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Understanding Private Car Aggregation Effect via Spatio-Temporal Analysis of Trajectory Data.

IEEE Trans Cybern 2021 Oct 15;PP. Epub 2021 Oct 15.

Understanding the private car aggregation effect is conducive to a broad range of applications, from intelligent transportation management to urban planning. However, this work is challenging, especially on weekends, due to the inefficient representations of spatiotemporal features for such aggregation effect and the considerable randomness of private car mobility on weekends. In this article, we propose a deep learning framework for a spatiotemporal attention network (STANet) with a neural algorithm logic unit (NALU), the so-called STANet-NALU, to understand the dynamic aggregation effect of private cars on weekends. Read More

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October 2021

Case Report: Successful Long-Term Management of a Low-Birth Weight Preterm Infant With Compound Heterozygous Protein C Deficiency With Subcutaneous Protein C Concentrate Up to Adolescence.

Front Pediatr 2021 28;9:591052. Epub 2021 Sep 28.

Department of Neonatology, Heidelberg University Children's Hospital, Heidelberg, Germany.

Homozygous/compound heterozygous forms of congenital protein C deficiency are often associated with severe antenatal and postnatal thrombotic or hemorrhagic complications. Protein C deficiency frequently leads to severe adverse outcomes like blindness and neurodevelopmental delay in children and may even lead to death. The most widely used long-term postnatal treatment consists of oral anticoagulation with vitamin K antagonists (e. Read More

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September 2021

O-JMeSH: creating a bilingual English-Japanese controlled vocabulary of MeSH UIDs through machine translation and mutual information.

Genomics Inform 2021 Sep 30;19(3):e26. Epub 2021 Sep 30.

Graduate School of Integrative Science and Engineering, Tokyo City University, Tokyo 158-8557, Japan.

Previous approaches to create a controlled vocabulary for Japanese have resorted to existing bilingual dictionary and transformation rules to allow such mappings. However, given the possible new terms introduced due to coronavirus disease 2019 (COVID-19) and the emphasis on respiratory and infection-related terms, coverage might not be guaranteed. We propose creating a Japanese bilingual controlled vocabulary based on MeSH terms assigned to COVID-19 related publications in this work. Read More

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September 2021

An Efficient Dynamic Optimization Algorithm for Path-Constrained Switched Systems.

Chi Zhang Jun Fu

IEEE Trans Neural Netw Learn Syst 2021 Oct 6;PP. Epub 2021 Oct 6.

Dynamic optimization is one of the model-based adaptive reinforcement learning methods, which has been widely used in industrial systems with switching mechanisms. This article presents an efficient dynamic optimization strategy to locate an optimal input and switch times for switched systems with guaranteed satisfaction for path constraints during the whole time period. In this article, we propose a single-level algorithm where, at each iteration, gradients of the objective function with respect to switch times and the system input are evaluated by solving adjoint systems and sensitivity equations, respectively. Read More

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October 2021

Teaching Multiple Inverse Reinforcement Learners.

Front Artif Intell 2021 16;4:625183. Epub 2021 Sep 16.

INESC-ID, Instituto Superior Técnico, University of Lisbon, Lisbon, Portugal.

In this paper, we propose the first machine teaching algorithm for multiple inverse reinforcement learners. As our initial contribution, we formalize the problem of optimally teaching a sequential task to a heterogeneous class of learners. We then contribute a theoretical analysis of such problem, identifying conditions under which it is possible to conduct such teaching using the same demonstration for all learners. Read More

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September 2021

GeoDualCNN: Geometry-supporting Dual Convolutional Neural Network for Noisy Point Clouds.

IEEE Trans Vis Comput Graph 2021 Sep 21;PP. Epub 2021 Sep 21.

We propose a geometry-supporting dual convolutional neural network (GeoDualCNN) for both point cloud normal estimation and denoising. GeoDualCNN fuses the geometry domain knowledge that the underlying surface of a noisy point cloud is piecewisely smooth with the fact that a point normal is properly defined only when local surface smoothness is guaranteed. Centered around this insight, we define the homogeneous neighborhood (HoNe) which stays clear of surface discontinuities, and associate each HoNe with a point whose geometry and normal orientation is mostly consistent with that of HoNe. Read More

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September 2021

Hierarchical Generation of Human Pose With Part-Based Layer Representation.

IEEE Trans Image Process 2021 20;30:7856-7866. Epub 2021 Sep 20.

Human pose transfer has been becoming one of the emerging research topics in recent years. However, state-of-the-art results are still far from satisfactory. One main reason is that these end-to-end methods are often blindly trained without the semantic understanding of its content. Read More

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September 2021

A Novel Method for Inferring Chemical Compounds with Prescribed Topological Substructures Based on Integer Programming.

