Miracle-dz/UniFAR-FTUs huggingface dataset:
Mental Representation and Mental Practice: Experimental Investigation on the Functional Links between Motor Memory and Motor Imagery

Recent research on mental representation of complex action has revealed distinct differences in the structure of representational frameworks between experts and novices. More recently, research on the development of mental representation structure has elicited functional changes in novices' representations as a result of practice. However, research investigating if and how mental practice adds to this adaptation process is lacking. In the present study, we examined the influence of mental practice (i.e., motor imagery rehearsal) on both putting performance and the development of one's representation of the golf putt during early skill acquisition. Novice golfers (N = 52) practiced the task of golf putting under one of four different practice conditions: mental, physical, mental-physical combined, and no practice. Participants were tested prior to and after a practice phase, as well as after a three day retention interval. Mental representation structures of the putt were measured, using the structural dimensional analysis of mental representation. This method provides psychometric data on the distances and groupings of basic action concepts in long-term memory. Additionally, putting accuracy and putting consistency were measured using two-dimensional error scores of each putt. Findings revealed significant performance improvements over the course of practice together with functional adaptations in mental representation structure. Interestingly, after three days of practice, the mental representations of participants who incorporated mental practice into their practice regime displayed representation structures that were more similar to a functional structure than did participants who did not incorporate mental practice. The findings of the present study suggest that mental practice promotes the cognitive adaptation process during motor learning, leading to more elaborate representations than physical practice only.
Simulating Crowd Behaviors with a Communication Model

A system for pumping and heating viscous fluids in a wellbore includes electrical power supplies, a switchboard, conductors, and a submergible pumping system having a pump and a submergible electric motor. The electrical power supplies are coupled to the submergible pumping system through a switchboard and conductors that supply electrical power to the motor. The electrical power supplies provide direct or alternating current and include protective circuitry. The submergible pumping system may be supplied with electrical power to motor stator windings to generate heat to raise the temperature and lower the viscosity of adjacent viscous fluids.
A Novel Tensor-Based Receiver for Joint Symbol and Channel Estimation in Two-Hop Cooperative MIMO Relay Systems

In this letter, we develop a novel tensor-based receiver for two-hop cooperative multiple-input multiple-output (MIMO) relay systems. At the source node, the proposed transmit signal design combines the linear constellation precoding with time-domain spreading. We show that the received signal at the destination node is formulated as a fourth-order tensor satisfying a nested parallel factor (PARAFAC) model, and then a new tensor-based receiver is derived by resorting to the proposed receiver algorithm. Under the assumption that channel state information (CSI) is not available at each node, the proposed receiver jointly estimates the channel parameters and transmitted symbols. Numerical results show that the proposed receiver outperforms some competing tensor-based receivers and operates close to the zero forcing (ZF) receiver with perfect CSI.
Modelling of organic aerosols over Europe (2002--2007) using a volatility basis set (VBS) framework: application of different assumptions regarding the formation of secondary organic aerosol

A new organic aerosol module has been implemented into the EMEP chemical transport model. Four different volatility basis set (VBS) schemes have been tested in long-term simulations for Europe, covering the six years 2002-2007. Different assumptions regarding partitioning of primary organic aerosol and aging of primary semi-volatile and intermediate volatility organic carbon (S/IVOC) species and secondary organic aerosol (SOA) have been explored. Model results are compared to filter measurements, aerosol mass spectrometry (AMS) data and source apportionment studies, as well as to other model studies. The present study indicates that many different sources contribute significantly to organic aerosol in Europe. Biogenic and anthropogenic SOA, residential wood combustion and vegetation fire emissions may all contribute more than 10% each over substantial parts of Europe. This study shows smaller contributions from biogenic SOA to organic aerosol in Europe than earlier work, but relatively greater anthropogenic SOA. Simple VBS based organic aerosol models can give reasonably good results for summer conditions but more observational studies are needed to constrain the VBS parameterisations and to help improve emission inventories. The volatility distribution of primary emissions is one important issue for further work. Emissions of volatile organic compounds from biogenic sources are also highly uncertain and need further validation. We can not reproduce winter levels of organic aerosol in Europe, and there are many indications that the present emission inventories substantially underestimate emissions from residential wood combustion in large parts of Europe.
Awareness and Impact of Education on Breast Self Examination Among College Going Girls

