Virtual Flux Predictive Direct Power Control of Five-level T-type Multi-terminal VSC-HVDC System

This paper proposes a Virtual Flux Predictive Direct Power Control (PDPC) for a five-level T-type multi-terminal Voltage Source Converter High Voltage Direct Current (VSC-HVDC) transmission system. The proposed PDPC scheme is based on the computation of the average voltage vector using a virtual flux predictive control algorithm, which allows the cancellation of active and reactive power tracking errors at each sampling period. The active and reactive power can be estimated based on the virtual flux vector that makes AC line voltage sensors not necessary. A constant converter switching frequency is achieved by employing a multilevel space vector modulation, which ensures the balance of the DC capacitor voltages of the five-level t-type converters as well. Simulation results validate the efficiency of the proposed control law, and they are compared with those given by a traditional direct power control. These results exhibit excellent transient responses during range of operating conditions

Etude et Caractérisation des Fils en Acier Dur Destinés pour la Fabrication des Torons

The main aim of this work is to study the evolution of the texture in the ferrite phase during plastic deformation by drawing pearlitic steel wires of grade (C82D) intended for manufacture of strand wires, and more generally to undertake a correlation between the microstructure and the behavior of these steel wires under mechanical stress. Wire drawing induces the development of the density of dislocations, the reduction of the interlamellar spacing and the refinement of grains sizes which leads to a strong hardening of the wires. This explains the increase in tensile strength from 1242 MPa to 2618 MPa with higher strain. In addition, the cementite lamellae are turned towards the wire drawing axis and the thickness of the lamellae decreases further when the level of deformation increases, this phenomenon leads to a somewhat fibrous structure. The quantitative analysis of the texture obtained by EBSD data shows the development and reinforcement of a fiber texture over the entire section of the drawn wire (center and surface). A variety of experimental measurement and characterization techniques have made it possible to carry out this work. These are scanning electron microscopy (SEM/EDX), X-ray diffraction, backscattered electron diffraction (EBSD), tensile and torsion tests and microhardness measurements, some of which have made it possible to correlate the microstructure to the mechanical properties

DiverGet: A Search-Based Software Testing Approach for Deep Neural Network Quantization Assessment

Quantization is one of the most applied Deep Neural Network (DNN) compression strategies, when deploying a trained DNN model on an embedded system or a cell phone. This is owing to its simplicity and adaptability to a wide range of applications and circumstances, as opposed to specific Artificial Intelligence (AI) accelerators and compilers that are often designed only for certain specific hardware (e.g., Google Coral Edge TPU). With the growing demand for quantization, ensuring the reliability of this strategy is becoming a critical challenge. Traditional testing methods, which gather more and more genuine data for better assessment, are often not practical because of the large size of the input space and the high similarity between the original DNN and its quantized counterpart. As a result, advanced assessment strategies have become of paramount importance. In this paper, we present DiverGet, a search-based testing framework for quantization assessment. DiverGet defines a space of metamorphic relations that simulate naturally-occurring distortions on the inputs. Then, it optimally explores these relations to reveal the disagreements among DNNs of different arithmetic precision. We evaluate the performance of DiverGet on state-of-the-art DNNs applied to hyperspectral remote sensing images. We chose the remote sensing DNNs as they're being increasingly deployed at the edge (e.g., high-lift drones) in critical domains like climate change research and astronomy. Our results show that DiverGet successfully challenges the robustness of established quantization techniques against naturally-occurring shifted data, and outperforms its most recent concurrent, DiffChaser, with a success rate that is (on average) four times higher.Comment: Accepted for publication in The Empirical Software Engineering Journal (EMSE

A Malaria Vaccine That Elicits in Humans Antibodies Able to Kill Plasmodium falciparum

