Miracle-dz/UniFAR-FTUs huggingface dataset:
Transfer of knowledge from scientific research projects towards middle school scholars

This paper presents authors motivation and experience gained through creation of eLearning course named “GaN/SiC based High Electron Mobility Transistors for integrated microwave and power circuits” located on portal “eLearn central”. The main aim of the course is to present new technologies and concepts of HEMTs and is intended primarily for scholars at Middle schools. This paper shows that eLearning is an excellent tool for transfer of knowledge, research results and latest findings into the education process.
Hypervelocity Stars. III. The Space Density and Ejection History of Main-Sequence Stars from the Galactic Center

We report the discovery of three new unbound hypervelocity stars (HVSs), stars traveling with such extreme velocities that dynamical ejection from a massive black hole (MBH) is their only suggested origin. We also detect a population of possibly bound HVSs. The significant asymmetry we observe in the velocity distribution—we find 26 stars with vrf > 275 km s−1 and one star with vrf < − 275 km s−1—shows that HVSs must be short-lived, probably 3-4 M☉ main-sequence stars. Any population of hypervelocity post-main-sequence stars should contain stars falling back onto the Galaxy, contrary to the observations. The spatial distribution of HVSs also supports the main-sequence interpretation: longer lived 3 M☉ HVSs fill our survey volume; shorter lived 4 M☉ HVSs are missing at faint magnitudes. We infer that there are 96 ± 10 HVSs of mass 3-4 M☉ within R < 100 kpc, possibly enough HVSs to constrain ejection mechanisms and potential models. Depending on the mass function of HVSs, we predict that SEGUE may find up to 5-15 new HVSs. The travel times of our HVSs favor a continuous ejection process, although a ~120 Myr old burst of HVSs is also allowed.
The nature of evidence in empirical software engineering

In this paper, we argue that the gap between empirical software engineering and software engineering practice might be lessened if more attention were paid to two important aspects of evidence. The first is that evidence from case or field studies of actual software engineering practice are essential in order to understand and inform that practice. The second is that the nature of evidence should fit the purpose to which the evidence is going to be put. One type of evidence is not per se better than another. For example, the evidence required to persuade a manager to change an aspect of practice might be totally different in nature from that required to deepen the academic community's understanding of such practice.
Political Dynasties ( Preliminary-comments welcome )

We study political dynasties in the United States Congress since its inception in 1789. We document patterns in the evolution and pro le of political dynasties, study the self-perpetuation of political elites, and analyze the connection between political dynasties and political competition. We nd that the percentage of dynastic legislators is decreasing over time and that dynastic legislators have been signi cantly more prevalent in the South, the Senate and the Democratic party. While regional and party di¤erences have largely disappeared over time, the di¤erence across chambers has not. We document di¤erences and similarities in the pro le and political careers of dynastic politicians relative to the rest of legislators. We also nd that legislators that enjoy longer tenures are signi cantly more likely to have relatives entering Congress later. Using instrumental variables methods, we establish that this relationship is causal: a longer period in power increases the chance that a person may start (or continue) a political dynasty. Therefore, dynastic political power is self-perpetuating in that a positive exogenous shock to a persons political power has persistent e¤ects through posterior dynastic attainment. Finally, we nd that increases in political competition are associated with fewer dynastic legislators, suggesting that dynastic politicians may be less valued by voters. JEL codes: D70, J45, N41, N42.
Recognising faces in unseen modes: A tensor based approach

This paper addresses the limitation of current multilinear techniques (multilinear PCA, multilinear ICA) when applied to face recognition for handling faces in unseen illumination and viewpoints. We propose a new recognition method, exploiting the interaction of all the subspaces resulting from multilinear decomposition (for both multilinear PCA and ICA), to produce a new basis called multilinear-eigenmodes. This basis offers the flexibility to handle face images at unseen illumination or viewpoints. Experiments on benchmarked datasets yield superior performance in terms of both accuracy and computational cost.
Show me how you move and I will tell you who you are

