Miracle-dz/UniFAR-FTUs huggingface dataset:
The Test Results of AC and DC HTS Cables in Russia

Urgent problems of the power industry of the 21st century require the creation of smart energy systems, providing high efficiency in the generation, transportation, and consumption of electricity as well as increased requirements for the manageability of energy systems and environmental and resource-saving characteristics. One of the solutions to the many problems of the power industry is the creation of new high-efficiency electrical equipment for intelligent power systems based on superconducting technologies to ensure a qualitatively new level of functioning of the electric power industry. In most industrialized countries, superconducting power cables are one of the most advanced developments of superconducting devices. Taking into account the obvious advantages of superconducting cable lines for the transmission of large power flow through an electric network, compared with conventional cables, the Federal Grid Company of Unified Energy System (PJSC “FGC UES”) initiated an R&D program that includes the creation of high-temperature superconducting ac and dc cable lines. Two cable lines and accessories on the transmitted power of 50 MW at 20 kV were made. Tests of both types of cables were conducted in the R&D Center at FGC UES JSC in Moscow. The test results are presented in the report.
A Tool to Assess Student Performance in a Clostridium difficile Infection Simulation Scenario

Objective. To develop and validate an evaluation tool to assess student pharmacists' performance in a simulation scenario involving a patient with Clostridium difficile infection (CDI). Methods. The authors used an expert panel review process to establish content validity of the tool. Four faculty members used the tool to evaluate student pharmacist groups during 2011 and tested a modified version of the tool in 2012. The authors analyzed the results for each year to determine internal consistency and inter-rater reliability. Results. The 2011 tool demonstrated sound internal consistency, but several items had poor inter-rater agreement. The revised 2012 tool demonstrated acceptable internal consistency and good to excellent inter-rater agreement for all items except one. Conclusions. The tool facilitated reliable assessment of student pharmacists' clinical decision-making during simulation performance involving a patient with CDI.
A Multilingual Parallel Parsed Corpus as Gold Standard for Grammatical Inference Evaluation

In this article we investigate how (computational) grammar inference systems are evaluated and how the evaluation procedure can be improved. First, we describe the currently used evaluation methods and look at the advantages and disadvantages of each method. The main problems of the methods are: the dependency on language experts, the influence of the annotation scheme of language data, and the language dependency of the evaluation. We then propose a new method that will allow for an evaluation independently of language and annotation scheme. This method requires (syntactically) structured corpora in multiple languages to test for language independency of the grammatical inference system and corpora structured using different annotation schemes to diminish the influence the annotation has on the evaluation.
Effective Computational Modeling for Early Arrhythmia Symptom Classification by Using Decision Tree Approach

Heart disease has been the leading global cause of death for almost 15 years. One of the common causes lead to chronic heart disease and sudden death is Arrhythmia. However, the conventional or computational approach of Arrhythmia detection is not an easy task. It requires suitable method with a very specific timeline to detect the symptom. In addition, the symptom itself is very complex in behavior. Therefore, an automatic detection method with simple computational model to detect accurately Arrhythmia in ECG data is needed to deal with such critical issue. In this paper, a novel framework based on decision tree approach by utilizing five peaks taken from ECG segment is proposed to detect Arrhythmia from the first minute of the ECG data. The experimental results show that the proposed decision tree approach with the proposed five peaks is able to detect Arrhythmia with the accuracy of 98% outperforming the other data mining techniques. Moreover, the five proposed parameters to classify the disease show that these computational models have a strong level of sustainability in detecting Arrhythmia when it is compared to different numbers of parameters and methods.
Schizosaccharomyces pombe MutSα and MutLα Maintain Stability of Tetra-Nucleotide Repeats and Msh3 of Hepta-Nucleotide Repeats

