Miracle-dz/UniFAR-FTUs huggingface dataset:
Sell your experiences: a market mechanism based incentive for participatory sensing

This paper studies economic models of user participation incentive in participatory sensing applications. User participation is the most important element in participatory sensing applications for providing adequate level of service quality. However, incentive mechanism and its economic model for user participation have never been addressed so far in this research domain. In order to stimulate user participation, we design and evaluate a novel Reverse Auction based Dynamic Price (RADP) incentive mechanism, where users can sell their sensing data to a service provider with users' claimed bid prices. The proposed incentive mechanism focuses on minimizing and stabilizing incentive cost while maintaining adequate number of participants by preventing users from dropping out of participatory sensing applications. Compared with a Random Selection with Fixed Price (RSFP) incentive mechanism, the proposed mechanism not only reduces the incentive cost for retaining same number of participants by more than 60% but also improves the fairness of incentive distribution and social welfare. More importantly, RADP can remove burden of accurate pricing for user sensing data, the most difficult step in RSFP.
Utiliser le coefficient omega de McDonald à la place de l’alpha de Cronbach

Des chercheurs discutaient récemment de l’importance de rester à jour au sujet des plus récentes avancées en méthodes quantitatives. À ce titre, de nombreux auteurs ont exposé leur souhait de voir les chercheurs abandonner le populaire coefficient alpha de Cronbach. C’est dans une optique de diffusion et de vulgarisation que ce court article a comme objectif de présenter l’alternative qui semble la plus prometteuse pour mesurer la fidélité d’un test, le coefficient omega de McDonald, qui est basée sur l’analyse factorielle à un facteur commun.
Thinking together? Teacher autonomy, collaboration and professional development in Turkish lower secondary schools

This paper reports on a PhD research which investigates the concept of teacher autonomy in the context of Turkish lower secondary schools. The study uses the English language teaching profession as a focus. There are two primary aims of this study: to explore the extent to which teachers of English exercise autonomy in relation to teaching and assessment, professional development, school management and curriculum development; and to ascertain the factors influencing their exercise of autonomy in these areas. This paper discusses the professional development aspect of this study and, whilst drawing on the literature, argues that teacher autonomy can support meaningful professional development. The following four data collection methods were used: document analysis; classroom and school-wide observations; surveys, and interviews with teachers of English, head teachers, and educational administrators. The participants have reported a strong desire to exercise autonomy in relation to their own professional development. However, there are personal and structural influences; each reproducing the other.
Capturability-based analysis and control of legged locomotion, Part 2: Application to M2V2, a lower-body humanoid

This two-part paper discusses the analysis and control of legged locomotion in terms of N-step capturability: the ability of a legged system to come to a stop without falling by taking N or fewer steps. We consider this ability to be crucial to legged locomotion and a useful, yet not overly restrictive criterion for stability. Part 1 introduced the N-step capturability framework and showed how to obtain capture regions and control sequences for simplified gait models. In Part 2, we describe an algorithm that uses these results as approximations to control a humanoid robot. The main contributions of this part are (1) step location adjustment using the 1-step capture region, (2) novel instantaneous capture point control strategies, and 3) an experimental evaluation of the 1-step capturability margin. The presented algorithm was tested using M2V2, a 3D force-controlled bipedal robot with 12 actuated degrees of freedom in the legs, both in simulation and in physical experiments. The physical robot was able to recover from forward and sideways pushes of up to 21 Ns while balancing on one leg and stepping to regain balance. The simulated robot was able to recover from sideways pushes of up to 15 Ns while walking, and walked across randomly placed stepping stones.
Isosurface reconstruction with topology control

