Miracle-dz/UniFAR-FTUs huggingface dataset:
Simultaneous use of sensory stimulation and motor exercise improves the manual skills of educable children with mental retardation at preprimary and primary school levels

Background: Children with mental retardation have various clinical problems. They mostly have motor delay and sensory deficit. Neurorehabilitation focuses on restoring remaining abilities. Thus, the present study was designed to study the effects of simultaneous use of sensory-motor therapy on manual skills of children with mental retardation. Methods: In this study, 120 educable boys and girls with mental retardation (9-12 years) were selected from 2 preprimary and primary exceptional centers in Tehran using stratified sampling method considering the geographical dispersion. The participants were divided into 2 equal trial and control groups using simple random sampling. Lincoln-Oseretsky Motor Development Scale, Purdue Pegboard test, and Handwriting Legibility Checklist of Persian Language were used. Simultaneous sensory stimulations and motor exercises were used for 3 one-hour weekly sessions for 12 consecutive weeks. Pre and posttests were done for evaluation. Using parametric paired and independent samples t tests, the findings were analyzed in SPSS 23. Results: The manual skills significantly improved following therapeutic use of simultaneous sensory stimulation and motor exercise (p=0.001). In the control group, the pre and post evaluation difference was not significant (p=0.813) Conclusion: Based on the findings of this study, simultaneous use of sensory-motor techniques can have better clinical results in the trial group compared to the control group. Thus, these types of techniques should be used more in clinics. However, further studies are needed for more comparison between separate applications of these techniques.
Does teachers’ perceived corporate social responsibility lead to organisational citizenship behaviour? The mediating roles of job satisfaction and organisational identification

Background: Corporate social responsibility (CSR) literature indicates that employees develop positive organisational behaviour towards their organisation when their organisation is perceived as being socially responsible. Such organisational behaviours include organisational citizenship behaviour (OCB), job satisfaction and organisational identity. Objectives: The main objective of this study was to provide empirical evidence as to whether teachers’ perceptions of their schools’ CSR influence their OCB as well as to indicate the mediating role of organisational identification and job satisfaction in this relationship. Setting: Corporate social responsibility is a valuable way for organisations to promote favourable employee behaviours. Method: Data were collected through the use of a questionnaire from 260 teachers working at high schools in North Cyprus. Structural equation modelling was employed to test the hypotheses. Results: The results of this study suggested that employees’ perceptions of CSR positively influence their OCB when job satisfaction and organisational identification mediate the relationship. Conclusion: The results of this study indicate that as long as employees are satisfied with their jobs and as long as they identify with their organisation, CSR favourably influences their voluntary behaviour, which in turn influences the overall performance of the organisation.
Semantic Segmentation of LiDAR Points Clouds: Rasterization Beyond Digital Elevation Models

LiDAR point clouds are receiving a growing interest in remote sensing as they provide rich information to be used independently or together with optical data sources, such as aerial imagery. However, their nonstructured and sparse nature make them difficult to handle, conversely to raw imagery for which many efficient tools are available. To overcome this specific nature of LiDAR point clouds, the standard approach relies on converting the point cloud into a digital elevation model, represented as a 2-D raster. Such a raster can then be used similarly as optical images, e.g., with 2-D convolutional neural networks (CNNs) for semantic segmentation. In this letter, we show that LiDAR point clouds provide more information than only the digital elevation model and that considering alternative rasterization strategies helps to achieve better semantic segmentation results. We illustrate our findings on the IEEE Data Fusion Contest (DFC) 2018 data set.
Clinical characteristics and risk factors of twin pregnancies with single fetal malformation: a multi-center analysis in Southeastern China

Objective: Twin pregnancy, which has risen in the incidence across the world, causes an increased risk to both mother and babies. However, there is little knowledge on the clinical characteristics and risk factors of twin pregnancies with single fetal malformation. This multi-center analysis aimed to investigate the clinical characteristics and identify the risk factors of twin pregnancies with single fetal malformation in Fujian Province, Southeastern China. Methods: A total of 216 twin pregnancies with single fetal malformation diagnosed at 6 tertiary hospitals in Fujian Province during the period from October 1, 2013 through June 30, 2016 were sampled as the case group, while 216 normal twin pregnancies were selected as controls. The fetal malformations were identified from the subjects’ medical records, and univariate and multivariate logistic regression analyses were employed to identify the risk factors of twin pregnancies with single fetal malformation. Results: The prevalence of twin pregnancies with single fetal malformation was 15.2% in Fujian Province, Southeastern China from 2013 to 2016. There were 225 types of fetal malformations diagnosed in the 216 twin pregnancies with single fetal malformation, and the most three common organs where the fetal malformation developed were the cardiovascular system, the skeletal system, and the urinary system. Univariate analysis revealed that the development of twin pregnancies with single fetal malformation was positively correlated with natural conception and monochorionic twins (P = 0), and multivariate logistic regression analysis identified monochorionic twins as an independent risk factor for twin pregnancies with single fetal malformation (P = 0). Conclusions: The results of the present study demonstrate a high rate of twin pregnancies with single fetal malformation in Fujian Province, southeastern China, and the fetal malformation mainly occurs in the cardiovascular system, the skeletal system and the urinary system. In addition, having monochorionic twins is an independent risk factor for twin pregnancies with single fetal malformation.
PRESSURE CHANGES IN REINJECTION WELLS AND GRAVITY CHANGES IN OTAKE GEOTHERMAL FIELD, JAPAN

