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2,500 | Ghosting-free DCT based multi-exposure image fusion | We propose a novel algorithm for multi-exposure fusion (MEF). This algorithm decomposes image patches with the DCT transform. Coefficients from patches with different exposure are combined. The luminance and chrominance of the different images are fused separately. The algorithm adapts to dynamic sequences in order to avoid ghosting effects. The initial sequence is processed to be made static before applying the fusion procedure. Experiments with several data sets show that the proposed algorithm performs better than state-of-the-art. |
2,501 | Scatter Component Analysis: A Unified Framework for Domain Adaptation and Domain Generalization | This paper addresses classification tasks on a particular target domain in which labeled training data are only available from source domains different from (but related to) the target. Two closely related frameworks, domain adaptation and domain generalization, are concerned with such tasks, where the only difference between those frameworks is the availability of the unlabeled target data: domain adaptation can leverage unlabeled target information, while domain generalization cannot. We propose Scatter Component Analyis (SCA), a fast representation learning algorithm that can be applied to both domain adaptation and domain generalization. SCA is based on a simple geometrical measure, i.e., scatter, which operates on reproducing kernel Hilbert space. SCA finds a representation that trades between maximizing the separability of classes, minimizing the mismatch between domains, and maximizing the separability of data; each of which is quantified through scatter. The optimization problem of SCA can be reduced to a generalized eigenvalue problem, which results in a fast and exact solution. Comprehensive experiments on benchmark cross-domain object recognition datasets verify that SCA performs much faster than several state-of-the-art algorithms and also provides state-ofthe- art classification accuracy in both domain adaptation and domain generalization. We also show that scatter can be used to establish a theoretical generalization bound in the case of domain adaptation. |
2,502 | Robust occlusion-aware part-based visual tracking with object scale adaptation | Visual tracking is still a challenging task as the objects suffer significant appearance changes, fast motion, and serious occlusion. In this paper, we propose an occlusion-aware part-based tracker for robust visual tracking. We first present a novel occlusion-aware part-based model based on correlation filters to integrate the global model and part-based model adaptively. It can effectively employ both the global and local information to improve the robustness of the tracker. Then we propose an integral pipeline aiming to the long-term tracking under the correlation filters, which achieves the state-of-the-art performance. In this tracking pipeline, we adopt separate translation and scale estimation. For translation estimation, we exploit and jointly learn the hierarchical features of deep Convolutional Neural Networks (CNNs) to locate the target center accurately. Then we learn an independent scale correlation filter to handle the scale variation. This design realizes scale adaptation of the target preferably, and reduces computational complexity efficiently. We further ameliorate the model update method by introducing the original reliable information. It greatly alleviates the error accumulation of the incorrect information and efficiently achieves long-term tracking. Extensive experimental results on several different challenging benchmark datasets show that our proposed tracker achieves outstanding performance against the state-of-the-art methods. (C) 2018 Elsevier Ltd. All rights reserved. |
2,503 | Position sensors based on the delay line principle | A position sensor is presented based on the magnetostrictive delay line (MDL) principle. The sensor is accompanied by its electronic circuitry and packaging. We present and analyze the sensor principle, electronics, calibration procedure as well as its evaluation with respect to the state of the art, showing its advantages and applications. (C) 2003 Elsevier B.V All rights reserved. |
2,504 | Gray whale density during seismic surveys near their Sakhalin feeding ground | Oil and gas development off northeastern Sakhalin Island, Russia, has exposed the western gray whale population on their summer-fall foraging grounds to a range of anthropogenic activities, such as pile driving, dredging, pipeline installation, and seismic surveys. In 2015, the number of seismic surveys within a feeding season surpassed the level of the number and duration of previous seismic survey activities known to have occurred close to the gray whales' feeding ground, with the potential to cause disturbance to their feeding activity. To examine the extent that gray whales were potentially avoiding areas when exposed to seismic and vessel sounds, shore-based teams monitored the abundance and distribution of gray whales from 13 stations that encompassed the known nearshore feeding area. Gray whale density was examined in relation to natural (spatial, temporal, and prey energy) and anthropogenic (cumulative sound exposure from vessel and seismic sounds) explanatory variables using Generalized Additive Models (GAM). Distance from shore, water depth, date, and northing explained a significant amount of variation in gray whale densities. Prey energy from crustaceans, specifically amphipods, isopods, and cumaceans also significantly influenced gray whale densities in the nearshore feeding area. Increasing cumulative exposure to vessel and seismic sounds resulted in both a short- and longer-term decline in gray whale density in an area. This study provides further insights about western gray whale responses to anthropogenic activity in proximity to and within the nearshore feeding area. As the frequency of seismic surveys and other non-oil and gas anthropogenic activity are expected to increase off Sakhalin Island, it is critical to continue to monitor and assess potential impacts on this endangered population of gray whales. |
2,505 | Targeting TNF-α-producing macrophages activates antitumor immunity in pancreatic cancer via IL-33 signaling | Pancreatic ductal adenocarcinoma (PDA) remains resistant to immune therapies, largely owing to robustly fibrotic and immunosuppressive tumor microenvironments. It has been postulated that excessive accumulation of immunosuppressive myeloid cells influences immunotherapy resistance, and recent studies targeting macrophages in combination with checkpoint blockade have demonstrated promising preclinical results. Yet our understanding of tumor-associated macrophage (TAM) function, complexity, and diversity in PDA remains limited. Our analysis reveals significant macrophage heterogeneity, with bone marrow-derived monocytes serving as the primary source for immunosuppressive TAMs. These cells also serve as a primary source of TNF-α, which suppresses expression of the alarmin IL-33 in carcinoma cells. Deletion of Ccr2 in genetically engineered mice decreased monocyte recruitment, resulting in profoundly decreased TNF-α and increased IL-33 expression, decreased metastasis, and increased survival. Moreover, intervention studies targeting CCR2 with a new orthosteric inhibitor (CCX598) rendered PDA susceptible to checkpoint blockade, resulting in reduced metastatic burden and increased survival. Our data indicate that this shift in antitumor immunity is influenced by increased levels of IL-33, which increases dendritic cell and cytotoxic T cell activity. These data demonstrate that interventions to disrupt infiltration of immunosuppressive macrophages, or their signaling, have the potential to overcome barriers to effective immunotherapeutics for PDA. |
2,506 | Preventing Aerosol Emissions in a CO2 Capture System: Combining Aerosol Formation Inhibition and Wet Electrostatic Precipitation | Aerosol emission from the CO2 capture system has raised great concern for causing solvent loss and serious environmental issues. Here, we propose a comprehensive method for reducing aerosol emissions in a CO2 capture system under the synergy of aerosol formation inhibition and wet electrostatic precipitation. The gas-solvent temperature difference plays a vital role in aerosol formation, with aerosol emissions of 740.80 mg/m3 at 50 K and 119.36 mg/m3 at 0 K. Different effects of SO2 and SO3 on aerosol formation are also found in this research; the aerosol mass concentration could reach 2341.25 mg/m3 at 20 ppm SO3 and 681.01 mg/m3 at 50 ppm SO2 with different aerosol size distributions. After the CO2 capture process, an aerosol removal efficiency of 98% can be realized by electrostatic precipitation under different CO2 concentrations. Due to the high concentration of aerosols and aerosol space charge generated by SO2 and SO3, the removal performance of the wet electrostatic precipitator decreases, resulting in a high aerosol emission concentration (up to 130.26 mg/m3). Thus, a heat exchanger is installed before the electrostatic precipitation section to enhance aerosol growth and increase aerosol removal efficiency. Under the synergy of aerosol formation inhibition and electrostatic precipitation, an aerosol removal efficiency of 99% and emission concentrations lower than 5 mg/m3 are achieved, contributing to global warming mitigation and environmental protection. |
2,507 | Fully-differential flipped-source-follower low-pass analogue filter in CMOS 28nm bulk | This study presents a novel low-pass continuous-time filter based on the voltage flipped-source-follower (SF). The filter efficiently operates in CMOS 28nm and improves the SF filters state-of-the-art thanks to a dedicated circuit that operates in fully-differential fashion (instead of the pseudo-differential typically used in state-of-the-art SF filters) with a dedicated Common-Mode-Feedback circuit. Thus this work extends the application of the SF filtering stages to the nm-range technologies where threshold voltage (V-TH) is only two times lower than the supply voltage (V-DD) for what regards standard-process MOS transistors. In order to validate the design concept, the proposed filter has been designed in CMOS 28nm technology. Extensive simulation results of a 131MHz -3dB frequency proof-of-concept second-order filter are proposed. The device consumes 510 mu W power from a single 1V supply-voltage. In-band integrated noise is 160 mu V-RMS and IIP3 is 19dBm for 20 and 21MHz input tones frequencies. Simulation results lead to 166J(-1) figure-of-merit, outperforming the analogue filter state-of-the-art. |
2,508 | Efficient Multiple Organ Localization in CT Image Using 3D Region Proposal Network | Organ localization is an essential preprocessing step for many medical image analysis tasks, such as image registration, organ segmentation, and lesion detection. In this paper, we propose an efficient method for multiple organ localization in CT image using a 3D region proposal network. Compared with other convolutional neural network-based methods that successively detect the target organs in all slices to assemble the final 3D bounding box, our method is fully implemented in a 3D manner, and thus, it can take full advantages of the spatial context information in CT image to perform efficient organ localization with only one prediction. We also propose a novel backbone network architecture that generates high-resolution feature maps to further improve the localization performance on small organs. We evaluate our method on two clinical datasets, where 11 body organs and 12 head organs (or anatomical structures) are included. As our results shown, the proposed method achieves higher detection precision and localization accuracy than the current state-of-the-art methods with approximate 4 to 18 times faster processing speed. Additionally, we have established a public dataset dedicated for organ localization on http://dx.doi.org/10.21227/df8g-pq27. The full implementation of the proposed method has also been made publicly available on https://github.com/superxuang/caffe_3d_faster_rcnn. |
2,509 | Friction-resilient position control for machine tools-Adaptive and sliding-mode methods compared | Robust trajectory tracking and increasing demand for high-accuracy tool positioning have motivated research in advanced control design for machine tools. State-of-the-art industry solutions employ cascades of Proportional (P) and Proportional Integral (PI) controllers for closed-loop servo control of position and velocity of the machine axes. Although these schemes provide the required positioning accuracy in nominal conditions, performance deteriorates with increased friction and wear of the machine. With conventional control, re-tuning is necessary during the lifetime if specified accuracy shall be maintained. This paper investigates whether nonlinear and adaptive controllers can cope with typical levels of friction increase without loss of performance. It evaluates the performance of a state-of-art industry solution with that obtainable with adaptive and sliding mode positioning controls. The main finding is that an adaptive backstepping control is resilient to unknown and increasing friction at realistic levels of wear, where the P-PI control fall short with respect to accuracy. A single-axis test rig with adjustable friction is used to assess the performance of different controllers. |
2,510 | Blockade of CD127 Exerts a Dichotomous Clinical Effect in Marmoset Experimental Autoimmune Encephalomyelitis | Non-human primate models of human disease have an important role in the translation of a new scientific finding in lower species into an effective treatment. In this study, we tested a new therapeutic antibody against the IL-7 receptor α chain (CD127), which in a C57BL/6 mouse model of experimental autoimmune encephalomyelitis (EAE) ameliorates disease, demonstrating an important pathogenic function of IL-7. We observed that while the treatment was effective in 100 % of the mice, it was only partially effective in the EAE model in common marmosets (Callithrix jacchus), a small-bodied Neotropical primate. EAE was induced in seven female marmoset twins and treatment with the anti-CD127 mAb or PBS as control was started 21 days after immunization followed by weekly intravenous administration. The anti-CD127 mAb caused functional blockade of IL-7 signaling through its receptor as shown by reduced phosphorylation of STAT5 in lymphocytes upon stimulation with IL-7. Group-wise analysis showed no significant effects on the clinical course and neuropathology. However, paired twin analysis revealed a delayed disease onset in three twins, which were high responders to the immunization. In addition, we observed markedly opposite effects of the antibody on pathological changes in the spinal cord in high versus low responder twins. In conclusion, promising clinical effect of CD127 blockade observed in a standard inbred/SPF mouse EAE model could only be partially replicated in an outbred/non-SPF non-human primate EAE model. Only in high responders to the immunization we found a positive response to the treatment. The mechanism underpinning this dichotomous response will be discussed. |
2,511 | State of art of biomass fast pyrolysis for bio-oil in China: a review | This paper presents a review of biomass fast pyrolysis for the production of bio-oil in Mainland China. The main contents are as follows. The feedstock for fast pyrolysis and main pyrolysis reactor developed in Mainland China are introduced. The process of fast pyrolysis for each pyrolysis reactor mentioned in this paper is described. The effects of key parameters of fast pyrolysis on fluidised bed reactor are illustrated. Finally, the properties, upgrading and application of bio-oil are discussed. |
2,512 | Premenopausal and postmenopausal women during the COVID-19 pandemic | The current global COVID-19 mortality rate is estimated to be around 3.4%; however, it is dependent on age, sex, and comorbidities. Epidemiological evidence shows gender disparities in COVID-19 severity and fatality, with non-menopausal females having milder severity and better outcomes than age-matched males. However, the difference vanishes when comparing postmenopausal women with age-matched men. It has been suggested that, to some extent, this is due to the protective role of female hormones, such as anti-Müllerian hormone and oestradiol (E2), in non-menopausal women. Oestrogens have been hypothesized to be crucial in modulating viral infection and the progression of the disease via an action on immune/inflammatory responses and angiotensin-converting enzyme type 2 expression. Hence, the most likely explanation is that, because the levels of oestrogen in females after menopause decrease, oestrogen no longer offers a beneficial effect as seen in younger females. The COVID-19 pandemic has highlighted the serious negative effects arising from the state of E2 deficiency. Therefore, hormone replacement therapy gains further support as the damaging effect of the decline in ovarian function affects many biological systems, and recently with the COVID-19 pandemic, oestrogen's vital role within the immune system has become quite clear. However, additional clinical investigations regarding hormone replacement therapy are urgently needed to further verify the protective and therapeutic effects of E2 on menopausal women with COVID-19. |