Due to the emergence of geolocated applications, more and more mobility traces are generated on a daily basis and collected in the form of geolocated datasets. If an unauthorized entity can access this data, it can used it to infer personal information about the individuals whose movements are contained within these datasets, such as learning their home and place of work or even their social network, thus causing a privacy breach. In order to protect the privacy of individuals, a sanitization process, which adds uncertainty to the data and removes some sensible information, has to be performed. The global objective of GEPETO (for GEoPrivacy Enhancing TOolkit) is to provide researchers concerned with geo-privacy with means to evaluate various sanitization techniques and inference attacks on geolocated data. In this paper, we report on our preliminary experiments with GEPETO for comparing different clustering algorithms and heuristics that can be used as inference attacks, and evaluate their efficiency for the identification of point of interests, as well as their resilience to sanitization mechanisms such as sampling and perturbation.
Characterising stellar micro-variability for planetary transit searches

A method for simulating light curves containing stellar micro-variability for a range of spectral types and ages is presented. It is based on parameter-by-parameter scaling of a multi-component fit to the solar irradiance power spectrum (based on VIRGO/PMO6 data), and scaling laws derived from ground based observations of various stellar samples. A correlation is observed in the Sun between the amplitude of the power spectrum on long (weeks) timescales and the BBSO Ca  K-line index of chromospheric activity. On the basis of this evidence, the chromospheric activity level, predicted from rotation period and B − V colour estimates according to the relationship first introduced by Noyes (1983) and Noyes et al. (1984), is used to predict the variability power on weeks time scales. The rotation period is estimated on the basis of a fit to the distribution of rotation period versus B−V observed in the Hyades and the Skumanich (1972) spin-down law. The characteristic timescale of the variability is also scaled according to the rotation period. This model is used to estimate the impact of the target star spectral type and age on the detection capability of space based transit searches such as Eddington and Kepler. K stars are found to be the most promising targets, while the performance drops significantly for stars earlier than G and younger than 2.0 Gyr. Simulations also show that Eddington should detect terrestrial planets orbiting solar-age stars in most of the habitable zone for G2 types and all of it for K0 and K5 types.
Influence of Amino Acid Compositions and Peptide Profiles on Antioxidant Capacities of Two Protein Hydrolysates from Skipjack Tuna (Katsuwonus pelamis) Dark Muscle

Influence of amino acid compositions and peptide profiles on antioxidant capacities of two protein hydrolysates from skipjack tuna (Katsuwonus pelamis) dark muscle was investigated. Dark muscles from skipjack tuna were hydrolyzed using five separate proteases, including pepsin, trypsin, Neutrase, papain and Alcalase. Two hydrolysates, ATH and NTH, prepared using Alcalase and Neutrase, respectively, showed the strongest antioxidant capacities and were further fractionated using ultrafiltration and gel filtration chromatography. Two fractions, Fr.A3 and Fr.B2, isolated from ATH and NTH, respectively, showed strong radical scavenging activities toward 2,2-diphenyl-1-picrylhydrazyl radicals (EC50 1.08% ± 0.08% and 0.98% ± 0.07%), hydroxyl radicals (EC50 0.22% ± 0.03% and 0.48% ± 0.05%), and superoxide anion radicals (EC50 1.31% ± 0.11% and 1.56% ± 1.03%) and effectively inhibited lipid peroxidation. Eighteen peptides from Fr.A3 and 13 peptides from Fr.B2 were isolated by reversed-phase high performance liquid chromatography, and their amino acid sequences were determined. The elevated antioxidant activity of Fr.A3 might be due to its high content of hydrophobic and aromatic amino acid residues (181.1 and 469.9 residues/1000 residues, respectively), small molecular sizes (3–6 peptides), low molecular weights (524.78 kDa), and amino acid sequences (antioxidant score 6.11). This study confirmed that a smaller molecular size, the presence of hydrophobic and aromatic amino acid residues, and the amino acid sequences were the key factors that determined the antioxidant activities of the proteins, hydrolysates and peptides. The results also demonstrated that the derived hydrolysates and fractions from skipjack tuna (K. pelamis) dark muscles could prevent oxidative reactions and might be useful for food preservation and medicinal purposes.
Noncoherent Sequence Detection : a New Perspectivein Receiver

