nils-herrmann/clean_scirepeval huggingface dataset:
A Study of Anti Fat Bias among Danish General Practitioners and Whether This Bias and General Practitioners' Lifestyle Can Affect Treatment of Tension Headache in Patients with Obesity
Venue: Obesity Facts
Year: 2018

The study investigated whether treatment options for episodic tension type headache vary among general practitioners (GPs) in Denmark depending on the patients' weight status and gender, and whether these decisions can be explained by the GPs' own anti fat bias and lifestyle.  A cross sectional questionnaire study with responses from 240 GPs on measures of anti fat bias, healthiness of GPs' lifestyles, and reported patient treatment decisions.  GPs tended to exhibit negative explicit and implicit anti fat bias. There were no differences in choice of medical treatment for patients with obesity and those of a normal weight. GPs were more likely to advise a general health check to a patient with obesity (p 0.001) GPs treating a male patient with obesity were less likely to believe that their patient would comply with the advised treatment compared to those with a male patient of normal weight. Compared with other patient types (4.4 7.7% GPs who treated a male patient with obesity (27.9% were more likely to advise a general health check only and no diary keeping or follow up consultation (p 0.001) This was explained by the healthiness of the GPs' lifestyles (Spearman's r 0.367; p 0.01)  Despite the presence of clear anti fat bias, there were no differences in medical treatment, and GPs managed the general health of patients with obesity proactively. The fact that the GPs' own lifestyle influenced the likelihood that they would recommend diary keeping and follow up consultations for male patients with obesity is remarkable and requires further investigation.
Examining the Literacy Practices of Engineers to Develop a Model of Disciplinary Literacy Instruction for K 12 Engineering (Work in Progress)
Year: 2018

Examining the Literacy Practices of Engineers to Develop a Model of Disciplinary Literacy Instruction for K 12 Engineering (Work in Progress) Theresa Green, Utah State University Theresa Green is a graduate student at Utah State University pursuing a PhD in Engineering Education. Her research interests include K 12 STEM integration and improving diversity and inclusion in engineering. Dr. Angela Minichiello P.E. Utah State University Angela Minichiello is an assistant professor in the Department of Engineering Education at Utah State University and a registered professional mechanical engineer. Her research examines issues of access, diversity, and inclusivity in engineering education. In particular, she is interested in engineering learning, problem solving, and the intersections of online learning and alternative pathways for adult, nontraditional, and veteran undergraduates in engineering. Dr. Amy Wilson Lopez, Utah State University Engineering Education Amy Wilson Lopez is an associate professor at Utah State University who studies culturally responsive engineering and literacy infused engineering with linguistically diverse students.
Yi Chong Gai Jin De Duo Shi Tu Ju Lei Ji Cheng Suan Fa (Improved Multi view Clustering Ensemble Algorithm)
Venue: Ji Suan Ji Ke Xue
Year: 2017

In recent years,data mining and machine learning algorithms for big data become increasingly important.In the clustering,with the appearance of multi view data,multi view clustering has become an important clustering method. However,many existing multi view clustering algorithms are easily affected by parameter setting and dataset itself,SO the clustering results are usualy unstable.To overcome this problem,we presented a new multi view clustering ensemble algorithm based on the multi view K means clustering algorithm in this paper.This algorithm uses ensemble tech nique to improve the multi view K means algorithm performance,increasing the accuracy,robustness,and stability of clustering results.It is well known that one single computer cannot process too much data.because one computer has the limited computation resources.To improve the efficiency of multi view clustering,we implemented a distributed multi view clustering ensemble algorithm based on distributed processing technology.Experimental results show that the proposed approach has higher efficiency when processing large dataset,and it is suitable for multi view clustering in big data environment.
BUSINESS MODEL CANVAS AND SUSTAINABLE PRODUCT SERVICE SYSTEM DESIGN: PROPOSAL FOR A CONVERGENT APPROACH FOR DESIGNING SUSTAINABLE AND INNOVATIVE BUSINESS MODELS
Year: 2018

This paper presents the results of a research on the applicability of the sustainable product service system design (S.PSS) and business model design, adopting Business Model Canvas as a main tool. This resource is an essential part of an integrated and modular methodology for research and development (R&D) that was designed to support the development of new materials, products and business models from solid waste, but also useful in other projects focused in sustainable innovation. The research methodology included, beyond critical literature review, the construction of the methodological model, including one page briefs for each tool incorporated in the model. The results pointed out that is possible to combine sustainability and business in a comprehensive and feasible method to improve the quality of R&D projects on solid waste, in a more systemic way.
Incorporating Multimodal Information in Open Domain Web Keyphrase Extraction
Venue: EMNLP
Year: 2020

