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2,800 | Recognizing Actions Through Action-Specific Person Detection | Action recognition in still images is a challenging problem in computer vision. To facilitate comparative evaluation independently of person detection, the standard evaluation protocol for action recognition uses an oracle person detector to obtain perfect bounding box information at both training and test time. The assumption is that, in practice, a general person detector will provide candidate bounding boxes for action recognition. In this paper, we argue that this paradigm is suboptimal and that action class labels should already be considered during the detection stage. Motivated by the observation that body pose is strongly conditioned on action class, we show that: 1) the existing state-of-the-art generic person detectors are not adequate for proposing candidate bounding boxes for action classification; 2) due to limited training examples, the direct training of action-specific person detectors is also inadequate; and 3) using only a small number of labeled action examples, the transfer learning is able to adapt an existing detector to propose higher quality bounding boxes for subsequent action classification. To the best of our knowledge, we are the first to investigate transfer learning for the task of action-specific person detection in still images. We perform extensive experiments on two benchmark data sets: 1) Stanford-40 and 2) PASCAL VOC 2012. For the action detection task (i.e., both person localization and classification of the action performed), our approach outperforms methods based on general person detection by 5.7% mean average precision (MAP) on Stanford-40 and 2.1% MAP on PASCAL VOC 2012. Our approach also significantly outperforms the state of the art with a MAP of 45.4% on Stanford-40 and 31.4% on PASCAL VOC 2012. We also evaluate our action detection approach for the task of action classification (i.e., recognizing actions without localizing them). For this task, our approach, without using any ground-truth person localization at test time, outperforms on both data sets state-of-the-art methods, which do use person locations. |
2,801 | Kernelized Bayesian Matrix Factorization | We extend kernelized matrix factorization with a full-Bayesian treatment and with an ability to work with multiple side information sources expressed as different kernels. Kernels have been introduced to integrate side information about the rows and columns, which is necessary for making out-of-matrix predictions. We discuss specifically binary output matrices but extensions to real-valued matrices are straightforward. We extend the state of the art in two key aspects: (i) A full-conjugate probabilistic formulation of the kernelized matrix factorization enables an efficient variational approximation, whereas full-Bayesian treatments are not computationally feasible in the earlier approaches. (ii) Multiple side information sources are included, treated as different kernels in multiple kernel learning which additionally reveals which side sources are informative. We then show that the framework can also be used for supervised and semi-supervised multilabel classification and multi-output regression, by considering samples and outputs as the domains where matrix factorization operates. Our method outperforms alternatives in predicting drug-protein interactions on two data sets. On multilabel classification, our algorithm obtains the lowest Hamming losses on 10 out of 14 data sets compared to five state-of-the-art multilabel classification algorithms. We finally show that the proposed approach outperforms alternatives in multi-output regression experiments on a yeast cell cycle data set. |
2,802 | SPACE AND TIME OF LIGHTING DESIGN: THE RESULTS OF THE INTERNATIONAL RESEARCH-TO-PRACTICE CONFERENCE "LIGHTING DESIGN-2016" | The paper is an overview of the main discussion areas of the International Research-to-Practice Conference "Lighting design-2016". The theme of the year 2016 was devoted to "Light, Space, and Time". Professional design community, scientists, architects, artists, engineers, representatives of media and IT-technologies from nine countries including Russia discussed the issues related to art and science integration, urban lighting environment, technical culture and new technologies, education in the field of lighting design. |
2,803 | Fully Automatic Left Atrium Segmentation From Late Gadolinium Enhanced Magnetic Resonance Imaging Using a Dual Fully Convolutional Neural Network | Atrial fibrillation (AF) is the most prevalent form of cardiac arrhythmia. Current treatments for AF remain suboptimal due to a lack of understanding of the underlying atrial structures that directly sustain AF. Existing approaches for analyzing atrial structures in 3-D, especially from late gadolinium-enhanced (LGE) magnetic resonance imaging, rely heavily on manual segmentation methods that are extremely labor-intensive and prone to errors. As a result, a robust and automated method for analyzing atrial structures in 3-D is of high interest. We have, therefore, developed AtriaNet, a 16-layer convolutional neural network (CNN), on 154 3-D LGE-MRIs with a spatial resolution of 0.625 mm x 0.625 mm x 1.25 mm from patients with AF, to automatically segment the left atrial (LA) epicardium and endocardium. AtriaNet consists of a multi-scaled, dual-pathway architecture that captures both the local atrial tissue geometry and the global positional information of LA using 13 successive convolutions and three further convolutions for merging. By utilizing computationally efficient batch prediction, AtriaNet was able to successfully process each 3-D LGE-MRI within 1 min. Furthermore, benchmarking experiments have shown that AtriaNet has outperformed the state-of-the-art CNNs, with a DICE score of 0.940 and 0.942 for the LA epicardium and endocardium, respectively, and an inter-patient variance of <0.001. The estimated LA diameter and volume computed from the automatic segmentations were accurate to within 1.59 mm and 4.01 cm(3) of the ground truths. Our proposed CNN was tested on the largest known data set for LA segmentation, and to the best of our knowledge, it is the most robust approach that has ever been developed for segmenting LGE-MRIs. The increased accuracy of atrial reconstruction and analysis could potentially improve the understanding and treatment of AF. |
2,804 | Methodologies and applications for critical infrastructure protection: State-of-the-art | This work provides an update of the state-of-the-art on energy security relating to critical infrastructure protection. For this purpose, this survey is based upon the conceptual view of OECD countries, and specifically in accordance with EU Directive 114/08/EC on the identification and designation of European critical infrastructures, and on the 2009 US National Infrastructure Protection Plan. The review discusses the different definitions of energy security, critical infrastructure and key resources, and shows some of the experie'nces in countries considered as international reference on the subject, including some information-sharing issues. In addition, the paper carries out a complete review of current methodologies, software applications and modelling techniques around critical infrastructure protection in accordance with their functionality in a risk management framework. The study of threats and vulnerabilities in critical infrastructure systems shows two important trends in methodologies and modelling. A first trend relates to the identification of methods, techniques, tools and diagrams to describe the current state of infrastructure. The other trend accomplishes a dynamic behaviour of the infrastructure systems by means of simulation techniques including systems dynamics, Monte Carlo simulation, multi-agent systems, etc. (C) 2011 Elsevier Ltd. All rights reserved. |
2,805 | Extensive Benchmark and Survey of Modeling Methods for Scene Background Initialization | Scene background initialization is the process by which a method tries to recover the background image of a video without foreground objects in it. Having a clear understanding about which approach is more robust and/or more suited to a given scenario is of great interest to many end users or practitioners. The aim of this paper is to provide an extensive survey of scene background initialization methods as well as a novel benchmarking framework. The proposed framework involves several evaluation metrics and state-of-the-art methods, as well as the largest video data set ever made for this purpose. The data set consists of several camera-captured videos that: 1) span categories focused on various background initialization challenges; 2) are obtained with different cameras of different lengths, frame rates, spatial resolutions, lighting conditions, and levels of compression; and 3) contain indoor and outdoor scenes. The wide variety of our data set prevents our analysis from favoring a certain family of background initialization methods over others. Our evaluation framework allows us to quantitatively identify solved and unsolved issues related to scene background initialization. We also identify scenarios for which state-of-the-art methods systematically fail. |
2,806 | Diffusion 19F-NMR of Nanofluorides: In Situ Quantification of Colloidal Diameters and Protein Corona Formation in Solution | The NMR-detectability of elements of organic ligands that stabilize colloidal inorganic nanocrystals (NCs) allow the study of their diffusion characteristics in solutions. Nevertheless, these measurements are sensitive to dynamic ligand exchange and often lead to overestimation of diffusion coefficients of dispersed colloids. Here, we present an approach for the quantitative assessment of the diffusion properties of colloidal NCs based on the NMR signals of the elements of their inorganic cores. Benefiting from the robust 19F-NMR signals of the fluorides in the core of colloidal CaF2 and SrF2, we show the immunity of 19F-diffusion NMR to dynamic ligand exchange and, thus, the ability to quantify, with high accuracy, the colloidal diameters of different types of nanofluorides in situ. With the demonstrated ability to characterize the formation of protein corona at the surface of nanofluorides, we envision that this study can be extended to additional formulations and applications. |
2,807 | The "Expo" and the Post-"Expo": The Role of Public Art in Urban Regeneration Processes in the Late 20th Century | In 1998, the Lisbon Universal Exhibition-Expo'98-led to an urban regeneration process on Lisbon's waterfront. Following the example of other cities, this event was a pretext for rethinking and replacing a depressed area and for reconnecting it with the Tagus river through the creation of a set of new spaces for common use along the water. It was promoted as a public art program, which can be considered quite innovative in the Portuguese context. In view of this framework, this article aims to debate the relationships between public art and the dynamics of urban regeneration at the end of the 20th century. For that, it will analyse: (1) Expo'98's public art program, comparing its initial assumptions with the final results; and (2) the impact of this program, through the identification of the placement of public art before (1974-1998) and after (1999-2009) the event. Although most of the implemented works did not (intentionally) explore aspects of space integration nor issues of public space appropriation, Expo'98's public art program originated a monumentalisation of Lisbon's eastern riverfront, later extended to other waterfront areas. At the same time, it played an important role in the way of understanding the city and public space that decisively influenced subsequent policies and projects. It is concluded that public art had a significant role in urban processes in the late 20th century, which is quite evident in a discourse of urban art as space qualifier and as a means of economic and social development. |
2,808 | Traffic grooming and clique partitioning-based spectrum assignment in elastic optical networks | We adopt a fragmentation reducing policy for spectrum assignment and incorporate it with multicast traffic grooming in EON. To reduce fragmentation, the spectrum is partitioned based on the clique partitioning approach and spectral slots are assigned to traffic demands depending on which partition they belong. Simulation results predict that the proposed approach has better spectrum slot utilization compared to the state-of-the-art non-partitioning approach and the proposed approach reduces fragmentation, and also has less blocking ratio compared to the state-of-the-art partitioning approach. |
2,809 | Affine invariant features from the trace transform | The trace transform is a generalization of the Radon transform that allows one to construct image features that are invariant to a chosen group of image transformations. In this paper, we propose a methodology and appropriate functionals that can be computed from the image function and which can be used to calculate features invariant to the group of affine transforms. We demonstrate the usefulness of the constructed image descriptors in retrieving images from an image database and compare it with relevant state-of-the-art object retrieval methods. |
2,810 | A Scalable Near-Memory Architecture for Training Deep Neural Networks on Large In-Memory Datasets | Most investigations into near-memory hardware accelerators for deep neural networks have primarily focused on inference, while the potential of accelerating training has received relatively little attention so far. Based on an in-depth analysis of the key computational patterns in state-of-the-art gradient-based training methods, we propose an efficient near-memory acceleration engine called NTX that can be used to train state-of-the-art deep convolutional neural networks at scale. Our main contributions are: (i) a loose coupling of RISC-V cores and NTX co-processors reducing offloading overhead by 7 x over previously published results; (ii) an optimized IEEE 754 compliant data path for fast high-precision convolutions and gradient propagation; (iii) evaluation of near-memory computing with NTX embedded into residual area on the Logic Base die of a Hybrid Memory Cube; and (iv) a scaling analysis to meshes of HMCs in a data center scenario. We demonstrate a 2.7 x energy efficiency improvement of NTX over contemporary GPUs at 4.4 x less silicon area, and a compute performance of 1.2 Tflop/s for training large state-of-the-art networks with full floating-point precision. At the data center scale, a mesh of NTX achieves above 95 percent parallel and energy efficiency, while providing 2.1 x energy savings or 3.1 x performance improvement over a GPU-based system. |
2,811 | MMA: a multi-view and multi-modality benchmark dataset for human action recognition | Human action recognition is an active research topic in both computer vision and machine learning communities, which has broad applications including surveillance, biometrics and human computer interaction. In the past decades, although some famous action datasets have been released, there still exist limitations, including the limited action categories and samples, camera views and variety of scenarios. Moreover, most of them are designed for a subset of the learning problems, such as single-view learning problem, cross-view learning problem and multi-task learning problem. In this paper, we introduce a multi-view, multi-modality benchmark dataset for human action recognition (abbreviated to MMA). MMA consists of 7080 action samples from 25 action categories, including 15 single-subject actions and 10 double-subject interactive actions in three views of two different scenarios. Further, we systematically benchmark the state-of-the-art approaches on MMA with respective to all three learning problems by different temporal-spatial feature representations. Experimental results demonstrate that MMA is challenging on all three learning problems due to significant intra-class variations, occlusion issues, views and scene variations, and multiple similar action categories. Meanwhile, we provide the baseline for the evaluation of existing state-of-the-art algorithms. |
2,812 | Risk assessment in livestock supply chain using the MCDM method: a case of emerging economy | The purpose of the study is to identify and assess the risks related to the livestock supply chain. The major risk related to the livestock supply chain are identified through the comprehensive literature review and finalized with the help of the expert's feedback. Initially, seventeen major livestock supply chain risks are finalized, and these risks are categorized into four major dimensions. Further, analytical hierarchical process (AHP) is used to prioritize these identified major risks based on their severity. Finally, sensitivity analysis is conducted to check the robustness of the risk priorities. The result shows that "input supply risk" is the most significant risk dimension followed by "production risk," "post-harvest risk," and "marketing & price risk." The finding also suggests that "poor quality and under supply of feed and fodder," "lack of proper waste disposal," and "absence of certification for the quality of animals" are the major risks among all seventeen risks. The highest priority risks are input supply risks which require the attention of the livestock supply chain partners. The proposed research framework is used to identify and analyze the livestock supply chain risks. The findings of this research might be beneficial for the farmers and other livestock supply chain stakeholders in developing policies/plans/strategies to control the risk in their livestock supply chain. |