| In typical bandpass transmission systems, data detection must be performed in the absence of a phase reference. Noncoherent sequence detection represents the optimal solution of this problem, in the sense that it minimizes the probability of erroneously detecting the information sequence. This paper adopts this viewpoint and describes a class of recently-proposed approximate noncoherent sequence detectors which are based on searching properly deened trellis diagrams by means of a Viterbi algorithm. The proposed noncoherent receivers have a performance which approaches that of coherent detection for increasing receiver complexity, with losses of only a fraction of dB at aaordable complexity levels. They are robust to phase and/or frequency instabilities and very attractive for burst-mode transmission. Applications including noncoherent decoding of trellis coded modulations (TCM) and noncoherent detection of continuous phase modulations (CPM) are described.
A STUDY OF WEAR RATE ESTIMATION OF CASTING PARTS BY SUPPORT VECTOR MACHINE

Abrasive wear is one of the prime and mostly costly causes of secondary failure in the design and operation of mechanical machines and equipment. Wear limits must be known and measured to assure quality and durability of products by an experimental process to determine an optimum material composition. The development of wear monitoring systems for industrial processes is well recognised in the industry due to the continued demand for improved product quality and productivity. In this paper, a novel method of wear rate identification, based on a Support Vector Machine (SVM) is proposed. SVM is used to relate the wear rate and technological parameters of the wear resistant drip moulding. The SVM model for determining the wear rate of white iron casting with a low chromium content, was trained and tested by using the existing exploitation data from the Bor Flotation Plant, Serbia. The simulated results of wear prediction show that the accuracy rate of the SVM is 97%.
Impact of Triage: A Study of Mozilla and Gnome

Triage is of great interest in software projects because it has the potential to reduce developer effort by involving a broader base of non-developer contributors to filter and augment reported issues. Using issue tracking data and interviews with experienced contributors we investigate ways to quantify the impact of triagers on reducing the number of issues developers need to resolve in two OSS projects: Mozilla and Gnome. We find the primary impact of triagers to involve issue filtering, filling missing information, and determining the relevant product. While triagers were good at filtering invalid issues and as accurate as developers in filling in missing issue attributes, they had more difficulty accurately pinpointing the relevant product. We expect that this work will highlight the importance of issue triage in software projects and will help design further studies on understanding and improving triage practices.
OCLSP at SemEval-2016 Task 9: Multilayered LSTM as a Neural Semantic Dependency Parser

Semantic dependency parsing aims at extracting arcs and semantic role labels for all words in a sentence. In this paper, we propose a semantic dependency parser which is based on Long Short-term Memory and makes heavy use of embeddings of words and POS tags. We describe in detail the implementation of the neural parser, including preprocessing, postprocessing and various input features, and show that the neural parser performs close to the top system in the shared task and is very good at capturing non-local dependencies. We also discuss some issues re-lated to the parser and how to improve it.
Linux Implementation and Evaluation of a Cooperation Mechanism for Hybrid Wireless Networks

Communication over multiple hops, such as in hybrid wireless networks, can only work if the individual hops cooperate by forwarding packets from other hops. We present the Linux implementation of our previously proposed cooperation and accounting strategy for hybrid wireless networks called CASHnet. We describe our implementation as well as our testbed, where we performed different evaluations regarding introduced delay and packet processing time. We identify the limitations of our scheme in a real-life scenario and discuss possible improvements
Detecting finger movement through classification of electromyography signals for use in control of robots