2,513 | A fast framework construction and visualization method for particle-based fluid | Fast and vivid fluid simulation and visualization is a challenge topic of study in recent years. Particle-based simulation method has been widely used in the art animation modeling and multimedia field. However, the requirements of huge numerical calculation and high quality of visualization usually result in a poor computing efficiency. In this work, in order to improve those issues, we present a fast framework for 3D fluid fast constructing and visualization which parallelizes the fluid algorithm based on the GPU computing framework and designs a direct surface visualization method for particle-based fluid data such as WCSPH, IISPH, and PCISPH. Considering on conventional polygonization or adaptive mesh methods may incur high computing costs and detail losses, an improved particle-based method is provided for real-time fluid surface rendering with the screen-space technology and the utilities of the modern graphics hardware to achieve the high performance rendering; meanwhile, it effectively protects fluid details. Furthermore, to realize the fast construction of scenes, an optimized design of parallel framework and interface is also discussed in our paper. Our method is convenient to enforce, and the results demonstrate a significant improvement in the performance and efficiency by being compared with several examples. |
2,514 | CNN-Based Ultrasound Image Reconstruction for Ultrafast Displacement Tracking | Thanks to its capability of acquiring full-view frames at multiple kilohertz, ultrafast ultrasound imaging unlocked the analysis of rapidly changing physical phenomena in the human body, with pioneering applications such as ultrasensitive flow imaging in the cardiovascular system or shear-wave elastography. The accuracy achievable with these motion estimation techniques is strongly contingent upon two contradictory requirements: a high quality of consecutive frames and a high frame rate. Indeed, the image quality can usually be improved by increasing the number of steered ultrafast acquisitions, but at the expense of a reduced frame rate and possible motion artifacts. To achieve accurate motion estimation at uncompromised frame rates and immune to motion artifacts, the proposed approach relies on single ultrafast acquisitions to reconstruct high-quality frames and on only two consecutive frames to obtain 2-D displacement estimates. To this end, we deployed a convolutional neural network-based image reconstruction method combined with a speckle tracking algorithm based on cross-correlation. Numerical and in vivo experiments, conducted in the context of plane-wave imaging, demonstrate that the proposed approach is capable of estimating displacements in regions where the presence of side lobe and grating lobe artifacts prevents any displacement estimation with a state-of-the-art technique that relies on conventional delay-and-sum beamforming. The proposed approach may therefore unlock the full potential of ultrafast ultrasound, in applications such as ultrasensitive cardiovascular motion and flow analysis or shear-wave elastography. |
2,515 | Local Phase Velocity Based Imaging: A New Technique Used for Ultrasound Shear Wave Elastography | Ultrasound shear wave elastography is an imaging modality for noninvasive evaluation of tissue mechanical properties. However, many current techniques overestimate lesions dimension or shape especially when small inclusions are taken into account. In this paper, we propose a new method called local phase velocity-based imaging (LPVI) as an alternative technique to measure tissue elasticity. Two separate acquisitions with ultrasound push beams focused once on the left side and once on the right side of the inclusion were generated. A local shear wave velocity is then recovered in the frequency domain (for a single frequency or frequency band) for both acquired data sets. Finally, a two-dimensional shear wave velocity map is reconstructed by combining maps from two separate acquisitions. Robust and accurate shear wave velocity maps are reconstructed using the proposed LPVI method in calibrated liver fibrosis tissue mimicking homogeneous phantoms, a calibrated elastography phantom with stepped cylinder inclusions and a homemade gelatin phantom with ex vivo porcine liver inclusion. Results are compared with an existing phase velocity-based imaging approach and a group velocity-based method considered as the state of the art. Results from the phantom study showed that increased frequency improved the shape of the reconstructed inclusions and contrast-to-noise ratio between the target and background. |
2,516 | The influence of 5-fluorouracil on the α-ketoglutarate dehydrogenase complex in rat's cardiac muscle - a preliminary study | 5-fluorouracil (5-FU), which is a commonly used chemotherapy agent exerts undesired cardiac toxicity. Mitochondrial dysfunction is thought to be one of potentially important mechanisms of 5-FU- induced cardiotoxicity. α-ketoglutarate dehydrogenase (α-KGDHC) is the key regulatory enzyme of TCA cycle. The complex consists of multiple copies of three catalytic subunits: α-ketoglutarate dehydrogenase (E1), dihydrolipoamide succinyltransferase (E2) and dihydrolipoamide dehydrogenase (E3). α-KGDHC together with branched chain α-ketoacid dehydrogenase (BCKDH) and pyruvate dehydrogenase (PDH), are the members of 2-oxoacid dehydrogenases family that share some structural and functional similarities. Recently, it has been found that 5-FU stimulates BCKDH in rat's cardiac muscle. Therefore, we hypothesize that 5-FU modifies α-KGDHC activity and affects cardiac muscle metabolism. The aim of this study was to determine the effect of 5-FU on α-KGDHC activity and protein levels of E1 and E2 subunits of the complex in rat's cardiac muscle. Wistar male rats were administered with 4 doses of 5-FU, 150 mg/ kg b.wt. each (study group) or 0.3% methylcellulose (control group). α-KGDHC activity was assayed spectrophotometrically. The E1 and E2 proteins levels were quantified by Western blot. 5-FU administration resulted in stimulation of myocardial α-KGDHC activity in rats. In addition, E2 protein level increased in response to 5-FU treatment, while the E1 protein level remained unchanged. Up-regulation of α-KGDHC appears to result from change in E2 subunit protein level. However, the effect of 5-FU on factors modifying α-KGDHC activity at post-translational level cannot be excluded. |
2,517 | Computational Approaches and Challenges in Spatial Transcriptomics | The development of spatial transcriptomics (ST) technologies has transformed genetic research from a single-cell data level to a two-dimensional spatial coordinate system and facilitated the study of the composition and function of various cell subsets in different environments and organs. The large-scale data generated by these ST technologies, which contain spatial gene expression information, have elicited the need for spatially resolved approaches to meet the requirements of computational and biological data interpretation. These requirements include dealing with the explosive growth of data to determine the cell-level and gene-level expression, correcting the inner batch effect and loss of expression to improve the data quality, conducting efficient interpretation and in-depth knowledge mining both at the single-cell and tissue-wide levels, and conducting multi-omics integration analysis to provide an extensible framework toward the in-depth understanding of biological processes. However, algorithms designed specifically for ST technologies to meet these requirements are still in their infancy. Here, we review computational approaches to these problems in light of corresponding issues and challenges, and present forward-looking insights into algorithm development. |
2,518 | A Fast Superresolution Image Reconstruction Algorithm | In a previous paper we have proposed two new superresolution image reconstruction algorithms, based on a non-parametric numerical integration Bayesian inference method, the Integrated Nested Laplace Approximation (INLA). Despite achieving superior image reconstruction results compared to other state-of-the-art methods, such algorithms manipulate huge matrices (although sparse). Therefore, the demand for memory usage and computation is high. In this paper, review such algorithms, solving these problems through relaxing one equation in the original mathematical model and involving the high-resolution (HR) image in a Torus. The result is a meaningful reduction in the computation cost of such algorithms and in the dimensions of the matrices handled as well (from n(2)-by-n(2) to n-byn, the size of the HR image). The result is a new algorithm, much faster than its previous version and other meaningful state-of-the-art algorithms. |
2,519 | Atrazine exposure induces necroptosis through the P450/ROS pathway and causes inflammation in the gill of common carp (Cyprinus carpioL.) | Atrazine (ATR) is used worldwide and has been confirmed be hazardous materials that harmful to the health of organisms. Since ATR was more persistent in the water, the specific damage caused by ATR to aquatic organisms should be concern. The role of P450/ROS has been proposed in many pathomechanisms. To explore whether P450/ROS mediated necroptosis and promote inflammatory response caused by ATR exposure, 120 common carp (Cyprinus carpio L.) were randomly divided into four groups which were exposed to 0 μg/L, 4 μg/L, 40 μg/L and 400 μg/L ATR respectively. The residual levels of ATR and its metabolites increased, signs of necrosis and inflammation were found in the gills of the ATR-treatment groups. The levels of ROS and cytochrome P450 content were increased, and P450 enzymes were activated. The expression levels of the core components of necroptosis (RIPK1, RIPK3 and MLKL) increased. Moreover, gene expression of inflammatory factors (TNF-α, NF-κB, iNOS, COX-2, IL-1β and PTGE) increased significantly in the ATR-spiked group. Our results suggested that ATR exposure triggered necroptosis through the P450/ROS pathway and causes inflammation of common carp gill. This study provides valuable clue about the mechanism by which ATR causes injury to common carp gill. |
2,520 | Boronates as hydrogen peroxide-reactive warheads in the design of detection probes, prodrugs, and nanomedicines used in tumors and other diseases | Hydrogen peroxide (H2O2) has always been a topic of great interests attributed to its vital role in biological process. H2O2 is known as a major reactive oxygen species (ROS) which is involve in numerous physiological processes such as cell proliferation, signal transduction, differentiation, and even pathogenesis. A plenty of diseases development such as chronic disease, inflammatory disease, and organ dysfunction are found to be relevant to abnormality of H2O2 production. Thus, imminent and feasible strategies to modulate and detect H2O2 level in vitro and in vivo have gained great importance. To date, the boronate-based chemical structure probes have been widely used to address the problems from the above aspects because of the rearranged chemical bonding which can detect and quantify ROS including hydrogen peroxide (H2O2) and peroxynitrite (ONOO-). This present article discusses boronate-based probes based on the chemical structure difference as well as reactivities to H2O2 and ONOO-. In this review, we also focus on the application of boronate-based probes in the field of cell imaging, prodrugs nanoplatform, nanomedicines, and electrochemical biosensors for disease diagnosis and treatment. In a nutshell, we outline the recent application of boronate-based probes and represent the prospective potentiality in biomedical domain in the future. |
2,521 | SV-RCNet: Workflow Recognition From Surgical Videos Using Recurrent Convolutional Network | We propose an analysis of surgical videos that is based on a novel recurrent convolutional network (SV-RCNet), specifically for automatic workflow recognition from surgical videos online, which is a key component for developing the context-aware computer-assisted intervention systems. Different from previous methods which harness visual and temporal information separately, the proposed SV-RCNet seamlessly integrates a convolutional neural network (CNN) and a recurrent neural network (RNN) to forma novel recurrent convolutional architecture in order to take full advantages of the complementary information of visual and temporal features learned from surgical videos. We effectively train the SV-RCNet in an end-to-end manner so that the visual representations and sequential dynamics can be jointly optimized in the learning process. In order to produce more discriminative spatio-temporal features, we exploit a deep residual network (ResNet) and a long short term memory (LSTM) network, to extract visual features and temporal dependencies, respectively, and integrate them into the SV-RCNet. Moreover, based on the phase transition-sensitive predictions from the SV-RCNet, we propose a simple yet effective inference scheme, namely the prior knowledge inference (PKI), by leveraging the natural characteristic of surgical video. Such a strategy further improves the consistency of results and largely boosts the recognition performance. Extensive experiments have been conducted with the MICCAI 2016 Modeling and Monitoring of Computer Assisted Interventions Workflow Challenge dataset and Cholec80 dataset to validate SV-RCNet. Our approach not only achieves superior performance on these two datasets but also outperforms the state-of-the-art methods by a significant margin. |
2,522 | Automating unambiguous NOE data usage in NVR for NMR protein structure-based assignments | Nuclear Magnetic Resonance (NMR) Spectroscopy is an important technique that allows determining protein structure in solution. An important problem in protein structure determination using NMR spectroscopy is the mapping of peaks to corresponding amino acids, also known as the assignment problem. Structure-Based Assignment (SBA) is an approach to solve this problem using a template structure that is homologous to the target. Our previously developed approach Nuclear Vector Replacement-Binary Integer Programming (NVR-BIP) computed the optimal solution for small proteins, but was unable to solve the assignments of large proteins. NVR-Ant Colony Optimization (ACO) extended the applicability of the NVR approach for such proteins. One of the input data utilized in these approaches is the Nuclear Overhauser Effect (NOE) data. NOE is an interaction observed between two protons if the protons are located close in space. These protons could be amide protons, protons attached to the alpha-carbon atom in the backbone of the protein, or side chain protons. NVR only uses backbone protons. In this paper, we reformulate the NVR-BIP model to distinguish the type of proton in NOE data and use the corresponding proton coordinates in the extended formulation. In addition, the threshold value over interproton distances is set in a standard manner for all proteins by extracting the NOE upper bound distance information from the data. We also convert NOE intensities into distance thresholds. Our new approach thus handles the NOE data correctly and without manually determined parameters. We accordingly adapt NVR-ACO solution methodology to these changes. Computational results show that our approaches obtain optimal solutions for small proteins. For the large proteins our ant colony optimization-based approach obtains promising results. |
2,523 | Expert systems in production planning and scheduling: A state-of-the-art survey | Intelligent solutions, based on expert systems, to solve problems in the field of production planning and scheduling are becoming more and more widespread nowadays. Especially the last decade has witnessed a growing number of manufacturing companies, including glass, oil, aerospace, computers, electronics, metal and chemical industries-to name just a few-interested in the applications of expert systems (ESs) in manufacturing. This paper is a state-of-the-art review of the use of ESs in the field of production planning and scheduling. The paper presents famous expert systems known in the literature and current applications, analyzes the relative benefits and concludes by sharing thoughts and estimations on ESs future prospects in this area. |
