinsic characteristics (i.e., immersion, combined physical and cognitive activity, interactions, complex motor skills, playfulness, and variety of collective games) give this new type of exergame a promising future. Future studies should be conducted to investigate the effects of an I2WE program on the physical and cognitive functions of older adults. |
2,207 | UK Transcatheter Aortic Valve Implantation trial - time to differentiate "non-inferiority" from "equivalence"? | The UK Transcatheter Aortic Valve Implantation (UK-TAVI) trial has compared transcatheter aortic valve implantation (TAVI) and surgical aortic valve replacement (SAVR) in patients above the age of 70 years with moderate operative risk. The primary outcome was 1-year all-cause mortality. This was a non-inferiority trial that concluded that TAVI in this cohort was non-inferior to SAVR. This appraisal reports the main findings of the study and discusses the strengths and weaknesses of the trial. |
2,208 | Addressing the value of art in cartographic communication | Contemporary methods for depicting the earth and its cultural and natural attributes use graphic and non-graphic formats, maps and map-related artefacts, for visualizing geography and building virtual landscapes and environments. The discipline area of cartography, traditionally, has applied art (design), science and technology to map making to design and realise these products. Prior to the mid-1950s, cartographic artefacts were built under the theoretical and practical 'umbrella' of this partnership of art, science and technology. However, since then, the theory and methodology associated with visualizing geography has focused on Science and Technology, and away from Art. This 'move' away from art was accelerated by: (1) computing, computers and complete automated systems; and (2) the 'quest' to gain 'scientific legitimacy' by using scientific visualization as a lodestone for gauging the 'quality' of theories and applications. Science and Technology has been embraced by cartography as a means to ensure that what is presented is scientifically 'correct' products are considered to 'work' if they are scientifically 'elegant', 'technologically' buildable' and 'deliverable' using contemporary communication systems. But, it is argued, science or technology, need not always take on primary roles, and there now is a need to address the role that design should take to facilitate the further development of contemporary cartography, especially in the areas where new media has been applied to facilitate the building of geographical visualization tools. This paper will address how, by incorporating art elements into the design criteria of geographical visualization artefacts, 'different' visualization tools might be provided using all three elements of cartography: art, science and technology. (C) 2010 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved. |
2,209 | Art and craft material use patterns by pre-school and elementary school children at home and school: a year long survey for refining exposure assessments | BACKGROUND: Use frequency and times are critical parameters for estimating realistic chemical exposures associated with the use of consumer products. Very limited information is available in the published literature for children's use patterns of art and craft materials at home and school.OBJECTIVE: Conduct a year-long survey of art materials use at home and school by pre-school and elementary school children, teachers, and parents which can be used to refine chemical exposure assessments for these consumer products.METHODS: Parent and teacher online surveys were conducted on the daily use of markers and monthly use of fifteen additional art and craft materials.RESULTS: Daily marker use by elementary children was widespread at home and school (65% and 80%, respectively). On average, pre-school and elementary students used markers for 27 min per day, more than double daily home use. Adults used markers for longer durations relative to their children/students with teachers reporting the highest average daily usage time. School use of general art materials exceeded home use for both age groups, with elementary children using art materials more frequently than their pre-school counterparts. Examples of how these data can be used to refine exposure estimates are provided.SIGNIFICANCE: Accurate art material usage data contributes to refined estimates of chemical exposure for these consumer products. |
2,210 | Source segregation of food waste in office areas: Factors affecting waste generation rates and quality | Existing legislation mandates that the amount of waste being recycled should be increased. Among others, in its Resource Strategy Plan, the Danish Government decided that at least 60% of food waste generated by the service sector, including in office areas, should be source-sorted and collected separately by 2018. To assess the achievability of these targets, source-sorted food waste and residual waste from office areas was collected and weighed on a daily basis during 133 working days. Waste composition analyses were conducted every week to investigate the efficiency of the source-sorting campaign and the purity of the source-sorted food waste. The moisture content of source-sorted food waste and residual waste fractions, and potential methane production from source-sorted food waste, was also investigated. Food waste generation equated to 23 ± 5 kg/employee/year, of which 20 ± 5 kg/employee/year was source-sorted, with a considerably high purity of 99%. Residual waste amounted to 10 ± 5 kg/employee/year and consisted mainly of paper (29 ± 13%), plastic (23 ± 9%) and missorted food waste (24 ± 16%). The moisture content of source-sorted food waste was significantly higher (8%) than missorted food waste, and the methane potential of source-sorted food waste was 463 ± 42 mL CH4/g VS. These results show that food waste in office areas offers promising potential for relatively easily collectable and pure source-sorted food waste, suggesting that recycling targets for food waste could be achieved with reasonable logistical ease in office areas. |
2,211 | Predicting the evolution trajectory of population-driven connectional brain templates using recurrent multigraph neural networks | The mapping of the time-dependent evolution of the human brain connectivity using longitudinal and multimodal neuroimaging datasets provides insights into the development of neurological disorders and the way they alter the brain morphology, structure and function over time. Recently, the connectional brain template (CBT) was introduced as a compact representation integrating a population of brain multigraphs, where two brain regions can have multiple connections, into a single graph. Given a population of brain multigraphs observed at a baseline timepoint t1, we aim to learn how to predict the evolution of the population CBT at follow-up timepoints t>t1. Such model will allow us to foresee the evolution of the connectivity patterns of healthy and disordered individuals at the population level. Here we present recurrent multigraph integrator network (ReMI-Net⋆) to forecast population templates at consecutive timepoints from a given single timepoint. In particular, we unprecedentedly design a graph neural network architecture to model the changes in the brain multigraph and identify the biomarkers that differentiate between the typical and atypical populations. Addressing such issues is of paramount importance in diagnosing neurodegenerative disorders at early stages and promoting new clinical studies based on the pinned-down biomarker brain regions or connectivities. In this paper, we demonstrate the design and use of the ReMI-Net⋆ model, which learns both the multigraph node level and time level dependencies concurrently. Thanks to its novel graph convolutional design and normalization layers, ReMI-Net⋆ predicts well-centered, discriminative, and topologically sound connectional templates over time. Additionally, the results show that our model outperforms all benchmarks and state-of-the-art methods by comparing and discovering the atypical connectivity alterations over time. Our ReMI-Net⋆ code is available on GitHub at https://github.com/basiralab/ReMI-Net-Star. |
2,212 | 3,4,5-Trimethoxycinnamic acid, one of the constituents of Polygalae Radix exerts anti-seizure effects by modulating GABAAergic systems in mice | Polygalae Radix is an important medicinal plant that is widely used in most of Africa. 3,4,5-Trimethoxycinnamic acid (TMCA) is one of the constituents of Polygalae Radix. Until now, the mechanisms involved in the anti-seizure property of TMCA are still unclear. We examined the anti-seizure effect of TMCA. TMCA administered at doses of 5, 10 and 20 mg/kg and evaluated anti-seizure effects by maximal electroshock (MES) and pentylenetetrazol (PTZ) models in mice. TMCA administered at doses of 10 and 20 mg/kg significantly reduced the incidence of MES-induced tonic hindlimb extension (THE). TMCA significantly delayed the onset of myoclonic jerks (MJ), and decreased the seizure severity and mortality compared with the vehicle-treated animals in PTZ seizure model. TMCA 10 and 20 mg/kg treated groups also did not determined generalized clonic seizures (GCS). Pretreatment with a GABAA/benzodiazepine (BZ) receptor antagonist flumazenil blocked the anti-seizure effects of TMCA. These data support the further investigation of TMCA as a GABAA/BZ receptor agonist for anti-seizure therapy. |
2,213 | Discrimination of EMG Signals Using a Neuromorphic Implementation of a Spiking Neural Network | An accurate description of muscular activity plays an important role in the clinical diagnosis and rehabilitation research. The electromyography (EMG) is the most used technique to make accurate descriptions of muscular activity. The EMG is associated with the electrical changes generated by the activity of the motor neurons. Typically, to decode the muscular activation during different movements, a large number of individual motor neurons are monitored simultaneously, producing large amounts of data to be transferred and processed by the computing devices. In this paper, we follow an alternative approach that can be deployed locally on the sensor side. We propose a neuromorphic implementation of a spiking neural network (SNN) to extract spatio-temporal information of EMG signals locally and classify hand gestures with very low power consumption. We present experimental results on the input data stream using a mixed-signal analog/digital neuromorphic processor. We performed a thorough investigation on the performance of the SNN implemented on the chip, by: first, calculating PCA on the activity of the silicon neurons at the input and the hidden layers to show how the network helps in separating the samples of different classes; second, performing classification of the data using state-of-the-art SVM and logistic regression methods and a hardware-friendly spike-based read-out. The traditional algorithm achieved a classification rate of $\text{84}\%$ and $\text{81}\%$, respectively, and the spiking learning method achieved $\text{74}\%$. The power consumption of the SNN is $\text{0.05 mW}$, showing the potential of this approach for ultra-low power processing. |
2,214 | State-of-the-art progress for the selective crystallization of actinides, synthesis of actinide compounds and their functionalization | Crystallization and immobilization of actinides to form actinide compounds are of significant importance for the extraction and reutilization of nuclear waste in the nuclear industry. In this paper, the state-of-art progress in the crystallization of actinides are summarized, as well as the main functionalization of the actinide compounds, i.e., as adsorbents for heavy metal ions and organic pollutant in waste management, as (photo)catalysts for organic degradation and conversion, including degradation of organic dyes and antibiotics, dehydrogenation of N-heterocycles, CO2 cycloaddition, selective alcohol oxidation and selective oxidation of sulfides. This review will give a comprehensive summary about the synthesis and application exploration of solid actinide crystalline salts and actinide-based metal organic frameworks in the past decades. Finally, the future perspectives and challenges are proposed in the end to give a promising direction for future investigation. |
2,215 | The Abstract Expressionists and Les Automatistes: A shared multi-fractal depth? | Statistical analysis of abstract paintings is becoming an increasingly important tool for understanding the creative process of visual artists. We present a multifractal analysis of 'poured' paintings from the Abstract Expressionism and Les Automatistes movements. The box-counting dimension (D-o) is measured for the analyzed paintings, as is the associated multifractal depth Delta D=D-o - D-infinity, where D-infinity, is the asymptotic dimension. We investigate the role of depth by plotting a 'phase space' diagram that examines the relationship between D-o and D-infinity. We show that, although the D-o and D-infinity values vary between individual paintings, the collection of paintings exhibit a similar depth, suggesting a shared visual characteristic for this genre. We discuss the visual implications of this result. (C) 2012 Elsevier B.V. All rights reserved. |
2,216 | Two distinct conformational states of Mycobacterium tuberculosis virulent factor early secreted antigenic target 6 kDa are behind the discrepancy around its biological functions | Early secreted antigenic target 6 kDa (ESAT-6) and culture filtrate protein 10 kDa (CFP-10) are complex proteins secreted by Mycobacterium tuberculosis that play a major role in the pathogenesis of tuberculosis. However, studies focusing on the biological functions of ESAT-6 led to discordant results and the role of ESAT-6 remains controversial. In the present study, we aim to address a potential explanation for this discrepancy and to highlight the physiological impact of two conformational states of ESAT-6. Analysis of a recombinant form of ESAT-6 by native gel electrophoresis, size exclusion chromatography and CD spectroscopy revealed that ESAT-6 forms dimers/multimers with higher molecular weight, which disappeared under the action of the detergent amidosulfobetaine-14 (ASB), giving rise to another conformational state of the protein. NMR has further indicated that ASB-treated versus nontreated ESAT-6 adopted distinct structural forms but with no well defined tertiary structure. However, protein-protein docking analysis favored a dimeric state of ESAT-6. Interestingly, the two preparations presented opposing effects on mycobacterial infectivity, as well as macrophage survival, interferon-γ secretion and membrane pore formation. Thereafter, we generated a recombinant form of the physiological heterodimer ESAT-6/CFP-10 that ASB was also able to dissociate and which showed functions similar to those of ESAT-6 dimers/multimers. Our data suggest that, in the absence of CFP-10, the hydrophobic regions of the ESAT-6 can form dimers/multimers, mimicking the ESAT-6/CFP-10 heterodimer, whereas their dissociation generates a protein presenting entirely different activities. Overall, the present study clarifies the intriguing divergences between reports that could be attributed to the ESAT-6 oligomeric state and sheds light on its importance for a better comprehension of the physiopathology of tuberculosis. |
2,217 | Deformable Image Registration Using Functions of Bounded Deformation | Deformable image registration is a widely used technique in the field of computer vision and medical image processing. Basically, the task of deformable image registration is to find the displacement field between the moving image and the fixed image. Many variational models are proposed for deformable image registration, under the assumption that the displacement field is continuous and smooth. However, displacement fields may be discontinuous, especially for medical images with intensity inhomogeneity, pathological tissues, or heavy noises. In the mathematical theory of elastoplasticity, when the displacement fields are possibly discontinuous, a suitable framework for describing the displacement fields is the space of functions of bounded deformation (BD). Inspired by this, we propose a novel deformable registration model, called the BD model, which allows discontinuities of displacement fields in images. The BD model is formulated in a variational framework by supposing the displacement field to be a function of BD. The existence of solutions of this model is proven. Numerical experiments on 2D images show that the BD model outperforms the classical demons model, the log-domain diffeomorphic demons model, and the state-of-the-art vectorial total variation model. Numerical experiments on two public 3D databases showthat the target registration error of the BD model is competitive compared with more than ten other models. |
