Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and implementation of a high-efficiency on- board battery charger for electric vehicles with frequency control strategy

This paper presents a design and implementation of 3.3 kW on-board battery charger for electric vehicles or plug-in hybrid electric vehicles. A series-loaded resonant dc-dc converter and frequency control are adopted in consideration of efficiency, reliability, volume, cost, and so on. In order to obtain high efficiency and less volume within 6 liters, a prototype of the charger is designed and implemented by using high frequency of 80–130kHz and zero voltage switching method. The experimental result indicates 93% of the maximum efficiency and 5.84 liters in volume of the developed 3.3 kW on-board battery charger. Keywords-fuel cell electric vehicle; FCEV; low frequency current ripple; fuel cell; driving condition
Assignment of Biochemical Functions to Glycosyl Transferase Genes Which Are Essential for Biosynthesis of Exopolysaccharides in Sphingomonas Strain S88 andRhizobium leguminosarum

ABSTRACT Glycosyl transferases which recognize identical substrates (nucleotide-sugars and lipid-linked carbohydrates) can substitute for one another in bacterial polysaccharide biosynthesis, even if the enzymes originate in different genera of bacteria. This substitution can be used to identify the substrate specificities of uncharacterized transferase genes. The spsK gene ofSphingomonas strain S88 and the pssDE genes ofRhizobium leguminosarum were identified as encoding glucuronosyl-(β1→4)-glucosyl transferases based on reciprocal genetic complementation of mutations in the spsK gene and the pssDE genes by segments of cloned DNA and by the SpsK-dependent incorporation of radioactive glucose (Glc) and glucuronic acid (GlcA) into lipid-linked disaccharides in EDTA-permeabilized cells. By contrast, glycosyl transferases which form alternative sugar linkages to the same substrate caused inhibition of polysaccharide synthesis or were deleterious or lethal in a foreign host. The negative effects also suggested specific substrate requirements: we propose that spsL codes for a glucosyl-(β1→4)-glucuronosyl transferase inSphingomonas and that pssC codes for a glucuronosyl-(β1→4)-glucuronosyl transferase in R. leguminosarum. Finally, the complementation results indicate the order of attachment of sphingan main-chain sugars to the C55-isoprenylphosphate carrier as -Glc-GlcA-Glc-isoprenylpyrophosphate.
K-MCore for Multicasting on Mobile Ad Hoc Networks

A k-cluster of a tree includes a single path and k-1 sub-paths growing from that path. A k-MCore is a k-cluster that minimizes the sum of the distances of all vertices to the cluster plus the size of the cluster. This structure is motivated by the applications on overlay multicasting. The overlay multicast protocol constructs a virtual mesh spanning all member nodes of a multicast group. It employs standard unicast routing and forwarding to fulfill multicast functionality. In this paper, we propose effective distributed algorithms for constructing k-MCore on a tree network. The k-MCore is more stable and easier to maintain than the spanning tree in virtual mesh. The simulation results show that our approach handles the flexibility and mobility issues in an overlay multicast protocol effectively, especially when the group size is large
Theta oscillations by synaptic excitation in a neocortical circuit model

Neocortical theta-band oscillatory activity is associated with cognitive tasks involving learning and memory. This oscillatory activity is proposed to originate from the synchronization of interconnected layer V intrinsic bursting (IB) neurons by recurrent excitation. To test this hypothesis, a sparsely connected spiking circuit model based on empirical data was simulated using Hodgkin-Huxley-type bursting neurons and use-dependent depressing synaptic connections. In response to a heterogeneous tonic current stimulus, the model generated coherent and robust oscillatory activity throughout the theta-band (4-12 Hz). These oscillations were not, however, self-sustaining without a driving current, and not dependent on N-methyl-D-aspartate receptor synaptic currents. At realistic connection strengths, synaptic depression was necessary to avoid instability and expanded the basin of attraction for theta oscillations by controlling the gain of recurrent excitation. These results support the hypothesis that IB neuron networks can generate robust and coherent theta-band oscillations in neocortex.
Analysis of MLH3 C2531T polymorphism in Iranian women with unexplained infertility

