Miracle-dz/UniFAR-FTUs huggingface dataset:
Speech enhancement using an MMSE spectral amplitude estimator based on a modulation domain Kalman filter with a Gamma prior

In this paper, we propose a minimum mean square error spectral estimator for clean speech spectral amplitudes that uses a Kalman filter to model the temporal dynamics of the spectral amplitudes in the modulation domain. Using a two-parameter Gamma distribution to model the prior distribution of the speech spectral amplitudes, we derive closed form expressions for the posterior mean and variance of the spectral amplitudes as well as for the associated update step of the Kalman filter. The performance of the proposed algorithm is evaluated on the TIMIT core test set using the perceptual evaluation of speech quality (PESQ) measure and segmental SNR measure and is shown to give a consistent improvement over a wide range of SNRs when compared to competitive algorithms.
A Mobility Prediction-Based Adaptive Data Gathering Protocol for Delay Tolerant Mobile Sensor Network

The basic operation of delay tolerant mobile sensor network (DTMSN) is for pervasive data gathering in networks with intermittent connectivity, where traditional data gathering methods can not be applied. In this paper, an efficient mobility prediction-based adaptive data gathering protocol (MPAD) based on the random waypoint mobility model tailored for DTMSN is proposed. In MPAD, a node independently makes decision to replicate messages and send them to the neighbor sensor nodes with a higher probability of meeting the sink node. MPAD consists of two components for data transmission and queue management. Data transmission makes decisions on when and where to transmit data messages according to the node delivery probability, and the queue management employs the message survival time to decide whether the message should be transmitted or dropped for minimizing the transmission overhead. Simulation results show that the proposed MPAD achieves the longer network lifetime and the higher message delivery ratio with the lower transmission overhead and data delivery delay than some other previous solutions designed for DTMSN, such as direct transmission, flooding and message fault tolerance-based data delivery protocol (FAD).
Where Are We Going? An Update on Assessment, Treatment, and Neurobiological Research in Dissociative Disorders as We Move Toward the DSM-5

This article provides an overview of the process of developing the 5th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) of the American Psychiatric Association with a focus on issues related to the trauma-related disorders, particularly the dissociative disorders (DD). We also discuss the highlights of research within the past 5 years in the assessment, treatment, and neurobiological basis of trauma disorders. Recent research shows that DD are associated with severe symptoms as well as a higher rate of utilization of mental health treatment compared with other psychiatric disorders. As a result, DD, like other complex posttraumatic disorders, exact a high economic as well as personal burden for patients and society. The latest research indicates that DD patients show a suboptimal response to standard exposure-based treatments for posttraumatic stress disorder as well as high levels of attrition from treatment. An emerging body of research on DD treatment, primarily of naturalistic and open trials, indicates that patients who receive specialized treatment that addresses their trauma-based, dissociative symptoms show improved functioning and reduced symptoms. Recent studies of the underlying neurobiological basis for dissociation support a model of excessive limbic inhibition in DD that is consistent with the phenomenology and clinical presentation of these patients. We are optimistic that the forthcoming DSM-5 will stimulate research on dissociation and the DD and suggest areas for future studies.
Cilk vs MPI: comparing two very different parallel programming styles

We measured the relative performance of two support systems for parallel programming on networks of workstations: Cilk - an extension of C with dataflow semantics - and MPI - a commonly used library for message passing. Although the two systems present significantly different parallel processing models, we attempted to code the benchmark problems in similar ways. The problems selected were matrix multiplication, travelling salesman problem, quick sort, Gaussian elimination, fast Fourier transform and finite differencing. We compared run times, speed-ups and coding efficiency as measured by lines of code in our implementations of the problems. Cilk showed a speed advantage when smaller numbers of large messages are transferred in a computation, enabling it to gain more from the underlying active messages implementation. Cilk code for algorithms with natural dataflow solutions was more compact, whereas algorithms which have simple iterative 'update-in-place' styles (Gaussian elimination and finite differencing) were more efficiently expressed when MPI was used
Adopted Yet Underused : A Technology Commitment Model of Post-Adoptive Behavior

Every year, individuals and organizations end up adopting (licensing) many competing software products. Yet, over time, much of the adopted software remains underused because users forgo the use of one for another adopted alternative. Although much research in the IS field has examined first-time IS adoption, less is known about post-adoption behavior, especially why users continue to use one software over competing alternatives. This paper proposes a comprehensive technology commitment model that explains why some IS technology products enjoy sustained use while others’ use are often discontinued. This paper forwards the notion that IS continuance may be best understood by investigating user commitment towards specific technologies, along with their corresponding antecedents. Besides examining the mediating role of technology commitment, the paper introduces technological inertia as a moderator on continuous use. The hypotheses are further tested to validate our model and draw important cues for explaining user commitment and continuous use of technologies.
A novel Bot detection algorithm based on API call correlation