2,813 | Western gray whales on their summer feeding ground off Sakhalin Island in 2015: who is foraging where? | In the face of cumulative effects of oil and gas activities on the endangered western gray whale, informed management decisions rely on knowledge of gray whale spatial use patterns as a function of demographic group and prey energy. In particular, the gray whale foraging ground off Sakhalin Island consists of two distinct areas (nearshore and offshore) with the offshore feeding area exhibiting markedly high prey energy content. Based on photo-identification data collected from 2002 to 2015, we determined that gray whale use of the offshore feeding area increased with age. Pregnant females were more likely to be sighted only nearshore when nearshore prey energy and the proportion of nearshore energy from amphipods were higher. Likewise, females arriving with calves were less likely to be sighted offshore when the proportion of nearshore energy from amphipods was higher. Photo-identification effort in 2015 was increased substantially, with the intent of maximizing resighting data of individual whales to determine the relative proportion of different demographic groups utilizing the nearshore and offshore feeding areas. Comparing sighting data collected in 2015 with data from all previous years combined, mothers arriving with calves were sighted in the offshore feeding area earlier in 2015, with no evidence that they returned to forage nearshore later in the season. Other reproductive females constituted a higher proportion of the animals foraging nearshore prior to 2015, while juveniles were a higher proportion during 2015. Thus, the offshore feeding area is an important component of the gray whales' annual life cycle, particularly if nearshore prey energy continues to decline, and offshore anthropogenic activities need to be monitored and addressed. |
2,814 | A joint loss function for deep face recognition | Convolutional neural networks (CNNs) have been widely used in computer vision community, and significantly improving the state-of-the-art. How to train an intra-class variant and inter-class discriminative feature is a central topic in face recognition. This paper proposes to learn an effective feature from face images by a joint loss function which combines the hard sample triplet (HST) and the absolute constraint triplet (ACT) loss, under the criteria that a maximum intra-class distance should be smaller than any inter-class distance. With the joint supervision of HST and ACT loss, CNNs is enable to learn discriminative features to improve face recognition performance. Experiments on labeled faces in the wild, IARPA Janus Benchmark (IJB-A) and YouTube Faces datasets achieve a comparable or superior performance to the state-of-the-arts. |
2,815 | Dimensioning V2N Services in 5G Networks Through Forecast-Based Scaling | With the increasing adoption of intelligent transportation systems and the upcoming era of autonomous vehicles, vehicular services (such as remote driving, cooperative awareness, and hazard warning) will have to operate in an ever-changing and dynamic environment. Anticipating the dynamics of traffic flows on the roads is critical for these services and, therefore, it is of paramount importance to forecast how they will evolve over time. By predicting future events (such as traffic jams) and demands, vehicular services can take proactive actions to minimize Service Level Agreement (SLA) violations and reduce the risk of accidents. In this paper, we compare several techniques, including both traditional time-series and recent Machine Learning (ML)-based approaches, to forecast the traffic flow at different road segments in the city of Torino (Italy). Using the most accurate forecasting technique, we propose n-max algorithm as a forecast-based scaling algorithm for vertical scaling of edge resources, comparing its benefits against state-of-the-art solutions for three distinct Vehicle-to-Network (V2N) services. Results show that the proposed scaling algorithm outperforms the state-of-the-art, reducing Service Level Objective (SLO) violations for remote driving and hazard warning services. |
2,816 | Facial Sentiment Analysis Using AI Techniques: State-of-the-Art, Taxonomies, and Challenges | With the advancements in machine and deep learning algorithms, the envision of various critical real-life applications in computer vision becomes possible. One of the applications is facial sentiment analysis. Deep learning has made facial expression recognition the most trending research fields in computer vision area. Recently, deep learning-based FER models have suffered from various technological issues like under-fitting or over-fitting. It is due to either insufficient training and expression data. Motivated from the above facts, this paper presents a systematic and comprehensive survey on current state-of-art Artificial Intelligence techniques (datasets and algorithms) that provide a solution to the aforementioned issues. It also presents a taxonomy of existing facial sentiment analysis strategies in brief. Then, this paper reviews the existing novel machine and deep learning networks proposed by researchers that are specifically designed for facial expression recognition based on static images and present their merits and demerits and summarized their approach. Finally, this paper also presents the open issues and research challenges for the design of a robust facial expression recognition system. |
2,817 | Decentralized Caching Schemes and Performance Limits in Two-Layer Networks | We study the decentralized caching scheme in a two-layer network, which includes a server, multiple helpers, and multiple users. Basically, the proposed caching scheme consists of two phases, i.e., placement phase and delivery phase. In the placement phase, each helper/user randomly and independently selects contents from the server and stores them into its memory. In the delivery phase, the users request contents from the server, and the server satisfies each user through a helper. Different from the existing caching scheme, the proposed caching scheme takes into account the pre- stored contents at both helpers and users in the placement phase to design the delivery phase. Meanwhile, the proposed caching scheme exploits index coding in the delivery phase and leverages multicast opportunities, even when different users request distinct contents. Besides, we analytically characterize the performance limit of the proposed caching scheme, and show that the achievable rate region of the proposed caching scheme lies within constant margins to the information-theoretic optimum. In particular, the multiplicative and additive factors are carefully sharpened to be 1/48 and 4, respectively, both of which are better than the state of arts. Finally, simulation results demonstrate the advantage of the proposed caching scheme compared with the state of arts. |
2,818 | Robust vowel region detection method for multimode speech | The aim of this paper is to explore a robust method for vowel region detection from multimode speech. In realistic scenario, speech can be classified into three modes namely; conversation, extempore, and read. The existing method detects the vowel form the speech recorded in clean environment which may not be appropriate for the multimode speech tasks. To address this issue, we proposed an approach based on continuous wavelet transform coefficients and phone boundaries for detecting the vowel regions from different modes of the speech signal. For evaluation of the proposed vowel region (VR) detection technique, TIMIT (read speech) and Bengali (read, extempore, and conversation speech) corpora are used. The proposed VR detection technique is compared to the state-of-the-art methods. The experiments has recorded significant gain in the performance of the proposed technique than the state-of-the-art methods. The efficiency of the proposed technique is shown by extracting vocal tract and excitation source features from automatically detected VRs for developing the multilingual speech mode classification (MSMC) model. The evaluation results report that the performance of the MSMC model is significantly improved when features are extracted from the vowel regions than the entire speech utterance. |
2,819 | Short-term effects of post-fire soil mulching with wheat straw and wood chips on the enzymatic activities in a Mediterranean pine forest | Soils of Mediterranean forests can be severely degraded due to wildfire. However, post-fire management techniques, such as soil mulching with vegetal residues, can limit degradation and increase functionality of burned soils. The effects of post-fire mulching on soil functionality have been little studied in Mediterranean forests, and it is still unclear whether the application of straw or wood residues is beneficial. This study explores the changes in important soil chemical and biochemical properties in a pine forest of Central Eastern Spain after a wildfire and post-fire mulching with straw or wood chips. Only basal soil respiration (BSR), dehydrogenase activity (DHA), pH and water field capacity (WFC) significantly changed after the fire and mulching. In contrast, the other enzymatic activities - urease (UA), alkaline phosphatase (Alk-PA) and β-glucosidase (BGA), - total organic carbon (TOC) and electrical conductivity (EC) were not influenced by these soil disturbances. Time from fire and soil conditions (due to burning and management) were significant variability factors for BSR, pH, BGA, UA, TOC, EC. Mulching increased BSR compared to burned areas, especially in soils with straw (+30 %), thanks to addition of fresh organic residues, quickly incorporated in the soil. Soil pH showed a low variability among the four soil conditions, and TOC was higher in mulched soils (on average + 20 % compared to the burned soils), and this was correlated to the increased BSR. The role of mulching was essential with reference to WFC, as the post-fire management limited its reduction after the fire (on average from -30 % to -20 %). Finally, the Principal Component Analysis coupled to the Analytical Hierarchical Cluster Analysis confirmed the significant influence of the post-fire management on some enzymatic activities, although a sharp discrimination among the four soil conditions was only evident between unburned and burned sites, regardless of the management. Overall, it has been shown that mulching promotes conservation of fragile Mediterranean soils, indicating its effectiveness at preserving soil functionality in areas affected by forest fires. |
2,820 | A multi-technique approach to contextualising painted rock art in the Central Pilbara of Western Australia: Integrating in-field and laboratory methods | For nearly 70 years scientific techniques have been routinely applied in archaeological research. Yet some artefacts hold such cultural significance that sampling is inappropriate, restricting the methods that can be brought to bear in their analysis. Such restrictions often apply to rock art, especially where research is directed by the indigenous peoples who have stewardship over not only the site fabric, but its inseparable cultural context. Here we report a multi-technique program of in-field and laboratory-based analyses to describe the materiality of a painted rock art site in Nyiyaparli country, in the Central Pilbara region of Western Australia. The relationship between the rock art, nearby potential pigment sources and evidence for ochre processing at the site was investigated using in situ portable X-Ray Fluorescence and optical microscopy, with interpretations aided by field and laboratory-based residue analysis of grinding related stone artefacts and X-Ray Powder Diffraction of potential ochre sources. Our findings provide an example of the nuanced interpretations that scientific analyses can add to rock art investigations. Our work suggests that local materials were used in the production of painted art and that ochre processing was ubiquitous at the site and other nearby mckshelters. Combined with the placement of rock art in a hidden context within the site, we suggest the panels at BBH15-01 were part of in-group events and that art and ochre processing in the Baby Hope study area were part of everyday activities. |
2,821 | Review of extra-embryonic tissues in the closest arthropod relatives, onychophorans and tardigrades | The so-called extra-embryonic tissues are important for embryonic development in many animals, although they are not considered to be part of the germ band or the embryo proper. They can serve a variety of functions, such as nutrient uptake and waste removal, protection of the embryo against mechanical stress, immune response and morphogenesis. In insects, a subgroup of arthropods, extra-embryonic tissues have been studied extensively and there is increasing evidence that they might contribute more to embryonic development than previously thought. In this review, we provide an assessment of the occurrence and possible functions of extra-embryonic tissues in the closest arthropod relatives, onychophorans (velvet worms) and tardigrades (water bears). While there is no evidence for their existence in tardigrades, these tissues show a remarkable diversity across the onychophoran subgroups. A comparison of extra-embryonic tissues of onychophorans to those of arthropods suggests shared functions in embryonic nutrition and morphogenesis. Apparent contribution to the final form of the embryo in onychophorans and at least some arthropods supports the hypothesis that extra-embryonic tissues are involved in organogenesis. In order to account for this role, the commonly used definition of these tissues as 'extra-embryonic' should be reconsidered. This article is part of the theme issue 'Extraembryonic tissues: exploring concepts, definitions and functions across the animal kingdom'. |
2,822 | Fibroelastolytic papulosis: histopathologic confirmation of disease spectrum variants in a single case | Fibroelastolytic papulosis is a rare, acquired fibroelastolytic disorder that presents clinically as white-to-yellow papules and plaques most commonly occurring on the neck of elderly patients. The term fibroelastolytic papulosis encompasses two closely related conditions previously described as pseudoxanthoma elasticum-like papillary dermal elastolysis (PDE) and white fibrous papulosis of the neck (WFPN). Here we present a case of a 78-year-old white female with a several-year history of numerous, asymptomatic 2-3 mm yellowish, non-follicular papules distributed symmetrically over the posterior neck, axillae, arm and antecubital fossae. Histopathologic examination revealed thickened and clumped elastotic fibers admixed with thick, sclerotic appearing collagen bundles in the mid and deep reticular dermis. Rare melanophages, loss of vertically oriented elastic fibers and scattered elastotic globes were noted in the papillary dermis. Based on the shared clinicopathologic features showed in this case, strong consideration should be made for the additional inclusion of papillary dermal elastosis as existing along the disease continuum of fibroelastolytic papulosis. This occurrence of fibroelastolytic papulosis shows unique histopathologic findings of pseudoxanthoma elasticum-like PDE, papillary dermal elastosis and WFPN, further supporting the theory that these entities exist as variants along the fibroelastolytic papulosis spectrum. |
2,823 | PWM regenerative rectifiers: State of the art | New regulations impose more stringent limits on current harmonies injected by power converters that are achieved with pulsewidth-modulated (PWM) rectifiers. In addition, several applications demand the capability of power regeneration to the power supply. This paper presents the state of the art in the field of regenerative rectifiers with reduced input harmonics and improved power factor. Regenerative rectifiers are able to deliver energy back from the dc side to the ac power supply. Topologies for single- and three-phase power supplies are considered with their corresponding control strategies. Special attention is given to the application of voltage- and current-source PWM rectifiers in different processes with a power range from a few kilowatts up to several megawatts. This paper shows that PWM regenerative rectifiers are a highly developed and mature technology with a wide industrial acceptance. |