Extracting isosurfaces from volumetric datasets is an essential step for indirect volume rendering algorithms. For physically measured data, e.g. in medical imaging applications, one often introduces topological errors such as small handles that stem from measurement inaccuracy and cavities that are generated by tight folds of an organ. During isosurface extraction these measurement errors result in a surface whose genus is much higher than that of the actual surface. In many cases, however, the topological type of the object under consideration is known beforehand, e.g., the cortex of a human brain is always homeomorphic to a sphere. By using topology preserving morphological operators we can exploit this knowledge to gradually dilate an initial set of voxels with correct topology until it fits the target isosurface. This approach avoids the formation of handles and cavities and guarantees a topologically correct reconstruction of the object's surface.
Adaptive dynamic programming boundary control of uncertain coupled semi-linear parabolic PDE

This paper develops an adaptive dynamic programming (ADP) based near optimal boundary control of distributed parameter systems (DPS) governed by uncertain coupled semi-linear parabolic partial differential equations (PDE) under Neumann boundary control condition. First, Hamilton-Jacobi-Bellman (HJB) equation is formulated without any model reduction and the optimal control policy is derived. Subsequently, a novel identifier is developed to estimate the unknown nonlinearity in PDE dynamics. Accordingly, the sub-optimal control policy is obtained by forward-in-time estimation of the value functional using a neural network (NN) online approximator and the identifier. Adaptive tuning laws are proposed for learning the value functional online. Local ultimate boundedness (UB) of the closed-loop system is verified by using Lyapunov theory. The performance of proposed controller is verified via simulation on an unstable coupled diffusion reaction process.
Hybridization of Evolutionary Algorithms

Evolutionary algorithms are good general problem solver but suffer from a lack of domain specific knowledge. However, the problem specific knowledge can be added to evolutionary algorithms by hybridizing. Interestingly, all the elements of the evolutionary algorithms can be hybridized. In this chapter, the hybridization of the three elements of the evolutionary algorithms is discussed: the objective function, the survivor selection operator and the parameter settings. As an objective function, the existing heuristic function that construct the solution of the problem in traditional way is used. However, this function is embedded into the evolutionary algorithm that serves as a generator of new solutions. In addition, the objective function is improved by local search heuristics. The new neutral selection operator has been developed that is capable to deal with neutral solutions, i.e. solutions that have the different representation but expose the equal values of objective function. The aim of this operator is to directs the evolutionary search into a new undiscovered regions of the search space. To avoid of wrong setting of parameters that control the behavior of the evolutionary algorithm, the self-adaptation is used. Finally, such hybrid self-adaptive evolutionary algorithm is applied to the two real-world NP-hard problems: the graph 3-coloring and the optimization of markers in the clothing industry. Extensive experiments shown that these hybridization improves the results of the evolutionary algorithms a lot. Furthermore, the impact of the particular hybridizations is analyzed in details as well.
Towards Modeling of DataWeb Applications - A Requirement's Perspective

The web is more and more used as a platform for fullfledged, increasingly complex information systems, where a huge amount of change-intensive data is managed by underlying database systems. From a software engineering point of view, the development of such so called DataWeb applications requires proper modeling methods in order to ensure architectural soundness and maintainability. The goal of this paper is twofold. First, a framework of requirements, covering the design space of DataWeb modeling methods in terms of three orthogonal dimensions is suggested. Second, on the basis of this framework, eight representative modeling methods for DataWeb applications are surveyed and general shortcomings are identified pointing the way to nextgeneration modeling methods.
Time Critical Disinformation Influence Minimization in Online Social Networks

If a piece of disinformation released from a terrorist organization propagates on Twitter and this adversarial campaign is detected after a while, how emergence responders can wisely choose a set of source users to start the counter campaign to minimize the disruptive influence of disinformation in a short time? This practical problem is challenging and critical for authorities to make online social networks a more trustworthy source of information. In this work, we propose to study the time critical disinformation influence minimization problem in online social networks based on a continuous-time multiple campaign diffusion model. We show that the complexity of this optimization problem is NP-hard and provide a provable guaranteed approximation algorithm for this problem by proving several critical properties of the objective function. Experimental results on a sample of real online social network show that the proposed approximation algorithm outperforms various heuristics and the transmission temporal dynamics knowledge is vital for selecting the counter campaign source users, especially when the time window is small.
Case Report: Electronic Screening Improves Efficiency in Clinical Trial Recruitment