Introduction: Breast cancer accounts for 19-34% of all cancer cases among women in India. There is high mortality due to late stage diagnosis as patients usually present at an advanced stage because of lack of awareness and nonexistent breast cancer screening programs. Early detection and prompt treatment offer the greatest chance of long-term survival and breast self-examination (BSE) seems to be a important viable optional substitute for early detection of cancer. Objectives: 1) To assess the level of knowledge of degree college female students on BSE. 2) To determine the effectiveness of planned teaching program among degree college female students on BSE. 3) To find the association between pretest knowledge and selected demographic variables. Materials and Methods: Pre-experimental one group pretestpost-test design was carried out among 40 degree female students by using cluster sampling method from selected colleges of Udupi district. Results: The data analyzed showed that majority (52%) of them was in the age group of 18-19 years and 72% of them were had average knowledge on BSE in the pretest score. Out of 40 participants only one student was performing BSE occasionally. Conclusions: Awareness regarding breast self examination among young generations is useful and it is the most important viable tool for early detection.
Robustness of SiC JFETs and Cascodes United Silicon Carbide supplies a

Trench JFET Structure Figure 1 shows the structure of the trench JFET. The low on-resistance derives from the vertical channel that repeats with a high cell density, creating a short path between the source and drain contacts via the channel and drift regions. The drift region doping and thickness are set by the desired voltage rating. This device does not contain a body diode, or any parasitic NPN transistor. It does not have a gate-oxide or any surface conduction path.
The Genetic Content of Chromosomal Inversions across a Wide Latitudinal Gradient

There is increasing evidence regarding the role of chromosomal inversions in relevant biological processes such as local adaptation and speciation. A classic example of the adaptive role of chromosomal polymorphisms is given by the clines of inversion frequencies in Drosophila subobscura, repeatable across continents. Nevertheless, not much is known about the molecular variation associated with these polymorphisms. We characterized the genetic content of ca. 600 individuals from nine European populations following a latitudinal gradient by analysing 19 microsatellite loci from two autosomes (J and U) and the sex chromosome (A), taking into account their chromosomal inversions. Our results clearly demonstrate the molecular genetic uniformity within a given chromosomal inversion across a large latitudinal gradient, particularly from Groningen (Netherlands) in the north to Málaga (Spain) in the south, experiencing highly diverse environmental conditions. This low genetic differentiation within the same gene arrangement across the nine European populations is consistent with the local adaptation hypothesis for th evolutionof chromosomal polymorphisms. We also show the effective role of chromosomal inversions in maintaining different genetic pools within these inverted genomic regions even in the presence of high gene flow. Inversions represent thus an important barrier to gene flux and can help maintain specific allelic combinations with positive effects on fitness. Consistent patterns of microsatellite allele-inversion linkage disequilibrium particularly in loci within inversions were also observed. Finally, we identified areas within inversions presenting clinal variation that might be under selection.
Partial correlation mapping of cognitive measure and cortical thickness in autism

s: We correlated face recognition task scores to cortical thickness measurements in a group of autistic subjects. Many previous autism anatomical studies neglect to account for age effect and the subsequent statistical parametric maps tend to report spurious results. We demonstrate that the partial correlation mapping proposed here can remove the effect of age and global cortical area difference effectively while localizing the regions of high correlation. Methods: 14 high functioning autistic (HFA) and 12 normal control (NC) subjects used in the study were screened to be right-handed males (Chung, et al., 2004). Face recognition task was performed for the both groups. Age distributions for HFA and NC are 15.93±4.71 and 17.08±2.78 respectively. The face recognition task scores for HFA and NC are 27.14±15.34 and 39.42±0.79 respectively. The outer cortical surface areas are and for HFA and NC respectively. MRIs were collected and both the outer and inner cortical surfaces were extracted for each subject via deformable surface algorithm (MacDonald et al., 2000). Surface normalization is performed by minimizing an objective function that measures the global fit of two surfaces while maximizing the smoothness of the deformation in such a way that the pattern of gyral ridges are matched smoothly (Robbins, 2003). Afterward cortical thickness was computed for each subject (Chung et al., 2005). Heat kernel smoothing was applied to the cortical thickness measures to increase the signal-to-noise ratio with relatively large FWHM of 30mm (Chung et al., 2005). The simple correlation between thickness and score were computed for both groups. To partial out the effect of age and global surface area difference in the correlation, the concept of partial correlation was used (Grunwald et al., 2001). 5 (2.84 0.17) 10 mm ± ⋅ 2 2 5 (2.73 0.06) 10 mm ± ⋅ Results: Comparing the partial correlation to the simple correlation, there is statistically significant increase in the correlation in many areas indicating that the age and the area terms should be accounted for proper correlation analysis. The partial correlation mapping can remove the effect of the age and global area difference in the simple correlation measure as illustrated in the figure. Conclusions: The partial correlation mapping is an effective way of visualizing and localizing the cortical regions of high correlation removing the effect of covariates. Figure 1. Correlation map of face recognition task and cortical thickness. The partial correlation mapping can remove the effect of the age and global area difference in the simple correlation measure.
Comments on Shaun Gallagher: ‘Neurocognitive Models of Schizophrenia: A Neurophenomenological Critique’

