Miracle-dz/UniFAR-FTUs huggingface dataset:
A Training-based Identification Approach to VIN Adversarial Examples

With the rapid development of Artificial Intelligence (AI), the problem of AI security has gradually emerged. Most existing machine learning algorithms may be attacked by adversarial examples. An adversarial example is a slightly modified input sample that can lead to a false result of machine learning algorithms. The adversarial examples pose a potential security threat for many AI application areas, especially in the domain of robot path planning. In this field, the adversarial examples obstruct the algorithm by adding obstacles to the normal maps, resulting in multiple effects on the predicted path. However, there is no suitable approach to automatically identify them. To our knowledge, all previous work uses manual observation method to estimate the attack results of adversarial maps, which is time-consuming. Aiming at the existing problem, this paper explores a method to automatically identify the adversarial examples in Value Iteration Networks (VIN), which has a strong generalization ability. We analyze the possible scenarios caused by the adversarial maps. We propose a training-based identification approach to VIN adversarial examples by combing the path feature comparison and path image classification. We evaluate our method using the adversarial maps dataset, show that our method can achieve a high-accuracy and faster identification than manual observation method.
Moral expansiveness short form: Validity and reliability of the MESx

Moral expansiveness refers to the range of entities (human and non-human) deemed worthy of moral concern and treatment. Previous research has established that the Moral Expansiveness Scale (MES) is a powerful predictor of altruistic moral decision-making and captures a unique dimension of moral cognition. However, the length of the full MES may be restrictive for some researchers. Here we establish the reliability and validity of a reduced moral expansiveness scale, the MESx. Consistent with the full version, the MESx is strongly associated with (but not reducible to) theoretically related constructs, such as endorsement of universalism values, identification with all humanity, and connectedness to nature. The MESx also predicted measures of altruistic moral decision-making to the same degree as the full MES. Further, the MESx passed tests of discriminant validity, was unrelated to political conservatism (unlike the full MES), only mildly associated with the tendency to provide socially desirable responses, and produced moderate reliability over time. We conclude that the MESx is a psychometrically valid alternative for researchers requiring a short measure of moral expansiveness.
Multi-Shot Human Re-Identification for the Security in Video Surveillance Systems

Keeping a safe city against security breaches and acts of violence is something critical. In a smart video-surveillance system, multi-shot human re-identification is a major challenge because of the large variations in a human's appearance caused by different types of noise such as occlusion, viewpoint and illumination variations. In this paper, we propose a model based-on the analysis of all the video surveillance data extracted from camera networks by exploiting the performance of the space-time covariance descriptor. This model not only deals with one video frame as the majority of models, but also considers all the extracted groups of pictures to implicitly encode the described pedestrian in motion by the integration of time parameter with the appearance features such as color, gradient and LBP, and the clustering step. The experiments conducted on PRID dataset showed the importance of video surveillance data analytics in recognition rates.
Reusing Titanium Healing Abutments: Comparison of Two Decontamination Methods.

PURPOSE To assess the amount of contamination remaining on used healing abutments after autoclaving and to compare the effectiveness of two additional decontamination methods. MATERIALS AND METHODS After autoclaving, a total of 120 used healing abutments were divided equally into three groups: used healing abutments after autoclaving only (group 1); used healing abutments after autoclaving and air-flow polishing (Master Piezon, EMS) using erythritol powder (AIR-FLOW PLUS, EMS) (group 2); and used healing abutments after autoclaving and sodium hypochlorite (NaOCl; 25 g/L) treatment (group 3). Residual contaminants were stained using Phloxine B (400 g/mL), and healing abutments were photographed using a light microscope with digital capture system (Nikon SMZ800). The proportion of stained (ie, contaminated) areas on each healing abutment was then measured using imaging software (ImageJ). The healing abutments were also examined using scanning electron microscopy (SEM). RESULTS Mean proportion of surface area affected by residual contaminants on the body, top (screwdriver-engaging), and bottom (implant-abutment interface) surfaces for group 1 was 38.2% ± 28.34%, 30.0% ± 19.55%, and 18.7% ± 17.87%, respectively; group 2 showed 3.5% ± 4.90%, 5.3% ± 3.74%, and 5.4% ± 8.49%, respectively; and group 3 showed 0.3% ± 0.16%, 1.9% ± 2.14%, and 0.7% ± 1.02%, respectively. Autoclaving alone was insufficient for successful decontamination, while additional decontamination procedures significantly reduced remaining contaminants. NaOCl was significantly more effective than air polishing. SEM analysis showed no detectable differences in the surface appearance of titanium healing abutments. CONCLUSION The results show that decontamination of used healing abutments is achievable, thus strengthening the feasibility of reusing healing abutments.
Enhanced Channel Estimation and Codebook Design for Millimeter-Wave Communication

