Miracle-dz/UniFAR-FTUs huggingface dataset:
Measuring the violence experienced by sexual minorities: Sampling, data collection strategies, and population heterogeneity

Based on data from the VIRAGE (Violence and Gender Relations: INED, 2015–2016) survey, this article explores reports of violence in minority populations through the case of family violence reported by members of sexual minorities. VIRAGE provides two samples of homo-/bisexual respondents who answered the same questionnaire: a volunteer sample recruited through a communications campaign, who responded via Internet; and respondents to a general population telephone survey who identified as lesbian, gay or bisexual. Sexual identification is a sensitive issue, and surveys of private households do not necessarily capture either all victims of violence or all of those who identify as homosexual or bisexual. The general population sample thus cannot be considered representative of these groups. Lesbian and bisexual women in both samples reported more family violence than gay and bisexual men. Homo-/bisexual respondents in VIRAGE’s convenience sample reported more experiences of violence than those in its general population sample. This difference may be explained by various factors: effects of the data collection mode, and of data collection strategies more generally, as well as the heterogeneity of populations in terms of either exposure to violence or the propensity to report it. We use logistic regression methods to understand these differences, controlling for the differences between the characteristics of the respondents in the two samples. In addition to sociodemographic characteristics, we hypothesized that sexual trajectories and practices of sociability among homosexuals and bisexuals could affect the reporting and perception of violence. After these analyses, differences remain, but to a variable extent depending on sex, sexual identification, and forms of violence. The resulting models explain the differences in reporting between samples for men less well than for women. This result can be interpreted as the consequence of a difference between women’s and men’s exposure to violence: independently of the effects of data collection mode and sampling differences, the high probability that female sexual minorities will experience family violence leads to relatively high reporting in the two samples.
Network Calculus-Based Latency for Time-Triggered Traffic under Flexible Window-Overlapping Scheduling (FWOS) in a Time-Sensitive Network (TSN)

Deterministic latency is an urgent demand to pursue the continuous increase in intelligence in several real-time applications, such as connected vehicles and automation industries. A time-sensitive network (TSN) is a new framework introduced to serve these applications. Several functions are defined in the TSN standard to support time-triggered (TT) requirements, such as IEEE 802.1Qbv and IEEE 802.1Qbu for traffic scheduling and preemption mechanisms, respectively. However, implementing strict timing constraints to support scheduled traffic can miss the needs of unscheduled real-time flows. Accordingly, more relaxed scheduling algorithms are required. In this paper, we introduce the flexible window-overlapping scheduling (FWOS) algorithm that optimizes the overlapping among TT windows by three different metrics: the priority of overlapping, the position of overlapping, and the overlapping ratio (OR). An analytical model for the worst-case end-to-end delay (WCD) is derived using the network calculus (NC) approach considering the relative relationships between window offsets for consecutive nodes and evaluated under a realistic vehicle use case. While guaranteeing latency deadline for TT traffic, the FWOS algorithm defines the maximum allowable OR that maximizes the bandwidth available for unscheduled transmission. Even under a non-overlapping scenario, less pessimistic latency bounds have been obtained using FWOS than the latest related works.
Effectiveness of Signal Precision and Risky Choice

Higher signal precision helps to predict returns more accurately. But higher signal precision requires higher more costs and longer time. The acquisition of higher precision signals has two opposite effects for investors. First, the higher precision helps with return forecast. Second, the longer processing time is a disadvantage for decision making. We build a rational expected model under the assumption that the longer processing time takes, the higher the signal precision. The results show that higher signal precision is not always better after considering signal processing time. There is an optimal signal waiting time for investors.
A soft switching four‐phase converter with ultra‐high step down conversion ratio and automatic uniform current sharing

