Miracle-dz/UniFAR-FTUs huggingface dataset:
An efficient load balancing multicast scheduling for solving congestion problem in social data center networks

Recently, social network sites have become more popular. The web site traffic on Facebook reaches 22.36% proportion of global data traffic in the world. There are various and complex kinds of data types such as texts, photographs, and videos which are transmitted in social network sites. In social networks, cloud services are generally accomplished by multicast-based group communications. The extensive data of social networks is generated within a relatively short period of time and is concentrated on partial servers. Subsequently, the rate of multicast congestion increases substantially, resulting in severe packet loss and transmission error. Therefore, we study the congestion problem of multicast-based group communications in the social data center network. Then, we propose an efficient load balancing multicast scheduling (LBMS) by observing users' behaviors on the social network to alleviate the congestion problems of the multicast traffic. Simulation results shows that LBMS can achieve load balance and significantly improve throughput and average delay.
Sparse Representation for Color Image Based on Geometric Algebra

Existing sparse representation models represent RGB channels separately without thinking about the relationship color channels, which lose some color structures inevitably. In this paper, we introduce a novel sparse representation model for color image based on geometric algebra (GA) theory and its corresponding dictionary learning algorithm, namely K-GASVD is proposed. The model represents the color image as a multivector with the spatial and spectral information in GA space, providing a kind of vectorial representation for the inherent color structures rather than a scalar representation via current sparse image models. The proposed sparse model is validated in the applications of color image denoising and reconstruction. The experimental results demonstrate that our sparse image model avoids the hue bias phenomenon successfully and retained the color structures completely. It shows its potential as a general and powerful tool in various applications of color image analysis.
Gated Four-Probe Method to Evaluate the Impact of SAM Gate Dielectric on Mobility in MoS2 FET

This study reports the impact of interfacial engineering by means of SAM (Self-assembled monolayer)-based gate dielectric on channel mobility in molybdenum disulfide (MoS2) field-effect transistors (FETs). A gated four-probe method was implemented to eliminate the effect of contact resistance on channel mobility. The formation of SAM significantly plays an important role in the improvement of channel mobility as high as 19 cm2/Vs in Mos2FETs because the superior interfacial properties can be realized in MoS2/SAM structure. This study opens up interesting direction of interface engineering for research in the applications and developments of 2-dimensional materials-based thin film devices.
Frequency and Geographic Distribution of CARD9 Mutations in Patients With Severe Fungal Infections

Autosomal recessive deficiency in the caspase recruitment domain containing protein 9 (CARD9) results in susceptibility to fungal infections. In the last decade, infections associated with CARD9 deficiency are more reported due to the advent of genome sequencing. The aim of this study was to evaluate the frequency, geographic distribution and nature of mutations in patients with CARD9 deficiency. We identified 60 patients with 24 mutations and different fungal infections. The presence of the homozygous (HMZ) p.Q295X (c.883C > T) and HMZ p.Q289X (c.865C > T) mutations were associated with an elevated risk of candidiasis (OR: 1.6; 95% CI: 1.18–2.15; p = 0.004) and dermatophytosis (OR: 1.85; 95% CI: 1.47–2.37; p < 0.001), respectively. The geographical distribution differed, showing that the main mutations in African patients were different Asian patients; HMZ p.Q289X (c.865C > T) and HMZ p.Q295X (c.865C > T) accounted for 75% and 37.9% of the African and Asian cases, respectively. The spectrum of CARD9 mutations in Asian patients was higher than in African. Asia is the most populous continent in the world and may have a greater genetic burden resulting in more patients with severe fungal infections. The presence of a high diversity of mutations revealing 24 distinct variations among 60 patients emphasize that the unique genetic alteration in CARD9 gene may be associated with certain geographical areas.
Sensorless DTC-SVM Strategy for Doubly-Fed Induction Machine Drive using Model Reference Adaptive System