BACKGROUND: Plasmodium falciparum merozoite surface protein 3 is a malaria vaccine candidate that was identified, characterised, and developed based on a unique immuno-clinical approach. The vaccine construct was derived from regions fully conserved among various strains and containing B cell epitopes targeted by human antibodies (from malaria-immune adults) that are able to mediate a monocyte-dependent parasite killing effect. The corresponding long synthetic peptide was administered to 36 volunteers, with either alum or Montanide ISA720 as adjuvant. METHODS AND FINDINGS: Both formulations induced cellular and humoral immune responses. With alum, the responses lasted up to 12 mo. The vaccine-induced antibodies were predominantly of cytophilic classes, i.e., able to cooperate with effector cells. In vitro, the antibodies induced an inhibition of the P. falciparum erythrocytic growth in a monocyte-dependent manner, which was in most instances as high as or greater than that induced by natural antibodies from immune African adults. In vivo transfer of the volunteers' sera into P. falciparum–infected humanized SCID mice profoundly reduced or abrogated parasitaemia. These inhibitory effects were related to the antibody reactivity with the parasite native protein, which was seen in 60% of the volunteers, and remained in samples taken 12 mo postimmunisation. CONCLUSION: This is the first malaria vaccine clinical trial to clearly demonstrate antiparasitic activity by vaccine-induced antibodies by both in vitro and in vivo methods. The results, showing the induction of long-lasting antibodies directed to a fully conserved polypeptide, also challenge current concepts about malaria vaccines, such as unavoidable polymorphism, low antigenicity, and poor induction of immune memory

High Therapeutic Efficacy of a New Survivin LSP-Cancer Vaccine Containing CD4+ and CD8+ T-Cell Epitopes

The efficacy of an antitumoral vaccine relies both on the choice of the antigen targeted and on its design. The tumor antigen survivin is an attractive target to develop therapeutic cancer vaccines because of its restricted over-expression and vital functions in most human tumors. Accordingly, several clinical trials targeting survivin in various cancer indications have been conducted. Most of them relied on short peptide-based vaccines and showed promising, but limited clinical results. In this study, we investigated the immunogenicity and therapeutic efficacy of a new long synthetic peptide (LSP)-based cancer vaccine targeting the tumor antigen survivin (SVX). This SVX vaccine is composed of three long synthetic peptides containing several CD4+ and CD8+ T-cell epitopes, which bind to various HLA class II and class I molecules. Studies in healthy individuals showed CD4+ and CD8+ T-cell immunogenicity of SVX peptides in human, irrespective of the individual's HLA types. Importantly, high frequencies of spontaneous T-cell precursors specific to SVX peptides were also detected in the blood of various cancer patients, demonstrating the absence of tolerance against these peptides. We then demonstrated SVX vaccine's high therapeutic efficacy against four different established murine tumor models, associated with its capacity to generate both specific cytotoxic CD8+ and multifunctional Th1 CD4+ T-cell responses. When tumors were eradicated, generated memory T-cell responses protected against rechallenge allowing long-term protection against relapses. Treatment with SVX vaccine was also found to reshape the tumor microenvironment by increasing the tumor infiltration of both CD4+ and CD8+ T cells but not Treg cells therefore tipping the balance toward a highly efficient immune response. These results highlight that this LSP-based SVX vaccine appears as a promising cancer vaccine and warrants its further clinical development

Pacifica: Poetry International: Revolutions in Tunisian Poetry

A collection of contemporary poetry from Tunisia, including poems in translation with their French and Arabic original texts

The impact of viral mutations on recognition by SARS-CoV-2 specific T cells.