2,218 | Illness representations and psychological adjustment of Greek couples dealing with a recently-diagnosed cancer: dyadic, interaction and perception-dissimilarity effects | The aim was to examine the impact of the dyadic, interaction and dissimilarity effects of the illness representations on the psychological health of recently diagnosed cancer patients and spouses in Greece. The sample consisted of 298 individuals nested in 149 couples. Effects were examined with the Actor-Partner Interdependence Model. Both actor (i.e., within person) and partner (i.e., between partners) effects were detected for both patients' and spouses' psychological symptoms. The negative association of patients' psychological symptoms with their representations of illness coherence was weak at the higher and medium levels, and stronger at the lower levels of spouse corresponding representations. Patient-partner discrepancy in perceived illness consequences was associated with more psychological symptoms in patients. Adaptation to cancer is a dyadic process within the context of which patient and partner psychological well-being is affected by each other's understanding of illness. Thus, the parallel examination of the illness representations of both partners is needed from the early phases of the illness trajectory. |
2,219 | A concise tutorial on human motion tracking and recognition with Microsoft Kinect | This paper provides a concise tutorial on the Microsoft Kinect technology and the state of art research on human motion tracking and recognition with Microsoft Kinect. A pre-requisite for human motion recognition is feature extraction. There are two types of feature extraction methods: skeleton joint based, and depth/color image based. Given a set of feature vectors, a motion could be recognized using machine learning, direct comparison, or rule-based methods. We also outline future research directions on the Kinect technology. |
2,220 | Ideal Regularized Composite Kernel for Hyperspectral Image Classification | This paper proposes an ideal regularized composite kernel (IRCK) framework for hyperspectral image (HSI) classification. In learning a composite kernel, IRCK exploits spectral information, spatial information, and label information simultaneously. It incorporates the labels into standard spectral and spatial kernels by means of the ideal kernel according to a regularization kernel learning framework, which captures both the sample similarity and label similarity and makes the resulting kernel more appropriate for specific HSI classification tasks. With the ideal regularization, the kernel learning problem has a simple analytical solution and is very easy to implement. The ideal regularization can be used to improve and to refine state-of-the-art kernels, including spectral kernels, spatial kernels, and spectral-spatial composite kernels. The effectiveness of the proposed IRCK is validated on three benchmark hyperspectral datasets. Experimental results show the superiority of our IRCK method over the classical kernel methods and state-of-the-art HSI classification methods. |
2,221 | Mesothelial fusion mediates chorioallantoic membrane formation | In amniotic vertebrates (birds, reptiles and mammals), an extraembryonic structure called the chorioallantoic membrane (CAM) functions as respiratory organ for embryonic development. The CAM is derived from fusion between two pre-existing membranes, the allantois, a hindgut diverticulum and a reservoir for metabolic waste, and the chorion which marks the embryo's external boundary. Modified CAM in eutherian mammals, including humans, gives rise to chorioallantoic placenta. Despite its importance, little is known about cellular and molecular mechanisms mediating CAM formation and maturation. In this work, using the avian model, we focused on the early phase of CAM morphogenesis when the allantois and chorion meet and initiate fusion. We report here that chicken chorioallantoic fusion takes place when the allantois reaches the size of 2.5-3.0 mm in diameter and in about 6 hours between E3.75 and E4. Electron microscopy and immunofluorescence analyses suggested that before fusion, in both the allantois and chorion, an epithelial-shaped mesothelial layer is present, which dissolves after fusion, presumably by undergoing epithelial-mesenchymal transition. The fusion process per se, however, is independent of allantoic growth, circulation, or its connection to the developing mesonephros. Mesoderm cells derived from the allantois and chorion can intermingle post-fusion, and chorionic ectoderm cells exhibit a specialized sub-apical intercellular interface, possibly to facilitate infiltration of allantois-derived vascular progenitors into the chorionic ectoderm territory for optimal oxygen transport. Finally, we investigated chorioallantoic fusion-like process in primates, with limited numbers of archived human and fresh macaque samples. We summarize the similarities and differences of CAM formation among different amniote groups and propose that mesothelial epithelial-mesenchymal transition mediates chorioallantoic fusion in most amniotic vertebrates. Further study is needed to clarify tissue morphogenesis leading to chorioallantoic fusion in primates. Elucidating molecular mechanisms regulating mesothelial integrity and epithelial-mesenchymal transition will also help understand mesothelial diseases in the adult, including mesothelioma, ovarian cancer and fibrosis. This article is part of the theme issue 'Extraembryonic tissues: exploring concepts, definitions and functions across the animal kingdom'. |
2,222 | Renin-Angiotensin System Inhibitors and Major Cardiovascular Events after Sepsis | Rationale: Adult sepsis survivors have an increased risk of experiencing long-term cardiovascular events. Objectives: To determine whether the cardiovascular risk after sepsis is mitigated by renin-angiotensin system inhibitors (RASi). Methods: We conducted a population-based cohort study of adult sepsis survivors designed to emulate a target randomized trial with an active comparator and new-user design. We excluded patients with a first-line indication for prescription of RASi (e.g., coronary heart disease, heart failure, chronic kidney disease, and hypertension with diabetes mellitus). The main exposure of interest was a new prescription of a RASi within 30 days of hospital discharge. The active comparator was a new prescription of either a calcium channel blocker or a thiazide diuretic, also within 30 days of hospital discharge. The primary outcome of interest was the composite of myocardial infarction, stroke, and all-cause mortality during follow-up to 5 years. We used inverse probability weighting of a Cox proportional hazards model and reported results using hazard ratios with 95% confidence intervals. Results: The cohort included 7,174 adult sepsis survivors, of whom 3,805 were new users of a RASi and 3,369 were new users of a calcium channel blocker or a thiazide diuretic. New users of a RASi experienced a lower hazard of major cardiovascular events than new users of a calcium channel blocker or a thiazide diuretic (hazard ratio, 0.93; 95% confidence interval, 0.87-0.99). This association was consistent across different follow-up intervals and multiple sensitivity analyses. Conclusions: A new RASi prescription is associated with a reduction in major cardiovascular events after sepsis. A randomized controlled trial should be considered to confirm this finding. |
2,223 | Questions of value, questions of magnitude: An exploration and application of methods for comparing indirect effects in multiple mediator models | Mediation analysis is widely used to test and inform theory and debate about the mechanism(s) by which causal effects operate, quantitatively operationalized as an indirect effect in a mediation model. Most effects operate through multiple mechanisms simultaneously, and a mediation model is likely to be more realistic when it is specified to capture multiple mechanisms at the same time with the inclusion of more than one mediator in the model. This also allows an investigator to compare indirect effects to each other. After an overview of the mechanics of mediation analysis, we advocate formally comparing indirect effects in models that include more than one mediator, focusing on the important distinction between questions and claims about value (i.e., are two indirect effects the same number?) versus magnitude (i.e., are two indirect effects equidistant from zero or the same in strength?). After discussing the shortcomings of the conventional method for comparing two indirect effects in a multiple mediator model-which only answers a question about magnitude in some circumstances-we introduce several methods that, unlike the conventional approach, always answer questions about difference in magnitude. We illustrate the use of these methods and provide code that implements them in popular software. We end by summarizing simulation findings and recommending which method(s) to prefer when comparing like- and opposite-signed indirect effects. |
2,224 | A Conceptual Framework for Blockchain Enhanced Information Modeling for Healing and Therapeutic Design | In the face of the health challenges caused by the COVID-19 pandemic, healing and therapeutic design (HTD) as interventions can help with improving people's health. It is considered to have great potential to promote health in the forms of art, architecture, landscape, space, and environment. However, there are insufficient design approaches to address the challenges during the HTD process. An increased number of studies have shown that emerging information modeling (IM) such as building information modeling (BIM), landscape information modeling (LIM), and city information modeling (CIM) coupled with blockchain (BC) functionalities have the potential to enhance designers' HTD by considering important design elements, namely design variables, design knowledge, and design decision. It can also address challenges during the design process, such as design changes, conflicts in design requirements, the lack of design evaluation tools and frameworks, and incomplete design information. Therefore, this paper aims to develop a conceptual BC enhanced IM for HTD (BC-HTD) framework that addresses the challenges in the HTD and promotes health and well-being. The structure of BC-HTD framework is twofold: (1) a conceptual high-level framework comprising three levels: user; system; and information, (2) a conceptual low-level framework of detailed content at the system level, which has been constructed using a mixed quantitative and qualitative method of literature analysis, and validated via a pre-interview questionnaire survey and follow-up interviews with industry experts and academics. This paper analyzes the process of BC enhanced HTD and the knowledge management of HTD to aid design decisions in managing design information. This paper is the first attempt to apply the advantages of BC enabled IM to enhance the HTD process. The results of this study can foster and propel new research pathways and knowledge on the value of design in the form of non-fungible token (NFT) based on the extended advantages of BC in the field of design, which can fully mobilize the healing and therapeutic behaviors of designers and the advantage potential of HTD to promote health, and realize the vision of Health Metaverse in the context of sustainable development. |
2,225 | Area-efficient fully digital memory using minimum height standard cells for near-threshold voltage computing | This paper proposes a standard-cell based memory (SCM) as an alternative to a traditional on-chip SRAM for near-threshold voltage computing. It focuses on area- and energy-efficiency using minimum height standard-cells. Unlike conventional SCMs, the proposed SCM has standard-cells with a minimum possible cell height allowed by the logic design rule of the target technology. This paper also presents energy efficient readout and write schemes for reducing dynamic energy consumption. Post layout simulation using a 65-nm FD-SOI technology shows that the proposed SCM achieves area efficiency of 6.82 mu m(2) per bit (682F(2) per bit), which is 20% less than that of the state of the art SCMs. The results also show that the energy consumption of the proposed SCM is 31% less than that of the state of the art low voltage SRAMs. |
2,226 | Effectiveness of a low-cost UVGI chamber for decontaminating filtering facepiece respirators to extend reuse | In emergencies like the COVID-19 pandemic, the reuse or reprocessing of filtering facepiece respirators (FFRs) may be required to mitigate exposure risk. Research gap: Only a few studies evaluated decontamination effectiveness against SARS-CoV-2 that are practical for low-resource settings. This study aimed to determine the effectiveness of a relatively inexpensive ultraviolet germicidal irradiation chamber to decontaminate FFRs contaminated with SARS-CoV-2. A custom-designed UVGI chamber was constructed to determine the ability to decontaminate seven FFR models including N95s, KN95, and FFP2s inoculated with SARS-CoV-2. Vflex was excluded due to design folds/pleats and UVGI shadowing inside the chamber. Structural and functional integrity tolerated by each FFR model on repeated decontamination cycles was assessed. Twenty-seven participants were fit-tested over 30 cycles for each model and passed if the fit factor was ≥100. Of the FFR models included for testing, only the KN95 model failed filtration. The 3M™ 3M 1860 and Halyard™ duckbill 46727 (formerly Kimberly Clark) models performed better on fit testing than other models for both pre-and-post decontaminations. Fewer participants (0.3 and 0.7%, respectively) passed fit testing for Makrite 9500 N95 and Greenline 5200 FFP2 and only two for the KN95 model post decontamination. Fit testing appeared to be more affected by donning & doffing, as some passed with adjustment and repeat fit testing. A ≥ 3 log reduction of SARS-CoV-2 was achieved for worn-in FFRs namely Greenline 5200 FFP2. Conclusion: The study showed that not all FFRs tested could withstand 30 cycles of UVGI decontamination without diminishing filtration efficiency or facial fit. In addition, SARS-CoV-2 log reduction varied across the FFRs, implying that the decontamination efficacy largely depends on the decontamination protocol and selection of FFRs. We demonstrated the effectiveness of a low-cost and scalable decontamination method for SARS-CoV-2 and the effect on fit testing using people instead of manikins. It is recognized that extensive experimental evidence for the reuse of decontaminated FFRs is lacking, and thus this study would be relevant and of interest in crisis-capacity settings, particularly in low-resource facilities. |
2,227 | Optimized Backlight Power Saving Algorithm Using Joint Power-PSNR Characteristics Among Multiple Frames | In this paper, an optimized backlight power saving algorithm using joint power-peak signal-to-noise ratio (PSNR) characteristics among multiple frames is proposed. In existing state-of-the-art methods, the optimal decision for clipping point is made only with consideration of current frame, and the target frame PSNR are set the same for all frames. Therefore they have the same power-PSNR performance. In the proposed work, we show that better power-PSNR performance can be achieved by assigning different target frame PSNR for different frames. In the proposed algorithm, the decisions for clipping points associated with all frames are made at once. The inefficiency ratio of each clipping point is evaluated and put into the algorithm design. An optimization problem is formulated, and a solution-search procedure is proposed. Compared with state-of-the-art methods, the proposed work performs better in both aspects of power and PSNR; the BD-PSNR and the BD-Power of the proposed work against all other methods are better for every tested video; the BD-PSNR and the BD-Power can be as high as 19.80 dB on average, and the BD-Power can be as low as -26.25% on average. |
