Miracle-dz/UniFAR-FTUs huggingface dataset:
MOTIVATION DIFFERENCES ON DOING SPORTS ACTIVELY AT THE DEPARTMENT OF PHYSICAL EDUCATION AND SPORTS TEACHER IN ACCORDANCE WITH THEIR GRADE LEVELS

The purpose of the present research is examining the differences between motivations of Physical Education and Sports (PES) Teaching Department students, who actively do sports in team sports and individual sports branches, in accordance with their grade levels. The participants of the present research are female (n=199) and male (n=344) the total of 543 athletes with age average of 21,25 ±2,66, who study at PES Teaching Departments of Ege and Uludag Universities and do different branches of sports. Sport Motivation Scale (SMS) developed by Pelletier et al. (1995) and adapted for Turkish athletes and tested for reliability and validity by Kazak (2004) was used to collect data. According to data collected from the participants, there are statistically significant differences between different grade levels in terms of “intrinsic motivation” (p<.05) and “intrinsic motivation to experience stimulation”, which is a sub-dimension of intrinsic motivation (p<.01) values. Fourth grade students have the highest average of intrinsic motivation while second grade students have the lowest, and first grade students have the highest level of intrinsic motivation to experience stimulation, while second grade students have the lowest average. According to the data related to grade levels by gender, the variations among female students in terms of intrinsic motivation to experience stimulation aren’t statistically significant, while the variations among male participants in terms of intrinsic motivation to experience stimulation and “amotivation” values are statistically significant (p<.05). Among the male participants, fourth grade students have the highest intrinsic motivation to experience stimulation average, while second graders have the lowest; and second grade students have the highest average for amotivation while the third graders have the lowest average for the related value. Data analyses were conducted on SPSS 17.0, and the variations in motivation by grade levels were tested with Mann-Whitney U and Kruskal Wallis tests. Article visualizations:
A Generalization of the Classic Combination Rules to DSm Hyper-power Sets

In this article, the author generalizes Dempster's rule, Yager's rule, and Dubois-Prade's rule for belief functions combination in order to be applica- ble to hyper-power sets according to the Dezert-Smarandache (DSm) Theory. A comparison of the rules with the DSm rule of combination is further presented.
Neural correlates and serotonergic modulation of behavioural inhibition and reward in healthy and antisocial individuals

Individuals with antisocial personality disorder (ASPD) are impulsive and show impairment in reinforcement processing. There is increasing evidence for a neurobiological basis of psychopathy, which shares some of the characteristics of ASPD, but research on the neuronal correlates of neuropsychological processes in ASPD remains limited. Furthermore, no research has examined the effects of serotonergic manipulation on brain activations in antisocial groups. In this study, 25 male participants with ASPD (mean age 42.1) and 32 male control participants (mean age 30.5; 25 participants providing usable scans) were randomly allocated to receive the 5-HT2C-agonist mCPP or placebo. Participants were scanned using functional magnetic resonance imaging (fMRI) during a behavioural inhibition (Go/NoGo) and a reward task. In comparison to healthy controls the ASPD group showed reduced task related activations in the dorsolateral prefrontal cortex (DLPFC) but increased signal in the pre/subgenual anterior cingulate cortex (ACC) in the Go/No-Go task and increased activation in OFC in the reward task. mCPP modulated brain responses in both tasks in the whole group. Interactions between group and drug occured in bilateral OFC, caudate and ventral pallidum during the reward task but no significant interactions were found in the Go/No-Go task. This suggests that ASPD involves altered serotonin modulation of reward, but not motor inhibition pathways. These findings suggest that ASPD involves altered DLPFC, ACC and OFC function. Altered serotonergic modulation of reward pathways seen in the ASPD group raises the possibility that targeting serotonin systems may be therapeutic. 2009 Elsevier Ltd. All rights reserved.
Sustained Effects of Acupuncture Stimulation Investigated with Centrality Mapping Analysis

Acupuncture can have instant and sustained effects, however, its mechanisms of action are still unclear. Here, we investigated the sustained effect of acupuncture by evaluating centrality changes in resting-state functional magnetic resonance imaging after manually stimulating the acupuncture point ST36 at the lower leg or two control point locations (CP1 same dermatome, CP2 different dermatome). Data from a previously published experiment evaluating instant BOLD effects and S2-seed-based resting state connectivity was re-analyzed using eigenvector centrality mapping and degree centrality mapping. These data-driven methods might add new insights into sustained acupuncture effects on both global and local inter-region connectivity (centrality) by evaluating the summary of connections of every voxel. We found higher centrality in parahippocampal gyrus and middle temporal gyrus after ST36 stimulation in comparison to the two control points. These regions are positively correlated to major hubs of the default mode network, which might be the primary network affected by chronic pain. The stronger integration of both regions within the whole-brain connectome after stimulation of ST36 might be a potential contributor to pain modulation by acupuncture. These findings highlight centrality mapping as a valuable analysis for future imaging studies investigating clinically relevant outcomes associated with physiological response to acupuncture stimulation. Clinical trial registration: NCT01079689, ClinicalTrials.gov.
Simulation-based planning in support of multi-agent scenarios