This paper presents a comparative performance assessment between a fictitious impedance based model reference adaptive system (Z-MRAS) with well-known instantaneous reactive power based MRAS (Q-MRAS) in space-vector modulation (SVM) based direct torque control (DTC) of grid-connected doubly-fed induction machine (DFIM) drive. Both the methods are free from flux terms and are also independent of stator/rotor resistances. Moreover, both Z-/Q-MRAS when used in combination with DTC-SVM scheme for DFIM the torque and flux ripples reduces drastically in comparison to conventional DTC of DFIM drive. The effectiveness of the control algorithms are verified in MATLAB/Simulink. The experimental results obtained by dSPACE-1103 based laboratory prototype further validate the simulation results.
A Reconfigurable Analog Baseband for Ka Band Transmitter

In this paper, a Ka band analog baseband for satellite communication is presented. The baseband is made up of two cascade third-order low pass filter with a variable bandwidth and a programmaule gain amplifier (PGA). The DC offset cancellation circuit is added at the output of PGA. To achieve high linearity with less power consumption, a novel integrated frequency compensation technology is employed. The simulation results show that circuit has a variable -3dB bandwidth range from 5MHx to 60MHz. The gain range of baseband is from -12dB to 37dB. And the output 1dB compression up to 10. 2dBm at 0dB gain setting. The circuit was implemented in TSMC 65-nm CMOS technology with 27. 8mW power consumption from a 1. 2V supply.
Reliability Analysis of Repairable Systems Based on a Two-Segment Bathtub-Shaped Failure Intensity Function

The reliability analysis of complex repairable systems is an important but computationally intensive task that requires fitting the failure data of whole life cycles well. Because the existing reliability models are mainly based on the assumptions that systems are either unrepairable or will go through an “as good as new” type of repair which does not describe actual situations effectively and precisely, a two-segment failure intensity model based on sectional non-homogeneous Poisson process is developed. This model is capable of analyzing repairable systems with bathtub-shaped failure intensity. It considers minimal maintenance activities and preserves the time series of failures based on the whole life cycle. The advantages of this model lie in its flexibility to describe monotonic, non-monotonic failure intensities and its practicality to determine the burn-in or replacement time for repairable systems. Three real lifetime failure data sets are applied to illustrate the developed model. The results show that the model performs well regarding the Akaike information criterion value, mean squared errors, and Cramér–von Mises values.
Detecting Stubborn Permission Requests in Android Applications

The Android permission mechanism is designed to protect the privacy of Android users. An Android application must request permissions when it needs to access sensitive data at runtime. If users do not grant the application requested permissions, the application would not provide functionalities related to these permissions. However, some applications violate this purpose in that they request permissions at initialization. If the user does not grant the requested permissions, these applications would simply exit, refusing to provide any functionalities, including the ones that do not require sensitive data. This behavior of stubbornly requesting permissions damages the right of users in utilizing non-sensitive functionalities. To address this problem, we propose an approach to detect this kind of permission requests. First, we model the key features of stubborn permission requests. Then, we identify the stubborn permission requests by statically analyzing Android applications. We evaluate our approach with real-world market applications and the experimental result shows that our app roach can effectively detect stubborn permission requests in Android applications.
Visual and Haptic Error Modulating Controllers for Robotic Gait Training

Robotic algorithms that augment movement errors have been proposed as promising training strategies to enhance motor training and neurorehabilitation. However, research effort has mainly focused on rehabilitation of upper limbs. In this study, we investigated the effect of training with novel error modulating strategies on learning an asymmetric gait pattern. Thirty healthy young participants walked in the robotic exoskeleton Lokomat, while learning a foot target-tracking task which required an increased hip and knee flexion in the dominant leg. Learning with three different strategies was evaluated: (i) No guidance: no disturbance/guidance was applied, (ii) Haptic error amplification: dangerous and discouraging large errors were limited with haptic guidance, while awareness of task relevant errors was enhanced with error amplification, and (iii) Visual error amplification: visually perceived errors were amplified in a virtual reality environment. We also evaluated whether increasing the movement variability during training by adding randomly-varying haptic disturbances on top of the other training strategies further enhanced learning. We found that training with the novel haptic error amplification strategy limited large errors during training, did not hamper learning and enhanced transfer of the learned asymmetric gait pattern. Training with visual error amplification, on the other hand, increased errors during training and hampered motor learning. Adding haptic disturbances did not have a significant effect on learning. The novel haptic error modulating controller that amplifies small task-relevant errors while limiting large errors provided the best framework to enhance motor learning.
Automated Assistive Therapy Device for Patients with Neurological Diseases

