nils-herrmann/clean_scirepeval huggingface dataset:
Occupational therapy outcomes for clients with traumatic brain injury and stroke using the Canadian Occupational Performance Measure.

The purpose of this study was to determine whether 155 ethnically diverse clients with traumatic brain injury (TBI) and stroke (cerebrovascular accident; CVA) who received occupational therapy services perceived that they reached self-identified goals related to tasks of daily life as measured by the Canadian Occupational Performance Measure (COPM). This study found that a statistically and clinically significant change in self-perceived performance and satisfaction with tasks of daily life occurred at the end of a client-centered occupational therapy program (p < .001). There were no significant differences in performance and satisfaction between the TBI and CVA groups. However, the group with right CVA reported a higher level of satisfaction with performance in daily activities than the group with left CVA (p = .03). The COPM process can effectively assist clients with neurological impairments in identifying meaningful occupational performance goals. The occupational therapist also can use the COPM to design occupation-based and client-centered intervention programs and measure occupational therapy outcomes.
AN INNOVATIVE MOVING OBJECT DETECTION AND TRACKING SYSTEM BY USING MODIFIED REGION GROWING ALGORITHM

The ultimate goal of this study is to afford enhanced video object detection and tracking by eliminating the limitations which are existing nowadays. Although high performance ratio for video object detection and tracking is achieved in the earlier work it takes more time for computation. Consequently we are in need to propose a novel video object detection and tracking technique so as to minimize the computational complexity. Our proposed technique covers five stages they are preprocessing, segmentation, feature extraction, background subtraction and hole filling. Originally the video clip in the database is split into frames. Then preprocessing is performed so as to get rid of noise, an adaptive median filter is used in this stage to eliminate the noise. The preprocessed image then undergoes segmentation by means of modified region growing algorithm. The segmented image is subjected to feature extraction phase so as to extract the multi features from the segmented image and the background image, the feature value thus obtained are compared so as to attain optimal value, consequently a foreground image is attained in this stage. The foreground image is then subjected to morphological operations of erosion and dilation so as to fill the holes and to get the object accurately as these foreground image contains holes and discontinuities. Thus the moving object is tracked in this stage. This method will be employed in MATLAB platform and the outcomes will be studied and compared with the existing techniques so as to reveal the performance of the novel video object detection and tracking technique.
Maternal neglect: oxytocin, dopamine and the neurobiology of attachment.

Maternal neglect, including physical and emotional neglect, is a pervasive public health challenge with serious long-term effects on child health and development. I provide an overview of the neurobiological basis of maternal caregiving, aiming to better understand how to prevent and respond to maternal neglect. Drawing from both animal and human studies, key biological systems are identified that contribute to maternal caregiving behaviour, focusing on the oxytocinergic and dopaminergic systems. Mesocorticolimbic and nigrostriatal dopamine pathways contribute to the processing of infant-related sensory cues leading to a behavioural response. Oxytocin may activate the dopaminergic reward pathways in response to social cues. Human neuroimaging studies are summarised that demonstrate parallels between animal and human maternal caregiving responses in the brain. By comparing different patterns of human adult attachment, we gain a clearer understanding of how differences in maternal brain and endocrine responses may contribute to maternal neglect. For example, in insecure/dismissing attachment, which may be associated with emotional neglect, we see reduced activation of the mesocorticolimbic dopamine reward system in response to infant face cues, as well as decreased peripheral oxytocin response to mother-infant contact. We are currently testing whether the administration of intranasal oxytocin, as part of a randomised placebo controlled trial, may reverse some of these neurological differences, and potentially augment psychosocial and behavioural interventions for maternal neglect.
Dissociating valence of outcome from behavioral control in human orbital and ventral prefrontal cortices.

The precise role of orbitofrontal cortex (OFC) in affective processing is still debated. One view suggests OFC represents stimulus reward value and supports learning and relearning of stimulus-reward associations. An alternate view implicates OFC in behavioral control after rewarding or punishing feedback. To discriminate between these possibilities, we used event-related functional magnetic resonance imaging in subjects performing a reversal task in which, on each trial, selection of the correct stimulus led to a 70% probability of receiving a monetary reward and a 30% probability of obtaining a monetary punishment. The incorrect stimulus had the reverse contingency. In one condition (choice), subjects had to choose which stimulus to select and switch their response to the other stimulus once contingencies had changed. In another condition (imperative), subjects had simply to track the currently rewarded stimulus. In some regions of OFC and medial prefrontal cortex, activity was related to valence of outcome, whereas in adjacent areas activity was associated with behavioral choice, signaling maintenance of the current response strategy on a subsequent trial. Caudolateral OFC-anterior insula was activated by punishing feedback preceding a switch in stimulus in both the choice and imperative conditions, indicating a possible role for this region in signaling a change in reward contingencies. These results suggest functional heterogeneity within the OFC, with a role for this region in representing stimulus-reward values, signaling changes in reinforcement contingencies and in behavioral control.
Analysis of length of hospital stay using electronic health records: A statistical and data mining approach