Open domain Keyphrase extraction (KPE) on the Web is a fundamental yet complex NLP task with a wide range of practical applications within the field of Information Retrieval. In contrast to other document types, web page designs are intended for easy navigation and information finding. Effective designs encode within the layout and formatting signals that point to where the important information can be found. In this work, we propose a modeling approach that leverages these multi modal signals to aid in the KPE task. In particular, we leverage both lexical and visual features (e.g. size, font, position) at the micro level to enable effective strategy induction and meta level features that describe pages at a macro level to aid in strategy selection. Our evaluation demonstrates that a combination of effective strategy induction and strategy selection within this approach for the KPE task outperforms state of the art models. A qualitative post hoc analysis illustrates how these features function within the model.
Aerosols and contact insecticides as alternatives to methyl bromide in flour mills, food production facilities, and food warehouses
Venue: Journal of Pest Science
Year: 2012

The fumigant methyl bromide (MB) is being phased out of production and usage to control stored product insects in flour and rice mills, as well as feed and food production plants, in the United States and other developed countries throughout the world. A phase out schedule has also been established for undeveloped counties under a delayed timeline compared to the one established for developed countries. Whole plant alternatives to MB treatment, such as the fumigant sulfuryl fluoride and heat, can be used in place of MB, but they have some limitations as well, which will be briefly discussed in this review. Hence, residual surface treatments with contact insecticides and insect growth regulators and aerosol applications are receiving increased attention for incorporation into management programs that historically relied on MB fumigations. This review will focus on recent research with contact insecticides and aerosols for controlling stored product insects in structures and how they can be viewed as options for control to alleviate concerns regarding the phase out and reduced availability of MB for structural fumigations. A brief discussion of emerging pest species or groups, and how they can be controlled with surface treatments and aerosols, is also included in the review.
Repressive coping among British college women: A potential protective factor against body image concerns, drive for thinness, and bulimia symptoms.
Venue: Body image
Year: 2017

Repressive coping, as a means of preserving a positive self image, has been widely explored in the context of dealing with self evaluative cues. The current study extends this research by exploring whether repressive coping is associated with lower levels of body image concerns, drive for thinness, bulimic symptoms, and higher positive rational acceptance. A sample of 229 female college students was recruited in South London. Repressive coping was measured via the interaction between trait anxiety and defensiveness. The results of moderated regression analysis with simple slope analysis show that compared to non repressors, repressors reported lower levels of body image concerns, drive for thinness, and bulimic symptoms while exhibiting a higher use of positive rational acceptance. These findings, in line with previous evidence, suggest that repressive coping may be adaptive particularly in the context of body image.
Event Aware Framework for Dynamic Services Discovery and Selection in the Context of Ambient Intelligence and Internet of Things
Venue: IEEE Transactions on Automation Science and Engineering
Year: 2016

The Internet of Things is the natural continuity of the Ambient Intelligence where smart and ambient environments are built mainly by integrating a large number of interconnected smart objects (sensors, actuators, Smartphone, appliances, etc. with heterogeneous capabilities abstracted as software services. These services can be composed on the fly and provided, all the time and everywhere, to assist users in their daily activities. A key issue in user centered services composition is to intelligently and effectively discover and select the most relevant services that best match the users' requirements and closely meet the specified quality of service level. Monitoring seamlessly the provided services and enhancing their quality, is still a challenging issue due mainly to the dynamicity and uncertainty characterizing ambient environments. In this paper, we propose a new service oriented, user centered and event aware Framework capable of performing services monitoring to handle automatically events that may occur in ambient environments. This monitoring is based on a dynamic services discovery and selection process to enhance self adaptation to unpredicted changes, and ensure services continuity with best quality. The overall proposed Framework has been implemented and validated through a scenario dedicated to daily activity recognition in an Ambient Assisted Living environment. In addition, the obtained performances from extensive tests show clearly the efficiency and feasibility of the proposed approach in the case of a large scale environment.
Leptin Receptor Promotes Adipogenesis and Reduces Osteogenesis by Regulating Mesenchymal Stromal Cells in Adult Bone Marrow.
Venue: Cell stem cell
Year: 2016