In this paper we describe the development of an automated therapy device for the use in neurological rehabilitation. The movement patterns of the therapy device belong to a manual therapy method which is based on hippotherapy. This manual therapy method can be used for patients with high movement restrictions because the patient can exercise in a lying position. Those parts of the development of the automated therapy device which we describe in this paper include the movement analysis of the manual therapy method, the mechanic dimensioning, the modeling and the path planning. Furthermore, we illustrate the implementation of our approach into a demonstrator and partially present our validation. The paper serves to demonstrate the clear advantages of developing and using automated assistive therapy devices in neurological rehabilitation.
A mutual authentication scheme with user anonymity for cyber-physical and internet of things

Cyber-Physical Systems (CPS) and Internet of Things (IoT) are emerging technologies, which makes the remote sensing and control across heterogeneous network a reality, and has good prospects in industrial applications. Due to the resource constrained feature of CPS devices, the design of security and efficiency balanced authentication scheme for CPS/IoT devices becomes a big challenge in CPS/IoT applications. This paper presents a two-factor authentication with key agreement scheme for CPS/IoT applications. The proposed mechanism integrates IMSI identifier and identity-based remote mutual authentication scheme on BAN logic designs. It supports flawless two-factor and mutual authentication of participants and agreement of session keys for user, device and gateway server. The proposed mechanism also provide user anonymity, it can be adopt in critical applications. Besides, it does not require modifying the software of clients; thus, it is highly flexibly. We believe the proposed mechanism is usable for CPS/IoT applications.
Approximating the maximum weighted decomposable graph problem with applications to probabilistic graphical models

In this work we deal with the problem of learning a maximum weighted (k+1)-order decomposable graph coarser than a given maximal k-order decomposable graph (also known as hypertree of treewidth k − 1). An Integer Linear Programming formulation for the problem has recently been proposed and used in order to solve instances of the problem with a moderate number of vertices. However, as the problem is known to be NP-hard, it is of practical interest to develop approximate algorithms able to work with a limited amount of computational resources. In this paper we propose an approximate Integer Linear Programming formulation for the problem using a threshold distance which discards the edges that, on average, have a low probability of being contained in the solution. Experiments have been carried out with weighted graphs and probabilistic graphical models. Using the proposed formulation we have obtained results close to the optimum, even when most of the candidate edges were discarded using the distance criterion. The obtained good results indicate that the approximate formulation has important applications for learning probabilistic graphical models using decomposable scores, e.g., BDe.
Effects of Early Postoperative Intraocular Pressure after Ahmed Glaucoma Valve Implantation on Long-term Surgical Outcomes

Purpose To evaluate the long-term effects of early postoperative intraocular pressure (IOP) after Ahmed glaucoma valve (AGV) implantation on long-term surgical outcomes. Methods This retrospective, non-randomized study included 100 eyes of 100 patients who underwent AGV surgery. We divided the enrolled patients into four groups according to the presence of transient hypotony within the first postoperative week or the presence of a hypertensive phase during the first three postoperative months. Postoperative IOP, the number of glaucoma medications, and cumulative success rate were compared among the groups. Results There was significantly better IOP control and a better success rate in the non-hypertensive phase group 2 years postoperatively. However, no significant difference was found in the IOP or success rate at 2 years postoperatively between the transient hypotony and non-hypotony groups. Further subgroup analysis showed that the non-hypotony, non-hypertensive phase group had a significantly higher success rate (100%) at 2 years postoperatively. Conclusions We can predict the long-term prognosis after AGV implantation by considering the early postoperative IOP state and the presence of a hypertensive phase.
Standard Access for Research to Feat Spatial Time-Based Data Using RFID and Sensors