2,524 | Temporal Readout Noise Analysis and Reduction Techniques for Low-Light CMOS Image Sensors | In this paper, an analytical noise calculation is presented to derive the impact of process and design parameters on 1/f and thermal noise for a low-noise CMOS image sensor (CIS) readout chain. It is shown that dramatic noise reduction is obtained by using a thin-oxide transistor as the source follower of a typical 4T pixel. This approach is confirmed by a test chip designed in a 180-nm CIS process and embedding small arrays of the proposed new pixels together with state-ofthe- art 4T pixels for comparison. The new pixels feature a pitch of 7.5 mu m and a fill factor of 66%. A 0.4e-rms input-referred noise and a 185-mu V/e-conversion gain are obtained. Compared with state-of-the-art pixels, also present onto the test chip, the rms noise is divided by more than 2 and the conversion gain is multiplied by 2.2. |
2,525 | A spatiotemporal reconstruction of the C. elegans pharyngeal cuticle reveals a structure rich in phase-separating proteins | How the cuticles of the roughly 4.5 million species of ecdysozoan animals are constructed is not well understood. Here, we systematically mine gene expression datasets to uncover the spatiotemporal blueprint for how the chitin-based pharyngeal cuticle of the nematode Caenorhabditis elegans is built. We demonstrate that the blueprint correctly predicts expression patterns and functional relevance to cuticle development. We find that as larvae prepare to molt, catabolic enzymes are upregulated and the genes that encode chitin synthase, chitin cross-linkers, and homologs of amyloid regulators subsequently peak in expression. Forty-eight percent of the gene products secreted during the molt are predicted to be intrinsically disordered proteins (IDPs), many of which belong to four distinct families whose transcripts are expressed in overlapping waves. These include the IDPAs, IDPBs, and IDPCs, which are introduced for the first time here. All four families have sequence properties that drive phase separation and we demonstrate phase separation for one exemplar in vitro. This systematic analysis represents the first blueprint for cuticle construction and highlights the massive contribution that phase-separating materials make to the structure. |
2,526 | Proteomic and metabonomic analysis uncovering Enterovirus A71 reprogramming host cell metabolic pathway | Enterovirus A71 (EV71) infection can cause hand, foot, and mouth disease (HFMD) and severe neurological complications in children. However, the biological processes regulated by EV71 remain poorly understood. Herein, proteomics and metabonomics studies were conducted to uncover the mechanism of EV71 infection in rhabdomyosarcoma (RD) cells and identify potential drug targets. Differential expressed proteins from enriched membrane were analyzed by isobaric tags for relative and absolute quantitation (iTRAQ)-based proteomics technology. Twenty-six differential proteins with 1.5-fold (p < 0.05) change were detected, including 14 upregulated proteins and 12 downregulated proteins. The upregulated proteins are mainly involved in metabolic process, especially in the glycolysis pathway. Alpha-enolase (ENO1) protein was found to increase with temporal dependence following EV71 infection. The targeted metabolomics analysis revealed that glucose absorption and glycolysis metabolites were increased after EV71 infection. The glycolysis pathway was inhibited by knocking down ENO1 or the use of a glycolysis inhibitor (dichloroacetic acid [DCA]); and we found that EV71 infection was inhibited by depleting ENO1 or using DCA. Our study indicates that EV71 may reprogram glucose metabolism by activating glycolysis, and EV71 infection can be inhibited by interrupting the glycolysis pathway. ENO1 may be a potential target against EV71, and DCA could act as an inhibitor of EV71. |
2,527 | SAR Image Despeckling Using Continuous Attention Module | Speckle removal process is inevitable in the restoration of synthetic aperture radar (SAR) images. Several variant methods have been proposed for enhancing SAR images over the past decades. However, in recent studies, convolutional neural networks (CNNs) have been widely applied in SAR image despeckling because of their versatility in representation learning. Nonetheless, a fair number of textures of the images are still lost when despeckling using simple CNN structures. To solve this problem, an encoder-decoder architecture was previously proposed. Although this architecture extracts features on different scales and has been shown to yield state-of-the-art performance, it still learns representation locally, resulting in missing overall information of convolutional features. Therefore, we herein introduce a new method for SAR image despeckling (SAR-CAM), which improves the performance of an encoder-decoder CNN architecture by using various attention modules. Moreover, a context block is introduced at the minimum scale to capture multiscale information. The model is trained via a data-driven approach using the gradient descent algorithm with a combination of modified despeckling gain and total variation loss function. Experiments performed on simulated and real SAR data demonstrate that the proposed method achieves significant improvements over state-of-the-art methodologies. |
2,528 | ATM- and ATR-induced primary ciliogenesis promotes cisplatin resistance in pancreatic ductal adenocarcinoma | Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers because of its late diagnosis and chemoresistance. Primary cilia, the cellular antennae, are observed in most human cells to maintain development and differentiation. Primary cilia are gradually lost during the progression of pancreatic cancer and are eventually absent in PDAC. Here, we showed that cisplatin-resistant PDAC regrew primary cilia. Additionally, genetic or pharmacological disruption of primary cilia sensitized PDAC to cisplatin treatment. Mechanistically, ataxia telangiectasia mutated (ATM) and ATM and RAD3-related (ATR), tumor suppressors that initiate DNA damage responses, promoted the excessive formation of centriolar satellites (EFoCS) and autophagy activation. Disruption of EFoCS and autophagy inhibited primary ciliogenesis, sensitizing PDAC cells to cisplatin treatment. Collectively, our findings revealed an unexpected interplay among the DNA damage response, primary cilia, and chemoresistance in PDAC and deciphered the molecular mechanism by which ATM/ATR-mediated EFoCS and autophagy cooperatively regulate primary ciliogenesis. |
2,529 | PDAM: A Panoptic-Level Feature Alignment Framework for Unsupervised Domain Adaptive Instance Segmentation in Microscopy Images | In this work, we present an unsupervised domain adaptation (UDA) method, named Panoptic Domain Adaptive Mask R-CNN (PDAM), for unsupervised instance segmentation in microscopy images. Since there currently lack methods particularly for UDA instance segmentation, we first design a Domain Adaptive Mask R-CNN (DAM) as the baseline, with cross-domain feature alignment at the image and instance levels. In addition to the image- and instance-level domain discrepancy, there also exists domain bias at the semantic level in the contextual information. Next, we, therefore, design a semantic segmentation branch with a domain discriminator to bridge the domain gap at the contextual level. By integrating the semantic- and instance-level feature adaptation, our method aligns the cross-domain features at the panoptic level. Third, we propose a task re-weighting mechanism to assign trade-off weights for the detection and segmentation loss functions. The task re-weighting mechanism solves the domain bias issue by alleviating the task learning for some iterations when the features contain source-specific factors. Furthermore, we design a feature similarity maximization mechanism to facilitate instance-level feature adaptation from the perspective of representational learning. Different from the typical feature alignment methods, our feature similarity maximization mechanism separates the domain-invariant and domain-specific features by enlarging their feature distribution dependency. Experimental results on three UDA instance segmentation scenarios with five datasets demonstrate the effectiveness of our proposed PDAM method, which outperforms state-of-the-art UDA methods by a large margin. |
2,530 | Graphitic carbon nitride nanosheets as promising candidates for the detection of hazardous contaminants of environmental and biological concern in aqueous matrices | Monitoring of pollutant and toxic substances is essential for cleaner environment and healthy life. Sensing of various environmental contaminants and biomolecules such as heavy metals, pharmaceutics, toxic gases, volatile organic compounds, food toxins, and pathogens is of high importance to guaranty the good health and sustainable environment to community. In recent years, graphitic carbon nitride (g-CN) has drawn a significant amount of interest as a sensor due to its large surface area and unique electrochemical properties, low bandgap energy, high thermal and chemical stability, facile synthesis, nontoxicity, and electron rich property. Furthermore, the binary and ternary nanocomposites of graphitic carbon nitride further enhance their performance as a sensor making it a cost effective, fast, and reliable gadget for the purpose, and opens a wide area of research. Numerous reviews addressing a variety of applications including photocatalytic energy conversion, photoelectrochemical detection, and hydrogen evolution of graphitic carbon nitride have been documented to date. But a lesser attention has been devoted to the mechanistic approaches towards sensing of variety of pollutants concerned with environmental and biological aspects. Herein, we present the sensing features of graphitic carbon nitride towards the detection of various analytes including toxic heavy metals, pharmaceuticals, phenolic compounds, nitroaromatic compounds, volatile organic molecules, toxic gases, and foodborne pathogens. This review will undoubtedly provide future insights for researchers working in the field of sensors, allowing them to investigate the intriguing graphitic carbon nitride material as a sensing platform that is comparable to several other nanomaterials documented in the literature. Therefore, we hope that this study could reveal some intriguing sensing properties of graphitic carbon nitride, which may help researchers better understand how it interacts with contaminants of environmental and biological concern. Graphitic carbon nitride Nanosheets as Promising Analytical Tool for Environmental and Biological Monitoring of Hazardous Substances. |
2,531 | Environmental assessment of fabric wet processing from gate-to-gate perspective: Comparative study of weaving and materials | Textile industry has yet to be developed beyond low efficiency, high resources consumption, and toxic emissions, with wet processing process a dominant contributor to resources consumption and pollution emissions. Recognition of the environmental impact of the representative wet processing is essential to achieve eco-friendly development of textile industry. Using Life Cycle Assessment (LCA), this study addressed the environmental impacts of wet processing of woven/knitted cotton and polyester fabrics from 4 textile enterprises in China by deploying gate to gate system boundary. One ton of grey cloth was chosen as the functional unit. Eighteen midpoint impact categories and three endpoint impact categories were assessed via ReCiPe 2016 v1.1 (H) method. The results indicated "dyeing unit" as the dominant unit for all the impact categories at the midpoint, which was mainly derived from electricity consumed by cotton wet processing and detergents used in polyester wet processing. Among 4 different fabric wet processing, woven polyester wet processing exhibited the highest impact, while the least impact was assigned to knitted cotton. In the midpoint categories of water use, dyeing unit was also the major contributor in wet processing of knitted cotton (41.20 m3) and knitted polyester (44.70 m3). Pretreatment accounted for an overwhelming percentage of water use in woven cotton (48.00 %) and woven polyester (56.00 %). Woven polyester wet processing was also the most energy-intensive and resource-consuming industry among all scenarios, with a 3.37-fold higher fossil resource scarcity per ton of fabric compared with woven cotton. The results recommend measures for cleaner production in the wet processing. |
2,532 | Permanent central diabetes insipidus after traumatic brain injury. Case report and literature review | The authors report permanent central diabetes insipidus (CDI) in a patient after severe traumatic brain injury (TBI) in traffic accident. A 16-year-old boy entered to a medical facility in coma (GCS score 6) with the following diagnosis: acute TBI, severe cerebral contusion, subarachnoid hemorrhage, depressed comminuted cranial vault fracture, basilar skull fracture, visceral contusion. CDI was diagnosed in 3 days after injury considering polyuria and hypernatremia (155 mmol/l). Desmopressin therapy was initiated through a feeding tube. Thirst appeared when a patient came out of the coma after 21 days despite ongoing desmopressin therapy. Considering persistent thirst and polyuria, we continued desmopressin therapy in a spray form. Under this therapy, polyuria reduced to 3-3.5 liters per a day. Symptoms of CDI persisted in long-term period (2 years after TBI) while function of adenohypophysis was intact. This case demonstrates a rare development of permanent diabetes insipidus after TBI. CDI manifested only as polyuria and hypernatremia in coma. Thirst joined after recovery of consciousness. Probable causes of CDI were damage to neurohypophysis and partially injury of pituitary stalk because of extended basilar skull fracture and/or irreversible secondary lesion of hypothalamus following diffuse axonal damage after TBI. |
2,533 | Facing the Void: Overcoming Missing Data in Multi-View Imagery | In some scenarios, a single input image may not be enough to allow the object classification. In those cases, it is crucial to explore the complementary information extracted from images presenting the same object from multiple perspectives (or views) in order to enhance the general scene understanding and, consequently, increase the performance. However, this task, commonly called multi-view image classification, has a major challenge: missing data. In this paper, we propose a novel technique for multi-view image classification robust to this problem. The proposed method, based on state-of-the-art deep learning-based approaches and metric learning, can be easily adapted and exploited in other applications and domains. A systematic evaluation of the proposed algorithm was conducted using two multi-view aerial-ground datasets with very distinct properties. Results show that the proposed algorithm provides improvements in multi-view image classification accuracy when compared to state-of-the-art methods. |
2,534 | Edge-based color constancy | Color constancy is the ability to measure colors of objects independent of the color of the light source. A well-known color constancy method is based on the gray-world assumption which assumes that the average reflectance of surfaces in the world is achromatic. In this paper, we propose a new hypothesis for color constancy namely the gray-edge hypothesis, which assumes that the average edge difference in a scene is achromatic. Based on this hypothesis, we propose an algorithm for color constancy. Contrary to existing color constancy algorithms, which are computed from the zero-order structure of images, our method is based on the derivative structure of images. Furthermore, we propose a framework which unifies a variety of known (gray-world, max-RGB, Minkowski norm) and the newly proposed gray-edge and higher order gray-edge algorithms. The quality of the various instantiations of the framework is tested and compared to the state-of-the-art color constancy methods on two large data sets of images recording objects under a large number of different light sources. The experiments show that the proposed color constancy algorithms obtain comparable results as the state-of-the-art color constancy methods with the merit of being computationally more efficient. |