IEEE/ACM Trans Comput Biol Bioinform 2021 Sep 14;PP. Epub 2021 Sep 14.

Drug discovery is one of the major goals of computational biology and bioinformatics. A novel framework has recently been proposed for the design of chemical graphs using both artificial neural networks (ANNs) and mixed integer linear programming (MILP). This method consists of a prediction phase and an inverse prediction phase. Read More

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September 2021

Training Generative Adversarial Networks via Stochastic Nash Games.

IEEE Trans Neural Netw Learn Syst 2021 Aug 26;PP. Epub 2021 Aug 26.

Generative adversarial networks (GANs) are a class of generative models with two antagonistic neural networks: a generator and a discriminator. These two neural networks compete against each other through an adversarial process that can be modeled as a stochastic Nash equilibrium problem. Since the associated training process is challenging, it is fundamental to design reliable algorithms to compute an equilibrium. Read More

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Multi-feature representation for burn depth classification via burn images.

Artif Intell Med 2021 08 27;118:102128. Epub 2021 Jun 27.

PAMI Research Group, Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Macau.

Burns are a common and severe problem in public health. Early and timely classification of burn depth is effective for patients to receive targeted treatment, which can save their lives. However, identifying burn depth from burn images requires physicians to have a lot of medical experience. Read More

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Saturation-Tolerant Prescribed Control for a Class of MIMO Nonlinear Systems.

IEEE Trans Cybern 2021 Aug 16;PP. Epub 2021 Aug 16.

This article proposes a saturation-tolerant prescribed control (SPC) for a class of multiinput and multioutput (MIMO) nonlinear systems simultaneously considering user-specified performance, unmeasurable system states, and actuator faults. To simplify the control design and decrease the conservatism, tunnel prescribed performance (TPP) is proposed not only with concise form but also smaller overshoot performance. By introducing non-negative modified signals into TPP as saturation-tolerant prescribed performance (SPP), we propose SPC to guarantee tracking errors not to violate SPP constraints despite the existence of saturation and actuator faults. Read More

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Gaps in global wildlife trade monitoring leave amphibians vulnerable.

Elife 2021 08 12;10. Epub 2021 Aug 12.

School of Biology, Institute of Science, Suranaree University of Technology, Nakhon Ratchasima, Thailand.

As the biodiversity crisis continues, we must redouble efforts to understand and curb pressures pushing species closer to extinction. One major driver is the unsustainable trade of wildlife. Trade in internationally regulated species gains the most research attention, but this only accounts for a minority of traded species and we risk failing to appreciate the scale and impacts of unregulated legal trade. Read More

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Edge Sensing and Control Co-Design for Industrial Cyber-Physical Systems: Observability Guaranteed Method.

IEEE Trans Cybern 2021 Aug 3;PP. Epub 2021 Aug 3.

The new generation of the industrial cyber-physical system (ICPS) supported by the edge computing technology facilitates the deep integration of sensing and control. System observability is the key factor to characterize the internal relationship of them. In most existing works, the observability is regarded as the assumption for subsequent sensing and control. Read More

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Facing an unfortunate trade-off: policy responses, lessons and spill-overs during the COVID-19 pandemic.

Econ Hum Biol 2021 Jul 27;43:101052. Epub 2021 Jul 27.

Center for European Studies (CefES), University of Milano-Bicocca, Italy. Electronic address:

Although COVID-19 emerged as a global shock, governments adopted non-pharmaceutical policy responses that were rather heterogeneous, depending on cultural and institutional characteristics. At the country level, the stringency of 'lockdown'-type policies should be set to achieve the best possible trade-off between economic and fatality dynamics, obviously accounting for possible cross-border influences. To allow for policy learning, I assume that the first country implementing a policy initiative that is worth emulating must either get the best possible health or the best possible economic outcome. Read More

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Artifact and Detail Attention Generative Adversarial Networks for Low-Dose CT Denoising.

IEEE Trans Med Imaging 2021 Jul 30;PP. Epub 2021 Jul 30.

Generative adversarial networks are being extensively studied for low-dose computed tomography denoising. However, due to the similar distribution of noise, artifacts, and high-frequency components of useful tissue images, it is difficult for existing generative adversarial network-based denoising networks to effectively separate the artifacts and noise in the low-dose computed tomography images. In addition, aggressive denoising may damage the edge and structural information of the computed tomography image and make the denoised image too smooth. Read More

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Efficient Estimation of Pauli Observables by Derandomization.