2,228 | WDCCNet: Weighted Double-Classifier Constraint Neural Network for Mammographic Image Classification | The early detection and timely treatment of breast cancer can save lives. Mammography is one of the most efficient approaches to screening early breast cancer. An automatic mammographic image classification method could improve the work efficiency of radiologists. Current deep learning-based methods typically use the traditional softmax loss to optimize the feature extraction part, which aims to learn the features of mammographic images. However, previous studies have shown that the feature extraction part cannot learn discriminative features from complex data using the standard softmax loss. In this paper, we design a new architecture and propose respective loss functions. Specifically, we develop a double-classifier network architecture that constrains the extracted features' distribution by changing the classifiers' decision boundaries. Then, we propose the double-classifier constraint loss function to constrain the decision boundaries so that the feature extraction part can learn discriminative features. Furthermore, by taking advantage of the architecture of two classifiers, the neural network can detect the difficult-to-classify samples. We propose a weighted double-classifier constraint method to make the feature extract part pay more attention to learning difficult-to-classify samples' features. Our proposed method can be easily applied to an existing convolutional neural network to improve mammographic image classification performance. We conducted extensive experiments to evaluate our methods on three public benchmark mammographic image datasets. The results showed that our methods outperformed many other similar methods and state-of-the-art methods on the three public medical benchmarks. Our code and weights can be found on GitHub. |
2,229 | Symptomatic Lymphocele Formation After Sentinel Lymph Node Biopsy for Early Stage Cervical Cancer | In early stage cervical cancer, nodal status is the most important prognostic factor, and execution of retroperitoneal lymphadenectomy is currently an integral part of surgical therapy. Sentinel lymph node biopsy has been progressively incorporated with surgical therapy and could reduce morbidity. However, the current incidence of complications exclusively related to the procedure is unknown. We report on a 29-year-old woman affected by cervical cancer (Fédération Internationale de Gynécologie et d'Obstétrique Stage 1b1), who underwent sentinel lymph node biopsy in combination with radical vaginal trachelectomy, and who later developed a symptomatic pelvic lymphocele that required surgical therapy. Conservative procedures in the pelvic lymph nodes are not free of complications, especially with regard to the formation of symptomatic lymphoceles. This report brings to light an important discussion about the exact magnitude of the complications associated with the procedure. |
2,230 | An Event Detection Method for Social Networks Based on Evolution Fluctuations of Nodes | How can we discover and estimate major events in complex social networks? Event detection and evaluation in social networks provide an effective solution, which has become the critical basis for many real applications, such as crisis management and decision making. However, the existing methods ignore the difference of the evolution fluctuations of nodes. In order to further improve the accuracy of event detection, this paper proposes an event detection method for social networks based on node evolution fluctuations (NodeED). It contains a node similarity index algorithm (SimJudge) and a microevolution fluctuation detection algorithm (MicroFluc). The main work is as follows: 1) based on particle swarm optimization algorithm, SimJudge is proposed to apply the values of different similarity indexes to quantify the evolution fluctuations of nodes, and the optimal similarity index is determined for each node and 2) microFluc is proposed to integrate the evolution fluctuations of different nodes and quantify the impacts of events in the evolutions of social networks. The results of comparisons with state-of-the-art methods using extensive experiments show that NodeED improves the event detection accuracy and has more advantages to detect events in social networks than other state-of-the-art methods. |
2,231 | Parallel query execution over encrypted data in database-as-a-service (DaaS) | The main challenge in database-as-a-service is the security and privacy of data because service providers are not usually considered as trustworthy. So, the data must be encrypted before storing into the database. Another challenge arises that the performance is degraded on the deployment of encryption algorithm on runtime. Furthermore, the connectivity through the Internet adds more delay. To tackle this, we have proposed parallel query execution methodology using multithreading technique up to 6 threads. We have conducted experiments up to 1000,000 (1 million) encrypted records. Our results are quite promising. For data encryption/decryption, we have used advance encryption standard with blocking length of 256 bits. We have designed our methodology in the context of parallel computation method proposed in the literature (Ho et al., in: Proceedings of the 2017 international conference on machine learning and soft computing, pp 47-52, 2017). We compared the results with state-of-art algorithms. The state-of-art algorithms execute the experiments on 10,120 encrypted records maximum which took about time of 1000 ms with 2 threads. But the proposed methodology is proved outstanding that executed the experiments which were performed on 100,000 encrypted records. It outperformed with 6 threads which took only 507 ms even with 2 threads, and the proposed methodology is much better which took only 994 ms. So, the efficiency and scalability of the proposed methodology are proved better as compared to state-of-the-art algorithms. |
2,232 | Gaussian mixture reduction based on fuzzy ART for extended target tracking | This paper presents a global Gaussian mixture (GM) reduction algorithm via clustering for extended target tracking in clutter. The proposed global clustering algorithm is obtained by combining a fuzzy Adaptive Resonance Theory (ART) neural network architecture with the weighted Kullback-Leibler (KL) difference which describes discrimination of one component from another. Therefore, we call the proposed algorithm as ART-KL clustering (ART-KL-C) in the paper. The weighted KL difference is used as a category choice function of ART-KL-C, derived by considering both the la divergence between two components and their weights. The performance of ART-KL-C is evaluated by the normalized integrated squared distance (NISD) measure, which describes the deviation between the original and reduced GM. The proposed algorithm is tested on both one-dimensional and four-dimensional simulation examples, and the results show that the proposed algorithm can more accurately approximate the original mixture and is useful in extended target tracking. (C) 2013 Elsevier B.V. All rights reserved. |
2,233 | Bridging the European Data Sharing Divide in Genomic Science | In this viewpoint, we argue for the importance of creating data spaces for genomic research that are detached from contexts in which fundamental rights concerns related to surveillance measures override a purpose-specific balancing of fundamental rights. Genomic research relies on molecular and phenotypic data, on comparing findings within large data sets, on searchable metadata, and on translating research results into a clinical setting. These methods require sensitive genetic and health data to be shared across borders. International data sharing between the European Union (EU) or the European Economic Area and third countries has accordingly become a cornerstone of genomics. The EU General Data Protection Regulation contains rules that accord privileged status to data processing for research purposes to ensure that strict data protection requirements do not impede biomedical research. However, the General Data Protection Regulation rules applicable to international transfers of data accord no such preferential treatment to international data transfers made in the research context. The rules that govern the international transfer of data create considerable barriers to international data sharing because of the cost-intensive procedural and substantive compliance burdens that they impose. For certain jurisdictions and select use cases, there exist practically no lawful mechanisms to enable the international transfer of data because of concerns about the protection of fundamental rights. The proposed solutions further fail to address the need to share large data sets of local and regional cohorts across national borders to enable joint analyses. The European Health Data Space is an emerging federated, EU-wide data infrastructure that is intended to function as an infrastructure bringing together EU health data to improve patient care and enable the secondary use of health-related data for research purposes. Such infrastructure is implementing new institutions to support its functioning and is being implemented in reliance on a new enabling law, the regulation on the European Health Data Space. This innovation provides the opportunity to facilitate EU contribution to international genomic research efforts. The draft regulation for this data space provides for a concept of data infrastructure intended to enable cross-border data exchange and access, including access to genetic and health data for scientific analysis purposes. The draft regulation also provides for obligations of national actors aimed at making data widely available. This effort is laudable. However, in the absence of further, more fundamental changes to the manner in which the EU regulates the secondary use of health data, it is reasonable to believe that EU participation in international genomic research efforts will remain impeded. |
2,234 | 15-nW Biopotential LPFs in 0.35-mu m CMOS Using Subthreshold-Source-Follower Biquads With and Without Gain Compensation | Most biopotential readout front-ends rely on the g(m)-C lowpass filter (LPF) for forefront signal conditioning. A small g(m) realizes a large time constant (tau = C/g(m)) suitable for ultra-low-cutoff filtering, saving both power and area. Yet, the noise and linearity can be compromised, given that each g(m) cell can involve one or several noisy and nonlinear V-I conversions originated from the active devices. This paper proposes the subthreshold-source-follower (SSF) Biquad as a prospective alternative. It features: 1) a very small number of active devices reducing the noise and nonlinearity footsteps; 2) No explicit feedback in differential implementation, and 3) extension of filter order by cascading. This paper presents an in-depth treatment of SSF Biquad in the nW-power regime, analyzing its power and area tradeoffs with gain, linearity and noise. A gain-compensation (GC) scheme addressing the gain-loss problem of NMOS-based SSF Biquad due to the body effect is also proposed. Two 100-Hz 4th-order Butterworth LPFs using the SSF Biquads with and without GC were fabricated in 0.35-mu m CMOS. Measurement results show that the non-GC (GC) LPF can achieve a DC gain of -3.7 dB (0 dB), an input-referred noise of 36 mu V-rm (29 mu V-rms), a HD3@60 Hz of -55.2 dB (-60.7 dB) and a die size of 0.11 mm(2) (0.08 mm(2)). Both LPFs draw 15 nW at 3 V. The achieved figure-of-merits (FoMs) are favorably comparable with the state-of-the-art. |
2,235 | Early Detection of Failing Automotive Batteries Using Gas Sensors | Safety for automotive lithium-ion battery (LIB) applications is of crucial importance, especially for electric vehicle applications using batteries with high capacity and high energy density. In case of a defect inside or outside the cell, serious safety risks are possible including extensive heat generation, toxic and flammable gas generation, and consequently fire and explosion. New regulations (GB 38031-2020) require a warning for passengers at least five minutes before serious incidents. This regulation can hardly be fulfilled with state-of-the-art battery monitoring. In this study, gases produced during battery failure before and during a thermal runaway (TR) are investigated in detail and the use of different gas sensors as early detectors of battery incidents is tested and proposed. The response of several commercially available gas sensors is tested in four battery failure cases: unwanted electrolysis of voltage carrying parts, electrolyte vapor, first venting of the cell and the TR. The experiments show that battery failure detection with gas sensors is possible but depends highly on the failure case. The chosen gas sensor can detect H-2 produced by unwanted electrolysis and electrolyte vapor and gases produced by degassing of state-of-the-art LIBs. The results may contribute significantly to failure detection and improvement of battery safety. |
2,236 | Ultrasound Aided Vertebral Level Localization for Lumbar Surgery | Localization of the correct vertebral level for surgical entry during lumbar hernia surgery is not straightforward. In this paper, we develop and evaluate a solution using free-hand 2-D ultrasound (US) imaging in the operation room (OR). Our system exploits the difference in spinous process shapes of the vertebrae. The spinous processes are pre-operatively outlined and labeled in a lateral lumbar X-ray of the patient. Then, in the OR the spinous processes are imaged with 2-D sagittal US, and are automatically segmented and registered with the X-ray shapes. After a small number of scanned vertebrae, the system robustly matches the shapes, and propagates the X-ray label to the US images. The main contributions of our work are: we propose a deep convolutional neural network-based bone segmentation algorithm from US imaging that outperforms state of the art methods in both performance and speed. We present a matching strategy that determines the levels of the spinal processes being imaged. And lastly, we evaluate the complete procedure on 19 clinical data sets from two hospitals, and two observers. The final labeling was correct in 92% of the cases, demonstrating the feasibility of US-based surgical entry point detection for spinal surgeries. |
2,237 | Maximum Correntropy Criterion for Robust Face Recognition | In this paper, we present a sparse correntropy framework for computing robust sparse representations of face images for recognition. Compared with the state-of-the-art l(1) norm-based sparse representation classifier ( SRC), which assumes that noise also has a sparse representation, our sparse algorithm is developed based on the maximum correntropy criterion, which is much more insensitive to outliers. In order to develop a more tractable and practical approach, we in particular impose nonnegativity constraint on the variables in the maximum correntropy criterion and develop a half-quadratic optimization technique to approximately maximize the objective function in an alternating way so that the complex optimization problem is reduced to learning a sparse representation through a weighted linear least squares problem with nonnegativity constraint at each iteration. Our extensive experiments demonstrate that the proposed method is more robust and efficient in dealing with the occlusion and corruption problems in face recognition as compared to the related state-of-the-art methods. In particular, it shows that the proposed method can improve both recognition accuracy and receiver operator characteristic (ROC) curves, while the computational cost is much lower than the SRC algorithms. |