2,535 | A compression strategy for an efficient TSP-based microaggregation | The advent of decentralised systems and the continuous collection of personal data managed by public and private entities require the application of measures to guarantee the privacy of individuals. Due to the necessity to preserve both the privacy and the utility of such data, different techniques have been proposed in the literature. Microaggregation, a family of data perturbation methods, relies on the principle of k-anonymity to aggregate personal data records. While several microaggregation heuristics exist, those based on the Travelling Salesman Problem (TSP) have been shown to outperform the state of the art when considering the trade-off between privacy protection and data utility. However, TSP-based heuristics suffer from scalability issues. Intuitively, methods that may reduce the computational time of TSP-based heuristics may incur a higher information loss. Nevertheless, in this article, we propose a method that improves the performance of TSP-based heuristics and can be used in both small and large datasets effectively. Moreover, instead of focusing only on the computational time perspective, our method can preserve and sometimes reduce the information loss resulting from the microaggregation. Extensive experiments with different benchmarks show how our method is able to outperform the current state of the art, considering the trade-off between information loss and computational time. |
2,536 | Silicon Thyristors for Ultrahigh Power (GW) Applications | Evolution of thyristor technology and the design concepts, which brought and maintain the phase control thyristor (PCT) at the top of a power pyramid, are discussed. The state-of-the-art device concepts like electrically triggered thyristor and light triggered thyristor are described for voltage classes up to 8.5 kV and maximal on-state rated current of 6 kA. Main focus is laid on the PCTs for high-voltage direct current transmission, the enabler of power transmission beyond the 10-GW level. |
2,537 | Context model based edge preservation filter for impulse noise removal | In this article, a new edge preserving contextual model based image restoration technique is proposed for images affected by impulse noise. The proposed restoration technique consists of two stages: noisy pixel identification and restoration. Center sliding window is considered as current processing pixel for both noisy pixel identification and restoration. In the first stage of the proposed technique, we follow an absolute directional difference of the neighborhood pixels to identify the pixels those are affected by impulse noise. We propose an edge preserving contextual model to restore the noisy pixels. The noise correction stage of the proposed scheme depends on the context model of the noise-free pixels in the selected window. The parameters of the contextual model are obtained using a Gaussian kernel. The proposed algorithm is tested on nine benchmark test images. The evaluation of the proposed algorithm is carried out by comparing it against nine competitive state-of-the-art algorithms for impulse noise removal. The proposed algorithm is evaluated using Peak Signal to Noise Ratio (PSNR), Mean Structural Similarity Index (MSSIM), Non-shifted Edge Ratio (NSER) and Correlation Factor (CF) performance measures. Experimental results corroborate that the proposed algorithm provides better performance than the existing state-of-art impulse denoising methods. (C) 2017 Elsevier Ltd. All rights reserved. |
2,538 | Explicit Edge Inconsistency Evaluation Model for Color-Guided Depth Map Enhancement | Color-guided depth enhancement is used to refine depth maps according to the assumption that the depth edges and the color edges at the corresponding locations are consistent. In methods on such low-level vision tasks, the Markov random field (MRF), including its variants, is one of the major approaches that have dominated this area for several years. However, the assumption above is not always true. To tackle the problem, the state-of-the-art solutions are to adjust the weighting coefficient inside the smoothness term of the MRF model. These methods lack an explicit evaluation model to quantitatively measure the inconsistency between the depth edge map and the color edge map, so they cannot adaptively control the efforts of the guidance from the color image for depth enhancement, leading to various defects such as texture-copy artifacts and blurring depth edges. In this paper, we propose a quantitative measurement on such inconsistency and explicitly embed it into the smoothness term. The proposed method demonstrates promising experimental results compared with the benchmark and state-of-the-art methods on the Middlebury ToF-Mark, and NYU data sets. |
2,539 | Cultures of peace and the art of war in Saharan rock art | Based on the quality and abundance of its rock art, the Central Sahara constitutes a veritable open-air repository of extraordinary testimonies of the lives of Neolithic herders. How can we understand and interpret this rock art? Why the images? Why do the bovidian representations of daily life in the Saharan Neolithic with surprising realism give way to schematic images and cryptic imprints that express the existential uncertainties of "Round Head" societies confronted with a changing world? In distinguishing the myth, substance of the collective unconscious, from the mythological stories that it generates, the present author brings forth in successive stages the underlying logic of these astonishing compositions. Drawing on the combined methods of prehistoric archaeology, art history, and sociocultural anthropology, I illustrate the principles for an anthropology of rock art. Finally, in placing these results in the context of the prehistoric Saharan ecology, I indicate the potential causes of tension and conflict among the groups of pastoral nomads. Before aridity and desertification favored the emergence of a protohistoric society of merchants and warriors, the Bovidian groups established the conditions that allowed for the rise and maintenance of a grand pastoral civilization. The stories that captured the essence of this society are lost forever, but the mythological system that generated them remains fleetingly visible. (C) 2017 Elsevier Ltd and INQUA. All rights reserved. |
2,540 | Malignant peripheral nerve sheath tumor of the maxilla: Case report and review of the literature with emphasis on its poor prognosis | Malignant peripheral nerve sheath tumor (MPNST) is a spindle cell sarcoma with poor prognosis. Although patients with neurofibromatosis type 1 (NF1) have a higher risk of MPNST, it can also occur in the sporadic setting and may rarely arise centrally within bone. In this study, we present an extremely rare case of intraosseous MPNST of the maxilla arising in a 38-year-old female with no history of NF1. Despite radical surgery and postoperative radiotherapy, the patient died due to multiple distant metastases 1 year after treatment. According to the results of the literature analysis performed in this study, maxillary MPNST cases have worse clinical outcomes than general MPNSTs. In addition, it seems that NF1 and histological necrosis are poor prognostic indicators in patients with maxillary MPNST. |
2,541 | MFFN: An Underwater Sensing Scene Image Enhancement Method Based on Multiscale Feature Fusion Network | Vision-guided autonomous underwater vehicles based on remote sensing play an important role in ocean missions. However, some problems exist in underwater visual perception, such as color distortion, low contrast, and fuzzy details, which restrict the applications of underwater visual tasks. Most of the state-of-the-art image enhancement methods are still limited in scene adaptability, recovery accuracy, and real-time processing. To solve these problems, we propose an underwater sensing scene image enhancement method called a multiscale feature fusion network (MFFN). To extract the multiscale feature, the measure merging the feature extraction module, the feature fusion module, and the attention reconstruction module is designed. This measure can also enhance the adaptability and visual effect of the scene. Moreover, we propose multiple objective functions for supervised training to match the nonlinear mapping. Based on the qualitative and quantitative evaluations, the proposed method produces competitive performance compared with some state-of-the-art methods, and the perception and statistical quality of underwater images are enhanced effectively. |
2,542 | Characteristics of Early Mother-Infant and Father-Infant Interactions: A Comparison between Assisted Reproductive Technology and Spontaneous Conceiving Parents | This study aims to describe parents' and infant's interactive styles after assisted reproduction treatments (ART), to compare them with parent-infant interactions after spontaneous conception (SC), and to assess the effect of specific ART variables (cause of infertility, treatment type, and previous ART attempts) on interaction quality. The sample included 25 ART conceiving couples and 31 SC couples with their 3-months-old babies. Free parent-infant interactions (3-5 min) were coded using the CARE-Index, a video-based assessment scale that gives both dimensional (e.g., sensitivity, control, passivity) and categorical scores (sensitive, inept, at-risk) for parents and infants. Results showed a global similarity between groups in CARE-Index dimensions. Nevertheless, differences emerged in categorical scores, as the interactive patterns of ART parents were more frequently classified as "inept" and "at-risk" compared to SC parents. With regards to ART dyads only, infants conceived through intracytoplasmic sperm injection scored significantly lower to the dimension compulsivity and higher to passivity, compared to infants conceived through in vitro fertilization. Yet, infants conceived at the first ART cycle had significantly lower levels of difficulty than infants conceived after one ART attempt. These results speak about the existence of important parent-infant interactive differences related to conception modality and ART technique and suggest the need to implement support programs to promote more sensitive parenting styles. |
2,543 | Food Recipe Ingredient Substitution Ontology Design Pattern | This paper describes a notion of substitutions in food recipes and their ontology design pattern. We build upon state-of-the-art models for food and process. We also present scenarios and examples for the design pattern. Finally, the pattern is mapped to available and relevant domain ontologies and made publicly available at the ontologydesignpatterns.org portal. |
2,544 | Umpolung Synthesis of Pyridyl Ethers by BiV -Mediated O-Arylation of Pyridones | We report that O-selective arylation of 2- and 4-pyridones with arylboronic acids is affected by a modular, bismacycle-based system. The utility of this umpolung approach to pyridyl ethers, which is complementary to conventional methods based on SN Ar or cross-coupling, is demonstrated through the concise synthesis of Ki6783 and picolinafen, and the formal synthesis of cabozantib and golvatinib. Computational investigations reveal that arylation proceeds in a concerted fashion via a 5-membered transition state. The kinetically-controlled regioselectivity for O-arylation-which is reversed relative to previous BiV -mediated pyridone arylations-is attributed primarily to the geometric constraints imposed by the bismacyclic scaffold. |
2,545 | Phenomenology and dynamics of competitive ecosystems beyond the niche-neutral regimes | Structure, composition, and stability of ecological populations are shaped by the inter- and intraspecies interactions within their communities. It remains to be fully understood how the interplay of these interactions with other factors, such as immigration, controls the structure, the diversity, and the long-term stability of ecological systems in the presence of noise and fluctuations. We address this problem using a minimal model of interacting multispecies ecological communities that incorporates competition, immigration, and demographic noise. We find that a complete phase diagram exhibits rich behavior with multiple regimes that go beyond the classical "niche" and "neutral" regimes, extending and modifying the "rare biosphere" or "niche-like" dichotomy. In particular, we observe regimes that cannot be characterized as either niche or neutral where a multimodal species abundance distribution is observed. We characterize the transitions between the different regimes and show how these arise from the underlying kinetics of the species turnover, extinction, and invasion. Our model serves as a minimal null model of noisy competitive ecological systems, against which more complex models that include factors such as mutations and environmental noise can be compared. |
2,546 | A label-free electrochemical affisensor for cancer marker detection: The case of HER2 | In this paper, we report the development of a sensitive label-free impedimetric biosensor based on the use of affibody as bioreceptor and gold nanostructured screen-printed graphite as a sensor platform for the detection of human epidermal growth factor receptor 2 (HER2). The affisensor is realized by immobilizing a terminal cysteine-modified affibody on gold nanoparticles. The sensor was characterized by electrochemical techniques and scanning electron microscopy (SEM). Furthermore, surface plasmon resonance (SPR) technology was also applied to explore the potential of affibodies as small-molecule discriminating tools. Using optimized experimental conditions, a single-use affisensor showed a good analytical performance for HER2 detection from 0 to 40 μg/L. The estimated limit of detection was 6.0 μg/L. Finally, the realized affisensor was applied to human serum samples. |
2,547 | Neutral Grounding Resistor Monitoring State-of-the-Art | Neutral grounding resistors are used to overcome safety concerns and equipment stress by controlling transient overvoltages and limiting ground overcurrents. Failure of these apparatuses is an undetected event in unfaulted condition that causes many challenges in case of ground faults. Recently, various monitoring methods have emerged to solve this issue. The literature and current state of this art are the main targets of this research work, which classifies all existing methods into three categories based on the used measurement instruments and operation characteristics. In this article, each of these methods are explained briefly including the used measurement instruments, monitoring scheme, and few performance results. Further, the evolution trend of these methods is demonstrated as well as a thorough comparison based on their performance under various conditions. |
2,548 | A method for quick capital cost estimation of biorefineries beyond the state of the art | This paper presents the 'process blocks build-up estimating' method for the capital cost estimation of biorefineries at Technology Readiness Levels 2 to 3 with a -50% to +100% accuracy, corresponding to a Class 5 estimate. Through systematic cost modeling, the method introduces a modular approach to cost estimation by breaking down a biorefinery into its major process blocks and using separate cost power functions. Suitable cost parameters (exponents and reference capital costs) for 11 biochemical, chemical and thermochemical biorefinery types are developed, as well as reference block efficiencies for estimating the costs of biorefineries within and beyond the state of the art. A framework for uncertainty modeling is also proposed to decide on contingencies for a biorefinery investment. The cost models are addressed to the biorefinery community, from experimental chemists to process engineers and decision makers, to assist them in selecting optimal pathways and budgeting new projects. The modular estimation approach is illustrated with a simple example on a biodiesel plant and a first-of-a-kind polyhydroxybuturate (PHB) plant. (c) 2020 The Authors.Biofuels, Bioproducts and Biorefiningpublished by Society of Industrial Chemistry and John Wiley & Sons Ltd |
2,549 | Journey of the mouse primitive endoderm: from specification to maturation | The blastocyst is a conserved stage and distinct milestone in the development of the mammalian embryo. Blastocyst stage embryos comprise three cell lineages which arise through two sequential binary cell fate specification steps. In the first, extra-embryonic trophectoderm (TE) cells segregate from inner cell mass (ICM) cells. Subsequently, ICM cells acquire a pluripotent epiblast (Epi) or extra-embryonic primitive endoderm (PrE, also referred to as hypoblast) identity. In the mouse, nascent Epi and PrE cells emerge in a salt-and-pepper distribution in the early blastocyst and are subsequently sorted into adjacent tissue layers by the late blastocyst stage. Epi cells cluster at the interior of the ICM, while PrE cells are positioned on its surface interfacing the blastocyst cavity, where they display apicobasal polarity. As the embryo implants into the maternal uterus, cells at the periphery of the PrE epithelium, at the intersection with the TE, break away and migrate along the TE as they mature into parietal endoderm (ParE). PrE cells remaining in association with the Epi mature into visceral endoderm. In this review, we discuss our current understanding of the PrE from its specification to its maturation. This article is part of the theme issue 'Extraembryonic tissues: exploring concepts, definitions and functions across the animal kingdom'. |