Phys Rev Lett 2021 Jul;127(3):030503

Institute for Quantum Information and Matter, Caltech, Pasadena, California 91125, USA.

We consider the problem of jointly estimating expectation values of many Pauli observables, a crucial subroutine in variational quantum algorithms. Starting with randomized measurements, we propose an efficient derandomization procedure that iteratively replaces random single-qubit measurements by fixed Pauli measurements; the resulting deterministic measurement procedure is guaranteed to perform at least as well as the randomized one. In particular, for estimating any L low-weight Pauli observables, a deterministic measurement on only of order log(L) copies of a quantum state suffices. Read More

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A Case-Control Study on Behavioral Addictions and Neurocognition: Description of the BANCO and BANCO2 Protocols.

Neuropsychiatr Dis Treat 2021 20;17:2369-2386. Epub 2021 Jul 20.

CHU Nantes, Addictology and Psychiatry Department, Nantes, France.

Introduction: Only two behavioral addictions (BAs) are currently recognized in international classifications (gambling disorder: GbD; gaming disorder: GmD), while some of them await further investigation (food addiction: FA; sexual addiction: SA). Neurocognitive functioning is considered a risk factor for BAs. Research is quite abundant for GbD and highlights specific deficits in several cognitive functions. Read More

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Multiple Access-Enabled Relaying with Piece-Wise and Forward NOMA: Rate Optimization under Reliability Constraints.

Sensors (Basel) 2021 Jul 13;21(14). Epub 2021 Jul 13.

Department of Information Systems and Technology, Mid Sweden University, 851 70 Sundsvall, Sweden.

The increasing proliferation of Internet-of-things (IoT) networks in a given space requires exploring various communication solutions (e.g., cooperative relaying, non-orthogonal multiple access, spectrum sharing) jointly to increase the performance of coexisting IoT systems. Read More

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Finite-Time Observer-Based Sliding-Mode Control for Markovian Jump Systems With Switching Chain: Average Dwell-Time Method.

IEEE Trans Cybern 2021 Jul 20;PP. Epub 2021 Jul 20.

In this article, the finite-time observer-based sliding-mode control (SMC) problem is considered for stochastic Markovian jump systems (MJSs) with a deterministic switching chain (DSC) subject to time-varying delay and packet losses (PLs). First, the stochastic MJSs with DSC are appropriately modeled and the PLs case is characterized by using some Bernoulli random variables. Then, a nonfragile finite-time bounded sliding-mode observer is designed. Read More

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Significant Geo-Social Group Discovery over Location-Based Social Network.

Sensors (Basel) 2021 Jul 2;21(13). Epub 2021 Jul 2.

Faculty of Arts, Design and Architecture, School of Built Environment, The University of New South Wales, Sydney, NSW 2052, Australia.

Geo-social community detection over location-based social networks combining both location and social factors to generate useful computational results has attracted increasing interest from both industrial and academic communities. In this paper, we formulate a novel community model, termed (GSG), to enforce both spatial and social factors to generate significant computational patterns and to investigate the problem of community detection over location-based social networks. Specifically, GSG detection aims to extract all group-venue clusters, where users are similar to each other in the same group and they are located in a minimum covering circle (MCC) for which the radius is no greater than a distance threshold γ. Read More

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Advancing admixture graph estimation via maximum likelihood network orientation.

Bioinformatics 2021 07;37(Suppl_1):i142-i150

Department of Computer Science, University of California, Los Angeles, LA 90095, USA.

Motivation: Admixture, the interbreeding between previously distinct populations, is a pervasive force in evolution. The evolutionary history of populations in the presence of admixture can be modeled by augmenting phylogenetic trees with additional nodes that represent admixture events. While enabling a more faithful representation of evolutionary history, admixture graphs present formidable inferential challenges, and there is an increasing need for methods that are accurate, fully automated and computationally efficient. Read More

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Autoencoder based self-supervised test-time adaptation for medical image analysis.

Med Image Anal 2021 08 19;72:102136. Epub 2021 Jun 19.

Dept. of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD 21218, USA.

Deep neural networks have been successfully applied to medical image analysis tasks like segmentation and synthesis. However, even if a network is trained on a large dataset from the source domain, its performance on unseen test domains is not guaranteed. The performance drop on data obtained differently from the network's training data is a major problem (known as domain shift) in deploying deep learning in clinical practice. Read More

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Three Birds with One Stone: Preventive Protection of Paper Materials by ZnO-PHMB and UV-531 Composite Systems.

Langmuir 2021 07 8;37(28):8445-8454. Epub 2021 Jul 8.

Department of Chemistry, Renmin University of China, Beijing 100872, China.