This paper introduces a new method for surface electromyography (EMG) classification that it is used for controlling robot. EMG signals from individual's muscles are important items for controlling the prosthesis movements. For this purpose, two EMG electrodes located on the human forearm are utilized to collect the EMG data. Time and frequency sets such as Number of Zero Crossings (ZC), Autoregressive (AR) and wavelet coefficients are considered as features. On the other hand, Support Vector Machine (SVM) is used as a classification method. Results show accuracy of proposed approach is ≅ 80%. Finally to show the effectiveness and applicability of results, outputs of classification system are implemented on a fixed robot named Tabriz-Puma.
Walls of marginal stability and dyon spectrum in N = 4 supersymmetric string theories

: The spectrum of quarter BPS dyons in N = 4 supersymmetric string theories can change as the asymptotic moduli cross walls of marginal stability on which the dyon can break apart into a pair of half BPS states. In this paper we classify these marginal stability walls and examine this phenomenon in the context of exact dyon spectrum found in a class of N = 4 supersymmetric string theories. We argue that the dyon partition functions in diﬀerent domains separated by marginal stability walls are the same, but the choice of integration contour needed for extracting the degeneracies from the partition function diﬀer in these diﬀerent regions. We also ﬁnd that in the limit of large charges the change in the degeneracy is exponentially suppressed compared to the leading contribution. This is consistent with the fact that in the computation of black hole entropy we do not encounter any change as the asymptotic moduli ﬁelds move across the walls of marginal stability. Finally we carry out some tests of S-duality invariance in the theory.
Self-Organizing Sparse Codes

Sparse coding as applied to natural image patches learns Gabor-like components that resemble those found in the lower areas of the visual cortex. This biological motivation for sparse coding would also suggest that the learned receptive field elements be organized spatially by their response properties. However, the factorized prior in the original sparse coding model does not enforce this. We investigate ways of enforcing a topography over the learned codes in a locally self-organizing map approach.
Plasma Levels of Uric Acid, Urea and Creatinine in Diabetics Who Visit the Clinical Analysis Laboratory (CAn-Lab) at Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.

INTRODUCTION Diabetes mellitus is one of the most common metabolic diseases worldwide. This metabolic disorder contributes greatly to the significant proportion of the burden of renal damage and dysfunction. The aim of the study was to investigate the renal function of the diabetic patients who visit the Clinical Analysis Laboratory (CAn-Lab) at the Kwame Nkrumah University of Science and Technology (KNUST), Kumasi, Ghana. MATERIALS AND METHODS Demographic data as well as medical history were obtained through the administration of a questionnaire. Anthro-pometric measurements were taken and blood samples were analysed for glucose, uric acid, urea and creatinine. Data collected were analysed using SPSS version 16.0. RESULTS A total of 34 diabetic patients, aged from 40-77 y were recruited, 22 (64.7%) of them were males with mean age of 57.40 ± 11.8 y (±SD), while 12 (35.3%) were females with mean age of 58.17 ± 7.47 y. There was a statistically significant difference between the mean duration of the disease, as the females had longer duration, 12.50 ± 6.95 y, as compared to 7.32 ± 4.48 y in males (p=0.033). The mean plasma creatinine level in the females was 84.17 ± 54.73 μmol/l. In the diabetic population, there was a positive correlation between age and plasma creatinine level, (r=0.375, p=0.029). In the female diabetics, there was a positive correlation between fasting blood sugar (FBS) and the measured metabolic end products (r>0.5, p<0.05), a positive correlation between body mass index (BMI) and uric acid (r=0.576, p=0.005) and a positive correlation between BMI and FBS (r= 0.625, p= 0.030). CONCLUSION Our results on the parameters measured; show that the diabetic population was experiencing mild kidney dysfunction, compared to non-diabetic controls.
A team of presentation agents for edutainment

