Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of edge magnetization and electric fields on zigzag silicene, germanene and stanene nanoribbons

Using a multi-orbital tight-binding model, we have studied the edge states of zigzag silicene, germanene, and stanene nanoribbons (ZSiNRs, ZGeNRs and ZSnNRs, respectively) in the presence of the Coulomb interaction and a vertical electric field. The resulting edge states have non-linear energy dispersions due to multi-orbital effects, and the nanoribbons show induced magnetization at the edges. Owing to this non-linear dispersion, ZSiNRs, ZGeNRs and ZSnNRs may not provide superior performance in field effect transistors, as has been proposed from single-orbital tight-binding model calculations. We propose an effective low-energy model that describes the edge states of ZSiNRs, ZGeNRs, and ZSnNRs. We demonstrate that the edge states of ZGeNR and ZSnNR show anti-crossing of bands with opposite spins, even if only out-of-plane edge magnetization is present. The ability to tune the spin polarizations of the edge states by applying an electric field points to future opportunities to fabricate silicene, germanene and stanene nanoribbons as spintronics devices.
Cavity Perturbation Technique to Characterize Dielectric Materials at Ka-band

The characterization of permittivity and dielectric loss of dielectric materials using a perturbation technique is conducted in simulation. The working frequency of this technique has been extended to the Ka-band. Simulation results demonstrate this perturbation technique is suitable for mm-wave characterization of high permittivity dielectric materials and maintains good accuracy.
11. Microvascular Complications and Foot Care: Standards of Medical Care in Diabetes—2019

The American Diabetes Association (ADA) “Standards of Medical Care in Diabetes” includes ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations, please refer to the Standards of Care Introduction. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes. org/SOC.
GPU-enhanced Multimodal Dense Matching

Multiple modalities for stereo matching are beneficial for robust path estimation and actioning of autonomous robots in harsh environments, e.g. in the presence of smoke and dust. In order to combine the information resulting from the different modalities, a dense stereo matching approach based on semi-global matching and a combined cost function using cross-based support regions and phase congruency shows a good performance. However, these computationally complex algorithmic steps set high requirements for the mobile processing platform and prohibit a real-time execution at limited power budget on mobile platforms. Therefore, this paper explores the usage of graphic processors for the parallelization and acceleration of the aforementioned algorithm. The resulting implementation performs the computation of phase congruency and cross-based support regions at 68 and 5 frames per second for $[960\mathrm{x}560]$ pixel images on a Nvidia Quadro P5000 and Tegra X2 GPU respectively.
Requirements for Power Hardware-in-the-Loop Emulation of Distribution Grid Challenges

The ongoing transition of low voltage (LV) power grids towards active systems requires novel evaluation and testing concepts, in particular for realistic testing of devices. Power Hardware-in-the-Loop (PHIL) evaluations are a promising approach for this purpose. This paper presents preliminary investigations addressing the systematic design of PHIL applications and their applicable stability mechanisms and gives a detailed review of the related work. A requirement analysis for emulation of grid situations demanding system services is given and the realization of a PHIL setup is demonstrated in a residential scenario, comprising a hybrid electrical energy storage system (HESS).
Early age at menarche is associated with insulin resistance: a systemic review and meta-analysis

ABSTRACT Objectives: We aimed to conduct a systemic review and meta-analysis of the relevant studies to further investigate the association between age at menarche and insulin resistance. Methods: PubMed, EMBASE, and Web of Science (SCI) databases were systemically searched until December 2017. Observational studies comparing the incidences of insulin resistance in patients with early, average, and late menarchal ages were identified. Weighted mean difference (WMD) for HOMA-IR scores and fasting serum insulin levels in early vs late, early vs average. and average vs late comparisons were calculated with a random- or fixed-effects model. Results: A total of eight articles involving 5504 subjects were finally included. In the analysis of HOMA-IR, the pooled WMDs in five studies were 0.45 (95% confidence interval [CI] 0.31–0.60, p < 0.001), 0.40 (95% CI 0.28–0.52, p < 0.001), and −0.01 (95% CI −0.09 to 0.07, p = 0.854) for early vs late, early vs average, and average vs late comparisons, respectively. The fasting serum insulin levels in eight studies were analyzed, and it was significantly higher in subjects with earlier age at menarche (WMD 1.28, 95% CI 0.92–1.63, p < 0.001 for early vs late comparison, WMD 1.28, 95% CI 1.13–1.43, p < 0.001 for early vs average comparison) with mild and acceptable heterogeneity (I2 = 42.5% and 7.4%, respectively). Publication bias was not detected via funnel plots and Egger’s tests. Conclusions: Our study revealed that earlier age at menarche was significantly associated with insulin resistance. Trial Registration Number: CRD42018083874
Association between alcoholic interventions and abstinence rates for alcohol use disorders