The existing channel estimation methods for millimeter-wave communications, e.g., hierarchical search and compressed sensing, either acquire only one single multipath component (MPC) or require considerably high training overhead. To realize fast yet accurate channel estimation, we propose a multipath decomposition and recovery approach in this paper. The proposed approach has two stages. In the first stage, instead of directly searching the real MPCs, we decompose each real MPC into several virtual MPCs and acquire the virtual MPCs by using the hierarchical search based on a normal-resolution codebook. Then, in the second stage, the real MPCs are recovered from the acquired virtual MPCs in the first stage, which turns out to be a sparse reconstruction problem, where the size of the dictionary matrix is greatly reduced by exploiting the results of the virtual multipath acquisition. Moreover, to make the proposed approach applicable for both analog and hybrid beamforming/combining devices with strict constant-modulus constraint, we particularly design a codebook for the hierarchical search by using an enhanced subarray technique, and the codebook is also applicable in other hierarchical search methods. Performance comparisons show that the proposed approach achieves a superior tradeoff between estimation performance and training penalty over the state-of-the-art alternatives.
Power Minimization in Distributed Antenna Systems Using Non-Orthogonal Multiple Access and Mutual Successive Interference Cancellation

This paper introduces new approaches for combining non-orthogonal multiple access with distributed antenna systems. The study targets a minimization of the total transmit power in each cell, under user rate and power multiplexing constraints. Several new suboptimal power allocation techniques are proposed. They are shown to yield very close performance to an optimal power allocation scheme. Also, a new approach based on mutual successive interference cancellation of paired users is proposed. Different techniques are designed for the joint allocation of subcarriers, antennas, and power, with a particular care given to maintain a moderate complexity. The coupling of non-orthogonal multiple access to distributed antenna systems is shown to greatly outperform any other combination of orthogonal/non-orthogonal multiple access schemes with distributed or centralized deployment scenarios.
Elimination of Unipolar Leakage Flux in Consequent-Pole PM Machines by Employing Novel Pole Sequence

This paper proposes a novel consequent-pole permanent magnet (CPM) machine featuring N-iron-N-iron-N-S-iron-S-iron-S sequence to eliminate the unipolar leakage flux in the conventional CPM machine. Furthermore, the tangential magnetized PMs are embedded into the rotor of the proposed CPM machine to improve the unbalanced flux and, hence, enhance the output torque and efficiency. Both the rotors of the proposed and conventional CPM machines are optimized by the finite element (FE) analyses. It is demonstrated that the unipolar leakage flux does not exist in the proposed machines, and hence, the magnetization of the mechanical components can be effectively eliminated. In addition, the electromagnetic performance of the proposed CPM machine, including the phase back EMF, average torque, torque ripple, loss, efficiency, unbalanced magnetic force (UMF), and unipolar leakage flux, is compared with the conventional CPM machine. It shows that the proposed CPM machine can obtain similar torque and efficiency to the conventional CPM machine, while it reduces the UMF. Finally, a CPM machine is prototyped and measured to validate the analyses.
Controlling Progression of Myopia: Optical and Pharmaceutical Strategies

Abstract: The burden associated with the rising prevalence of myopia and high myopia, and the associated vision impairment and sight‐threatening complications, has triggered the need to evaluate strategies to control the progression of myopia. We provide an overview of the literature on the use of optical (spectacles, contact lenses, and orthokeratology) and pharmaceutical approaches to slow progress of myopia. The evidence indicates that myopia progression can be slowed by varying degrees using these strategies. All approaches play a role in the management of myopia as needs and requirements of an individual vary based on age, suitability, affordability, safety of the approach, subjective needs of the individual, and rate of progression. This review also identifies and discusses the lack of long‐term efficacy data and rebound on discontinuation of myopia control products.
Application and Design of New Controller Based on Fuzzy PID and FACTS Devices in Multi-machine Power System

This paper presents a new strategy includes of fuzzy PID controller and Flexible AC transmission system (FACTS) devices in power system for damping the oscillation. This models improves the stability in multi-machine power system by coupling the fuzzy controller with an intelligent algorithm and equipping the FACTS devices to control voltages and power flows. Also, the thyristor-controlled series capacitor (TCSC) as well as Static VAR Compensator (SVC) effects have been considered in this design. The harmony search algorithm (HSA) is applied in this model for fine tuning of the fuzzy PID parameters through time overriding and stability enhancement of proposed controller. Effectiveness of the proposed approach is applied over standard multi-machine power system through comparison with other techniques. Obtained results demonstrate the validity of proposed strategy.
Sensory neuropathy-causing mutations in ATL3 affect ER–mitochondria contact sites and impair axonal mitochondrial distribution