Defective mismatch repair (MMR) in humans is associated with colon cancer and instability of microsatellites, that is, DNA sequences with one or several nucleotides repeated. Key factors of eukaryotic MMR are the heterodimers MutSα (Msh2-Msh6), which recognizes base-base mismatches and unpaired nucleotides in DNA, and MutLα (Mlh1-Pms1), which facilitates downstream steps. In addition, MutSβ (Msh2-Msh3) recognizes DNA loops of various sizes, although our previous data and the data presented here suggest that Msh3 of Schizosaccharomyces pombe does not play a role in MMR. To test microsatellite stability in S. pombe and hence DNA loop repair, we have inserted tetra-, penta-, and hepta-nucleotide repeats in the ade6 gene and determined their Ade+ reversion rates and spectra in wild type and various mutants. Our data indicate that loops with four unpaired nucleotides in the nascent and the template strand are the upper limit of MutSα- and MutLα-mediated MMR in S. pombe. Stability of hepta-nucleotide repeats requires Msh3 and Exo1 in MMR-independent processes as well as the DNA repair proteins Rad50, Rad51, and Rad2FEN1. Most strikingly, mutation rates in the double mutants msh3 exo1 and msh3 rad51 were decreased when compared to respective single mutants, indicating that Msh3 prevents error prone processes carried out by Exo1 and Rad51. We conclude that Msh3 has no obvious function in MMR in S. pombe, but contributes to DNA repeat stability in MMR-independent processes.
Performance evaluation of declarative memory systems in Soar

A rarely studied issue with using persistent computational models is whether the underlying computational mechanisms scale as knowledge is accumulated through learning. In this paper we evaluate the declarative memories of Soar: working memory, semantic memory, and episodic memory, using a detailed simulation of a mobile robot running for one hour of real-time. Our results indicate that our implementation is sufficient for tasks of this length. Moreover our system executes orders of magnitudes faster than real-time, with relatively modest storage requirements. We also project the computational resources required for extended operations.
Melanocortins and agouti‐related protein modulate the excitability of two arcuate nucleus neuron populations by alteration of resting potassium conductances

The hypothalamic melanocortin system is crucial for the control of appetite and body weight. Two of the five melanocortin receptors, MC3R and MC4R are involved in hypothalamic control of energy homeostasis, with the MC4R having the major influence. It is generally thought that the main impact of the melanocortin system on hypothalamic circuits is external to the arcuate nucleus, and that any effect locally in the arcuate nucleus is inhibitory on proopiomelanocortin‐expressing (POMC) neurons. In contrast, using current‐ and voltage‐clamp recordings from identified neurons, we demonstrate that MC3R and MC4R agonists depolarize arcuate POMC neurons and a separate arcuate neuronal population identified by the rat insulin 2 promoter (RIPCre) transgene expression. Furthermore, the endogenous MC3R and MC4R antagonist, agouti‐related protein (AgRP), hyperpolarizes POMC and RIPCre neurons in the absence of melanocortin agonist, consistent with inverse agonism at the MC4R. A decreased transient outward (IA) potassium conductance, and to a lesser extent the inward rectifier (KIR) conductance, underlies neuronal depolarization, whereas an increase in IA mediates AgRP‐induced hyperpolarization. Accordingly, POMC and RIPCre neurons may be targets for peptide transmitters that are possibly released locally from AgRP‐expressing and POMC neurons in the arcuate nucleus, adding further previously unappreciated complexity to the arcuate system.
The Role of Complex Network Dynamics in the Emergence of Multiagent Coalition

Emergence of a single coalition among self-interested agents operating on large scale-free networks is a challenging task. Many existing approaches assume a given static network platform and do not use the network dynamics to facilitate the dynamics of agent interactions. In this paper, we present a decentralized game-theoretic approach to this single coalition emergence problem in which agent communications are limited only to their immediate neighbors. Our coalition emergence algorithm is based on the heuristic that agents benefit by forming coalitions with wealthy (higher payoff) and influential (higher accumulated coupling strength) neighbors. Simulation results show that the emergence phenomenon is significantly enhanced when the topological insights, such as increasing degree-heterogeneity and clustering, are embedded into the agent partner selection strategy.
The COST292 experimental framework for TRECVID 2007