2,238 | Enhanced Junction Selection Mechanism for Routing Protocol in VANETs | Routing in infrastructure less vehicular ad hoc networks is challenging because of the dynamic network, predictable topology, high speed of nodes, and predictable mobility patterns. This paper presents an enhanced routing protocol specifically designed for city environments. It uses vehicular speed and directional density for dynamic junction selection. Simulation results exhibit increased packet delivery ratio while decreased end-to-end delay when compared with state of the art protocols. |
2,239 | A case of lymphocytic myocarditis in a patient treated with an immune checkpoint inhibitor, a recent class of chemotherapy agents | Chemotherapy-associated cardiotoxicity is a common adverse event. Immune checkpoint inhibitors (ICI) - a new class of monoclonal antibodies - have revolutionized the management of various diseases. Their use is expected to increase in the near future and their cardiac side effects have been increasingly recognized. CLINICAL CASE: We describe a case of a 67-year-old female patient with urothelial carcinoma undergoing treatment with pembrolizumab who presented to the emergency department with progressive fatigue, retrosternal pain and palpitations for three days. On admission she was diagnosed with acute heart failure (HF). The electrocardiogram revealed a right bundle branch block and ventricular bigeminy. Blood tests showed elevated troponin I, while transthoracic echocardiography revealed severe left ventricular dysfunction. Coronary angiography excluded coronary artery disease. Cardiac magnetic resonance revealed moderate left ventricular dysfunction and late gadolinium enhancement typical of myocarditis. Endomyocardial biopsy confirmed the diagnosis of lymphocytic myocarditis. In the first 48h of hospitalization, she developed transient complete AV block. Corticoid and HF therapy were initiated, leading to symptom improvement and disappearance of the rhythm disturbances. She was discharged on the 12th day, maintaining moderate LV dysfunction, which improved only mildly at a subsequent outpatient assessment. She died suddenly 35 days after discharge. CONCLUSION: Lymphocytic myocarditis is a serious cardiac side effect of ICI therapy. Pembrolizumab is increasingly used, so it is important to be aware of its effects, in order to perform an early diagnosis and provide adequate treatment. Corticosteroid therapy seems to be crucial in preventing disease progression and enabling ventricular remodeling. |
2,240 | Toward Understanding the Effect of Fluoride Ions on the Solvation Structure in Lithium Metal Batteries: Insights from First-Principles Simulations | Regulating the structure and composition of the lithium-ion (Li+) solvation shell is crucial to the performance of lithium metal batteries. The introduction of fluorine anions (F-) into the electrolyte significantly enhances the cycle efficiency and the interfacial stability of lithium metal anodes. However, the effect of dissolved F- on the solvation shell is rarely touched in the literature. Herein, we investigate the evolution processing of the fluorine-containing solvation structure to explore the underlying mechanisms via first-principles calculations. The additive F- is found to invade the first solvation shell and strongly coordinate with Li+, liberating the bis(trifluoromethanesulfonyl) imide anion (TFSI-) from the Li+ local environment, which enhances the Li+ diffusivity by altering the transport mode. Moreover, the fluorine-containing Li+ solvation shell exhibits a higher lowest unoccupied molecular orbital energy level than that of the solvation sheath without F- additives, suggesting the reduction stability of the electrolyte. Furthermore, the Gibbs free energy calculations for Li+ desolvation reveal that the energy barrier of the Li+ desolvation process will be reduced because of the presence of F-. Our work provides new insights into the mechanisms of electrolyte fluorinated strategies and leads to the rational design of high-performance lithium metal batteries. |
2,241 | LCAart: Communicating industrial ecology at a human scale | This Forum piece describes a collaborative project between engineering and architecture to visualize some of the most influential results from industrial ecology using human-scale, photorealistic images that are quantitatively accurate. Our goal was to apply visualization theories and practices from art and architecture to address a major communication problem in our field: though inspirational in concept, in practice much industrial ecology research is difficult to comprehend for the average person. Models are large and complex, metrics are esoteric, and results are often reported on a scale that is devoid of personal meaning. Our strategy was to place hidden flows and embodied emissions in plain sight, creating images that show the environmental implications of consumption as absurd insertions into scenes of daily life, at a scale that is relatable and personally meaningful. We also compare with and discuss other artistic efforts around the world in the oeuvre of "Consumption Art," providing historical context. Industrial ecology envisions a world where production systems can incorporate social and environmental implications in real-time, where policy is informed by our best understanding of trade-offs and inequities, and where the public has an appreciation for what actions are meaningful, all with the goals of improving quality of life for all while safeguarding the environment and human health. Effective communication of our research is vital to build consensus for policy and action toward this vision, and one under-appreciated aspect of communication in our field is the sympathetic power of Art. |
2,242 | A Direct Thrust Control Scheme for Linear Permanent Magnet Synchronous Motor Based on Online Duty Ratio Control | Linear permanent magnet synchronous motors, especially those with low inductance and short pole pitch, exhibit significant ripple in flux and thrust force under conventional direct thrust force control. Aimed at reducing ripple in the flux and the force, a duty ratio control scheme for direct thrust force control of linear permanent magnet synchronous motors is proposed. The effect of inverter voltage vectors on the flux and the thrust force is analyzed. Subsequently, a precise expression for the online computation of the required duty ratio is derived. Compared to the state-of-the-art duty ratio control, the proposed approach eliminates the need to tune gains. The proposed online duty ratio calculation is based on the selected voltage vector from the switching table and takes into account the mover's speed. The proposed approach retains the characteristics of the conventional direct thrust control in terms of fast transient and steady-state responses for both flux and thrust force. Experimental results demonstrate a faster transient response and negligible steady-state error for flux, force, and speed responses under the proposed approach when compared to the state of the art. |
2,243 | New Benchmark for Household Garbage Image Recognition | Household garbage images are usually faced with complex backgrounds, variable illuminations, diverse angles, and changeable shapes, which bring a great difficulty in garbage image classification. Due to the ability to discover problem-specific features, deep learning and especially convolutional neural networks (CNNs) have been successfully and widely used for image representation learning. However, available and stable household garbage datasets are insufficient, which seriously limits the development of research and application. Besides, the state-of-the-art in the field of garbage image classification is not entirely clear. To solve this problem, in this study, we built a new open benchmark dataset for household garbage image classification by simulating different lightings, backgrounds, angles, and shapes. This dataset is named 30 classes of household garbage images (HGI-30), which contains 18 000 images of 30 household garbage classes. The publicly available HGI-30 dataset allows researchers to develop accurate and robust methods for household garbage recognition. We also conducted experiments and performance analyses of the state-of-the-art deep CNN methods on HGI-30, which serves as baseline results on this benchmark. |
2,244 | Blind symbol packing ratio estimation for faster-than-Nyquist signalling based on deep learning | This Letter proposes a blind symbol packing ratio estimation for faster-than-Nyquist (FTN) signalling based on state-of-the-art deep learning technology. The symbol packing ratio (also named speeding parameter, time packing parameter etc.) is a vital parameter to obtain the real symbol rate and recover the origin symbols from the received symbols by calculating the intersymbol interference. To the best of the authors' knowledge, this is the first effective estimation approach for symbol packing ratio in FTN signalling and has shown its fast convergence and robustness to signal-to-noise ratio by numerical simulations. Benefiting from the proposed blind estimation, the packing-ratio-based adaptive FTN transmission without dedicate channel or control frame becomes available. Also, the secure FTN communications based on the secret symbol packing ratio can be easily cracked. |
2,245 | CCLS: An Efficient Local Search Algorithm for Weighted Maximum Satisfiability | The maximum satisfiability (MAX-SAT) problem, especially the weighted version, has extensive applications. Weighted MAX-SAT instances encoded from real-world applications may be very large, which calls for efficient approximate methods, mainly stochastic local search (SLS) ones. However, few works exist on SLS algorithms for weighted MAX-SAT. In this paper, we propose a new heuristic called CCM for weighted MAX-SAT. The CCM heuristic prefers to select a CCMP variable. By combining CCM with random walk, we design a simple SLS algorithm dubbed CCLS for weighted MAX-SAT. The CCLS algorithm is evaluated against a state-of-the-art SLS solver IRoTS and two state-of-the-art complete solvers namely akmaxsat_ls and New WPM2, on a broad range of weighted MAX-SAT instances. Experimental results illustrate that the quality of solution found by CCLS is much better than that found by IRoTS, akmaxsat_ls and New WPM2 on most industrial, crafted and random instances, indicating the efficiency and the robustness of the CCLS algorithm. Furthermore, CCLS is evaluated in the weighted and unweighted MAX-SAT tracks of incomplete solvers in the Eighth Max-SAT Evaluation (Max-SAT 2013), and wins four tracks in this evaluation, illustrating that the performance of CCLS exceeds the current state-of-the-art performance of SLS algorithms on solving MAX-SAT instances. |
2,246 | The Effects of Group Art Therapy on the Primary Family Caregivers of Hospitalized Patients with Brain Injuries in South Korea | This study examined the effects of group art therapy on depression, burden, and self-efficacy in primary family caregivers of patients with brain injuries. This was a quasi-experimental, nonequivalent control group and a pre- and post-test design. This study was carried out in one national rehabilitation hospital targeting 41 primary family caregivers of patients with brain injuries. Group art therapy intervention was carried out three days per week comprising 12 sessions over four consecutive weeks. The experimental group (n = 20) received group art therapy, whereas the control group (n = 21) did not. We used a time difference method to minimize the risk of contaminating the control group by sampling sequentially. For depression, although there was a significant difference after the intervention (t = 3.296, p = 0.004), the mean difference score was not statistically significant between the experimental group and the control group (t = 0.861, p = 0.395). The experimental group showed a significantly greater decrease in burden (t = 2.462, p = 0.020) and significantly greater improvement in self-efficacy (t = -6.270, p < 0.001) than the control group. Group art therapy may be an effective nursing intervention for primary family caregivers of patients with brain injuries. |
2,247 | Deep Residual Autoencoder for Blind Universal JPEG Restoration | We propose a deep residual autoencoder exploiting Residual-in-Residual Dense Blocks (RRDB) leveraging both the learning capacity of deep residual networks and prior knowledge of the JPEG compression pipeline. The proposed method is blind and universal, consisting of a unique model that effectively restores images with any level of compression. It operates in the YCbCr color space and performs JPEG restoration in two phases using two different autoencoders: the first one restores the luma channel exploiting 2D convolutions; the second one, using the restored luma channel as a guide, restores the chroma channels exploiting 3D convolutions. Extensive experimental results on four widely used benchmark datasets (i.e. LIVE1, BDS500, CLASSIC-5, and Kodak) show that our model outperforms state of the art methods, even those using a different set of weights for each compression quality, in terms of all the evaluation metrics considered (i.e. PSNR, PSNR-B, and SSIM). Furthermore, the proposed model shows a greater robustness than state-of-the-art methods when applied to compression qualities not seen during training. |
2,248 | Self-Layer and Cross-Layer Bilinear Aggregation for Fine-Grained Recognition in Cyber-Physical-Social Systems | Cyber-Physical-Social Systems (CPSS) integrates cyber, physical and social spaces together, which makes our lives more convenient and intelligent by providing personalized service. In this paper, we will provide CPSS service for fine-grained recognition. Fine-grained visual recognition is a hot but challenging research in computer vision that aims to recognize object subcategories. The reason why it is challenging is that it extremely depends on the subtle discriminative features of local parts. Recently, some bilinear feature based methods were proposed, and the experimental results show state-of-the-art performance. However, most of them neglect the spatial relationships of part-region feature among multiple layers. In this paper, a novel approach of Self-layer and Cross-layer Bilinear Aggregation(SCBA) is proposed for fine-grained recognition. Firstly, a self-layer bilinear feature fusion module is proposed to model the spatial relationship of feature at the same layer. Secondly, we propose a cross-layer bilinear feature fusion module to capture the inter-layer interreaction of information to boost the ability of feature representation. In summary, the method we proposed not only can learn the correlations among different layers but the same layer, which makes it efficient and the experimental results show that it achieves state-of-the-art accuracy on three common fine-grained image datasets. |
2,249 | Compact and Low-Complexity Binary Feature Descriptor and Fisher Vectors for Video Analytics | In this paper, we propose a compact and low-complexity binary feature descriptor for video analytics. Our binary descriptor encodes the motion information of a spatio-temporal support region into a low-dimensional binary string. The descriptor is based on a binning strategy and a construction that binarizes separately the horizontal and vertical motion components of the spatio-temporal support region. We pair our descriptor with a novel Fisher Vector (FV) scheme for binary data to project a set of binary features into a fixed length vector in order to evaluate the similarity between feature sets. We test the effectiveness of our binary feature descriptor with FVs for action recognition, which is one of the most challenging tasks in computer vision, as well as gait recognition and animal behavior clustering. Several experiments on the KTH, UCF50, UCF101, CASIA-B, and TIGdog datasets show that the proposed binary feature descriptor outperforms the state-of-the-art feature descriptors in terms of computational time and memory and storage requirements. When paired with FVs, the proposed feature descriptor attains a very competitive performance, outperforming several state-of-the-art feature descriptors and some methods based on convolutional neural networks. |
