Miracle-dz/UniFAR-FTUs huggingface dataset:
Exogenous Coordination for Building Fog-Based Cyber Physical Social Computing and Networking Systems

With the proliferation of smart embedded devices, cyber physical social computing and networking systems (CPSCN) are emerging as a next generation of social networks. Unlike traditional social networks that run on cloud-based infrastructure, CPSCN systems usually depend on a large number of distributed, heterogeneous devices, such as mobile phones, smart vehicles, or network access points. These computing resources, which are often referred to as fog computing systems, provide a gateway to the physical world, and thus offer new possibilities for social applications. Unfortunately, building CPSCN systems that leverage fog computing infrastructure is not straightforward. Significant challenges arise from the large scale distribution of computing resources over a wide area, and the dynamic nature of multiple, possibly mobile, hosts. In this paper, we extend our previous work on a distributed dataflow programming model and propose an application platform for realizing CPSCN systems. A key aspect of our work is the development of an exogenous coordination model, which exhibits a separation of concern between computation and communication activities, and helps resolve some of the challenges brought about by the dynamic and large scale nature of CPSCN systems.
Event-Related Potential Responses of Motorcyclists Towards Rear End Collision Warning System

There are many types of collision warning systems to increase the safety of motorcyclists. These systems use different types of collision detection techniques with each one having some limitations, restricting the performance of the system. To find the effectiveness of collision warning system notifications, it is important to study the physiological response of drivers toward these systems. Existing studies are limited to the physiological response of car drivers and use only buzzer warnings for these systems. Unfortunately, no such work in that particular domain has been reported for motorcyclists. Since motorcycles have different maneuverability as compared with cars and other vehicles, it is important to investigate the response of motorcyclists toward these collision warning systems. Also, it is believed that providing verbal information about any potential hazard will further assist the motorcyclist to avoid it. The aim of this paper is to investigate the physiological responses of motorcyclists to the rear end collision warning system when auditory verbal warnings are utilized. To study the response of the motorcyclists, the N100, N200, P300, and N400 event-related potential components have been extracted from the recorded Electroencephalography data. It has been found that the rear end collision warning system with auditory verbal warnings significantly increases the alertness of the motorcyclist and can be helpful to avoid the possible rear-end collision scenarios. This system has shown positive effects at neural levels on motorcyclists and reduces their reaction time and attentional resources required for processing the target correctly.
Analytical and Numerical Calculation of Magnetic Field Distribution in the Slotted Air-Gap of Tangential Surface Permanent-Magnet Motors

This paper deals with the analytical and numerical analysis of the flux density distribution in the slotted air gap of permanent magnet motors with surface mounted tangentially magnetized permanent magnets. Two methods for magnetostatic field calculations are developed. The first one is an analytical method in which the effect of stator slots is taken into account by modulating the magnetic field distribution by the complex relative air gap permeance. The second one is a numerical method using 2-D finite element analysis with consideration of Dirichlet and anti-periodicity (periodicity) boundary conditions and Lagrange Multipliers for simulation of movement. The results obtained by the analytical method are compared to the results of finite-element analysis.
Haplotypic and Genotypic Association of Catechol-O-Methyltransferase rs4680 and rs4818 Polymorphisms and Treatment Resistance in Schizophrenia

