Miracle-dz/UniFAR-FTUs huggingface dataset:
Closed and Open World Multi-shot Person Re-identification. (Ré-identification de personnes à partir de multiples images dans le cadre de bases d'identités fermées et ouvertes)

More than ever, in today’s context of insecurity and terrorism, person re-identification based on video surveillance images has become a hot research topic. Indeed, tracking an individual not only requires to track him within a camera, but also to re-identify him when he re-appears in other cameras. In recent years, remarkable progress has been achieved in person re-identification, notably thanks to the availability of larger datasets composed of thousands of identities captured by several cameras where each camera captures multiple images per identity. Yet, we are still far from being able to automatically re-identify people accurately in real life. Considering the evolution of the available research data and the real applications needs, this thesis has followed one major research axis. How can we tackle the challenging question of open world re-identification in which the person we want to re-identify might not appear in the database of known identities? A secondary research axis consisted in relevantly making use of the multiple images that are available for each identity. The open world re-identification task we consider in this thesis consists in two subtasks: a detection task and a re-identification task. We are given a set of known identities, the gallery identities, but since we are in an open world situation, this set of known identities is supposed not to be overcomplete. Therefore, when presented a query person also referred to as probe person, the detection task aims at determining whether or not the query person is a probable known gallery person. Since the probe person might look similar to several gallery identities, the goal of the re-identification task is to the gallery identities from the most probable match to the least likely one. Our first contribution, COPReV for Closed and Open world Person RE-identification and Verification, is mainly designed for tackling the decision aspect of the problem. We formulate the re-identification task solely as a verification task and aim at determining whether two sets of images represent the same person or two distinct people. With this information, we can find out whether the query person has been identified previously or not and if so, who he is. This is achieved by learning a linear transformation of the features so that the distance between features of the same person are below a threshold and that of distinct people are above that same threshold. The
Classification of malignancy of lung nodules in CT images using Convolutional Neural Network

Lung cancer presents the highest mortality rate, besides being one of the smallest survival rates after diagnosis. Thereby, early detection is extremely important for the diagnosis and treatment. This paper proposes three different architectures of Convolutional Neural Network (CNN), which is a deep learning technique, for classiﬁcation of malignancy of lung nodules without computing the morphology and texture features. The methodology was tested onto the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI), with the best accuracy of 82.3%, sensitivity of 79.4% and speci-ﬁcity 83.8%.
Selecting Fully‐Modified XNA Aptamers Using Synthetic Genetics

This unit describes the application of “synthetic genetics,” i.e., the replication of xeno nucleic acids (XNAs), artificial analogs of DNA and RNA bearing alternative backbone or sugar congeners, to the directed evolution of synthetic oligonucleotide ligands (XNA aptamers) specific for target proteins or nucleic acid motifs, using a cross‐chemistry selective exponential enrichment (X‐SELEX) approach. Protocols are described for synthesis of diverse‐sequence XNA repertoires (typically 1014 molecules) using DNA templates, isolation and panning for functional XNA sequences using targets immobilized on solid phase or gel shift induced by target binding in solution, and XNA reverse transcription to allow cDNA amplification or sequencing. The method may be generally applied to select fully‐modified XNA aptamers specific for a wide range of target molecules. © 2018 by John Wiley & Sons, Inc.
Liquid In fi ltration into Carbon Nanotube Fibers : E ff ect on Structure and Electrical Properties

Jing Qiu, Jeronimo Terrones, Juan J. Vilatela, Mary E. Vickers, James A. Elliott, and Alan H. Windle* Department of Materials Science, University of Cambridge, 27 Charles Babbage Road, Cambridge, Cambridgeshire CB3 0FS, United Kingdom. These authors made equal contributions to the work. All authors have given approval to the final version of the manuscript. Present address: IMDEA Materials Institute, Eric Kandel 2, Getafe, Madrid 28906, Spain.
Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization

Large-scale distributed optimization is of great importance in various applications. For data-parallel based distributed learning, the inter-node gradient communication often becomes the performance bottleneck. In this paper, we propose the error compensated quantized stochastic gradient descent algorithm to improve the training efficiency. Local gradients are quantized to reduce the communication overhead, and accumulated quantization error is utilized to speed up the convergence. Furthermore, we present theoretical analysis on the convergence behaviour, and demonstrate its advantage over competitors. Extensive experiments indicate that our algorithm can compress gradients by a factor of up to two magnitudes without performance degradation.
Users’ Opinion About a Virtual Reality System as an Adjunct to Psychological Treatment for Stress-Related Disorders: A Quantitative and Qualitative Mixed-Methods Study

This study aims to explore patients’ and therapists’ attitudes about the psychological treatment they received (patients) or applied (therapists). The treatments were standard CBT protocols for post-traumatic stress disorder (PTSD), complicated grief (CG), or adjustment disorders (ADs), depending on each patient diagnosis. The treatments were delivered following a traditional format or supported by a virtual reality (VR) system “EMMA’s WORLD” designed for the treatment of stress-related disorders. “EMMA’s WORLD” is a VR application in which patients can explore negative experiences using different virtual elements that can be customized to make them more meaningful to the user. The sample was composed of two groups: the “professionals” (N = 10) were all clinical psychologists who applied the same psychological treatment in both the traditional format (“traditional condition”) and using the VR system (“EMMA” condition). The second group consisted of a sample of patients (N = 50) who met the criteria for at least one of three different diagnoses: PTSD (N = 15), CG (N = 15), or AD (N = 20). 25 patients received treatment in the traditional format and 25 supported by the VR system. The patients were asked about their expectations (before treatment) and satisfaction (after treatment) with the treatment they received. All the therapists were asked their opinions about both treatment conditions. A mixed-methods approach using quantitative and qualitative methodologies was used. In both conditions, high scores were observed, and the patient’s opinions were even better when they have already received the treatments. A more pronounced pre-test–post-test change in the EMMA therapy group than in the traditional group was observed. EMMA’s World was well-accepted by both patients and therapists, and it helped to foster motivation in patients, while helping the therapist to apply the treatment. Thus, VR can be useful as an adjunct tool to enhance the treatment.
Security solutions against attacks in mobile ad hoc networks and their verification using BAN logic

In the last few years, there has been tremendous interest in ad hoc wireless networks as they have massive military and commercial potential. An ad hoc wireless network serves as an independent network that comprises of mobile devices that utilize wireless transmission for communication, having no fixed infrastructure. These networks eliminate the complexity of infrastructure setup and hence can be deployed in quick time. However, on the negative side, such networks are very vulnerable to attacks against availability, service integrity, security, privacy and several other possible threats. To overcome these attacks, several security mechanisms have been proposed to ensure the reliability of ad hoc networks.
Anaphora Resolution with the ARRAU Corpus

The ARRAU corpus is an anaphorically annotated corpus of English providing rich linguistic information about anaphora resolution. The most distinctive feature of the corpus is the annotation of a wide range of anaphoric relations, including bridging references and discourse deixis in addition to identity (coreference). Other distinctive features include treating all NPs as markables, including non-referring NPs; and the annotation of a variety of morphosyntactic and semantic mention and entity attributes, including the genericity status of the entities referred to by markables. The corpus however has not been extensively used for anaphora resolution research so far. In this paper, we discuss three datasets extracted from the ARRAU corpus to support the three subtasks of the CRAC 2018 Shared Task–identity anaphora resolution over ARRAU-style markables, bridging references resolution, and discourse deixis; the evaluation scripts assessing system performance on those datasets; and preliminary results on these three tasks that may serve as baseline for subsequent research in these phenomena.
Identification of novel genes to assign enhanced tolerance to osmotic stress in Saccharomyces cerevisiae