2,250 | Implementation of energy-efficient fast convolution algorithm for deep convolutional neural networks based on FPGA | The state-of-the-art convolutional neural networks (CNNs) have been widely applied to many deep neural networks models. As the model becomes more accurate, both the number of computation and the data accesses are significantly increased. The proposed design uses the row stationary with network-on-chip and the fast convolution algorithm in process elements to reduce the number of computation and data accesses simultaneously. The experimental evaluation which using the CNN layers of VGG-16 with a batch size of three shows that the proposed design is more energy-efficient than the state-of-the-art work. The proposed design improves the total GOPs of the algorithm by 1.497 times and reduces the on-chip memory and off-chip memory accesses by 1.07 and 1.46 times than prior work, respectively. |
2,251 | UAVM: Towards Unifying Audio and Visual Models | Conventional audio-visual models have independent audio and video branches. In this work, we unify the audio and visual branches by designing a Unified Audio-Visual Model (UAVM). The UAVM achieves a new state-of-the-art audio-visual event classification accuracy of 65.8% on VGGSound. More interestingly, we also find a few intriguing properties of UAVM that the modality-independent counterparts do not have. Code at github.com/yuangongnd/uavm. |
2,252 | Exploring the Potential for Steel Slags Valorisation in an Industrial Symbiosis Perspective at Meso-scale Level | A greater reuse of steel slags would bring considerable benefits both from an environmental and economic point of view. The development of tools and strategies to monitor at different scales resources and waste flows would allow for better resource planning and a more sustainable management on territory. The aim of this study is to investigate and analyse the supply chain that deals with the management of steel slags at meso-level, in order to investigate the state of implementation of industrial symbiosis (IS), its potential and its improvement. A Mass Flow Analysis (MFA) has been implemented, through big data analysis coming from the integration of regional and provincial databases with a careful data processing from questionnaires. This integrated methodology has proved to be a valid tool to monitor the recovery and reuse, the implementation of industrial symbiosis and to plan improvement actions. This paper reports a representation of the current situation regarding the production, recovery and reuse of these materials in production processes for which they are suitable, with a view to their full exploitation, following the principles of circular economy and an analysis of the mutual exchange that occur among steelmaking plants and other business partners in a network of industrial companies. The results showed that most of the steel slags managed at meso-level (Province of Brescia, Italy) is still unfortunately destined for landfill with low percentage of them classified as by-product highlighting as the IS is not adequately applied. Of the slag destined for treatments and recovery processes, almost all of them are Electric Arc Furnace slag, which are mainly reused for hydraulically bound base layers and road sub-bases (about 85% of the total recovered) and as aggregates for the production of cement and bituminous mixes (about 15% of the total recovered). Results shows as further effort should be made in term of policies and strategies to incentivize IS and to increase the recovery. |
2,253 | CNN-Based Real-Time Dense Face Reconstruction with Inverse-Rendered Photo-Realistic Face Images | With the powerfulness of convolution neural networks (CNN), CNN based face reconstruction has recently shown promising performance in reconstructing detailed face shape from 2D face images. The success of CNN-based methods relies on a large number of labeled data. The state-of-the-art synthesizes such data using a coarse morphable face model, which however has difficulty to generate detailed photo-realistic images of faces (with wrinkles). This paper presents a novel face data generation method. Specifically, we render a large number of photo-realistic face images with different attributes based on inverse rendering. Furthermore, we construct a fine-detailed face image dataset by transferring different scales of details from one image to another. We also construct a large number of video-type adjacent frame pairs by simulating the distribution of real video data.(1) With these nicely constructed datasets, we propose a coarse-to-fine learning framework consisting of three convolutional networks. The networks are trained for real-time detailed 3D face reconstruction from monocular video as well as from a single image. Extensive experimental results demonstrate that our framework can produce high-quality reconstruction but with much less computation time compared to the state-of-the-art. Moreover, our method is robust to pose, expression and lighting due to the diversity of data. |
2,254 | Targeting the nitric oxide/cGMP signaling pathway to treat chronic pain | Nitric oxide (NO)/cyclic guanosine 3',5'-monophosphate (cGMP) signaling has been shown to act as a mediator involved in pain transmission and processing. In this review, we summarize and discuss the mechanisms of the NO/cGMP signaling pathway involved in chronic pain, including neuropathic pain, bone cancer pain, inflammatory pain, and morphine tolerance. The main process in the NO/cGMP signaling pathway in cells involves NO activating soluble guanylate cyclase, which leads to subsequent production of cGMP. cGMP then activates cGMP-dependent protein kinase (PKG), resulting in the activation of multiple targets such as the opening of ATP-sensitive K+ channels. The activation of NO/cGMP signaling in the spinal cord evidently induces upregulation of downstream molecules, as well as reactive astrogliosis and microglial polarization which participate in the process of chronic pain. In dorsal root ganglion neurons, natriuretic peptide binds to particulate guanylyl cyclase, generating and further activating the cGMP/PKG pathway, and it also contributes to the development of chronic pain. Upregulation of multiple receptors is involved in activation of the NO/cGMP signaling pathway in various pain models. Notably the NO/cGMP signaling pathway induces expression of downstream effectors, exerting both algesic and analgesic effects in neuropathic pain and inflammatory pain. These findings suggest that activation of NO/cGMP signaling plays a constituent role in the development of chronic pain, and this signaling pathway with dual effects is an interesting and promising target for chronic pain therapy. |
2,255 | iCVI-ARTMAP: Using Incremental Cluster Validity Indices and Adaptive Resonance Theory Reset Mechanism to Accelerate Validation and Achieve Multiprototype Unsupervised Representations | This article presents an adaptive resonance theory predictive mapping (ARTMAP) model, which uses incremental cluster validity indices (iCVIs) to perform unsupervised learning, namely, iCVI-ARTMAP. Incorporating iCVIs to the decision-making and many-to-one mapping capabilities of this adaptive resonance theory (ART)-based model can improve the choices of clusters to which samples are incrementally assigned. These improvements are accomplished by intelligently performing the operations of swapping sample assignments between clusters, splitting and merging clusters, and caching the values of variables when iCVI values need to be recomputed. Using recursive formulations enables iCVI-ARTMAP to considerably reduce the computational burden associated with cluster validity index (CVI)-based offline clustering. In this work, six iCVI-ARTMAP variants were realized via the integration of one information-theoretic and five sum-of-squares-based iCVIs into fuzzy ARTMAP. With proper choice of iCVI, iCVI-ARTMAP either outperformed or performed comparably to three ART-based and four non-ART-based clustering algorithms in experiments using benchmark datasets of different natures. Naturally, the performance of iCVI-ARTMAP is subject to the selected iCVI and its suitability to the data at hand; fortunately, it is a general model in which other iCVIs can be easily embedded. |
2,256 | Multi-Target Tracking With Time-Varying Clutter Rate and Detection Profile: Application to Time-Lapse Cell Microscopy Sequences | Quantitative analysis of the dynamics of tiny cellular and sub-cellular structures, known as particles, in time-lapse cell microscopy sequences requires the development of a reliable multi-target tracking method capable of tracking numerous similar targets in the presence of high levels of noise, high target density, complex motion patterns and intricate interactions. In this paper, we propose a framework for tracking these structures based on the random finite set Bayesian filtering framework. We focus on challenging biological applications where image characteristics such as noise and background intensity change during the acquisition process. Under these conditions, detection methods usually fail to detect all particles and are often followed by missed detections and many spurious measurements with unknown and time-varying rates. To deal with this, we propose a bootstrap filter composed of an estimator and a tracker. The estimator adaptively estimates the required meta parameters for the tracker such as clutter rate and the detection probability of the targets, while the tracker estimates the state of the targets. Our results show that the proposed approach can outperform state-of-the-art particle trackers on both synthetic and real data in this regime. |
2,257 | Monitoring Changes in Intracellular Reactive Oxygen Species Levels in Response to Histone Deacetylase Inhibitors | Reactive oxygen species (ROS) are induced by several chemotherapeutics. In this protocol, we describe a flow cytometry-based method for the analysis of the intracellular levels of ROS in vital leukemic cells in response to the histone deacetylase inhibitor vorinostat. This measurement of ROS using the cell-permeable dye CM-H2DCFDA indicates intracellular oxidative stress. |
2,258 | Epigenetic targeting of transposon relics: beating the dead horses of the genome? | Transposable elements (TEs) have been seen as selfish genetic elements that can propagate in a host genome. Their propagation success is however hindered by a combination of mechanisms such as mutations, selection, and their epigenetic silencing by the host genome. As a result, most copies of TEs in a given genome are dead relics: their sequence is too degenerated to allow any transposition. Nevertheless, these TE relics often, but not always, remain epigenetically silenced, and if not to prevent transposition anymore, one can wonder the reason for this phenomenon. The mere self-perpetuating loop inherent to epigenetic silencing could alone explain that even when inactive, TE copies remain silenced. Beyond this process, nevertheless, antagonistic selective forces are likely to act on TE relic silencing. Especially, without the benefit of preventing transposition, TE relic silencing may prove deleterious to the host fitness, suggesting that the maintenance of TE relic silencing is the result of a fine, and perhaps case-by-case, evolutionary trade-off between beneficial and deleterious effects. Ultimately, the release of TE relics silencing may provide a 'safe' ground for adaptive epimutations to arise. In this review, we provide an overview of these questions in both plants and animals. |
2,259 | Exploiting Hardware Multicast and GPUDirect RDMA for Efficient Broadcast | Broadcast is a widely used operation in many streaming and deep learning applications to disseminate large amounts of data on emerging heterogeneous High-Performance Computing (HPC) systems. However, traditional broadcast schemes do not fully utilize hardware features for Graphics Processing Unit (GPU)-based applications. In this paper, a model-oriented analysis is presented to identify performance bottlenecks of existing broadcast schemes on GPU clusters. Next, streaming-based broadcast schemes are proposed to exploit InfiniBand hardware multicast (IB-MCAST) and NVIDIA GPUDirect technology for efficient message transmission. The proposed designs are evaluated in the context of using Message Passing Interface (MPI) based benchmarks and applications. The experimental results indicate improved scalability and up to 82 percent reduction of latency compared to the state-of-the-art solutions in the benchmark-level evaluation. Furthermore, compared to the state-of-the-art, the proposed design yields stable higher throughput for a synthetic streaming workload, and 1.3x faster training time for a deep learning framework. |
2,260 | Neural progenitor cells derived from fibroblasts induced by small molecule compounds under hypoxia for treatment of Parkinson's disease in rats | Neural progenitor cells (NPCs) capable of self-renewal and differentiation into neural cell lineages offer broad prospects for cell therapy for neurodegenerative diseases. However, cell therapy based on NPC transplantation is limited by the inability to acquire sufficient quantities of NPCs. Previous studies have found that a chemical cocktail of valproic acid, CHIR99021, and Repsox (VCR) promotes mouse fibroblasts to differentiate into NPCs under hypoxic conditions. Therefore, we used VCR (0.5 mM valproic acid, 3 μM CHIR99021, and 1 μM Repsox) to induce the reprogramming of rat embryonic fibroblasts into NPCs under a hypoxic condition (5%). These NPCs exhibited typical neurosphere-like structures that can express NPC markers, such as Nestin, SRY-box transcription factor 2, and paired box 6 (Pax6), and could also differentiate into multiple types of functional neurons and astrocytes in vitro. They had similar gene expression profiles to those of rat brain-derived neural stem cells. Subsequently, the chemically-induced NPCs (ciNPCs) were stereotactically transplanted into the substantia nigra of 6-hydroxydopamine-lesioned parkinsonian rats. We found that the ciNPCs exhibited long-term survival, migrated long distances, and differentiated into multiple types of functional neurons and glial cells in vivo. Moreover, the parkinsonian behavioral defects of the parkinsonian model rats grafted with ciNPCs showed remarkable functional recovery. These findings suggest that rat fibroblasts can be directly transformed into NPCs using a chemical cocktail of VCR without introducing exogenous factors, which may be an attractive donor material for transplantation therapy for Parkinson's disease. |
2,261 | A Latency-Optimized Reconfigurable NoC for In-Memory Acceleration of DNNs | In-memory computing reduces latency and energy consumption of Deep Neural Networks (DNNs) by reducing the number of off-chip memory accesses. However, crossbar-based in-memory computing may significantly increase the volume of on-chip communication since the weights and activations are on-chip. State-of-the-art interconnect methodologies for in-memory computing deploy a bus-based network or mesh-based Network-on-Chip (NoC). Our experiments show that up to 90% of the total inference latency of a DNN hardware is spent on on-chip communication when the bus-based network is used. To reduce the communication latency, we propose a methodology to generate an NoC architecture along with a scheduling technique customized for different DNNs. We prove mathematically that the generated NoC architecture and corresponding schedules achieve the minimum possible communication latency for a given DNN. Furthermore, we generalize the proposed solution for edge computing and cloud computing. Experimental evaluations on a wide range of DNNs show that the proposed NoC architecture enables 20%-80% reduction in communication latency with respect to state-of-the-art interconnect solutions. |
2,262 | Security for Grids | Securing a Grid environment presents a distinctive set of challenges. This paper groups the activities that need to be secured into four categories: naming and authentication; secure communication; trust, policy, and authorization; and enforcement of access control. It examines the current state of the art in securing these activities and introduces new technologies that promise to meet the security requirements of Grids more completely. |