Background: Meiotic genes are very important candidates for genes contributing to female and male infertility. Mammalian MutL homologues have dual roles in DNA mismatch repair (MMR) after replication errors and meiotic reciprocal recombination. The MutL homologs, MLH1 and MLH3, are crucial for meiotic reciprocal recombination and human fertility. In this study the functional polymorphisms of MLH3 C2531T was investigated in Iranian women with unexplained infertility. Objective: Investigating the association between a common SNP (single nucleotide polymorphism) C2531T in the MLH3 gene and female infertility. Materials and Methods: In total, 105 women with unexplained infertility as case group and 100 women with at least one child and no history of infertility or abortion as controls were recruited for this association study. The MLH3 C2531T polymorphism was tested by tetra-amplification refractory mutation system-PCR (4P-ARMS-PCR) method. Results: The MLH3 2531C and T alleles frequencies were 43.33% and 56.67% among infertile patients, and 61.5% and 38.5% among normal controls, respectively. In the patient and control subjects the CC (Pro 844 Pro) genotype frequency of MLH3 C2531T was 4.76% and 25%, the CT (Pro 844 Leu) genotype was 77.15% and 73%, and the TT (Leu 844 Leu) genotype was 19% and 2%, respectively (p=0.0001). Conclusion: The presence of the polymorphic allele T leads to an increased risk of 2.09 times (OR=2.09, 95% CI=1.38-3.16; p=0.0001) for developing infertility in relation to the control group. Therefore, our data suggest that the MLH3 C2531T polymorphism can be associated with the risk of unexplained infertility in Iranian women.
Proteotoxic Stress Induces Phosphorylation of p62/SQSTM1 by ULK1 to Regulate Selective Autophagic Clearance of Protein Aggregates

Disruption of proteostasis, or protein homeostasis, is often associated with aberrant accumulation of misfolded proteins or protein aggregates. Autophagy offers protection to cells by removing toxic protein aggregates and injured organelles in response to proteotoxic stress. However, the exact mechanism whereby autophagy recognizes and degrades misfolded or aggregated proteins has yet to be elucidated. Mounting evidence demonstrates the selectivity of autophagy, which is mediated through autophagy receptor proteins (e.g. p62/SQSTM1) linking autophagy cargos and autophagosomes. Here we report that proteotoxic stress imposed by the proteasome inhibition or expression of polyglutamine expanded huntingtin (polyQ-Htt) induces p62 phosphorylation at its ubiquitin-association (UBA) domain that regulates its binding to ubiquitinated proteins. We find that autophagy-related kinase ULK1 phosphorylates p62 at a novel phosphorylation site S409 in UBA domain. Interestingly, phosphorylation of p62 by ULK1 does not occur upon nutrient starvation, in spite of its role in canonical autophagy signaling. ULK1 also phosphorylates S405, while S409 phosphorylation critically regulates S405 phosphorylation. We find that S409 phosphorylation destabilizes the UBA dimer interface, and increases binding affinity of p62 to ubiquitin. Furthermore, lack of S409 phosphorylation causes accumulation of p62, aberrant localization of autophagy proteins and inhibition of the clearance of ubiquitinated proteins or polyQ-Htt. Therefore, our data provide mechanistic insights into the regulation of selective autophagy by ULK1 and p62 upon proteotoxic stress. Our study suggests a potential novel drug target in developing autophagy-based therapeutics for the treatment of proteinopathies including Huntington’s disease.
Statistical Thermal Profile Considering Process Variations: Analysis and Applications