Objective: The aim of present study is to quantitatively evaluate the association between different interventions and abstinence rates based on network meta-analysis. Method: Following PRISMA guidelines, randomized clinical trials that compared different alcoholic interventions for alcohol use disorders associated with abstinence rates in treatment sessions or/and follow-up sessions were recruited. Main data synthesis was performed by Bayesian random-effects network meta-analyses, and the relative ranking of interventions was estimated by cumulative probability P values (SUCRA). Funnel plot symmetry was used to detect publication bias. Moreover, pair-wised comparison was also conducted to determine the statistical difference and forest plots were generated to calculate the differences between the groups. The Grades of Recommendations Assessment, Development and Evaluation (GRADE) criteria were utilized for the recommendations of evidence from pairwise direct comparisons. Results: A total of 137 RCTs containing 27,282 participants and 8 variations of psychotherapy, pharmacotherapy, contingency management, and brief intervention used as treatment interventions were included. In summary, contingency management plus psychotherapy was demonstrated to be effective and possessed the best rank of achieving the highest abstinence rate in treatment sessions (SUCRA, 0.61). Pharmacotherapy plus psychotherapy also revealed its efficacy and was associated with the highest abstinence rate in follow-up sessions (SUCRA, 0.40). More importantly, psychotherapy alone was demonstrated not to be associated with higher abstinence rates in both treatment (OR, 1.052; 95% CI, 0.907–1.220) and follow-up sessions (OR, 0.967; 95% CI, 0.552–1.693), yet pharmacotherapy seemed to be the only intervention associated with higher abstinence rates compared to controls in both sessions (treatment session: OR, 1.074; 95% CI, 1.002–1.152) (follow-up session: OR, 1.442; 95% CI, 1.094–1.900). Conclusions: Contingency management plus psychotherapy and pharmacotherapy plus psychotherapy were demonstrated to be associated with the highest abstinence rates in treatment sessions and follow-up sessions, respectively. However, contingency management and pharmacotherapy seemed to be the substantial crucial factors allowing for the maintenance of the highest abstinence rates in respective sessions, although we need more evidence for further validation.
Distributed Joint Source-Channel Coding Using Quasi-Uniform Systematic Polar Codes

This paper proposes a distributed joint source-channel coding (DJSCC) scheme using polar-like codes. In the proposed scheme, each distributed source encodes source message with a quasi-uniform systematic polar code (QSPC) or a punctured QSPC, and only transmits parity bits over its independent channel. These systematic codes play the role of both source compression and error protection. For the infinite code-length, we show that the proposed scheme approaches the information-theoretical limit by the technique of joint source-channel polarization with side information. For the finite code-length, the simulation results verify that the proposed scheme outperforms the distributed separate source-channel coding (DSSCC) scheme using polar codes and the DJSCC scheme using classic systematic polar codes.
Evaluation of Low-Cost Sensors for Ambient PM2.5 Monitoring

Low-cost sensors are an opportunity to improve the spatial and temporal resolution of particulate matter data. However, such sensors should be calibrated under conditions close to the final ones before any monitoring actions. The paper presents the results of a collocated comparison of four models of low-cost optical sensors with a TEOM 1400a analyser. SDS011 (Nova Fitness), ZH03A (Winsen), PMS7003 (Plantower), and OPC-N2 (Alphasense) sensors were used in this research. Three copies of each sensor model were placed in a common box to compare the sensor performance under the same measurement conditions. Monitoring of the PM2.5 fraction was conducted for almost half a year from 21 August 2017 to 19 February 2018 in Wrocław (Poland). Reproducibility between sensor units was assessed on the basis of coefficient of variation (CV). CV values were lower than 7% in the case of SDS011 and PMS7003 sensors and equal to 20% for OPC-N2 units. CV was higher than 50% for ZH03A, mainly due to malfunctions. During the measurements, the trends of outputs from sensors were generally similar to TEOM data, but significant overestimation of PM2.5 concentrations was observed for the sensor raw data. A high linear relationship between TEOM and sensors was noticed for 1 min, 15 min, and 1-hour averaged data for PMS7003 sensors (R2≈0.83–0.89), for SDS011 units (R2≈0.79–0.86), and for one unit of ZH03A (R2≈0.74–0.81). R2 values for daily averages were at the level 0.91–0.93 for PMS7003, 0.87–0.90 for SDS011, and 0.89 for ZH03A. OPC-N2 had only a moderate linear relationship with TEOM (R2≈0.53–0.69 for daily data and 0.43–0.61 for shorter time averages). Quite large dispersion of data and high relative errors of PM2.5 estimation were observed for concentration ranges below 20–30 μg/m3. The impact of high relative humidity level was observed for SDS011 and OPC-N2 devices—clear overestimation of outputs was observed above 80% RH.
Boosting Few-Shot Image Recognition Via Domain Alignment Prototypical Networks