This paper presents the development of a presentation team that shows, explains and provides useful advices to children in the domain of "healthy nutrition". Agents of the team are endowed with different roles and personality traits so as to explain domain concepts from different viewpoints. In order to develop a system independent from the domain and the bodies of the agents, explanations and pieces of advice are generated and not statically scripted. The presentation plan is distributed to the various team actors and it is adapted to the characteristics of the interlocutor. To test the system and to evaluate the efficacy of the team in this domain we used a family of characters already present in the cartoon world: the Smurfies.
Augmented Medical Image Management

Thomas M. Lehmann, Henning Müller, Qi Tian, Nikolas P. Galatsanos, and Daniel Mlynek 1) Dept. of Medical Informatics, RWTH Aachen University of Technology, Aachen, Germany 2) Medical Informatics Service, University Hospitals of Geneva, Geneva, Switzerland 3) Inst. f. Infocomm Research, Agency for Science, Techn. and Research (A*Star), Singapore 4) Biom. Research Inst. , Found. for Research & Technology – HELLAS, Ioannina, Greece 5) Signal Processing Lab. 3, École Politech. Féd. de Lausanne (EPFL), Lausanne, Switzerland
Application of hybrid BCI and exergames for balance rehabilitation after stroke

This paper proposes the hybridization between two types of videogames (VG) that can be complementary in motor restoration tasks: the VG based on motion capture systems and the VG based on brain computer interfaces. This hybrid system allow the interaction inside of a VG created for the rehabilitation of standing balance in hemiparetic stroke patients through of movements and modulated mental intentions. The Brain Kinect Interface (BKI) is shown as a tool not only for improve the immersivity in serious VG for health, but as an instrumental arrangement for recording and analyzing of motion capture signals and electro-encephalographic (EEG) signals recorded from the low cost sensors in order to improve the objectivity in analyzing motor recovery process.
Human control of multiple robots in the RoboFlag simulation environment

Human performance and supervisory control strategies were examined using the RoboFlag simulation environment. In an emulation of a multiple unmanned vehicle mission, a single operator supervised a team of six robots using automated modes or "plays" as well as manual control. Simplified form of a delegation type interface, Playbook, was used. Effects on user performance of two factors, opponent "posture" (offensive, defensive, or mixed) and environmental uncertainty (visual range of the robots: low, medium, or high), were examined in 18 participants who completed five mission trials in each of the nine combinations of these factors. Objective performance measures and subjective assessments of mental workload and situation awareness were obtained from each participant. Opponent posture had a significant effect on the percent of missions successfully completed and the duration of the games. Both opponent posture and visual range also significantly affected the use of manual and automated control strategies. Operator strategy selection and implementation are discussed with regard to performance data and the design of supervisory control interfaces that support flexible task delegation.
Spatio-temporal GIS Design for Exploring Interactions of Human Activities

An effective representation of human activities in geographic information systems (GIS) presents a challenging research topic. Recent developments of information and communication technologies (ICT), which enable a virtual space and allow people to interact with others remotely, make such efforts even more difficult. This paper first extends the space–time path concept of Hägerstrand's time geography to represent both physical and virtual activities in a space–time context. A spatio-temporal GIS design which can accommodate the extended space–time path concept is proposed to support the exploration of spatio-temporal patterns of human interactions in physical and virtual spaces. Using time as a linear referencing system, a temporal dynamic segmentation method was developed to dynamically locate physical and virtual activities on space–time paths. The GIS design supports the identification of four different spatio-temporal patterns (i.e., co-existence, co-location in space, co-location in time, and no co-location in either space or time) of human interactions through their space–time paths. Using a hypothetical activity dataset, a prototype system is implemented as a three-dimensional GIS (i.e., two-dimensional space + one-dimensional time) in ArcGIS. The prototype system demonstrates the feasibility and potential of applying spatio-temporal GIS concepts to extend Hagerstrand's time–geographic framework for the representation and analysis of human interactions in both physical and virtual spaces. The proposed GIS design can be useful in such applications as understanding traffic congestion, tracking terrorist activities, and modeling the spread of infectious diseases.