Abstract Axonopathies are neurodegenerative disorders caused by axonal degeneration, affecting predominantly the longest neurons. Several of these axonopathies are caused by genetic defects in proteins involved in the shaping and dynamics of the endoplasmic reticulum (ER); however, it is unclear how these defects impinge on neuronal survival. Given its central and widespread position within a cell, the ER is a pivotal player in inter-organelle communication. Here, we demonstrate that defects in the ER fusion protein ATL3, which were identified in patients suffering from hereditary sensory and autonomic neuropathy, result in an increased number of ER–mitochondria contact sites both in HeLa cells and in patient-derived fibroblasts. This increased contact is reflected in higher phospholipid metabolism, upregulated autophagy and augmented Ca2+ crosstalk between both organelles. Moreover, the mitochondria in these cells display lowered motility, and the number of axonal mitochondria in neurons expressing disease-causing mutations in ATL3 is strongly decreased. These results underscore the functional interdependence of subcellular organelles in health and disease and show that disorders caused by ER-shaping defects are more complex than previously assumed.
Anxiety Sensitivity and Suicidal Ideation/Suicide Risk: A Meta-Analysis

Objective: Suicide is a global public health concern. To inform the prevention and treatment of suicidality, it is crucial to identify transdiagnostic vulnerability factors for suicide and suicide-related conditions. One candidate factor is anxiety sensitivity (AS)—the fear of anxiety-related sensations—which has been implicated in the pathogenesis of a host of mental health outcomes, including suicidal thoughts and behaviors. Importantly, AS is distinct from trait anxiety and negative affectivity, highlighting its potential incremental utility in the understanding of psychopathology. Despite a burgeoning body of literature demonstrating that AS is linked to suicidal thoughts and behaviors, this research has yet to be synthesized. Method: This meta-analysis includes 33 articles representing 34 nonredundant samples (N = 14,002) that examined at least one relationship between AS global or subfactor (i.e., cognitive, physical, social) scores and suicidal ideation and/or suicide risk. Results: Findings revealed small-to-moderate and moderate associations between global AS and suicidal ideation (r = .24, 95% confidence interval (CI): [. 21, . 26], p < . 001) and suicide risk (r = .35, 95% CI [.31, .38], p < .001), respectively. All AS subfactors evinced significant associations with suicidal ideation (rs = .13–.24) and suicide risk (rs = .22–.32). Conclusions: AS is related to suicidal ideation and global suicide risk. Research is needed to disentangle AS from other indices of distress in the prediction of suicidal thoughts and behaviors. Theoretical and clinical implications of these findings are discussed.
Nonlinear Energy Harvesting for Millimeter Wave Networks With Large-Scale Antennas

In this paper, an analytical framework is proposed to explore the potential of wireless power transfer (WPT) for a millimeter wave (mmWave) network with large-scale antennas. Prior works mostly focus on WPT systems with a linear energy harvesting (EH) model, which cannot properly capture the power dependent EH efficiency. On the other hand, based on a nonlinear EH model, the effect of practical EH circuit specifications on the EH performance can be analyzed. By using stochastic geometry approach, analytical and asymptotic expressions for the energy coverage probability, average harvested energy, and achievable rate are derived under different base station (BS) configuration and deployment scenarios. Numerical results provide interesting design insights that the EH circuit specifications significantly affect the network performance. Increasing the BS density and number of BS antennas can improve the network performance. Due to saturation of EH circuits, the typical receiver can only achieve finite maximum amount of harvested energy and achievable rate even when the BS has a large number of antennas.
Is granulomatosis with polyangiitis in Asia different from the West?

The incidence and clinical features of antineutrophil cytoplasmic antibody (ANCA) associated vasculitis (AAV) have been shown to vary according to geographical areas, with granulomatosis with polyangiitis (GPA) being more common in northern Europe and microscopic polyangiitis (MPA) being more common in Asian countries. The annual incidence of GPA among Asians varies between 0.37/million to 2.1/million population. The prevalence of GPA has been estimated to be 1.94/100 000 in a Chinese population. Polymorphisms in class II major histocompatibility genes and ETS1 proto‐oncogene has been shown in Asian patients with GPA. There is a difference in mean age at onset and proteinase 3 (PR3) or myeloperoxidase (MPO) positivity in GPA patients from different Asian countries. Those from India had mean age of 40 years and those from Japan had mean age of 65 years. Sixty percent of GPA patients from China and Japan were MPO ANCA positive while the majority of patients from India and Korea were PR3 positive. Geographical variation with lower frequency of renal involvement in Indian studies and higher frequency in Chinese patients has also been noted. Treatment outcomes have been similar to those reported from other parts of the world. Remission was achieved in about two‐thirds of patients while relapses were noted in one‐third to half of the patients. Apart from minor differences in the organ systems involved, MPO‐ANCA GPA and PR3‐ANCA GPA had similar rates of remission and relapses.
Professional identity in interprofessional teams: findings from a scoping review