The nonuniform substrate thermal profile and process variations are two major concerns in the present-day ultra-deep submicrometer designs. To correctly predict performance/ leakage/reliability measures and address any yield losses during the early stages of design phases, it is desirable to have a reliable thermal estimation of the chip. However, the leakage power sources vary greatly due to process variations and temperature, which result in significant variations in the hotspot and thermal profile formation in very large scale integration chips. Traditionally, no leakage variations have been considered during full-chip thermal analysis. In this paper, the dependence behavior among the process variability, leakage power consumption, and thermal profile construction are established to effectively extract a reliable statistical thermal profile over a die at the microarchitectural level. Knowledge of this is the key to the design and analysis of circuits. The probability density functions of temperatures are extracted while considering the leakage variations due to the gate-length and oxide-thickness variations and while accounting for the coupling between the temperature and the total leakage. Two applications of the developed analyzer are investigated, namely, the evaluation of the hotspots' relocations and the total full-chip power estimation. Finally, the accuracy and efficiency of the developed analyzer are validated by comparisons with Monte Carlo simulations.
Toward an analysis of forward pruning

Sever0,1 early game-playing computer programs used forward pruning (i.e., the practice of delib- erately ignoring nodes that are believed unlikely to affect a game tree's minimax value), but this technique did not seem to result in good decision- making. The poor performance of forward prun- ing presents a major puzzle for AI research on game playing, because some version of forward pruning seems to be "what people do," and the best chess-playing programs still do not play as well as the best humans. As a step toward deeper understanding of how for- ward pruning affects quality of play, in this paper we set up a model of forward pruning on two ab- stract classes of binary game trees, and we use this model to investigate how forward pruning affects the accuracy of the minimax values returned. The primary result of our study is that forward prun- ing does better when there is a high correlation among the minimax values of sibling nodes in a game tree. This result suggests that forward pruning may possibly be a useful decision-making technique in certain kinds of games. In particular, we believe that bridge may be such a game.
Lexicon Optimization: Maximizing Lexical Coverage in Speech Recognition through Automated Compounding

In this report we show that a lexicon can be designed in such a way that lexical coverage can be maximized by real-time lexicon expansion and a limited word part lexicon for Dutch speech recognition. More specifically, we describe how the lexicon is designed and how the real-time expansion module was built and tested. Tests were performed using a 36.000 entries lexicon. The test results show that out-ofvocabulary rates are rather small, due to automated rule-based compounding of the lexical building blocks. Statistical information was included to improve the accuracy of the rule-based compounding system. This approach proved to be successful.
Theory of pseudomodes in quantum optical processes

This paper deals with non-Markovian behavior in atomic systems coupled to a structured reservoir of quantum electromagnetic field modes, with particular relevance to atoms interacting with the field in high-Q cavities or photonic band-gap materials. In cases such as the former, we show that the pseudomode theory for single-quantum reservoir excitations can be obtained by applying the Fano diagonalization method to a system in which the atomic transitions are coupled to a discrete set of (cavity) quasimodes, which in turn are coupled to a continuum set of (external) quasimodes with slowly varying coupling constants and continuum mode density. Each pseudomode can be identified with a discrete quasimode, which gives structure to the actual reservoir of true modes via the expressions for the equivalent atom-true mode coupling constants. The quasimode theory enables cases of multiple excitation of the reservoir to now be treated via Markovian master equations for the atom-discrete quasimode system. Applications of the theory to one, two, and many discrete quasimodes are made. For a simple photonic band-gap model, where the reservoir structure is associated with the true mode density rather than the coupling constants, the single quantum excitation case appears to be equivalent to a case with two discrete quasimodes.
Consensus Based Medical Image Segmentation Using Semi-Supervised Learning And Graph Cuts

Medical image segmentation requires consensus ground truth segmentations to be derived from multiple expert annotations. A novel approach is proposed that obtains consensus segmentations from experts using graph cuts (GC) and semi supervised learning (SSL). Popular approaches use iterative Expectation Maximization (EM) to estimate the final annotation and quantify annotator's performance. Such techniques pose the risk of getting trapped in local minima. We propose a self consistency (SC) score to quantify annotator consistency using low level image features. SSL is used to predict missing annotations by considering global features and local image consistency. The SC score also serves as the penalty cost in a second order Markov random field (MRF) cost function optimized using graph cuts to derive the final consensus label. Graph cut obtains a global maximum without an iterative procedure. Experimental results on synthetic images, real data of Crohn's disease patients and retinal images show our final segmentation to be accurate and more consistent than competing methods.
Robust Speaker Recognition Using Binary Time-Frequency Masks