2,824 | Structures and mechanisms of actin ATP hydrolysis | The major cytoskeleton protein actin undergoes cyclic transitions between the monomeric G-form and the filamentous F-form, which drive organelle transport and cell motility. This mechanical work is driven by the ATPase activity at the catalytic site in the F-form. For deeper understanding of the actin cellular functions, the reaction mechanism must be elucidated. Here, we show that a single actin molecule is trapped in the F-form by fragmin domain-1 binding and present their crystal structures in the ATP analog-, ADP-Pi-, and ADP-bound forms, at 1.15-Å resolutions. The G-to-F conformational transition shifts the side chains of Gln137 and His161, which relocate four water molecules including W1 (attacking water) and W2 (helping water) to facilitate the hydrolysis. By applying quantum mechanics/molecular mechanics calculations to the structures, we have revealed a consistent and comprehensive reaction path of ATP hydrolysis by the F-form actin. The reaction path consists of four steps: 1) W1 and W2 rotations; 2) PG-O3B bond cleavage; 3) four concomitant events: W1-PO3- formation, OH- and proton cleavage, nucleophilic attack by the OH- against PG, and the abstracted proton transfer; and 4) proton relocation that stabilizes the ADP-Pi-bound F-form actin. The mechanism explains the slow rate of ATP hydrolysis by actin and the irreversibility of the hydrolysis reaction. While the catalytic strategy of actin ATP hydrolysis is essentially the same as those of motor proteins like myosin, the process after the hydrolysis is distinct and discussed in terms of Pi release, F-form destabilization, and global conformational changes. |
2,825 | Thermodynamic performance analysis of state of the art gas turbine cycles with inter-stage turbine reheat and steam injection | Inter-stage turbine reheat is an effective gas turbine retrofit which can easily be used with simple and steam injected (SI) gas turbines as well. Although reheat provides higher inlet temperatures for HRSG in SI cycles and also increases net work output significantly, reheat combustor increases fuel consumption and thermal efficiency may still decrease. Therefore effects of reheat and steam injection in terms of thermodynamic performance require a detailed thermodynamic investigation. In this regard, simple, reheat, steam injected (STIG) and reheat steam injected (RHSTIG) gas turbine cycles are compared using the state of the art cycle parameters. Optimal performance parameters are determined using a new comprehensive cycle model which simulates combustion process regarding 14 exhaust species. It has been found that reheat provides a significant improvement on the cycle net work but it is not suitable for cycles having low pressure ratios if the only concern is maximum thermal efficiency. Results show that a good compromise between the maximum net work and maximum thermal efficiency is observed when reheat pressure is equal to the 0.4th power to the maximum cycle pressure. At this case, reheat provided 35.5% improvement in net cycle work with an efficiency penalty of only 5%. (c) 2021 Elsevier Ltd. All rights reserved. |
2,826 | An arts-led dialogue to elicit shared, plural and cultural values of ecosystems | This paper introduces arts-led dialogue as a critical alternative to the prevailing instrumental and deliberative approaches to environmental valuation and decision-making. The dialogue, directed by an artist in collaboration with a community of participants, can comprise a single event, such as a workshop, or unfold over a period of years. Rather than seeking closure on a pre-determined problem, its intentions are typically to explore a subject or problem in original, challenging or provocative ways, which question the truth claims of any one discipline, at times with unexpected, emancipatory outcomes. We locate arts-led dialogue between deliberative and interpretive approaches to environmental decision-making, and within the history and theory of socially-engaged art, and analyse its key features: its purpose, participation, audience, format, content, and changes in values and identities through transformative learning. We illustrate these features by reporting on a creative enquiry into the shared, plural and cultural values associated with the Caledonian pinewoods of Scotland, focusing on the Black Wood of Rannoch in Highland Perthshire. The conclusions highlight two distinctive features: a commitment to critical dialogue and open exchange, and the character and experience of the artist who directs the process. |
2,827 | Digital Image Steganalysis Based on Visual Attention and Deep Reinforcement Learning | Recently, the adaptive steganography methods have been developed to embed secret information with the minimal distortion of images. As the opposite art, steganalysis methods, especially some convolutional neural network-based steganalysis methods, have been proposed to detect whether an image is embedded with secret information or not. The state-of-the-art steganography methods hide secret information in different regions of an image with different probabilities. However, most of the current steganalysis methods extract the steganalysis features from different regions without discrimination, which reduces the performance of the current deep-learning-based steganalysis methods when attacking the adaptive steganography methods. In this paper, we propose a new self-seeking steganalysis method based on visual attention and deep reinforcement learning to detect the JPEG-based adaptive steganography. First, a region is selected from the image by a visual attention method, and a continuous decision is then made to generate a summary region by reinforcement learning. Thereby, the deep learning model is guided to focus on these regions that are favorable to steganalysis and ignore those regions that are unfavorable. Finally, the quality of training set and the detection ability of steganalysis are improved by replacing the mis-classified training images with their corresponding summary regions. The experiments show that our method obtains the competitive detection accuracy, compared with the other state-of-the-art advanced detection methods. |
2,828 | Development and External Validation of a Multivariable Prediction Model to Identify Nondiabetic Hyperglycemia and Undiagnosed Type 2 Diabetes: Diabetes Risk Assessment in Dentistry Score (DDS) | The aim of this study was to develop and externally validate a score for use in dental settings to identify those at risk of undiagnosed nondiabetic hyperglycemia (NDH) or type 2 diabetes (T2D). The Studies of Health in Pomerania (SHIP) project comprises 2 representative population-based cohort studies conducted in northeast Germany. SHIP-TREND-0, 2008 to 2012 (the development data set) had 3,339 eligible participants, with 329 having undiagnosed NDH or T2D. Missing data were replaced using multiple imputation. Potential covariates were selected for inclusion in the model using backward elimination. Heuristic shrinkage was used to reduce overfitting, and the final model was adjusted for optimism. We report the full model and a simplified paper-based point-score system. External validation of the model and score employed an independent data set comprising 2,359 participants with 357 events. Predictive performance, discrimination, calibration, and clinical utility were assessed. The final model included age, sex, body mass index, smoking status, first-degree relative with diabetes, presence of a dental prosthesis, presence of mobile teeth, history of periodontal treatment, and probing pocket depths ≥5 mm as well as prespecified interaction terms. In SHIP-TREND-0, the model area under the curve (AUC) was 0.72 (95% confidence interval [CI] 0.69, 0.75), calibration in the large was -0.025. The point score AUC was 0.69 (95% CI 0.65, 0.72), with sensitivity of 77.0 (95% CI 76.8, 77.2), specificity of 51.5 (95% CI 51.4, 51.7), negative predictive value of 94.5 (95% CI 94.5, 94.6), and positive predictive value of 17.0 (95% CI 17.0, 17.1). External validation of the point score gave an AUC of 0.69 (95% CI 0.66, 0.71), sensitivity of 79.2 (95% CI 79.0, 79.4), specificity of 49.9 (95% CI 49.8, 50.00), negative predictive value 91.5 (95% CI 91.5, 91.6), and positive predictive value of 25.9 (95% CI 25.8, 26.0). A validated prediction model involving dental variables can identify NDH or undiagnosed T2DM. Further studies are required to validate the model for different European populations. |
2,829 | Optimization of the Progressive Image Mosaicing Algorithm in Fine Art Image Fusion for Virtual Reality | The fade-in and fade-out algorithm based on the Bernstein polynomial has certain limitations in image fusion. Therefore, this article proposes a new image fusion algorithm. First, the SIFT algorithm is used to register the images. Second, for the disjointed case of overlapping regions, a progressive image mosaic fusion algorithm in the form of a sine function is proposed. Finally, in order to make the progressive image mosaic fusion algorithm suitable for a variety of overlapping regions, this paper adds segmentation technology. The simulation experiment results show that the algorithm proposed in this paper is in good agreement with the spatial details and texture details of a high-resolution panchromatic image, and the time is shorter, which meets the real-time requirements. In addition, the algorithm proposed in this paper is effective in applications such as virtual reality and art image fusion. |
2,830 | The possibilities of explicit Striga (Striga asiatica) risk monitoring using phenometric, edaphic, and climatic variables, demonstrated for Malawi and Zambia | Food insecurity continues to affect more than two-thirds of the population in sub-Saharan Africa (SSA), particularly those depending on rain-fed agriculture. Striga, a parasitic weed, has caused yield losses of cereal crops, immensely affecting smallholder farmers in SSA. Although earlier studies have established that Striga is a constraint to crop production, there is little information on the spatial extent of spread and infestation severity of the weed in some SSA countries like Malawi and Zambia. This study aimed to use remotely sensed vegetation phenological (n = 11), climatic (n = 3), and soil (n = 4) variables to develop a data-driven ecological niche model to estimate Striga (Striga asiatica) spatial distribution patterns over Malawi and Zambia, respectively. Vegetation phenological variables were calculated from 250-m enhanced vegetation index (EVI) timeline data, spanning 2013 to 2016. A multicollinearity test was performed on all 18 predictor variables using the variance inflation factor (VIF) and Pearson's correlation approach. From the initial 18 variables, 12 non-correlated predictor variables were selected to predict Striga risk zones over the two focus countries. The variable "start of the season" (start of the rainy season) showed the highest model relevance, contributing 26.8% and 37.9% to Striga risk models for Malawi and Zambia, respectively. This indicates that the crop planting date influences the occurrence and the level of Striga infestation. The resultant occurrence maps revealed interesting spatial patterns; while a very high Striga occurrence was predicted for central Malawi and eastern Zambia (mono-cultural maize growing areas), lower occurrence rates were found in the northern regions. Our study shows the possibilities of integrating various ecological factors with a better spatial and temporal resolution for operational and explicit monitoring of Striga-affected areas in SSA. The explicit identification of Striga "hotspot" areas is crucial for effectively informing intervention activities on the ground. |
2,831 | Modified LMS synchronization technique for distributed energy resources with DC-offset and harmonic elimination capabilities | Grid synchronization techniques are needed to improve the distribution system's power quality with the Shunt Active Power Filter (SAPF). The traditional synchronization technique or the Phase Locked Loop (PLL) works well under ideal grid conditions; however, its performance deteriorates under non-ideal grid conditions. In this paper, a new scheme has been proposed to function as PLL. The Modified Least Mean Square (MLMS)-PLL has been proposed for tracking the phase angle under non-ideal grid conditions such as phase shift, frequency deviation, harmonics in the signal, DC offset and combinations of these grid voltage issues. The proposed method has added the advantage of DC-offset estimation and perfect synchronization template generation over conventional PLL. The MLMS-PLL algorithm precisely estimates phase, amplitude and frequency information and generates a synchronizing signal under abnormal grid conditions. The designed algorithm is extensively tested and shows advantages such as least steady-state error, faster dynamics and DC-offset rejection capability. Experimental findings of the proposed synchronizing technique show the effectiveness of the proposed technique and experimental results are also compared with other modern synchronization techniques. The application of MLMS-PLL for synchronization, reactive power compensation and harmonic elimination in a grid-tied PV system has been validated in the experimental prototype. |
2,832 | CMOS DPDT switch at 2 GHz | A double-pole double-throw (DPDT) switch has been designed to operate from DC to 2 GHz. using a 0.18-mu m CMOS process. Each branch adopts series/shunt/series-type and large resistances art added to connect the bulks of series transistors to the ground to lower the insertion loss and increase the isolation. (c) 2006 Wiley Periodicals, Inc. |
2,833 | Food insecurity reported by children, but not by mothers, is associated with lower quality of diet and shifts in foods consumed | Household food security shows little indication of nutrient inadequacy among children, according to reports made by parents. We examined the associations of food insecurity as reported by children and mothers with children's consumption of energy, macronutrients such as vitamin A, calcium, iron and zinc, and selected foods, and whether these associations differed by child's gender. This cross-sectional study had non-probabilistic 128 Venezuelan mother-child pairs. We assessed food insecurity and management strategies in children using 10- and nine-item instruments, respectively. Mothers' report of food insecurity came from a previously validated 12-item instrument. Nutrient intake of children was assessed with a 67-item food frequency questionnaire. Comparisons were made using chi-square test for contingency tables and t-tests for trends (P < 0.05). Linear regression models were used for intakes of nutrients and selected foods. We tested for interactions with gender. Prevalence of child- and mother-reported food insecurity was 83.6 and 61.7%, respectively (P < 0.01). Greater food insecurity or management strategies reported by boys was associated with lower calcium, iron and zinc intake (P < 0.05), but reported intakes were low in girls who are even food secure. Rice and corn flour consumption was higher with higher food insecurity in children. Papaya and banana were less consumed by food-insecure children. We found shifts in 13 of 67 foods consumed, with less quality in those food insecure, as reported by children. Mother-reported food insecurity was associated only with rice intake of children. In contrast to mothers' reports, food insecurity reported by children was associated with children's lower quality of diet and shifts in foods consumed. |
2,834 | Spherical Deformable U-Net: Application to Cortical Surface Parcellation and Development Prediction | Convolutional Neural Networks (CNNs) have achieved overwhelming success in learning-related problems for 2D/3D images in the Euclidean space. However, unlike in the Euclidean space, the shapes of many structures in medical imaging have an inherent spherical topology in a manifold space, e.g., the convoluted brain cortical surfaces represented by triangular meshes. There is no consistent neighborhood definition and thus no straightforward convolution/pooling operations for such cortical surface data. In this paper, leveraging the regular and hierarchical geometric structure of the resampled spherical cortical surfaces, we create the 1-ring filter on spherical cortical triangular meshes and accordingly develop convolution/pooling operations for constructing Spherical U-Net for cortical surface data. However, the regular nature of the 1-ring filter makes it inherently limited to model fixed geometric transformations. To further enhance the transformation modeling capability of Spherical U-Net, we introduce the deformable convolution and deformable pooling to cortical surface data and accordingly propose the Spherical Deformable U-Net (SDU-Net). Specifically, spherical offsets are learned to freely deform the 1-ring filter on the sphere to adaptively localize cortical structures with different sizes and shapes. We then apply the SDU-Net to two challenging and scientifically important tasks in neuroimaging: cortical surface parcellation and cortical attribute map prediction. Both applications validate the competitive performance of our approach in accuracy and computational efficiency in comparison with state-of-the-art methods. |
