Miracle-dz/UniFAR-FTUs huggingface dataset:
A Goal-oriented Analysis to Guide the Development of a User Feedback Ontology

Nowadays, developers and service providers put a lot of effort on collecting and analyzing user feedback with the purpose of improving their applications and services. This motivates the proposal of new tools to collect and analyze feedback. In our work, we develop a user feedback ontology, aimed at clarifying the concepts of this domain. For that, we follow a goal-oriented methodology to identify the competency questions that represent the ontology requirements. In this paper, we discuss an excerpt of the goal model used to guide the development of our ontology. Moreover, we present examples of competency questions identified through the analysis, and the corresponding fragment of the user feedback ontology.
Group delay features for speaker recognition

Group delay is proposed as an effective means of representing spectral phase information as a feature in speaker recognition. Robustness of group delay features is difficult to achieve, since the spiky nature of the group delay masks the fine structure of the group delay. In this paper, two features based on group delay are proposed by reducing the effect of spikes with two different approaches. The first is log compression, to address the masking effects of the spikes, and the second is to use a sub-band based approach, where masking is restricted within certain bands containing the spikes. The purpose of this paper is to introduce different types of group delay feature extraction methods. The two features are evaluated on the cellular NIST 2001 database.
The first outburst of the new magnetar candidate SGR 0501+4516

We report here on the outburst onset and evolution of the new soft gamma-ray repeater SGR 0501+4516. We monitored the new SGR with XMM- Newton starting on 2008 August 23, 1 day after the source became burst active, and continuing with four more observations in the following month, with the last one on 2008 September 30. Combining the data with the Swift X-ray telescope (Swift-XRT) and Suzaku data, we modelled the outburst decay over a 3-month period, and we found that the source flux decreased exponentially with a time-scale of t(c) = 23.8 d. In the first XMM-Newton observation, a large number of short X-ray bursts were observed, the rate of which decayed drastically in the following observations. We found large changes in the spectral and timing behaviour of the source during the first month of the outburst decay, with softening emission as the flux decayed, and the non-thermal soft X-ray spectral component fading faster than the thermal one. Almost simultaneously to our second and fourth XMM-Newton observations (on 2008 August 29 and September 2), we observed the source in the hard X-ray range with INTEGRAL, which clearly detected the source up to similar to 100 keV in the first pointing, while giving only upper limits during the second pointing, discovering a variable hard X-ray component fading in less than 10 days after the bursting activation. We performed a phase-coherent X-ray timing analysis over about 160 days starting with the burst activation and found evidence of a strong second derivative period component [(sic) = -1.6(4) x 10(-19) s s(-2)]. Thanks to the phase connection, we were able to study the phase-resolved spectral evolution of SGR 0501+ 4516 in great detail. We also report on the ROSAT quiescent source data, taken back in 1992 when the source exhibits a flux similar to 80 times lower than that measured during the outburst, and a rather soft, thermal spectrum.
Handling smart environment devices, data and services at the semantic level with the FI-WARE core platform

The development of IoT (Internet of Things) applications poses a number of scientific and technological challenges which stem from the characteristics of the IoT domain itself. These include the huge and increasing number of connected entities (devices, physical objects, people,.) populating the physical environment, the variety of their types which leads to heterogeneity of the data produced or consumed by those connected entities. In this paper we argue that semantic modeling takes up many of these challenges and explain how the core platform developed by the FI-WARE project supports IoT application developers. After a short introduction of the characteristics and requirements of IoT applications we identify the contribution of semantic technologies to address some of them. We describe the FI-WARE platform enablers which support these technologies and illustrate through a real application how these enablers help developers satisfy these requirements.
Exact null tachyons from RG flows

We construct exact 2d CFTs, corresponding to closed string tachyon and metric profiles invariant under shifts in a null coordinate, which can be constructed from any 2d renormalization group flow. These solutions satisfy first order equations of motion in the conjugate null coordinate. The direction along which the tachyon varies is identified precisely with the worldsheet scale, and the tachyon equations of motion are the RG flow equations.
An investigation of the relationship between psychosocial work factors and cognitive failures in nursing