2,263 | An adaptive rejection sampler for sampling from the Wiener diffusion model | The Wiener diffusion model with two absorbing boundaries is one of the most frequently applied models for jointly modeling responses and response latencies in psychological research. We consider four methods for sampling from the model with and without variability in drift rate, starting point, and non-decision time: Inverse transform sampling, rejection sampling, and two new methods based on adaptive rejection sampling (ARS). We implement these four methods in an R package, validate the methods, and compare their sampling speed in different settings. All four implemented methods provide samples that follow the intended distributions. The ARS-based methods, however, outperform the other methods in sampling speed as the requested sample size increases. We provide guidelines for when using ARS is more efficient than using traditional methods and vice versa. |
2,264 | A rapid bacterial pathogen and antimicrobial resistance diagnosis workflow using Oxford nanopore adaptive sequencing method | Metagenomic sequencing analysis (mNGS) has been implemented as an alternative approach for pathogen diagnosis in recent years, which is independent of cultivation and is able to identify all potential antibiotic resistance genes (ARGs). However, current mNGS methods have to deal with low amounts of prokaryotic deoxyribonucleic acid (DNA) and high amounts of host DNA in clinical samples, which significantly decrease the overall microbial detection resolution. The recently released nanopore adaptive sampling (NAS) technology facilitates immediate mapping of individual nucleotides to a given reference as each molecule is sequenced. User-defined thresholds allow for the retention or rejection of specific molecules, informed by the real-time reference mapping results, as they are physically passing through a given sequencing nanopore. We developed a metagenomics workflow for ultra-sensitive diagnosis of bacterial pathogens and ARGs from clinical samples, which is based on the efficient selective 'human host depletion' NAS sequencing, real-time species identification and species-specific resistance gene prediction. Our method increased the microbial sequence yield at least 8-fold in all 21 sequenced clinical Bronchoalveolar Lavage Fluid (BALF) samples (4.5 h from sample to result) and accurately detected the ARGs at species level. The species-level positive percent agreement between metagenomic sequencing and laboratory culturing was 100% (16/16) and negative percent agreement was 100% (5/5) in our approach. Further work is required for a more robust validation of our approach with large sample size to allow its application to other infection types. |
2,265 | DCNS: An Adaptable High Throughput RFID Reader-to-Reader Anticollision Protocol | The reader-to-reader collision problem represents a research topic of great recent interest for the radio frequency identification (RFID) technology. Among the state-of-the-art anticollision protocols, the ones that provide high throughput often have special requirements, such as extra hardware. This study investigates new high throughput solutions for static RFID networks without additional requirements. In this paper, two contributions are presented: a new configuration, called Killer, and a new protocol, called distributed color noncooperative selection (DCNS). The proposed configuration generates selfish behavior, thereby increasing channel utilization and throughput. DCNS fully exploits the Killer configuration and provides new features, such as dynamic priority management, which modifies the performance of the RFID readers when it is requested. Simulations have been conducted in order to analyze the effects of the innovations proposed. The proposed approach is especially suitable for low-cost applications with a priority not uniformly distributed among readers. The experimental analysis has shown that DCNS provides a greater throughput than the state-of-the-art protocols, even those with additional requirements (e. g., 16 percent better than NFRA). |
2,266 | GM-CSF-activated human dendritic cells promote type 1 T follicular helper cell polarization in a CD40-dependent manner | T follicular helper (Tfh) cells regulate humoral responses and present a marked phenotypic and functional diversity. Type 1 Tfh (Tfh1) cells were recently identified and associated with disease severity in infection and autoimmune diseases. The cellular and molecular requirements to induce human Tfh1 differentiation are not known. Here, using single-cell RNA sequencing (scRNAseq) and protein validation, we report that human blood CD1c+ dendritic cells (DCs) activated by GM-CSF (also known as CSF2) drive the differentiation of naive CD4+ T cells into Tfh1 cells. These Tfh1 cells displayed typical Tfh molecular features, including high levels of PD-1 (encoded by PDCD1), CXCR5 and ICOS. They co-expressed BCL6 and TBET (encoded by TBX21), and secreted large amounts of IL-21 and IFN-γ (encoded by IFNG). Mechanistically, GM-CSF triggered the emergence of two DC sub-populations defined by their expression of CD40 and ICOS ligand (ICOS-L), presenting distinct phenotypes, morphologies, transcriptomic signatures and functions. CD40High ICOS-LLow DCs efficiently induced Tfh1 differentiation in a CD40-dependent manner. In patients with mild COVID-19 or latent Mycobacterium tuberculosis infection, Tfh1 cells were positively correlated with a CD40High ICOS-LLow DC signature in scRNAseq of peripheral blood mononuclear cells or blood transcriptomics, respectively. Our study uncovered a novel CD40-dependent Tfh1 axis with potential physiopathological relevance to infection. This article has an associated First Person interview with the first author of the paper. |
2,267 | Attention and counter-framing in the Black Lives Matter movement on Twitter | The social media platform Twitter platform has played a crucial role in the Black Lives Matter (BLM) movement. The immediate, flexible nature of tweets plays a crucial role both in spreading information about the movement's aims and in organizing individual protests. Twitter has also played an important role in the right-wing reaction to BLM, providing a means to reframe and recontextualize activists' claims in a more sinister light. The ability to bring about social change depends on the balance of these two forces, and in particular which side can capture and maintain sustained attention. The present study examines 2 years worth of tweets about BLM (about 118 million in total). Timeseries analysis reveals that activists are better at mobilizing rapid attention, whereas right-wing accounts show a pattern of moderate but more sustained activity driven by reaction to political opponents. Topic modeling reveals differences in how different political groups talk about BLM. Most notably, the murder of George Floyd appears to have solidified a right-wing counter-framing of protests as arising from dangerous "terrorist" actors. The study thus sheds light on the complex network and rhetorical effects that drive the struggle for online attention to the BLM movement. |
2,268 | Statistical comparison of InSAR tropospheric correction techniques | Correcting for tropospheric delays is one of the largest challenges facing the interferometric synthetic aperture radar (InSAR) community. Spatial and temporal variations in temperature, pressure, and relative humidity create tropospheric signals in InSAR data, masking smaller surface displacements due to tectonic or volcanic deformation. Correction methods using weather model data, GNSS and/or spectrometer data have been applied in the past, but are often limited by the spatial and temporal resolution of the auxiliary data. Alternatively a correction can be estimated from the interferometric phase by assuming a linear or a power-law relationship between the phase and topography. Typically the challenge lies in separating deformation from tropospheric phase signals. In this study we performed a statistical comparison of the state-of-the-art tropospheric corrections estimated from the MERIS and MODIS spectrometers, a low and high spatial-resolution weather model (ERA-I and WRF), and both the conventional linear and new power-law empirical methods. Our test-regions include Southern Mexico, Italy, and El Hierro. We find spectrometers give the largest reduction in tropospheric signal, but are limited to cloud-free and daylight acquisitions. We find a similar to 10-20% RMSE increase with increasing cloud cover consistent across methods. None of the other tropospheric correction methods consistently reduced tropospheric signals over different regions and times. We have released a new software package called TRAIN (Toolbox for Reducing Atmospheric InSAR Noise), which includes all these state-of-the-art correction methods. We recommend future developments should aim towards combining the different correction methods in an optimal manner. (C) 2015 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license |
2,269 | Left common pulmonary venous trunk-better be careful than sorry | Pulmonary vein abnormalities are very commonly encountered in general thoracic surgical practice. While performing a lobectomy, ideally all the pulmonary veins should be identified before ligating the corresponding vein. Failing to recognize a common pulmonary vein may lead to an unwarranted pneumonectomy which may end up morbid for the patient. In this report, we present a patient with left lower lobe bronchiectasis who underwent a left lower lobectomy and was identified to have a common left pulmonary venous trunk intra-operatively. |
2,270 | Lossless compression of hyperspectral images using lookup tables | In this letter, we propose a new algorithm for lossless compression of hyperspectral images. The proposed method searches the previous band for a pixel of equal value to the pixel co-located to the one to be coded. The pixel in the same position as the obtained pixel in the current band is used as the predictor. Lookup tables are used to speed up the search. The algorithm is suitable for compression of hyperspectral image data in the band-interleaved-by-line (BIL) format. The method outperforms other state-of-the-art compression algorithms for the BIL data, at a lower time complexity level. Moreover, its compression ratios for the band sequential format data are within a few percentage points of the current state-of-the-art methods. |
2,271 | Explicit shift-invariant dictionary learning | In this article we give efficient solutions to the construction of structured dictionaries for sparse representations. We study circulant and Toeplitz structures and give fast algorithms based on least squares solutions. We take advantage of explicit circulant structures and we apply the resulting algorithms to shift-invariant learning scenarios. Synthetic experiments and comparisons with state-of-the-art methods show the superiority of the proposed methods. |
2,272 | Experimental and numerical study on DCB specimens bonded with similar and dissimilar materials | In this paper, the influence of the bonding materials on the failure modes and the critical energy release rate (CERR) is studied through the double cantilever beam (DCB) test. The test results show that the failure mode and CERR of the bonded structure are closely related to the bonding materials, and three failure modes, i.e., the cohesive failure, the interface failure and the mixed-mode failure are identified on the bonding surface. The finite element method is used to simulate the interface debonding behavior of the DCB test specimens, and the influence of material randomness on the interface failure is introduced. A XFEM/CZM coupled approach is proposed to model the crack migration phenomena. The predicted results have a good agreement with the experimental results. |
2,273 | New developments in the radiocarbon dating of mud wasp nests | This paper reports on the development of radiocarbon dating of mud wasp nests to provide age estimates for rock art and other anthropogenic modifications to the surfaces of open rock shelters. Over 150 rock shelters in the remote Kimberley region of Western Australia were visited in five field seasons. Mud wasp nest samples were collected from 108 sites. Thirty newly constructed wasp nests were collected to understand their initial composition and to determine the major sources of carbon. Charcoal-rich fractions extracted from 9 modem nests were radiocarbon dated and, whilst most were of zero age, some were found to be up to 1000 years old with the mean age being 255 years. Of the old wasp nest samples, 120 were utilised in the experiments reported here. A variety of different physical and chemical pretreatment methods were explored but small sample sizes and low carbon concentrations limit the range of techniques that can be used in practice. The radiocarbon ages measured on the 75 nest samples that contained sufficient carbon for analysis ranged from Modern to just over 20 cal ka BP. Half of these nests were older than 8 cal ka BP and 20% were older than 11 cal ka BP. Even allowing for the inherent uncertainties due to any inbuilt carbon age, the method is capable of producing useful age estimates for rock art and other features of archaeological interest, in relatively open rock shelters. |
2,274 | Development of redox stable fuel electrode supported solid oxide cells | A novel solid oxide cell concept, named as redox solid oxide cell, is proposed in this work. To demonstrate the concept, solid oxide cells with doped-SrTiO3 fuel electrodes and modified NiO-3YSZ fuel electrode support were developed to realize the redox-stable solid oxide cells. By modifying the particle characteristics of NiO, 3YSZ, slurry composition and sintering profile, a redox stable and multifunctional NiO-3YSZ fuel electrode support was successfully developed. Furthermore, two different types of doped-SrTiO3 (Sr0.94Ti0.9Nb0.1O3 and La0.49Sr0.31Fe0.03Ni0.03Ti0.94O3) fuel electrode materials were successfully integrated in to the half-cells with redox stable NiO-3YSZ support. Defect free solid oxide cells of 12 cm x 12 cm size were fabricated. The redox stability of these cells was evaluated and compared with the state-of-the-art NiO-3YSZ solid oxide cells at 850 degrees C. It was clearly demonstrated that the newly developed redox solid oxide cells have superior stability compared to the state-of-the-art cells. In order to establish the potential of the newly developed redox solid oxide cells, the evaluation of the electrochemical performance is required. (C) 2019 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved. |
2,275 | Some new results on Cox-Czanner divergence and their applications in survival studies | In the present communication, we propose a quantile-based measure for the divergence between two survival functions. This can also be used in a dynamic way where the divergence between survival functions varies with time. Several new properties of the proposed measure are investigated with suitable examples. The behavior of the measure for various reliability models is also investigated. A real data analysis is employed to compare the relative efficacy of two treatment groups using the proposed divergence measure. |