In this paper, a novel Bot detection algorithm for Windows system based on API call correlation was proposed. the coefficient of product-moment correlation was utilized to calculate the correlation of different API calls. More other activities were correlated as well as keylogging. According to the characteristics of different Bot activities with API calls, the membership of different activities were calculated and integrated to form the fuzzy set of unknown process. Lattice Degree was applied to correlate the fuzzy set of unknown processed and the fuzzy sets of known processes. The type of the unknown processes was distinguished utilizing F Pattern Identification. Experimental results show that the algorithm can detect Bots with a high detection rate and can well distinguish between normal processes and Bot process with a low false positive degree.
A novel on-demand cognitive pilot channel enabling dynamic spectrum allocation

This paper addresses the implementation of the cognitive pilot channel (CPC), which has been recently proposed as a solution to assist the mobile reconfigurable and cognitive terminals in heterogeneous wireless scenarios with different access networks available and varying spectrum allocations. The paper describes the operation of the CPC and the different approaches existing in the literature depending on how it is mapped onto specific radio resources. Then, it focuses on the implementation of the CPC information delivery and proposes the use of an on-demand CPC, which requires a significantly lower bit rate than the broadcast approach to achieve similar performance.
A memetic algorithm for the low autocorrelation binary sequence problem

Finding binary sequences with low auto correlation is a very hard problem with many practical applications. In this paper we analyze several meta heuristic approaches to tackle the construction of this kind of sequences. We focus on two different local search strategies, steepest descent local search (SDLS) and tabu search (TS), and their use both as stand-alone techniques and embedded within a memetic algorithm (MA). Plain evolutionary algorithms are shown to perform worse than stand-alone local search strategies. However, a MA endowed with TS turns out to be a state-of-the-art algorithm: it consistently finds optimal sequences in considerably less time than previous approaches reported in the literature.
Document-based inter-organizational information exchange

In this paper, we present tour research work on document services for interstate e-government carried out in the FASME project. First, we depict the background for our research and we describe its basic challenges. Then we discuss the required services out of the perspective of inter-organizational document services and documentation issues. From the evaluations of our prototypical implementation with user groups, we may conclude that interstate e-government services are feasible and that life without personal documents in paper form may become possible.
Biomedical Communications: Purposes, Audiences, and Strategies

Biomedical Communications: Purposes, Audiences, and Strategies. Jon D. Miller and Linda G. Kimmel. San Diego, CA: Academic Press, 2001. 458 pp. $29.95 pbk. The American public is increasingly bombarded with media reports of promising new drugs and miraculous medical procedures. It also is besieged by information about the dangers allegedly associated with these and other biomedical advances. As a result of the high volume of information available from an increasing number of media outlets and sources, and despite the sometimes-conflicting information with which it is presented, the public believes itself to be knowledgeable about health issues and sound health practices. But, the authors warn, the facts reveal a grimmer reality: Although most Americans are interested in biomedical information, fewer than 20 percent of them actually meet the definition of biomedical literacy. Nor, the authors state, is there a correlation between the extent of an individual's interest and the level of an individual's literacy. Inaccuracies in online information and the excessive value some communicators place on television are among the many factors the authors address as contributing to the dismal picture. But, while they do not minimize the difficulties, the authors also do not oversimplify the requirements for overcoming them. Strategies, they stress, must differ depending upon the type of news that is being presented (biomedical or biotechnical, for example) and the audiences) to which it is being offered. They examine the extent to which differences in biomedical literacy can be linked to such factors as age, educational level, and racial and ethnic background, and the sources of information most used by and therefore most likely to improve the biomedical literacy of each audience. At a time when Americans believe themselves to be both empowered by knowledge and required by the realities of the health care system to play an increasingly active role in their own health care, the need to combat public ignorance is apparent. There is thus an urgent need for a book such as this one that analyzes how Americans find and filter information, and how communicators can improve that process, influence attitudes and policy, and alter behavior. The authors undertake their task diligently, building upon their research and that of others. Some of what they present is not surprising. It is not startling, for example, to read that the higher the level of education and exposure to science courses, the higher the level of biomedical literacy. …
Antidiabetic and Antioxidant Activity of Jackfruit ( Artocarpus Heterophyllus ) Extract