2,835 | L-0-Regularized Intensity and Gradient Prior for Deblurring Text Images and Beyond | We propose a simple yet effective L-0-regularized prior based on intensity and gradient for text image deblurring. The proposed image prior is based on distinctive properties of text images, with which we develop an efficient optimization algorithm to generate reliable intermediate results for kernel estimation. The proposed algorithm does not require any heuristic edge selection methods, which are critical to the state-of-the-art edge-based deblurring methods. We discuss the relationship with other edge-based deblurring methods and present how to select salient edges more principally. For the final latent image restoration step, we present an effective method to remove artifacts for better deblurred results. We show the proposed algorithm can be extended to deblur natural images with complex scenes and low illumination, as well as non-uniform deblurring. Experimental results demonstrate that the proposed algorithm performs favorably against the state-of-the-art image deblurring methods. |
2,836 | Contour detection refined by a sparse reconstruction-based discrimination method | Sparse representations have been widely used for many image processing tasks. In this paper, a sparse reconstruction-based discrimination (SRBD) method, which was previously proposed for the classification of image patches, is utilized to improve boundary detection in colour images. This method is applied to refining the results generated by three different algorithms: a biologically inspired method, and two state-of-the-art algorithms for contour detection. All of the contour detection results are evaluated by the BSDS300 and BSDS500 benchmarks using the quantitative measures: F-score, ODS, OIS and AP. Evaluation results shows that the performance of each algorithm is improved using the proposed method of refinement with at least one of the quantitative measures increased by 0.01. In particularly, even two state-of-the-art algorithms are slightly improved by applying the SRBD method to refine their contour detection results. |
2,837 | Materialization of interactive stereoscopic artwork based on hand-painted images | This paper presents interactive stereoscopic artwork and an algorithm for natural artistic expression using hand-painted images expressed by the artist's manual brush strokes. The system proposes a new interactive method that allows a viewer to experience the painting process representing the consecutive process of an actual artist's oil painting. The combination of analog and digital techniques stimulates emotions of the audience. The system architecture is composed of the Kinect sensor, which recognizes the movement of the user, a module that generates real-time stereoscopic images, and a projection module that displays the generated image. The survey is conducted to evaluate the effects of the 3D modeling method and the artistic modeling method. The statistical result show that the proposed hand-painted method provides more artistic satisfaction to the viewers than the 3D modeling method. |
2,838 | A Don't-Care-Based Approach to Reducing the Multiplicative Complexity in Logic Networks | Reducing the number of AND gates in logic networks benefits the applications in cryptography, security, and quantum computing. This work proposes a don't-care-based (DC-based) approach to reduce the number of AND gates further in the well-optimized network. Furthermore, this work also proposes an enhanced synthesis flow by integrating our approach with the state-of-the-art. The experimental results show that our approach can further reduce up to 25% of the number of AND gates in the network. For the experiments about the enhanced synthesis flow, we achieve a speedup of almost 10x on average for the cryptography benchmarks while having competitive results as compared to the flow in the state-of-the-art. |
2,839 | A Survey of Deep Learning on Mobile Devices: Applications, Optimizations, Challenges, and Research Opportunities | Deep learning (DL) has demonstrated great performance in various applications on powerful computers and servers. Recently, with the advancement of more powerful mobile devices (e.g., smartphones and touch pads), researchers are seeking DL solutions that could be deployed on mobile devices. Compared to traditional DL solutions using cloud servers, deploying DL on mobile devices have unique advantages in data privacy, communication overhead, and system cost. This article provides a comprehensive survey for the current studies of adopting and deploying DL on mobile devices. Specifically, we summarize and compare the state-of-the-art DL techniques on mobile devices in various application domains involving vision, speech/speaker recognition, human activity recognition, transportation mode detection, and security. We generalize an optimization pipeline for bringing DL to mobile devices, including model-oriented optimization mechanisms (e.g., pruning and quantization) and nonmodel-oriented optimization mechanisms (e.g., software accelerator and hardware design). Moreover, we summarize popular DL libraries regarding their support to state-of-the-art models (software) and processors (hardware). Based on our summarization, we further provide insights into potential research opportunities for developing DL for mobile devices. |
2,840 | Computing Crowd Consensus with Partial Agreement | Crowdsourcing has been widely established as a means to enable human computation at large-scale, in particular for tasks that require manual labelling of large sets of data items. Answers obtained from heterogeneous crowd workers are aggregated to obtain a robust result. However, existing methods for answer aggregation are designed for discrete tasks, where answers are given as a single label per item. In this paper, we consider partial-agreement tasks that are common in many applications such as image tagging and document annotation, where items are assigned sets of labels. Common approaches for the aggregation of partial-agreement answers either (i) reduce the problem to several instances of an aggregation problem for discrete tasks or (ii) consider each label independently. Going beyond the state-of-the-art, we propose a novel Bayesian nonparametric model to aggregate the partial-agreement answers in a generic way. This model enables us to compute the consensus of partially-sound and partially-complete worker answers, while taking into account mutual relationships in labels and different answer sets. We also show how this model is instantiated for incremental learning, incorporating new answers from crowd workers as they arrive. An evaluation of our method using real-world datasets reveals that it consistently outperforms the state-of-the-art in terms of precision, recall, and robustness against faulty workers and data sparsity. |
2,841 | A Dynamic Zoom ADC With 109-dB DR for Audio Applications | This paper presents the first dynamic zoom ADC. Intended for audio applications, it achieves 109-dB DR, 106-dB signal-to-noise ratio, and 103-dB SNDR in a 20-kHz bandwidth, while dissipating only 1.12 mW. This translates into the stateof- the-art energy efficiency as expressed by a Schreier FoM of 181.5 dB. It also achieves the state-of-the-art area efficiency, occupying only 0.16 mm(2) in the 0.16-mu m CMOS. These advances are enabled by the use of concurrent fine and coarse conversions, dynamic error-correction techniques, and a dynamically biased inverter-based operational transconductance amplifier. |
2,842 | Two Case Reports of Patients With Transverse Myelitis as a Complication of SARS-CoV-2 Infection | Transverse myelitis is a nontraumatic spinal cord injury that presents with sudden onset weakness, sensory deficits, and autonomic dysfunction. It can be caused by multiple etiologies including malignancy, autoimmune disorders, viral, bacterial, or fungal infections, and environmental factors. In this article, we describe cases of two elderly male patients affected by the SARS-CoV-2 virus. Patients did not exhibit classic or had only mild classic symptoms of SARS-CoV-2 infection; however, both patients developed transverse myelitis. Patients were treated with intravenous steroids and therapeutic plasmapheresis, achieving partial improvement. The study aimed to understand rare complications like transverse myelitis of SARS-CoV-2 infection and treatment accordingly. |
2,843 | Leveraging Auxiliary Information on Marginal Distributions in Nonignorable Models for Item and Unit Nonresponse | Often, government agencies and survey organizations know the population counts or percentages for some of the variables in a survey. These may be available from auxiliary sources, for example, administrative databases or other high quality surveys. We present and illustrate a model-based framework for leveraging such auxiliary marginal information when handling unit and item nonresponse. We show how one can use the margins to specify different missingness mechanisms for each type of nonresponse. We use the framework to impute missing values in voter turnout in a subset of data from the U.S. Current Population Survey (CPS). In doing so, we examine the sensitivity of results to different assumptions about the unit and item nonresponse. |
2,844 | Cellular type of hemangioblastoma. Case report and literature review | The authors report a patient with spinomedullary tumor who underwent resection with subsequent histological examination. However, the authors encountered difficulties in determining the exact histological type of neoplasm. Microscopic and immunohistochemical examination of spinomedullary neoplasm revealed two types of tumor: ependymoma and hemangioblastoma. However, analysis of literature data indicated that the identified tumor could be attributed to a certain cellular type of hemangioblastoma. |
2,845 | Accelerated and Concerted Aza-Michael Addition and SuFEx Reaction in Microdroplets in Unitary and High-Throughput Formats | The sulfur fluoride exchange (SuFEx) reaction is significant in drug discovery, materials science, and chemical biology. Conventionally, it involves installation of SO2 F followed by fluoride exchange by a catalyst. We report catalyst-free Aza-Michael addition to install SO2 F and then SuFEx reaction with amines, both occurring in concert, in microdroplets under ambient conditions. The microdroplet reaction is accelerated by a factor of ∼104 relative to the corresponding bulk reaction. We suggest that the superacidic microdroplet surface assists SuFEx reaction by protonating fluorine to create a good leaving group. The reaction scope was established by performing individual reactions in microdroplets of 18 amines in four solvents and confirmed using high-throughput desorption electrospray ionization experiments. The study demonstrates the value of microdroplet-assisted accelerated reactions in combination with high-throughput experimentation for characterization of reaction scope. |
2,846 | Optimum sizing of the inverter for maximizing the energy yield in state-of-the-art high-concentrator photovoltaic systems | The sizing of the inverter in comparison to the rated capacity of the photovoltaic generator is investigated for high-concentrator photovoltaic (HCPV) systems. An HCPV module of typical characteristics is modelled and parameterized, taking into account direct normal irradiance (DNI), ambient temperature, air mass and aerosol optical depth as atmospheric inputs, while the DC losses of the HCPV generator are allowed to vary in the ranges reported in the literature. A set of 80 commercial inverters are analysed to obtain the typical efficiency curves of state-of-the-art low-, medium-, and high-efficiency inverters. Four locations worldwide with high annual DNI levels and different average values of the weather variables influencing HCPV performance are studied. Results show that the inverter can be sized between 84% and 112% of the rated capacity of the HCPV generator at Concentrator Standard Test Conditions depending on the scenario considered for maximizing the final energy yield of the system. The proposed methodology uses analytical equations, all the model parameters are provided and justified and atmospheric inputs are obtained from meteorological databases in order to make the application easy regarding its use in other locations where the climate data is available. |
2,847 | Correlation-Based Tracker-Level Fusion for Robust Visual Tracking | Although visual object tracking algorithms are capable of handling various challenging scenarios individually, none of them are robust enough to handle all the challenges simultaneously. For any online tracking by detection method, the key issue lies in detecting the target over the whole frame and updating systematically a target model based on the last detected appearance to avoid the drift phenomenon. This paper aims at proposing a novel robust tracking algorithm by fusing the frame level detection strategy of tracking, learning, & detection with the systematic model update strategy of Kernelized Correlation Filter tracker. The risk of drift is mitigated by the fact that the model updates are primarily driven by the detections that occur in the spatial neighborhood of the latest detections. The motivation behind the selection of trackers is their complementary nature in handling tracking challenges. The proposed algorithm efficiently combines the two state-of-the-art tracking algorithms based on conservative correspondence measure with strategic model updates, which takes advantages of both and outperforms them on their short ends by virtue of other. Extensive evaluation of the proposed method based on different metrics is carried out on the data sets ALOV300++, Visual Tracker Benchmark, and Visual Object Tracking. We demonstrated its performance in terms of robustness and success rate by comparing with state-of-the-art trackers. |
2,848 | Tipping the balance toward stemness in trophoblast: Metabolic programming by Cox6B2 | Metabolic effector(s) driving cell fate is an emerging concept in stem cell biology. Here we showed that Cytochrome C Oxidase Subunit 6B2 (Cox6B2) is essential to maintain the stemness of trophoblast stem (TS) cells. RNA interference of Cox6b2 resulted in decreased mitochondrial Complex IV activity, ATP production, and oxygen consumption rate in TS cells. Furthermore, depletion of Cox6b2 in TS cells led to decreased self-renewal capacity indicated by compromised BrdU incorporation, Ki67 staining, and decreased expression of TS cell genetic markers. As expected, the consequence of Cox6b2 knockdown was the induction of differentiation. TS cell stemness factor CDX2 transactivates Cox6b2 promoter in TS cells. In differentiated cells, Cox6b2 is post-transcriptionally regulated by two microRNAs, miR-322-5p and miR-503-5p, leading to its downregulation as demonstrated by the gain-in or loss of function of these miRNAs. Cox6b2 transcripts gradually rise in placental trophoblast gestation progresses in both mice and rats with predominant expression in labyrinthine trophoblast. Cox6b2 expression is compromised in the growth-restricted placenta of rats with reciprocal up-regulation of miR-322-5p and miR-503-5p. These data highlight the importance of Cox6B2 in the regulation of TS cell state and uncompromised placental growth. |
2,849 | Vehicular Communication Systems: Enabling Technologies, Applications, and Future Outlook on Intelligent Transportation | Numerous technologies have been deployed to assist and manage transportation. But recent concerted efforts in academia and industry point to a paradigm shift in intelligent transportation systems. Vehicles will carry computing and communication platforms, and will have enhanced sensing capabilities. They will enable new versatile systems that enhance transportation safety and efficiency and will provide infotainment. This article surveys the state-of-the-art approaches, solutions, and technologies across a broad range of projects for vehicular communication systems. |
2,850 | Carbon nanotubes supported tyrosinase in the synthesis of lipophilic hydroxytyrosol and dihydrocaffeoyl catechols with antiviral activity against DNA and RNA viruses | Hydroxytyrosol and dihydrocaffeoyl catechols with lipophilic properties have been synthesized in high yield using tyrosinase immobilized on multi-walled carbon nanotubes by the Layer-by-Layer technique. All synthesized catechols were evaluated against a large panel of DNA and RNA viruses, including Poliovirus type 1, Echovirus type 9, Herpes simplex virus type 1 (HSV-1), Herpes simplex virus type 2 (HSV-2), Coxsackievirus type B3 (Cox B3), Adenovirus type 2 and type 5 and Cytomegalovirus (CMV). A significant antiviral activity was observed in the inhibition of HSV-1, HSV-2, Cox B3 and CMV. The mechanism of action of the most active dihydrocaffeoyl derivative was investigated against a model of HSV-1 infection. |