ABSTRACT In the Otake geothermal field, gravity changes at reinjection well OR-15 have been monitored together with pressure changes using water level data for wells OR-15, OR-19 and O-16R to clarify the behavior of the reinjected water in the reservoir and its effect on the production zone. Using these data, the correlation between water level changes in the observation wells, changes in flow-rate of reinjected water and the observed gravity changes have been studied. The water level changes in OR-15 are similar to the water level changes in O-16R. The reinjection area is subdivided into four blocks. Multiple regression analysis shows the pressure changes around these wells are affected not only by the reinjection rate changes in the immediate block but also by the reinjection changes in other blocks and the amount of rainfall (after a 3-month time lag). However, the pressure changes in OR-19 strongly correlate with the reinjection flow-rate in block D, and the presence of an impermeable structure between OR-15 and OR-19 is indicated. The repeated gravity measurements show the gravity changes at each station have similar tendencies. However , a discrepancy was recognized between the values of the maximum value minus minimum value at each station. The general tendency of gravity changes at OR-15 is similar to the water level changes in OR-15. A quasi-three-dimensional inversion of the gravity changes was therefore applied to delineate the behavior of reinjected water in the reservoir and its effect in the production zone. From the inversion results, the geothermal reservoir in the Otake field is considered to be controlled by a NW-SE trending structure between OR-15 and OR-19. In addition, the reinjected water in the reservoir is considered to be flowing mainly in a northerly direction.
Pitfalls in the ankle-brachial index and brachial- ankle pulse wave velocity

php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). Vascular Health and Risk Management 2018:14 41–62 Vascular Health and Risk Management Dovepress
On Hookean solids in seismology: anisotropy and fractures

Geophysics—similarly to astrophysics—relies on remote sensing. Inferring material properties of the Earth’s interior is akin to inferring the composition of a distant star. In both cases, scientists rely on matching theoretical predictions or explanations with observations. Notably, obtaining a sample of a material from the interior of our planet might not be less difficult than obtaining a sample from a distant celestial object.
Changes in soil chemical and physical properties in pasture fertilised with liquid swine manure

Chemical and physical properties of soil can be altered with the successive application of liquid swine manure (LSM), also known as slurry. Therefore, monitoring the impact of LSM is essential to an assessment of the potential agronomic and environmental benefits and risks associated with management practices. The aim of this study was to evaluate the effects of LSM on the chemical and physical attributes of soil under pasture (Cynodon spp.), located in southern Brazil. Four areas were sampled: three areas cultivated with Cynodon spp. pasture with successive applications of 200 m3 ha–1 y–1 of LSM for three, eight and 15 years; and untreated native forest as a reference. The soil attributes evaluated were: organic carbon (OC), active (pH water) and potential acidity (H + Al+ 3), nutrient availability (i.e., P, K, Ca, Mg, Cu and Zn), soil bulk density, macro, micro and total porosity. Successive applications of LSM on pasture reduced soil active acidity, and increased the soil organic C and plant-available N, P, Ca, Mg, Cu and Zn contents. These effects were more intense with time and in the shallowest layers, i.e. 0-10 cm. Excessive increases in P, Cu and Zn in the soil should be carefully monitored to minimize the contamination risks to soil, ground and surface waters. Soil physical attribute changes were more associated with land use (pasture versus native forest) than LSM use, and LSM applications induced slight improvements in the soil structural quality over time.
Pressure-Tuned Interactions in Frustrated Magnets: Pathway to Quantum Spin Liquids?