When I started to develop the assumption that a defect in self-monitoring might explain some of the symptoms of schizophrenia [Frith, 1987] I had no idea that this would become of such an interest to philosophers. I trained as an experimental psychologist so that one of my principal aims was to provide an account that could generate predictions, which could be tested experimentally. At that time, there had been a number of attempts to explain schizophrenia in terms of cognition (then referred to as ‘information processing’). My approach was, however, somewhat novel in that I attempted to explain certain specific symptoms of schizophrenia rather than the disorder as a unitary entity. To that extent, my approach was concerned with phenomenology. I hoped that, by explaining symptoms such as delusions of control, for example, in terms of deviations from normal cognitive processes, these symptoms would become more understandable (compare with Jaspers [1962]) and we might get some idea of what it is like to experience such symptoms. I am therefore extremely sympathetic to Shaun Gallagher’s approach to the explanation of symptoms. The Development of the Model
Historical spatio-temporal aggregation

Spatio-temporal databases store information about the positions of individual objects over time. However, in many applications such as traffic supervision or mobile communication systems, only summarized data, like the number of cars in an area for a specific period, or phone-calls serviced by a cell each day, is required. Although this information can be obtained from operational databases, its computation is expensive, rendering online processing inapplicable. In this paper, we present specialized methods, which integrate spatio-temporal indexing with pre-aggregation. The methods support dynamic spatio-temporal dimensions for the efficient processing of historical aggregate queries without a priori knowledge of grouping hierarchies. The superiority of the proposed techniques over existing methods is demonstrated through a comprehensive probabilistic analysis and an extensive experimental evaluation.
Amplification of the c-myb oncogene in a case of human acute myelogenous leukemia.

Amplification is one of the mechanisms by which cellular oncogenes may be altered in their function, possibly leading to neoplastic transformation. The oncogenes c-myc, c- abl , and c-Ki-ras are amplified in several different human neoplasias. The oncogene c-myb, which is specifically expressed and regulated in hematopoietic cells, was found to be amplified in cell lines ML-1, ML-2, and ML-3, which were separately cultured from cells of a patient with acute myelogenous leukemia (AML). A five- to tenfold amplification was correlated with high levels of expression of normal size c-myb messenger RNA and with chromosomal abnormalities in the region 6q22 -24, where the c-myb locus is normally located. Amplification and cytogenetic abnormalities were detected in DNA's from primary and secondary cultures of ML cells, suggesting that they may have contributed to leukemogenesis. The similar AML cell lines HL-60 and ML's contain different amplified oncogenes: c-myc and c-myb, respectively. Alternative activation of structurally and possibly functionally similar oncogenes may distinguish--at the pathogenetic level--phenotypically similar tumors.
Epidemiology of restless legs in the Netherlands

The prevalence of restless legs syndrome (RLS) in various regions in the world has been estimated between 2.5 and 29%. For the Netherlands these figures are not known. Our observational and cross‐sectional study was performed to estimate the prevalence of RLS in the Netherlands. A cross‐sectional survey by postal questionnaire was carried out through a general practice in a small town in which one general practice serves 93% of the population. All men and women aged 50 years and older were invited to fill out the questionnaire on leg movements, quality of sleep and daytime symptoms. A total of 1485 (88.2%) persons returned their questionnaire and 1437 (85.4%) patients answered the questions on leg movements. A total of 102 (7.1%) inhabitants answered positively to the questions on leg movements and probably have RLS. The prevalence was higher in women and increased with age. People who complain of RLS have significantly more complaints of disturbances in initiating and maintaining sleep, sleepiness, tiredness during the day and less refreshing sleep. RLS is common in the Netherlands with an estimated prevalence of 7.1% in the population over 50 years of age.
The Effects of Opiod and Benzodiazepine Weaning on Cognitive Ability in the Context of a Chronic Pain Rehabilitation Program

