Miracle-dz/UniFAR-FTUs huggingface dataset:
Stabilization for discrete-time stochastic systems with multiple input delays

This paper is concerned with the stabilization problem for discrete-time stochastic systems with multiplicative noise and multiple input delays. Our approach is based on a reduction technique, by which the system under consideration is converted into a delay-free system. The necessary and sufficient stabilization condition for stabilization and the associated feedback controller are characterized via a generalized Riccati equation.
Distributed Collision-Free Data Aggregation Approach for Wireless Sensor Networks

This paper presents a distributed serial data aggregation approach, called Spreading Aggregation~(SA), in which one packet hops sequentially over nodes and aggregates their data. The next hop of the aggregation packet is determined locally by each traversed node using only its one-hop neighborhood information, so no network topology information needs to be known by nodes, nor collisions are generated as only one node is communicating at any given time. This localized and distributed characteristic makes the proposed approach highly scalable and very efficient in terms of communication-reduction, energy conservation, and aggregation time, as confirmed by the numerous simulation results we obtained. These results confirm also the superiority of the proposed approach over the state-of-the-art serial approaches, particularly in very large scale network deployments.
Traffic Identification of Mobile Apps Based on Variational Autoencoder Network

Traffic identification is a fundamental issue in network security. Traditional methods, such as depth packet inspection (DPI) and flow-based classifiers, have difficulties in labeling massive samples and extracting features manually. Motivated by the achievements in computer vision, we focus on mobile app traffic, proposing a deep learning model based on variational autoencoder network (VEAN). Our contributions are two-fold. First, we propose a novel method of transforming mobile app traffic flows into vision-meaningful images, and thus enable the machine to identify the traffic in a human way. Then, based on the transformation method, we create an open dataset named IMTD17. Second, an improved network model is proposed, where variational autoencoder (VAE) algorithm is introduced into a two-stage learning. The model realizes the learning from massive unlabeled data, and the feasibility of the replacement for manual feature extraction is illustrated by the visualization analysis of the latent features. The experimental results show that the identification accuracy can reach 99.6%, which satisfies the practical requirement.
Feasibility of a home-based exercise intervention with remote guidance for patients with stable grade II and III gliomas: a pilot randomized controlled trial

Objective: In this pilot study, we investigated the feasibility of a home-based, remotely guided exercise intervention for patients with gliomas. Design: Pilot randomized controlled trial (RCT) with randomization (2:1) to exercise or control group. Subjects: Patients with stable grade II and III gliomas. Intervention: The six-month intervention included three home-based exercise sessions per week at 60%–85% of maximum heart rate. Participants wore heart rate monitors connected to an online platform to record activities that were monitored weekly by the physiotherapist. Main measures: Accrual, attrition, adherence, safety, satisfaction, patient-reported physical activity, VO2 peak (by maximal cardiopulmonary exercise testing) and body mass index (BMI) at baseline and at six-month follow-up. Results: In all, 34 of 136 eligible patients (25%) were randomized to exercise training (N = 23) or the control group (N = 11), of whom 19 and 9, respectively, underwent follow-up. Mean adherence to prescribed sessions was 79%. Patients’ experiences were positive. There were no adverse events. Compared to the control group, the exercise group showed larger improvements in absolute VO2 peak (+158.9 mL/min; 95% CI: −44.8 to 362.5) and BMI (−0.3 kg/m²; 95% CI: −0.9 to 0.2). The median increase in physical activity was 1489 metabolic equivalent of task (MET) minutes higher in the exercise group. The most reported reasons for non-participation were lack of motivation or time. Conclusion: This innovative and intensive home-based exercise intervention was feasible in a small subset of patients with stable gliomas who were interested in exercising. The observed effects suggest that the programme may improve cardiorespiratory fitness. These results support the need for large-scale trials of exercise interventions in brain tumour patients.
Correlational selection on personality and social plasticity: morphology and social context determine behavioural effects on mating success