The length of stay (LOS) is an important indicator of the efficiency of hospital management. Reduction in the number of inpatient days results in decreased risk of infection and medication side effects, improvement in the quality of treatment, and increased hospital profit with more efficient bed management. The purpose of this study was to determine which factors are associated with length of hospital stay, based on electronic health records, in order to manage hospital stay more efficiently.



Research subjects were retrieved from a database of patients admitted to a tertiary general university hospital in South Korea between January and December 2013. Patients were analyzed according to the following three categories: descriptive and exploratory analysis, process pattern analysis using process mining techniques, and statistical analysis and prediction of LOS.



Overall, 55% (25,228) of inpatients were discharged within 4 days. The department of rehabilitation medicine (RH) had the highest average LOS at 15.9 days. Of all the conditions diagnosed over 250 times, diagnoses of I63.8 (cerebral infarction, middle cerebral artery), I63.9 (infarction of middle cerebral artery territory) and I21.9 (myocardial infarction) were associated with the longest average hospital stay and high standard deviation. Patients with these conditions were also more likely to be transferred to the RH department for rehabilitation. A range of variables, such as transfer, discharge delay time, operation frequency, frequency of diagnosis, severity, bed grade, and insurance type was significantly correlated with the LOS.



Accurate understanding of the factors associating with the LOS and progressive improvements in processing and monitoring may allow more efficient management of the LOS of inpatients.
Translational biomarker discovery in clinical metabolomics: an introductory tutorial

Metabolomics is increasingly being applied towards the identification of biomarkers for disease diagnosis, prognosis and risk prediction. Unfortunately among the many published metabolomic studies focusing on biomarker discovery, there is very little consistency and relatively little rigor in how researchers select, assess or report their candidate biomarkers. In particular, few studies report any measure of sensitivity, specificity, or provide receiver operator characteristic (ROC) curves with associated confidence intervals. Even fewer studies explicitly describe or release the biomarker model used to generate their ROC curves. This is surprising given that for biomarker studies in most other biomedical fields, ROC curve analysis is generally considered the standard method for performance assessment. Because the ultimate goal of biomarker discovery is the translation of those biomarkers to clinical practice, it is clear that the metabolomics community needs to start “speaking the same language” in terms of biomarker analysis and reporting-especially if it wants to see metabolite markers being routinely used in the clinic. In this tutorial, we will first introduce the concept of ROC curves and describe their use in single biomarker analysis for clinical chemistry. This includes the construction of ROC curves, understanding the meaning of area under ROC curves (AUC) and partial AUC, as well as the calculation of confidence intervals. The second part of the tutorial focuses on biomarker analyses within the context of metabolomics. This section describes different statistical and machine learning strategies that can be used to create multi-metabolite biomarker models and explains how these models can be assessed using ROC curves. In the third part of the tutorial we discuss common issues and potential pitfalls associated with different analysis methods and provide readers with a list of nine recommendations for biomarker analysis and reporting. To help readers test, visualize and explore the concepts presented in this tutorial, we also introduce a web-based tool called ROCCET (ROC Curve Explorer & Tester, http://www.roccet.ca ). ROCCET was originally developed as a teaching aid but it can also serve as a training and testing resource to assist metabolomics researchers build biomarker models and conduct a range of common ROC curve analyses for biomarker studies.
Improving penetration testing through static and dynamic analysis

Penetration testing is widely used to help ensure the security of web applications. Using penetration testing, testers discover vulnerabilities by simulating attacks on a target web application. To do this efficiently, testers rely on automated techniques that gather input vector information about the target web application and analyze the application’s responses to determine whether an attack was successful. Techniques for performing these steps are often incomplete, which can leave parts of the web application untested and vulnerabilities undiscovered. This paper proposes a new approach to penetration testing that addresses the limitations of current techniques. The approach incorporates two recently developed analysis techniques to improve input vector identification and detect when attacks have been successful against a web application. This paper compares the proposed approach against two popular penetration testing tools for a suite of web applications with known and unknown vulnerabilities. The evaluation results show that the proposed approach performs a more thorough penetration testing and leads to the discovery of more vulnerabilities than both the tools.
Narrative , Identity , and the Politics of Exclusion : Social Change and the Gay and Lesbian Life Course