2,550 | Time and Memory Efficient Online Piecewise Linear Approximation of Sensor Signals | Piecewise linear approximation of sensor signals is a well-known technique in the fields of Data Mining and Activity Recognition. In this context, several algorithms have been developed, some of them with the purpose to be performed on resource constrained microcontroller architectures of wireless sensor nodes. While microcontrollers are usually constrained in computational power and memory resources, all state-of-the-art piecewise linear approximation techniques either need to buffer sensor data or have an execution time depending on the segment's length. In the paper at hand, we propose a novel piecewise linear approximation algorithm, with a constant computational complexity as well as a constant memory complexity. Our proposed algorithm's worst-case execution time is one to three orders of magnitude smaller and its average execution time is three to seventy times smaller compared to the state-of-the-art Piecewise Linear Approximation (PLA) algorithms in our experiments. In our evaluations, we show that our algorithm is time and memory efficient without sacrificing the approximation quality compared to other state-of-the-art piecewise linear approximation techniques, while providing a maximum error guarantee per segment, a small parameter space of only one parameter, and a maximum latency of one sample period plus its worst-case execution time. |
2,551 | Deep Scattering Spectrum | A scattering transform defines a locally translation invariant representation which is stable to time-warping deformation. It extends MFCC representations by computing modulation spectrum coefficients of multiple orders, through cascades of wavelet convolutions and modulus operators. Second-order scattering coefficients characterize transient phenomena such as attacks and amplitude modulation. A frequency transposition invariant representation is obtained by applying a scattering transform along log-frequency. State-the-of-art classification results are obtained for musical genre and phone classification on GTZAN and TIMIT databases, respectively. |
2,552 | Combination of low-dose spinal anesthesia and epidural anesthesia as anesthetic management in patient with uncorrected Double Outlet Right Ventricle (DORV) underwent cesarean section | Pregnant patients with uncorrected Double Outlet Right Ventricle (DORV) undergoing cesarean section are challenging for anesthesiologists. We present a case of a 24-year-old woman with a gestational age of 30-32 weeks with DORV, ventricular septal defect, pulmonary hypertension, and stage C functional class III heart failure who was successfully managed using a combination of low-dose spinal anesthesia bupivacaine 0.5% 7.5 mg with adjuvant fentanyl 50 mcg and epidural ropivacaine 0.2%, and fentanyl 50 mcg TV 10 cc given 30 minutes after the birth of her baby. Hemodynamics was stable after low-dose spinal anesthesia and until the end of the operation. |
2,553 | DSP-CC-: I/O Efficient Parallel Computation of Connected Components in Billion-Scale Networks | Computing connected components is a core operation on graph data. Since billion-scale graphs cannot be resident in memory of a single server, several approaches based on distributed machines have recently been proposed. The representative methods are Hash-To-Min and PowerGraph. Hash-To-Min is the state-of-the art disk-based distributed method which minimizes the number of MapReduce rounds. PowerGraph is the-state-of-the-art in-memory distributed system, which is typically faster than the disk-based distributed one, however, requires a lot of machines for handling billion-scale graphs. In this paper, we propose an I/O efficient parallel algorithm for billion-scale graphs in a single PC. We first propose the Disk-based Sequential access-oriented Parallel processing (DSP) model that exploits sequential disk access in terms of disk I/Os and parallel processing in terms of computation. We then propose an ultra-fast disk-based parallel algorithm for computing connected components, DSP-CC, which largely improves the performance through sequential disk scan and page-level cache-conscious parallel processing. Extensive experimental results show that DSP-CC 1) computes connected components in billion-scale graphs using the limited memory size whereas in-memory algorithms can only support medium-sized graphs with the same memory size, and 2) significantly outperforms all distributed competitors as well as a representative disk-based parallel method. |
2,554 | Using a 29-mRNA Host Response Classifier To Detect Bacterial Coinfections and Predict Outcomes in COVID-19 Patients Presenting to the Emergency Department | Clinicians in the emergency department (ED) face challenges in concurrently assessing patients with suspected COVID-19 infection, detecting bacterial coinfection, and determining illness severity since current practices require separate workflows. Here, we explore the accuracy of the IMX-BVN-3/IMX-SEV-3 29 mRNA host response classifiers in simultaneously detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and bacterial coinfections and predicting clinical severity of COVID-19. A total of 161 patients with PCR-confirmed COVID-19 (52.2% female; median age, 50.0 years; 51% hospitalized; 5.6% deaths) were enrolled at the Stanford Hospital ED. RNA was extracted (2.5 mL whole blood in PAXgene blood RNA), and 29 host mRNAs in response to the infection were quantified using Nanostring nCounter. The IMX-BVN-3 classifier identified SARS-CoV-2 infection in 151 patients with a sensitivity of 93.8%. Six of 10 patients undetected by the classifier had positive COVID tests more than 9 days prior to enrollment, and the remaining patients oscillated between positive and negative results in subsequent tests. The classifier also predicted that 6 (3.7%) patients had a bacterial coinfection. Clinical adjudication confirmed that 5/6 (83.3%) of the patients had bacterial infections, i.e., Clostridioides difficile colitis (n = 1), urinary tract infection (n = 1), and clinically diagnosed bacterial infections (n = 3), for a specificity of 99.4%. Two of 101 (2.8%) patients in the IMX-SEV-3 "Low" severity classification and 7/60 (11.7%) in the "Moderate" severity classification died within 30 days of enrollment. IMX-BVN-3/IMX-SEV-3 classifiers accurately identified patients with COVID-19 and bacterial coinfections and predicted patients' risk of death. A point-of-care version of these classifiers, under development, could improve ED patient management, including more accurate treatment decisions and optimized resource utilization. IMPORTANCE We assay the utility of the single-test IMX-BVN-3/IMX-SEV-3 classifiers that require just 2.5 mL of patient blood in concurrently detecting viral and bacterial infections as well as predicting the severity and 30-day outcome from the infection. A point-of-care device, in development, will circumvent the need for blood culturing and drastically reduce the time needed to detect an infection. This will negate the need for empirical use of broad-spectrum antibiotics and allow for antibiotic use stewardship. Additionally, accurate classification of the severity of infection and the prediction of 30-day severe outcomes will allow for appropriate allocation of hospital resources. |
2,555 | The Beginnings of Scientific Psychiatric Twin Research: Luxenburger's 1928 "Preliminary Report on the Psychiatric Examination of a Series of Twins" | While reports of twin pairs concordant for insanity began to appear in the 19th century, the first modern psychiatric twin study that fulfilled Galton's 1875 promise of the value of the twin method was published by the German Psychiatrist and Geneticist Hans Luxenburger in 1928. Luxenburger introduced four major methodological advances: the use of representative sampling, proband-wise concordance, rigorous zygosity diagnoses, and age correction. He used a narrow Kraepelinian diagnostic approach diagnosis and ascertained twins hospitalized, on a specific day, in all large Bavarian asylums. We include a brief biography of Luxenburger, summarize the findings of his paper and provide a full English translation in the appendix. Luxenburger presents evidence that the frequency of twinning in those with severe mental illness were as expected and reports proband-wise concordance for probable and definite dementia praecox (MZ-76%, DZ-0%) and manic-depressive insanity (MZ-75%, DZ-0%). He also examined eccentricity and hyperthymic or hypothymic personality in the dementia praecox and manic-depressive pairs, respectively. Luxenburger's substantial contributions to the history of psychiatric genetics should be considered in the context of his intimate but ambivalent relationship with the racial-hygiene policy of the German National Socialists. |
2,556 | Development and Fabrication of an Innovative Smart Tool to Monitor the Impact Carving Process on Brittle Stones and Marble | The art of sculpting is related to the processing of brittle materials, such as granite, marble, and stone, and is implemented using percussive hand tools or rotational roughing tools. The outcome of percussion carving is still directly related to the technique, experience, and capacity of the sculptor. Any attempt to automate the art of sculpturing is exhausted in the subtraction method of brittle materials using a rotating tool. In the process of percussion carving, there is no equivalent expertise. In this work, we present the design, manufacturing (3D printing and CNC machining), and use of a smart, percussion carving tool, either manually by the hand of a sculptor, adjusted in a percussive pneumatic hammer, or guided by a digitally driven machine. The scope is to measure and record the technological variables and sizes that describe and document the carving process through the sensors and electronic devices that the smart tool incorporates, the development and programming of which was implemented for the purposes of this work. The smart carving tool was meticulously tested in various carving stones and stressing scenarios to test the functionality and efficacy of the tool. All the tests were successfully implemented according to the specifications set. |
2,557 | Robust face alignment by dual-attentional spatial-aware capsule networks | Face alignment in-the-wild still faces great challenges due to that i) partial occlusion blurs the inter features spatial relations of faces and ii) traditional CNN makes the network more difficult to capture the spatial positional relations between landmarks. To address the issues above, we propose a face alignment algorithm named Dual-attentional Spatial-aware Capsule Network (DSCN). Firstly, the spatial-aware module builds a more accurate inter-features spatial constrained model with the hourglass capsule network (HGCaps) as the backbone, which can effectively enhance its robustness against occlusions. Then, two sorts of attention mechanisms, namely capsule attention and spatial attention, are added to the attention-guided module to make the network focus more on the advantageous features and suppress other unrelated ones for more effective f eature recalibration. Our method achieves 1.08% failure rate on the COFW dataset, which is much lower than the current state-of-the-art algorithms. The mean error under 300W dataset and WFLW dataset are respectively 3.91% and 5.66%, which shows that DSCN is more robust to occlusion and outperforms state-of-the-art methods in the literature. (c) 2021 Elsevier Ltd. All rights reserved. |
2,558 | A Totipotent "All-In-One" Peptide Sequentially Blocks Immune Checkpoint and Reverses the Immunosuppressive Tumor Microenvironment | Immune checkpoint blockade combined with reversal of the immunosuppressive tumor microenvironment (TME) can dramatically enhance anti-tumor immunity, which can be achieved by using multiple-agent therapy. However, the optimal dose and order of administration of different agents remain elusive. To address this dilemma, multiple agents are often grafted together to construct "all-in-one" totipotent drugs, but this usually comes at the cost of a lack of synergy between the agents. Herein, by comprehensively analyzing the conserved sites of the immune checkpoint and TME drug targets, peptide secondary structures, assembly properties, and other physicochemical properties, a high-content peptide library is designed. By using the "3D-molecular-evolution" screening strategy, an efficient and totipotent "all-in-one" peptide (TAP) is obtained, which possesses the abilities of self-assembling, blocking the PD-1/PD-L1 axis, inhibiting Rbm38-eIF4E complex formation, and activating p53. It is shown that in mice treated with TAP, with either subcutaneous tumors or patient-derived xenografts, PD-L1 is blocked, with increased activation of both T and NK cells whilst reversing the immunosuppressive TME. Moreover, TAP can mitigate tumor activity and suppress tumor growth, showing superior therapeutic effect over antibody-based drugs. |
2,559 | Emergence and the art system 'plus minus now' | Emergence is discussed in the context of a practice-based study of interactive art and a new taxonomy of emergence is proposed. The interactive art system 'plus minus now' is described and its relationship to emergence is discussed. 'Plus minus now' uses a novel method for instantiating emergent shapes. A preliminary investigation of this art system has been conducted and reveals the creation of temporal compositions by a participant. These temporal compositions and the emergent shapes are described using the taxonomy of emergence. Characteristics of emergent interactions and the implications of designing for them are discussed. (C) 2008 Elsevier Ltd. All rights reserved. |
2,560 | Main product detection with graph networks for fashion | Computer vision has established a foothold in the online fashion retail industry. Main product detection is a crucial step of vision-based fashion product feed parsing pipelines, focused on identifying the bounding boxes that contain the product being sold in the gallery of images of the product page. The current state-of-the-art approach does not leverage the relations between regions in the image, and treats images of the same product independently, therefore not fully exploiting visual and product contextual information. In this paper, we propose a model that incorporates Graph Convolutional Networks (GCN) that jointly represent all detected bounding boxes in the gallery as nodes. We show that the proposed method is better than the state-of-the-art, especially, when we consider the scenario where title-input is missing at inference time and for cross-dataset evaluation, our method outperforms previous approaches by a large margin. |
2,561 | LIGHT IN ARCHITECTURE OF NEW STATIONS OF THE MOSCOW UNDERGROUND | An important role in construction of the underground architectural space is given to its lighting solutions. It should be remembered that the Moscow Underground is a huge power-consuming system. As of January 2008, there are about four hundred thousand light points at metro stations, and more than one hundred eighty thousand in section tunnels. When designing new underground lines and station ensembles, as well as when maintaining already operating stations, continuous modernization of lighting equipment is performed. Much attention is devoted to energy saving. |
2,562 | Spatial Statistics for Segmenting Histological Structures in H&E Stained Tissue Images | Segmenting a broad class of histological structures in transmitted light and/or fluorescence-based images is a prerequisite for determining the pathological basis of cancer, elucidating spatial interactions between histological structures in tumor microenvironments (e.g., tumor infiltrating lymphocytes), facilitating precision medicine studies with deep molecular profiling, and providing an exploratory tool for pathologists. This paper focuses on segmenting histological structures in hematoxylin-and eosin-stained images of breast tissues, e.g., invasive carcinoma, carcinoma in situ, atypical and normal ducts, adipose tissue, and lymphocytes. We propose two graph-theoretic segmentation methods based on local spatial color and nuclei neighborhood statistics. For benchmarking, we curated a data set of 232 high-power field breast tissue images together with expertly annotated ground truth. To accurately model the preference for histological structures (ducts, vessels, tumor nets, adipose, etc.) over the remaining connective tissue and non-tissue areas in ground truth annotations, we propose a new region-based score for evaluating segmentation algorithms. We demonstrate the improvement of our proposed methods over the state-of-the-art algorithms in both region-and boundary-based performance measures. |