This study evaluated the performance of an electronic screening (E-screening) method and used it to recruit patients for the NIH sponsored ACCORD trial. Out of the 193 E-screened patients, 125 met the age criterion ("age>or=40"). For all of these 125 patients, the performance of E-screening was compared with investigator review. E-screening achieved a negative predictive accuracy of 100% (95% CI: 98-100%), a positive predictive accuracy of 13% (95% CI: 6-13%), a sensitivity of 100% (95% CI: 45-100%), and a specificity of 84% (95% CI: 82-84%). The method maximized the use of a patient database query (i.e., excluded ineligible patients with a 100% accuracy and automatically assembled patient information to facilitate manual review of only patients who were classified as "potentially eligible" by E-screening) and significantly reduced the screening burden associated with the ACCORD trial.
Patient specific predictions in the intensive care unit using a Bayesian ensemble

An intensive care unit mortality prediction model for the PhysioNet/Computing in Cardiology Challenge 2012 using a novel Bayesian ensemble learning algorithm is described. Methods: Data pre-processing was automatically performed based upon domain knowledge to remove artefacts and erroneous recordings, e.g. physiologically invalid entries and unit conversion errors. A range of diverse features was extracted from the original time series signals including standard statistical descriptors such as the minimum, maximum, median, first, last, and the number of values. A new Bayesian ensemble scheme comprising 500 weak learners was then developed to classify the data samples. Each weak learner was a decision tree of depth two, which randomly assigned an intercept and gradient to a randomly selected single feature. The parameters of the ensemble learner were determined using a custom Markov chain Monte Carlo sampler. Results: The model was trained using 4000 observations from the training set, and was evaluated by the organisers of the competition on two new datasets with 4000 observations each (set b and set c). The outcomes of the datasets were unavailable to the competitors. The competition was judged on two events by two scores. Score 1 was the minimum of the positive predictive value and sensitivity for binary model predictions, and the model achieved 0.5310 and 0.5353 on the unseen datasets. Score 2, a range-normalized Hosmer-Lemeshow C statistic, evaluated to 26.44 and 29.86. The model was re-developed using the updated data sets from phase 2 after the competition, and achieved a score 1 of 0.5374 and a score 2 of 18.20 on set c. Conclusion: The proposed prediction model performs favourably on both the provided and hidden data sets (set A and set B), and has the potential to be used effectively for patient-specific predictions.
Phase II trial of pemetrexed-based induction chemotherapy followed by concomitant chemoradiotherapy in previously irradiated patients with squamous cell carcinoma of the head and neck.

BACKGROUND Concurrent chemoreirradiation therapy (CRRT) offers a therapeutic option for patients with locoregionally recurrent squamous cell carcinoma of the head and neck (SCCHN). We hypothesized that response to induction chemotherapy (IC) would improve outcome and predict increased survival. PATIENTS AND METHODS Subjects with recurrent SCCHN not amenable to standard therapy were eligible. IC consisted of two 28-day cycles of gemcitabine and pemetrexed on days 1 and 14, followed by surgical resection, if appropriate, and/or CRRT consisting of carboplatin, pemetrexed, and single daily fractionated radiotherapy. RESULTS Thirty-five subjects were enrolled, 31 were assessable for response, with 11 responders [response rate = 35%; 95% confidence interval (CI) 19.2-54.6]. Among 24 subjects who started CRRT, 11 were assessable for radiographic response, 4 complete response, 2 partial response, and 5 progressive disease. Median progression-free survival and overall survival (OS) were 5.5 months (95% CI 3.6-8.3) and 9.5 months (95% CI 7.2-15.4), respectively. One-year OS was 43% (95% CI 26% to 58%). Subjects who responded to IC had improved survival (P = 0.02). Toxic effects included mucositis, dermatitis, neutropenia, infection, hemorrhage, dehydration, and pain. CONCLUSIONS The combination of pemetrexed plus gemcitabine was active and well tolerated in recurrent SCCHN. Response to IC may help stratify prognosis and offer an objective and dynamic metric in recurrent SCCHN patients being considered for CRRT.
Mutations in mitochondrial DNA causing tubulointerstitial kidney disease