Background and aims : The psychosocial work factors have a major impact on employees’ cognitive performance. The purpose of this study was to investigate the relationship between psychosocial work factors and cognitive failures among nurses. Methods : In this study, 300 nurses who worked in educational hospitals were selected by simple random sampling method. The questionnaires that used for data collection included: demographics information, COPSOQ and CFQ questionnaires. To analyze the relationship between variables, independent t-test, ANOVA, Pearson correlation coefficient and linear regression analysis were used. Results : There was a significant relationship between the majority of dimensions of psychosocial work factors such as role clarity, influence at work, job satisfaction, and insecurity at work, quantitative demands, emotional demands, total job demands and meaning of work with cognitive failures of nurses. Also, the dimensions of total job demands, meaning of work and influence at work with high and significant correlations had a good predictition of cognitive failure in nurses. Conclusion : According to the results, some of the psychosocial work factors affect on the rate of cognitive failures. Therefore, organizational interventions must be considered in order to control important psychosocial work factors. Further studies are needed to identify other factors affecting nurses’ cognitive failures.
Copepod feeding and reproduction in relation to phytoplankton development during the PeECE III mesocosm experiment

Abstract. Within the frame of the Pelagic Ecosystem CO2 Enrichment (PeECE III) experiment, reproduction and feeding of the copepod Calanus finmarchicus was monitored in relation to phytoplankton development in two mesocosms, at present 1× (350 μatm) and ca 3× present (1050 μatm) CO2 concentrations, respectively. Both mesocosms showed rapid phytoplankton growth after the initial nutrient additions and reached maximum chlorophyll (Chl) a concentrations around day 10. Flow-cytometry and specific pigment analysis (HPLC-CHEMTAX), showed that diatoms and prymnesiophyceae (Emiliania huxleyi (Ehux) and other nanoplankton) dominated the biomass. Feeding and egg production rates of C. finmarchicus developed similarly in both mesocosms, and were positively correlated with Chla, Ehux, diatom and prymnesiophyceae concentrations. Although the total number of copepod nauplii recruited during the experiment was similar in 1× and 3×, significantly less nauplii were recruited in 3× during the peak of the bloom compared to in 1×. We conclude that the algae responsible for the higher biomass in 3× during the peak of the bloom (diatoms and Ehux), may have been relatively inferior food for C. finmarchicus naupliar recruitment, possibly due to a high C:N ratio (>8). Nevertheless, the 3 fold increase in CO2 concentration did not show any clear overall effect on bulk phytoplankton or zooplankton development over the whole experiment, suggesting a more complex coupling between increased CO2 and the nutritional status of the system.
A SURVEY OF FACE RECOGNITION ON FEATURE EXTRACTION PROCESS OF DIMENSIONALITY REDUCTION TECHNIQUES

Face Recognition is one of the most successful chal lenging applications in the field of computer vision and pattern recognition. Generally there are two types of recognitions such as intrusive recogn ition means that the user aware about the recognition i.e . , Palm print recognition; the users have to place their palm in the scanner, where as face recognition is n on-i trusive, with out user cooperation it can able to recognize the person as authenticated person or not . The applications of face recognition are time attendance system, visitor management system and ac cess ontrol system, etc. the face recognition give s efficient performance under the controlled environm e t. But still we have the unsolved problems in rea l time applications. The dimensionality reduction is a most important task in the field of face recognit io . In this paper, it proposed all the recent emerging tec hniques of feature extraction process in the dimens ionality reduction.
Validation and User Evaluation of a Sensor-Based Method for Detecting Mobility-Related Activities in Older Adults

