nils-herrmann/clean_scirepeval huggingface dataset:
Effect of intimate partner violence on health of women of Palestinian origin.
Venue: International nursing review

Intimate partner violence is a problem in women who are refugees but the relationship of this violence to physical health has not been studied well.  To identify significant associations between physical health problems and partner violence by type in refugee women.  For this cross sectional study, data were collected from a convenience sample of 238 women attending healthcare centres of the United Nations Relief and Works Agency for Palestine Refugees (UNRWA) in three Jordanian cities (Amman, Irbid and Zarqa) RESULTS Victims of violence reported different health problems. However, rates of health problems were higher among victims of psychological partner violence and more health problems had significant associations with psychological violence when compared to physical and sexual partner violence. Furthermore, women's self rated health status was only significantly associated with psychological partner violence but not with the other types of partner violence.  Vulnerability to partner violence is related to life stressors women may encounter. Physical health is a fundamental target for psychological partner violence; evidenced by the resultant wide range of health problems in victims. This association occurs although psychological violence is not associated with health trauma/injury that physical and sexual partner violence usually generate. This conclusion highlights one aspect of the associated harm of psychological partner violence in victims' lives.  with related community parties, should be an adopted international health policy by the governments. Screening policy for partner violence should be integrated with health and nursing services. Nurses are in a position to facilitate the implementation of health policy. Their role include helping women identify resources of help, develop required skills necessary for dealing with violence and identify their social support network.  Social desirability and use of convenience sampling are major limitations of the study.
A DESCRIPTIVE ANALYSIS OF ENGLISH INDONESIAN CODE SWITCHING SPOKEN BY THE TEACHER IN THE FIRST GRADE OF MTsN MODEL MAKASSAR

The research aims to analyse the English Indonesia Code Switching Spoken by the Teacher in First Grade of MTsN Model Makassar. The principal issue into several subproblems or research questions such as 1) What are grammatical aspects of code switching in English Indonesian code switching spoken by the teacher in the first grade of MTsN Model Makassar? 2) What are sosiolinguistic aspects of code switching in English Indonesian code switching spoken by the teacher in the first grade of MTsN Model Makassar? and 3) What is the function of code switching in English Indonesian code switching spoken by the teacher in the first grade of MTsN Model Makassar? The study was designed in the form of qualitative descriptive study. The subject in this study wasone of English teachers in the 7 th grade of MTsN Model Makassar who teaches the VII.11 class. The data were collected by using the methods of recording and writing on note of what teacher said in teaching learning process, then collected it and classified based on grammatical aspect of code switching, sociolinguistic aspect, and the function (phatic function) of code switching. A grammatical focuses on the structural aspect of code switching. While, a sociolinguistic approach is concerned with the role of social factors of code switching. The result of this research showed that the grammatical aspect of code switching are extrasentential/tag switching, intersentential switching, and intra word of code switching. Sociolinguistic aspects of code switching are situational and metaphorical switching. The function of code switching are referential function, directive function, phatic function and metalingustic function. But this thesis only focused on phatic function to clarify or emphasize a message. The achievement of this research can be used to make easier in teaching foreign language and can be used as additional source and also can develop code switching field in the next research.
Universal Dependencies for Learner English
Venue: ACL

We introduce the Treebank of Learner English (TLE) the first publicly available syntactic treebank for English as a Second Language (ESL) The TLE provides manually annotated POS tags and Universal Dependency (UD) trees for 5,124 sentences from the Cambridge First Certificate in English (FCE) corpus. The UD annotations are tied to a pre existing error annotation of the FCE, whereby full syntactic analyses are provided for both the original and error corrected versions of each sentence. Further on, we delineate ESL annotation guidelines that allow for consistent syntactic treatment of ungrammatical English. Finally, we benchmark POS tagging and dependency parsing performance on the TLE dataset and measure the effect of grammatical errors on parsing accuracy. We envision the treebank to support a wide range of linguistic and computational research on second language acquisition as well as automatic processing of ungrammatical language. The treebank is available at universaldependencies.org. The annotation manual used in this project and a graphical query engine are available at esltreebank.org.
Catchment scale High resolution Flash Flood Simulation Using the GPU based Technology