The social and political context of sexual identity development in the United States has changed dramatically since the mid twentieth century. Same-sex attracted individuals have long needed to reconcile their desire with policies of exclusion, ranging from explicit outlaws on same-sex activity to exclusion from major social institutions such as marriage. This paper focuses on the implications of political exclusion for the life course of individuals with same-sex desire through the analytic lens of narrative. Using illustrative evidence from a study of autobiographies of gay men spanning a 60-year period and a study of the life stories of contemporary same-sex attracted youth, we detail the implications of historic silence, exclusion, and subordination for the life course.
Development of maximum power point tracker for PV panels using SEPIC converter

"Photovoltaic panel maximum power point tracker". As the name implied, it is a photovoltaic system that uses the photovoltaic array as a source of electrical power supply and since every photovoltaic (PV) array has an optimum operating point, called the maximum power point, which varies depending on cell temperature, the insolation level and array voltage. A maximum power point tracker (MPPT) is needed to operate the PV array at its maximum power point. The objective of this paper is to build MPPT to charge a 12-volts lead acid battery by using a (TBP1275) 74 - watts PV panel. A technique for efficiency extracting the maximum output power from a solar panel under varying meteorological conditions is presented. The methodology is based on connecting a pulse width modulated dc/dc SEPIC converter, which is controlled by a micro controller based unit. The main difference between the method used in the proposed MPPT systems and other technique used in the past is that PV array output power is used to directly control the dc/dc converter thus reducing the complexity of the system. The resulting system has high efficiency, low cost and can be easily modified. This approach ensured maximum power transfer under all conditions by using micro controller for calculation. The tracking capability of the proposed technique has been verified experimentally with a 74 W solar panel at different insolation levels.
Design and control for a compliant knee exoskeleton

In this paper, we design a novel knee exoskeleton. The designed exoskeleton has a 1 DOF with knee joint actuated in the sagittal plane. The exoskeleton is actuated base on Series Elastic Actuator (SEA) instead of traditonal stiff actuator. SEA is a compliant actuator, having the advantages of low output impedance, low friction, high quality force control and backdrivability. Thanks to these nice characteristics, it is easy to realize a safe and friendly human-machine interaction compare with traditonal stiff actuator. In order to achieve the goal of assistance as needed, a robust force control must be guaranteed. Sliding-Mode Control (SMC) is a way to robust force control. Instead of using the standard SMC, we employ Integral Sliding-Mode Control Algorithm (ISM) to avoid reaching phase, where the performance of system is not so good. Meanwhile, we also use continuous approximation of SMC, which can eliminate the effect of chattering. To verify the efficiency of ISM, we excutes the torque tarcking experiments. We also use the classical PID algorithm to compare with ISM. From the results of experiments, ISM outperform much better than PID, tracking the torque trajectory with high accuracy whereas employing PID produce high errors.
Subband-Based Group Delay Segmentation of Spontaneous Speech into Syllable-Like Units

In the development of a syllable-centric automatic speech recognition (ASR) system, segmentation of the acoustic signal into syllabic units is an important stage. Although the short-term energy (STE) function contains useful information about syllable segment boundaries, it has to be processed before segment boundaries can be extracted. This paper presents a subband-based group delay approach to segment spontaneous speech into syllable-like units. This technique exploits the additive property of the Fourier transform phase and the deconvolution property of the cepstrum to smooth the STE function of the speech signal and make it suitable for syllable boundary detection. By treating the STE function as a magnitude spectrum of an arbitrary signal, a minimum-phase group delay function is derived. This group delay function is found to be a better representative of the STE function for syllable boundary detection. Although the group delay function derived from the STE function of the speech signal contains segment boundaries, the boundaries are difficult to determine in the context of long silences, semivowels, and fricatives. In this paper, these issues are specifically addressed and algorithms are developed to improve the segmentation performance. The speech signal is first passed through a bank of three filters, corresponding to three different spectral bands. The STE functions of these signals are computed. Using these three STE functions, three minimum-phase group delay functions are derived. By combining the evidence derived from these group delay functions, the syllable boundaries are detected. Further, a multiresolutionbased technique is presented to overcome the problem of shift in segment boundaries during smoothing. Experiments carried out on the Switchboard and OGI-MLTS corpora show that the error in segmentation is at most 25milliseconds for 67% and 76.6% of the syllable segments, respectively.
Evaluation of Multiple-F0 Estimation and Tracking Systems