Despite a central line of research aimed at quantifying relationships between mating success and sexually dimorphic traits (e.g., ornaments), individual variation in sexually selected traits often explains only a modest portion of the variation in mating success. Another line of research suggests that a significant portion of the variation in mating success observed in animal populations could be explained by correlational selection, where the fitness advantage of a given trait depends on other components of an individual's phenotype and/or its environment. We tested the hypothesis that interactions between multiple traits within an individual (phenotype dependence) or between an individual's phenotype and its social environment (context dependence) can select for individual differences in behaviour (i.e., personality) and social plasticity. To quantify the importance of phenotype- and context-dependent selection on mating success, we repeatedly measured the behaviour, social environment and mating success of about 300 male stream water striders, Aquarius remigis. Rather than explaining individual differences in long-term mating success, we instead quantified how the combination of a male's phenotype interacted with the immediate social context to explain variation in hour-by-hour mating decisions. We suggest that this analysis captures more of the mechanisms leading to differences in mating success. Males differed consistently in activity, aggressiveness and social plasticity. The mating advantage of these behavioural traits depended on male morphology and varied with the number of rival males in the pool, suggesting mechanisms selecting for consistent differences in behaviour and social plasticity. Accounting for phenotype and context dependence improved the amount of variation in male mating success we explained statistically by 30-274%. Our analysis of the determinants of male mating success provides important insights into the evolutionary forces that shape phenotypic variation. In particular, our results suggest that sexual selection is likely to favour individual differences in behaviour, social plasticity (i.e., individuals adjusting their behaviour), niche preference (i.e., individuals dispersing to particular social conditions) or social niche construction (i.e., individuals modifying the social environment). The true effect of sexual traits can only be understood in interaction with the individual's phenotype and environment.
Dynamic organization of chromatin domains revealed by super-resolution live-cell imaging

How is the long strand of human genome DNA organized in the cell? DNA is wrapped around core histones, forming a nucleosome structure. The nucleosome had been long assumed to be folded into a regular 30-nm chromatin fiber and other helical folding structures. However, several recent evidences including our cryo-microscopy and synchrotron X-ray scattering analyses showed that chromatin in the cells mainly consists of irregularly folded nucleosome fibers without such regular fibers. This irregular folding implies a less physically constrained and locally more dynamic chromatin state. Recently, using the super-resolution imaging, we revealed the chromatin domains and their local dynamics (" fluctuation ") in live mammalian cells. Our simulation result suggested that the fluctuation increases chromatin accessibility, which is advantageous for many " information searching " biological processes, such as RNA transcription, DNA replication and DNA repair/recombination.
Interference-Alignment and Soft-Space-Reuse Based Cooperative Transmission for Multi-cell Massive MIMO Networks

As a revolutionary wireless transmission strategy, interference alignment (IA) can improve the capacity of cell-edge users. However, the acquisition of the global channel state information for IA leads to unacceptable overhead in the massive MIMO systems. To tackle this problem, in this paper, we propose an IA and soft-space-reuse (IA-SSR)-based cooperative transmission scheme under the two-stage precoding framework. Specifically, the cell-center and the cell-edge users are separately treated to fully exploit the spatial degrees of freedoms. Then, the optimal power allocation policy is developed to maximize the sum-capacity of the network. Next, a low-cost channel estimator is designed for the proposed IA-SSR framework. Some practical issues in IA-SSR implementation are also discussed. Finally, plenty of numerical results are presented to show the efficiency of the proposed algorithm.
Toward the next generation of recruitment tools: An online social network-based job recommender system

This paper presents a content-based recommender system which proposes jobs to Facebook and LinkedIn users. A variant of this recommender system is currently used by Work4, a San Francisco-based software company that offers Facebook recruitment solutions. Work4 is the world leader in social recruitment technology; to use its applications, Facebook or LinkedIn users explicitly grant access to some parts of their data, and they are presented with the jobs whose descriptions are matching their profiles the most. The profile of a user contains two types of data: interactions data (user's own data) and social connections data (user's friends data). Furthermore the users profiles and the description of jobs are divided into several parts called fields. Our experiments suggest that to predict the users interests for jobs, using basic similarity measures together with their interactions data collected by Work4 can be improved upon. The second part of this study presents a method to estimate the importance of each field of users and jobs in the task of job recommendation. Finally, the third part is devoted to the use of a machine learning algorithm in order to improve the results obtained with similarity measures: we trained a linear SVM (Support Vector Machines). Our results show that using this supervised learning procedure increases the performance of our content-based recommender system.
Mold Fabricated by Nanoscratching for Nanoimprint Lithography

The MEMS technology for various nano/micro devices often requires special facilities and complicated and multistage processes, thus the fabrication cost is extremely high. This research aimed to fabricate nanoscale basic structures on silicon substrates using nanoscratching, which can be potentially used to make nano/micro molds for nanoimprint lithography. In this study, various nano/micro-scale structures, such as groove and, single and multiple layer structures were generated on the silicon substrate using an atomic force microscope equipped with a sharp probe made of monocrystalline diamond. The nanoimprint experiment was also performed using the fabricated single-step mold and silicon-resin to fabricate single island structures.
Enriching Source for English-to-Urdu Machine Translation