2,851 | Combining Individual Travel Preferences Into Destination Prediction: A Multi-Module Deep Learning Network | Accurate destination prediction over sub-trajectories is essential for a wide range of location-based services. Traditional trip matching methods fail to capture temporal dependence hidden in trajectories and may suffer from data sparsity problems. With the help of massive trajectory data, state-of-the-art approaches based on deep learning (DL) have achieved great success. However, existing DL approaches rarely consider the influence of individual travel preferences in destination prediction. When the trip is long but the known partial trajectory is short, DL models are unable to produce satisfactory results. Thus, we design a feature extraction mechanism to extract useful temporal features, spatial features, and static covariates for destination prediction, among which the spatial features characterize individual travel preferences by considering two main movement patterns in daily travel. Then, a hierarchical model including multiple modules is proposed to finely process heterogeneous features. Extensive experiments conducted on two public datasets demonstrate the superior performance of the proposed model compared to the state-of-the-art methods. Moreover, further experimental results show that the proposed model still performs well when trajectory prefix is short or travel duration is long, which confirms the effectiveness of integrating individual travel preferences. |
2,852 | Industry-Fit AI Usage for Crack Detection in Ground Steel | We investigated optimal implementation strategies for industrial inspection systems aiming to detect cracks on ground steel billets' surfaces by combining state-of-the-art AI-based methods and classical computational imaging techniques. In 2D texture images, the interesting patterns of surface irregularities are often surrounded by visual clutter, which is to be ignored, e.g., grinding patterns. Even neural networks struggle to reliably distinguish between actual surface disruptions and irrelevant background patterns. Consequently, the image acquisition procedure already has to be optimised to the specific application. In our case, we use photometric stereo (PS) imaging to generate 3D surface models of steel billets using multiple illumination units. However, we demonstrate that the neural networks, especially in high-speed scenarios, still suffer from recognition deficiencies when using raw photometric stereo camera data, and are unable to generalise to new billets and image acquisition conditions. Only the additional application of adequate state-of-the-art image processing algorithms guarantees the best results in both aspects. The neural networks benefit when appropriate image acquisition methods together with image processing algorithms emphasise relevant surface structures and reduce overall pattern variation. Our proposed combined strategy shows a 9.25% better detection rate on validation data and is 14.7% better on test data, displaying the best generalisation. |
2,853 | Vasoactive Intestinal Peptide Tumor as the Cause of Persistent Diarrhea: A Diagnostic Challenge | Although chronic diarrhea is frequent, some of its causes are rare, namely, neuroendocrine tumors (NETs). Due to their rarity and non-specific symptoms, such as diarrhea, they are often underdiagnosed. An 80-year-old woman presented to the emergency department due to emesis and watery diarrhea. Blood tests showed acute kidney injury, hypokalemia, and metabolic acidosis. An abdominal computed tomography revealed a 51 mm pancreatic lesion. An endoscopic ultrasound-guided biopsy raised the hypothesis of a NET. The patient refused surgery and was lost to follow-up. At the eighth hospitalization, 11 months later, the suspicion of a vasoactive intestinal peptide tumor (VIPoma) was raised and confirmed by assessing the vasoactive intestinal peptide (VIP) levels (>100 pmol/L). Octreotide was started with the resolution of the symptoms. 68Ga-DOTANOC positron emission tomography/computed tomography excluded metastatic disease. After six months of octreotide therapy, the tumor shrunk 13 mm in maximum diameter. At the last follow-up, one year later, she remained asymptomatic. The delayed diagnosis of VIPoma led to multiple life-threatening episodes. This case highlights the importance of considering all potential differential diagnoses of common symptoms such as diarrhea. Although VIPomas are rare, clinicians should be aware of this entity and suspect this diagnosis in patients with chronic diarrhea with a poor response to standard antidiarrheal agents. Somatostatin analogs should be promptly prescribed for symptom control and tumor progression prevention in patients who refuse surgery or have unresectable tumors. Tumor shrinkage might also be observed in these cases. |
2,854 | The relationship between past exercise behavior and future exercise adherence: A sequential mediation analysis | The present study explored the mediation role of past exercise adherence, self-reported frequency and intentions in the association between past experience and future exercise adherence. In total, 431 exercisers (female = 216; male = 215) aged 18 and 64 years, engaged in fitness activities such as group fitness classes and resistance training, were included in the analysis. Serial mediation procedures were employed to examine the direct, indirect, and total indirect effects among variables. The predictor variable and all mediators displayed a positive and significant association with future six-month adherence. Past six-month exercise adherence displayed the most significant association with future six-month adherence. The sequential indirect path from exercise experience → past six-months adherence → self-reported frequency → intentions future six-months adherence displayed a positive and significant effect (β = .19 [CI95% = .09, .31]), presenting a partial mediation effect. Past behaviour is the most significant predictor of future adherence, and thus interventions should be based on promoting consistent exercise frequency. Professionals working in the fitness centre context can identify possible dropouts based on their past behaviour and intentions to be physically active in the future. |
2,855 | Minimum phase finite impulse response filter design | The design of minimum phase finite impulse response (FIR) filters is considered. The study demonstrates that the residual errors achieved by current state-of-the-art design methods are nowhere near the smallest error possible on a finite resolution digital computer. This is shown to be due to conceptual errors in the literature pertaining to what constitutes a factorable linear phase filter. This study shows that factorisation is possible with a zero residual error (in the absence of machine finite resolution error) if the linear operator or matrix representing the linear phase filter is positive definite. Methodology is proposed able to design a minimum phase filter that is optimal-in the sense that the residual error is limited only by the finite precision of the digital computer, with no systematic error. The study presents practical application of the proposed methodology by designing two minimum phase Chebyshev FIR filters. Results are compared to state-of-the-art methods from the literature, and it is shown that the proposed methodology is able to reduce currently achievable residual errors by several orders of magnitude. |
2,856 | ARID1A, BRG1, and INI1 deficiency in undifferentiated and dedifferentiated endometrial carcinoma: a clinicopathologic, immunohistochemical, and next-generation sequencing analysis of a case series from a single institution | Undifferentiated/dedifferentiated endometrial carcinomas (UDEC and DDEC) are rare, aggressive uterine neoplasms, with no specific line of differentiation. A significant proportion of these cases feature mutations of SWI/SNF chromatin remodeling complex members, including ARID1A, SMARCA4, and SMARCB1 genes. To study these entities more comprehensively, we identified 10 UDECs and 10 DDECs from our pathology archives, obtained clinicopathologic findings and follow-up data, and performed immunohistochemical studies for ARID1A, BRG1 (SMARCA4), and INI1 (SMARCB1) proteins. In addition, we successfully conducted targeted next-generation sequencing for 23 samples, including 7 UDECs, and 7 undifferentiated and 9 well/moderately-differentiated components of DDECs. Cases consisted of 18 hysterectomies and 2 curettage/biopsy specimens. Patient age ranged from 47 to 77 years (median, 59 years), with a median tumor size of 8.0 cm (range, 2.5-13.0 cm). All cases demonstrated lymphovascular invasion and the majority (13/20) were FIGO stage III-IV. By immunohistochemistry, ARID1A loss was observed in 15 cases, BRG1 loss in 4, and all cases had intact INI1 expression. A trend for enrichment of the undifferentiated component of DDECs for ARID1A loss was seen, although not statistically significant. Sequencing revealed frequent pathogenic mutations in PTEN, PIK3CA, ARID1A, CTNNB1, and RNF43, a recurrent MAX pathogenic mutation, and MYC and 12p copy number gains. In DDECs, the undifferentiated component featured a higher tumor mutational burden compared to the well/moderately-differentiated component; however, the mutational landscape largely overlapped. Overall, our study provides deep insights into the mutational landscape of UDEC/DDEC, SWI/SNF chromatin remodeling complex member status, and their potential relationships with tumor features. |
2,857 | Compensatory Genetic and Transcriptional Cytonuclear Coordination in Allopolyploid Lager Yeast (Saccharomyces pastorianus) | Cytonuclear coordination between biparental-nuclear genomes and uniparental-cytoplasmic organellar genomes in plants is often resolved by genetic and transcriptional cytonuclear responses. Whether this mechanism also acts in allopolyploid members of other kingdoms is not clear. Additionally, cytonuclear coordination of interleaved allopolyploid cells/individuals within the same population is underexplored. The yeast Saccharomyces pastorianus provides the opportunity to explore cytonuclear coevolution during different growth stages and from novel dimensions. Using S. pastorianus cells from multiple growth stages in the same environment, we show that nuclear mitochondria-targeted genes have undergone both asymmetric gene conversion and growth stage-specific biased expression favoring genes from the mitochondrial genome donor (Saccharomyces eubayanus). Our results suggest that cytonuclear coordination in allopolyploid lager yeast species entails an orchestrated and compensatory genetic and transcriptional evolutionary regulatory shift. The common as well as unique properties of cytonuclear coordination underlying allopolyploidy between unicellular yeasts and higher plants offers novel insights into mechanisms of cytonuclear evolution associated with allopolyploid speciation. |
2,858 | Endoscopic Medial Orbitotomy for Lateral Access to Anterior Cranial Base Pathology | This article showcases a technique to further expand the endoscopic endonasal approach to the skull base by traversing the orbit for further lateral exposure. Laryngoscope, 133:1336-1338, 2023. |
2,859 | Coastal Waste Detection Based on Deep Convolutional Neural Networks | Coastal waste not only has a seriously destructive effect on human life and marine ecosystems, but it also poses a long-term economic and environmental threat. To solve the issues of a poor manual coastal waste sorting environment, such as low sorting efficiency and heavy tasks, we develop a novel deep convolutional neural network by combining several strategies to realize intelligent waste recognition and classification based on the state-of-the-art Faster R-CNN framework. Firstly, to effectively detect small objects, we consider multiple-scale fusion to get rich semantic information from the shallower feature map. Secondly, RoI Align is introduced to solve positioning deviation caused by the regions of interest pooling. Moreover, it is necessary to correct key parameters and take on data augmentation to improve model performance. Besides, we create a new waste object dataset, named IST-Waste, which is made publicly to facilitate future research in this field. As a consequence, the experiment shows that the algorithm's mAP reaches 83%. Detection performance is significantly better than Faster R-CNN and SSD. Thus, the developed scheme achieves higher accuracy and better performance against the state-of-the-art alternative. |
2,860 | Error Bounded Foreground and Background Modeling for Moving Object Detection in Satellite Videos | Detecting moving objects from ground-based videos is commonly achieved by using background subtraction (BS) techniques. Low-rank matrix decomposition inspires a set of state-of-the-art approaches for this task. It is integrated with structured sparsity regularization to achieve BS in the developed method of low-rank and structured sparse decomposition (LSD). However, when this method is applied to satellite videos where spatial resolution is poor and targets' contrast to the background is low, its performance is limited as the data no longer fit adequately either the foreground structure or the background model. In this article, we handle these unexplained data explicitly and address the moving target detection from space as one of the pioneering studies. We propose a new technique by extending the decomposition formulation with bounded errors, named Extended LSD (E-LSD). This formulation integrates low-rank background, structured sparse foreground, as well as their residuals in a matrix decomposition problem. Solving this optimization problem is challenging. We provide an effective solution by introducing an alternative treatment and adopting the direct extension of alternating direction method of multipliers (ADMM). The proposed E-LSD was validated on two satellite videos, and the experimental results demonstrate the improvement in background modeling with boosted moving object detection precision over state-of-the-art methods. |
2,861 | Conditional Deletion of KOR (Oprk1) in Kisspeptin Cells Does Not Alter LH Pulses, Puberty, or Fertility in Mice | Classic pharmacological studies suggested that endogenous dynorphin-KOR signaling is important for reproductive neuroendocrine regulation. With the seminal discovery of an interconnected network of hypothalamic arcuate neurons co-expressing kisspeptin, neurokinin B, and dynorphin (KNDy neurons), the KNDy hypothesis was developed to explain how gonadotropin-releasing hormone (GnRH) and luteinizing hormone (LH) pulses are generated. Key to this hypothesis is dynorphin released from KNDy neurons acting in a paracrine manner on other KNDy neurons via kappa opioid receptor (KOR) signaling to terminate neural "pulse" events. While in vitro evidence supports this aspect of the KNDy hypothesis, a direct in vivo test of the necessity of KOR signaling in kisspeptin neurons for proper LH secretion has been lacking. We therefore conditionally knocked out KOR selectively from kisspeptin neurons of male and female mice and tested numerous reproductive measures, including in vivo LH pulse secretion. Surprisingly, despite validating successful knockout of KOR in kisspeptin neurons, we found no significant effect of kisspeptin cell-specific deletion of KOR on any measure of puberty, LH pulse parameters, LH surges, follicle-stimulating hormone (FSH) levels, estrous cycles, or fertility. These outcomes suggest that the KNDy hypothesis, while sufficient normally, may not be the only neural mechanism for sculpting GnRH and LH pulses, supported by recent findings in humans and mice. Thus, besides normally acting via KOR in KNDy neurons, endogenous dynorphin and other opioids may, under some conditions, regulate LH and FSH secretion via KOR in non-kisspeptin cells or perhaps via non-KOR pathways. The current models for GnRH and LH pulse generation should be expanded to consider such alternate mechanisms. |
2,862 | Developing ecotourism sustainability maximization (ESM) model: a safe minimum standard for climate change mitigation in the Indian Himalayas | Recently, ecotourism has been identified as an adaptation strategy for mitigating climate change impacts, as it can optimize carbon sequestration, biodiversity recovery, and livelihood benefits and generate new opportunities for the sustenance of the economy, environment, and society of the area endowed with natural resources and cultural values. With the growing responsibility at the global level, ecotourism resource management (ERM) becomes inevitable for its sustainable requirements. The integration of ecological and socio-economic factors is vital for ERM, as has been demonstrated by developing an Ecotourism Sustainability Maximization Model for an area under study, that is the Yuksam-Dzongri corridor (also known as Kangchendzonga Base Camp Trek), in the Khangchendzonga Biosphere Reserve (KBR), Sikkim, India. This model is based on the earlier developed ecotourism sustainability assessment (ESA) framework by the authors, which is based on the hierarchical relationship among ecotourism principles, criteria, indicators, and verifiers. Employing such relationships, this paper attempts to maximize ecotourism sustainability (ES) as a function of its sustainability principles, criteria, indicators, and verifiers, subject to the constraints identified through the safe minimum standard (SMS) approach by employing linear programming. Using 58 indicators as decision variables and 114 constraints, the model resulted in a maximum level of achievable ES with a score of 84.6%, allowing the resultant optimum values of the indicators to be maintained at the operational level. A central tenet of the model is the collective responsibility and adoption of a holistic approach involving the government, tourists, tourism enterprises, and local people. |
