Miracle-dz/UniFAR-FTUs huggingface dataset:
Differential Diagnosis of Aphasia With the Minnesota Test.

In 1964 Dr. Schuell and associates published a sizeable volume "Aphasia in Adults" in which her approach to the study of aphasia was given and of which the monograph now under review represents the nuclear material. Her approach is essentially pragmatic, ie, she wishes to classify aphasics for purposes of treatment and prognosis, rather than to analyze aphasic syndromes in order to gain a deeper knowledge of brain function. This means that, while no one doubts the usefulness and humanitarianism of her techniques, many neurologists will be left unsatisfied by their lack of intellectualism. The therapist must deal with the hundreds of thousands of aphasics who suffer from "nonspecific" speech disorders; the physician is attracted to the rare "interesting" case with sharply defined linguistic deficits from which he hopes to illuminate problems of cerebral function.
Aversive reinforcement learning

We hypothesise that human aversive learning can be described algorithmically by Reinforcement Learning models. Our first experiment uses a second-order conditioning design to study sequential outcome prediction. We show that aversive prediction errors are expressed robustly in the ventral striatum, supporting the validity of temporal difference algorithms (as in reward learning), and suggesting a putative critical area for appetitive-aversive interactions. With this in mind, the second experiment explores the nature of pain relief, which as expounded in theories of motivational opponency, is rewarding. In a Pavlovian conditioning task with phasic relief of tonic noxious thermal stimulation, we show that both appetitive and aversive prediction errors are co-expressed in anatomically dissociable regions (in a mirror opponent pattern) and that striatal activity appears to reflect integrated appetitive-aversive processing. Next we designed a Pavlovian task in which cues predicted either financial gains, losses, or both, thereby forcing integration of both motivational streams. This showed anatomical dissociation of aversive and appetitive predictions along a posterior-anterior gradient within the striatum, respectively. Lastly, we studied aversive instrumental control (avoidance). We designed a simultaneous pain avoidance and financial reward learning task, in which subjects had to learn independently learn about each, and trade off aversive and appetitive predictions. We show that predictions for both converge on the medial head of caudate nucleus, suggesting that this is a critical site for appetitive-aversive integration in instrumental decision making. We also study also tested whether serotonin (5HT) modulates either phasic or tonic opponency using acute tryptophan depletion. Both behavioural and imaging data confirm the latter, in which it appears to mediate an average reward term, providing an aspiration level against which the benefits of exploration are judged. In summary, our data provide a basic computational and neuroanatomical framework for human aversive learning. We demonstrate the algorithmic and implementational validity of reinforcement learning models for both aversive prediction and control, illustrate the nature and neuroanatomy of appetitive-aversive integration, and discover the critical (and somewhat unexpected) central role for the striatum.
An Atlas framework for scalable mapping

This paper describes Atlas, a hybrid metrical/topological approach to SLAM that achieves efficient mapping of large-scale environments. The representation is a graph of coordinate frames, with each vertex in the graph representing a local frame, and each edge representing the transformation between adjacent frames. In each frame, we build a map that captures the local environment and the current robot pose along with the uncertainties of each. Each map's uncertainties are modeled with respect to its own frame. Probabilities of entities with respect to arbitrary frames are generated by following a path formed by the edges between adjacent frames, computed via Dijkstra's shortest path algorithm. Loop closing is achieved via an efficient map matching algorithm. We demonstrate the technique running in real-time in a large indoor structured environment (2.2 km path length) with multiple nested loops using laser or ultrasonic ranging sensors.
Vibrotactile Sensitivity of the Head

Abstract : The brain rarely processes events of the physical world using signals from a single sensory modality. While the visual and auditory modalities are considered frequently in communication research, the tactile modality is considered the least as a possible mode of communication. In addition, previous studies of tactile sensitivity and solutions in utilizing the tactile modality have been focused on torso and limb locations. However, there are currently no tactile sensitivity data for the head. The goal of the present study was to investigate tactile sensitivity of the various locations on the head and the effect of signal frequency on the tactile threshold. An adaptive psychophysical procedure was used to determine differences in tactile sensitivity at various points on the head. Obtained results indicate that the crown of the scalp is less sensitive to vibration than the areas near the forehead, temples, and lower part of the back of the head.
Understanding the Fault Resilience of File System Checkers

File system checkers serve as the last line of defense to recover a corrupted file system back to a consistent state. Therefore, their reliability is critically important. Motivated by real accidents, in this paper we study the behavior of file system checkers under faults. We systematically inject emulated faults to interrupt the checkers and examine the impact on the file system images. In doing so, we answer two important questions: Does running the checker after an interrupted-check successfully return the file system to a correct state? If not, what goes wrong? Our results show that there are vulnerabilities in popular file system checkers which could lead to unrecoverable data loss under faults.
Expressing privacy metrics as one-symbol information