The Artocarpus heterophyllus (Jackfruit) is a species of tree of the mulberry family Moraceae. The plants of Artocarpus species have been used by traditional folk medicine in Indonesia. can be useful as anti-bacterial, antidiabetic, anti-inflammatory, antioxidant and anti-helmintics. The present study was aimed to evaluate antidiabetic and antioxidant activity of aqueous extract of Jackfruit. The antidiabetic activity were determined by inhibition of haemoglobin glycation method. Phytochemical constituent like ascorbic acid, -carotene and lycopene also determined. Antioxidant activity was measured by hydroxl radical and hydrogen peroxide scavenging activity, and chellating effect of ferrous iron. From the result of this study we can see the increasing of haemoglobin glycation concentration is followed by the increasing of jackfruit extracts concentration. From this study also we found the IC 50 of jackfruit exctracts is 56,43 %. The result of this study also showed that the extract of jackfruit has a phytochemical constituent with ascorbic acid is the highest, and followed by -carotene and lycopene. Jackfruit also has antioxidant activity. The highest antioxidant activity is scavenging hydroxyl radical activity and followed by scavenging hydrogen peroxide and chellating of ferrous iron. The result of this study suggest that the jackfruit extract potential as an diabetic agent.
Approximation of the Maximal Alpha -- Consensus Local Community Detection Problem in Complex Networks

The problem of community detection has received great attention by the complex networks researchers in the last decades. Although the notion of community does not actually have a unanimous accepted definition, it is generally admitted that it consists in a set of densely connected nodes. Moreover, density measures the strength of the relationships in the community. The need of these well connected and dense communities has led to the notion of α-consensus community. An α-consensus community, is a group of nodes where each member is connected to more than a proportion α of the other nodes. An α-consensus community is maximal if and only if adding a new node to the set breaks the rule. Consequently, an α-consensus community has a density greater than α. Existing methods for mining α-consensus communities generally assume that the network is entirely known and they try to detect all such consensus communities. In some cases, the network can be so large that each node can only have local information or one can be only interested in the α-consensus set of a particular node in the network. In this paper, we propose an efficient algorithm based on local optimizations to approximate the maximal α-consensus local community of a given node. The proposed method is evaluated experimentally on real and artificial complex networks in terms of quality, execution time and stability. It provides better results than the existing methods.
Old and new challenges in automatic plagiarism detection

Automatic methods of measuring similarity between program code and natural language text pairs have been used for many years to assist humans in detecting plagiarism. For example, over the past thirty years or so, a vast number of approaches have been proposed for detecting likely plagiarism between programs written by Computer Science students. However, more recently, approaches to identifying similarities between natural language texts have been addressed, but given the ambiguity and complexity of natural over program languages, this task is very difficult. Automatic detection is gaining further interest from both the academic and commercial worlds given the ease with which texts can now be found, copied and rewritten. Following the recent increase in the popularity of on-line services offering plagiarism detection services and the increased publicity surrounding cases of plagiarism in academia and industry, this paper explores the nature of the plagiarism problem, and in particular summarise the approaches used so far for its detection. I focus on plagiarism detection in natural language, and discuss a number of methods I have used to measure text reuse. I end by suggesting a number of recommendations for further work in the field of automatic plagiarism detection.
Development of a cost‐efficient novel method for rapid, concurrent genotyping of five common single nucleotide polymorphisms of the brain derived neurotrophic factor (BDNF) gene by tetra‐primer amplification refractory mutation system

Brain derived neurotrophic factor (BDNF) is a molecular trophic factor that plays a key role in neuronal survival and plasticity. Single nucleotide polymorphisms (SNPs) of the BDNF gene have been associated with specific phenotypic traits in a large number of neuropsychiatric disorders and the response to psychotherapeutic medications in patient populations. Nevertheless, due to study differences and occasionally contrasting findings, substantial further research is required to understand in better detail the association between specific BDNF SNPs and these psychiatric disorders. While considerable progress has been made recently in developing advanced genotyping platforms of SNPs, many high‐throughput probe‐ or array‐based detection methods currently available are limited by high costs, slow processing times or access to advanced instrumentation. The polymerase chain reaction (PCR)‐based, tetra‐primer amplification refractory mutation system (T‐ARMS) method is a potential alternative technique for detecting SNP genotypes efficiently, quickly, easily, and cheaply. As a tool in psychopathology research, T‐ARMS was shown to be capable of detecting five common SNPs in the BDNF gene (rs6265, rs988748, rs11030104, 11757G/C and rs7103411), which are all SNPs with previously demonstrated clinical relevance to schizophrenia and depression. The present technique therefore represents a suitable protocol for many research laboratories to study the genetic correlates of BDNF in psychiatric disorders. Copyright Copyright © 2015 John Wiley & Sons, Ltd.
Vibrational computations beyond the harmonic approximation: Performances of the B3LYP density functional for semirigid molecules