This paper introduces a new high step down four-phase converter with soft switching and automatic uniform current sharing. The phase number of the introduced topology can be expanded. In this converter, the main switches are turned on under zero voltage zero current switching condition and turned off under zero voltage switching. Also, the auxiliary switches and diodes operate respectively under zero voltage switching and zero current switching conditions. In the proposed architecture, the duty cycle is extended and the semiconductors voltage stress is reduced by applying series capacitors and coupled inductors. The leakage energy associated with the coupled inductors is absorbed and the reverse recovery losses of diodes are eliminated. Uniform current sharing between four phases is achieved without any extra current sharing control circuit. Furthermore, by utilizing the interleaved method, the current stress and the output current ripple are reduced. This converter provides above advantages while its input and output grounds are connected. As a result, the introduced topology can provide high step down conversions at high frequen-cies. The converter operation and its characteristics are analysed in detail. The accuracy of the theoretical analysis is veriﬁed by a laboratory prototype.
Temporal Knowledge Graph Embedding for Effective Service Recommendation

Over the last decade, service selection and recommendation had been two strongly related service filtering steps. While service selection aims to filter the best available services according to QoS and contextual criteria, service recommendation refines the selection results by taking into account additional criteria, such as users feedbacks and ratings, similarities between users tastes, etc. However, the ever changing services environment, users tastes, as well as the perception and popularity of available services, rise a question regarding the appropriate means to capture and analyze such changes over time. Most service recommendation solutions are static and do not offer a multi-relational modeling of user-service interactions over time. Time is a contextual dimension that has, recently, received a lot of attention, leading to a new class of recommender systems, called time-aware recommender systems. In this work, we propose a service recommendation method that takes advantage of temporal knowledge graphs. As a de facto standard to model multiple and complex interactions between heterogeneous entities, knowledge graphs will serve as a historical knowledge base for our TASR system. We, first, model the user-service interactions over time, by constructing a temporal service knowledge graph (TSKG) that will be later enriched through a completion step. Second, to explore the TSKG and extract top-rated services, we use Convolutional Neural Networks (CNN) to embed the TSKG into a low-dimensional vector space, facilitating then its mining. Experimental studies have proven the effectiveness and accuracy of our approach, compared to traditional TASR methods and time-unaware KG-based recommendation.
The Beautiful and the Fit Reap the Spoils: Body Image as a Condition for the Positive Effects of Electronic Media Communication on Well-being Among Early Adolescents

The effects of electronic media communication (EMC) and social media on young people’s health and well-being remain under debate, with no conclusive evidence on the connection between the two. By using data on 1,843 early adolescents aged 12–17 years provided by the Danish Health Behaviour in School-aged Children study and ordinary least squares (OLS) regression models and by measuring the intensity of EMC instead of the time spent on social media, the study finds that early adolescents tend to experience greater feelings of well-being with a higher intensity of EMC. However, this relationship is conditional. A negative perceptual body image acts as a moderator of the relationship between the intensity of EMC and well-being, whereas the positive relationship between EMC disappears under the condition of a negative body image. These findings provide nuance to the debates on the ways in which EMC affects young people.
The impact of emotional signals on credibility assessment

Fake news is considered one of the main threats of our society. The aim of fake news is usually to confuse readers and trigger intense emotions to them in an attempt to be spread through social networks. Even though recent studies have explored the effectiveness of different linguistic patterns for fake news detection, the role of emotional signals has not yet been explored. In this paper, we focus on extracting emotional signals from claims and evaluating their effectiveness on credibility assessment. First, we explore different methodologies for extracting the emotional signals that can be triggered to the users when they read a claim. Then, we present emoCred, a model that is based on a long‐short term memory model that incorporates emotional signals extracted from the text of the claims to differentiate between credible and non‐credible ones. In addition, we perform an analysis to understand which emotional signals and which terms are the most useful for the different credibility classes. We conduct extensive experiments and a thorough analysis on real‐world datasets. Our results indicate the importance of incorporating emotional signals in the credibility assessment problem.
Immersion and invariance control for Euler angles of a fixed‐wing unmanned aerial vehicle