Organizations often need to release microdata without revealing sensitive information. To this scope, data are anonymized and, to assess the quality of the process, various privacy metrics have been proposed, such as k-anonymity, l-diversity, and t-closeness. These metrics are able to capture different aspects of the disclosure risk, imposing minimal requirements on the association of an individual with the sensitive attributes. If we want to combine them in a optimization problem, we need a common framework able to express all these privacy conditions. Previous studies proposed the notion of mutual information to measure the different kinds of disclosure risks and the utility, but, since mutual information is an average quantity, it is not able to completely express these conditions on single records. We introduce here the notion of one-symbol information (i.e., the contribution to mutual information by a single record) that allows to express the disclosure risk metrics. We also show, with a simple example, how l-diversity and t-closeness can be represented in terms of two different, but equally acceptable, conditions on the information gain.
Active/semi-active suspension control using magnetorheological actuators

Magnetorheological dampers, which are semi-active devices that use MR fluids to produce controllable forces, can be used as smart actuators to reduce the vibrations of mechanical systems. The advantage of these actuators is the low power input requirements and the high output force they produce. An analytical study is performed in this article to examine the effectiveness of this type of actuator in suppressing the vibrations of a passenger car suspension system. A half-car model including passenger dynamics subjected to road disturbance is used. Two MR dampers attached to the front and back axles are used as actuators. An optimal control scheme is used to control the overall suspension system such that the vibrations of the passenger seats as well as the chassis of the car are greatly reduced or eliminated. The simulation results show that properly controlled MR dampers are effective means for vibration suppression for passenger cars.
Rainbow fair queueing: fair bandwidth sharing without per-flow state

Fair bandwidth sharing at routers has several advantages, including protection of well-behaved flows and possible simplification of end-to-end congestion control mechanisms. Traditional mechanisms to achieve fair sharing (e.g., weighted fair queueing, flow random early discard) require per-flow state to determine which packets to drop under congestion, and therefore are complex to implement at the interior of a high-speed network. In recent work, Stoica et al., (1998), have proposed core-stateless fair queueing (CSFQ), a scheme to approximate fair bandwidth sharing without per-flow state in the interior routers. In this paper, we also achieve approximate fair sharing without per-flow state, however our mechanism differs from CSFQ. Specifically, we divide each flow into a set of layers, based on rate. The packets in a flow are marked at an edge router with a layer label (or "color"). A core router maintains a color threshold and drops layers whose color exceeds the threshold. Using simulations, we show that the performance of our rainbow fair queueing (RFQ) scheme is comparable to CSFQ when the application data does not contain any preferential structure. RFQ outperforms CSFQ in goodput when the application takes advantage of the coloring to encode preferences.
Biological Networks for Predicting Chemical Hepatocarcinogenicity Using Gene Expression Data from Treated Mice and Relevance across Human and Rat Species

Background Several groups have employed genomic data from subchronic chemical toxicity studies in rodents (90 days) to derive gene-centric predictors of chronic toxicity and carcinogenicity. Genes are annotated to belong to biological processes or molecular pathways that are mechanistically well understood and are described in public databases. Objectives To develop a molecular pathway-based prediction model of long term hepatocarcinogenicity using 90-day gene expression data and to evaluate the performance of this model with respect to both intra-species, dose-dependent and cross-species predictions. Methods Genome-wide hepatic mRNA expression was retrospectively measured in B6C3F1 mice following subchronic exposure to twenty-six (26) chemicals (10 were positive, 2 equivocal and 14 negative for liver tumors) previously studied by the US National Toxicology Program. Using these data, a pathway-based predictor model for long-term liver cancer risk was derived using random forests. The prediction model was independently validated on test sets associated with liver cancer risk obtained from mice, rats and humans. Results Using 5-fold cross validation, the developed prediction model had reasonable predictive performance with the area under receiver-operator curve (AUC) equal to 0.66. The developed prediction model was then used to extrapolate the results to data associated with rat and human liver cancer. The extrapolated model worked well for both extrapolated species (AUC value of 0.74 for rats and 0.91 for humans). The prediction models implied a balanced interplay between all pathway responses leading to carcinogenicity predictions. Conclusions Pathway-based prediction models estimated from sub-chronic data hold promise for predicting long-term carcinogenicity and also for its ability to extrapolate results across multiple species.
Accelerated forgetting and memory consolidation in children with idiopathic generalised epilepsy