The main purpose of this paper to analysis present creates occupancy monitoring and multi-model data fusion approaches for smart commercial structures. Additionally to energy issues, real-time occupancy monitoring also may help saving heirs in case of emergency response programs. Enabled by such occupancy monitoring abilities, we will find extensive opportunities for enhancing the power use of buildings via wise Heating and cooling control. In this way, the main challenges we envision are to attain occupancy monitoring inside a minimally intrusive way, e.g., while using existing infrastructure in the buildings and never needing installing of any apps within the users ‘smart products, and a pair to build up effective data fusion techniques for enhancing occupancy monitoring precision utilizing a multitude of sources. Using the proliferation of Internet of products (Iota) products for example smart phones, sensors, cameras, and RFIDs, it’s easy to collect lots of information for localization and monitoring of individuals within commercial structures. The aim would be to lay lower a framework for future research to take advantage of the patio-temporal data acquired from one or even more of numerous Iota products for example temperature sensors, surveillance cameras, and RFID tags which may be already used in the structures.
Impact of short-term exercise training intensity on β-cell function in older obese adults with prediabetes.

The effect of work-matched exercise intensity on β-cell function is unknown in people with prediabetes before clinical weight loss. We determined if short-term moderate continuous (CONT) vs. high-intensity interval (INT) exercise increased β-cell function. Thirty-one subjects (age: 61.4 ± 2.5 yr; body mass index: 32.1 ± 1.0 kg/m2) with prediabetes [American Diabetes Association criteria, 75-g oral glucose tolerance test (OGTT)] were randomized to work-matched CONT (70% HRpeak) or INT (3 min 90% HRpeak and 3 min 50% HRpeak) exercise for 60 min/day over 2 wk. A 75-g 2-h OGTT was conducted after an overnight fast, and plasma glucose, insulin, C-peptide, and free fatty acids were determined for calculations of skeletal muscle [oral minimal model (OMM)], hepatic (homeostatic model of insulin resistance), and adipose (Adipose-IR) insulin sensitivity. β-Cell function was defined from glucose-stimulated insulin secretion (GSIS, deconvolution modeling) and the disposition index (DI). Glucagon-like polypeptide-1 [GLP-1(active)] and glucose-dependent insulinotropic polypeptide (GIP) were also measured during the OGTT, along with peak oxygen consumption and body composition. CONT and INT increased skeletal muscle- but not hepatic- or adipose-derived DI ( P < 0.05). Although both treatments tended to reduce fasting GLP-1(active) ( P = 0.08), early phase GLP-1(active) increased post-CONT and INT training ( P < 0.001). Interestingly, CONT exercise increased fasting GIP compared with decreases in INT ( P = 0.02). Early and total-phase skeletal muscle DI correlated with decreased total glucose area under the curve ( r = -0.52, P = 0.002 and r = -0.50, P = 0.003, respectively). Independent of intensity, short-term training increased pancreatic function adjusted to skeletal muscle in relation to improved glucose tolerance in adults with prediabetes. Exercise also uniquely affected GIP and GLP-1(active). Further work is needed to elucidate the dose-dependent mechanism(s) by which exercise impacts glycemia. NEW & NOTEWORTHY Exercise is cornerstone for reducing blood glucose, but whether high-intensity interval training is better than moderate continuous exercise is unclear in people with prediabetes before weight loss. We show that 2 wk of exercise training, independent of intensity, increased pancreatic function in relation to elevated glucagon-like polypeptide-1 secretion. Furthermore, β-cell function, but not insulin sensitivity, was also correlated with improved glucose tolerance. These data suggest that β-cell function is a strong predictor of glycemia regardless of exercise intensity.
Multi-Target Approach for Drug Discovery against Schizophrenia