In this paper, an asymptotically stabilizing, nonlinear flight controller design via immersion and invariance (I&I) approach for a fixed‐wing unmanned aerial vehicle is presented. The objective is to adjust pitch, roll, and yaw angles with the control inputs aileron, elevator, and rudder deflections. The important issues in designing a controller for fixed‐wing unmanned aerial vehicles (UAVs) are to cope with its nonlinear dynamics and to obtain a controller that can deal with various disturbances. Existing linear controllers cannot deal well with the nonlinear dynamics of the UAVs and that can not guarantee stability outside of the considered operating point. On the other hand, widely used nonlinear controllers have some weaknesses. Such as sliding mode controllers are robust to disturbances but suffer from the chattering phenomenon, and the backstepping controllers are not very robust to disturbances. The proposed controller ensures global stability with smooth and precise reference tracking and also yields significant disturbance attenuation without the chattering phenomenon. I&I approach also enables us to directly assign closed‐loop dynamics. Thus, tuning of the proposed controller is straightforward. Most of the other nonlinear methods do not have straightforward tuning of control parameters to assign desired dynamics to a closed‐loop system. The superior performance of the proposed controller is shown via simulations for various disturbances in comparison with the sliding mode controllers; the one with standard control law and the one with modified control law that eliminate the chattering phenomenon.
Molecular Docking of Polyphenol Compounds from Anacardium occidentale with Alpha-Glucosidase and Dipeptidyl-Peptidase-4 Enzymes

Type 2 diabetes mellitus (T2DM) is a chronic disease, in which the body failed to regulate blood glucose level due to insulin resistance. This condition may lead to high glucose level, which could potentially causes many serious health problems associated with cardiovascular system, nerve, eye and kidney. In treatment of T2DM, enzymes such as alpha-glucosidase (AG) and dipeptidyl-peptidase IV (DPP-4) have become the main targets since these enzymes play important roles in controlling the blood glucose level in the human body. In this study, the computational approach using molecular docking simulation study was used to predict the interaction and binding affinity of polyphenol compounds from Anacardium occidentale (A. occidentale) towards the AG and DPP-4 enzymes. The results were analysed based on three parameters: binding energy value, hydrogen bond formation and hydrophobic interaction between the compound and the protein at the binding site. The result showed that myricetin interacted with AG with the lowest binding energy of -7.6 kcal/mol and formed only one hydrogen bond to the Asp327 residue. In contrast, acarbose the positive control, interacted with many residues such as Asp327, Asp443 and Asp542 with the binding energy of - 6.0 kcal/mol. As for DPP-4 enzyme, sitagliptin was predicted as the best binder out of 15 polyphenols with binding energy of -9.2 kcal/mol. At the DPP-4 enzyme druggable region, sitagliptin formed an interaction with Tyr547 residue. In conclusion, our result suggested alpha-glucosidase as the most promising enzyme interacted with polyphenol compounds with favourable inhibitory effect since it can interact better than the current anti-diabetic drug, acarbose.
Student belonging: the impact of disability status within and between academic institutions.

Belonging at university is a complex and important issue which relates to student attainment but is more challenging for nontraditional students, including those with disability. This study, part of a larger project, explored differences in academic selfconfidence and engagement, belonging, peer belonging and institutional acceptance in those with and without disability in two academic institutions. Quantitative data, collected using a series of statements in online questionnaires, indicated that academic self-confidence was significantly lower in those with disability, as were aspects of peer belonging. By contrast, academic engagement and institutional acceptance did not differ for most statements by disability status. Possible reasons for this, and the implications of the findings, are discussed.
Highly efficient conversion of sugarcane bagasse pretreated with liquid hot water into ethanol at high solid loading