Regular physical activity is essential for older adults to stay healthy and independent. However, daily physical activity is generally low among older adults and mainly consists of activities such as standing and shuffling around indoors. Accurate measurement of this low-energy expenditure daily physical activity is crucial for stimulation of activity. The objective of this study was to assess the validity of a necklace-worn sensor-based method for detecting time-on-legs and daily life mobility related postures in older adults. In addition user opinion about the practical use of the sensor was evaluated. Twenty frail and non-frail older adults performed a standardized and free movement protocol in their own home. Results of the sensor-based method were compared to video observation. Sensitivity, specificity and overall agreement of sensor outcomes compared to video observation were calculated. Mobility was assessed based on time-on-legs. Further assessment included the categories standing, sitting, walking and lying. Time-on-legs based sensitivity, specificity and percentage agreement were good to excellent and comparable to laboratory outcomes in other studies. Category-based sensitivity, specificity and overall agreement were moderate to excellent. The necklace-worn sensor is considered an acceptable valid instrument for assessing home-based physical activity based upon time-on-legs in frail and non-frail older adults, but category-based assessment of gait and postures could be further developed.
A MFoM learning approach to robust multiclass multi-label text categorization

We propose a multiclass (MC) classification approach to text categorization (TC). To fully take advantage of both positive and negative training examples, a maximal figure-of-merit (MFoM) learning algorithm is introduced to train high performance MC classifiers. In contrast to conventional binary classification, the proposed MC scheme assigns a uniform score function to each category for each given test sample, and thus the classical Bayes decision rules can now be applied. Since all the MC MFoM classifiers are simultaneously trained, we expect them to be more robust and work better than the binary MFoM classifiers, which are trained separately and are known to give the best TC performance. Experimental results on the Reuters-21578 TC task indicate that the MC MFoM classifiers achieve a micro-averaging F1 value of 0.377, which is significantly better than 0.138, obtained with the binary MFoM classifiers, for the categories with less than 4 training samples. Furthermore, for all 90 categories, most with large training sizes, the MC MFoM classifiers give a micro-averaging F1 value of 0.888, better than 0.884, obtained with the binary MFoM classifiers.
Classical solutions in string field theory around the tachyon vacuum

In a previous paper [hep-th/0012251] we proposed a simple class of actions for string field theory around the tachyon vacuum. In this paper we search for classical solutions describing D-branes of different dimensions using the ansatz that the solutions factorize into the direct product of a matter state and a universal ghost state. We find closed form expressions for the matter state describing D-branes of all dimensions. For the space filling D25-brane the state is the matter part of the zero angle wedge state, the ``sliver'', built in [hep-th/0006240]. For the other D-brane solutions the matter states are constructed using a solution generating technique outlined in [hep-th/0008252]. The ratios of tensions of various D-branes, requiring evaluation of determinants of infinite dimensional matrices, are calculated numerically and are in very good agreement with the known results.
Single‐cell analysis of siRNA‐mediated gene silencing using multiparameter flow cytometry

Use of synthetic short interfering RNAs (siRNAs) to study gene function has been limited by an inability to selectively analyze subsets of cells in complex populations, low and variable transfection efficiencies, and semiquantitative assays for measuring protein down‐regulation. Intracellular flow cytometry can overcome these limitations by analyzing populations at the single‐cell level in a high‐throughput and quantitative fashion. Individual cells displaying a knockdown phenotype can be selectively interrogated for functional responses using multiparameter analysis.
A User Interface for the Construction of 3 D Active Shape Models

We present a graphical user interface which facilitates the definition of anatomical boundaries and landmarks for automated model-based segmentation and anal ysis using 3D Active Shape Models (ASMs). ASMs provide a statistically-based approach to automatic s egmentation which is completely general in terms of both imaging modalities and the anatomical objects of int erest. Further, the ASMguarantees an anatomically plausible result by incorporating a priori knowledge of the objects of interest. This approach is there fore well suited to the interpretation of medical images.
Full-Body Gait Reconstruction Using Covariance-Based Mapping Within a Realtime HMM-Based Framework

