Miracle-dz/UniFAR-FTUs huggingface dataset:
A Dynamic-alliance-based Adaptive Task Allocation Algorithm in Wireless Sensor Networks

In distributed sensor networks, which have limited resources, such as energy and storage, and work in a dynamic environment, the networks should effectively allocate some real-time tasks on those limited resources. Additionally, we should do our best to maximize the lifetime of wireless sensor networks (WSNs) and the accuracy of the results. Due to most of previous works focusing on static task allocation for WSNs and only a few works having paid attention to dynamic resource allocation for sensor networks, this paper present an effectively adaptive task allocation (EATA) in WSNs which applied dynamic alliance. Instead of being aid of manual adjustment, each node can autonomously adjust its parameters and state by means of EATA according to tracking the change of environment, such as energy depletion. By comparing with static task allocation, experiment results show that our scheme can save a great deal of energy and prolong the lifetime of the network.
Handwriting difficulties in primary school children: a search for underlying mechanisms.

OBJECTIVE This study investigated the contribution of perceptual-motor dysfunction and cognitive planning problems to the quality or speed of handwriting in children with handwriting problems (HWP). METHOD Twenty-nine children with HWP and 20 classroom peers attending regular schools (grade 2 and grade 3) were tested with regard to visual perception, visual-motor integration, fine motor coordination, and cognitive planning abilities. RESULTS The HWP group scored significantly lower on visual perception, visual-motor integration, fine motor coordination, and cognitive planning in comparison with classroom controls. Regression analyses showed that visual-motor integration was the only significant predictor for quality of handwriting in the HWP group, whereas fine motor coordination (i.e., unimanual dexterity) was the only significant predictor of quality of handwriting in the control group. CONCLUSIONS Results suggest that two different mechanisms underlie the quality of handwriting in children with and without handwriting problems. Poor quality of handwriting of children with HWP seems particularly related to a deficiency in visual-motor integration.
The Road to Prosperity: Saving Capitalism from Capitalists

The corrupt version of capitalism—when powerful corporations deliberately try to eliminate healthy competition to preserve their privileged position— generates economic inefficiencies and social injustice, thereby undermining political support for the free-market-based system; however, an ownership structure that is too dispersed is just as ineffective and dangerous. When ownership is correctly distributed, given the right dose of regulations and the alleviation of social costs, a political consensus in favor of markets can be achieved.
Differences and Discriminatory Power of Water Polo Game-Related Statistics in Men in International Championships and Their Relationship With the Phase of the Competition

Abstract Escalante, Y, Saavedra, JM, Tella, V, Mansilla, M, García-Hermoso, A, and Domínguez, AM. Differences and discriminatory power of water polo game-related statistics in men in international championships and their relationship with the phase of the competition. J Strength Cond Res 27(4): 893–901, 2013—The aims of this study were (a) to compare water polo game-related statistics by context (winning and losing teams) and phase (preliminary, classification, and semifinal/bronze medal/gold medal), and (b) identify characteristics that discriminate performances for each phase. The game-related statistics of the 230 men's matches played in World Championships (2007, 2009, and 2011) and European Championships (2008 and 2010) were analyzed. Differences between contexts (winning or losing teams) in each phase (preliminary, classification, and semifinal/bronze medal/gold medal) were determined using the chi-squared statistic, also calculating the effect sizes of the differences. A discriminant analysis was then performed after the sample-splitting method according to context (winning and losing teams) in each of the 3 phases. It was found that the game-related statistics differentiate the winning from the losing teams in each phase of an international championship. The differentiating variables are both offensive and defensive, including action shots, sprints, goalkeeper-blocked shots, and goalkeeper-blocked action shots. However, the number of discriminatory variables decreases as the phase becomes more demanding and the teams become more equally matched. The discriminant analysis showed the game-related statistics to discriminate performance in all phases (preliminary, classificatory, and semifinal/bronze medal/gold medal phase) with high percentages (91, 90, and 73%, respectively). Again, the model selected both defensive and offensive variables.
Research on Safety Monitoring System of Mine Based on Ad Hoc Technology

Coal mining exist very big risk for the special underground mine environment, This paper present a wireless sensor network monitoring and measure system based on ad hoc technology. The system completed the data acquisition of underground gas concentrations, air humidity, soil pressure and the data was rapidly transmitted to the ground terminals. So that the men on the ground can know the situation underground in time by these data to reduce the possibility of the occurrence of accident. The system solved the inconvenience of traditional wired networks and wireless networks. The overall construction and the hardware structure of sensor nodes were presented. The concrete design method of system's physical layer and medium access control (MAC) layer and network layer were given in this paper. Finally, the localization and notice of the system were explained.
MuRF-1 and p-GSK3β expression in muscle atrophy of liver cirrhosis

