nils-herrmann/clean_scirepeval huggingface dataset:
Coagulation parameters and major bleeding in critically ill patients with cirrhosis
Venue: Hepatology

Disturbances of coagulation and hemostasis are common in patients with liver cirrhosis. The typical laboratory pattern mimics disseminated intravascular coagulation (DIC) The aim of this study was to assess the impact of routine coagulation parameters in critically ill cirrhosis patients with regard to new onset of major bleeding and outcome. A total of 1,493 critically ill patients were studied prospectively. Routine coagulation parameters were assessed, and the DIC score was calculated based on platelets, fibrinogen, d dimer, and prothrombin index. New onset of major bleeding during the stay at the intensive care unit and mortality were assessed. Patients were followed for 1 year. Two hundred eleven patients of the cohort had liver cirrhosis. Platelets, fibrinogen, prothrombin index, activated partial thromboplastin time, and d dimer as well as the DIC score differed significantly between patients with and without cirrhosis (P 0.001 for all) Moreover, fibrinogen, platelets, and activated partial thromboplastin time (but not prothrombin index) differed significantly between cirrhosis patients with and without major bleeding (P 0.01 for all) Bleeding on admission, platelet count <30 109/L, fibrinogen level <60 mg/dL, and activated partial thromboplastin time values >100 seconds were the strongest independent predictors for new onset of major bleeding in multivariate regression analysis. One year mortality in cirrhosis patients with and without major bleeding was 89% and 68% respectively (P 0.05 between groups)  Abnormal coagulation parameters and high DIC scores (primarily due to fibrinogen and platelets) correspond to increased bleeding risk in patients with liver cirrhosis in the intensive care unit, and fibrinogen and platelet count were identified as the best routine coagulation parameters for prediction of new onset of major bleeding; however, further studies are required to evaluate the potential therapeutic implications of these findings. (Hepatology 2016;64:556 568)
Large scale multi label text classification of a hierarchical dataset using Rocchio algorithm
Venue: 2016 International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS)

Hierarchical data is becoming increasingly prominent, especially on the web. Wikipedia is one such example where there are millions of documents that are classified into multiple classes in a hierarchical fashion. This gives rise to an interesting problem of automating the classification of new documents. As the size of the dataset grows, so does the number of classes. Further, there seems to be sparsity issue even with the increase in the dataset. Therefore, this poses a challenge to classify data in such a manner. We present two different algorithms based on text categorization: Rocchio algorithm and kNN. We implement and compare the above mentioned methods to better understand the approach to take in classifying hierarchical data.
Motivational Factors for the Master s Degree a Comparison between Students in Accounting And Economics in the Light of the Self Determination Theory

The general aim of this study was identifying the motivational level of students in Accounting and Economics regarding the search for a stricto sensu graduate degree. Also, it sought to determine the variables that significantly influence the motivation of these individuals. Having the Self Determination Theory as a basis, a questionnaire was prepared resorting to the Academic Motivation Scale developed by Vallerand, Pelletier, Blais, Briere, Senecal, and Vallieres (1992) and translated into Portuguese by Sobral (2003) The database contains observations of 173 university students from public institutions in Minas Gerais, Brazil, which provided courses in Accounting and Economics. The methodological procedure consisted in conducting a non parametric test of mean values for the Motivation Self Determination Index (MSI) of students, in calculating the correlations between the MSI and individual characteristics of students, and finally in estimating multiple linear regressions. Research results indicated that students in Accounting showed no difference regarding the motivational level when compared to students in Economics. It was also possible to notice that women, older students, scientific initiation scholarship holders, those from lower socioeconomic backgrounds, and those whose mothers have higher educational level tend to have a rather self determined motivation. Additionally, it was found that insertion into the labor market increases self determined motivation to pursue a stricto sensu Master's degree only in the case of students in Accounting. The research was limited to the fact that the sample only included students of public education institutions from Minas Gerais. For future research, it is suggested that the procedures of this study be replicated in privet institution and in different states.
Keyphrase Extraction Using Deep Recurrent Neural Networks on Twitter
Venue: EMNLP

Keyphrases can provide highly condensed and valuable information that allows users to quickly acquire the main ideas. The task of automatically extracting them have received considerable attention in recent decades. Different from previous studies, which are usually focused on automatically extracting keyphrases from documents or articles, in this study, we considered the problem of automatically extracting keyphrases from tweets. Because of the length limitations of Twitter like sites, the performances of existing methods usually drop sharply. We proposed a novel deep recurrent neural network (RNN) model to combine keywords and context information to perform this problem. To evaluate the proposed method, we also constructed a large scale dataset collected from Twitter. The experimental results showed that the proposed method performs significantly better than previous methods.
Cloud adaptiveness within industry sectors Measurement and observations