In this paper we propose a new HMM-based framework for the exploration of realtime gesture-to-gesture mapping strategies. This framework enables the realtime HMM-based recognition of a given gesture sequence from a subset of its dimensions, the covariancebased mapping of the gesture stylistics from this subset onto the remaining dimensions and the realtime synthesis of the remaining dimensions from their corresponding HMMs. This idea has been embedded into a proof-of-concept prototype that “reconstructs” the lower-body dimensions of a walking sequence from the upper-body gestures in realtime. In order to achieve this reconstruction, we adapt various machine learning tools from the speech processing research. Notably we have adapted the HTK toolkit to motion capture data and modified MAGE, a HTS-based library for reactive speech synthesis, to accommodate our use case. We have also adapted a covariancebased mapping strategy used in the articulatory inversion process of silent speech interfaces to the case of transferring stylistic information from the upperto the lower-body statistical models. The main achievement of this work is to show that this reconstruction process applies the inherent stylistics of the input gestures onto the synthesised motion thanks to the mapping function applied at the state level.
The effects of dietary fibre type on satiety-related hormones and voluntary food intake in dogs

Depending on type and inclusion level, dietary fibre may increase and maintain satiety and postpone the onset of hunger. This 7-week study evaluated the effect of fibre fermentability on physiological satiety-related metabolites and voluntary food intake (VFI) in dogs. Sixteen healthy adult dogs were fed a low-fermentable fibre (LFF) diet containing 8·5 % cellulose or a high-fermentable fibre (HFF) diet containing 8·5 % sugarbeet pulp and 2 % inulin. Large intestinal fibre degradation was evaluated by apparent faecal digestibility of nutrients and faecal SCFA and NH3 concentrations. Postprandial blood samples were obtained to determine postprandial plasma glucose, insulin, total peptide tyrosine–tyrosine (PYY), total glucagon-like peptide-1 (GLP-1) and total ghrelin concentrations. At the end of the study, the dogs were given a single meal of a dry dog food to determine VFI. Dogs fed the HFF diet had a significantly higher large intestinal fibre degradation and production of SCFA compared with the dogs fed the LFF diet. The HFF-fed dogs tended (P = 0·058) to show a lower VFI at the end of the study. No treatment effects were found for postprandial plasma glucose, PYY, GLP-1 and ghrelin responses. The concentrations of these metabolites could not be related to the observed difference in VFI. The inclusion of fermentable fibre in canine diets may contribute to the prevention or mitigation of obesity through its effects on satiety. The underlying mechanisms require further investigation.
PatchDroid: scalable third-party security patches for Android devices

Android is currently the largest mobile platform with around 750 million devices worldwide. Unfortunately, more than 30% of all devices contain publicly known security vulnerabilities and, in practice, cannot be updated through normal mechanisms since they are not longer supported by the manufacturer and mobile operator. This failure of traditional patch distribution systems has resulted in the creation of a large population of vulnerable mobile devices. In this paper, we present PatchDroid, a system to distribute and apply third-party security patches for Android. Our system is designed for device-independent patch creation, and uses in-memory patching techniques to address vulnerabilities in both native and managed code. We created a fully usable prototype of PatchDroid, including a number of patches for well-known vulnerabilities in Android devices. We evaluated our system on different devices from multiple manufacturers and show that we can effectively patch security vulnerabilities on Android devices without impacting performance or usability. Therefore, PatchDroid represents a realistic path towards dramatically reducing the number of exploitable Android devices in the wild.
Moderne Behandlungsverfahren der Varikose der unteren Extremität

Abstract Varicosis of the lower limb is a common disease that can lead to edema, trophic disturbances and skin ulcerations. In addition to the classic surgical procedure of crossectomy with stripping of the saphenous vein, a growing number of minimally invasive endoluminal treatment methods has been established over the past 15 years, offering a colorful array of procedures to the modern phlebologist. It is important to choose the optimal treatment option for each individual patient.
b-Type Dihydroorotate Dehydrogenase Is Purified as a H2O2-Forming NADH Oxidase from Bifidobacterium bifidum