The performances of the B3LYP density functional in the computation of harmonic and anharmonic frequencies were tested using 14 standard basis sets of double and triple zeta quality for a set of semirigid molecules containing from 4 to 12 atoms. The quality of the results is assessed by comparison with the most reliable computations available in the literature. The study reveals that the relatively cheap 6‐31+G(d,p) basis set performs a very good job for harmonic frequency calculations and that B3LYP anharmonicities are in close agreement with the reference values irrespective of the basis set used. On these grounds “hybrid force fields” are proposed to achieve the best compromise between computer time and quality of the results. © 2005 Wiley Periodicals, Inc. J Comput Chem 26: 384–388, 2005
Association between Global Life Satisfaction and Self-Rated Oral Health Conditions among Adolescents in Lithuania

Background: This study aims to explore the extent to which the perceived oral conditions predict adolescent global life satisfaction (GLS); Methods: The sample in a cross-sectional survey consisted of 1510 Lithuanian adolescents (41.7% boys) aged 11–18. The survey was conducted by means of self-report questionnaires that were administrated in school classrooms ensuring confidentiality and anonymity of the participants. The schoolchildren rated their GLS and answered the questions about perceptions of their oral health. The relationship between GLS and oral health variables was estimated using unadjusted and adjusted binary logistic regression and nonparametric correlation analyses; Results: The research showed that the majority of adolescents rated their GLS highly; however, girls, older adolescents and adolescents from less affluent families were less likely to report high scores. GLS was significantly associated with subjective overall oral health assessment. The odds of reporting low GLS were 50% higher for adolescents with good oral health (OR = 1.51; p < 0.001; 95% CI = 1.18–1.93), and two and half time as higher for adolescents with perceived fair/poor oral health (OR = 2.78; p < 0.001; 95% CI = 1.72–4.50) compared to adolescents with subjectively excellent/very good oral health. Nonparametric correlations indicated lower GLS to be significantly associated with higher scores of Child Perceptions Questionnaire (𝜌 = −0.17/−0.30; p < 0.01); Conclusions: Adolescents with oral health impairments more likely to report lower GLS, regardless of their gender and age.
In vivo accumulation of 8-hydroxy-2'-deoxyguanosine in DNA correlates with release of reactive oxygen species in Fanconi's anaemia families.

The present study was aimed at verifying the occurrence, if any, of in vivo oxidative DNA damage in FA homozygotes, their parents and siblings. 8-Hydroxy-2'-deoxyguanosine (8-OHdG) was measured, by HPLC/EC, in DNA from circulating blood leucocytes from FA homozygotes and their relatives and compared with a group of paediatric and adult healthy subjects. The population studied consisted of: (i) 15 FA homozygotes; (ii) 24 FA heterozygotes; (iii) 11 siblings. The 8-OHdG level in FA homozygotes was significantly higher with respect to age-matched controls, with a mean level of 33.3 +/- 6.8 (mean +/- SE) and 3.9 +/- 0.26 8-OHdG/10(5) dG respectively. The FA parents (heterozygotes) also displayed higher 8-OHdG levels relative to controls. The release of hydroxyl (.OH) and . OH-like radicals from leucocytes was determined by luminol-dependent chemiluminescence (LDCL) in a subgroup of FA homo- and heterozygotes, showing a very large in vivo formation of non-superoxide radicals. Chromosomal instability was also measured in the FA population. When relating either 8-OHdG or LDCL levels to spontaneous or diepoxybutane-induced chromosomal instability (S-CI and DEB-CI respectively), a significant correlation was observed between the 8-OHdG, LDCL and S-CI data. Within families a positive association was found between 8-OHdG levels in homozygotes and their related heterozygotes, suggesting segregation of the genetic defect(s) underlying the abnormal oxidative metabolism. The present study provides evidence for an in vivo pro-oxidant state in FA, in terms of excess formation of . OH and . OH-like radicals, and of DNA hydroxyl adducts. This finding appears to be shared by homozygotes and, to a lesser extent, by heterozygotes.
Hierarchical wavelet modelling of environmental sensor data

Motivated by the need to smooth and to summarize multiple simultaneous time series arising from networks of environmental monitors, we propose a hierarchical wavelet model for which estimation of hyperparameters can be performed by marginal maximum likelihood. The result is an empirical Bayes thresholding procedure whose results improve on those of wavethresh in terms of mean square error. We apply the approach to data from the SensorScope environmental modelling system, and briefly discuss issues that arise concerning variance estimation in this context.
Design and characterization of the EP-Face connector

We present the EP-Face connector, a novel connector for hybrid chain-lattice type modular robots that is highstrength (88.4N), compact, fast, power efficient, and robust to position errors. The connector consists of an array of electro-permanent magnets (EP magnets) embedded in a planar face. EP magnets are solid-state magnets that can be turned on and off and require power only when changing state. In this paper, we present the design of the connector, manufacturing process, detailed experimental characterization of the connector strength under different loading conditions, and compare its performance to existing magnetic and mechanical connectors. We also illustrate the functional benefits of the EPFace by demonstrating reconfiguration with the SMORES-EP robot.