ABSTRACT Integrated care has been identified as being fundamental to health and social care reforms. How this interprofessional working impacts on professional identity is unclear. There is a lack of reviews synthesising this growing body of literature. It is therefore timely to conduct a scoping study of the literature which explores the intersection between interprofessional care and professional identity. The aim of this study is to identify the factors that impact on professional identity when working in interprofessional teams. A scoping review was conducted; Business Source Complete (EBSCO); CINAHL; Proquest; Medline; Scopus; and Cochrane Reviews (January 1980 to July 2018) were systematically searched for studies focusing on professional identity and interprofessional teams. Inclusion and exclusion criteria were identified and applied, data were charted, and a synthesis of the narrative was conducted. Sixteen papers are identified as central to this scoping review. Analysis of the papers highlights three key areas of interest: the creation of professional identity; challenges and barriers to professional identity; and implications for leadership and management. The significance of this review is considered along with an agenda for future research. Expanding the research to include more empirical studies to consider areas such as the value of interprofessional education programmes and to include the voice of those professionals no longer working or choosing not to work in an interprofessional care setting should also feature within future research.
The Effects of Perceived Quality and Usefulness of Consumer Reviews on Review Reading and Purchase Intention

Online customer reviews are peer-generated product evaluations posted on company or third party websites. Many retailers offer consumers opportunities to participate in product reviews and share their experiences and opinions with other consumers on their online store websites. This study identifies factors that generate negative perceptions of information quality in online reviews. In addition, the influential role of negative perceptions of consumer reviews and perceived usefulness of online reviews on reading of online reviews and purchase intentions in online stores hosting the reviews are examined. Using a survey, data were collected from 312 male and female university undergraduate students with experience purchasing products online and reading reviews online. Hypotheses were tested using measurement and structural equation models. Four information quality elements (irrelevancy, incredibility, exaggeration, and untimeliness) were developed as measures of negative perceptions of review quality. Based on the results of the research model, researchers found consumers’ negative perceptions of review quality decreased online purchase intentions by deterring the reading behavior of reviews while consumers’ positive perceptions of the usefulness of reviews increased reading activity. This study highlights the importance of consumer review reading behavior and its effect on purchase intention in online stores. Creating supportive systems to enhance the quality of online reviews will allow consumers to make better purchase decisions.
Real-Time Pedestrian Detection for Autonomous Driving

Fast and efficient pedestrian detection technology has become an increasingly important task in the autonomous driving technology. Traditional pedestrian detection algorithms are usually too time-consuming to meet the realtime requirements of autonomous driving. In this paper, we propose a new pedestrian detection algorithm based on the Darknet with optimized feature concatenation, hard negative mining, multi-scale training, model pretraining, and proper calibration of key parameters. In view of the characteristics of pedestrian detection system, we adopt the priori experience about the feature box sizes, instead of K-mean clustering algorithm. We also conduct statistical analysis on the dataset pedestrian label, and design the initial value of the preselection box that is more in line with pedestrian characteristics. The proposed algorithm not only improves the detection accuracy, but also enhances the efficiency of pedestrian detection. Experimental results on traffic record benchmark demonstrate that the optimized algorithm satisfies the real-time and accuracy requirements of the low-speed autonomous driving.
Deep Learning Approach for Short-Term Stock Trends Prediction Based on Two-Stream Gated Recurrent Unit Network

Financial news has been proven to be a crucial factor which causes fluctuations in stock prices. However, previous studies heavily relied on analyzing shallow features and ignored the structural relation among words in a sentence. Several sentiment analysis studies have tried to point out the relationship between investors’ reaction and news events. However, the sentiment dataset was usually constructed from the lingual dataset which is unrelated to the financial sector and led to poor performance. This paper proposes a novel framework to predict the directions of stock prices by using both financial news and sentiment dictionary. The original contributions of this paper include the proposal of a novel two-stream gated recurrent unit network and Stock2Vec—a sentiment word embedding trained on financial news dataset and Harvard IV-4. Two main experiments are conducted: the first experiment predicts S&P 500 index stock price directions using the historical S&P 500 prices and the articles crawled from Reuters and Bloomberg, and the second experiment forecasts the price trends of VN-index using VietStock news and stock prices from cophieu68. Results show that: 1) two-stream GRU outperforms state-of-the-art models; 2) Stock2Vec is more efficient in dealing with financial datasets; and 3) applying the model, a simulation scenario proves that our model is effective for the stock sector.