A number of studies have predicted more frequent and intensive storms as a result of climate change in UK and other parts of the world, which may consequently cause more hazardous flash floods in steep catchments of small to medium size (e.g. up to 100 km 2 These flash floods are commonly characterized by high velocity overland flow as a result of rapid catchment response to the intense rainfall. The hydrological processes related to the rapid catchment response are poorly understood and reliable prediction is generally beyond the capability of traditional hydrological models or simplified hydrodynamic models. This work aims to present a shock capturing hydrodynamic modelling system to simulate the complex rainfall runoff and the subsequent flash surface flooding process in a rapid response catchment. The model solves the fully 2D shallow water equations using a finite volume Godunov type shock capturing numerical scheme for the rapidly varying overland flow hydrodynamics following intense rainfall. Typically, this type of shock capturing hydrodynamic models is not able to provide efficient and high resolution simulations for large scale flash flood events due to their high computational demand. In order to substantially improve the computational efficiency and enable catchment scale simulations at very high resolution involving millions of computational nodes, the model is implemented on GPUs for high performance parallel computing. After being validated against the analytical benchmark of Tilted V catchment test, the GPU accelerated hydrodynamic modelling system is applied to simulate the rainfall runoff process in the 42 km 2 Haltwhistle Burn Catchment in England.
Real Time Contingency Measures to Cope with Rainfall Variability in Southern Karnataka

Real time contingency practices viz. selection of varieties, date of sowing, method of crop establishment, soil and moisture conservation practices were demonstrated in the Chikkamaranahalli cluster villages, Bengaluru rural district of Karnataka during 2011 to 2014. Selection of long duration variety (MR 1) for July sowing, medium duration (GPU 28) for August 1st fortnight and short duration (GPU 48) for August 2nd fort night performed better. In situ conservation moisture through opening of conservation furrow between paired rows of pigeonpea under finger millet pigeonpea (8: 2) and groundnut pigeonpea (8: 2) recorded significantly higher yields (2749 kg/ha and 1347 kg/ha, respectively) compared to farmers' practice. Among different methods of establishment in finger millet, transplanting recorded significantly higher grain yield (2461 kg/ha) and sowing of finger millet using modified bullock drawn seed drill recorded significantly higher yield (2417 kg/ha) compared to conventional method of broadcasting.
Sexual harassment at the workplace: how organizations can pro actively reduce its incidence

This paper aims to describe the role of human resources in organizations in preventing sexual harassment (SH) at the workplace.  This paper explains how SH is detrimental to the organization and why creating awareness about SH is essential for both men and women in the organization.  Findings show how organizations can pro actively prevent the incidence of SH by creating a zero tolerance for SH in organizations with top management commitment and the formulation and enforcement of a policy against SH.  The paper creates a case for proactive preventive measures such as sensitization, policy formulation and enforcement to combat SH in organizations rather than pursuing a reactive approach.
WELDON: Weakly Supervised Learning of Deep Convolutional Neural Networks
Venue: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

In this paper, we introduce a novel framework for WEakly supervised Learning of Deep cOnvolutional neural Networks (WELDON) Our method is dedicated to automatically selecting relevant image regions from weak annotations, e.g. global image labels, and encompasses the following contributions. Firstly, WELDON leverages recent improvements on the Multiple Instance Learning paradigm, i.e. negative evidence scoring and top instance selection. Secondly, the deep CNN is trained to optimize Average Precision, and fine tuned on the target dataset with efficient computations due to convolutional feature sharing. A thorough experimental validation shows that WELDON outperforms state of the art results on six different datasets.
Scanning Electron Microscopy Study of Hair Shaft Damage Secondary to Cosmetic Treatments of the Hair
Venue: International journal of trichology

Cosmetic procedures for hair, such as bleaching, dyeing, and straightening, are commonly used around the world. It has been suggested that excessive use of such procedures can cause damage to the hair shaft. We aimed to assess hair shaft changes using scanning electron microscopy (SEM) in female volunteers who frequently use hair treatment procedures such as bleaching, dyeing, or straightening.  A cross sectional, controlled study in a sample of 25 female volunteers (19 study group and 6 controls) in the age group of 18 45 years. The study group was composed of volunteers who regularly used different cosmetic hair treatment procedures such as bleaching, dyeing, and straightening (any one of these or a combination) The control group had never used any specific hair treatment procedure. The hair shaft damage as seen on SEM was assessed using a standardized scoring system and compared among the two groups statistically. The hair shafts were also examined clinically and with light microscopy.  No significant differences were seen between the test and control groups with regard to normal clinical examination and light microscopy findings. A higher degree of hair shaft damage was evident under SEM in the study group as compared to the control group. This difference was statistically significant.  Regular use of procedures such as bleaching, dyeing, or straightening can lead to subtle changes in the hair shaft which can be detected early by SEM.
Evolutionary K Means with pair wise constraints
Venue: Soft Comput.