As the most frequently used archival materials for painting and recording, paper lays the groundwork for the development of prosperous human civilization. However, its susceptibility to three primary factors including external ultraviolet light, increased acidity, and biological pathogens in long-term storage shortens the longevity of paper. Therefore, the protection of paper-based cultural relics is extremely urgent. Read More

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Adaptive Neural-Network-Based Fault-Tolerant Control for a Flexible String With Composite Disturbance Observer and Input Constraints.

IEEE Trans Cybern 2021 Jul 7;PP. Epub 2021 Jul 7.

We propose an adaptive neural-network-based fault-tolerant control scheme for a flexible string considering the input constraint, actuator gain fault, and external disturbances. First, we utilize a radial basis function neural network to compensate for the actuator gain fault. In addition, an observer is used to handle composite disturbances, including unknown approximation errors and boundary disturbances. Read More

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Light-Induced Quantum Anomalous Hall Effect on the 2D Surfaces of 3D Topological Insulators.

Adv Sci (Weinh) 2021 Sep 2;8(17):e2101508. Epub 2021 Jul 2.

Department of Nuclear Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.

Quantum anomalous Hall (QAH) effect generates quantized electric charge Hall conductance without external magnetic field. It requires both nontrivial band topology and time-reversal symmetry (TRS) breaking. In most cases, one can break the TRS of time-reversal invariant topological materials to yield QAH effect, which is essentially a topological phase transition. Read More

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September 2021

Efficient Verification of Continuous-Variable Quantum States and Devices without Assuming Identical and Independent Operations.

Phys Rev Lett 2021 Jun;126(24):240503

Institute of Natural Sciences, Shanghai Jiao Tong University, Shanghai 200240, China.

Continuous-variable quantum information, encoded into infinite-dimensional quantum systems, is a promising platform for the realization of many quantum information protocols, including quantum computation, quantum metrology, quantum cryptography, and quantum communication. To successfully demonstrate these protocols, an essential step is the certification of multimode continuous-variable quantum states and quantum devices. This problem is well studied under the assumption that multiple uses of the same device result in identical and independently distributed (i. Read More

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Dextran-Curcumin Nanosystems Inhibit Cell Growth and Migration Regulating the Epithelial to Mesenchymal Transition in Prostate Cancer Cells.

Int J Mol Sci 2021 Jun 29;22(13). Epub 2021 Jun 29.

Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, 87036 Rende, Italy.

Functional nanocarriers which are able to simultaneously vectorize drugs to the site of interest and exert their own cytotoxic activity represent a significant breakthrough in the search for effective anticancer strategies with fewer side effects than conventional chemotherapeutics. Here, we propose previously developed, self-assembling dextran-curcumin nanoparticles for the treatment of prostate cancer in combination therapy with Doxorubicin (DOXO). Biological effectiveness was investigated by evaluating the cell viability in either cancer and normal cells, reactive oxygen species (ROS) production, apoptotic effect, interference with the cell cycle, and the ability to inhibit cell migration and reverse the epithelial to mesenchymal transition (EMT). Read More

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Output tracking for nonlinear systems subject to unmodeled sluggish actuator dynamics via model-based extended state observer.

ISA Trans 2021 Jun 23. Epub 2021 Jun 23.

Qian Xuesen Laboratory of Space Technology, China Academy of Space Technology, Beijing, 100094, China.

We propose an output tracking control approach for a class of uncertain, nonlinear systems with unmodeled, sluggish actuator dynamics. The normal extended state observer (ESO) is modified with a nominal model of the largely unknown actuator dynamics. The total disturbance is redefined to include the uncertainties of the actuator dynamics. Read More

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Training Robust Object Detectors From Noisy Category Labels and Imprecise Bounding Boxes.

IEEE Trans Image Process 2021 23;30:5782-5792. Epub 2021 Jun 23.

Object detection has gained great improvements with the advances of convolutional neural networks and the availability of large amounts of accurate training data. Though the amount of data is increasing significantly, the quality of data annotations is not guaranteed from the existing crowd-sourcing labeling platforms. In addition to noisy category labels, imprecise bounding box annotations are commonly existed for object detection data. Read More

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PPalign: optimal alignment of Potts models representing proteins with direct coupling information.

BMC Bioinformatics 2021 Jun 10;22(1):317. Epub 2021 Jun 10.

Univ Rennes, Inria, CNRS, IRISA, Rennes, France.

Background: To assign structural and functional annotations to the ever increasing amount of sequenced proteins, the main approach relies on sequence-based homology search methods, e.g. BLAST or the current state-of-the-art methods based on profile Hidden Markov Models, which rely on significant alignments of query sequences to annotated proteins or protein families. Read More

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