Cloud computing combines established computing technologies and outsourcing advantages into a new ICT paradigm that is generally expected to foster productivity and economic growth. However, despite a series of studies on the drivers of cloud adoption, evidence of its economic effects is lacking, possibly because many of the datasets on cloud computing are of insufficient size and often lack a time dimension as well as precise definitions of cloud computing, thus making them unsuitable for rigorous quantitative analysis. To overcome these limitations, we propose a proxy variable for cloud computing usage cloud adaptiveness based on survey panel data from European firms. Observations based on a descriptive analysis suggest three important aspects for further research. First, cloud studies should be conducted at the industry level as cloud computing adaptiveness differs widely across industry sectors. Second, it is important to know what firms do with cloud computing to understand the economic mechanisms and effects triggered by this innovation. And third, cloud adaptiveness is potentially correlated to a firm's position in the supply chain and thus the type of output it produces as well as the market in which it operates. Our indicator can be employed to further analyze the effects of cloud computing in the context of firm heterogeneity. We propose a measure for cloud computing using existing datasets.Our empirical findings map out an agenda for future research.Cloud studies should be at the industry level.Researchers need to figure out what firms actually do with cloud computing.Studying cloud usage across the value chain helps understanding the mechanisms.
A Review Evaluating the Validity of Motion Based Gaming Platforms to Measure Clinical Outcomes in Clinical Research

Motion based video game platforms provide the capability to track 3D body movements and may offer a versatile, easy to use and low cost approach to measuring objective clinical outcomes. We reviewed published validation studies comparing clinical outcomes derived from video game platforms to gold standard approaches.  We categorized studies in our review into three areas of application and summarized validation findings. We confined our review to studies using the Microsoft Kinect platform due to the volume of work in this area.  Gait and balance: Five validation studies reported varied findings. One study in MS reported good correlation of most parameters with ClinROs; and a second study reported good validation of walk test parameters in Stroke patients. A treadmill test in healthy volunteers found Kinect underestimated joint flexion and over estimated extension; and a further study was able to detect gait disturbances in MS during a speed walking test compared to healthy volunteers although correlation to clinician assessment was modest (r=0.447) Kinect use during a battery of balance and dexterity tests in PD accurately measured the timing (ICCs: 0.940 0.999) and gross spatial characteristics of clinically relevant movements, but spatial accuracy for smaller movements, such as toe tapping (ICC 0.038) was poor. Upper extremity movement: Eight studies reported good validity in measurement of shoulder range of motion (r's 0.8, ICCs 0.864) Spirometry: One study reported strong correlation of spirometry parameters (r>0.866) estimated using multiple sensors to generate a 3D image of the chest.  Motion based video gaming platforms offer potential for low cost assessment of movement and mobility in large scale clinical trials without reliance on specialist centers. Studies report good validity in some application areas. The ability to provide the level of accuracy needed in more rapid and finer movements requires more validation work.
EXPERIMENTAL STUDY ON COMPOSITE SOLID PROPELLANT MATERIAL BURNING RATE USING MATLAB ALGORITHM

In rock etry ap pli ca tion, now a days in stead of monopropellants slowly com pos ite pro pel lants are in tro duced. Burn ing rate of a solid state com pos ite pro pel lant de pends on many fac tors like ox i dizer binder ra tio, ox i dizer par ti cle size and dis tri bu tion, par ti cle size and its dis tri bu tion, pres sure, tem per a ture, etc. Sev eral re search ers had taken the mass var ied com pos ite pro pel lant. In that, the am mo nium perchlorate mainly var ied from 85 to 90% This pa per deals with the ox i dizer rich pro pel lant by al low ing small vari a tion of fuel cum binder rang ing from 2% 4% 6% and 8% by mass. Since the per cent of the binder is very less com pared to the ox i dizer, the mix ture re mains in a pow der form. The pow der sam ples are used to make a pressed pel let. Experiments were con ducted in closed win dow bomb set up at pres sures of 2, 3.5, and 7 MN/m. The burn ing rates are cal cu lated from the com bus tion pho tog ra phy (im ages) taken by a high speed cam era. These im ages were pro cessed frame by frame in MATLAB, de tect ing the edges in the im ages of the frames. The burn ing rate is ob tained as the slope of the lin ear fit from MATLAB and ob served that the burn rate in creases with the mass vari a tion of con stit u ents pres ent in solid state com pos ite pro pel lant. The re sult in di cates a re mark able in crease in burn rate of 26.66% 20% 16.66% and 3.33% for Mix 1, 2, 3, 4 com pared with Mix 5 at 7 MN/m. The per cent age vari a tions in burn rate be tween Mix 1 and Mix 5 at 2, 3.5, and 7 MN/m are 25.833% 32.322% and 26.185% re spec tively.
A Relational Model of Perceived Overqualification: The Moderating Role of Interpersonal Influence on Social Acceptance