Saccharomyces cerevisiae strains tolerant to osmotic stress are important for ethanol production during very high gravity (VHG) fermentation. We aimed to identify novel genes that confer enhanced tolerance to osmotic stress in S. cerevisiae. Two strains tolerant to up to 30% (w/v) glucose were isolated by screening a transposon-mediated mutant library. Two genes were identified: TIS11 and SDS23. In addition, the ability of these genes to confer osmotic stress tolerance was demonstrated by disrupting and overexpressing the open reading frame of each gene. The two transposon mutants grew faster than the control strain in YPD rich medium containing 30% (w/v) glucose and showed activation of Hog1p in response to VHG glucose. The disruption of genes identified in this study, TIS11 and SDS23, provides a basis for improved tolerance to osmotic stress under VHG fermentation condition.
Energy efficient routing considering link robustness in wireless sensor networks

One of the most limiting constraint for the widespread use of wireless sensor network (WSN) is the limited energy of the individual sensor node. The distributed nodes in the WSN need to communicate the information either directly or indirectly from the source to the destination. The selection of optimal path from the source to destination becomes very critical for network lifetime. To maximize the network lifetime, this paper proposes a modied version of Dijkstra's algorithm with a new evaluation metric. The evaluation metric considers the residual energy of the nodes, their distance, number of neighbors and the link reliability to minimize the energy consumption of the network. The simulation results show the proposed algorithm signicantly improves the network life, approximately 12.25% (27.73%) as compared to Dijkstra's and Floyd Warshall's algorithm, by minimizing the energy consumption by reducing the need to re-route the message due to link failure.
The Coping Strategies Employed by Female College Athletes after Losing a Game

The purpose of this study is to examine the coping strategies employed by university athletes who have lost in a competition. A sample of ten hand ball women athletes (age between 21-24 years old) who represented one of the largest universities in Kuala Lumpur in the Malaysian Inter-varsity games agreed to participate in this study. All of the athletes have signed the consent letter, giving their permission for the interview to be recorded. The result for content analysis has identified two major dimensions; 1) how athletes cope, and 2) ways to cope. In the first dimension (how athletes cope), three major themes have emerged from the interview, which are social support, problem solving, and doing other activities. On the other hand, the second dimension (ways to cope) has identified two major themes, which are concentration and self confidence. However, social support has been claimed by losing athletes as the main coping strategy used to overcome their grief after losing the competition. Suggestions are also recommended in the paper.
THE IMPACT OF GENDER ON CHILD DENTAL ANXIETY IN A SAMPLE OF EGYPTIAN CHILDREN (A CROSS-SECTIONAL STUDY)

INTRODUCTION: Despite the recent developments in the dental equipment and treatment procedures, dental fear and anxiety (DFA) arerelatively common among children and adults. Relating dental fear and anxiety to gender is a controversial issue in scientific literature.OBJECTIVES: The aim of this study is to examine the impact of gender on the child’s dental anxiety in a sample of Egyptian children.MATERIALS AND METHODS: One hundred and twenty-six children 6-10 years old (60 boys and 66 girls), at the Department of PediatricDentistry, Faculty of Dentistry Alexandria University were asked to participate in the study. Children answered the Child Fear Survey Schedule– Dental Subscale (CFSS-DS). RESULTS: About forty-six percent of the children in the studied sample were non-anxious, 30.2% were potentially anxious and only 23%were very anxious. Girls were significantly more dentally anxious than boys. (p=0.02). CONCLUSIONS: The level of DFA was affected by the child gender where girls were more dentally anxious than boys. Injection wasidentified as the most fearful item in the dental visit.KEYWORDS: Dental anxiety, dental fear, child gender, CFSS-D
A study on fuzzy controller and neuro-fuzzy controller for speed control of PMSM motor