2,863 | Multi-fusion feature pyramid for real-time hand detection | Real-time HI (Human Interface) systems need accurate and efficient hand detection models to meet the limited resources in budget, dimension, memory, computing, and electric power. The detection task is also important for other applications such as homecare systems, fine-grained action recognition, movie interpretation, and even for understanding dance gestures. In recent years, object detection has become a less challenging task with the latest deep CNN-based state-of-the-art models, i.e., RCNN, SSD, and YOLO. However, these models cannot achieve desired efficiency and accuracy on HI-based embedded devices due to their complex time-consuming architecture. Another critical issue in hand detection is that small hands (<30 x 30 pixels) are still challenging for all the above methods. We proposed a shallow model named Multi-fusion Feature Pyramid for real-time hand detection to deal with the above problems. Experimental results on the Oxford hand dataset combined with the skin dataset show that the proposed method outperforms other SoTA methods in terms of accuracy, efficiency, and real-time speed. The COCO dataset is also used to compare with other state-of-the-art method and shows the highest efficiency and accuracy with the proposed CFPN model. Thus we conclude that the proposed model is useful for real-life small hand detection on embedded devices. |
2,864 | A 30 Gb/s/Link 2.2 Tb/s/mm(2) Inductively-Coupled Injection-Locking CDR for High-Speed DRAM Interface | This paper presents a 30 Gb/s/link 2.2 Tb/s/mm(2) inductive-coupling link for a high-speed DRAM interface. The data rate per layout area is the highest among DRAM interfaces reported up to now. The proposed interface employs a high-speed injection-locking CDR technique that utilizes the derivative property of inductive coupling. Compared to conventional injection-locking CDR based on an XOR edge detector, the proposed technique doubles the operation speed and increases the data rate to 30 Gb/s/link. As a result, the data rate per layout area is increased to 2.2 Tb/s/mm(2), which is 2X that of the state-of-the-art inductive-coupling link, and 22X that of the state-of-the-art wired link. |
2,865 | CRY2 gene of rice (Oryza sativa subsp. indica) encodes a blue light sensory receptor involved in regulating flowering, plant height and partial photomorphogenesis in dark | OsiCRY2 is involved in light-regulated plant development and plays a role in regulating photomorphogenesis, plant height, flowering and most strikingly partial photomorphogenesis in dark. Cryptochrome 2 (CRY2), the blue/UV-A light photoreceptor in plants, has been reported to regulate photoperiod-dependent flowering and seedling photomorphogenesis (under low-intensity light). Among monocots, CRY2 has been reported from japonica rice, wheat, sorghum and barley. The two sub-species of rice, indica and japonica, exhibit a high degree of genetic variation and morphological and physiological differences. This article describes the characterization of CRY2 of indica rice (OsiCRY2). While the transcript levels of OsiCRY2 did not change significantly under blue light, its protein levels were found to decline with increased time duration under blue light. For phenotypic characterization, OsiCRY2 over-expression (OX) transgenics were generated in Oryza sativa Pusa Sugandh 2 (PS2) cultivar, a highly scented Basmati cultivar. The OsiCRY2OX transgenics displayed shorter coleoptiles and dwarfism than wild-type under blue light, white, and far-red light. Interestingly, even the dark-grown transgenics were shorter, concomitant with higher OsiCRY2 protein levels in transgenics than wild-type. Histological analysis revealed that the decrease in the length of the seedlings was due to a decrease in the length of the epidermal cells. The fully mature rice transgenics were shorter than the untransformed plants but flowered at the same time as wild-type. However, the OsiCRY2 Arabidopsis over-expressors exhibited early flowering by 10-15 days, indicating the potential and conservation of function of OsiCRY2. The whole-genome transcriptome profiling of rice transgenics revealed the differential up-regulation of several light-regulated genes in dark-grown coleoptiles. These data provide evidence that OsiCRY2 regulates photomorphogenesis, plant height, and flowering in indica rice. |
2,866 | Treatment of copper nanoparticles (CuNPs) for two spermatogenic cycles impairs testicular activity via down-regulating steroid receptors and inhibition of germ cell proliferation in a mice model | Although copper is an indispensable trace metal for biological functions, its excess exposure causes hazardous effects on health. Copper in the form of nanoparticles (CuNPs) is widely used at present and therefore, the living organism is at continuous risk of its adverse effect. The prolonged treatment of CuNPs has not been evaluated yet on the male reproductive system. To demonstrate the combined adverse effects and the mechanism of copper nanoparticles (CuNPs), three doses of CuNPs, 10, 100 and 200 mg/kg were orally given to mice for 70 days. The present study demonstrated that CuNPs decreased the sperm quality parameters, male circulating hormones, induces testicular damages, increased oxidative stress, apoptosis, decreases antioxidant enzymes, germ cell proliferation, and increases the expression of 8-oxoguanine DNA glycosylase-1 (OGG1), apelin receptor (APJ) as well. CuNPs also down-regulated the expression of AR and Erα in the testis. These results suggest that CuNPs manifested their adverse effect on testis via modulating steroid and cytokine (apelin) receptors. The adverse effect of testis was most pronounced at the highest dose (200 mg/kg) of CuNPs, however, other doses show a less toxic effect on various parameters. In conclusion, results indicated that CuNPs may impair spermatogenesis via oxidative stress-mediated DNA damage and germ cell apoptosis at high doses. |
2,867 | Zero-point attracting projection algorithm for sequential compressive sensing | Sequential Compressive Sensing, which may be widely used in sensing devices, is a popular topic of recent research. This paper proposes an online recovery algorithm for sparse approximation of sequential compressive sensing. Several techniques including warm start, fast iteration, and variable step size are adopted in the proposed algorithm to improve its online performance. Finally, numerical simulations demonstrate its better performance than the relative art. |
2,868 | Cross-Database Micro-Expression Recognition: A Benchmark | Cross-database micro-expression recognition (CDMER) is one of recently emerging and interesting problem in micro-expression analysis. CDMER is more challenging than the conventional micro-expression recognition (MER), because the training and testing samples in CDMER come from different micro-expression databases, resulting in inconsistency of the feature distributions between the training and testing sets. In this paper, we contribute to this topic from three aspects. First, we establish a CDMER experimental evaluation protocol aiming to allow the researchers to conveniently work on this topic and evaluate their proposed methods under the same standard. Second, we conduct benchmark experiments by using NINE state-of-the-art domain adaptation (DA) methods and SIX popular spatiotemporal descriptors for investigating CDMER problem from two different perspectives. Third, we propose a novel DA method called region selective transfer regression (RSTR) to deal with the CDMER task. The overall superior performance of RSTR over the state-of-the-art DA methods demonstrates that taking into consideration the facial local region information used in RSTR contributes to developing effective DA methods for dealing with CDMER problem. |
2,869 | Coronary computed tomography angiography-based endothelial wall shear stress in normal coronary arteries | Endothelial wall shear stress (ESS) is a biomechanical force which plays a role in the formation and evolution of atherosclerotic lesions. The purpose of this study is to evaluate coronary computed tomography angiography (CCTA)-based ESS in coronary arteries without atherosclerosis, and to assess factors affecting ESS values. CCTA images from patients with suspected coronary artery disease were analyzed to identify coronary arteries without atherosclerosis. Minimal and maximal ESS values were calculated for 3-mm segments. Factors potentially affecting ESS values were examined, including sex, lumen diameter and distance from the ostium. Segments were categorized according to lumen diameter tertiles into small (< 2.6 mm), intermediate (2.6-3.2 mm) or large (≥ 3.2 mm) segments. A total of 349 normal vessels from 168 patients (mean age 59 ± 9 years, 39% men) were included. ESS was highest in the left anterior descending artery compared to the left circumflex artery and right coronary artery (minimal ESS 2.3 Pa vs. 1.9 Pa vs. 1.6 Pa, p < 0.001 and maximal ESS 3.7 Pa vs. 3.0 Pa vs. 2.5 Pa, p < 0.001). Men had lower ESS values than women, also after adjusting for lumen diameter (p < 0.001). ESS values were highest in small segments compared to intermediate or large segments (minimal ESS 3.8 Pa vs. 1.7 Pa vs. 1.2 Pa, p < 0.001 and maximal ESS 6.0 Pa vs. 2.6 Pa vs. 2.0 Pa, p < 0.001). A weak to strong correlation was found between ESS and distance from the ostium (ρ = 0.22-0.62, p < 0.001). CCTA-based ESS values increase rapidly and become widely scattered with decreasing lumen diameter. This needs to be taken into account when assessing the added value of ESS beyond lumen diameter in highly stenotic lesions. |
2,870 | Blocking postsynaptic density-93 binding to C-X3-C motif chemokine ligand 1 promotes microglial phenotypic transformation during acute ischemic stroke | We previously reported that postsynaptic density-93 mediates neuron-microglia crosstalk by interacting with amino acids 357-395 of C X3 C motif chemokine ligand 1 (CX3CL1) to induce microglia polarization. More importantly, the peptide Tat-CX3CL1 (comprising amino acids 357-395 of CX3CL1) disrupts the interaction between postsynaptic density-93 and CX3CL1, reducing neurological impairment and exerting a protective effect in the context of acute ischemic stroke. However, the mechanism underlying these effects remains unclear. In the current study, we found that the pro-inflammatory M1 phenotype increased and the anti-inflammatory M2 phenotype decreased at different time points. The M1 phenotype increased at 6 hours after stroke and peaked at 24 hours after perfusion, whereas the M2 phenotype decreased at 6 and 24 hours following reperfusion. We found that the peptide Tat-CX3CL1 (357-395aa) facilitates microglial polarization from M1 to M2 by reducing the production of soluble CX3CL1. Furthermore, the a disintegrin and metalloprotease domain 17 (ADAM17) inhibitor GW280264x, which inhibits metalloprotease activity and prevents CX3CL1 from being sheared into its soluble form, facilitated microglial polarization from M1 to M2 by inhibiting soluble CX3CL1 formation. Additionally, Tat-CX3CL1 (357-395aa) attenuated long-term cognitive deficits and improved white matter integrity as determined by the Morris water maze test at 31-34 days following surgery and immunofluorescence staining at 35 days after stroke, respectively. In conclusion, Tat-CX3CL1 (357-395aa) facilitates functional recovery after ischemic stroke by promoting microglial polarization from M1 to M2. Therefore, the Tat-CX3CL1 (357-395aa) is a potential therapeutic agent for ischemic stroke. |
2,871 | Single-Track Vehicle Dynamics Control: State of the Art and Perspective | The reduction of hardware costs and the availability of smaller, lighter electromechanical actuators have led to the development of numerous control systems for powered two wheelers (PTW). Although the community working on PTW dynamics control is smaller than the community addressing automotive control, a considerable number of contributions are available. This paper presents a review on the control of PTW, and anticipates future research and industrial trends. This paper proposes a reasoned classification of different approaches based on the controlled vehicle dynamics, separating between control systems dealing with the in-plane and out-of-plane dynamics and then presents an analysis of the state-of-the-art of each control problem. A section is then devoted to the control of narrow track tilting vehicles that share many features with PTW. |
2,872 | Understanding the salinity stress on plant and developing sustainable management strategies mediated salt-tolerant plant growth-promoting rhizobacteria and CRISPR/Cas9 | Soil salinity is a worldwide concern that decreases plant growth performance in agricultural fields and contributes to food scarcity. Salt stressors have adverse impacts on the plant's ionic, osmotic, and oxidative balance, as well as numerous physiological functions. Plants have a variety of coping strategies to deal with salt stress, including osmosensing, osmoregulation, ion-homeostasis, increased antioxidant synthesis, and so on. Not only does salt stress cause oxidative stress but also many types of stress do as well, thus plants have an effective antioxidant system to battle the negative effects of excessive reactive oxygen species produced as a result of stress. Rising salinity in the agricultural field affects crop productivity and plant development considerably; nevertheless, plants have a well-known copying mechanism that shields them from salt stress by facilitated production of secondary metabolites, antioxidants, ionhomeostasis, ABAbiosynthesis, and so on. To address this problem, various environment-friendly solutions such as salt-tolerant plant growth-promoting rhizobacteria, eco-friendly additives, and foliar applications of osmoprotectants/antioxidants are urgently needed. CRISPR/Cas9, a new genetic scissor, has recently been discovered to be an efficient approach for reducing salt stress in plants growing in saline soil. Understanding the processes underlying these physiological and biochemical responses to salt stress might lead to more effective crop yield control measures in the future. In order to address this information, the current review discusses recent advances in plant stress mechanisms against salinity stress-mediated antioxidant systems, as well as the development of appropriate long-term strategies for plant growth mediated by CRISPR/Cas9 techniques under salinity stress. |
2,873 | Cross clamping of the supraceliac aorta is effective for bleeding control in ruptured giant splenic artery pseudoaneurysm when proximal and distal control of the splenic artery is not possible: a case report | Splenic artery pseudoaneurysm is the most common of all the visceral artery pseudoaneurysms. Presentation is often variable and the condition demands immediate diagnosis and management because pseudoaneurysm rupture increases morbidity and mortality. It is associated with pancreatitis and other conditions like abdominal trauma, chronic pancreatitis, pseudocyst of the pancreas, liver transplantation, and, rarely, peptic ulcer disease. We present a case of a giant splenic artery pseudoaneurysm measuring 14x8 cm. Proximal and distal control of the vessels could not be achieved during the procedure because of local adhesions and inflammation and it was necessary to cross clamp the supraceliac aorta to control bleeding. |
2,874 | Hyperspectral Multispectral Image Fusion via Fast Matrix Truncated Singular Value Decomposition | Recently, methods for obtaining a high spatial resolution hyperspectral image (HR-HSI) by fusing a low spatial resolution hyperspectral image (LR-HSI) and high spatial resolution multispectral image (HR-MSI) have become increasingly popular. However, most fusion methods require knowing the point spread function (PSF) or the spectral response function (SRF) in advance, which are uncertain and thus limit the practicability of these fusion methods. To solve this problem, we propose a fast fusion method based on the matrix truncated singular value decomposition (FTMSVD) without using the SRF, in which our first finding about the similarity between the HR-HSI and HR-MSI is utilized after matrix truncated singular value decomposition (TMSVD). We tested the FTMSVD method on two simulated data sets, Pavia University and CAVE, and a real data set wherein the remote sensing images are generated by two different spectral cameras, Sentinel 2 and Hyperion. The advantages of FTMSVD method are demonstrated by the experimental results for all data sets. Compared with the state-of-the-art non-blind methods, our proposed method can achieve more effective fusion results while reducing the fusing time to less than 1% of such methods; moreover, our proposed method can improve the PSNR value by up to 16 dB compared with the state-of-the-art blind methods. |