Treatment-resistant schizophrenia (TRS) continues to be a challenge. It was related to different factors, including alterations in the activity of brain dopaminergic system, which could be influenced by the dopamine-degrading enzyme, catechol-O-methyltransferase (COMT). Variants of the COMT gene have been extensively studied as risk factors for schizophrenia; however, their association with TRS has been poorly investigated. The aim of the present study was to determine the haplotypic and genotypic association of COMT rs4680 and rs4818 polymorphisms with the presence of TRS. Overall, 931 Caucasian patients diagnosed with schizophrenia (386 females and 545 males) were included, while 270 participants met the criteria for TRS. In males, no significant haplotypic and genotypic associations between COMT rs4680 and rs4818 polymorphisms and TRS were detected. However, genotypic analyses demonstrated higher frequency of COMT rs4680 AA genotype carriers compared to G-allele carriers (p = 0.033) and higher frequency of COMT rs4818 CC genotype carriers than G-allele carriers (p = 0.014) in females with TRS. Haplotype analyses confirmed that the presence of the G allele in females was associated with lower risk of TRS. In women with TRS, the high activity G-G/G-G haplotype was rare, while carriers of other haplotypes were overrepresented (p = 0.009). Such associations of COMT rs4680 and rs4818 high-activity (G variants), as well as G-G/G-G haplotype, with the lower risk of TRS in females, but not in males, suggest significant, but sex-specific influence of COMT variants on the development of treatment-resistance in patients with schizophrenia. However, due to relatively low number of females, those findings require replication in a larger sample.
Assessing User Transparency with Muscle Synergies during Exoskeleton-Assisted Movements: A Pilot Study on the LIGHTarm Device for Neurorehabilitation

Exoskeleton devices for upper limb neurorehabilitation are one of the most exploited solutions for the recovery of lost motor functions. By providing weight support, passively compensated exoskeletons allow patients to experience upper limb training. Transparency is a desirable feature of exoskeletons that describes how the device alters free movements or interferes with spontaneous muscle patterns. A pilot study on healthy subjects was conducted to evaluate the feasibility of assessing transparency in the framework of muscle synergies. For such purpose, the LIGHTarm exoskeleton prototype was used. LIGHTarm provides gravity support to the upper limb during the execution of movements in the tridimensional workspace. Surface electromyography was acquired during the execution of three daily life movements (reaching, hand-to-mouth, and hand-to-nape) in three different conditions: free movement, exoskeleton-assisted (without gravity compensation), and exoskeleton-assisted (with gravity compensation) on healthy people. Preliminary results suggest that the muscle synergy framework may provide valuable assessment of user transparency and weight support features of devices aimed at rehabilitation.
Parallel matrix multiplication

Utilizing all CPU cores available for numerical computations is a topic of considerable interest in HPC. This paper analyzes and compares four different parallel algorithms for matrix multiplication without block partitioning using OpenMP. The comparison of the algorithms is based on the achieved speed, memory bandwidth and efficient use of the cache of the algorithms.
Modeling Transcranial Direct-Current Stimulation-Induced Electric Fields in Children and Adults

Transcranial direct-current stimulation (tDCS) is a form of non-invasive brain stimulation that induces electric fields in neuronal tissue, modulating cortical excitability. Therapeutic applications of tDCS are rapidly expanding, and are being investigated in pediatrics for various clinical conditions. Anatomical variations are among a host of factors that influence the effects of tDCS, and pronounced anatomical differences between children and adults suggest that induced electric fields may be substantially different across development. The aim of this study was to determine the strength and distribution of tDCS-induced electric fields across development. Typically developing children, adolescents, and adults were recruited. Individualized finite-element method modeling of primary motor cortex (M1) targeting tDCS was performed. In the largest pediatric sample to date, we found significantly higher peak and mean M1 electric field strength, and more expansive electric field spread for children compared to adults. Electric fields were often comparable between adolescents and adults. Our results suggest that these differences may be associated with age-related differences in skull and extra-axial space thickness, as well as developmental changes occurring in gray and white matter. Individualized current modeling may be a valuable tool for personalizing effective doses of tDCS in future pediatric clinical trials.
Effect of moisture and geometrical parameter on dielectric behavior of ester oil impregnated insulation using dielectric spectroscopy measurement