Multi-pitch estimation of sources in music is an ongoing research area that has a wealth of applications in music information retrieval systems. This paper presents the systematic evaluations of over a dozen competing methods and algorithms for extracting the fundamental frequencies of pitched sound sources in polyphonic music. The evaluations were carried out as part of the Music Information Retrieval Evaluation eXchange (MIREX) over the course of two years, from 2007 to 2008. The generation of the dataset and its corresponding ground-truth, the methods by which systems can be evaluated, and the evaluation results of the different systems are presented and discussed.
Bridging the Gap between Probabilistic and Deterministic Models: A Simulation Study on a Variational Bayes Predictive Coding Recurrent Neural Network Model

The current paper proposes a novel variational Bayes predictive coding RNN model, which can learn to generate fluctuated temporal patterns from exemplars. The model learns to maximize the lower bound of the weighted sum of the regularization and reconstruction error terms. We examined how this weighting can affect development of different types of information processing while learning fluctuated temporal patterns. Simulation results show that strong weighting of the reconstruction term causes the development of deterministic chaos for imitating the randomness observed in target sequences, while strong weighting of the regularization term causes the development of stochastic dynamics imitating probabilistic processes observed in targets. Moreover, results indicate that the most generalized learning emerges between these two extremes. The paper concludes with implications in terms of the underlying neuronal mechanisms for autism spectrum disorder and for free action.
3 Westernization : The Role of Mass Media on Body Image and Eating Disorders

This chapter aims to illustrate the relationship between sociocultural globalisation and body image – globalising mechanisms appear to disseminate the Western standard of female and male beauty. Thus, the combination of ubiquitous messages for eating behaviours and beauty in both advertising and mass media programming may lead to confusion and body image dissatisfaction amongst many young people. The aim is to examine the framework of causality of culturally-induced manifestations of eating and body image disorders by gender and, in particular, to examine the role that the mass media plays in the development of male and female body attitudes regarding ideal body images and how this may in turn have an impact on their mental health.
A bibliometric chronicling of library and information science's first hundred years

This paper presents a condensed history of LIS over the course of more than a century using a variety of bibliometric measures. It examines in detail the variable rate of knowledge production in the field, shifts in subject coverage, the dominance of particular publication genres at different times, prevailing modes of production, interactions with other disciplines, and, more generally, observes how the field has evolved. It shows that, despite a striking growth in the number of journals, papers and contributing authors, a decrease was observed in the field’s market-share of all social science and humanities research. Collaborative authorship is now the norm, a pattern seen across the social sciences. The idea of boundary crossing was also examined: in 2010, nearly 60% of authors who published in LIS also published in another discipline. This high degree of permeability in LIS was also demonstrated through reference and citation practices: LIS scholars now cite and receive citations from other fields more than from LIS itself. Two major structural shifts are revealed from the data: in 1960, where LIS changed from a professional field focused on librarianship to an academic field focused on information and use and in 1990, when LIS began to receive a growing number of citations from outside the field, notably from Computer Science and Management, as well as a dramatic increase in the number of authors contributing to the literature of the field.
Comparison of Web Service Testing Tools

Web Services are considered an essential services-oriented technology today on networked application architectures due to their language and platform-independence. Their language and platform independence also brings difficulties in testing them especially in an automated manner. In this paper, a comparative evaluation of testing techniques based on, TTCN-3 and SoapUI, in order of contributing towards resolving these difficulties is performed. Aspects of TTCN-3 and SoapUI are highlighted, including test abstraction, performance efficiency and powerful matching mechanisms in TTCN-3 that allow a separation between behaviour and the conditions governing behaviour.  Web Services Testing, Automated Testing, Web Testing, SoapUI, TTCN-3, Titan TTCN-3, Testing
Design and Comparison of Digital Filters for Removal of Baseline Wandering from ECG Signal

Heart diseases, which are one of the death reasons, are among the several serious problems in this century and as per the latest survey, 60% of the patients die due to Heart problems. These diseases can be diagnosed by ECG (Electrocardiogram) signals. ECG measures electrical potentials on the body surface via contact electrodes thus it is very important signal in cardiology. Different artifacts affect the ECG signals which can thus cause problems in analyzing the ECG Thus signal processing schemes are applied to remove those interferences. The work proposed in this paper is removal of low frequency interference i.e. baseline wandering in ECG signal and digital filters are designed to remove it. The digital filters designed are FIR with different windowing methods as of Rectangular, Gaussian, Hamming, and Kaiser. The results obtained are at a low order of 56. The signals are taken from the MIT-BIH database which includes the normal and abnormal waveforms. The work has been done in MAT LAB environment where filters are designed in FDA Tool. The parameters are selected such that the noise is removed permanently. Also the best results are obtained at an order of 56 which makes hardware implementation easier. The result obtained for all FIR filters with different windows are compared by comparing the waveforms and power spectrums of the original and filtered ECG signals. The filters which gives the best results is the one using Kaiser Window.