Quantum spin liquids are prime examples of strongly entangled phases of matter with unconventional exotic excitations. Here, strong quantum fluctuations prohibit the freezing of the spin system. On the other hand, frustrated magnets, the proper platforms to search for the quantum spin liquid candidates, still show a magnetic ground state in most of the cases. Pressure is an effective tuning parameter of structural properties and electronic correlations. Nevertheless, the ability to influence the magnetic phases should not be forgotten. We review experimental progress in the field of pressure-tuned magnetic interactions in candidate systems. Elaborating on the possibility of tuned quantum phase transitions, we further show that chemical or external pressure is a suitable parameter in these exotic states of matter.
Potential drug–drug interactions in children with acute lymphoblastic leukaemia: a cohort study

Objective To evaluate the potential drug interactions in patients with acute lymphoblastic leukaemia in the remission induction period of treatment. Design A prospective cohort study. Setting A tertiary referral centre. Subjects Twenty‐two children undergoing treatment for acute lymphoblastic leukaemia. The median age was 4.5 years (minimum of 1 and maximum of 18 years) with male predominance (54.4%). Main outcome measure Presence of potential drug interactions in patients undergoing treatment for precursor cell lymphoblastic leukaemia‐ lymphoma. The potential drug interactions term refers to the ability of a drug to affect the pharmacologic intensity as well as the therapeutic effect of another and cause adverse reactions, as well as the possibility of clinical manifestations. Results All participants were exposed to at least one potential drug interaction. About 60% of interactions classified as more severe. Every new drug included in the treatment increased the chance of potential drug‐drug interactions by 0.4 times. Conclusion These results demonstrated the patients under chemotherapeutic care for lymphoblastic leukaemia‐lymphoma have high potential for drug interactions of greater severity.
Dual Multi-head Co-attention for Multi-choice Reading Comprehension

Multi-choice Machine Reading Comprehension (MRC) requires model to decide the correct answer from a set of answer options when given a passage and a question. Thus in addition to a powerful pre-trained Language Model as encoder, multi-choice MRC especially relies on a matching network design which is supposed to effectively capture the relationship among the triplet of passage, question and answers. While the latest pre-trained Language Models have shown powerful enough even without the support from a matching network, and the latest matching network has been complicated enough, we thus propose a novel going-back-to-the-basic solution which straightforwardly models the MRC relationship as attention mechanism inside network. The proposed DUal Multi-head Co-Attention (DUMA) has been shown simple but effective and is capable of generally promoting pre-trained Language Models. Our proposed method is evaluated on two benchmark multi-choice MRC tasks, DREAM and RACE, showing that in terms of strong Language Models, DUMA may still boost the model to reach new state-of-the-art performance.
Non-linear evolutions of magnetized thick discs around black holes: dependence on the initial data

We build equilibrium solutions of magnetised thick discs around a highly spinning Kerr black hole and evolve these initial data up to a final time of about 100 orbital periods. The numerical simulations reported in this paper solve the general relativistic magnetohydrodynamics equations using the BHAC code and are performed in axisymmetry. Our study assumes non-self-gravitating, polytropic, constant angular momentum discs endowed with a purely toroidal magnetic field. In order to build the initial data we consider three approaches, two of which incorporate the magnetic field in a self-consistent way and a third approach in which the magnetic field is included as a perturbation on to an otherwise purely hydrodynamical solution. To test the dependence of the evolution on the initial data, we explore four representative values of the magnetisation parameter spanning from almost hydrodynamical discs to very strongly magnetised tori. The initial data are perturbed to allow for mass and angular momentum accretion on to the black hole. Notable differences are found in the long-term evolutions of the initial data. In particular, our study reveals that highly magnetised discs are unstable, and hence prone to be fully accreted and expelled, unless the magnetic field is incorporated into the initial data in a self-consistent way.
Variance Reduction with Sparse Gradients

Variance reduction methods such as SVRG and SpiderBoost use a mixture of large and small batch gradients to reduce the variance of stochastic gradients. Compared to SGD, these methods require at least double the number of operations per update to model parameters. To reduce the computational cost of these methods, we introduce a new sparsity operator: The random-top-k operator. Our operator reduces computational complexity by estimating gradient sparsity exhibited in a variety of applications by combining the top-k operator and the randomized coordinate descent operator. With this operator, large batch gradients offer an extra benefit beyond variance reduction: A reliable estimate of gradient sparsity. Theoretically, our algorithm is at least as good as the best algorithm (SpiderBoost), and further excels in performance whenever the random-top-k operator captures gradient sparsity. Empirically, our algorithm consistently outperforms SpiderBoost using various models on various tasks including image classification, natural language processing, and sparse matrix factorization. We also provide empirical evidence to support the intuition behind our algorithm via a simple gradient entropy computation, which serves to quantify gradient sparsity at every iteration.
Defect generation and dynamics during quenching in finite size homogeneous ion chains