Whenever a simulation involves multiple interacting intelligent objects, called agents, there is the issue of how to code the decision making procedures that drive the agents. The usual method of encoding decision-making procedures has been to use operator or rule-based models, representing the decision making intelligence of the coordinator (i.e., commander on a battleeeld). If the purpose of the simulation is to precisely emulate a particular coordinator's intelligence, then such rule-based models may often be most appropriate. However, the goal is often to win the engagement or have the agents perform a task to the satisfaction of an optimal condition. In these cases, we have created a methodology, Simulation-Based Planning, that embeds one simulation inside another. The embedded simulation simulates the actions of agents and intentions of coordinators before committing to a plan. Plan alternatives are generated based on discrete paths through spatial regions of a domain, while speciic optimal plans are generated through the use of experimental design and simulation. We have found that, through simulation-based planning, near-optimal plans can be constructed by using simulation, in addition to using simulation once a plan has been adopted. In the case of semi-automated force (SAFOR) development, this involves embedding the simulation-based planner inside the computer generated force simulation. These results point to extensions for SBP beyond the military domain.
Part-based Isolated 3-D Object Recognition through Next View Planning using Inner Camera Invariants

A single view of an object may not contain suÆcient features to recognize it unambiguously. Further, the entire object may not t in the camera's eld of view. This paper presents a new on-line recognition scheme for the recognition and pose estimation of an isolated 3-D object. Our approach is independent of the internal parameters of the camera. The scheme uses a probabilistic reasoning framework for recognition and planning. Our knowledge representation scheme encodes part-based information about objects as well as the uncertainty in the recognition process. This is used both in the probability calculations as well as in planning the next view.
Performance Measurements Using a Sub-Micronewton Resolution Thrust Stand ∗

A sub-micronewton level thrust stand is used to evaluate the performance of five different microthrusters. Using a torsional balance design, the JPL microthrust stand (µTS) is capable of measuring steady-state thrust as low as 1 µN with sub-micronewton resolution and an impulse as low as 1 µNs with sub-micronewton-second resolution. The µTS can support a test object with a mass as large as 10 kg while supplying multiple diagnostic, power, and propellant lines to the thruster. The thrust or impulse is measured by monitoring the position of the thrust arm and using a calibrated dynamic model that will be presented in this paper. The performances of a vacuum arc thruster (VAT), gas-fed pulsed plasma thruster (GFPPT), indium field emission electric propulsion thruster (In-FEEP), vaporizing liquid microthruster (VLM), and micro-cold gas thruster have been measured using this test stand to validate its accuracy and precision.
A nonconvex penalization algorithm with automatic choice of the regularization parameter in sparse imaging

This paper introduces an efficient method for solving nonconvex penalized minimization problems. The topic is relevant in many imaging problems characterized by sparse data. The proposed method originates from the iterative reweighting l1 scheme, modified by the automatic update of the regularization parameter on the basis of the behavior of the objective function. Besides proving the convergence of the method, a modified algorithm is obtained and the performance is tested on two different sparse imaging problems. The proposed method can be viewed as a general framework which can be adapted to different one-parameter nonconvex penalty functions and applied to problems characterized by sparse data.
A Review of Coding Standards and related

Coding standards have been around for many years and have been subject to some debate over their value. This paper attempts to examine what that value might be to programmers through seeing what others have learned or thought about them and some analysis of some specific standards and how they impact programming in given languages. We ultimately see that the direction of where we are going in software development practices will create a need for standards more than ever before. Using standards alone is not enough. They must be used appropriately.
Application of Bayesian hierarchical prior modeling to sparse channel estimation

Existing methods for sparse channel estimation typically provide an estimate computed as the solution maximizing an objective function defined as the sum of the log-likelihood function and a penalization term proportional to the ℓ1-norm of the parameter of interest. However, other penalization terms have proven to have strong sparsity-inducing properties. In this work, we design pilot-assisted channel estimators for OFDM wireless receivers within the framework of sparse Bayesian learning by defining hierarchical Bayesian prior models that lead to sparsity-inducing penalization terms. The estimators result as an application of the variational message-passing algorithm on the factor graph representing the signal model extended with the hierarchical prior models. Numerical results demonstrate the superior performance of our channel estimators as compared to traditional and state-of-the-art sparse methods.
Non-Commutative Topology for Curved Quantum Causality