Polypharmacology is nowadays considered an increasingly crucial aspect in discovering new drugs as a number of original single-target drugs have been performing far behind expectations during the last ten years. In this scenario, multi-target drugs are a promising approach against polygenic diseases with complex pathomechanisms such as schizophrenia. Indeed, second generation or atypical antipsychotics target a number of aminergic G protein-coupled receptors (GPCRs) simultaneously. Novel strategies in drug design and discovery against schizophrenia focus on targets beyond the dopaminergic hypothesis of the disease and even beyond the monoamine GPCRs. In particular these approaches concern proteins involved in glutamatergic and cholinergic neurotransmission, challenging the concept of antipsychotic activity without dopamine D2 receptor involvement. Potentially interesting compounds include ligands interacting with glycine modulatory binding pocket on N-methyl-d-aspartate (NMDA) receptors, positive allosteric modulators of α-Amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors, positive allosteric modulators of metabotropic glutamatergic receptors, agonists and positive allosteric modulators of α7 nicotinic receptors, as well as muscarinic receptor agonists. In this review we discuss classical and novel drug targets for schizophrenia, cover benefits and limitations of current strategies to design multi-target drugs and show examples of multi-target ligands as antipsychotics, including marketed drugs, substances in clinical trials, and other investigational compounds.
Analysis of Vibration and Noise in Permanent Magnet Synchronous Motors With Distributed Winding for the PWM Method

This paper describes the spatial mode, frequencies, the voltage reference update timing, and their interaction of pulsewidth modulation (PWM) harmonics, focusing on a distributed winding permanent magnet synchronous motor. We investigated the electromagnetic force generating the noise by using a couple of analyses between a circuit simulator and a two-dimensional finite element analysis. It was found that the electromagnetic noise and vibration result from a radial electromagnetic force spaced at the spatial zeroth mode of <inline-formula><tex-math notation="LaTeX">$f_{c}\pm 3f_{1},f_{c}$</tex-math></inline-formula>, and <inline-formula><tex-math notation="LaTeX">${{2}}f_{c}$</tex-math> </inline-formula> (<inline-formula><tex-math notation="LaTeX">$f_{c}$</tex-math></inline-formula>: carrier frequency, <inline-formula><tex-math notation="LaTeX">$f_{1}$</tex-math></inline-formula>: fundamental frequency of the current). We have shown that the radial electromagnetic force of frequency <inline-formula><tex-math notation="LaTeX">$f_{c}\pm 3f_{1}$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">${{2}}f_{c}$</tex-math> </inline-formula> results from PWM harmonics. Also, the radial electromagnetic force of frequency <inline-formula> <tex-math notation="LaTeX">$f_{c}$</tex-math></inline-formula> evidently results from the voltage reference update timing of <inline-formula><tex-math notation="LaTeX">${{1/ }}f_{c}$</tex-math></inline-formula>. The electromagnetic noise and the spatial mode are demonstrated in the experiment.
Oculo‐visual abnormalities in Parkinson's disease: Possible value as biomarkers

Parkinson's disease (PD) is one of the most common neurodegenerative disorders and the second leading cause of dementia worldwide. With an aging population, the prevalence of the disease has dramatically increased. Clinical management has advanced through recent developments in dopaminergic imaging and genetic risk profiling. However, early and accurate diagnosis of the disorder remains a challenge, largely because of the lack of noninvasive and inexpensive reliable diagnostic tests. Besides the well‐studied cerebral neurodegeneration that underlies the cardinal symptoms of PD (ie, bradykinesia, tremor, rigidity, and postural instability), ocular changes have also been described in PD, including visual dysfunction, pupil abnormality, lens opacity, and retinal neuronal loss and dysfunction. These ocular pathological processes are related to α‐synuclein deposition, and dopamine deficiency in the retina—mirroring the defining pathological features of PD in the brain. Together, these observations support the notion that the eye can serve as a window to the brain, providing clinicians with noninvasive methods to visualize disease. This review focuses on recent advances in the characterization of ocular changes in PD and their promising use as biomarkers in the eye, which can be potentially used for aiding in early diagnosis, tracking disease progression, and valuating novel therapeutic strategies. © 2018 International Parkinson and Movement Disorder Society