Conventional speaker recognition systems perform poorly under noisy conditions. In this paper, we evaluate binary time-frequency masks for robust speaker recognition. An ideal binary mask is a priori defined as a binary matrix where 1 indicates that the target is stronger than the interference within the corresponding time-frequency unit and 0 indicates otherwise. We perform speaker identification and verification using a missing data recognizer under cochannel and other noise conditions, and show that the ideal binary mask provides large performance gains. By employing a speech segregation system that estimates the ideal binary mask, we achieve significant improvements over alternative approaches. Our study, thus, demonstrates that the use of binary masking represents a promising direction for robust speaker recognition
Small and Long Regulatory RNAs in the Immune System and Immune Diseases

Cellular differentiation is regulated on the level of gene expression, and it is known that dysregulation of gene expression can lead to deficiencies in differentiation that contribute to a variety of diseases, particularly of the immune system. Until recently, it was thought that the dysregulation was governed by changes in the binding or activity of a class of proteins called transcription factors. However, the discovery of micro-RNAs and recent descriptions of long non-coding RNAs (lncRNAs) have given enormous momentum to a whole new field of biology: the regulatory RNAs. In this review, we describe these two classes of regulatory RNAs and summarize what is known about how they regulate aspects of the adaptive and innate immune systems. Finally, we describe what is known about the involvement of micro-RNAs and lncRNAs in three different autoimmune diseases (celiac disease, inflammatory bowel disease, and multiple sclerosis).
Towards Designing a Multipurpose Cybercrime Intelligence Framework

With the wide spread of the Internet and the increasing popularity of social networks that provide prompt and ease of communication, several criminal and radical groups have adopted it as a medium of operation. Existing literature in the area of cybercrime intelligence focuses on several research questions and adopts multiple methods using techniques such as social network analysis to address them. In this paper, we study the broad state-of-the-art research in cybercrime intelligence in order to identify existing research gaps. Our core aim is designing and developing a multipurpose framework that is able to fill these gaps using a wide range of techniques. We present an outlineof a framework designed to aid law enforcement in detecting, analysing and making sense out of cybercrime data.
Recent Advances in Needleless Electrospinning of Ultrathin Fibers: From Academia to Industrial Production

Electrospinning (e-spinning) has been extensively explored as a simple, versatile, and cost-effective method in preparing ultrathin fibers from a wide variety of materials. Electrospun (e-spun) ultrathin fibers are now widely used in tissue scaffold, wound dressing, energy harvesting and storage, environment engineering, catalyst, and textile. However, compared with conventional fiber industry, one major challenge associated with e-spinning technology is its production rate. Over the last decade, compared with conventional needle e-spinning, needleless e-spinning has emerged as the most efficient strategy for large-scale production of ultrathin fibers. For example, rolling cylinder and stationary wire as spinnerets have been commercialized successfully for significantly improving throughput of e-spun fibers. The significant advancements in needleless e-spinning approaches, including spinneret structures, productivity, and fiber quality are reviewed. In addition, some striking examples of innovative device designs toward higher throughput, as well as available industrial-scale equipment and commercial applications in the market are highlighted.
Percutaneous transhepatic biliary stenting in patients with intradiverticular papillae and biliary strictures caused by ampullary carcinoma: A case report

Endoscopic retrograde cholangiopancreatography with endoscopic sphincterotomy is a well-established procedure for the treatment of bile duct strictures. However, the procedure is difficult to perform in patients with intradiverticular papillae or tumor infiltration of the major papilla. Percutaneous transhepatic biliary stenting (PTBS) is commonly used in the management of malignant biliary stricture. The current study reports two cases of PTBS performed to treat malignant obstructive jaundice caused by ampullary carcinoma complicated with intradiverticular papillae. PTBS is potentially a safe technique for this relatively rare condition.
Combining Motion Sensors and Ultrasonic Hands Tracking for Continuous Activity Recognition in a Maintenance Scenario