Permanent Magnet Synchronous Motors (PMSM) are a popular method for motion actuation due to their long life, efficient use of power and low maintenance requirements. PMSM have been used widely in the control system of high performance depending development of the power electronic and control technology“, however, the performances of the PMSM are very hyper sensitive to the parameter and load variations. To overcome these problems several control schemes such as Fuzzy Logic Control (FLC), Neural Network (NN) and Sliding Mode Control have been preferred for speed control of the PMSM. FLC, NN algorithms have been used currently as effective methods in the control of system affected by the destroyed entrance which is unknown quality and unstraight line. Because of the absence of the structure of both methods has not been removed ANFIS algorithm has been created by the connection of both methods superiority. In this study, the ANFIS controller is designed for PMSM speed control.
The Bowtie Effect in Cylindrical Waveguides

Modes in step-index fibers are often studied using a scalar model, born to the approximations allowed by the assumption of low refractive index contrast. Such approximations lead to a perfectly linear polarization in the resulting modes, among which the Bessel-like ones are attracting increasing interest for their many applications. These modes, as described by the scalar model, have a circularly symmetric irradiance. Nevertheless, in some cases, their symmetry disappears as their intensity profile exhibits angular ripples that cannot be foreseen by the scalar approach. In this paper, this effect is thoroughly analyzed.
A novel approach for classification of hand movements using surface EMG signals

Surface Electromyography (EMG) signals are being used in various fields including myoelectric control for prosthetic devices, human machine-interaction and other clinical and biomedical applications. EMG signals acquired through surface electrodes include various sources of noise like electrode-skin interface and electromagnetic noise etc. Therefore, accurate processing and classification of EMG signals is a challenging step in order to achieve reliable results for myoelectric control and so on. This paper introduces a novel classifier using Stacked sparse autoencoders (SSAEs) for improved myoelectric control. Data of six surface EMG channels is collected from five able-bodied and two amputee subjects for two days using their right hand or the amputated one. For performance evaluation, offline classification error is used and performance of SSAEs is compared with state of the art LDA. For within day analysis, SSAEs (1.29 ± 0.83%) outperformed LDA (4.09 ± 2.15%) with p value of 0.0018 for both able-bodied and amputee subjects. In between days' analysis, SSAEs outperformed (P < 0.001) LDA for both able-bodied and amputee subjects. These findings suggest that deep features of Autoencoders have the potential to be used as control source for myoelectric control systems and it can significantly improve the performance as compared to classical machine learning algorithm.
Quantification of synovial cavity from knee X-ray images

The osteoarthritis (OA) is a common type of arthritis found in larger population in the world. Wear and tear occurring at the protective cartilage bone ends is the main cause of OA. To study the severity of OA, image Segmentation of synovial cavity in knee part is vital. In this work we propose an automatic segmentation algorithm for the segmentation of synovial cavity using image processing techniques. The OA affected knee images are enhanced using Wiener filter and image is binarized by applying thresholding. The region of interest is extracted by identifying concentration of synovial cavity. The unwanted region is cropped and synovial cavity is extracted by applying inverse transform. The segmentation results were compared with the manual segmentation obtained by the physicians and results are encouraging.
Synthesis, Characterization, and Function of an RNA‐Based Transfection Reagent

A synthetic 8‐mer, amphipathic, trans‐acting poly‐2′‐O‐methyluridylic thiophosphate triester RNA element (2′‐OMeUtaPS) can be prepared using solid‐phase synthesis protocols. 2′‐OMeUtaPS efficiently mediates the delivery of uncharged polyA‐tailed phosphorodiamidate morpholino (PMO) sequences in HeLa pLuc 705 cells, as evidenced by flow cytometry measurements. In this cell line, 2′‐OMeUtaPS‐mediated transfection of an antisense polyA‐tailed PMO sequence induces alternative splicing of an aberrant luciferase pre‐mRNA splice site, leading to restoration of functional luciferase, as quantitatively measured using a typical luciferase assay. 2′‐OMeUtaPS is also potent at delivering an uncharged antisense polyA‐tailed PMO sequence in muscle cells of the mdx mouse model of muscular dystrophy; targeting the polyA‐tailed PMO sequence against a splice site of the pre‐mRNA encoding mutated dystrophin triggers an alternate splicing event that results in excision of the mutated exon (exon 23) from the pre‐mRNA and production of functional dystrophin, as demonstrated by agarose gel electrophoresis. © 2018 by John Wiley & Sons, Inc.
How forage form can affect the fatty acid composition of animal products in the autumn- lambing flock