A quantum causal topology is presented. This is modeled after a non-commutative scheme type of theory for the curved finitary spacetime sheaves of the non-abelian incidence Rota algebras that represent `gravitational quantum causal sets'. The finitary spacetime primitive algebra scheme structures for quantum causal sets proposed here are interpreted as the kinematics of a curved and reticular local quantum causality. Dynamics for quantum causal sets is then represented by appropriate scheme morphisms, thus it has a purely categorical description that is manifestly `gauge-independent'. Hence, a schematic version of the Principle of General Covariance of General Relativity is formulated for the dynamically variable quantum causal sets. We compare our non-commutative scheme-theoretic curved quantum causal topology with some recent $C^{*}$-quantale models for non-abelian generalizations of classical commutative topological spaces or locales, as well as with some relevant recent results obtained from applying sheaf and topos-theoretic ideas to quantum logic proper. Motivated by the latter, we organize our finitary spacetime primitive algebra schemes of curved quantum causal sets into a topos-like structure, coined `quantum topos', and argue that it is a sound model of a structure that Selesnick has anticipated to underlie Finkelstein's reticular and curved quantum causal net. At the end we conjecture that the fundamental quantum time-asymmetry that Penrose has expected to be the main characteristic of the elusive `true quantum gravity' is possibly of a kinematical or structural rather than of a dynamical character, and we also discuss the possibility of a unified description of quantum logic and quantum gravity in quantum topos-theoretic terms.
Speech enhancement using β-divergence based NMF with update bases

In this paper, combination of statistical model based approach and Non-negative matrix factorization (NMF) based approach with on-line update of speech and noise bases for speech enhancement is proposed. Template based approaches are more robust and performs better to non-stationary noises compared to the statistical model based approaches. However, the template based approach is dependent on a priori information. Combining the approaches avoids the drawbacks of both. To improve the performance further, speech and noise bases are adapted simultaneously in NMF approach with the help of the estimated speech presence probability (SPP). The proposed approach yields better results than statistical based approach, NMF based approach and also combination of both approaches without on-line update in non-stationary noise environments.
Organization of Multisynaptic Inputs to the Dorsal and Ventral Dentate Gyrus: Retrograde Trans-Synaptic Tracing with Rabies Virus Vector in the Rat

Behavioral, anatomical, and gene expression studies have shown functional dissociations between the dorsal and ventral hippocampus with regard to their involvement in spatial cognition, emotion, and stress. In this study we examined the difference of the multisynaptic inputs to the dorsal and ventral dentate gyrus (DG) in the rat by using retrograde trans-synaptic tracing of recombinant rabies virus vectors. Three days after the vectors were injected into the dorsal or ventral DG, monosynaptic neuronal labeling was present in the entorhinal cortex, medial septum, diagonal band, and supramammillary nucleus, each of which is known to project to the DG directly. As in previous tracing studies, topographical patterns related to the dorsal and ventral DG were seen in these regions. Five days after infection, more of the neurons in these regions were labeled and labeled neurons were also seen in cortical and subcortical regions, including the piriform and medial prefrontal cortices, the endopiriform nucleus, the claustrum, the cortical amygdala, the medial raphe nucleus, the medial habenular nucleus, the interpeduncular nucleus, and the lateral septum. As in the monosynaptically labeled regions, a topographical distribution of labeled neurons was evident in most of these disynaptically labeled regions. These data indicate that the cortical and subcortical inputs to the dorsal and ventral DG are conveyed through parallel disynaptic pathways. This second-order input difference in the dorsal and ventral DG is likely to contribute to the functional differentiation of the hippocampus along the dorsoventral axis.
Calibration of range sensor pose on mobile platforms

This paper describes a new methodology for calculating the translational and rotational offsets of a range sensor to a reference coordinate frame on the platform to which it is affixed. The technique consists of observing an environment of known or partially known geometry, from which the offsets are determined by minimizing the error between the sensed data and the known structure. Analytic results are presented which derive the necessary conditions for a successful optimisation. Practical results confirm the analysis and show that it is possible to obtain more precise results than those obtained through hand measurement.
Mapping search relevance to social networks

This paper explores how information contained in the structure of the social graph can improve search result relevance on social networking websites. Traditional approaches to search include scoring documents for relevance based on a set of keywords or using the link structure across documents to infer quality and relevance. These approaches attempt to optimally match keywords to documents with little or no information about the searcher and no information about his network. This study analyzes 3.8M profile search queries from a large social networking site in conjunction with the tie structure of a 21M member social graph. The key finding is that a measure of social distance, when used in conjunction with standard search relevance methods, improves the ordering of profiles in search results.
A sharp bilinear cone restriction estimate