2,875 | Deep Neural Network for Respiratory Sound Classification in Wearable Devices Enabled by Patient Specific Model Tuning | The primary objective of this paper is to build classification models and strategies to identify breathing sound anomalies (wheeze, crackle) for automated diagnosis of respiratory and pulmonary diseases. In this work we propose a deep CNN-RNN model that classifies respiratory sounds based on Mel-spectrograms. We also implement a patient specific model tuning strategy that first screens respiratory patients and then builds patient specific classification models using limited patient data for reliable anomaly detection. Moreover, we devise a local log quantization strategy for model weights to reduce the memory footprint for deployment in memory constrained systems such as wearable devices. The proposed hybrid CNN-RNN model achieves a score of 66.31% on four-class classification of breathing cycles for ICBHI'17 scientific challenge respiratory sound database. When the model is re-trained with patient specific data, it produces a score of 71.81% for leave-one-out validation. The proposed weight quantization technique achieves approximate to 4x reduction in total memory cost without loss of performance. The main contribution of the paper is as follows: Firstly, the proposed model is able to achieve state of the art score on the ICBHI'17 dataset. Secondly, deep learning models are shown to successfully learn domain specific knowledge when pre-trained with breathing data and produce significantly superior performance compared to generalized models. Finally, local log quantization of trained weights is shown to be able to reduce the memory requirement significantly. This type of patient-specific re-training strategy can be very useful in developing reliable long-term automated patient monitoring systems particularly in wearable healthcare solutions. |
2,876 | Noise Reduction in Small-Animal PET Images Using a Multiresolution Transform | In this paper, we address the problem of denoising reconstructed small animal positron emission tomography (PET) images, based on a multiresolution approach which can be implemented with any transform such as contourlet, shearlet, curvelet, and wavelet. The PET images are analyzed and processed in the transform domain by modeling each subband as a set of different regions separated by boundaries. Homogeneous and heterogeneous regions are considered. Each region is independently processed using different filters: a linear estimator for homogeneous regions and a surface polynomial estimator for the heterogeneous region. The boundaries between the different regions are estimated using a modified edge focusing filter. The proposed approach was validated by a series of experiments. Our method achieved an overall reduction of up to 26% in the % STD of the reconstructed image of a small animal NEMA phantom. Additionally, a test on a simulated lesion showed that our method yields better contrast preservation than other state-of-the art techniques used for noise reduction. Thus, the proposed method provides a significant reduction of noise while at the same time preserving contrast and important structures such as lesions. |
2,877 | Double MAC on a DSP: Boosting the Performance of Convolutional Neural Networks on FPGAs | Deep learning workloads, such as convolutional neural networks (CNNs) are important due to increasingly demanding high-performance hardware acceleration. One distinguishing feature of a deep learning workload is that it is inherently resilient to small numerical errors and thus works very well with low precision hardware. We propose a novel method called double multiply-and-accumulate (MAC) to theoretically double the computation rate of CNN accelerators by packing two MAC operations into one digital signal processing block of off-the-shelf field-programmable gate arrays (FPGAs). We overcame several technical challenges by exploiting the mode of operation in the CNN accelerator. We have validated our method through FPGA synthesis and Verilog simulation, and evaluated our method by applying it to the state-of-the-art CNN accelerator. The double MAC approach used can double the computation throughput of a CNN layer. On the network level (all convolution layers combined), the performance improvement varies depending on the CNN application and FPGA size, from 14% to more than 80% over a highly optimized state-of-the-art accelerator solution, without sacrificing the output quality significantly. |
2,878 | Mapping Large LSTMs to FPGAs with Weight Reuse | Long-Short Term Memory (LSTM) can retain memory and learn from data sequences. It gives state-of-the-art accuracy in many applications such as speech recognition, natural language processing and video classifications. Field-Programmable Gate Arrays (FPGAs) have been used to speed up the inference of LSTMs, but FPGA-based LSTM accelerators are limited by the size of on-chip memory and the bandwidth of external memory on FPGA boards. We propose a novel hardware architecture to overcome data dependency and a new blocking-batching strategy to reuse the LSTM weights fetched from external memory to optimize the performance of systems with size-limited on-chip memory for large machine learning models. Evaluation results show that our architecture can achieve 20.8 GOPS/W, which is among the highest for the FPGA-based LSTM designs storing weights in off-chip memory. Our design achieves 1.65 times higher performance-per-watt efficiency and 2.48 times higher performance-per-DSP efficiency when compared with the current state-of-the-art designs of LSTM using weights stored in off-chip memory. Compared with CPU and GPU implementations, our FPGA implementation is 23.7 and 1.3 times faster while consuming 208 and 19.2 times lower energy respectively, which shows that our approach enables large LSTM systems to be processed efficiently on FPGAs with high performance and low power consumption. |
2,879 | Semi-Supervised Unmixing of Hyperspectral Data via Spectral-Spatial Factorization | Due to the limited spatial resolution of hyperspectral sensors, each pixel in hyperspectral image often consists of several components, called endmembers. Hyperspectral unmixing aims at extracting these endmembers and corresponding fractional abundances from the hyperspectral image (HSI) data. With the availability of spectral libraries, semi-supervised unmixing which estimates the abundance from given endmember matrix, have become more and more popular. General semi-supervised methods take advantage of the sparsity constraint on the abundance matrix and consider the pixels as independent trials. However, the spatial information for example the correlation between pixels often cannot be taken into consideration. In this paper, we derive a semi-supervised hyperspectral image unmixing algorithm which handles both spectral and spatial prior efficiently using matrix factorization. The abundance matrix is recast as a multiplication of two variables, in which the spectral and spatial priors are captured respectively. Numerical tests in both simulated and real datasets show that compared to state-of-the-art unmixing algorithms, the proposed spectral-spatial factorization method has lower computation cost, better unmixing results, and is more robust to regularization parameter selection. |
2,880 | Modern Details in Meaningful Architecture | Architecture is the art of shaping space, system, and technology. A close relationship is established between the building and its user, as the facility provides shelter and communicates with the inhabitants by meanings encoded in the form. The reception of architecture occurs through an ideological narrative and the quality of construction and material solutions. Contemporary pro-environmental postulates exert an increasingly clear influence on how architecture is shaped, especially on its aesthetic and semantic solutions. In this context, the article refers to the interdependence between art and technology in shaping the architecture of meanings through detail. The work aims to expand qualitative research on shaping contemporary detail in the context of pro-environmental trends in architecture. The detail was selected based on its clear message-its meaning provides the leading feature of the structure, both in technical (engineering solutions) and semantic (narrative) terms. The article provides an attempt to answer the question of how a semantic detail should be shaped, with the account to contemporary concepts on sustainable development architecture. A synthetic-comparative methodology was adopted; specific groups of completed objects were analyzed in the context of the indicated topics. The conclusions from this part of the work constitute case study guidelines, which was conducted on the example of an original project. |
2,881 | Contrast-Attentive Thoracic Disease Recognition With Dual-Weighting Graph Reasoning | Automatic thoracic disease diagnosis is a rising research topic in the medical imaging community, with many potential applications. However, the inconsistent appearances and high complexities of various lesions in chest X-rays currently hinder the development of a reliable and robust intelligent diagnosis system. Attending to the high-probability abnormal regions and exploiting the priori of a related knowledge graph offers one promising route to addressing these issues. As such, in this paper, we propose two contrastive abnormal attention models and a dual-weighting graph convolution to improve the performance of thoracic multi-disease recognition. First, a left-right lung contrastive network is designed to learn intra-attentive abnormal features to better identify the most common thoracic diseases, whose lesions rarely appear in both sides symmetrically. Moreover, an inter-contrastive abnormal attention model aims to compare the query scan with multiple anchor scans without lesions to compute the abnormal attention map. Once the intra- and inter-contrastive attentions are weighted over the features, in addition to the basic visual spatial convolution, a chest radiology graph is constructed for dual-weighting graph reasoning. Extensive experiments on the public NIH ChestX-ray and CheXpert datasets show that our model achieves consistent improvements over the state-of-the-art methods both on thoracic disease identification and localization. |
2,882 | Trastuzumab-based near-infrared photoimmunotherapy in xenograft mouse of breast cancer | Near-infrared photoimmunotherapy (NIR-PIT) is a novel form of cancer treatment using conjugates of antibody against overexpressed antigens in cancers and photoabsorber IRDye700DX. HER2 is overexpressed in various cancers, for which molecular targeted therapy such as trastuzumab has been developed. The present study investigated the efficacy potential of HER2-targeted NIR-PIT using trastuzumab-IRDye700DX conjugate (Tra-IR700) in HER2-positive breast cancer. We first examined the reactivity of Tra-IR700 and the cytotoxicity of NIR-PIT in vitro. HER2-positive BT-474 and SK-BR-3 cells and HER2-negative BT-20 cells were used. Tra-IR700 fluorescence was only observed in HER2-positive breast cancer cell lines, and the fluorescence was localized to the cell surface. Furthermore, HER2-positive breast cancer cell lines treated with NIR-PIT showed swelling and blebbing shortly after irradiation, and eventually increased PI-positive dead cells. Next, tumor accumulation of Tra-IR700 and tumor damage by NIR-PIT were examined in vivo. Tra-IR700 was administered intravenously to a xenograft model in which BT-474 cells were implanted subcutaneously in BALB/c nude mice. Tra-IR700 fluorescence was the highest in tumor tissue 1 day after administration, and the fluorescence was localized to the cell membrane of tumor cells. At this time point, NIR-PIT resulted in diffuse necrosis of tumor tissues 1 day after irradiation. These results suggest that NIR-PIT with Tra-IR700 induces a highly selective therapeutic effect in a HER2-positive breast cancer model. NIR-PIT using Tra-IR700 is expected to be a novel treatment for HER2-positive cancers, including breast cancer. |
2,883 | Improving Detection Accuracy of Memristor-Based Bio-Signal Sensing Platform | Recently a novel neuronal activity sensor exploiting the intrinsic thresholded integrator capabilities of memristor devices has been proposed. Extracellular potentials captured by a standard bio-signal acquisition platform are fed into a memristive device which reacts to the input by changing its resistive state (RS) only when the signal ampitude exceeds a threshold. Thus, significant peaks in the neural signal can be stored as non-volatile changes in memristor resistive state whilst noise is effectively suppressed. However, as a memristor is subjected to increasing numbers of supra-threshold stimuli during practical operation, it accumulates (RS) changes and eventually saturates. This leads to severely reduced neural activity detection capabilities. In this work we explore different signal processing and memristor operating procedure strategies in order to improve the detection rate of significant neuronal activity events. We analyse the data obtained from a single-memristive device biased with a reference neural recording and observe that performance can be improved markedly by a) increasing the frequency at which the memristor is reset to an initial resistive state where it is known to be highly responsive, b) appropriately preconditioning the input waveform through application of gain and offset in order to optimally exploit the intrinsic device behaviour. All results are validated by benchmarking obtained spike detection performance against a state-of-the-art template matching system utilising computationally-heavy, multi-dimensional, principal component analysis. |
2,884 | The use of ketamine as an induction agent for anesthesia in pulmonary thromboendarterectomy surgery: A case series | Pulmonary thromboendarterectomy (PTE) surgery is the treatment of choice for patients with chronic thromboembolic pulmonary hypertension (CTEPH). The induction of anesthesia in patients with severe pulmonary hypertension (PHT) can be challenging, with a risk of cardiovascular collapse. The administration of ketamine in patients with PHT is controversial, with some recommendations contraindicating its use. However, ketamine has been used safely in children with severe PHT. We present a retrospective case series of adult patients with severe PHT presenting for PTE surgery, using intravenous ketamine as a co-induction anesthetic agent. |
2,885 | A novel cost effective demosaicing approach | A unique color interpolation approach for digital still cameras is introduced and described in terms of color vectors. A new difference plane model is introduced and used in conjunction with the proposed here correction process. This avoids edge blurring while improving on the color appearance of previous methods. Experimental results indicate that the proposed method exhibits superior performance over state of-the-art color interpolation methods(1). |
2,886 | Microplastics in the first-year sea ice of the Novik Bay, Sea of Japan | Sea ice is heavily contaminated with microplastics particles (MPs, <5 mm). First-year sea ice cores (38-41 cm thick) were taken in the beginning of spring in a narrow populated bay of the Sea of Japan. Two ice cores were examined (layer-by-layer, excluding surface) for MPs content: one using μ-FTIR for 25-300 μm (SMPs), and another one - with visual+Raman identification for 300-5000 μm particles (LMPs). The integral (25-5000 μm) bulk mean abundance of MPs was found to be 428 items/L of meltwater, with fibers making 19 % in SMPs size range and 59 % in LMPs. Integral mean mass of MPs was estimated in 34.6 mg/L, with 99.6 % contribution from fragments of LMPs. Comparison with simple fragmentation models confirms deficit of SMPs (especially of fibers in size range 150-300 μm), suggested to result from their leakage with brine. Multivariate statistical analysis indicates strong positive correlation of large fiber (>300 μm) counts and ice salinity. |