Theories of perceived overqualification have tended to focus on employees' job related responses to account for effects on performance. We offer an alternative perspective and theorize that perceived overqualification could influence work performance through a relational mechanism. We propose that relational skills, in the form of interpersonal influence of overqualified employees, determine their tendency to experience social acceptance and, thus, engage in positive work related behaviors. We tested this relational model across two studies using time lagged, multisource data. In Study 1, the results indicated that for employees high on interpersonal influence, perceived overqualification was positively related to self reported social acceptance, whereas for employees low on interpersonal influence, the relationship was negative. Social acceptance, in turn, was positively related to in role job performance, interpersonal altruism, and team member proactivity evaluated by supervisors. In Study 2, we focused on peer reported social acceptance and found that the indirect relationships between perceived overqualification and supervisor reported behavioral outcomes via social acceptance were negative when interpersonal influence was low and nonsignificant when interpersonal influence was high. The implications of the general findings are discussed.
The Role of Consumer Susceptibility to Interpersonal Influence in Predicting Green Apparel Consumption Behavior of American Youth

In recent years, considering that consumers are giving more importance to their role and consequence with regards to social and environmental implication of their consumption decisions, there has been increase in ethical consumption research. However, to date, the role of individual susceptibility to interpersonal influence and other relevant factors (e.g. environmental apparel knowledge) have not been studied. Therefore, the present study explored several critical constructs related to green apparel consumption including consumer susceptibility to interpersonal influence (CSII) The present study focused on American youth (n 1,049) Based on extant literature review, a hypothesized model was proposed. To test research hypotheses, structural modeling technique was implemented. The results showed that the proposed research model explained 68% of the variance in green apparel consumption behavior of American youth. Furthermore, it was found that environmental apparel knowledge had a significant positive influence on general environmentally responsible behavior, in turn, which influenced green apparel consumption behavior. On the contrary, consumer susceptibility to interpersonal influence did not positively influence general environmentally responsible behavior. Marketing implications, strategies, and limitations of the present research study are discussed.
The Limits of Compensation: Swiss Neutrality Policy in the Cold War
Venue: Journal of Cold War Studies

Switzerland was in a unique place among European countries after World War II. Although situated in the center of Europe, it had not been attacked by Nazi Germany and therefore emerged from the war with a strong economy, stable political institutions, and social cohesion. The experience of World War II forged a collective identity different from that in other continental states. The Swiss had a deep emotional commitment to neutrality and a conviction that autonomous defense would continue to be an effective security strategy after 1945. The Swiss government acknowledged the need for, and indeed was supportive of, the new United Nations collective security system. The Swiss were well aware of the benefits of Western collective defense and European integration as the Cold War divide came about. But Switzerland was willing to associate with these new multilateral governance structures only to the extent that they did not negatively affect neutrality or, in the case of European integration, Swiss economic interests.
Fekete Szego problem for close to convex functions with respect to a certain convex function dependent on a real parameter

Given a [0, 1] let ha(z) z/(1 az) z D: {z D: |z| 1} An analytic standardly normalized function f in D is called close to convex with respect to ha if there exists d p/2, p/2) such that Re{eidzf'(z)/ha(z) 0, z D. For the class l (ha) of all close to convex functions with respect to ha, the Fekete Szego problem is studied.
NE STEM 4U: an out of school time academic program to improve achievement of socioeconomically disadvantaged youth in STEM areas

BackgroundThe Nebraska Science, Technology, Engineering, and Mathematics 4U (NE STEM 4U) program was initiated at the University of Nebraska at Omaha (UNO) in 2013. NE STEM 4U is a student run, faculty led program facilitating problem based learning (PBL) sessions in science, technology, engineering, and mathematics (STEM) for socioeconomically disadvantaged kindergarten through grade 8 (K 8) students. PBL sessions are provided throughout the academic year in a twice weekly, after school, informal education program. The instructional material provided after school builds upon the curricula of the school day. Importantly, this program is a partnership between faculty members and administrators in higher education at UNO with community partners of Omaha including Collective for Youth, Beyond School Bells, and Omaha Public Schools. We focus on engaging K 8 youth in after school immersion experiences in STEM fields using undergraduate students as mentors and facilitators using a model of problem based learning.ResultsThis program fosters an educational pipeline for students with hands on experience in problem solving and critical thinking. The partnerships among the community provide the foundation for success for students across the K 16 pipeline.ConclusionsHerein, we describe the model of this program as documented by demonstrated successes to date in an effort to guide others in developing such a model in their city or region. We also provide models for implementation of assessment instruments.
Unsupervised cyber bullying detection in social networks
Venue: 2016 23rd International Conference on Pattern Recognition (ICPR)