Condition monitoring of power transformers has been a continuous process and in the present scenario power utilities prefer condition-based maintenance (CBM) rather than time-based maintenance (TBM). Although several diagnostic tests are conducted on transformer to assess the healthiness of the transformer, interpretation of data still appears to be a challenging task due to multiple failure mechanisms. Moisture in the transformer plays a significant role in affecting the dielectric strength and increasing the rate of paper-oil insulation aging. Dielectric response measurements have been carried out to estimate the moisture and ageing state of paper-oil insulation system. Insulation geometry of the transformer is an important parameter and should be considered while interpreting the results as it affects the dielectric behavior. In recent times, efforts have been made to use vegetable based oil as a replacement for conventional mineral oil in large power transformer as it is nonhazardous, environmentally friendly nature and its superior thermal characteristics. In this paper an effort has been made to investigate the effect of moisture and geometry on dielectric behavior of natural ester oil impregnated paper and pressboard insulation using Polarization Depolarization current (PDC) and Frequency Domain Spectroscopy (FDS) methods. Results of dielectric response measurement and their analysis are reported in this paper.
Optimal Transport in Statistical Machine Learning : Selected Review and Some Open Questions

We review recent theoretical results underpinning the use of optimal transport and Wasserstein distances in statistical machine learning. The four primary results described in this report relate to the use of Wasserstein loss for train multi-class or multi-label classifiers [1], the use of composite Wasserstein loss to establish the convergence and contraction rates for mixing distributions in certain finite and infinite mixture models [2], the guarantees provided by optimal transport when used for domain adaptation [3, 4], and the use of Wasserstein loss in improving the training procedure of Generative Adversarial Networks [5].
Linkage Disequilibrium and Population Structure in Wild and Cultivated Populations of Rubber Tree (Hevea brasiliensis)

Among rubber tree species, which belong to the Hevea genus of the Euphorbiaceae family, Hevea brasiliensis (Willd. ex Adr.de Juss.) Muell. Arg. is the main commercial source of natural rubber production worldwide. Knowledge of the population structure and linkage disequilibrium (LD) of this species is essential for the efficient organization and exploitation of genetic resources. Here, we obtained single-nucleotide polymorphisms (SNPs) using a genotyping-by-sequencing (GBS) approach and then employed the SNPs for the following objectives: (i) to identify the positions of SNPs on a genetic map of a segregating mapping population, (ii) to evaluate the population structure of a germplasm collection, and (iii) to detect patterns of LD decay among chromosomes for future genetic association studies in rubber tree. A total of 626 genotypes, including both germplasm accessions (368) and individuals from a genetic mapping population (254), were genotyped. A total of 77,660 and 21,283 SNPs were detected by GBS in the germplasm and mapping populations, respectively. The mapping population, which was previously mapped, was constructed with 1,062 markers, among which only 576 SNPs came from GBS, reducing the average interval between two adjacent markers to 4.4 cM. SNPs from GBS genotyping were used for the analysis of genetic structure and LD estimation in the germplasm accessions. Two groups, which largely corresponded to the cultivated and wild populations, were detected using STRUCTURE and via principal coordinate analysis (PCoA). LD analysis, also using the mapped SNPs, revealed that non-random associations varied along chromosomes, with regions of high LD interspersed with regions of low LD. Considering the length of the genetic map (4,693 cM) and the mean LD (0.49 for cultivated and 0.02 for wild populations), a large number of evenly spaced SNPs would be needed to perform genome-wide association studies in rubber tree, and the wilder the genotypes used, the more difficult the mapping saturation.
History of Development of Visual Modeling Tools at the Saint Petersburg State University

The accumulated history and experience of using diagram-based software design methods demonstrate that provided with powerful tool support, the use of domain specific visual languages makes possible a conceptually new approach to creation of complex system with a rather low entry threshold for newbies and multiple increase of professionals' performance. For that purpose, software developers must have an extensive set of software tool, from visual editors and repository to debugging, versions control and model refactoring tools.
Software testing: Survey of the industry practices