2,276 | Effects of a Specialist-Led, School Physical Education Program on Bone Mass, Structure, and Strength in Primary School Children: A 4-Year Cluster Randomized Controlled Trial | This 4-year cluster randomized controlled trial of 365 boys and 362 girls (mean age 8.1 ± 0.3 years) from grade 2 in 29 primary schools investigated the effects of a specialist-taught physical education (PE) program on bone strength and body composition. All children received 150 min/week of common practice (CP) PE from general classroom teachers but in 13 schools 100 min/week of CP PE was replaced by specialized-led PE (SPE) by teachers who emphasized more vigorous exercise/games combined with static and dynamic postural activities involving muscle strength. Outcome measures assessed in grades 2, 4, and 6 included: total body bone mineral content (BMC), lean mass (LM), and fat mass (FM) by DXA, and radius and tibia (4% and 66% sites) bone structure, volumetric density and strength, and muscle cross-sectional area (CSA) by pQCT. After 4-years, gains in total body BMC, FM, and muscle CSA were similar between the groups in both sexes, but girls in the SPE group experienced a greater gain in total body LM (mean 1.0 kg; 95% CI, 0.2 to 1.9 kg). Compared to CP, girls in the SPE group also had greater gains in cortical area (CoA) and cortical thickness (CoTh) at the mid-tibia (CoA, 5.0% [95% CI, 0.2% to 1.9%]; CoTh, 7.5% [95% CI, 2.4% to 12.6%]) and mid-radius (CoA, 9.3% [95% CI, 3.5% to 15.1%]; CoTh, 14.4% [95% CI, 6.1% to 22.7%]), whereas SPE boys had a 5.2% (95% CI, 0.4% to 10.0%) greater gain in mid-tibia CoTh. These benefits were due to reduced endocortical expansion. There were no significant benefits of SPE on total bone area, cortical density or bone strength at the mid-shaft sites, nor any appreciable effects at the distal skeletal sites. This study indicates that a specialist-led school-based PE program improves cortical bone structure, due to reduced endocortical expansion. This finding challenges the notion that periosteal apposition is the predominant response of bone to loading during the prepubertal and early-pubertal period. |
2,277 | Factors Affecting Learners' Academic Success in Online Liberal Arts Courses Offered by a Traditional Korean University | This study aimed to empirically examine the factors affecting full-time undergraduate students' satisfaction and academic performance measured by grades using an existing large administrative dataset. The sample consisted of 21,662 undergraduate students who took online liberal arts courses offered by a large traditional Korean university in the spring semester of 2020. The theoretical framework of this study was formulated by selectively adopting and slightly modifying some of the factors from Choi's conceptual model for adult dropout from online degree programs. The findings indicated that gender, previous GPA, campus, type of online course, the relevance of the course, adequacy of assignments and assessments, learner-instructor interaction, and learner-content interaction significantly affect students' degree of satisfaction with online liberal arts courses. This study also found that students who considered the course less relevant to their goals or interests, had a low previous GPA, had frequent learner-instructor interactions, few learner-content interactions, and a low level of course satisfaction are more likely to earn a grade of B, C, or lower than to receive an A in online liberal arts courses. |
2,278 | Microbiome analysis revealing microbial interactions and secondary bacterial infections in COVID-19 patients comorbidly affected by Type 2 diabetes | The mortality of coronavirus disease 2019 (COVID-19) disease is very high among the elderly or individuals having comorbidities such as obesity, cardiovascular diseases, lung infections, hypertension, and/or diabetes. Our study characterizes the metagenomic features in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-infected patients with or without type 2 diabetes, to identify the microbial interactions associated with its fatal consequences.This study compared the baseline nasopharyngeal microbiome of SARS-CoV-2-infected diabetic and nondiabetic patients with controls adjusted for age and gender. The metagenomics based on next-generation sequencing was performed using Ion GeneStudio S5 Series and the data were analyzed by the Vegan-package in R. All three groups possessed significant bacterial diversity and dissimilarity indexes (p < 0.05). Spearman's correlation coefficient network analysis illustrated 183 significant positive correlations and 13 negative correlations of pathogenic bacteria (r = 0.6-1.0, p < 0.05), and 109 positive correlations between normal flora and probiotic bacteria (r > 0.6, p < 0.05). The SARS-CoV-2 diabetic group exhibited a significant increase in pathogens and secondary infection-causing bacteria (p < 0.05) with a simultaneous decrease of normal flora (p < 0.05). The dysbiosis of the bacterial community might be linked with severe consequences of COVID-19-infected diabetic patients, although a few probiotic strains inhibited numerous pathogens in the same pathological niches. This study suggested that the promotion of normal flora and probiotics through dietary supplementation and excessive inflammation reduction by preventing secondary infections might lead to a better outcome for those comorbid patients. |
2,279 | Machine learning algorithms to automate differentiating cardiac amyloidosis from hypertrophic cardiomyopathy | Cardiac amyloidosis has a poor prognosis, and high mortality and is often misdiagnosed as hypertrophic cardiomyopathy, leading to delayed diagnosis. Machine learning combined with speckle tracking echocardiography was proposed to automate differentiating two conditions. A total of 74 patients with pathologically confirmed monoclonal immunoglobulin light chain cardiac amyloidosis and 64 patients with hypertrophic cardiomyopathy were enrolled from June 2015 to November 2018. Machine learning models utilizing traditional and advanced algorithms were established and determined the most significant predictors. The performance was evaluated by the receiver operating characteristic curve (ROC) and the area under the curve (AUC). With clinical and echocardiography data, all models showed great discriminative performance (AUC > 0.9). Compared with logistic regression (AUC 0.91), machine learning such as support vector machine (AUC 0.95, p = 0.477), random forest (AUC 0.97, p = 0.301) and gradient boosting machine (AUC 0.98, p = 0.230) demonstrated similar capability to distinguish cardiac amyloidosis and hypertrophic cardiomyopathy. With speckle tracking echocardiography, the predictive performance of the voting model was similar to that of LightGBM (AUC was 0.86 for both), while the AUC of XGBoost was slightly lower (AUC 0.84). In fivefold cross-validation, the voting model was more robust globally and superior to the single model in some test sets. Data-driven machine learning had shown admirable performance in differentiating two conditions and could automatically integrate abundant variables to identify the most discriminating predictors without making preassumptions. In the era of big data, automated machine learning will help to identify patients with cardiac amyloidosis and timely and effectively intervene, thus improving the outcome. |
2,280 | A guiding framework for creating a comprehensive strategy for mHealth data sharing, privacy, and governance in low- and middle-income countries (LMICs) | With the numerous advances and broad applications of mobile health (mHealth), establishing concrete data sharing, privacy, and governance strategies at national (or regional) levels is essential to protect individual privacy and data usage. This article applies the recent Health Data Governance Principles to provide a guiding framework for low- and middle-income countries (LMICs) to create a comprehensive mHealth data governance strategy. We provide three objectives: (1) establish data rights and ownership to promote equitable benefits from health data, (2) protect people through building trust and addressing patients' concerns, and (3) promote health value by enhancing health systems and services. We also recommend actions for realizing each objective to guide LMICs based on their unique mHealth data ecosystems. These objectives require adopting a regulatory framework for data rights and protection, building trust for data sharing, and enhancing interoperability to use new datasets in advancing healthcare services and innovation. |
2,281 | High-Performance UV-Vis Broad-Spectra Photodetector Based on a β-Ga2O3/Au/MAPbBr3 Sandwich Structure | The UV-vis photodetector (PD), a detector that can simultaneously detect light in the ultraviolet region and the visible region, has a wide range of applications in military and civilian fields. Currently, it is very difficult to obtain good detection performance in the UV region (especially in the solar-blind range) like in the visible region with most UV-vis PDs. This severely affects the practical application of UV-vis broad-spectra PDs. Here, a simple sandwich structure PD (SSPD) composed of β-Ga2O3, Au electrodes, and the MAPbBr3 perovskite is designed and fabricated to simultaneous enhance the detection performance in the UV and visible light regions. The β-Ga2O3/Au/MAPbBr3 SSPD exhibits enhanced optoelectronic performance with high responsivities of 0.47 and 1.43 A W-1 at 240 and 520 nm under a bias of 6 voltage (V), respectively, which are 8.5 and 23 times than that of the metal-semiconductor-metal (MSM) structure MAPbBr3 PD at 6 V, respectively. The enhanced performance was attributed to the effective suppression of carrier recombination due to the efficient interface charge separation in the device structure. In addition, the self-powered response characteristic is also realized by forming a type-II heterojunction between β-Ga2O3 and MAPbBr3, which gives the β-Ga2O3/Au/MAPbBr3 SSPD superior single-pixel photo-imaging ability without an external power supply. This work provides a simple and effective method for the preparation of high-performance self-powered imaging PDs in the UV-visible region. |
2,282 | LCANet: Learnable Connected Attention Network for Human Identification Using Dental Images | Forensic odontology is regarded as an important branch of forensics dealing with human identification based on dental identification. This paper proposes a novel method that uses deep convolution neural networks to assist in human identification by automatically and accurately matching 2-D panoramic dental X-ray images. Designed as a top-down architecture, the network incorporates an improved channel attention module and a learnable connected module to better extract features for matching. By integrating associated features among all channel maps, the channel attention module can selectively emphasize interdependent channel information, which contributes to more precise recognition results. The learnable connected module not only connects different layers in a feed-forward fashion but also searches the optimal connections for each connected layer, resulting in automatically and adaptively learning the connections among layers. Extensive experiments demonstrate that our method can achieve new state-of-the-art performance in human identification using dental images. Specifically, the method is tested on a dataset including 1,168 dental panoramic images of 503 different subjects, and its dental image recognition accuracy for human identification reaches 87.21% rank-1 accuracy and 95.34% rank-5 accuracy. Code has been released on Github. (https://github.com/cclaiyc/TIdentify) |
2,283 | Review of alternative cooling technologies | This paper provides an update on alternative cooling technologies in the context of a report by Fischer et al. [2], which contains an extensive assessment of "not-in-kind" technologies including their state-of-the-art, development issues, and potentials to replace vapor compression equipment. After nearly 20 years, it is now of interest to update the status of alternative technologies considering regulatory actions aimed at refrigerants with high global warming potential. Several technologies are considered with sorption cooling, desiccant cooling, magnetic cooling, thermoacoustic cooling, thermoelectric cooling, and transcritical CO2 being discussed in some detail. For each technology we present its physical principle, a brief summary of the findings of Fischer et al., the technological advancements since their study leading to the current state-of-the-art, and our assessment as to the potential of each technology to enter the market as a supplement to or replacement of vapor compression equipment in the next 20 year period. (C) 2013 Elsevier Ltd. All rights reserved. |
2,284 | Morphogenetic processes on open-air rock art sites in tropical context: archaeo-geomorpho- logical analysis of the pre-Columbian rock art sites of Trois-Rivieres (Guadeloupe, French West Indies) | This work deals with the benefits of the archaeomorphological approach in rock art sites located in semi-tropical environment. Such approach was initially developed for studying rock art in caves and is applied here to two engraved pre-Colombian sites of Trois Rivieres (Guadeloupe): the Parc Archeologique des Roches Gravees and the Petit Carbet site. The aim was to identify the processes (gravitational, biological and hydrological) that shaped the current landscape, hence the spatial organization of the engraved rocks. Geomorphological mapping was conducted and supported by a high-resolution terrestrial LiDAR 3D mapping in order to identify landscape evolution processes pre-and post-rock art. Results show that before engraving, differential weathering of the volcanic rocks favored the genesis of monolithic formations. Those were later affected by mechanical processes (flaking and rock falls). Appart from the anthropic influence that affected some blocs (removal and displacement), the study highlights the influence of phytomechanical processes that were not considered until then. The integration of all those observations allows to reconstruct the shape of landscape at the time of the engravings. At another level, large planar spaces were identified on both sites without any rock art. They are the consequence of sediment infills linked with ancient flow paths. These results open new perspectives in terms of geophysical and archaeological investigations that could lead to a better understanding of the morphology of the site at the time of ornamentation, and potentially to the discovery, under the sediments, of ornamented ensembles, preserved from colonial and modern developments. |
2,285 | Long-Term Results of Total Hip Arthroplasty with 28-Millimeter Cobalt-Chromium Femoral Heads on Highly Cross-Linked Polyethylene in Patients 50 Years and Less | Highly cross-linked polyethylene (HXLPE) is the most commonly used bearing surface in total hip arthroplasty (THA) because of its superior wear properties, but long-term results in young patients are limited. We report on the clinical outcome, radiographic wear patterns and survivorship of 72 patients ≤50 years old who had a 28-millimeter cobalt-chromium femoral head on HXLPE acetabular liner. Mean and median true linear wear rates at average ten-year follow-up were 0.0104 and 0.01 mm per year ± 0.07 mm. Mean and median two-dimensional volumetric wear rates were 12.79 mm(3) and 5.834 mm(3) per year ± 26.1mm(3) as determined by Martell analysis. As a result of the minimal wear profile, there was no evidence of radiographic osteolysis and no wear-related revisions. |
2,286 | Forest cover resilience to climate change over India using the MC2 dynamic vegetation model | It is imperative to understand the climate change impact on the forest ecosystem to develop appropriate mitigation and management strategies. We have employed a process-based dynamic vegetation modeling (MAPSS-CENTURY: MC) approach to project change in vegetation life forms under projected climate conditions that attained 81% overall accuracy. The present and projected climate conditions suggested highly resilient/stable forest covers in wet climate regimes and moderately resilient in dry semi-arid regions. Several forested grids in the seasonally dry tropical forest in the Eastern Ghats and dry Deccan peninsula regions are estimated to be less resilient, which may experience a regime shift toward scrub and grassland. The future prediction demonstrated an upward temperature shift in the Western Himalayas and trans-Himalaya, which may facilitate forest spread at higher elevations. Although the forest cover resilience may increase in future climate conditions, the disturbances in several regions in the Deccan Peninsula and the Eastern Ghats may trigger forest to scrub and grassland transition. The inaccuracy in model simulation in the Western Himalayas could be attributed to coarse resolution grids (0.5°) failing to resolve the narrow climate niches. The spatially explicit model simulation provides opportunities to develop long-term climate change adaptation and conservation strategies. |