We present a novel method for continuous activity recognition based on ultrasonic hand tracking and motion sensors attached to the user's arms. It builds on previous work in which we have shown such a sensor combination to be effective for isolated recognition in manually segmented data. We describe the hand tracking based segmentation, show how classification is done on both the ultrasonic and the motion data and discuss different classifier fusion methods. The performance of our method is investigated in a large scale experiment in which typical bicycle repair actions are performed by 6 different subjects. The experiment contains a test set with 1008 activities from 21 classes encompassing 115 minutes randomly mixed with 252 minutes of 'NULL' class. To come as close as possible to a real life continuous scenario we have ensured a diverse and complex 'NULL' class, diverse and often similar activities, inter person training/testing and an additional data set only for training (299 extra minutes of data). A key result of the paper is that our method can handle the user independent testing (testing on users that were not seen in training) nearly as well as the user dependent case.
Comparing the Textural properties of Surimi and Fish Protein Isolate Gels Produced from Silver Carp

ABSTRACT- In this study, texture profile analysis and a creep test were used to determine the textural quality attributes of fish protein isolates and conventional surimi. These isolates were made from raw materials obtained from filleting processes of Silver carp (Hypophthalmichthys molitrix) using acid and alkaline aided treatments. Texture profile analysis was performed in order to obtain hardness, cohesiveness, springiness and chewiness of the samples. Added to this, a creep test was applied to measure the elasticity value of the samples. Results were compared to the attributes of conventional surimi produced from the fish. Textural assessment was performed on gel samples formed by heating in hot water at 85 °C for 30 min. Comparison of fish protein isolate gels and the conventional surimi indicated significant differences in texture profile analysis parameters except for springiness value. Furthermore, the results of the creep test revealed that conventional surimi had significantly lower elasticity (29.8±0.9%) than fish protein isolate gels.
An atrial fibrillation detection algorithm for an implantable atrial defibrillator

The purpose of study was to evaluate the performance of an atrial fibrillation (AF) defection method for use in an implantable atrial defibrillator. Since AF is not immediately life threatening, a detection algorithm can be designed to be highly specific to avoid inappropriate shock delivery. Wideband electrograms (EGMS) were recorded from an acute bipolar ventricular lead (RV), and from a vector formed by two multipolar mapping leads located in the right atrium (RA), and coronary sinus (CS) in humans. A filtered RV EGM was used to provide ventricular sensing for R-wave detection. A filtered RA-CS EGM was used for AF detection. The gain of each sensing channel was automatically adjusted. The AF detection algorithm consisted of two independent serial tests, Quiet Interval Analysis (QIA) and Baseline Crossing Analysis (BCA). To obtain high specificity, if was required that both algorithms detect the analyzed rhythm as atrial fibrillation to classify if as atrial fibrillation.
Entrepreneurship, Information, and Growth

We examine the contribution to economic growth of entrepreneurial "marketplace information" within a regional endogenous growth framework. Entrepreneurs are posited to provide an input to economic growth through the information revealed by their successes and failures. We empirically identify this information source with the regional variation in establishment births and deaths, which create geographic information asymmetries that influence subsequent entrepreneurial activity and economic growth. We find that local establishment birth and death rates are significantly and positively correlated with subsequent entrepreneurship for US counties. To account for the potential endogeneity caused by forward-looking entrepreneurs, we utilize instruments based on historic mining activity. We find that the information spillover component of local establishment birth and death rates have significant positive effects on subsequent entrepreneurship and employment growth for US counties and metropolitan areas. With the help of these intruments, we show that establishment births have a positive and significant effect on future employment growth within all counties, and that in line with the information hypothesis, local establishment death rates have a similar positive effect within metropolitan counties.