2,887 | A comparison of methods for sketch-based 3D shape retrieval | Sketch-based 3D shape retrieval has become an important research topic in content-based 3D object retrieval. To foster this research area, two Shape Retrieval Contest (SHREC) tracks on this topic have been organized by us in 2012 and 2013 based on a small-scale and large-scale benchmarks, respectively. Six and five (nine in total) distinct sketch-based 3D shape retrieval method have competed each other in these two contests, respectively. To measure and compare the performance of the top participating and other existing promising sketch-based 3D shape retrieval methods and solicit the state-of-the-art approaches, we perform a more comprehensive comparison of fifteen best (four top participating algorithms and eleven additional state-of-the-art methods) retrieval methods by completing the evaluation of each method on both benchmarks. The benchmarks, results, and evaluation tools for the two tracks are publicly available on our websites [1,2]. (C) 2013 Elsevier Ltd. All rights reserved. |
2,888 | AmbiKraf | This paper presents, AmbiKraf, a non-emissive fabric display that subtly animates patterns on common fabrics. We use thermochromic inks and peltier semiconductor elements to achieve this technology. With this technology we have produced numerous prototypes from animated wall paintings to pixilated fabric displays. The ability of this technology to subtly and ubiquitously change the color of the fabric itself has made us able to merge different fields and technologies with AmbiKraf. In addition, with an animated room divider screen, Ambikraf merged its technology with Japanese Byobu art to tighten the gap between traditional arts and contemporary technologies. Through this AmbiKraf Byobu art installation and other installations, we discuss the impact of this technology as a ubiquitous fabric display. With focus to improvements of some limitations of the existing system, we present our future vision that enables us to merge this technology into more applications fields thus making this technology a platform for ubiquitous interactions on our daily peripherals. |
2,889 | Patient-Centered Discussions About Disease Progression, Symptom, and Treatment Burden in Chronic Obstructive Pulmonary Disease Could Facilitate the Integration of End-of-Life Discussions in the Disease Trajectory: Patient, Clinician, and Literature Perspectives: A Multimethod Approach | Background: Patients with chronic obstructive pulmonary disease (COPD) seldom discuss preferences for future care/treatments with clinicians. The lack of discussions prevents the delivery of care grounded on patient preferences. Instead, treatments become increasingly burdensome as disease progresses and patients approach the end of life. Objective: Identify current and best practice in initiating and conducting conversations about future and palliative care, by integrating data from multiple sources. Design: Multiphasic study where the findings of a systematic literature review and qualitative interviews were combined and synthesized using a triangulation protocol. Setting/Participants: Thirty-three patients with COPD and 14 clinicians from multiple backgrounds were recruited in the United Kingdom. Results: Clinicians' and patients' poor understanding about palliative care and COPD, difficulties in timing and initiating discussions, and service rationing were the main factors for late discussions. Divergent perspectives between patients and clinicians about palliative care discussions often prevented their start. Instead, early and gradual patient-centered discussions on treatment choices, symptom, and treatment burden were recommended by patients, clinicians, and the literature. Earlier patient-centered discussions may reduce their emotional impact and enable patients to participate fully, while enabling clinicians to provide timely and accurate information on illness progression and appropriate self-management techniques. Conclusion: Current approaches toward palliative care discussions in COPD do not guarantee that patients' preferences are met. Early and gradual patient-centered discussions may enable patients to fully express their care preferences as they evolve over time, while minimizing the impact of symptom and treatment burden. |
2,890 | Threshold temperature scaling: Heuristic to address temperature and power issues in MPSoCs | In this article, we propose a scheduling based temperature and power-aware heuristic for multi-core systems. Instead of using a fixed value of temperature threshold in load balancing techniques, the proposed heuristic suggests adjusting the value of threshold temperature as a function of the workload. As the workload reduces, the value of the threshold is lowered accordingly and vice versa. Lowering the value of threshold temperature decreases the temperature peaks, temperature spatial, and temporal gradients. Furthermore, it also reduces the total power consumed by the processing unit. The effectiveness of the approach is evaluated in a simulation-based environment that includes a scheduling and a thermal modeling tool. For evaluation, the heuristic is integrated with a state of the art load balancing technique based on global scheduling and a comparison is performed with the popular thermal-aware techniques. The results analysis shows that the use of proposed heuristic lowers the temperature peak by up to 7 degrees C, temperature spatial gradients by up to 35%, temporal gradient by 65%, and power utilization by up to 5.5% when compared with the state-of-the-art thermal balancing techniques and predictive thermalaware models. (c) 2020 Elsevier B.V. All rights reserved. |
2,891 | The economics of CCS: Why have CCS technologies not had an international breakthrough? | Eleven years on since the United Nations' Intergovernmental Panel on Climate Change was awarded the Nobel Peace Prize in recognition of its efforts in combating climate change, fossil fuels remain the most dominant global energy source. As the total replacement of fossil fuel energy is not expected to take place immediately in the near future, the International Energy Agency has repeatedly declared carbon capture and sequestration (CCS) as a key technology for mitigating climate change. However, CCS lacks the scale required for substantial reduction in carbon dioxide emissions from fossil fuel power generation. Even though CCS is one of the key technologies for mitigating climate change, why has this technology not had an international breakthrough? To shed light on this question, this paper employs a simple model of energy generation, scrutinizes the economic drivers of CCS based on the analytical results, and discusses the possible obstacles that can prevent a widespread rollout of the technology. This is followed by a state-of-the-art in literature pertaining to the economics of CCS, and a discussion that points to a dichotomy between the economic theory and reality. The study concludes with some policy suggestions and directions for future research. |
2,892 | Methods for Simultaneous Robot-World-Hand-Eye Calibration: A Comparative Study | In this paper, we propose two novel methods for robot-world-hand-eye calibration and provide a comparative analysis against six state-of-the-art methods. We examine the calibration problem from two alternative geometrical interpretations, called hand-eye' and robot-world-hand-eye', respectively. The study analyses the effects of specifying the objective function as pose error or reprojection error minimization problem. We provide three real and three simulated datasets with rendered images as part of the study. In addition, we propose a robotic arm error modeling approach to be used along with the simulated datasets for generating a realistic response. The tests on simulated data are performed in both ideal cases and with pseudo-realistic robotic arm pose and visual noise. Our methods show significant improvement and robustness on many metrics in various scenarios compared to state-of-the-art methods. |
2,893 | The critical role of quercetin in autophagy and apoptosis in HeLa cells | In recent years, the effects of quercetin on autophagy and apoptosis of cancer cells have been widely reported, while effects on HeLa cells are still unclear. Here, HeLa cells were subjected to quercetin treatment, and then proliferation, apoptosis, and autophagy were evaluated using MTT, flow cytometry, and MDC staining, respectively. The LC3-I/II, Beclin 1, active caspase-3, and S6K1 phosphorylation were detected using Western blot assay. The ultrastructure of HeLa was observed via transmission electron microscope (TEM). Our findings showed that quercetin can dose-dependently inhibit the growth of HeLa cells. The MDC fluorescence was enhanced with increased concentration of quercetin and hit a plateau at 50 μmol/l. Western blot assay revealed that LC3-I/II ratio, Beclin 1, and active caspase-3 protein were enforced in a dose-dependent method. However, the phosphorylation of S6K1 gradually decreased, concomitant with an increase of autophagy. In addition, TEM revealed that the number of autophagic vacuoles was peaked at 50 μmol/l of quercetin. Besides, interference of autophagy with 3-MA led to proliferation inhibition and increased apoptosis in HeLa cells, accompanied by the decreased LC3-I/II conversion and the increased active caspase-3. In conclusion, quercetin can inhibit HeLa cell proliferation and induce protective autophagy at low concentrations; thus, 3-MA plus quercetin would suppress autophagy and effectively increased apoptosis. |
2,894 | Anti-PD-1 and PD-L1 therapy for bladder cancer: what is on the horizon? | Oncologic therapeutics has evolved enormously as we entered the 21st century. Unfortunately, the treatment of advanced urothelial cancer has remained unchanged over the last two decades despite a better understanding of the genetic alterations in bladder cancer. Pathways such as the PI3K/AKT3/mTOR and FGFR have been implicated in urothelial bladder cancer. However, targeted therapies have not shown proven benefit yet and are still considered investigational. Recently, researchers have been successful in manipulating the systemic immune response to mount antitumor effects in melanoma, lung cancer and lymphoma. Historically, intravesical Bacillus Calmette-Guérin immunotherapy has been highly active in nonmuscle invasive bladder cancer. Early data suggest that immune checkpoint inhibitors will soon prove to be another cornerstone in the treatment armamentarium of advanced bladder cancer. |
2,895 | Self-Path: Self-Supervision for Classification of Pathology Images With Limited Annotations | While high-resolution pathology images lend themselves well to 'data hungry' deep learning algorithms, obtaining exhaustive annotations on these images for learning is a major challenge. In this article, we propose a self-supervised convolutional neural network (CNN) framework to leverage unlabeled data for learning generalizable and domain invariant representations in pathology images. Our proposed framework, termed as Self-Path, employs multi-task learning where the main task is tissue classification and pretext tasks are a variety of self-supervised tasks with labels inherent to the input images. We introduce novel pathology-specific self-supervision tasks that leverage contextual, multi-resolution and semantic features in pathology images for semi-supervised learning and domain adaptation. We investigate the effectiveness of Self-Path on 3 different pathology datasets. Our results show that Self-Path with the pathology-specific pretext tasks achieves state-of-the-art performance for semi-supervised learning when small amounts of labeled data are available. Further, we show that Self-Path improves domain adaptation for histopathology image classification when there is no labeled data available for the target domain. This approach can potentially be employed for other applications in computational pathology, where annotation budget is often limited or large amount of unlabeled image data is available. |
2,896 | Design parameters of an omnidirectional planar microstrip antenna | The design parameters of all onmidirectional planar microstrip antenna art examined. The impedance bandwidth and radiation efficiency increase as the element width is increased. Increasing the element width can cause a lower-order mode to increase in frequency and degrade the omnidirectional pattern and sidelobes, and thus creates a beam scan from broadside. This beam scan and pattern degradation call he eliminated with narrower elements or by moving the position of the shorting pins at the expense of impedance bandwidth. (c) 2005 Wiley Periodicals, Inc. |
2,897 | Determinants of Survival of HIV Patients Receiving Dolutegravir: A Prospective Cohort Study in Conflict-Affected Bunia, Democratic Republic of Congo | This study aims to determine the factors influencing HIV-related mortality in settings experiencing continuous armed conflict atrocities. In such settings, people living with HIV (PLHIV), and the partners of those affected may encounter specific difficulties regarding adherence to antiretroviral therapy (ART), and retention in HIV prevention, treatment, and care programs. Between July 2019 and July 2021, we conducted an observational prospective cohort study of 468 PLHIV patients treated with Dolutegravir at all the ART facilities in Bunia. The probability of death being the primary outcome, as a function of time of inclusion in the cohort, was determined using Kaplan-Meier plots. We used the log-rank test to compare survival curves and Cox proportional hazard modeling to determine mortality predictors from the baseline to 31 July 2021 (endpoint). The total number of person-months (p-m) was 3435, with a death rate of 6.70 per 1000 p-m. Compared with the 35-year-old reference group, older patients had a higher mortality risk. ART-naive participants at the time of enrollment had a higher mortality risk than those already using ART. Patients with a high baseline viral load (>= 1000 copies/mL) had a higher mortality risk compared with the reference group (adjusted hazard ratio = 6.04; 95% CI: 1.78-20.43). One-fourth of deaths in the cohort were direct victims of armed conflict, with an estimated excess death of 35.6%. Improving baseline viral load monitoring, starting ART early in individuals with high baseline viral loads, the proper tailoring of ART regimens and optimizing long-term ART, and care to manage non-AIDS-related chronic complications are recommended actions to reduce mortality. Not least, fostering women's inclusion, justice, peace, and security in conflict zones is critical in preventing premature deaths in the general population as well as among PLHIV. |
2,898 | CRISPR/Cas9: A revolutionary genome editing tool for human cancers treatment | Cancer is a genetic disease stemming from genetic and epigenetic mutations and is the second most common cause of death across the globe. Clustered regularly interspaced short palindromic repeats (CRISPR) is an emerging gene-editing tool, acting as a defense system in bacteria and archaea. CRISPR/Cas9 technology holds immense potential in cancer diagnosis and treatment and has been utilized to develop cancer disease models such as medulloblastoma and glioblastoma mice models. In diagnostics, CRISPR can be used to quickly and efficiently detect genes involved in various cancer development, proliferation, metastasis, and drug resistance. CRISPR/Cas9 mediated cancer immunotherapy is a well-known treatment option after surgery, chemotherapy, and radiation therapy. It has marked a turning point in cancer treatment. However, despite its advantages and tremendous potential, there are many challenges such as off-target effects, editing efficiency of CRISPR/Cas9, efficient delivery of CRISPR/Cas9 components into the target cells and tissues, and low efficiency of HDR, which are some of the main issues and need further research and development for completely clinical application of this novel gene editing tool. Here, we present a CRISPR/Cas9 mediated cancer treatment method, its role and applications in various cancer treatments, its challenges, and possible solution to counter these challenges. |
2,899 | MR-Nucleomics: The study of pathological cellular processes with multinuclear magnetic resonance spectroscopy and imaging in vivo | Clinical medicine has experienced a rapid development in recent decades, during which therapies targeting specific cellular signaling pathways, or specific cell surface receptors, have been increasingly adopted. While these developments in clinical medicine call for improved precision in diagnosis and treatment monitoring, modern medical imaging methods are restricted mainly to anatomical imaging, lagging behind the requirements of precision medicine. Although positron emission tomography and single photon emission computed tomography have been used clinically for studies of metabolism, their applications have been limited by the exposure risk to ionizing radiation, the subsequent limitation in repeated and longitudinal studies, and the incapability in assessing downstream metabolism. Magnetic resonance spectroscopy (MRS) or spectroscopic imaging (MRSI) are, in theory, capable of assessing molecular activities in vivo, although they are often limited by sensitivity. Here, we review some recent developments in MRS and MRSI of multiple nuclei that have potential as molecular imaging tools in the clinic. |
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