Human has the ability of drawing inferences about other things from only one instance. Few-shot learning is aimed at imitating this generalized learning behavior of human beings, where the learning machine is expected to recognize novel categories not seen in the training set, given only a few training data for each novel category. In this paper, we enhance the Prototypical Network for few-shot learning tasks by introducing a domain alignment module, which takes into account the domain shifts existing between different categories. Compared to original Prototypical Network (PN), the most excellent model for few-shot learning at present, our proposed Domain Alignment Prototypical Network (DA-PN) is able to abate the distribution differences among the data of training and test classes, further optimizing the embedding space of prototype feature for each category and then boosting few-shot recognition. Comprehensive empirical evidence demonstrates that the proposed DA-PN can yield state-of-the-art few-shot recognition performance on the public benchmark dataset mini-ImageNet as well as a novel proposed few-shot dataset MNIST&CIFAR10.
Joint PHY-MAC Realistic Performance Evaluation of Body-to-Body Communication in IEEE 802.15.6 and SmartBAN

This paper presents the joint physical-medium access control (PHY-MAC) performance analysis of inter-BAN communication systems using realistic body-to-body (B2B) wireless channel model in IEEE 802.15. 6 and smartBAN standards. The time-varying distances for the space-time B2B link variations are generated by real-time motion capture traces which are then introduced into already established B2B wireless channel model to give the actual path-loss values in dynamic environments. The SNR (Signal to Noise Ratio), BER (Bit Error Rate) and PER (Packet Error Rate) computations are briefly discussed to give an overview of the radio link modeling employed in the simulations. Using the mobility and the proposed radio link models, a more tangible performance assessment of B2B systems with IEEE 802.15. 6 and SmartBAN specifications is achieved. Consequently, transmission power, packet length and data rate variations are investigated and the obtained results of packet reception rate (PRR) identify “head” as the best position to place the coordinator nodes for B2B communication.
Application of SDN Technologies to Protect Against Network Intrusions

This paper discusses the construction of an infrastructure for protecting against network intrusions based on SDN technologies. Protection technologies were developed earlier using rank distributions, and they allow for the finding of threshold values for the basic network variables, compile lists of regular users of the resource, and prepare databases of IP addresses from which intrusions are made in advance. It is proposed that all these methods can be improved by applying SDN technology, and an SDN infrastructure has been deployed for experimental testing of software modules being developed.
Beyond PTSD and Fear-Based Conditioning: Anger-Related Responses Following Experiences of Forced Migration—A Systematic Review

Introduction: Experiences of forced migration include traumas that are interpersonal in nature, as well as ongoing emotional responses, stress, and frustration in post-migration setti ngs. Open questions exist, regarding anger/anger-like responses following experiences of persecution and ongoing stress. The aim of this study was to explore the adaptive and maladaptive underlying mechanisms of anger/anger-like responses, cultural, linguistic, and social contingencies, and possible interventions for problematic anger behavior. Method: We searched two databases (PsycINFO and PILOTS) with the following search terms: (refugee OR “asylum seek*” OR IDP OR “internal* displac*” OR “forced migra*” OR “involuntary migra*”) AND anger. Findings: This search yielded 34 studies that were included in the final review. Although, anger is a moral, adaptive, and prosocial response, dysfunctional anger/anger-like responses arise from PTSD, “moral injury,” complicated grief, and independent forms of anger behavior. Cultural, linguistic, and social issues also emerged from the search. Finally, considerations for treatment and intervention are discussed. Discussion: Anger responses following experiences of forced migration may require assessment beyond PTSD models currently framed by DSM and ICD. A very promising framework is the Adaptation and Development after Persecution and Trauma (ADAPT) model. Implications: Further longitudinal and epidemiological research will be necessary to continue testing the ADAPT model and to begin the process of assessing its cross-cultural coherence in other refugee populations (e.g., see Hinton et al., 2003). As anger behavior is also a societal issue, avenues for reconciliation, expression of grievances, employment, civic participation, and integration are needed.
Reconnaissance de mots manuscrits par systèmes hybrides : Réseaux de neurones et modèles de Markov cachés

Ce memoire presente un systeme de lecture de mots manuscrits isoles, appartenant a un lexique, avec des techniques combinees reseaux de neurones (RN) et modeles de Markov caches (MMC). Les RN et les MMC ont ete abondamment etudies pour la reconnaissance de la parole entre autre. Leur maitrise a motive depuis 10 ans de nombreux travaux pour combiner les atouts des deux outils, en discrimination et en modelisation des sequences. Quelques systemes sont presentes pour la parole ou l'ecrit. Le principe des systemes hybrides RN et MMC est presente avec son apprentissage iteratif selon l'algorithme expectation maximisation (EM). Ce systeme pemet de remplacer la qualification vectorielle des MMC discrets, classification non supervisee qui perd beaucoup d'information, par un RN.
‘Perceptions of Performance Appraisal Quality’ and Employee Innovative Behavior: Do Psychological Empowerment and ‘Perceptions of HRM System Strength’ Matter?