In this paper, we give an overview of the four tasks submitted to TRECVID 2007 by COST292. In shot boundary (SB) detection task, four SB detectors have been developed and the results are merged using two merging algorithms. The framework developed for the high-level feature extraction task comprises four systems. The first system transforms a set of low-level descriptors into the semantic space using Latent Semantic Analysis and utilises neural networks for feature detection. The second system uses a Bayesian classifier trained with a “bag of subregions”. The third system uses a multi-modal classifier based on SVMs and several descriptors. The fourth system uses two image classifiers based on ant colony optimisation and particle swarm optimisation respectively. The system submitted to the search task is an interactive retrieval application combining retrieval functionalities in various modalities with a user interface supporting automatic and interactive search over all queries submitted. Finally, the rushes task submission is based on a video summarisation and browsing system comprising two dierent interest curve algorithms and three features.
Epidemic Threshold of an SIS Model in Dynamic Switching Networks

In this paper, we analyze dynamic switching networks, wherein the networks switch arbitrarily among a set of topologies. For this class of dynamic networks, we derive an epidemic threshold, considering the susceptible-infected-susceptible epidemic model. First, an epidemic probabilistic model is developed assuming independence between states of nodes. We identify the conditions under which the epidemic dies out by linearizing the underlying dynamical system and analyzing its asymptotic stability around the origin. The concept of joint spectral radius is then used to derive the epidemic threshold, which is later validated using several networks (Watts-Strogatz, Barabasi-Albert, MIT reality mining graphs, Regular, and Gilbert). A simplified version of the epidemic threshold is proposed for undirected networks. Moreover, in the case of static networks, the derived epidemic threshold is shown to match conventional analytical results. Then, analytical results for the epidemic threshold of dynamic networks are proved to be applicable to periodic networks. For dynamic regular networks, we demonstrate that the epidemic threshold is identical to the epidemic threshold for static regular networks. An upper bound for the epidemic spread probability in dynamic Gilbert networks is also derived and verified using simulation.
Sparsity Order Estimation and its Application in Compressive Spectrum Sensing for Cognitive Radios

Compressive sampling techniques can effectively reduce the acquisition costs of high-dimensional signals by utilizing the fact that typical signals of interest are often sparse in a certain domain. For compressive samplers, the number of samples Mr needed to reconstruct a sparse signal is determined by the actual sparsity order Snz of the signal, which can be much smaller than the signal dimension N. However, Snz is often unknown or dynamically varying in practice, and the practical sampling rate has to be chosen conservatively according to an upper bound Smax of the actual sparsity order in lieu of Snz, which can be unnecessarily high. To circumvent such wastage of the sampling resources, this paper introduces the concept of sparsity order estimation, which aims to accurately acquire Snz prior to sparse signal recovery, by using a very small number of samples Me less than Mr. A statistical learning methodology is used to quantify the gap between Mr and Me in a closed form via data fitting, which offers useful design guideline for compressive samplers. It is shown that Me ≥ 1.2Snz log(N/Snz + 2) + 3 for a broad range of sampling matrices. Capitalizing on this gap, this paper also develops a two-step compressive spectrum sensing algorithm for wideband cognitive radios as an illustrative application. The first step quickly estimates the actual sparsity order of the wide spectrum of interest using a small number of samples, and the second step adjusts the total number of collected samples according to the estimated signal sparsity order. By doing so, the overall sampling cost can be minimized adaptively, without degrading the sensing performance.
Disordered macrophage cytokine secretion underlies impaired acute inflammation and bacterial clearance in Crohn's disease