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Title Infection Spreading and Source Identification : A Hide andSeek Game

The goal of an infection source node (e.g., a rumor or computer virus source) in a network is to spread its infection to as many nodes as possible, while remaining hidden from the network administrator. On the other hand, the network administrator aims to identify the source node based on knowledge of which nodes have been infected. We model the infection spreading and source identification problem as a strategic game, where the infection source and the network administrator are the two players. As the Jordan center estimator is a minimax source estimator that has been shown to be robust in recent works, we assume that the network administrator utilizes a source estimation strategy that can probe any nodes within a given radius of the Jordan center. Given any estimation strategy, we design a best-response infection strategy for the source. Given any infection strategy, we design a best-response estimation strategy for the network administrator. We derive conditions under which a Nash equilibrium of the strategic game exists. Simulations in both synthetic and real-world networks demonstrate that our proposed infection strategy infects more nodes while maintaining the same safety margin between the true source node and the Jordan center source estimator.
Aspectual Differences with Syntactic Consequences : Argument Structure Alternations in L 2 Spanish

The aim of this article is to explore the L2 acquisition of argument structure by L1 English L2 Spanish learners. In particular, the study tries to determine whether L2ers are aware of the subtle aspectual distinctions that characterize different classes of psych-verbs and how these are encoded in their respective morphosyntactic configurations. The role of universal principles is considered as an essential element in this acquisition process that cannot be explained entirely in terms of L1 transfer, instruction or transparent extraction from the input. The organization of this article is the following: section 2 presents the theoretical issue under investigation, that is, the acquisition of argument structure. Section 2 describes the phenomenon studied in the current project, specifically, Spanish psych-verbs. Section 4 introduces the empirical study and section 5 offers some concluding remarks.
Timed Rise from Floor as a Predictor of Disease Progression in Duchenne Muscular Dystrophy: An Observational Study

Background The role of timed items, and more specifically, of the time to rise from the floor, has been reported as an early prognostic factor for disease progression and loss of ambulation. The aim of our study was to investigate the possible effect of the time to rise from the floor test on the changes observed on the 6MWT over 12 months in a cohort of ambulant Duchenne boys. Subjects and methods A total of 487 12-month data points were collected from 215 ambulant Duchenne boys. The age ranged between 5.0 and 20.0 years (mean 8.48 ±2.48 DS). Results The results of the time to rise from the floor at baseline ranged from 1.2 to 29.4 seconds in the boys who could perform the test. 49 patients were unable to perform the test at baseline and 87 at 12 month The 6MWT values ranged from 82 to 567 meters at baseline. 3 patients lost the ability to perform the 6mwt at 12 months. The correlation between time to rise from the floor and 6MWT at baseline was high (r = 0.6, p<0.01). Conclusions Both time to rise from the floor and baseline 6MWT were relevant for predicting 6MWT changes in the group above the age of 7 years, with no interaction between the two measures, as the impact of time to rise from the floor on 6MWT change was similar in the patients below and above 350 m. Our results suggest that, time to rise from the floor can be considered an additional important prognostic factor of 12 month changes on the 6MWT and, more generally, of disease progression.
Integrating Web-Scale OpenIE Extractions and Knowledge Bases with Entity Neighborhood Encoder

In this paper, we consider advancing webscale knowledge extraction and alignment by integrating OpenIE extractions in the form of (subject, predicate, object) triples with Knowledge Bases (KB). Traditional techniques from universal schema and schema mapping fall in two extremes: either they perform instancelevel inference relying on embedding for (subject, object) pairs, thus cannot handle entity pairs absent in any existing triples; or they perform predicate-level mapping and completely ignore evidence from individual entities – thus cannot achieve satisfying quality. In this paper, we propose an approach effective for new entity pairs – for each entity, we encode the rich information in its neighborhood in both KB and OpenIE extractions jointly in the same continuous latent space, and leverage this information in relation inference by exploring different methods of aggregation and attention. Extensive experiments with Freebase and IMDB show that this method not only significantly improves state-of-the-art for conventional OpenIE extractions like ReVerb, but also boosts the performance on OpenIE from semi-structured data, where new entity pairs are abundant and data are fairly sparse.
Ju l 2 01 7 On regular hypergraphs of high girth

We give lower bounds on the maximum possible girth of an runiform, d-regular hypergraph with at most n vertices, using the definition of a hypergraph cycle due to Berge. These differ from the trivial upper bound by an absolute constant factor (viz., by a factor of between 3/2 + o(1) and 2 + o(1)). We also define a random r-uniform ‘Cayley’ hypergraph on the symmetric group Sn which has girth Ω(n1/3) with high probability, in contrast to random regular r-uniform hypergraphs, which have constant girth with positive probability.
Galerkin-wavelet Modeling of Wave Propagation: Optimal Nite-diierence Stencil Design