Pain is a component of many disease processes; however in some cases, when pain becomes a chronic condition it can become the problem itself. It can be a debilitating condition which is emotionally and economically costly to the individual, his or her family, and societies as a whole. Theories of pain have evolved over the last several decades to incorporate a Biopsychosocial Model of Pain. The biological portion of the model relies on The Gate Control Theory of Pain, although some emerging research points to a Neuromatrix model. As is suggested by the term, Biopsychosocial Model of Pain, the biologic basis of pain is only a part of the overall phenomenon. The experience of pain relies on many subjective, individual and environmental factors. Similarly the treatment of pain has evolved to encompass multiple dimensions of the phenomena of pain. The predominant model of Interdisciplinary Treatment encompasses seven areas: Medication; Education; Psychophysiologic Pain and Stress Management; Individual and Group Psychotherapy; Physical and Occupational Therapy; Behavior Modification; and Family Therapy. While classically medication with opioid analgesics and benzodiazepines has been a mainstay of treatment, they have recently been the source of considerable debate. Some research and practitioners suggest that these medications may hinder a patient’s progress in treatment and reduce or inhibit their functioning overall and contribute to their pain. The exact nature of the relationship to neurocognitive functioning is still the source of considerable debate. This paper examines the relationship of two classes of medication: opioids and benzodiazepines to neurocognitive functioning as measured by two subtests of the WAIS-R (Digit Span & Digit-Symbol Substitution Test) in a Cleveland, OH pain rehabilitation clinic population.
Modular Continual Learning in a Unified Visual Environment

A core aspect of human intelligence is the ability to learn new tasks quickly and switch between them flexibly. Here, we describe a modular continual reinforcement learning paradigm inspired by these abilities. We first introduce a visual interaction environment that allows many types of tasks to be unified in a single framework. We then describe a reward map prediction scheme that learns new tasks robustly in the very large state and action spaces required by such an environment. We investigate how properties of module architecture influence efficiency of task learning, showing that a module motif incorporating specific design principles (e.g. early bottlenecks, low-order polynomial nonlinearities, and symmetry) significantly outperforms more standard neural network motifs, needing fewer training examples and fewer neurons to achieve high levels of performance. Finally, we present a meta-controller architecture for task switching based on a dynamic neural voting scheme, which allows new modules to use information learned from previously-seen tasks to substantially improve their own learning efficiency.
Semi-Distributed Resource Selection for D2D Communication in LTE-A Network

Device-to-Device (D2D) communication underlaying cellular network has received much attention as a means to utilize cellular resources in a more efficient manner. Since D2D communication range is expected to be shorter than the normal cellular communication range, there are potential advantages such as reduced delay, reduced number of hops, improved spectral efficiency, and offloaded cellular traffic. In this paper, a semi- distributed resource selection scheme for D2D communication is proposed to efficiently reuse cellular resources. In addition, we propose interference avoidance scheme and D2D power control scheme to enhance D2D performance and minimize the degradation of cellular network performance, respectively. We demonstrate that the proposed semi-distributed algorithm outperforms the existing scheme by as much as 64% in terms of sum throughput of D2D users.
Late reverberation PSD estimation for single-channel dereverberation using relative convolutive transfer functions

The estimation accuracy of the late reverberation power spectral density (PSD) is of paramount importance in single-channel frequency-domain dereverberation algorithms. In this domain, the reverberant signal can be modeled by the convolution of an early speech component and a relative convolutive transfer function (RCTF). In this work, the RCTF coefficients are modeled by a first-order Markov chain, which is well-suited to model time-varying scenarios. The RCTF coefficients are estimated online by a Kalman filter and are then used to compute the late reverberation PSD, which is used in a spectral enhancement filter to achieve dereverberation and noise reduction. It is shown that the proposed reverberation PSD estimator yields similar performance to other estimators, which impose a model on the reverberant tail and which depend on additional information like the reverberation time and the direct-to-reverberation ratio.
ThroughputScheduler: Learning to Schedule on Heterogeneous Hadoop Clusters

Hadoop is the de-facto standard for big data analytics applications. Presently available schedulers for Hadoop clusters assign tasks to nodes without regard to the capability of the nodes. We propose ThroughputScheduler, which reduces the overall job completion time on a clusters of heterogeneous nodes by actively scheduling tasks on nodes based on optimally matching job requirements to node capabilities. Node capabilities are learned by running probe jobs on the cluster. ThroughputScheduler uses a Bayesian, active learning scheme to learn the resource requirements of jobs on-the-fly. An empirical evaluation on a set of sample problems demonstrates that ThroughputScheduler can reduce total job completion time by almost 20% compared to the Hadoop FairScheduler and 40% compared to FIFOScheduler. ThroughputScheduler also reduces average mapping time by 33% compared to either of these schedulers.