The cause of Crohn's disease (CD) remains poorly understood. Counterintuitively, these patients possess an impaired acute inflammatory response, which could result in delayed clearance of bacteria penetrating the lining of the bowel and predispose to granuloma formation and chronicity. We tested this hypothesis in human subjects by monitoring responses to killed Escherichia coli injected subcutaneously into the forearm. Accumulation of 111In-labeled neutrophils at these sites and clearance of 32P-labeled bacteria from them were markedly impaired in CD. Locally increased blood flow and bacterial clearance were dependent on the numbers of bacteria injected. Secretion of proinflammatory cytokines by CD macrophages was grossly impaired in response to E. coli or specific Toll-like receptor agonists. Despite normal levels and stability of cytokine messenger RNA, intracellular levels of tumor necrosis factor (TNF) were abnormally low in CD macrophages. Coupled with reduced secretion, these findings indicate accelerated intracellular breakdown. Differential transcription profiles identified disease-specific genes, notably including those encoding proteins involved in vesicle trafficking. Intracellular destruction of TNF was decreased by inhibitors of lysosomal function. Together, our findings suggest that in CD macrophages, an abnormal proportion of cytokines are routed to lysosomes and degraded rather than being released through the normal secretory pathway.
DoS-Resilient Hybrid Controller for String-Stable Connected Vehicles

The problem of designing a decentralized Cooperative Adaptive Cruise Control (CACC) resilient to Denial-of-Service (DoS) attacks while satisfying performance requirements is studied. A decentralized proportional-derivative hybrid controller is employed for string stability of a platoon of vehicles. A timer triggering the arrival of new measurements from preceding vehicles augments the closed-loop system. A computationally affordable algorithm based on matrix inequalities is devised to design a CACC controller able to meet performance specifications and to guarantee string stability up to an estimated number of consecutive packet dropouts. Finally, the effectiveness of the proposed approach is shown in a numerical example.
A Performance Analysis on Message Passing Tools for the Grid

In this paper we introduce three message passing tools and we propose a high level performance evaluation based on a real deployment scenario and basic benchmarking scenario. In order to support the performance evaluation process, we introduce basic evaluation means at the application level and a generalized parallel message passing application scenario. We present the performance evaluation results and discuss the applicability of each solution in the grid application landscape.
An Online Multiple-speaker DOA Tracking Using the CappÉ-Moulines Recursive Expectation-maximization Algorithm

In this paper, we present a multiple-speaker direction of arrival (DOA) tracking algorithm with a microphone array that utilizes the recursive EM (REM) algorithm proposed by Cappé and Moulines. In our model, all sources can be located in one of a predefined set of candidate DOAs. Accordingly, the received signals from all microphones are modeled as Mixture of Gaussians (MoG) vectors in which each speaker is associated with a corresponding Gaussian. The localization task is then formulated as a maximum likelihood (ML) problem, where the MoG weights and the power spectral density (PSD) of the speakers are the unknown parameters. The REM algorithm is then utilized to estimate the ML parameters in an online manner, facilitating multiple source tracking. By using Fisher-Neyman factorization, the outputs of the minimum variance distortionless response (MVDR)-beamformer (BF) are shown to be sufficient statistics for estimating the parameters of the problem at hand. With that, the terms for the E-step are significantly simplified to a scalar form. An experimental study demonstrates the benefits of the using proposed algorithm in both a simulated data-set and real recordings from the acoustic source localization and tracking (LOCATA) data-set.
Restriction fragment length polymorphism study of Mycobacterium tuberculosis in Thailand using IS6110 as probe.

SETTING Three referral hospitals in central Thailand. OBJECTIVE To determine the population structure of Mycobacterium tuberculosis isolated from the referral hospitals. DESIGN Study of 211 isolates of the bacteria received from the hospitals in central Thailand by Southern hybridization, with IS6110 probe and other probes when indicated. RESULTS In 43 isolates only one copy of IS6110 was observed. These could be further differentiated by DR- and PGRS-specific probes. Two large groups of isolates with similar hybridization patterns were identified. The Beijing family, comprising 80 isolates, was previously reported to be commonly found in China, Mongolia, Thailand and Korea. The Nonthaburi group, comprising 29 isolates, were local strains. The age, sex and HIV status of the patients did not significantly correlate with the chance of being infected by isolates of any particular hybridization pattern. However, clustered isolates were found more commonly among the members of both the Beijing family and the Nonthaburi group. CONCLUSION Southern hybridization with IS6110 was found to be useful in studying the epidemiology of tuberculosis in Thailand. The existence of the Beijing family was confirmed. The unusually wide spread of the Beijing family in several countries in Asia merits further investigation.
EGFR Exon-Level Biomarkers of the Response to Bevacizumab/Erlotinib in Non-Small Cell Lung Cancer