2,287 | Energy efficiency techniques in machining process: a review | The paper presents an overview of the state of the art in energy-efficient techniques in the domain of discrete part manufacturing, focusing on the techniques including energy assessment model for machining process and the energy efficiency analysis and evaluation for machine tools, important components, and machining systems. The main motivation is to review the existing works related to reduce energy consumption in machining processes, to discuss the challenges towards energy-efficient manufacturing, and identify the major barriers from both technologies and approaches. |
2,288 | Image Retrieval Using a Deep Attention-Based Hash | Image retrieval is becoming more and more important due to the rapid increase of the number of images on the web. To improve the efficiency of computing the similarity of images, hashing has moved into the focus of research. This paper proposes a Deep Attention-based Hash (DAH) retrieval model, which combines an attention module and a convolutional neural network to obtain hash codes with strong representability. Our DAH has the following features: The Hamming distance between the hash codes generated by similar images is small and the Hamming distance of hash codes of dissimilar images has a larger constant value. The quantitative loss from Euclidean distance to Hamming distance is minimized. DAH has a high image retrieval precision: We thoroughly compare it with ten state-of-the-art approaches on the CIFAR-10 dataset. The results show that the Mean Average Precision (MAP) of DAH reaches more than 92% in terms of 12, 24, 36 and 48 bit hash codes on CIFAR-10, which is better than what the state-of- art methods used for comparison can deliver. |
2,289 | Inverse Synthetic Aperture Radar Imaging: A Historical Perspective and State-of-the-Art Survey | Radar can obtain high spatial resolution at large operating distances, and its operation is largely independent from weather and lighting conditions. This makes it an important instrument in an ever-increasing number of applications requiring robust and reliable sensing of the environment. Due to the advancements in semiconductor technology and digital computation power, radar can obtain increasingly better position estimation accuracy, detection sensitivity, and target resolution. High-resolution imaging is an example of a rapidly advancing field of radar technology. Inverse synthetic aperture radar (ISAR) is an imaging technique that uses the motion of a target to obtain a high-resolution radar image of it. This paper presents a comprehensive review of past work and the state of the art in ISAR imaging systems, algorithms, and applications. Starting from the early historical developments of simple monostatic range-Doppler imaging, we present the developments up to the current advanced spatially distributed imaging modalities and reconstruction algorithms. The list of references includes the most influential ISAR publications in the open literature up to early 2021. |
2,290 | Characterization of the novel KIR3DL1*01507 allele identified in a Chinese Han individual | The novel KIR3DL1*01507 allele differs from the closest allele KIR3DL1*01502 by a single synonymous mutation. |
2,291 | Genetic Algorithms for Multi-objective Optimization: Application to a Multi-reservoir System in the Chi River Basin, Thailand | The multi-objective genetic algorithm is applied to determine the optimal operation of a multi-reservoir system in the Chi River Basin, Thailand. Two competing objective functions are considered; dam release and dam storage. The predicted values for the release and storage needed are mostly lower than in current established management practice. |
2,292 | Keypoint detection by wave propagation | We propose to rely on the wave equation for the detection of repeatable keypoints invariant up to image scale and rotation and robust to viewpoint variations, blur, and lighting changes. The algorithm exploits the properties of local spatial-temporal extrema of the evolution of image intensities under the wave propagation to highlight salient symmetries at different scales. Although the image structures found by most state-of-the-art detectors, such as blobs and corners, occur typically on highly textured surfaces, salient symmetries are widespread in diverse kinds of images, including those related to poorly textured objects, which are hardly dealt with by current pipelines based on local invariant features. The impact on the overall algorithm of different numerical wave simulation schemes and their parameters is discussed, and a pyramidal approximation to speed-up the simulation is proposed and validated. Experiments on publicly available datasets show that the proposed algorithm offers state-of-the-art repeatability on a broad set of different images while detecting regions that can be distinctively described and robustly matched. (c) 2021 SPIE and IS&T |
2,293 | Information-Optimum LDPC Decoders Based on the Information Bottleneck Method | The Information Bottleneck method is a powerful and generic tool from the field of machine learning. It compresses an observation to a quantized variable while attempting to preserve the mutual information shared with a relevant random variable. This paper describes a new application of the Information Bottleneck method in communications. It explains in detail, how the Information Bottleneck method can be applied to construct discrete message passing decoders for regular low-density parity-check codes. The obtained decoders process only unsigned integers and use only simple lookup tables as node operations. As a consequence, the decoders can be implemented using only unsigned integer arithmetic which makes them significantly simpler and faster than the state-of-the-art decoders which process real valued log-likelihood ratios. Anyway, included results show that the considered discrete message passing decoders perform surprisingly close to optimum message passing decoders and even outperform state-of-the-art decoders, such as the min-sum decoder. We aim to take the reader on a journey from the theoretical idea of the Information Bottleneck method to a complete design framework for the considered discrete decoders. Several included figures and examples illustrate the decoder construction process and its analysis. |
2,294 | Treated Waste Water Comsumption Microlysimetric Quantification in Poinsettia (Euphorbia pulcherrima Willd. ex Klotzsch) | In an instrumented greenhouse a poinsettia culture was implemented in Jiutepec, Morelos, consumption of treated wastewater (ART) were measured with suction microlysimeters polyethylene pots 15 cm in diameter with similar granulometry substrates N, V and A, where N = plant leaf-litter/tezontle/coconut fiber in proportion 60: 20: 20, V = plant leaf-litter/tezontle/agrolita/coconut fiber (86:7:3.5:3.5) A = coconut fiber/plant leaf-litter/agrolita (40:40:20) and water consumption through microlysimeters balance with substrate N (BN) were measured, too; 11 of 22 variables had significant differences. BN has the highest values and V the lowest ones. N is equal to A, for all variables. The bracts have differences in area, fresh weight and dry weight, without differences in L*, C* and h. The leaves have no differences in area neither chlorophyll content, and they have differences in fresh and dry weight. Fresh and dry root weight without significant differences. The A substrate showed better agronomic results that N and V substrates. ART consumption of poinsettia can be affected by plant type and irrigation method. In the week after transplantation 2 (after punch), 8, 9 and 10 (start of pigmentation) there are differences between treatments and coincides with an ART decreased consumption period. The suction microlysimetric is a tool to quantify the consumption of ART on poinsettia. |
2,295 | SACNN: Self-Attention Convolutional Neural Network for Low-Dose CT Denoising With Self-Supervised Perceptual Loss Network | Computed tomography (CT) is a widely used screening and diagnostic tool that allows clinicians to obtain a high-resolution, volumetric image of internal structures in a non-invasive manner. Increasingly, efforts have been made to improve the image quality of low-dose CT (LDCT) to reduce the cumulative radiation exposure of patients undergoing routine screening exams. The resurgence of deep learning has yielded a new approach for noise reduction by training a deep multi-layer convolutional neural networks (CNN) to map the low-dose to normal-dose CT images. However, CNN-based methods heavily rely on convolutional kernels, which use fixed-sizefilters to process one local neighborhood within the receptive field at a time. As a result, they are not efficient at retrieving structural information across large regions. In this paper, we propose a novel 3D self-attention convolutional neural network for the LDCT denoising problem. Our 3D self-attention module leverages the 3D volume of CT images to capture a wide range of spatial information both within CT slices and between CT slices. With the help of the 3D self-attention module, CNNs are able to leverage pixels with stronger relationships regardless of their distance and achieve better denoising results. In addition, we propose a self-supervised learning scheme to train a domain-specific autoencoder as the perceptual loss function. We combine these two methods and demonstrate their effectiveness on both CNN-based neural networks and WGAN-based neural networks with comprehensive experiments. Tested on the AAPM-Mayo Clinic Low Dose CT Grand Challenge data set, our experiments demonstrate that self-attention (SA) module and autoencoder (AE) perceptual loss function can efficiently enhance traditional CNNs and can achieve comparable or better results than the state-of-the-art methods. |
2,296 | Adaptive Model Update Strategy for Correlation Filter Trackers | Model update is an important module in target trackers. It plays an important role in adaptive tracking. Many researches have proven that different model update strategies should be adopted, when tracking in different scenes, especially in occlusion and deformation. Though many strategies have been proposed in recent years, few of them make high improvement and good combination on trackers. In this paper, we first proved there is a close relationship between the tracking scenes and the response maps. Then, we proposed an adaptive model update strategy for calculating model update rate based on the response map. Many experiments have been done to compare the proposed model update strategy with some state-of-the-art strategies, and the results have shown that the proposed model update strategy outperforms the best model update strategy by 7 on the test of Kernel Correlation Filter tracker. Furthermore, the proposed model update strategy was evaluated on some state-of-the-art correlation filter trackers. Results have shown the proposed strategy was well integrated into many trackers, and improved the tracking accuracy effectively. |
2,297 | Molecular Screening of Clinical Multidrug-Resistant Gram-Negative Bacteria Shows Endemicity of Carbapenemases, Coexistence of Multiple Carbapenemases, and Rarity of mcr in South Africa | Background: Extensive use of carbapenems to treat multidrug-resistant (MDR) Gram-negative bacteria (GNB) facilitates the wide dissemination of carbapenemase-producing carbapenem-resistant GNB. Colistin was reintroduced into clinical settings to manage these GNB infections. However, there is currently an increase in the dissemination of mobile colistin resistance (mcr)-producing colistin-resistant GNB isolates in clinical settings. The epidemiology of carbapenemases and mcr in Pretoria was evaluated. Methods: Clinical MDR GNB were collected and screened for carbapenemases and mcr using polymerase chain reaction (PCR); their antibiotic susceptibility profiles were elucidated using the Vitek® 2 automated system (Biomerieux, France) and microbroth dilution (for colistin). Results and Discussion: A total of 306 isolates were collected; a majority of these were Klebsiella pneumoniae (n = 208) and were collected from males (n = 158). The isolates were retrieved from a variety of infection sites, including urine, blood cultures, and rectal swabs. The Vitek 2 system found that these isolates were largely resistant to β-lactams, where 217 (70.9%) had reduced susceptibility to at least one carbapenem (ertapenem, meropenem, or imipenem), and 81 isolates (26.5%) were resistant to colistin. PCR screening identified 201 (65.7%) isolates harboring carbapenemase genes consisting of blaOXA-48 (170, 84.2%), blaNDM (31, 15.4%), blaIMP (5, 2%), blaKPC (4, 1%), and blaVIM (5, 2%). Furthermore, 14 blaOXA-48-producing isolates were coharboring blaVIM (2), blaNDM (9), blaKPC (1), and blaIMP (2) genes. Only one isolate harbored the mobile colistin resistance (mcr)-1 gene, and this is the first report of an mcr-1-producing Acinetobacter baumannii isolate in South Africa. Conclusion: There is high endemicity of carbapenemase genes and a low prevalence of mcr genes in GNB, particularly in K. pneumoniae, in health care facilities in Pretoria and surrounding regions of South Africa. Significance: Health care facilities in Pretoria are becoming breeding grounds for MDR infections that threaten public health. Careful use of carbapenems and other antibiotics is necessary to prevent further escalation and outbreak of these MDR strains that can claim several lives. |
2,298 | Wave Energy Assessment and Performance Estimation of State of the Art Wave Energy Converters in Italian Hotspots | This paper presents an assessment of offshore wave energy potential at the scale of the whole Mediterranean Sea. The offshore wave data were propagated, by means of numerical modeling, toward four Italian coastal areas, namely stretches of coast of Tuscany, Liguria, Sardinia and Sicily. For each area, the wave power and the monthly, seasonal and annual variability at water depths of 50 m and 15 m were analyzed and hotspots were located. The results show strong variability of the wave energy potential from point to point of the same area thus highlighting the need for spatially detailed analysis. The higher values of wave energy potential are located in the hotspots of Sardinia and Sicily, at 11.4 kW/m and 9.1 kW/m, respectively. The Tuscany and the Liguria hotspots are characterized, respectively, by 4.7 kW/m and 2.0 kW/m. In order to point out which state of the art WEC is best suited for the Italian areas, the performances of six different state of the art Wave Energy Converters (WECs) were evaluated. Finally, a comparison of the performances of each WEC in the selected Italian sites and in some European (EU) oceanic sites was conducted. The energy potential in the most energetic EU oceanic site, among those here investigated, is up to 38-times greater than the potentials in the studied Italian areas but the power output, of the best WEC technology, is no more than nine times greater. |
2,299 | Robust Chalcogenophene Viologens as Anolytes for Long-Life Aqueous Organic Redox Flow Batteries with High Battery Voltage | A series of chalcogenophene viologens ([(NPr)2FV]Cl4, [(NPr)2TV]Cl4, and [(NPr)2SeV]Cl4) as anolytes for neutral aqueous organic redox flow batteries (AORFBs) via a combination of chalcogenophenes (furan, thiophene, and selenophene) and viologens are reported. The chalcogenophene viologens showed narrow HOMO-LUMO energy gap, high solubility, and stable electrochemical properties. Compared with the parent [(NPr)2V]Cl4, the introduction of π-conjugated chalcogenophene groups reduced the redox potential and enhanced the stability of their free radical state, which endowed the chalcogenophene viologens/FcNCl-based AORFBs with a higher theoretical battery voltage of 1.20 V and enhanced stability for one-electron storage. In particular, the [(NPr)2FV]Cl4/FcNCl-based AORFB exhibited excellent long-cycle stability for 3000 cycles with 0.0006% capacity decay per cycle for one-electron storage and 300 cycles with 0.06% capacity decay per cycle for two-electron storage at a charge voltage of 1.9 V (1.42 V theoretical battery voltage). This work provided a new strategy for regulating the voltage and improving the performance of neutral AORFBs. |
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