We identify amino acid variants within dominant SARS-CoV-2 T cell epitopes by interrogating global sequence data. Several variants within nucleocapsid and ORF3a epitopes have arisen independently in multiple lineages and result in loss of recognition by epitope-specific T cells assessed by IFN-γ and cytotoxic killing assays. Complete loss of T cell responsiveness was seen due to Q213K in the A∗01:01-restricted CD8+ ORF3a epitope FTSDYYQLY207-215; due to P13L, P13S, and P13T in the B∗27:05-restricted CD8+ nucleocapsid epitope QRNAPRITF9-17; and due to T362I and P365S in the A∗03:01/A∗11:01-restricted CD8+ nucleocapsid epitope KTFPPTEPK361-369. CD8+ T cell lines unable to recognize variant epitopes have diverse T cell receptor repertoires. These data demonstrate the potential for T cell evasion and highlight the need for ongoing surveillance for variants capable of escaping T cell as well as humoral immunity.This work is supported by the UK Medical Research Council (MRC); Chinese Academy of Medical Sciences(CAMS) Innovation Fund for Medical Sciences (CIFMS), China; National Institute for Health Research (NIHR)Oxford Biomedical Research Centre, and UK Researchand Innovation (UKRI)/NIHR through the UK Coro-navirus Immunology Consortium (UK-CIC). Sequencing of SARS-CoV-2 samples and collation of data wasundertaken by the COG-UK CONSORTIUM. COG-UK is supported by funding from the Medical ResearchCouncil (MRC) part of UK Research & Innovation (UKRI),the National Institute of Health Research (NIHR),and Genome Research Limited, operating as the Wellcome Sanger Institute. T.I.d.S. is supported by a Well-come Trust Intermediate Clinical Fellowship (110058/Z/15/Z). L.T. is supported by the Wellcome Trust(grant number 205228/Z/16/Z) and by theUniversity of Liverpool Centre for Excellence in Infectious DiseaseResearch (CEIDR). S.D. is funded by an NIHR GlobalResearch Professorship (NIHR300791). L.T. and S.C.M.are also supported by the U.S. Food and Drug Administration Medical Countermeasures Initiative contract75F40120C00085 and the National Institute for Health Research Health Protection Research Unit (HPRU) inEmerging and Zoonotic Infections (NIHR200907) at University of Liverpool inpartnership with Public HealthEngland (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford.L.T. is based at the University of Liverpool. M.D.P. is funded by the NIHR Sheffield Biomedical ResearchCentre (BRC – IS-BRC-1215-20017). ISARIC4C is supported by the MRC (grant no MC_PC_19059). J.C.K.is a Wellcome Investigator (WT204969/Z/16/Z) and supported by NIHR Oxford Biomedical Research Centreand CIFMS. The views expressed are those of the authors and not necessarily those of the NIHR or MRC

Prevalence, antimicrobial susceptibility and risk factors associated with non-typhoidal Salmonella on Ugandan layer hen farms

Abstract Background Non-typhoidal Salmonella (NTS) are among the leading global foodborne pathogens and a significant public health threat. Their occurrence in animal reservoirs and their susceptibilities to commonly used antimicrobials are poorly understood in developing countries. The aim of this study was to estimate the prevalence, determine antimicrobial susceptibility and identify risk factors associated with NTS presence in laying hen farms in Uganda through a cross-sectional study. Results Pooled faecal samples were collected from 237 laying hen farms and these were analysed for NTS following standard laboratory procedures. In total, 49 farms (20.7%; 95% Confidence interval (CI): 15.6–25.6%) were positive for NTS presence. Altogether, ten Salmonella serotypes were identified among the confirmed 78 isolates, and the predominant serotypes were Salmonella Newport (30.8%), S. Hadar (14.1%), S. Aberdeen (12.8%), S. Heidelberg (12.8%), and S. Bolton (12.8%). Phenotypic antimicrobial resistance was detected in 45(57.7%) of the isolates and the highest resistance was against ciprofloxacin (50.0%) followed by sulphonamides (26.9%) and sulphamethoxazole/trimethoprim (7.7%). Resistance was significantly associated with sampled districts (p = 0.034). Resistance to three or more drugs, multi-drug resistance (MDR) was detected in 12 (15.4%) of the isolates, 9 (75%) of these were from Wakiso district. A multivariable logistic model identified large farm size (OR = 7.0; 95% CI: 2.5–19.8) and the presence of other animal species on the farm (OR = 5.9; 95% CI: 2.1–16.1) as risk factors for NTS prevalence on farms. Having a separate house for birds newly brought to the farms was found to be protective (OR = 0,4; 95% CI: 0.2–0.8). Conclusion This study has highlighted a high prevalence and diversity of NTS species in laying hen farms in Uganda and identified associated risk factors. In addition, it has demonstrated high levels of antimicrobial resistance in isolates of NTS. This could be because of overuse or misuse of antimicrobials in poultry production. Also importantly, the insights provided in this study justifies a strong case for strengthening One Health practices and this will contribute to the development of NTS control strategies at local, national and international levels