An equally spaced linear chain of ions provides a test-bed for studying the defect formation during a topological phase transition from a linear to a zig-zag configuration. By using a particular axial potential leading to an homogeneous ion chain, the boundary conditions are not needed, allowing new rich defect dynamics to appear on an homogeneous system. A semi-empirical expression for the critical transition frequency provides an excellent agreement to the numerical results for low ion numbers. The non-adiabatic crossing of the phase transition shows different power-laws for the defect probability density for different quench rates regions. Information regarding defect dynamics is obtained through the measurement of the defect density at different times during the quench. By comparing the defect density and the correlation length dynamics among the different number of trapped ions, the role of the different defect loss mechanism can be deduced. An excellent agreement with the predictions given by the homogeneous Kibble–Zurek model is found on a finite size system of 30 ion system which can be tested in present ion trap experimental set-ups.
Improved mixing time for k-subgraph sampling

Understanding the local structure of a graph provides valuable insights about the underlying phenomena from which the graph has originated. Sampling and examining k-subgraphs is a widely used approach to understand the local structure of a graph. In this paper, we study the problem of sampling uniformly k-subgraphs from a given graph. We analyze a few different Markov chain Monte Carlo (MCMC) approaches, and obtain analytical results on their mixing times, which improve significantly the state of the art. In particular, we improve the bound on the mixing times of the standard MCMC approach, and the state-of-the-art MCMC sampling method PSRW, using the canonical-paths argument. In addition, we propose a novel sampling method, which we call recursive subgraph sampling, RSS, and its optimized variant RSS+. The proposed methods, RSS and RSS+, are significantly faster than existing approaches.
Elementary Cellular Automata along with delay sensitivity can model communal riot dynamics

This paper explores the potential of elementary cellular automata to model the dynamics of riot. Here, to model such dynamics, we introduce probabilistic loss of information and delay perturbation in the updating scheme of automata to capture sociological parameters—presence of anti-riot population and organizational presence of communal forces in the rioting society, respectively. Moreover, delay has also been incorporated in the model to capture the nonlocal interaction of neighbors. Finally, the model is verified by an event of riot that occurred in Baduria of West Bengal, India.
Extension operators and nonlinear structure of Banach spaces

The problem involving the extension of functions from a certain class and defined on subdomains of the ambient space to the whole space is an old and a well investigated theme in analysis. A related question whether the extensions that result in the process may be chosen in a linear or a continuous manner between appropriate spaces of functions turns out to be highly nontrivial. That this holds for the class of continuous functions defined on metric spaces is the well-known Borsuk-Dugundji theorem which asserts that given a metric space M and a subspace S of M, each continuous function g on S can be extended to a continuous function f on X such that the resulting assignment from C(S) to C(M) is a norm-one continuous linear extension operator. The present paper is devoted to an investigation of this problem in the context of extendability of Lipschitz functions from closed subspaces of a given Banach space to the whole space such that the choice of the extended function gives rise to a bounded linear (extension) operator between appropriate spaces of Lipschitz functions. It is shown that the indicated property holds precisely when the underlying space is isomorphic to a Hilbert space. Among certain useful consequences of this theorem, we provide an isomorphic analogue of a well-known theorem of S. Reich by show ing that closed convex subsets of a Banach space X arise as Lipschitz retracts of X precisely when X is isomorphically a Hilbert space. We shall also discuss the issue of bounded linear extension operators between spaces of Lipschitz functions now defined on arbitrary subsets of Banach spaces and provide a direct proof of the known non-existence of such an extension operator by using methods which are more accessible than those initially employed by the authors.
Some interpretations for algebraic invariants of edge ideals of hypergraphs via combinatorial invariants

Abstract The present work is concerned with characterizing some algebraic invariants of edge ideals of hypergraphs. To this aim, first, we introduce some kinds of combinatorial invariants similar to matching numbers for hypergraphs. Then we compare them to each other and to previously existing ones. These invariants are used for characterizing or bounding some algebraic invariants of edge ideals of hypergraphs such as graded Betti numbers, projective dimension and Castelnouvo–Mumford regularity. Communicated by Jason P. Bell
Gesticulator: A framework for semantically-aware speech-driven gesture generation

During speech, people spontaneously gesticulate, which plays a key role in conveying information. Similarly, realistic co-speech gestures are crucial to enable natural and smooth interactions with social agents. Current end-to-end co-speech gesture generation systems use a single modality for representing speech: either audio or text. These systems are therefore confined to producing either acoustically-linked beat gestures or semantically-linked gesticulation (e.g., raising a hand when saying "high''): they cannot appropriately learn to generate both gesture types. We present a model designed to produce arbitrary beat and semantic gestures together. Our deep-learning based model takes both acoustic and semantic representations of speech as input, and generates gestures as a sequence of joint angle rotations as output. The resulting gestures can be applied to both virtual agents and humanoid robots. Subjective and objective evaluations confirm the success of our approach. The code and video are available at the project page svito-zar.github. io/gesticulator .