ABSTRACT Liquid hot water (LHW), an environmental-friendly physico-chemical treatment, was applied to pretreat the sugarcane bagasse (SCB). Tween80, a non-ionic surfactant, was used to enhance the enzymatic hydrolysis of the pretreated SCB. It found that 0.125 mL Tween80 /g dry matter could make the maximum increase (33.2%) of the glycan conversion of the LHW-pretreated SCB. A self-designed laboratory facility with a plate-and-frame impeller was applied to conduct batch hydrolysis, fed-batch hydrolysis, and the process of high-temperature (50°C) fed-batch hydrolysis following low-temperature (30°C) simultaneous saccharification and fermentation (SSF) which was adopted to overcome the incompatible optimum temperature of saccharification and fermentation in the SSF process. After hydrolyzing LHW-pretreated SCB for 120 h with commercial cellulase, the total sugar concentration and glycan conversion obtained from fed-batch hydrolysis were 91.6 g/L and 68.3%, respectively, which were 9.7 g/L and 7.3% higher than those obtained from batch hydrolysis. With Saccharomyces cerevisiae Y2034 fermenting under the non-sterile condition, the ethanol production and theoretical yield obtained from the process of SSF after fed-batch hydrolysis were 55.4 g/L and 88.3% for 72h, respectively, which were 15.5 g/L and 24.7% higher than those from separate fed-batch hydrolysis and fermentation. The result of this work was superior to the reported results obtained from the LHW-pretreated SCB.
Structure and Formation Kinetics of Millimeter‐Size Single Domain Supercrystals

Organizing nanoparticles (NPs) into periodic structures is a central goal in materials science. Despite progress in the last decades, it is still challenging to produce macroscopic assemblies reliably. In this work, the analysis of the pervaporation‐induced organization of gold octahedra into supercrystals within microfluidic channels using a combination of X‐ray scattering techniques and FIB‐SEM tomography is reported. The results reveal the formation of a single‐domain supercrystal with a monoclinic C2/m symmetry and long‐range order extending over the dimensions of the microfluidic channel, covering at least 1.7 × 0.3 mm2. Time‐resolved small angle X‐ray scattering analysis shows that the formation of the superlattice involves an accumulation of the NPs within the channel before the nucleation and growth of the supercrystal. The orientation of the crystal remains unchanged during its formation, suggesting a growth mechanism directed by the channel interface. Together, these results show the potential application of the pervaporation strategy to providing spatially determined control over NP crystallization, which can be used for the rational fabrication of nanomaterial architectures.
NUMERICAL STUDY OF HEAT TRANSFER OF A SINGLE U-TUBE IN VERTICAL GROUND-COUPLED HEAT PUMP SYSTEMS

The heat transfer rate of a single U-tube ground heat exchanger was studied numerically. First, a 3D 60-m full scale computational model of a working single U-tube ground heat exchanger was built and numerical simulation was performed. The simulation was validated by comparing numerically calculated results with experimental results. After that, two models are built to compute the heat extraction rate of a single U-tube of a heat pump operating in both cooling and heating mode, under both continuous and cyclic operation. The effects of borehole depth, inlet temperature and velocity of the heat transfer medium on the heat transfer rate were investigated, for both cooling and heating mode, continuous and cyclic operation. Nomenclature a thermal diffusion coefficient cp specific heat capacity H borehole depth, m T temperature μ dynamic viscosity ρ density P pressure q heat transfer rate per unit depth. Q heat flux u,v,w velocity at the direction of x,y, z, respectively. x,y,z rectangular coordinates
Fire-driven landscape heterogeneity shapes habitat selection of bighorn sheep