This paper focuses on the generation of case markers for free word order languages that use case markers as phrasal clitics for marking the relationship between the dependent-noun and its head. The generation of such clitics becomes essential task especially when translating from fixed word order languages where syntactic relations are identified by the positions of the dependent-nouns. To address the problem of missing markers on source-side, artificial markers are added in source to improve alignments with its target counterparts. Up to 1 BLEU point increase is observed over the baseline on different test sets for English-to-Urdu.
Large-Area 2-D Electronics: Materials, Technology, and Devices

Recent experiments since the discovery of monolayer graphite or graphene have led to an exciting revival in the interest in the electronic applications for graphene, as well as other 2-D materials such as hexagonal boron nitride (hBN) and molybdenum disulfide (MoS2). These layered materials serve as an exciting new platform for flexible and transparent electronics where surfaces can be enriched with new functionality. This paper aims to provide an overview behind these new class of materials ranging upon important issues for electronic integration including synthesis all the way to current state-of-the-art circuits and devices made from these materials.
Exact and Parallel Triangle Counting in Dynamic Graphs

Triangle counting is an important building block for finding key players in a graph. It is an integral part of the popular clustering coefficient analytic and can be used for pattern matching in social networks. A triangle, which is also a 3-clique, represents a strong connection between three players that are all connected. While counting triangles is not overly expensive from a computational standpoint, especially in comparison to centrality metrics (such as betweenness centrality and closeness centrality), it can still prove to be prohibitive for large scale networks, especially for those with a power-law distribution. This problem only deepens for dynamic graphs where the network is constantly changing, requiring constant updating of the graph and the analytic. In this paper, we present a new dynamic graph algorithm for counting triangles that is based on an inclusion-exclusion formulation. While our algorithm is independent of the computing platform, we show performance results on an NVIDIA GPU. Our approach handles 32 million updates per second, or up to 11 million updates per second if the graph data structure is also updated. In past approaches, when a vertex was affected due to an edge insertion or deletion, it was necessary to find the triangles from scratch for that given vertex. Our new formulation does not need this and only requires considering the affected edges. As such our algorithm is typically several hundred times faster than the past approach - in some cases up to 819X faster.
Target detection algorithm for IARC seventh mission

We use HOG+SVM method to detect the target position, and propose an improved algorithm based on the height information. A method based on the characteristics of color and shape is proposed to detect the direction of target. The experimental results show that the improved position detection algorithm is faster than traditional algorithm, and the direction detection algorithm can get the direction with much accuracy.
Online Peer-to-peer Discussions: A Platform for Automatic Assessment of Communication Skill

This paper proposes a computational model to predict communication skill of individual participants in online peer-to-peer dyadic interactions. Participants interact using a web-interface (skype-like) developed to record videos of two participants separately and stream real-time. This platform allows interviews and group discussions to be conducted at any place without the need of colocation of all participants. Towards studying communication skill in such a setting, we collected 72 dyadic interactions of participants discussing on general topics. Manual rating of these interaction videos have been obtained from two external observers. Multimodal features related to non-verbal behavior: prosody, speaking activity, visual and verbal behavior are automatically extracted. The experimental results show that the multimodal fusion of features with reliefF feature ranking perform best with an accuracy of 74%. Also, we automatically rate the overall discussion by extracting features from both participants. Our best results on automatic discussion rating achieves an accuracy of 83%. Further to dyadic interactions, we make a comparative study of the communication skill rating of the same participants giving an interface-based interview. Our study indicates that participants communicate well in interaction based scenarios.
Proliferation genes in lung development associated with the prognosis of lung adenocarcinoma but not squamous cell carcinoma

There are many similarities between embryonic development and tumorigenesis, and gene expression profiles show that certain correlations exist between the gene signature during development and the clinical phenotypes of different cancers. Our group previously reported the gene expression profiles of human lung development, and the expression of one group of proliferation‐related genes (PTN1 genes) steadily decreased during lung development. Here, we examined the prognostic value of PTN1 genes in 5 independent lung adenocarcinoma (ADC) and 5 lung independent squamous cell carcinoma (SCC) microarray datasets and found that the expression levels of PTN1 genes were associated with survival in lung ADC but not lung SCC. All of the lung ADC datasets contained a set of highly correlated genes from PTN1 genes, but the lung SCC datasets had no similar set of genes. We identified 63 unique core genes from the PTN1 genes in the 5 lung ADC datasets: 17 of these core genes appeared in at least 4 of the lung ADC datasets, and the 17 corresponding proteins clearly interacted more strongly with each other in lung ADC than in lung SCC. Moreover, 16 of the 17 core genes play major roles in the G2/M phase of the cell cycle. These data indicate that proliferation‐related genes in lung development have a significant prognostic value for lung ADC; the synergistic effects of the 17 core genes play an important role in lung ADC prognosis. These genes may have significant clinical implications for the treatment and prognosis of lung ADC.
Research to the Typical Defects of Crystalline Silicon Photovoltaic Cells based on EL Images