4 Introduction 4 Methods 17 Results 24 Discussion 30 Reference 35 Appendix 1 42 Appendix 2 44 Appendix 3 45 Appendix 4 46 Acknowledgements Many thanks to Dr. Sharon Abrahams for her help in setting up the project and for her guidance and supervision throughout. Thanks also to Dr. Sarah McPherson for her guidance and supervision; Dr Liam Dorris for his help in the initial planning of the project; Dr Ailsa McLellan and Celia Brand for their help with recruiting patients; City of Edinburgh schools for their help and cooperation; all the participants in the study. Lastly I would like to thank my colleague Katie Williams for her invaluable help with setting up the project and testing participants.
ASVUniOfLeipzig: Sentiment Analysis in Twitter using Data-driven Machine Learning Techniques

This paper describes University of Leipzig’s approach to SemEval-2013 task 2B on Sentiment Analysis in Twitter: message polarity classification. Our system is designed to function as a baseline, to see what we can accomplish with well-understood and purely data-driven lexical features, simple generalizations as well as standard machine learning techniques: We use one-against-one Support Vector Machines with asymmetric cost factors and linear “kernels” as classifiers, word uni- and bigrams as features and additionally model negation of word uni- and bigrams in word n-gram feature space. We consider generalizations of URLs, user names, hash tags, repeated characters and expressions of laughter. Our method ranks 23 out of all 48 participating systems, achieving an averaged (positive, negative) F-Score of 0.5456 and an averaged (positive, negative, neutral) F-Score of 0.595, which is above median and average.
BTN1, the Saccharomyces cerevisiae homolog to the human Batten disease gene, is involved in phospholipid distribution

SUMMARY BTN1, the yeast homolog to human CLN3 (which is defective in Batten disease), has been implicated in the regulation of vacuolar pH, potentially by modulating vacuolar-type H+-ATPase (V-ATPase) activity. However, we report that Btn1p and the V-ATPase complex do not physically interact, suggesting that any influence that Btn1p has on V-ATPase is indirect. Because membrane lipid environment plays a crucial role in the activity and function of membrane proteins, we investigated whether cells lacking BTN1 have altered membrane phospholipid content. Deletion of BTN1 (btn1-Δ) led to a decreased level of phosphatidylethanolamine (PtdEtn) in both mitochondrial and vacuolar membranes. In yeast there are two phosphatidylserine (PtdSer) decarboxylases, Psd1p and Psd2p, and these proteins are responsible for the synthesis of PtdEtn in mitochondria and Golgi-endosome, respectively. Deletion of both BTN1 and PSD1 (btn1-Δ psd1-Δ) led to a further decrease in levels of PtdEtn in ER membranes associated to mitochondria (MAMs), with a parallel increase in PtdSer. Fluorescent-labeled PtdSer (NBD-PtdSer) transport assays demonstrated that transport of NBD-PtdSer from the ER to both mitochondria and endosomes and/or vacuole is affected in btn1-Δ cells. Moreover, btn1-Δ affects the synthesis of PtdEtn by the Kennedy pathway and impairs the ability of psd1-Δ cells to restore PtdEtn to normal levels in mitochondria and vacuoles by ethanolamine addition. In summary, lack of Btn1p alters phospholipid levels and might play a role in regulating their subcellular distribution.
A Statistical Model-Based Residual Echo Suppression

In this letter, we propose a novel residual echo suppression (RES) algorithm based on a statistical model constructed in the acoustic echo cancellation framework. In the proposed approach, all the possible near-end and far-end signal conditions are classified into four distinct hypotheses, and the power spectral density estimation is carried out according to the result of hypothesis testing. The distribution of each signal component is characterized by a parametric model, and the conventional likelihood ratio test is performed to make an optimal decision. The experimental results show that the proposed algorithm yields improved performance compared to that of the previous RES technique.
LocNES: a computational tool for locating classical NESs in CRM1 cargo proteins

MOTIVATION Classical nuclear export signals (NESs) are short cognate peptides that direct proteins out of the nucleus via the CRM1-mediated export pathway. CRM1 regulates the localization of hundreds of macromolecules involved in various cellular functions and diseases. Due to the diverse and complex nature of NESs, reliable prediction of the signal remains a challenge despite several attempts made in the last decade. RESULTS We present a new NES predictor, LocNES. LocNES scans query proteins for NES consensus-fitting peptides and assigns these peptides probability scores using Support Vector Machine model, whose feature set includes amino acid sequence, disorder propensity, and the rank of position-specific scoring matrix score. LocNES demonstrates both higher sensitivity and precision over existing NES prediction tools upon comparative analysis using experimentally identified NESs. AVAILABILITY AND IMPLEMENTATION LocNES is freely available at http://prodata.swmed. edu/LocNES CONTACT: yuhmin.chook@utsouthwestern.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Spinal Anesthesia and Spinal Anesthesia with Subdiaphragmatic Lidocaine in Shoulder Pain Reduction for Gynecological Laparoscopic Surgery: A Randomized Clinical Trial