The purpose of this paper is to prove an essentially sharp L2 Fourier restriction estimate for light cones, of the type which is called bilinear in the recent literature. Fix d ≥ 3, denote variables in Rd by (x, xd) with x ∈ Rd−1, and let Γ = {x : xd = |x| and 1 ≤ xd ≤ 2}. Let Γ1 and Γ2 be disjoint conical subsets, i.e. Γi = {x ∈ Γ : x xd ∈ Ωi} where Ωi are disjoint closed subsets of the sphere S d−2. Let f and g be two functions on Γ whose supports are contained in Γ1 and Γ2 respectively. We will prove the following estimate, where σ is surface measure on Γ, and f̂ dσ is the Rd Fourier transform: Theorem 1. If p > 1 + 2 d then
Isocyanate exposure and asthma in the UK vehicle repair industry

Background Organic diisocyanates are a common cause of occupational asthma, particularly in motor vehicle repair (MVR) workers. The UK Health & Safety Laboratory provides screening for urinary hexamethylenediamine (UHDA), a biomarker of exposure to 1,6-hexamethylene diisocyanate (HDI). The UK Surveillance of Work-related and Occupational Respiratory Disease scheme (SWORD) has collected reports of occupational asthma since 1996. Aims To compare trends in HDI exposure with trends in the incidence of work-related asthma attributed to isocyanates or paint spraying in MVR workers reported to SWORD. Methods Two-level regression models were used to estimate trends in UHDA levels and work-related asthma in MVR workers reported to SWORD. The direction and magnitude of the trends were compared descriptively. Results From 2006 to 2014, there was a significant decline in the number of urine samples with detectable levels of UHDA (odds ratio = 0.96; 95% confidence intervals 0.94–0.98) and minimal change in those over the guidance value (1.03; 1.00–1.06). Over the same period, there was a significant decline in all asthma cases attributed to isocyanates or paint spraying reported to SWORD (0.90; 0.86–0.94) and a non-significant decline among MVR workers (0.94; 0.86–1.02). Conclusions The simultaneous decrease in HDI exposure and incident cases of asthma reported to SWORD is temporally consistent with a reduction in exposure to airborne isocyanate leading to a reduction in asthma. Although this is not direct evidence of a causal relationship between the two trends, it is suggestive.
miR-125b Acts as a Tumor Suppressor in Breast Tumorigenesis via Its Novel Direct Targets ENPEP, CK2-α, CCNJ, and MEGF9

MicroRNAs (miRNAs) play important roles in diverse biological processes and are emerging as key regulators of tumorigenesis and tumor progression. To explore the dysregulation of miRNAs in breast cancer, a genome-wide expression profiling of 939 miRNAs was performed in 50 breast cancer patients. A total of 35 miRNAs were aberrantly expressed between breast cancer tissue and adjacent normal breast tissue and several novel miRNAs were identified as potential oncogenes or tumor suppressor miRNAs in breast tumorigenesis. miR-125b exhibited the largest decrease in expression. Enforced miR-125b expression in mammary cells decreased cell proliferation by inducing G2/M cell cycle arrest and reduced anchorage-independent cell growth of cells of mammary origin. miR-125b was found to perform its tumor suppressor function via the direct targeting of the 3’-UTRs of ENPEP, CK2-α, CCNJ, and MEGF9 mRNAs. Silencing these miR-125b targets mimicked the biological effects of miR-125b overexpression, confirming that they are modulated by miR-125b. Analysis of ENPEP, CK2-α, CCNJ, and MEGF9 protein expression in breast cancer patients revealed that they were overexpressed in 56%, 40–56%, 20%, and 32% of the tumors, respectively. The expression of ENPEP and CK2-α was inversely correlated with miR-125b expression in breast tumors, indicating the relevance of these potential oncogenic proteins in breast cancer patients. Our results support a prognostic role for CK2-α, whose expression may help clinicians predict breast tumor aggressiveness. In particular, our results show that restoration of miR-125b expression or knockdown of ENPEP, CK2-α, CCNJ, or MEGF9 may provide novel approaches for the treatment of breast cancer.
A model-based approach for RFID data stream cleansing

In recent years, RFID technologies have been used in many applications, such as inventory checking and object tracking. However, raw RFID data are inherently unreliable due to physical device limitations and different kinds of environmental noise. Currently, existing work mainly focuses on RFID data cleansing in a static environment (e.g. inventory checking). It is therefore difficult to cleanse RFID data streams in a mobile environment (e.g. object tracking) using the existing solutions, which do not address the data missing issue effectively. In this paper, we study how to cleanse RFID data streams for object tracking, which is a challenging problem, since a significant percentage of readings are routinely dropped. We propose a probabilistic model for object tracking in a mobile environment. We develop a Bayesian inference based approach for cleansing RFID data using the model. In order to sample data from the movement distribution, we devise a sequential sampler that cleans RFID data with high accuracy and efficiency. We validate the effectiveness and robustness of our solution through extensive simulations and demonstrate its performance by using two real RFID applications of human tracking and conveyor belt monitoring.