In this paper we describe a method for design of optimal nite-diierence stencils for wave propagation problems using an intrinsically explicit Galerkin-wavelet formulation. The method enables an eecient choice of stencils optimal for a certain problem. We compare group velocity curves corresponding to stencils obtained by our choice of wavelet basis and traditional nite-diierence schemes. Generally there exist choices of stencils with superior characteristics compared to conventional nite-diierence stencils of the same size. Beside gain in accuracy, this leads to large computational savings.
Pressure on Judges: How the Budgeting System Can Impact on Judge’s Autonomy

Performance-based budgeting is a label that groups different budgeting models, developed in the New Public Management era, that link the funding to the performance of agencies. If European justice systems have been unresponsive to apply managerial techniques to courts, this is particularly true for modern budgeting techniques. Courts’ budgets have been, and still are in many cases, drafted only on historical costs, and, although important for the court functioning, it has been one of the most neglected subjects in court administration studies. In recent years, some countries have been developing new approaches to justice systems and court budgeting, using a “performance-based” budget perspective, which relates the courts’ budget to the efficiency results, setting specific performance targets. Although fundamental to ensure transparency, accountability, and proper resource allocation among courts, these approaches have an impact on judicial independence and autonomy, because they may put pressure on judges’ productivity and efficiency, to the detriment of quality. Building on two case studies, Finland and The Netherlands, this paper aims to analyze how, and to what extent, the “performance-based” budgeting system is influencing the functioning of courts and the autonomy of judges.
Ensemble Voting System for Multiclass protein fold Recognition

Protein structure classification is an important issue in understanding the associations between sequence and structure as well as possible functional and evolutionary relationships. Recently structural genomes initiatives and other high-throughput experiments have populated the biological databases at a rapid pace. In this paper, three types of classifiers, k nearest neighbors, class center and nearest neighbor and probabilistic neural networks and their homogenous ensemble for multiclass protein fold recognition problem are evaluated firstly, and then a heterogenous ensemble Voting System is designed for the same problem. The different features and/or their combinations extracted from the protein fold dataset are used in these classification models. The heterogenous classification results are then put into a voting system to get the final result. The experimental results show that the proposed method can improve prediction accuracy by 4%–10% on a benchmark dataset containing 27 SCOP folds.
Stochastic reliability evaluation of Sea-of-Tiles based on Double Gate controllable-polarity FETs

In this paper, we introduce Bayesian network methods in order to evaluate the reliability of an application mapped onto the Sea-of-Tiles fabric based on DGFET nano devices. By using these methods, we show some interesting features of this kind of fabric at the functional level; the reliability of one tile of this fabric does not depend on the values of the control and the polarity gates, the diagnosis of a defective tile is possible with the input vector G = H = 1 (or G = H = 0) and with an observation on the value of the output F. Nevertheless, these features should also be checked at the device level to be more accurate. Bayesian networks give us the opportunity to estimate the reliability of a whole application mapped onto this fabric and to test the defective behaviour of tiles before the place-and-route procedure.
Research on resources integration of urban logistics based on grid management

At present, urban logistics is a new academic field in the Logistics and a new subject in construction and management of city. Many cities take the development of modern logistics industry and the formulation of logistics plan in an important agenda. The theory and practice of urban logistics is still in its infancy in our country, and urban logistics is uncoordinated clearly. Besides, there is a shortage of the experience in urban logistics management. These factors have been obstacles in improving urban economic. Urban logistics resources sharing, collaborative work researches are still in its infancy stage, and there is no systematic theoretical support. Grid management refers to the operation of mechanisms of grid, which can achieve resources sharing, business collaboration and integration of unified services effectively within its borders. It can schedule the resources effectively, and has the merits such as simplicity, effectiveness, timeliness and the normative. It has the same goal with resources integration of urban logistics, so this paper makes the theory of grid management for the theory of study, makes a deep research about grid-based management system for urban logistics resources, and then demonstrates the advantages of it. Through the research, we can find the reasonable and scientific method for the resources integration of urban logistics in theory, and provide the proposed countermeasures for the optimization and application of resources integration of domestic urban logistics.
Cognitive behavioral therapy improves diet and body composition in overweight and obese adolescents 1 – 3