Objective The aim of this study was to compare the effectiveness of spinal anesthesia with subdiaphragmatic lidocaine at the beginning of surgery versus spinal anesthesia in pain reduction for gynecological laparoscopic surgery. Methods This was a clinical trial conducted in Arash Hospital, Tehran, Iran. Eighty-four patients were randomized to either spinal anesthesia with subdiaphragmatic lidocaine, spinal anesthesia, or general anesthesia (GA). The primary outcome was patients' pain perception during surgery, 2, 4, 6, and 12 hours after surgery, and prior to discharge and was assessed by visual analogue scale (VAS). Results The results showed that there are no significant changes in pain perception over time in none of the three groups (F(4,76) = 0.37, P = 0.82). The severity of pain experienced by patients at all-time interval after surgery was similar between groups [F(2,79) = 0.54, P = 0.58]. Conclusion The use of subdiaphragmatic lidocaine at the beginning of surgery combined with spinal anesthesia was not associated with a statistically significant difference in patients' postoperative VAS scores compared to spinal anesthesia and GA during and after gynecological surgical procedures. The study was registered in Iranian Registry of Clinical Trial by the number of IRCT2016022226698N1.
Towards Development of Correct Software using Views

This paper aims at integrating heterogeneous documents used in pragmatic software develpoment methods to describe views with a formal refinement based software development process. Therefore we propose an integrated semantics of heterogeneous documents based on a common system model and a set of syntactic development steps with a welldefined semantics for document evolution. The use of the development steps is demonstrated in a small example.
The effect of recent changes of food habits on bowel motility.

The recent changes in food habits in which the branny portion of the wheat berry has been almost entirely eliminated from the modern diet, has had two important effects. Firstly, th absence of the bulk-forming cereal fibre has occasioned a great reduction in the bowel content - a reduction that has not been compensated for by the increased consumption of fruit and vegetables. Secondly, it has effected a great reduction in the intake of the B complex vitamins. The recent rise in the incidence of gastro-intestinal disorders is believed to be associated with this dietetic change.
Big Business and Community Welfare

Building on research published by C. Wright Mills and Melville Ulmer in 1946, the relationships among community welfare and civic engagement, the independent middle class, and big business are examined. Manufacturing-dependent counties are the units of analysis. Partial correlation analysis is used to identify the effects of the independent and mediated effects of big business, civic engagement, and the independent middle class on community welfare. Results show that a local economy organized around smaller-scale, diversified enterprises has more favorable outcomes than one dominated by one or more large corporations. Copyright 2006 American Journal of Economics and Sociology, Inc.
Event‐related brain potentials show changed attentional mechanisms in Gilles de la Tourette Syndrome

In many patients the Gilles de la Tourette Syndrome (TS) is associated with the childhood Attention Deficit Hyperactivity Disorder. To gain a general view of attentional processes in TS we recorded event‐related brain potentials (ERPs) in 12 TS patients and in a matched control group. Four visual attention experiments with different levels of complexity were done (oddball task, pop‐out experiment, figure extraction and figure conjunction task). The reaction times did not differ significantly between groups. The Tourette patients' event‐related brain potentials showed an increased amplitude of the N2 component to targets in the simple oddball and pop‐out experiments. While both groups had similar P3b latencies to targets in the figure extraction experiment, Tourette patients responded less accurately in the most complex figure conjunction task and had increased P3b latencies. This is interpreted as evidence for a stronger attentional effort of the Tourette patients to obtain behavioural results similar to control subjects in easy attentional tasks. Consequently, Tourette patients show a reduced performance in complex attentional tasks.
An item response theory analysis of self-report measures of adult attachment.

Self-report measures of adult attachment are typically scored in ways (e.g., averaging or summing items) that can lead to erroneous inferences about important theoretical issues, such as the degree of continuity in attachment security and the differential stability of insecure attachment patterns. To determine whether existing attachment scales suffer from scaling problems, the authors conducted an item response theory (IRT) analysis of 4 commonly used self-report inventories: Experiences in Close Relationships scales (K. A. Brennan, C. L. Clark, & P. R. Shaver, 1998), Adult Attachment Scales (N. L. Collins & S. J. Read, 1990), Relationship Styles Questionnaire (D. W. Griffin & K. Bartholomew, 1994) and J. Simpson's (1990) attachment scales. Data from 1,085 individuals were analyzed using F. Samejima's (1969) graded response model. The authors' findings indicate that commonly used attachment scales can be improved in a number of important ways. Accordingly, the authors show how IRT techniques can be used to develop new attachment scales with desirable psychometric properties.