Patterns in disturbance severity and time since fire can drive landscape heterogeneity that is critical to conservation; however, there is limited understanding of how wildlife interact with the spatial–temporal complexities of disturbance outcomes and at what scales. We conducted multiscale modeling of habitat selection for male and female Rocky Mountain bighorn sheep (Ovis canadensis canadensis) over an 8-year period. We aimed to identify the spatial scales at which bighorn sheep responded to various habitat features and determine how fire severity and time since fire can shape habitat selection by bighorn sheep over different seasons and between sexes. With the exception of litter cover, spatial scales that extended beyond the finest spatial grain (i.e., a 30-m pixel) to include the surrounding landscape were better at predicting habitat selection. Escape terrain, elevation, fire severity, year, perennial and annual forb and grass cover, and shrub cover occurred in every best-supported model. Associations with escape terrain, elevation, and perennial and annual forb and grass cover varied by sex and season. In contrast, bighorn sheep were consistently positively associated with low- and high-severity fire. Females increased use of low- and high-severity burned areas with greater time since fire, while males tended to decrease use of areas that burned at high severity with greater time since fire. Our results support the importance of landscape heterogeneity created by fire severity and time since fire for Rocky Mountain bighorn sheep and reinforces calls to integrate disturbance-driven heterogeneity into our assessments and management of wildlife.
Future Trend in Wearable Electronics in the Textile Industry

Smart wearable textiles can sense, react, and adapt themselves to external conditions or stimuli, and they can be divided into active and passive smart wearable textiles, which can work with the human brain for cognition, reasoning, and activating capacity. Wearable technology is among the fastest growing parts of health, entertainment, and education. In the future, the development of wearable electronics will be focused on multifunctional, user-friendly, and user acceptance and comfort features and shall be based on advanced electronic textile systems.
Filicides - a case series analysis

ABSTRACT Filicides lead to questions about motives and missed opportunities for prevention. The development of preventive strategies is difficult due to heterogeneous perpetrator-victim dynamics. Eighteen child killings by parents over a period of 10 consecutive years in the catchment area of Dusseldorf’s Institute of Legal Medicine were identified, and the autopsy reports and prosecution files were analysed. With regard to motives and psychodynamics, a heterogeneous group of perpetrators were identified; the perpetrators were responsible for 8 accidental filicides, 3 killings of unwanted children, 1 killing during perpetrator psychosis, 1 spousal revenge killing and 5 homicide-suicides. Except for the homicide-suicides, overburdening seemed to be the main risk factor for the killings. Preventive measures are difficult to establish. They should focus on awareness campaigns and increasing or establishing multi-professional support for affected families.
Green synthesis of 1,7-bis(substituted phenyl)1,6-heptadiene-3,5-diones and their inhibition of human pathogenic bacteria

Abstract Curcumin analogs are synthesized with solid support under the concept of green chemistry, i.e. in the absence of organic solvents or hazardous chemicals using silica-sulfuric acid under solvent free conditions. Their structures are established through infrared, NMR, and mass spectroscopy and elemental analysis. The antibacterial activities of the synthesized curcumin analogs are evaluated against three human pathogenic Gram negative bacteria, taking ciprofloxacin as standard compound. Most compounds exhibit some antibacterial activity, with an efficacy depending upon nature and position of the phenyl substituents. Graphical Abstract
PWM techniques for an asymmetric multilevel binary inverter: an FPGA‐based implementation

This paper deals with the design and implementation of the conventional Level-Shifted-PWM (LS-PWM) and the PWM-hybrid modulation techniques in a Field-Programmable Gate Array (FPGA) development card, applicable to binary asymmetric multilevel converters; particularly herein, the Binary-Asymmetric Cascade Multilevel Inverter is treated (B-ACMLI). We employ an FPGA-based switching-controller to provide pulses for Multi-level Inverter (MLI) power semiconductors via their gate-drivers. The modulation strategies were implemented via an FPGA with a 32-bit ﬂoating-point architecture considering the IEEE-754 standard’s recommendations. The portability of the design is ensured using VHDL . The use of embedded RAM blocks minimizes the logical resources consumed into the FPGA, increases overall speed, and reduces power consumption. A comparison is presented in terms of the number of resources used in both modulation techniques. A low-cost FPGA board named Pipistrello is used. Pipistrello is an FPGA development board for Xilinx Spartan-6 LX45, designed by Saanlima Electronics. The platform consisting of a single-phase seven-level inverter B-ACMLI hardware prototype. The experimental results show the effectiveness of the approach. As isolated voltage-sources, photovoltaic modules are used for the experimental setup to the B-ACMLI.