2,563 | A Novel Quasi-Newton Method for Composite Convex Minimization | A fast parallelable Jacobi iteration type optimization method for non-smooth convex composite optimization is presented. Traditional gradient-based techniques cannot solve the problem. Smooth approximate functions are attempted to be used as a replacement of those non-smooth terms without compromising the accuracy. Recently, proximal mapping concept has been introduced into this field. Techniques which utilize proximal average based proximal gradient have been used to solve the problem. The state-of-art methods only utilize first-order information of the smooth approximate function. We integrate both first and second-order techniques to use both first and second-order information to boost the convergence speed. A convergence rate with a lower bound of O(1/k(2)) is achieved by the proposed method and a super-linear convergence is enjoyed when there is proper second-order information. In experiments, the proposed method converges significantly better than the state of art methods which enjoy O(1/k) convergence. (C) 2021 Elsevier Ltd. All rights reserved. |
2,564 | A stop-and-start adaptive cellular genetic algorithm for mobility management of GSM-LTE cellular network users | The optimisation of the user tracking process is one of the most challenging tasks in today's advanced cellular networks. In this paper, we propose a new low-complexity adaptive cellular genetic algorithm to solve this problem. The proposed approach uses a torus-like structured population of candidate solutions and regulates interactions inside it by using a bi-dimensional neighbourhood. It also automatically adapts the algorithm's parameters and regenerates the algorithm's population using two algorithmically light operators. In order to draw reliable conclusions and perform an encompassing assessment, extensive experiments have been conducted on 25 differently-sized realistic networks. The proposed approach has been compared against 26 state-of-the-art algorithms previously designed to solve the mobility management problem, and a thorough statistical analysis of results has been performed. The obtained results have shown that our proposal is more efficient and algorithmically less complex than most of the state-of-the-art solvers. (C) 2018 Elsevier Ltd. All rights reserved. |
2,565 | Molecular characterization of SUT Gene Family in Solanaceae with emphasis on expression analysis of pepper genes during development and stresses | Sucrose, an essential carbohydrate, is transported from source to sink organs in the phloem and is involved in a variety of physiological and metabolic processes in plants. Sucrose transporter proteins (SUTs) may play significant parts in the phloem loading and unloading of sucrose. In our study, the SUT gene family was identified in four Solanaceae species (Capsicum annuum, Solanum lycopersicum, S. melongena, and S. tuberosum) and other 14 plant species ranged from lower and high plants. The comprehensive analysis was performed by integration of chromosomal distribution, gene structure, conserved motifs, evolutionary relationship and expression profiles during pepper growth under stresses. Chromosome mapping revealed that SUT genes in Solanaceae were distributed on chromosomes 4, 10 and 11. Gene structure analysis showed that the subgroup 1 members have the same number of introns and exons. All the SUTs had 12 transmembrane structural domains exception from CaSUT2 and SmSUT2, indicating that a structure variation might occurred among the Solanaceae SUT proteins. We also found a total of 20 conserved motifs, with over half of them shared by all SUT proteins, and the SUT proteins from the same subgroup shared common motifs. Phylogenetic analysis divided a total of 72 SUT genes in the plant species tested into three groups, and subgroup 1 might have diverged from a single common ancestor prior to the mono-dicot split. Finally, expression levels of CaSUTs were induced significantly under heat, cold, and salt treatments, indicating diverse functions of the CaSUTs to adapt to adverse environments. |
2,566 | Temporal scaling of human scalp-recorded potentials | Much of human behavior is governed by common processes that unfold over varying timescales. Standard event-related potential analysis assumes fixed-duration responses relative to experimental events. However, recent single-unit recordings in animals have revealed neural activity scales to span different durations during behaviors demanding flexible timing. Here, we employed a general linear modeling approach using a combination of fixed-duration and variable-duration regressors to unmix fixed-time and scaled-time components in human magneto-/electroencephalography (M/EEG) data. We use this to reveal consistent temporal scaling of human scalp-recorded potentials across four independent electroencephalogram (EEG) datasets, including interval perception, production, prediction, and value-based decision making. Between-trial variation in the temporally scaled response predicts between-trial variation in subject reaction times, demonstrating the relevance of this temporally scaled signal for temporal variation in behavior. Our results provide a general approach for studying flexibly timed behavior in the human brain. |
2,567 | A Fully Automated Multimodal MRI-Based Multi-Task Learning for Glioma Segmentation and IDH Genotyping | The accurate prediction of isocitrate dehydrogenase (IDH) mutation and glioma segmentation are important tasks for computer-aided diagnosis using preoperative multimodal magnetic resonance imaging (MRI). The two tasks are ongoing challenges due to the significant inter-tumor and intra-tumor heterogeneity. The existing methods to address them are mostly based on single-task approaches without considering the correlation between the two tasks. In addition, the acquisition of IDH genetic labels is expensive and costly, resulting in a limited number of IDH mutation data for modeling. To comprehensively address these problems, we propose a fully automated multimodal MRI-based multi-task learning framework for simultaneous glioma segmentation and IDH genotyping. Specifically, the task correlation and heterogeneity are tackled with a hybrid CNN-Transformer encoder that consists of a convolutional neural network and a transformer to extract the shared spatial and global information learned from a decoder for glioma segmentation and a multi-scale classifier for IDH genotyping. Then, a multi-task learning loss is designed to balance the two tasks by combining the segmentation and classification loss functions with uncertain weights. Finally, an uncertainty-aware pseudo-label selection is proposed to generate IDH pseudo-labels from larger unlabeled data for improving the accuracy of IDH genotyping by using semi-supervised learning. We evaluate our method on a multi-institutional public dataset. Experimental results show that our proposed multi-task network achieves promising performance and outperforms the single-task learning counterparts and other existing state-of-the-art methods. With the introduction of unlabeled data, the semi-supervised multi-task learning framework further improves the performance of glioma segmentation and IDH genotyping. The source codes of our framework are publicly available at https://github.com/miacsu/MTTU-Net.git. |
2,568 | Fast Parallel MR Image Reconstruction via B1-Based, Adaptive Restart, Iterative Soft Thresholding Algorithms (BARISTA) | Sparsity-promoting regularization is useful for combining compressed sensing assumptions with parallel MRI for reducing scan time while preserving image quality. Variable splitting algorithms are the current state-of-the-art algorithms for SENSE-type MR image reconstruction with sparsity-promoting regularization. These methods are very general and have been observed to work with almost any regularizer; however, the tuning of associated convergence parameters is a commonly-cited hindrance in their adoption. Conversely, majorize-minimize algorithms based on a single Lipschitz constant have been observed to be slow in shift-variant applications such as SENSE-type MR image reconstruction since the associated Lipschitz constants are loose bounds for the shift-variant behavior. This paper bridges the gap between the Lipschitz constant and the shift-variant aspects of SENSE-type MR imaging by introducing majorizing matrices in the range of the regularizer matrix. The proposed majorize-minimize methods (called BARISTA) converge faster than state-of-the-art variable splitting algorithms when combined with momentum acceleration and adaptive momentum restarting. Furthermore, the tuning parameters associated with the proposed methods are unitless convergence tolerances that are easier to choose than the constraint penalty parameters required by variable splitting algorithms. |
2,569 | Wavefront Marching Methods: A Unified Algorithm to Solve Eikonal and Static Hamilton-Jacobi Equations | This paper presents a unified propagation method for dealing with both the classic Eikonal equation, where the motion direction does not affect the propagation, and the more general static Hamilton-Jacobi equations, where it does. While classic Fast Marching Method (FMM) techniques achieve the solution to the Eikonal equation with a O(M log M) (or O(M) assuming some modifications), solving the more general static Hamilton-Jacobi equation requires a higher complexity. The proposed framework maintains the O(M log M) complexity for both problems, while achieving higher accuracy than available state-of-the-art. The key idea behind the proposed method is the creation of 'mini wave-fronts', where the solution is interpolated to minimize the discretization error. Experimental results show how our algorithm can outperform the state-of-the-art both in precision and computational cost. |
2,570 | 3D face-model reconstruction from a single image: A feature aggregation approach using hierarchical transformer with weak supervision | Convolutional Neural Networks (CNN) have gained popularity as the de-facto model for any computer vision task. However, CNN have drawbacks, i.e. they fail to extract long-range perceptions in images. Due to their ability to capture long-range dependencies, transformer networks are adopted in computer vision applications, where they show state-of-the-art (SOTA) results in popular tasks like image classification, instance segmentation, and object detection. Although they gained ample attention, transformers have not been applied to 3D face reconstruction tasks. In this work, we propose a novel hierarchical transformer model, added to a feature pyramid aggregation structure, to extract the 3D face parameters from a single 2D image. More specifically, we use pre-trained Swin Transformer backbone networks in a hierarchical manner and add the feature fusion module to aggregate the features in multiple stages. We use a semi-supervised training approach and train our model in a supervised way with the 3DMM parameters from a publicly available dataset and unsupervised training with a differential renderer on other parameters like facial keypoints and facial features. We also train our network on a hybrid unsupervised loss and compare the results with other SOTA approaches. When evaluated across two public datasets on face reconstruction and dense 3D face alignment tasks, our method can achieve comparable results to the current SOTA performance and in some instances do better than the SOTA methods. A detailed subjective evaluation also shows that our method performs better than the previous works in realism and occlusion resistance. |
2,571 | Percutaneous biopsy of musculoskeletal tumors and the potential for needle tract seeding: technical considerations, current controversies, and outcomes | Multidisciplinary communication and planning between the musculoskeletal radiologist and orthopedic oncologist are essential for proper biopsy planning when a primary musculoskeletal malignancy is suspected. Image-guided percutaneous biopsy allows for real-time visualization of the biopsy needle and surrounding structures, combining high diagnostic accuracy with safety and cost-effectiveness. However, determining a surgically optimal biopsy trajectory for a mass can be technically challenging due to critical surrounding anatomy or challenging needle approach angles. Inappropriately placed biopsies can have serious repercussions on patient function and oncological survival. The potential for needle tract seeding and local recurrence after biopsy of sarcoma has been central to the debate regarding the need for excision of the biopsy tract. This multidisciplinary review highlights current controversies in the field, including the issue of core needle biopsy tracts and their excision, technical considerations and advances in image-guidance in the setting of challenging biopsies, advances in histopathological diagnostics with implications for targeted therapy in sarcoma, as well as surgical and oncological outcomes after needle tract biopsy. |
2,572 | Neutrophil Extracellular Traps (NET) and SARS-CoV-2 | NETosis is a type of neutrophil extinction that outcome in the liberation of extracellular chromatin and protein accumulation, which contains antiviral proteins, produced by an external pathogen. Neutrophils can show bipolar action in special circumstances. This event, along with other circumstances, involves COVID-19. Neutrophil extracellular traps (NETs) are involved in the pathogenesis of COVID-19 by creating a pro-inflammatory and pre-coagulation state that leads to numerous organ losses. This form of host defense, which is promoted by neutrophils, is closely related to the known cytokine storm in severe COVID-19 patients. Hence, these two elements reveal possibly the treatment of the target for SARS-CoV-2 infections intense. |
2,573 | SARS-CoV-2 removal by mix matrix membrane: A novel application of artificial neural network based simulation in MATLAB for evaluating wastewater reuse risks | The COVID-19 outbreak led to the discovery of SARS-CoV-2 in sewage; thus, wastewater treatment plants (WWTPs) could have the virus in their effluent. However, whether SARS-CoV-2 is eradicated by sewage treatment is virtually unknown. Specifically, the objectives of this study include (i) determining whether a mixed matrixed membrane (MMM) is able to remove SARS-CoV-2 (polycarbonate (PC)-hydrous manganese oxide (HMO) and PC-silver nanoparticles (Ag-NP)), (ii) comparing filtration performance among different secondary treatment processes, and (iii) evaluating whether artificial neural networks (ANNs) can be employed as performance indicators to reduce SARS-CoV-2 in the treatment of sewage. At Shariati Hospital in Mashhad, Iran, secondary treatment effluent during the outbreak of COVID-19 was collected from a WWTP. There were two PC-Ag-NP and PC-HMO processes at the WWTP targeted. RT-qPCR was employed to detect the presence of SARS-CoV-2 in sewage fractions. For the purposes of determining SARS-CoV-2 prevalence rates in the treated effluent, 10 L of effluent specimens were collected in middle-risk and low-risk treatment MMMs. For PC-HMO, the log reduction value (LRV) for SARS-CoV-2 was 1.3-1 log10 for moderate risk and 0.96-1 log10 for low risk, whereas for PC-Ag-NP, the LRV was 0.99-1.3 log10 for moderate risk and 0.94-0.98 log10 for low risk. MMMs demonstrated the most robust absorption performance during the sampling period, with the least significant LRV recorded in PC-Ag-NP and PC-HMO at 0.94 log10 and 0.96 log10, respectively. |
2,574 | Lithium Enolate with a Lithium-Alkyne Interaction in the Enantioselective Construction of Quaternary Carbon Centers: Concise Synthesis of (+)-Goniomitine | We report a method for direct enantioselective alkylation of 3-alkynoic and 2,3-alkendioic acids that form quaternary stereogenic centers, and application of this method to the total enantioselective synthesis of a complex alkaloid (+)-goniomitine. The methods were effective in the alkylation of both 3-alkynoic acids, 2,3-alkendioic acids substrates with a broad range of heterocyclic and functionalized alkyl group substituents. Accompanying crystallographic studies provide mechanistic insight into the structure of well-defined chiral aggregates, highlighting cation-π interactions between lithium and alkyne groups. |