Activating epidermal growth factor receptor (EGFR) mutations are recognized biomarkers for patients with metastatic non-small cell lung cancer (NSCLC) treated with EGFR tyrosine kinase inhibitors (TKIs). EGFR TKIs can also have activity against NSCLC without EGFR mutations, requiring the identification of additional relevant biomarkers. Previous studies on tumor EGFR protein levels and EGFR gene copy number revealed inconsistent results. The aim of the study was to identify novel biomarkers of the response to TKIs in NSCLC by investigating whole genome expression at the exon-level. We used exon arrays and clinical samples from a previous trial (SAKK19/05) to investigate the expression variations at the exon-level of 3 genes potentially playing a key role in modulating treatment response: EGFR, V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) and vascular endothelial growth factor (VEGFA). We identified the expression of EGFR exon 18 as a new predictive marker for patients with untreated metastatic NSCLC treated with bevacizumab and erlotinib in the first line setting. The overexpression of EGFR exon 18 in tumor was significantly associated with tumor shrinkage, independently of EGFR mutation status. A similar significant association could be found in blood samples. In conclusion, exonic EGFR expression particularly in exon 18 was found to be a relevant predictive biomarker for response to bevacizumab and erlotinib. Based on these results, we propose a new model of EGFR testing in tumor and blood.
An improved simulated annealing maximum power point tracking technique for PV array under partial shading conditions

This paper presents an improved Simulated Annealing (SA) based Maximum Power Point Tracking (MPPT) technique designed for photovoltaic (PV) systems under partial shading conditions (PSC). Compared with existing SA MPPT algorithms, the proposed method performs faster convergence speed, higher tracking accuracy and continuously tracking of the global Maximum Power Point (GMPP) under climate changes. The new SA MPPT principle is fully explained, discussed and verified by simulation.
Optimized Generation of Functional Neutrophils and Macrophages from Patient-Specific Induced Pluripotent Stem Cells: Ex Vivo Models of X0-Linked, AR220- and AR470- Chronic Granulomatous Diseases

Abstract Chronic granulomatous disease (CGD) is an inherited orphan disorder caused by mutations in one of the five genes encoding reduced nicotinamide-adenine-dinucleotide-phosphate oxidase subunits, which subsequently lead to impairment in the production of microbicidal reactive oxygen species (ROS). In order to offer several cell line models of CGD and therefore support research on pathophysiology and new therapeutic approaches, we optimized protocols to differentiate induced pluripotent stem cells (iPSCs) from wild-type, X0-, AR220- and AR470-CGD patient's fibroblasts into neutrophils and into macrophages. Aberrant genetic clones were discarded after chromosome karyotyping and array-comparative genomic hybridization analysis. All remaining iPSC lines showed human embryonic stem cell–like morphology, expressed all tested pluripotency markers and formed embryoid bodies that contained cells originating from all three primary germ layers. Furthermore, each CGD patient-specific iPSC line retained the gp91phox, p47phox, and p22phox mutations found in the corresponding patient's neutrophils. The average production of CD34+ progenitors was of 1.5×106 cells after 10 days of differentiation of 10×106 iPSCs. They were terminally differentiated into about 3×105 neutrophils or into 3×107 macrophages. Based on morphological, phenotypical, and functional criteria both phagocyte types were mature and indistinguishable from the native human neutrophils and macrophages. However, neutrophils and macrophages derived from X0-, AR220-, and AR470-CGD patient-specific iPSC lines lacked ROS production and the corresponding mutated proteins. To simplify the phagocytes' production upon request, progenitors can be cryopreserved. In conclusion, we describe a reproducible, simple, and efficient way to generate neutrophils and macrophages from iPSCs and provide a new cellular model for the AR220-CGD genetic form that has not been described before.