K Means users usually have to decide on the number of clusters and the initial state by themselves. Evolutionary K Means (EKM) a hybrid algorithm of K Means and genetic algorithm, solves the problem by choosing the two parameters automatically through partition evolution; however, the final partition obtained often doesn't meet users' expectations. As a solution to this problem, we suggest using background knowledge for enhancing clustering quality and propose a semi supervised approach that incorporates instance level constraints into the objective function of EKM. Firstly, we define Constrained Silhouette Index (CS) for data instances, which decreases the silhouette index of the instance having violated constraints. Then, we present two weighted approaches to extend the influence of constraints beyond the level of instance for evaluating the quality of a cluster or a partition. To evaluate the performance of CS in guiding EKM algorithms, we combine the two types of CS with F EAC algorithm, and get two constrained EKM algorithms, which are named as CEAC1 and CEAC2, respectively. Experimental results on two artificial datasets and eight UCI datasets suggest a few constraints are often powerful enough to improve the accuracy of labelling instances and choosing K, and more constraints may improve the performance even more.
Constrained clustering for flocking based tracking in maneuvering target environment
Venue: Robotics Auton. Syst.

Self organizing ability is one of the most important requirements of modern sensor networks; particularly for tracking maneuvering targets. Flocking based approaches are biologically inspired methods that have recently gained significant attention to address the control and coordination problem in self organizing sensor networks. These approaches are exemplified by the two well known algorithms, namely, the Flocking and the Semi Flocking algorithms. Although these two algorithms have demonstrated promising performance in tracking linear target(s) they have deficiencies in tracking maneuvering targets.This paper introduces a constrained clustering approach that uses a novel extension of K means algorithm to provide better coverage over maneuvering targets. This extension clusters the sensors based on certain background knowledge, then uses the information about the clusters to improve coverage. The performances of flocking based algorithms, both with and without the proposed approach, are examined in tracking both linear and maneuvering targets. Experimental results demonstrate how constrained clustering yields better tracking of maneuvering targets, and how applying constraints on the clustering process improves the quality of clustering and increases the speed of convergence.
Exploiting flexible constrained K means clustering with word embedding for aspect phrase grouping
Venue: Inf. Sci.

Aspect phrase grouping is an important task for aspect finding in sentiment analysis. Most existing methods for this task are based on a window context model, which assumes that the same aspect has similar co occurrence contexts. This model does not always work well in practice. In this paper, we develop a novel weighted context representation model based on semantic relevance, which exploits word embedding method to represent aspect phrase. And we encode the lexical knowledge as constraints with a degree of belief, and further propose a flexible constrained K means algorithm to cluster aspect phrases. Empirical evaluation shows that the proposed method outperforms existing state of the art methods.
Colored selective absorber coating with excellent durability

The colored solar thermal collectors can provide advantages of architectural integration over energy performance. The colour appearance of the solar thermal collectors can be achieved by increasing the number of layers. W/WAlN/WAlON/Al2O3 coating, fabricated by DC and RF magnetron sputtering showed a high solar absorptance of 0.948 and the low thermal emittance of 0.08 with a sky blue color appearance. The tandem absorber exhibited excellent long term thermal stability at 500 degrees C in air for 150 h. The absorber deposited on SS substrates showed high solar selectivity (alpha/epsilon) of 0.918/0.11, even after heat treatment in air up to 500 degrees C for 100 h. The selective performance of the coating can be stable more than 25 years. The humidity test confirms the significant moisture resistant of the coating. In summary, the new W/WAlN/WAlON/Al2O3 based coating with its colourful appearance is appropriate to be used in solar thermal collectors.
The Structural Virality of Online Diffusion
Venue: Manag. Sci.

Viral products and ideas are intuitively understood to grow through a person to person diffusion process analogous to the spread of an infectious disease; however, until recently it has been prohibitively difficult to directly observe purportedly viral events, and thus to rigorously quantify or characterize their structural properties. Here we propose a formal measure of what we label "structural virality" that interpolates between two conceptual extremes: content that gains its popularity through a single, large broadcast and that which grows through multiple generations with any one individual directly responsible for only a fraction of the total adoption. We use this notion of structural virality to analyze a unique data set of a billion diffusion events on Twitter, including the propagation of news stories, videos, images, and petitions. We find that across all domains and all sizes of events, online diffusion is characterized by surprising structural diversity; that is, popular events regularly grow via both broadcast and viral mechanisms, as well as essentially all conceivable combinations of the two. Nevertheless, we find that structural virality is typically low, and remains so independent of size, suggesting that popularity is largely driven by the size of the largest broadcast. Finally, we attempt to replicate these findings with a model of contagion characterized by a low infection rate spreading on a scale free network. We find that although several of our empirical findings are consistent with such a model, it fails to replicate the observed diversity of structural virality, thereby suggesting new directions for future modeling efforts. This paper was accepted by Lorin Hitt, information systems.
Ego network structure in online social networks and its impact on information diffusion
Venue: Comput. Commun.