According to the electroluminescent imaging mechanism of crystalline silicon photovoltaic cells, EL images of four kinds of the typical defects that happened with high frequency in the course of the production in crystalline silicon photovoltaic cells, such as, black core, cracks, broken gate and over welding, etc, were analyzed with some emphasis in this articleon the aspects ofthe characteristic, production mechanism, harm and resolution of those images, then the solution to defects is applied to productive practice of Yingli , indicating its availability in its performance, which would help us make better use of the detected EL images in production practices by means of the rapid and accurate recognization on various defects,in order to impel the development of production technology and enhance the benefits.
Delayed feedback selective pattern formation in reaction-diffusion systems

In the natural world, there exist many autonomous spatially non-uniform patterns. From an engineering point of view, controlling these phenomena is potentially useful to many practical applications. In view of this, the authors formulated and solved a novel feedback control problem of such autonomous spatial patterns based on a specific reaction-diffusion system [5]. In this paper, toward development of an implementable control strategy, we derive a delay-dependent criterion under which the control law obtained in [5] suitably generates the desired spatial patterns. The effectiveness of the theoretical result is verified by numerical simulations.
Cigarette smoke (CS) and nicotine delay neutrophil spontaneous death via suppressing production of diphosphoinositol pentakisphosphate

Diphosphoinositol pentakisphosphate (InsP7), a higher inositol phosphate containing energetic pyrophosphate bonds, is beginning to emerge as a key cellular signaling molecule. However, the various physiological and pathological processes that involve InsP7 are not completely understood. Here we report that cigarette smoke (CS) extract and nicotine reduce InsP7 levels in aging neutrophils. This subsequently leads to suppression of Akt deactivation, a causal mediator of neutrophil spontaneous death, and delayed neutrophil death. The effect of CS extract and nicotine on neutrophil death can be suppressed by either directly inhibiting the PtdIns(3,4,5)P3/Akt pathway, or increasing InsP7 levels via overexpression of InsP6K1, an inositol hexakisphosphate (InsP6) kinase responsible for InsP7 production in neutrophils. Delayed neutrophil death contributes to the pathogenesis of CS-induced chronic obstructive pulmonary disease. Therefore, disruption of InsP6K1 augments CS-induced neutrophil accumulation and lung damage. Taken together, these results suggest that CS and nicotine delay neutrophil spontaneous death by suppressing InsP7 production and consequently blocking Akt deactivation in aging neutrophils. Modifying neutrophil death via this pathway provides a strategy and therapeutic target for the treatment of tobacco-induced chronic obstructive pulmonary disease.
Beam synthesis and target detection based on aperture coding metasurface

The coding-controlled phased array radar built the bridge between digital codes and physically metamaterial particle, which works in microwave frequency band. The links and differences will be discussed between this new radar and traditional phased array radar, then the mathematical theory illustrates how the direction (including elevation and azimuth) is controlled by coding combination. Metasurface antenna can also achieve good performance of target detection based on beam-scanning. This is proved by the simulation in the situation of single point target where the distance, azimuth and elevation are detected by impulse compression operation. Furthermore, the moving target tracking is also realized by metasurface antenna, assuming that the radial velocity and the angular velocity of the target follow the normal distribution of known mean and variance.
A miniaturized frequency selective radome with wide absorption response above X-band

In this paper, a miniaturized planar absorptive frequency selective radome is presented. The proposed design acts as a transparent sheet in the X-band (9.1–10.4 GHz) and behaves as an absorber above the X-band from 17.8 GHz to 27.5 GHz. The design is composed of a bandpass FSS and a resistive FSS separated by a foam spacer. The bandpass FSS consists of a slotted modified Jerusalem cross structure which transmits the signal in the X-band while reflecting the signals other than X-band. The resistive FSS consisting of modified square loop with surface resistance absorbs the signals above the X-band. The unit cell size and the overall thickness of the design with respect to X-band is 0. 2λo and 0. 07λo, respectively. The small periodicity of a unit cell of the proposed design ensures the passband angular stability. The proposed design is verified by full wave numerical simulations. The maximum insertion loss in the X-band is 0.75dB while the absorption above the X-band is above 20dB. The design is ideal to reduce the RCS of antennas operating in the X-band.