Modern young people "digital natives" have grown in an era dominated by new technologies where communications are pushed to quite a real time level, and pose no limits in establishing relationships with other people or communities. However, the speed of evolution does not allow young people to split consciously acceptable behaviors from potentially harmful ones and a new phenomenon known as cyber bullying is emerging with increasing evidence, attracting the attention of educators, and media. Cyber bullying is defined as "willful and repeated harm inflicted through the use of electronic devices"  In this paper we propose a possible solution for automatic detection of bully traces over a social network, using techniques derived from NLP (Natural Language Processing) and machine learning. Specifically, we shall design a model inspired by Growing Hierarchical SOMs, able to cluster efficiently documents containing bully traces, built upon semantic and syntactic features of textual sentences. We fine tuned our model to work with the social network Twitter, but we also tested the model against other social networks such as YouTube and Formspring. Finally, we report our results, showing that the proposed unsupervised approach could be effectively used with good performances in some scenarios.
Cognitive Orientation to (Daily) Occupational Performance intervention leads to improvements in impairments, activity and participation in children with Developmental Coordination Disorder
Venue: Disability and rehabilitation

Children diagnosed with Developmental Coordination Disorder (DCD) present with a variety of impairments in fine and gross motor function, which impact on their activity and participation in a variety of settings. This research aimed to determine if a 10 week group based Cognitive Orientation to Daily Occupational Performance (CO OP) intervention improved outcome measures across the impairment, activity and participation levels of the International Classification of Functioning, Disability and Health (ICF) framework.  In this quasi experimental, pre post test, 20 male children aged 8 10 years (9y1m 9 m) with a confirmed diagnosis of DCD participated in either the 10 week group intervention based on the CO OP framework (n 10) or in a control period of regular activity for 10 weeks (n 10) Outcome measures relating to impairment (MABC 2, motor overflow assessment) activity (Handwriting Speed Test) and participation [Canadian Occupational Performance Measure, (COPM) and Goal Attainment Scale) were measured at weeks 0 and 10 in the intervention group.  Children who participated in the CO OP intervention displayed improvements in outcome measures for impairment, activity and participation, particularly a reduction in severity of motor overflow. Parent and child performance and satisfaction ratings on the COPM improved from baseline to week 10 and all goals were achieved at or above the expected outcome. No significant changes were reported for the control group in impairment and activity (participation was not measured for this group)  The strategies implemented by children in the CO OP treatment group, targeted towards individualised goal attainment, show that CO OP, when run in a group environment, can lead to improvements across all levels of the ICF. Implications for Rehabilitation Development Coordination Disorder is a condition which has significant physical, academic and social impacts on a child and can lead to activity limitations and participation restrictions. Cognitive Orientation to Daily Occupational Performance is an approach which uses cognitive based strategies to improve performance of specific tasks based on child chosen goals. The intervention program had a positive effect on self perceived levels of performance which may lead to changes in quality of life. Parents felt the intervention enhanced socialisation, peer modelling and encouragement and felt that this increased confidence and independence.
Classification and mapping of the woody vegetation of Gonarezhou National Park, Zimbabwe

Within the framework of the Great Limpopo Transfrontier Conservation Area (GLTFCA) the purpose of this study was to produce a classification of the woody vegetation of the Gonarezhou National Park, Zimbabwe, and a map of its potential distribution. Cover abundance data of woody species were collected in 330 georeferenced releves across the Park. These data were used to produce two matrices: the first one using the cover abundance values as collected in five height layers and the second one based on merging the layers into a single cover value for each species. Automatic classifications were produced for both matrices to determine the optimal number of vegetation types. The two classification approaches both produced 14 types belonging to three macro groups: mopane, miombo and alluvial woodlands. The results of the two classifications were compared looking at the constant, dominant and diagnostic species of each type. The classification based on separate layers was considered more effective and retained. A high resolution map of the potential distribution of vegetation types for the whole study area was produced using Random Forest. In the model, the relationship between bioclimatic and topographic variables, known to be correlated to vegetation types, and the classified releves was used. Identified vegetation types were compared with those of other national parks within the GLTFCA, and an evaluation of the main threats and pressures was conducted.  Vegetation classification and mapping are useful tools for multiple purposes including: surveying and monitoring plant and animal populations, communities and their habitats, and development of management and conservation strategies. Filling the knowledge gap for the Gonarezhou National Park provides a basis for standardised and homogeneous vegetation classification and mapping for the entire Great Limpopo Transfrontier Conservation Area.