In the last few years, Online Social Networks (OSNs) attracted the interest of a large number of researchers, thanks to their central role in the society. Through the analysis of OSNs, many social phenomena have been studied, such as the viral diffusion of information amongst people. What is still unclear is the relation between micro level structural properties of OSNs (i.e. the properties of the personal networks of the users, also known as ego networks) and the emergence of such phenomena. A better knowledge of this relation could be essential for the creation of services for the Future Internet, such as highly personalised advertisements fitted on users' needs and characteristics. In this paper, we contribute to bridge this gap by analysing the ego networks of a large sample of Facebook and Twitter users. We show that micro level structural properties of OSNs are interestingly similar to those found in social networks formed offline. In particular, online ego networks show the same structure found offline, with social contacts arranged in layers with compatible size and composition. From the analysis of Twitter ego networks, we have been able to find a direct impact of tie strength and ego network circles on the diffusion of information in the network. Specifically, there is a high correlation between the frequency of direct contact between users and her friends in Twitter (a proxy for tie strength) and the frequency of retweets made by the users from tweets generated by their friends. We analysed the correlation for each ego network layer identified in Twitter, discovering their role in the diffusion of information.
Development and Application of CT SPI Model for Improving Computational Thinking for Elementary School Students

In this paper, we propose a CT SPI Model based on a physical computing for improving Computational Thinking(CT) for elementary students. This study analyzes the results obtained from applying the CT SPI model to fourth grade class. The model is designed to embrace the learning activities and CT elements for three different stages: System thinking, Prototyping and Interaction. For providing curriculum with CT SPI model, physical SW educational module is developed, so that learners could focus on internalizing CT. The study results indicate that a learning satisfaction and a degree of learner interest improve significantly. Comprehensive CT capability assessment results in three levels show that the capability in lowest level (score is below 4 out of 10) has decreased by 46.6% but capability in highest level (over 7 out of 10) has increased by 20%
MRIQC: Predicting Quality in Manual MRI Assessment Protocols Using No Reference Image Quality Measures

Quality control of MR images is essential for excluding problematic acquisitions and avoiding bias in subsequent image processing and analysis. However, the visual inspection of individual images is time consuming and limited by both intra and inter rater variance. The difficulty of visual inspection scales with study size and with the heterogeneity of multi site data. Here, we describe a tool for the automated assessment of Tl weighted MR images of the brain MRIQC. MRIQC calculates a set of quality measures from each image and uses them as features in a binary (include/exclude) classifier. The classifier was designed to ensure generalization to new samples acquired in different centers and using different scanning parameters from our training dataset. To achieve that goal, the classifier was trained on the Autism Brain Imaging Data Exchange (ABIDE) dataset (N=1102) acquired at 17 locations with heterogeneous scanning parameters. We selected random forests from a set of models and pre processing options using nested cross validation on the ABIDE dataset. We report a performance of ~89% accuracy of the best model evaluated with nested cross validation. The best performing classifier was then evaluated on a held out (unseen) dataset, unrelated to ABIDE and labeled by a different expert, yielding ~73% accuracy. The MRIQC software package and the trained classifier are released as an open source project, so that individual researchers and large consortia can readily curate their data regardless the size of their databases. Robust QC is crucial to identify early structured imaging artifacts in ongoing acquisition efforts, and helps detect individual substandard images that may bias downstream analyses.
Chapter 3: Research Support Services in Academic Libraries in Uganda: Challenges and Opportunities

Changing pedagogy and rapid growth of enabling technologies has significantly influenced research trends and processes within the higher education research ecosystem. These changes have triggered a series of positive responses from academic libraries such as the re evaluation of their approach to research support services. The expansion of the suite of research support services such as bibliometrics, systematic reviews, data management, digital preservation and curation,  This transition is viewed by many as revolutionary in terms of support for research production.The International Federation of Library Associations and Institutions' Academic and Research Libraries Standing Committee's preconference was held in Cape Town, South Africa, between 13 and 14 August 2015. The theme of the preconference was The quest for deeper meaning of research support. There was a blend of papers with young researchers sharing empirical research information while seasoned LIS researchers and practitioners shared 'best case practices'