ABSTRACT Our previous report showed the existence of microaerophilic Bifidobacterium species that can grow well under aerobic conditions rather than anoxic conditions in a liquid shaking culture. The difference in the aerobic growth properties between the O2-sensitive and microaerophilic species is due to the existence of a system to produce H2O2 in the growth medium. In this study, we purified and characterized the NADH oxidase that is considered to be a key enzyme in the production of H2O2. Bifidobacterium bifidum, an O2-sensitive bacterium and the type species of the genus Bifidobacterium, possessed one dominant active fraction of NADH oxidase and a minor active fraction of NAD(P)H oxidase activity detected in the first step of column chromatography for purification of the enzyme. The dominant active fraction was further purified and determined from its N-terminal sequence to be a homologue of b-type dihydroorotate dehydrogenase (DHOD), composed of PyrK (31 kDa) and PyrDb (34 kDa) subunits. The genes that encode PyrK and PryDb are tandemly located within an operon structure. The purified enzyme was found to be a heterotetramer showing the typical spectrum of a flavoprotein, and flavin mononucleotide and flavin adenine dinucleotide were identified as cofactors. The purified enzyme was characterized as the enzyme that catalyzes the DHOD reaction and also catalyzes a H2O2-forming NADH oxidase reaction in the presence of O2. The kinetic parameters suggested that the enzyme could be involved in H2O2 production in highly aerated environments.
A corpus-based study of Verb Phrase

Although considerable work exists on the subject of ellipsis resolution, there has been very little empirical, corpus-based work on it. We propose a system which will take free text and (i) detect instances of Verb Phrase ellipsis, (ii) identify their antecedents and (iii) resolve them, providing an end-to-end solution. For each of the steps, manually developed methods and machine learning techniques will be compared. The goal of the system is to be robust, accurate and domain-independent.
A wired router can eliminate 802.11 unfairness, but it's hard

As mobile computing becomes ubiquitous and airspace more congested, it is increasingly important to fairly distribute bandwidth between competing wireless devices in order to ensure predictable and satisfactory performance for end users. In prior work, we have proposed a cross-layer approach called Shaper [3, 4] that uses TCP and a central router rather than the 802.11 protocol to decide the outcome of bandwidth allocation. The key idea is to avoid airspace congestion from happening in the first place. Shaper is effective and also easy to deploy. However, its implementation faces many fundamentally difficult challenges. This paper details these challenges and possible solutions.
HT-RLS: High-Throughput Web Tool for Analysis of DNA Microarray Data Using RLS classifiers

Gene expression from DNA microarray data offers biologists and pathologists the possibility to deal with the problem of disease (e. g. cancer) diagnosis and prognosis from a quantitative point of view. Microarray data provide a snapshot of the molecular status of a sample of cells in a given tissue, returning the expression levels of thousands of genes simultaneously. Several mathematical methods from learning theory, such as Regularized Least Squares (RLS) classifiers or Support Vector Machines (SVM), have been extensively adopted to classify gene expression data. These methods can be useful to answer some relevant questions such as 1) what is the right amount of data to build an accurate classifier? 2) How many and which genes are correlated with a specific pathology? The computational analysis to statistically estimate the accuracy of the chosen models is particularly time consuming, burning several days of CPU time and without high-throughput or high- performance tools becomes practically unfeasible to obtain results in a reasonable time for biomedical community. We have implemented an independent, flexible and scalable platform, for a high-throughput large-scale microarray gene expression data analysis and classification, based on R tool for statistical computing. It integrates databases and computational intensive algorithms, based on RLS classifiers and a powerful web client for data training and graphical visualization of predicted results. Our platform provides statistically significant answers to the study of the gene expression by means of microarray data and supplying useful information to relevant questions in the diagnosis and prognosis of diseases in a reasonable time. The web resource is available free of charge for academic and non-profit institutions.