The objective of this survey was to explore industry practices concerning software testing. We studied software organizations to assess how they test their products and what process models they follow. The data collection was implemented as an online implementation of the survey method. Additionally the collected data was compared to our prior survey study to understand how the industry practices have changed. According to our results, the organizations have shifted towards test automation and more sophisticated testing infrastructure, they apply more agile practices even in the mission-critical software, and they have reduced the use of formal process models.
Upregulation of Immune Process-Associated Genes in RAW264.7 Macrophage Cells in Response to Burkholderia pseudomallei Infection

Melioidosis is a severe and fatal tropical zoonosis, which is triggered by Burkholderia pseudomallei. To better understand the host's response to infection of B. pseudomallei, an RNA-Seq technology was used to confirm differentially expressed genes (DEGs) in RAW264.7 cells infected with B. pseudomallei. In total, 4668 DEGs were identified across three time points (4, 8, and 11 hours after infection). Short Time-Series Expression Miner (STEM) analysis revealed the temporal gene expression profiles and identified seven significant patterns in a total of 26 profiles. Kyoto Encyclopedia of Genes and Genomes (KEGG) was utilized to confirm significantly enriched immune process-associated pathways, and 10 DEGs, including Ccl9, Ifnb1, Tnfα, Ptgs2, Tnfaip3, Zbp1, Ccl5, Ifi202b, Nfkbia, and Nfkbie, were mapped to eight immune process-associated pathways. Subsequent quantitative real-time PCR assays confirmed that the 10 DEGs were all upregulated during infection. Overall, the results showed that B. pseudomallei infection can initiate a time-series upregulation of immune process-associated DEGs in RAW264.7 macrophage cells. The discovery of this article helps us better understand the biological function of the immune process-associated genes during B. pseudomallei infection and may aid in the development of prophylaxis and treatment protocols for melioidosis.
Conducting Polymer-Based Cantilever Sensors for Detection Humidity

This paper describes the use of different conducting polymers (polyaniline, poly(o-ethoxyaniline), and polypyrrole) as a sensitive layer on a silicon cantilever sensor. The mechanical response (deflection) of the bimaterial (the coated cantilever) was investigated under the influence of relative humidity. The variations in the deflection of the coated cantilevers when exposed to relative humidity were evaluated. The results indicated a linear sensitivity in ranges, where the high value was obtained for a polypyrrole-sensitive layer between 20 and 45% of humidity. Furthermore, the sensor shows excellent performance along with rapid response and recovery times, relatively low hysteresis, and excellent stability. The sensors developed are potentially excellent materials for sensing low humidity for long time.
Predicting Estimated Time of Arrival for Commercial Flights

Unprecedented growth is expected globally in commercial air traffic over the next ten years. To accommodate this increase in volume, a new concept of operations has been implemented in the context of the Next Generation Air Transportation System (NextGen) in the USA and the Single European Sky ATM Research (SESAR) in Europe. However, both of the systems approach airspace capacity and efficiency deterministically, failing to account for external operational circumstances which can directly affect the aircraft's actual flight profile. A major factor in increased airspace efficiency and capacity is accurate prediction of Estimated Time of Arrival (ETA) for commercial flights, which can be a challenging task due to a non-deterministic nature of environmental factors, and air traffic. Inaccurate prediction of ETA can cause potential safety risks and loss of resources for Air Navigation Service Providers (ANSP), airlines and passengers. In this paper, we present a novel ETA Prediction System for commercial flights. The system learns from historical trajectories and uses their pertinent 3D grid points to collect key features such as weather parameters, air traffic, and airport data along the potential flight path. The features are fed into various regression models and a Recurrent Neural Network (RNN) and the best performing models with the most accurate ETA predictions are compared with the ETAs currently operational by the European ANSP, EUROCONTROL. Evaluations on an extensive set of real trajectory, weather, and airport data in Europe verify that our prediction system generates more accurate ETAs with a far smaller standard deviation than those of EUROCONTROL. This translates to smaller prediction windows of flight arrival times, thereby enabling airlines to make more cost-effective ground resource allocation and ANSPs to make more efficient flight schedules.
Benzbromarone Attenuates Oxidative Stress in Angiotensin II- and Salt-Induced Hypertensive Model Rats