2,575 | Image Restoration and Reconstruction using Targeted Plug-and-Play Priors | Leveraging current state-of-the-art denoisers to tackle other inverse problems in imaging is a challenging task, which has recently been the topic of significant research effort. In this paper, we present several contributions to this research front, based on two fundamental building blocks: 1) the recently proposed plug-and-play framework, which allows combining iterative algorithms for imaging inverse problems with state-of-the-art image denoisers, used in black-box fashion; and 2) patch-based denoisers, using Gaussian mixture models (GMM). We exploit the adaptability of GMM to learn class-adapted denoisers, which opens the door to embedding a patch classification step in the algorithmic loop, yielding simultaneous restoration and semantic segmentation. We apply the proposed approach to several standard imaging inverse problems (deblurring, compressive sensing reconstruction, and super-resolution), obtaining results that are competitive with the state of the art. |
2,576 | Sustainable Heritage Management: Exploring Dimensions of Pull and Push Factors | While determining sustainable heritage development, it is important to consider how heritage satisfies human needs. The purpose of this study is to explore the pull and push factors in heritage tourism. This study generated 38 initial items of pull factor and 18 initial items of push factor toward heritage tourism to assess the significance of items influencing people's decision to visit heritage sites. The study obtained 332 valid questionnaires to implement exploratory factor analysis to capture the pull and push factors. Four pull factors with 15 items and 2 push factors with 9 items were extracted. The pull factors consisted of heritage architecture, art activity, wide nature, and regional attraction, while the push factors comprised recreational benefits and long-term values. The study suggests that the heritage's outdoor environment should be planned through wide landscaping and natural elements, while art activities can be promoted to enhance attractiveness. |
2,577 | Psychosocial Support Programme Improves Adherence and Health Systems Experiences for Adolescents on Antiretroviral Therapy in Mpumalanga Province, South Africa | (1) Background: Psychosocial support (PSS) plays a significant role in persistent adherence to and retention in antiretroviral therapy (ART) for adolescents living with the human immunodeficiency virus (ALHIV). This paper qualitatively explores the experiences of ALHIV on ART, who participated in a PSS programme in five public primary healthcare facilities in Mpumalanga Province in South Africa during the COVID-19 pandemic. (2) Methods: Data were collected through 24 focus group discussions with 173 ALHIV on ART and subjected to inductive thematic analysis. Informed consent was obtained before all data collection. (3) Results: The PSS programme facilitated the process of full HIV disclosure to these adolescents with the support of parents/guardians while motivating adherence through peer support groups and health education for improved treatment literacy. Participants reported positive health systems experiences, improved healthcare provider-client relations, and prompt access to health services. (4) Conclusions: The PSS programme successfully kept ALHIV engaged in ART care despite the health service disruptions encountered during the COVID-19 pandemic. We recommend rigorous evaluation of the effects of the PSS intervention on adherence to and retention in ART among ALHIV in HIV-endemic settings. |
2,578 | Fatal low-dose methotrexate toxicity: A case report and literature review | Methotrexate (MTX) is a chemotherapeutic agent that acts primarily by inhibiting the folic acid cycle. In addition to its application for treating malignancies, MTX is also used to treat chronic inflammatory diseases including psoriasis. Adverse effects have been reported even at low doses (up to 25 mg/week), and there is risk of toxicity in the form of myelosuppression, hepatotoxicity, or pulmonary fibrosis. Here, we report a case of a 67-year-old male with a past medical history of end stage renal disease on peritoneal dialysis and moderate-to-severe psoriasis with psoriatic arthritis presented with abdominal pain, diarrhea, rash, mucositis, and mucocutaneous ulcers and erosions. The patient was taking methotrexate 10 mg weekly without folic acid supplementation and was found to be pancytopenic. Despite treatment, the patient developed multiorgan failure and passed away after 16 days of hospitalization. Myelosuppression is considered the most serious side effect with the highest risk of mortality. Risk factors for toxicity include renal insufficiency, advanced age, lack of folate supplementation, drug interactions, and medication errors. Importantly, serum levels of MTX do not correlate with toxicity; therefore, folinic acid rescue therapy should be started as soon as MTX toxicity is suspected. MTX toxicity is rare with low dose, proper dose scheduling, and adherence to the recommended guidelines. It is imperative that physicians considering therapy with low dose MTX for dermatologic indications take into consideration a patient's risk factors for toxicity and monitor appropriately. |
2,579 | Convolver Design and Convolve-Accumulate Unit Design for Low-Power Edge Computing | Convolution operations have a significant influence on the overall performance of a convolutional neural network, especially in edge-computing hardware design. In this paper, we propose a low-power signed convolver hardware architecture that is well suited for low-power edge computing. The basic idea of the proposed convolver design is to combine all multipliers' final additions and their corresponding adder tree to form a partial product matrix (PPM) and then to use the reduction tree algorithm to reduce this PPM. As a result, compared with the state-of-the-art approach, our convolver design not only saves a lot of carry propagation adders but also saves one clock cycle per convolution operation. Moreover, the proposed convolver design can be adapted for different dataflows (including input stationary dataflow, weight stationary dataflow, and output stationary dataflow). According to dataflows, two types of convolve-accumulate units are proposed to perform the accumulation of convolution results. The results show that, compared with the state-of-the-art approach, the proposed convolver design can save 15.6% power consumption. Furthermore, compared with the state-of-the-art approach, on average, the proposed convolve-accumulate units can reduce 15.7% power consumption. |
2,580 | Minimally invasive posterior cervical foraminotomy versus anterior cervical discectomy and fusion for cervical radiculopathy: a meta-analysis | With the recent development of minimally invasive techniques, minimally invasive posterior cervical foraminotomy (MIS-PCF) has become increasingly popular as a minimally invasive method to treat cervical radiculopathy. However, there are still controversies about whether MIS-PCF is superior to anterior cervical discectomy and fusion (ACDF). The purpose of this study is to evaluate the therapeutic effects of MIS-PCF and ACDF on unilateral cervical radiculopathy without myelopathy. We searched PubMed, Embase, the Cochrane Library, and Scopus comprehensively using the terms related to MIS-PCF. Two reviewers independently evaluated the potential studies, and extracted and analyzed the data of operation time, hospital stay, neck disability index (NDI) score, visual analog scale for neck pain (VAS-neck) and arm pain (VAS-arm) scores, reoperation rate, and complications. Seven studies with 1175 patients were included. The study population was 53.5% male, with a mean age of 48.9. MIS-PCF presented a significantly shorter postoperative hospitalization time compared to ACDF, while the operation time, complication/reoperation rate, and VAS-arm, VAS-neck, and NDI scores were comparable between the two cohorts. In North America, the average cost of MIS-PCF is lower than ACDF. Thus, we suggest that MIS-PCF is an alternative to ACDF for selected patients. |
2,581 | Management of perioperative pain after TKA | Postoperative pain is the prime obstacle to recovery of motion and return to activity after total knee arthroplasty (TKA). Combating pain is a key point in enhanced recovery after surgery (ERAS) protocols. Outcome depends on the efficacy of pain relief, making it a major issue. The pain originates locally in the knee and also remotely via neural pathways. Regression can be slow, over several months. Pain may sometimes be definitive, to a varying degree. Pain should be managed at each step of ERAS, from the preoperative period to the last follow-up consultation, and most especially during the perioperative phase. Pain needs to be anticipated and limited for as long as necessary. The impact of analgesics should be enhanced by means of potentiators. Some are administered by general route, sometimes preoperatively; others are applied locally, directly in the surgical site by local injection, or close to the nerves, to reduce painful stimuli. The two main principles of pain management are preventive analgesia and multimodal analgesia associating various molecules and routes. |
2,582 | A nondestructive dendrochronological study on japanese wooden shinto art sculptures using micro-focus X-ray Computed Tomography (CT) Reviewing two methods for scanning objects of different sizes | This paper discusses a dendrochronological approach to studying works of art associated with Shintoism, an indigenous religion of Japan. Chronological studies of Shinto artwork are, by comparison, lagging behind the studies on artwork associated with the other primary religion of Japan, Buddhism. This author believes that a scientific approach, such as dendrochronology, could play an effective part in narrowing this gap. In this experiment, we conducted a series of nondestructive imaging of wooden Shinto sculptures, utilizing a micro-focus X-ray Computed Tomography (CT) system, and performed tree-ring width measurements using digital image measurement software to obtain dendrochronological information. In terms of scanning operations, one of two methods was used according to the size of the object under review. The larger object, a statue of a guardian lion-dog (Komainu), was dendrochronologically dated to 1581, and the smaller deity statues were dated 1178. The dendrochronological data gained through this experiment will be an extremely valuable resource for future studies on Shinto artwork in Japan. (C) 2016 Elsevier GmbH. All rights reserved. |
2,583 | Vision Robot Path Control Based on Artificial Intelligence Image Classification and Sustainable Ultrasonic Signal Transformation Technology | The unsupervised algorithm of artificial intelligence (AI), named ART (Adaptive Resonance Theory), is used to first roughly classify an image, that is, after the image is processed by the edge filtering technology, the image window is divided into 25 square areas of 5 rows and 5 columns, and then, according to the location of the edge of the image, it determines whether the robot should go straight (represented by S), turn around (represented by A), stop (T), turn left (represented by L), or turn right (represented by R). Then, after sustainable ultrasonic signal acquisition and transformation into digital signals are completed, the sustainable supervised neural network named SGAFNN (Supervised Gaussian adaptive fuzzy neural network) will perform an optimal path control that can accurately control the traveling speed and turning of the robot to avoid hitting walls or obstacles. Based on the above, this paper proposes the use of the ART operation after image processing to judge the rough direction, followed by the use of the ultrasonic signal to carry out the sustainable development of artificial intelligence and to carry out accurate speed and direction SGAFNN control to avoid obstacles. After simulation and practical evaluations, the proposed method is proved to be feasible and to exhibit good performance. |
2,584 | Hierarchical approach to optimization of parallel matrix multiplication on large-scale platforms | Many state-of-the-art parallel algorithms, which are widely used in scientific applications executed on high-end computing systems, were designed in the twentieth century with relatively small-scale parallelism in mind. Indeed, while in 1990s a system with few hundred cores was considered a powerful supercomputer, modern top supercomputers have millions of cores. In this paper, we present a hierarchical approach to optimization of message-passing parallel algorithms for execution on large-scale distributed-memory systems. The idea is to reduce the communication cost by introducing hierarchy and hence more parallelism in the communication scheme. We apply this approach to SUMMA, the state-of-the-art parallel algorithm for matrix-matrix multiplication, and demonstrate both theoretically and experimentally that the modified Hierarchical SUMMA significantly improves the communication cost and the overall performance on large-scale platforms. |
2,585 | Integrated Passive Devices and Switching Circuit Design for a 3D DC/DC Converter up to 60 V | This work presents the design and test of a switched-cap 3D DC/DC converter able to work up to 60V. The switches and the control circuits are integrated single-chip in a high-voltage (HV) MOS technology, and the passive devices are stacked on top of the chip. As an innovation versus the state-of-the-art, the work first presents the design of integrated passive devices, based on through silicon vias (TSV) MOS-compatible technology, which are suitable for switching converter applications up to 60V. Then, the implementation and experimental characterization of the switched-cap 3D DC/DC is proposed, with the silicon TSV capacitors stacked on top of the 0.35 mu m HV-MOS die. Compared with the state-of-the-art, the proposed 3D DC/DC converter is a compact circuit, able to directly regulate a wide input voltage range (from 6V to 60V) to a 5V, 2W output. Hence, it is suitable to supply low-power loads, such as control units and/or sensors, directly from the 48V power line available in hybrid vehicles or telecom and networking systems. |
2,586 | Stratified pooling based deep convolutional neural networks for human action recognition | Video based human action recognition is an active and challenging topic in computer vision. Over the last few years, deep convolutional neural networks (CNN) has become the most popular method and achieved the state-of-the-art performance on several datasets, such as HMDB-51 and UCF-101. Since each video has a various number of frame-level features, how to combine these features to acquire good video-level feature becomes a challenging task. Therefore, this paper proposed a novel action recognition method named stratified pooling, which is based on deep convolutional neural networks (SP-CNN). The process is mainly composed of five parts: (i) fine-tuning a pre-trained CNN on the target dataset, (ii) frame-level features extraction; (iii) the principal component analysis (PCA) method for feature dimensionality reduction; (iv) stratified pooling frame-level features to get video-level feature; and (v) SVM for multiclass classification. Finally, the experimental results conducted on HMDB-51 and UCF-101 datasets show that the proposed method outperforms the state-of-the-art. |
2,587 | Customized valorization of waste streams by Pseudomonas putida: State-of-the-art, challenges, and future trends | Preventing catastrophic climate events warrants prompt action to delay global warming, which threatens health and food security. In this context, waste management using engineered microbes has emerged as a long-term eco-friendly solution for addressing the global climate crisis and transitioning to clean energy. Notably, Pseudomonas putida can valorize industry-derived synthetic wastes including plastics, oils, food, and agricultural waste into products of interest, and it has been extensively explored for establishing a fully circular bioeconomy through the conversion of waste into bio-based products, including platform chemicals (e.g., cis,cis-muconic and adipic acid) and biopolymers (e.g., medium-chain length polyhydroxyalkanoate). However, the efficiency of waste pre-treatment technologies, capability of microbial cell factories, and practicability of synthetic biology tools remain low, posing a challenge to the industrial application of P. putida. The present review discusses the state-of-the-art, challenges, and future prospects for divergent biosynthesis of versatile products from waste-derived feedstocks using P. putida. |