Tubulointerstitial kidney disease is an important cause of progressive renal failure whose aetiology is incompletely understood. We analysed a large pedigree with maternally inherited tubulointerstitial kidney disease and identified a homoplasmic substitution in the control region of the mitochondrial genome (m.547A>T). While mutations in mtDNA coding sequence are a well recognised cause of disease affecting multiple organs, mutations in the control region have never been shown to cause disease. Strikingly, our patients did not have classical features of mitochondrial disease. Patient fibroblasts showed reduced levels of mitochondrial tRNAPhe, tRNALeu1 and reduced mitochondrial protein translation and respiration. Mitochondrial transfer demonstrated mitochondrial transmission of the defect and in vitro assays showed reduced activity of the heavy strand promoter. We also identified further kindreds with the same phenotype carrying a homoplasmic mutation in mitochondrial tRNAPhe (m.616T>C). Thus mutations in mitochondrial DNA can cause maternally inherited renal disease, likely mediated through reduced function of mitochondrial tRNAPhe.
Demonstrating Dynamic Ethernet Virtualization for Efficient Bandwidth Management

This paper presents a microscopic traffic estimation algorithm for smartphones by employing their built-in probes (such as GPS and acceleration sensors) to increase the accuracy of estimating the real-time traffic condition without significantly increasing these smart phones' energy consumption. In this approach, real-time traffic data is collected through cooperating smartphone users traveling on urban roads. A new reporting algorithm is provided on smartphone users’ side to minimize smartphone probes’ connection with the server. Based on these probes’ data, realtime traffic condition is estimated on the server side by applying the Kalman Filtering algorithm. Also the real-time traffic level of service (LOS) is estimated on urban roads. Simulation results show that the proposed algorithm requires less energy usage than existing methods without sacrificing the accuracy of the real-time traffic estimation. Keywords— Real-Time Traffic Estimation; Energy Saving; Kalman-Filtering; GPS
RESOLVED DUST EMISSION IN A QUASAR AT z = 3.65

We present submillimeter observations of the z= 3.653 quasar SDSS 160705+533558 together with data in the optical and infrared. The object is unusually bright in the far-IR and submillimeter with an IR luminosity of ∼1014 L☉. We ascribe this luminosity to a combination of active galactic nucleus (AGN) and starburst emission, with the starburst forming stars at a rate of a few thousand solar masses per year. Submillimeter Array imaging observations with a resolution ∼1″ show that the submillimeter (850 μm) emission is extended on scales of 10– 35 kpc and is offset from the optical position by ∼10 kpc. This morphology is dissimilar to that found in submillimeter galaxies, which are generally unresolved or marginally resolved on arcsecond scales, or submillimeter-luminous AGNs where the AGN lies at the peak of the submillimeter or molecular emission. The simplest explanation is that the object is in the early stages of a merger between a gas-rich galaxy, which hosts the starburst, and a gas-poor AGN-host galaxy, which is responsible for the quasar emission. It is also possible that jet-induced star formation might contribute to the unusual morphology.
Codebook-Based SDMA for Coexistence with Fixed Wireless Service

A portion of frequency band for International Mobile Telecommunications (IMT)-Advanced is currently allocated to Fixed Wireless Service (FWS) such as Fixed Service (FS), Fixed Satellite Service (FSS), or Fixed Wireless Access (FWA), which requires frequency sharing between both the systems. SDMA, due to its high throughput nature, is candidate for IMT-Advanced. This paper proposes a systematic design of a precoder codebook for SDMA sharing spectrum with existing FWS. Based on an estimated direction angle of a victim FWS system, an interfering transmitter adaptively constructs a codebook forming a transmit null in the direction angle while satisfying orthogonal beamforming constraint. We derive not only asymptotic throughput scaling laws, but also an upperbound on throughput loss to analyze performance loss of the proposed SDMA relative to the popular SDMA called per-user unitary rate control (PU2RC). Furthermore, we develop a method of evaluating protection distance in order to analyze the spectrum sharing performance of the proposed approach. The simulation results of protection distance confirm that the proposed SDMA efficiently shares spectrum with FWS systems by reducing protection distance to more than 66%. Although our proposed SDMA always has lower throughput compared to PU2RC in non-coexistence scenario, it offers an intriguing opportunity to reuse spectrum already allocated to FWS.
Stature: Does it really make a difference in match-play outcomes among professional tennis players?