Organizations need to be innovative for their long-term survival and this can be achieved when their employees demonstrate innovative behaviors at the workplace. Innovative behavior has thus received considerable attention from researchers, particularly on exploring the factors which foster employee innovative behaviors. Based on human resource system strength theory, the objective of this study is twofold. First, it examines the direct and indirect relationship between perceptions of performance appraisal quality (PPAQ) and innovative behavior mediated through psychological empowerment. Second, it examines the moderating effect of perceptions of HRM system strength in the hypothesized links. A total of 360 faculty members participated in the study from twelve public sector higher education institutes in Islamabad, Pakistan. Partial least squares structural equation modeling (PLS-SEM) is used for statistical analysis of the quantitative data collected through self-administered questionnaire. Results demonstrated that PPAQ is positively related with innovative behavior. The findings also support the mediating role of psychological empowerment and the moderating role of perceptions of human resource management (HRM) system strength. We contribute to the literature by demonstrating that HRM content and process are two complementary facets of an HRM system in bringing out positive work behaviors. A number of practical implications and directions for future research are outlined.
Low-Cost Software-Defined GPS Simulator with the Capability of Time Synchronization

In this paper, a low-cost software-defined Global Positioning System (GPS) simulator for indoor positioning is proposed. The purpose of the proposed GPS simulator is to generate GPS signals so that the users can obtain the desired positions in an indoor environment with conventional GPS receivers. Since some commercial GPS receivers cannot properly provide position solutions if the calculated time based on the simulated signals is earlier than the last measured time based on the actual signals, the proposed GPS simulator generates GPS signals that do not cause this problem. In order to achieve this, an outdoor receiver was utilized to retrieve live ephemeris data, and the proposed GPS simulator generated base band GPS signals that can provide a desired indoor position and time based on the ephemeris data. During the process of base band GPS signal generation, time delay in the simulation process was compensated. Then, the base band signals were modulated to GPS L1 frequency and were broadcast as radio frequency (RF) signals using a software-defined radio platform. The proposed GPS simulator was implemented using a u-blox M8T as an outdoor receiver and a USRP N210 as a software-defined radio platform. The performance of the proposed simulator was validated with another u-blox receiver as a user. The u-blox receiver successfully acquired the desired position with the simulated RF signals that were transmitted via a coaxial cable to the receiver.
Design of Stacked-MOS Transistor mm-Wave Class C Amplifiers for Doherty Power Amplifiers

This paper discusses the design requirements of class C auxiliary (aux) amplifiers deployed in Doherty power amplifiers (DPA). Taking conduction angle and back-off (BO) level into account a global design chart is presented which can be utilized to properly dimension the aux amplifier. Based on the proposed method a class C power amplifier is designed and exploited in a DPA circuit at 28GHz which is evaluated using simulations based on 45nm CMOS technology. Simulations reveal 27dBm saturated output power, 60% maximum drain efficiency (DE), 45% DE at 6dBBO, and 2 times efficiency enhancement at 6dB BO which is a new record in this trend.
Anomaly Detection in Satellite Communications Systems using LSTM Networks

Most satellite communications monitoring tools use simple thresholding of univariate measurements to alert the operator to unusual events [1], [2]. This approach suffers from frequent false alarms, and is moreover unable to detect sequence or multivariate anomalies [3]. Here we consider the problem of detecting outliers in high-dimensional time-series data, such as transponder frequency spectra. Long Short Term Memory (LSTM) networks are able to form sophisticated representations of such multivariate temporal data, and can be used to predict future sequences when presented with sufficient context. We report here on the utility of LSTM prediction error as a defacto measure for detecting outliers. We show that this approach significantly improves on simple threshold models, as well as on moving average and static predictors. The latter simply assume the next trace will be equal to the previous trace. The advantages of using an LSTM network for anomaly detection are twofold. Firstly, the training data do not need to be labelled. This alleviates the need to provide the model with specific examples of anomalies. Secondly, the trained model is able to detect previously unseen anomalies. Such anomalies have a degree of unpredictability that makes them stand out. LSTM networks are further able to potentially detect more nuanced sequence and multivariate anomalies. These occur when all values are within normal tolerances, but the sequence or combinations of values are themselves unusual. The technique we describe could be used in practice for alerting satellite network operators to unusual conditions requiring their attention.