The study was carried out to evaluate the effect of forag e form around parturition on fatty acid (FA) composition of ewes' milk and on meat from suckling lambs (10-12 kg BW). Forty eight Churra Tensina ewes rearing single lambs were assigned to one of four treatments in a 2 x 2 factorial design. The factors were the physiological status (pre-partum, last month of pregnancy, vs post-partum, 5 weeks of lactation) and the feeding system (grazing vs hay indoors). From lambing to the target BW of lambs, weekly milk samples were recorded. After slaughter, samples of M. Longissimus dorsi muscle were taken. Both products were used to determine FA content. Results show that forage form around parturition affects milk FA of ewes, the post-partum period exerting greater influence than the pre-partum period. Forage source influences the intramuscular FA composition of suckling lambs meat to a lesser extent. CLA and n6/n3 ratio are the most affected by grazing, with a positive effect of this feeding management for human health. Pre- partum grazing, regardless of post-partum feeding, can improve the FA composition, increasing the CLA content in both milk and meat.
Learning what is above and what is below: horizon approach to monocular obstacle detection

A novel approach is proposed for monocular obstacle detection, which relies on self-supervised learning to discriminate everything above the horizon line from everything below. Obstacles on the path of a robot that keeps moving at the same height, will appear both above and under the horizon line. This implies that classifying obstacle pixels will be inherently uncertain. Hence, in the proposed approach the classifier's uncertainty is used for obstacle detection. The (preliminary) results show that this approach can indeed work in different environments. On the well-known KITTI data set, the self-supervised learning scheme clearly segments the road and sky, while application to a flying data set leads to the segmentation of the flight arena's floor.
Phytophthora infestans RXLR effector SFI5 requires association with calmodulin for PTI/MTI suppressing activity

Summary Pathogens secrete effector proteins to interfere with plant innate immunity, in which Ca2+/calmodulin (CaM) signalling plays key roles. Thus far, few effectors have been identified that directly interact with CaM for defence suppression. Here, we report that SFI5, an RXLR effector from Phytophthora infestans, suppresses microbe‐associated molecular pattern (MAMP)‐triggered immunity (MTI) by interacting with host CaMs. We predicted the CaM‐binding site in SFI5 using in silico analysis. The interaction between SFI5 and CaM was tested by both in vitro and in vivo assays. MTI suppression by SFI5 and truncated variants were performed in a tomato protoplast system. We found that both the predicted CaM‐binding site and the full‐length SFI5 protein interact with CaM in the presence of Ca2+. MTI responses, such as FRK1 upregulation, reactive oxygen species accumulation, and mitogen‐activated protein kinase activation were suppressed by truncated SFI5 proteins containing the C‐terminal CaM‐binding site but not by those without it. The plasma membrane localization of SFI5 and its ability to enhance infection were also perturbed by loss of the CaM‐binding site. We conclude that CaM‐binding is required for localization and activity of SFI5. We propose that SFI5 suppresses plant immunity by interfering with immune signalling components after activation by CaMs.
Inter image element loss less image compression with delimiter and folding

Digital color image is a grid of picture elements where each color is an ordered triplet consisting of at least three color components generally red, green and blue. In general each pixel occupies at least eight bits, a digital image consist of millions of picture elements lead to high storage space and high bandwidth required during the transmission in computer networks. The solution is to reduce the image file size that can be achieved through image compression. The image compression possible only when there exists and identified redundancy in digital images. The proposed method try to find and remove redundancy within pixel element based on inter element redundancy by dividing image element into individual digits. The repeated individual digits of image elements are folded into triplet and merged. Finally, high compression rates achieved through entropy coding.