2,588 | A Neuromorphic Proto-Object Based Dynamic Visual Saliency Model With a Hybrid FPGA Implementation | Computing and attending to salient regions of a visual scene is an innate and necessary preprocessing step for both biological and engineered systems performing high-level visual tasks including object detection, tracking, and classification. Computational bandwidth and speed are improved by preferentially devoting computational resources to salient regions of the visual field. The human brain computes saliency effortlessly, but modeling this task in engineered systems is challenging. We first present a neuromorphic dynamic saliency model, which is bottom-up, feed-forward, and based on the notion of proto-objects with neurophysiological spatio-temporal features requiring no training. Our neuromorphic model outperforms state-of-the-art dynamic visual saliency models in predicting human eye fixations (i.e., ground truth saliency). Secondly, we present a hybrid FPGA implementation of the model for real-time applications, capable of processing 112 x 84 resolution frames at 18.71 Hz running at a 100 MHz clock rate-a 23.77xspeedup from the software implementation. Additionally, our fixed-point model of the FPGA implementation yields comparable results to the software implementation. |
2,589 | Non-human contributions to personality neuroscience - from fish through primates. An introduction to the special issue | The most fundamental emotional systems that show trait control are evolutionarily old and extensively conserved. Psychology in general has benefited from non-human neuroscience and from the analytical simplicity of behaviour in those with simpler nervous systems. It has been argued that integration between personality, psychopathology, and neuroscience is particularly promising if we are to understand the neurobiology of human experience. Here, we provide some general arguments for a non-human approach being at least as productive in relation to personality, psychopathology, and their interface. Some early personality theories were directly linked to psychopathology (e.g., Eysenck, Panksepp, and Cloninger). They shared a common interest in brain systems that naturally led to the use of non-human data; behavioural, neural, and pharmacological. In Eysenck's case, this also led to the selective breeding, at the Maudsley Institute, of emotionally reactive and non-reactive strains of rat as models of trait neuroticism or trait emotionality. Dimensional personality research and categorical approaches to clinical disorder then drifted apart from each other, from neuropsychology, and from non-human data. Recently, the conceptualizations of both healthy personality and psychopathology have moved towards a common hierarchical trait perspective. Indeed, the proposed two sets of trait dimensions appear similar and may even be eventually the same. We provide, here, an introduction to this special issue of Personality Neuroscience, where the authors provide overviews of detailed areas where non-human data inform human personality and its psychopathology or provide explicit models for translation to human neuroscience. Once all the papers in the issue have appeared, we will also provide a concluding summary of them. |
2,590 | E. coli biosensor based on modular GFP and luxI/luxR cyclic amplification circuit for sensitive detection of lysine | In this study, an E. coli biosensor based on modular green fluorescent protein and luxI/IuxR cycle amplification circuit was constructed for sensitive detection of bioavailable lysine. The results indicated that the luxI/IuxR positive feedback circuit based on quorum sensing can be used as a signal amplifier to improve the sensitivity to lysine detection with the detection limit of 256 nM. The presented method was more sensitive than the previously reported whole-cell fluorescent microbial biosensors. In addition, the developed E. coli biosensor was specific for lysine detection, and other amino acids and proteins did not cause any interference. The constructed genetic engineered biosensor was accurate for lysine detection, the lysine content of 6.87 ± 0.36% in tryptone was successfully measured, and after adding 10, 30, and 50 μM lysine in tryptone, the recoveries of 109.98 ± 10.44%, 103.88 ± 7.66%, and 105.89 ± 6.34% were obtained, respectively. Furthermore, as the design of the genetic engineered biosensor is modular, it can conceivably be utilized as a component in the design of more complex synthetic gene circuits without any changes to the amplifier and reporter system. |
2,591 | A Splitting-Based Iterative Algorithm for Accelerated Statistical X-Ray CT Reconstruction | Statistical image reconstruction using penalized weighted least-squares (PWLS) criteria can improve image-quality in X-ray computed tomography (CT). However, the huge dynamic range of the statistical weights leads to a highly shift-variant inverse problem making it difficult to precondition and accelerate existing iterative algorithms that attack the statistical model directly. We propose to alleviate the problem by using a variable-splitting scheme that separates the shift-variant and ("nearly") invariant components of the statistical data model and also decouples the regularization term. This leads to an equivalent constrained problem that we tackle using the classical method-of-multipliers framework with alternating minimization. The specific form of our splitting yields an alternating direction method of multipliers (ADMM) algorithm with an inner-step involving a "nearly" shift-invariant linear system that is suitable for FFT-based preconditioning using cone-type filters. The proposed method can efficiently handle a variety of convex regularization criteria including smooth edge-preserving regularizers and non-smooth sparsity-promoting ones based on the l(1)-norm and total variation. Numerical experiments with synthetic and real in vivo human data illustrate that cone-filter preconditioners accelerate the proposed ADMM resulting in fast convergence of ADMM compared to conventional (nonlinear conjugate gradient, ordered subsets) and state-of-the-art (MFISTA, split-Bregman) algorithms that are applicable for CT. |
2,592 | Modeling fine-grained spatio-temporal pollution maps with low-cost sensors | The use of air quality monitoring networks to inform urban policies is critical especially where urban populations are exposed to unprecedented levels of air pollution. High costs, however, limit city governments' ability to deploy reference grade air quality monitors at scale; for instance, only 33 reference grade monitors are available for the entire territory of Delhi, India, spanning 1500 sq km with 15 million residents. In this paper, we describe a high-precision spatio-temporal prediction model that can be used to derive fine-grained pollution maps. We utilize two years of data from a low-cost monitoring network of 28 custom-designed low-cost portable air quality sensors covering a dense region of Delhi. The model uses a combination of message-passing recurrent neural networks combined with conventional spatio-temporal geostatistics models to achieve high predictive accuracy in the face of high data variability and intermittent data availability from low-cost sensors (due to sensor faults, network, and power issues). Using data from reference grade monitors for validation, our spatio-temporal pollution model can make predictions within 1-hour time-windows at 9.4, 10.5, and 9.6% Mean Absolute Percentage Error (MAPE) over our low-cost monitors, reference grade monitors, and the combined monitoring network respectively. These accurate fine-grained pollution sensing maps provide a way forward to build citizen-driven low-cost monitoring systems that detect hazardous urban air quality at fine-grained granularities. |
2,593 | Palliative Care Utilization in Burn Patients | Background: Burn injuries are a common cause for hospitalization, and severe burns have an increased risk of death in patients with advanced age, inhalational injury, comorbid conditions. Very little is known about the utilization of palliative care consultation in burn patients. Objective: The aim of this study was to evaluate the factors influencing the utilization of inpatient palliative care consultation for patients with severe burn injuries. Methods: This was a retrospective chart review study at a single burn center. Results: Seventeen out of 191 patients (8.9%) received a palliative care consultation with the average time for consultation of 10.3 days. Factors that appear to impact consultation were age, presence of inhalational injury, and multiple comorbid conditions. Conclusion: Inpatient palliative care consultation was underutilized in patients with severe burn injurie. Further research into the outcomes of palliative care consultation could help further support the utility of early involvement in burn patients. |
2,594 | Pedestrian Detection Inspired by Appearance Constancy and Shape Symmetry | Most state-of-the-art methods in pedestrian detection are unable to achieve a good trade-off between accuracy and efficiency. For example, ACF has a fast speed but a relatively low detection rate, while checkerboards have a high detection rate but a slow speed. Inspired by some simple inherent attributes of pedestrians (i.e., appearance constancy and shape symmetry), we propose two new types of non-neighboring features: side-inner difference features (SIDF) and symmetrical similarity features (SSFs). SIDF can characterize the difference between the background and pedestrian and the difference between the pedestrian contour and its inner part. SSF can capture the symmetrical similarity of pedestrian shape. However, it is difficult for neighboring features to have such above characterization abilities. Finally, we propose to combine both non-neighboring features and neighboring features for pedestrian detection. It is found that non-neighboring features can further decrease the log-average miss rate by 4.44%. The relationship between our proposed method and some state-of-the-art methods is also given. Experimental results on INRIA, Caltech, and KITTI data sets demonstrate the effectiveness and efficiency of the proposed method. Compared with the state-of-the-art methods without using CNN, our method achieves the best detection performance on Caltech, outperforming the second best method (i.e., checkerboards) by 2.27%. Using the new annotations of Caltech, it can achieve 11.87% miss rate, which outperforms other methods. |
2,595 | The education of art culture at Sultanate of Oman through the multidisciplinary integration between graphic design and eco-friendly textile printing. Part 1: Standardization of extraction and dyeing with natural wastes products | Scientific research today is marked by a growing differentiation and specialization in the disciplines and interdisciplinary research. This paper investigates a number of challenges of Interdisciplinary collaborations in implementation of a circular economy approach within textile and graphic designs. These challenges range from achieving economy of scale required for commercial viability and finding secondary markets for the recycled materials to developing 'resource efficient recycling processes' that are especially tailored to the specific needs of eco-friendly textile products. Art Education Department at Sultan Qaboos University created interdisciplinary education strategy through an artistic relevant, and engaging the textile printing and graphic design courses in a project. The aim of this project is to apply some natural waste products which contain pigments to be served as recycling sources for natural dyes in textile coloration regarding their increasing interest due to their biodegradability and environmental awareness. The research project was divided in two parts; part one depends on studying the optimum condition of extraction with different co-solvent on different textile fabrics, as the extraction can be an energy, economic and environmental friendly by waste recycling. Part two deals on studying the mixing of the resulted extractions in producing a variety of hues under the effect of different pH values, mordants and mordanting methods to promote artistic printed textile patterns assisted by the graphic design. Therefore, students are introduced to different and integrated ways of thinking, aiming to make them more aware of circular economy and sustainability issues in all of their art activities, from personal to professional environments. As a result, this research is considered as a double scientific leap in terms of development strategies for teaching art curricula through the Multidisciplinary Integration in serving the community and the environment. (C) 2020 Published by Elsevier Ltd. |
2,596 | Coadministration of seasonal influenza and COVID-19 vaccines: A systematic review of clinical studies | The lifting of non-pharmaceutical measures preventing transmission of SARS-CoV-2 (and other viruses, including influenza viruses) raises concerns about healthcare resources and fears of an increased number of cases of influenza and COVID-19. For the 2021-2022 influenza season, the WHO and >20 European countries promoted coadministration of influenza and COVID-19 vaccines. Recently, the French Health Authority recommended coupling the COVID-19 vaccination with the 2022-2023 influenza vaccination campaign for healthcare professionals and people at risk of severe COVID-19. The present systematic review examines published data on the safety, immunogenicity, efficacy/effectiveness, and acceptability/acceptance of coadministration of influenza and COVID-19 vaccines. No safety concerns or immune interferences were found whatever the vaccines or the age of vaccinated subjects (65- or 65+). No efficacy/effectiveness data were available. The results should reassure vaccinees and vaccinators in case of coadministration and increase vaccine coverage. Healthcare systems promoting coupled campaigns must provide the necessary means for successful coadministration. |
2,597 | [Incidence and causes of early end in awake surgery for language mapping not directly related to eloquence] | The incidence and causes that may lead to an early end (unfinished cortical/subcortical mapping) of awake surgery for language mapping are little known. A study was conducted on 41 patients with brain glioma located in the language area that had awake surgery under conscious sedation. Surgery was ended early in 6 patients. The causes were: tonic-clonic seizure (1), lack of cooperation due to fatigue/sleep (4), whether or not word articulation was involved, a decreased level of consciousness for ammonia encephalopathy that required endotracheal intubation (1). There are causes that could be expected and in some cases avoided. Tumour size, preoperative aphasia, valproate treatment, and type of anaesthesia used are variables to consider to avoid failure in awake surgery for language mapping. With these results, the following measures are proposed: l) If the tumour is large, perform surgery in two times to avoid fatigue, 2) if patient has a preoperative aphasia, do not use sedation during surgery to ensure that sleepiness does not cause worse word articulation, 3) if the patient is on valproate treatment, it is necessary to rule out the pre-operative symptoms that are not due to ammonia encephalopathy. |
2,598 | Real-Time Lexicon-Free Scene Text Localization and Recognition | An end-to-end real-time text localization and recognition method is presented. Its real-time performance is achieved by posing the character detection and segmentation problem as an efficient sequential selection from the set of Extremal Regions. The ER detector is robust against blur, low contrast and illumination, color and texture variation. In the first stage, the probability of each ER being a character is estimated using features calculated by a novel algorithm in constant time and only ERs with locally maximal probability are selected for the second stage, where the classification accuracy is improved using computationally more expensive features. A highly efficient clustering algorithm then groups ERs into text lines and an OCR classifier trained on synthetic fonts is exploited to label character regions. The most probable character sequence is selected in the last stage when the context of each character is known. The method was evaluated on three public datasets. On the ICDAR 2013 dataset the method achieves state-of-the-art results in text localization; on the more challenging SVT dataset, the proposed method significantly outperforms the state-of-the-art methods and demonstrates that the proposed pipeline can incorporate additional prior knowledge about the detected text. The proposed method was exploited as the baseline in the ICDAR 2015 Robust Reading competition, where it compares favourably to the state-of-the art. |
2,599 | miRNA-15a/16: as tumor suppressors and more | Since their first discovery in chronic lymphocytic leukemia, miR-15a and miR-16 have been reported to act as tumor suppressors or potential oncomiRs in different types of cancer. This review summarizes the history, biological properties and the important functions of these two miRNAs in cancer. It also introduces their roles as regulators of immune responses and angiogenesis, endogenous controls as well as potential targets and hallmarks of cancer. |
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