Oxidative stress induced by hyperuricemia is closely associated with the renin-angiotensin system, as well as the onset and progression of cardiovascular disease (CVD) and chronic kidney disease (CKD). It is therefore important to reduce oxidative stress to treat hyperuricemia. We previously found that benzbromarone, a uricosuric agent, has a direct free radical scavenging effect in vitro. The antioxidant effects of benzbromarone were evaluated in vivo via oral administration of benzbromarone for 4 weeks to model rats with angiotensin II- and salt-induced hypertension. Benzbromarone did not alter plasma uric acid levels or blood pressure but significantly reduced the levels of advanced oxidation protein products, which are oxidative stress markers. Furthermore, dihydroethidium staining of the kidney revealed a reduction in oxidative stress after benzbromarone administration. These results suggest that benzbromarone has a direct antioxidant effect in vivo and great potential to prevent CVD and CKD.
The functional verification of a satellite transponder

The evolution of the microelectronics industry in recent years has induced the possibility of integrating digital, mixed-signal and radiofrequency components in the same die; that has introduced higher complexity during the SoC development, specially in the verification process. In this paper, we present the verification strategy for a Transponder IP, focusing on the receiver and transmitter functionality and ensuring communication inside of SoC. In the verification process, we have adopted a testbench template with an environment model, which directly connects the analog transmitter to the analog receiver and establishes a closed flow to the signal of the Transponder IP. This approach's purpose is to guarantee the digital macroblocks correctness while reducing the verification complexity in the analog-digital interface.
Cuisine classification using recipe's ingredients

The purpose of this paper is to explore the linkage between recipe's ingredients and identification of a cuisine. This has been tackled as a problem of cuisine classification. We will examine various approaches (different machine learning algorithms) for recipes classification based on the recipe's ingredients. The output will be the recommendation of the classification methodology, i.e. what kind of preprocessing can be done to improve the classification and the performance of several classifiers on the dataset we will be using.
A Novel Substrate-Integrated Suspended Line Stacked-Patch Antenna Array for WLAN

A novel stacked-patch antenna based on substrate-integrated suspended line technology is proposed. The antenna is designed to be self-packaged using five substrate layers with embedded air cavities. Via is utilized to connect the antenna driven patch with the feed line, and then resonant frequency at 5.2 GHz is generated. U-shaped slot is etched on the antenna driven patch for impedance matching. In order to further extend the impedance bandwidth, a stacked patch with slant slot is introduced and then another resonant frequency at 6.2 GHz is produced. According to the measured results, the antenna element achieves a fractional bandwidth of 17.5% from 5.2 to 6.2 GHz and gain of 9.7 dBi. Based on the antenna element, the eight-element antenna array with feeding network is presented. The microstrip–slotline balun is introduced in the feeding network to achieve 180° phase difference with equal amplitude so that symmetrical radiation patterns are achieved. Simulation and measurement results for the proposed antenna array are in good agreement. In the frequency band from 5.28 to 6.05 GHz, antenna gain of 16.24 dBi with gain flatness variation of 1.5 dB is achieved. In addition, the front-to-back ratio of the self-packaged antenna array is better than 20 dB.
Elastic Neural Networks: A Scalable Framework for Embedded Computer Vision

We propose a new framework for image classification with deep neural networks. The framework introduces intermediate outputs to the computational graph of a network. This enables flexible control of the computational load and balances the tradeoff between accuracy and execution time. Moreover, we present an interesting finding that the intermediate outputs can act as a regularizer at training time, improving the prediction accuracy. In the experimental section we demonstrate the performance of our proposed framework with various commonly used pretrained deep networks in the use case of apparent age estimation.