Abstract The purpose of this study was to determine the effects of body height on match-play characteristics among professional tennis players participated in the 2017 Wimbledon Championships. Anthropometric features and 11 match-play statistics of 119 players (male = 60, female = 59) were obtained from the official web page of the tournament and/or from the ATP and WTA. They were divided into three consecutive sub-groups according to their heights. Results revealed that, regardless of gender, players in the tallest group had significantly produced higher speed on both first and second serve than the players in the other groups. Tallest male players exhibited significantly greater scores on the percentage of first serve points won and aces per set than the players in the shortest group. Conversely, players in the shortest groups achieved significantly more percentage of return point than the players in the tallest groups. Height was found to be significantly and positively correlated with both first and second serve speeds, and aces performed per set and significantly and negatively associated with percentage of return points won in both genders. These findings highlight the considerable advantages and disadvantages of stature on serve and return related match outcomes in a grass court tournament.
Synapses The Time Course of Signaling at Central Glutamatergic

Sci./Am.Physiol. Soc. ESSN: 1548-9221. Visit our website at http://www.the-aps.org/. American Physiological Society, 9650 Rockville Pike, Bethesda MD 20814-3991. © 2000 Int. Union Physiol. the physiological developments. It is published bimonthly in February, April, June, August, October, and December by (formerly published as News in Physiological Science) publishes brief review articles on major Physiology by gest on O cber 9, 2016 http://physioline.physiology. org/ D ow nladed fom
EEG Biometrics Using Visual Stimuli: A Longitudinal Study

In this letter, we investigate the permanence issue of electroencephalographic (EEG) signals, elicited by visual stimuli, for biometric recognition purposes. Specifically, we evaluate the discriminative capabilities of generic visually-evoked potentials (VEPs) and of visual event-related potentials (ERPs) associated to specific cognitive tasks. Furthermore, we analyze the permanence issue of the considered EEG traits by verifying the stability across time of the achievable recognition rates. Experimental tests performed on a longitudinal database, comprising EEG data taken from 50 subjects during 3 different sessions, give evidence of the presence of repeatable discriminative characteristics in the individuals' EEG activity.
Enriching an ontology with WordNet based on similarity measures

In this work we have used five semantic similarity measures and WordNet to add information to an ontology, the Common Procurement Vocabulary. The added information is used to automatically classify product descriptions according to the Common Procurement Vocabulary. It is shown that the similarity measure proposed by Leacock and Chodorow is the most suitable for this task, out of the five measures compared. Leacock-Chodorow shows average precision between 0.684 and 0.711 and recall between 0.845 and 0.977, depending on whether threshold is used or not. Baseline average precision peaks at 0.592.
Far-Ultraviolet Cooling Features of the Antlia Supernova Remnant

We present far-ultraviolet observations of the Antlia supernova remnant obtained with Far-Ultraviolet Imaging Spectrograph (FIMS, also called SPEAR). The strongest lines observed are C IV λλ1548, 1551 and C III λ977. The C IV emission of this mixed-morphology supernova remnant shows a clumpy distribution, and the line intensity is nearly constant with radius. The C III λ977 line, although too weak to be mapped over the whole remnant, is shown to vary radially. The line intensity peaks at about half the radius and drops at the edge of the remnant. Both the clumpy distribution of C IV and the rise in the C IV to C III ratio toward the edge suggest that central emission is from evaporating cloudlets rather than thermal conduction in a more uniform, dense medium.