Background: Cognitive behavioral therapy (CBT) teaches behavioral and cognitive strategies that focus on achieving and maintaining lifestyle changes. Objective: We examined the effectiveness of a CBT program (CHOOSE HEALTH) for improving body composition, diet, and physical activity in overweight and obese adolescents. Design: Adolescents [16 male, 31 female; aged 14.5 1.6 y; body mass index (BMI; in kg/m) 30.9 4.2] were block-matched into 2 groups by age, sex, Tanner stage, BMI, and hip and waist circumferences and were randomly assigned to CBT or no treatment (control). CBT consisted of 10 weekly sessions, followed by 5 fortnightly telephone sessions. Results: Compared with the control, over 20 wk, CBT improved (significant group time interactions) BMI (CBT, 1.3 0.4; control, 0.3 0.3; P 0.007), weight (CBT, 1.9 1.0 kg; control, 3.8 0.9 kg; P 0.001), body fat (CBT, 1.5 0.9 kg; control, 2.3 1.0 kg; P 0.001), and abdominal fat (CBT, 124.0 46.9 g; control, 50.1 53.5 g; P 0.008). CBT showed a greater reduction in intake of sugared soft drinks as a percentage of total energy (CBT, 4.0 0.9%; control, 0.3 0.9%; P 0.005 for group time interaction), which was related to reductions in weight (r 0.48, P 0.04), BMI (r 0.53, P 0.02), and waist circumference (r 0.54, P 0.02). Physical activity did not change significantly. Conclusions: A 10-wk CBT program followed by 10 wk of fortnightly phone contact improved body composition in overweight and obese adolescents. Changes in soft drink consumption may have contributed to this benefit. Am J Clin Nutr 2008;87:1134–40.
A new forecasting approach for the hospitality industry

Purpose – This study aims to apply a new forecasting approach to improve predictions in the hospitality industry. To do so, the authors developed a multivariate setting that allows the incorporation of the cross-correlations in the evolution of tourist arrivals from visitor markets to a specific destination in neural network models. Design/methodology/approach – This multiple-input-multiple-output approach allows the generation of predictions for all visitor markets simultaneously. Official data of tourist arrivals to Catalonia (Spain) from 2001 to 2012 were used to generate forecasts for one, three and six months ahead with three different networks. Findings – The study revealed that multivariate architectures that take into account the connections between different markets may improve the predictive performance of neural networks. Additionally, the authors developed a new forecasting accuracy measure and found that radial basis function networks outperform the rest of the models. Research limitations/im.
WiFi architecture for traffic control using MIPv6

This paper focuses on the wireless communication aspect of the traffic control problem in urban areas. The IEEE 802.11b standard is used and an architecture is developed that produces zero packet loss at vehicle speeds of up to 60 Km/hr. A quantitative comparison is made between the Mobile Internet Protocol v4 (MIPv4) and MIPv6. It is shown that MIPv6 produces much less packet losses than MIPv4. Burst communication is then used to eliminate packet losses completely and the inter-packet and inter-burst intervals are determined. Finally, the effects of the router advertisement interval (RAI) and the mobility detection factor (MDF) are investigated and the optimum parameter values are determined in the context of the traffic control problem.
Psychometric Properties of the Job Engagement Scale: A Cross-Country Analysis

Job engagement is a motivational construct that refers to the willingness of employees to invest their physical, emotional and cognitive energies in their jobs in a holistic and simultaneous manner. Researchers use the Job Engagement Scale (JES) to measure the above conceptualization of job engagement, whose application is recent in job engagement research and is based largely on Western samples. In order to examine how job engagement is perceived in Asian contexts, this exploratory study aimed to provide a cross-country analysis of psychometric properties of the JES. We utilized data from earlier research of the first author, which were collected from 347 Pakistani and 498 Malaysian employees worked at diverse organizations. Psychometric analyses with reliability and validity estimations were performed using the Structural Equation Modeling. Results showed good internal consistency reliability, convergent validity and factorial validity of the JES for both Pakistani and Malaysian samples. However, psychometric properties of the JES for Pakistan outperformed those for Malaysia in all the estimations. Implications for future use of the JES and limitations of the study are discussed.
Sound Event Detection Based on Multi-States Transition Model

Deep Neural Network Hidden Markov Model (DNN-HMM) is a popular sound event modeling framework in recent years, which shows excellent performance in various sound event detection tasks. However, the traditional DNNHMM framework shows vast performance differences for the detection of different types of events. Multi-states transition topologies can efficiently solve the problem that the simple states transition topology cannot adapt to multiple types of sound events. We evaluated the performance on the DCASE2017 task2 development dataset, which shows that proposed DNN-HMM system outperforms the baseline. The error rate (ER) is 23% lower than the Multiple Layers Perception(MLP) system, and 14% lower than the traditional DNN-HMM system. Keywords—sound event detection; multi-states transition model; hidden Markov model; transfer learning; multi-task learning