Skeletal stem cells (SSCs) that are the major source of osteoblasts and adipocytes in adult bone marrow express leptin receptor (LepR) To test whether LepR regulates SSC function, we conditionally deleted Lepr from limb bone marrow stromal cells, but not from the axial skeleton or hypothalamic neurons, using Prx1 Cre. Prx1 Cre;Lepr(fl/fl) mice exhibited normal body mass and normal hematopoiesis. However, limb bones from Prx1 Cre;Lepr(fl/fl) mice exhibited increased osteogenesis, decreased adipogenesis, and accelerated fracture healing. Leptin increased adipogenesis and reduced osteogenesis by activating Jak2/Stat3 signaling in bone marrow stromal cells. A high fat diet increased adipogenesis and reduced osteogenesis in limb bones from wild type mice, but not from Prx1 Cre;Lepr(fl/fl) mice. This reflected local effects of LepR on osteogenesis and adipogenesis by bone marrow stromal cells and systemic effects on bone resorption. Leptin/LepR signaling regulates adipogenesis and osteogenesis by mesenchymal stromal cells in the bone marrow in response to diet and adiposity.
Towards Interactive Multidimensional Visualisations for Corpus Linguistics
Venue: J. Lang. Technol. Comput. Linguistics
Year: 2016

We propose the novel application of dynamic and interactive visualisation techniques to support the iterative and exploratory investigations typical of the corpus linguistics methodology. Very large scale text analysis is already carried out in corpus based language analysis by employing methods such as frequency profiling, keywords, concordancing, collocations and n grams. However, at present only basic visualisation methods are utilised. In this paper, we describe case studies of multiple types of key word clouds, explorer tools for collocation networks, and compare network and language distance visualisations for online social networks. These are shown to fit better with the iterative data driven corpus methodology, and permit some level of scalability to cope with ever increasing corpus size and complexity. In addition, they will allow corpus linguistic methods to be used more widely in the digital humanities and social sciences since the learning curve with visualisations is shallower for non experts
Rethinking evidence based practice and two generation programs to create the future of early childhood policy
Venue: Development and Psychopathology
Year: 2013

Half a century of research and program evaluation has fueled a diverse landscape of early childhood policies and practices that produce a range of positive effects on the life prospects of children who face the burdens of significant adversity. Drawing on advances in neurobiology, developmental psychology, developmental psychopathology, and prevention science, this paper presents a framework for elucidating underlying causal mechanisms that explain differences in outcomes, formulating enhanced theories of change about how to shift developmental trajectories, designing creative interventions and rethinking the concept of a two generation strategy to produce breakthrough impacts, and launching a new era of investment in young children and their families that will achieve greater reductions in intergenerational disparities in learning, behavior, and health than those produced by current best practices. Particular attention is focused on the hypothesis that substantially better outcomes for vulnerable, young children could be achieved by greater attention to strengthening the resources and capabilities of the adults who care for them rather than by continuing to focus primarily on the provision of child focused enrichment, parenting education, and informal support. Central to achieving this goal is the need to establish an innovation friendly environment that embraces fast cycle sharing, supports risk taking, and celebrates learning from failure.
Repairing Ontologies via Axiom Weakening
Venue: AAAI
Year: 2018

Ontology engineering is a hard and error prone task, in which small changes may lead to errors, or even produce an inconsistent ontology. As ontologies grow in size, the need for automated methods for repairing inconsistencies while preserving as much of the original knowledge as possible increases. Most previous approaches to this task are based on removing a few axioms from the ontology to regain consistency. We propose a new method based on weakening these axioms to make them less restrictive, employing the use of refinement operators. We introduce the theoretical framework for weakening DL ontologies, propose algorithms to repair ontologies based on the framework, and provide an analysis of the computational complexity. Through an empirical analysis made over real life ontologies, we show that our approach preserves significantly more of the original knowledge of the ontology than removing axioms.
AM I A TROUBLE MAKER? FILLER WORDS IN SPONTANEOUS SPEECH; STRATEGIES OR INTERFERENCE(PRELIMINARY STUDY)
Year: 2012

The present paper attempts to address the subtopic of the seminar, language acquisition, by going through the phenomenon of filler words in students' spontaneous speech. In addition, this paper also tries to scrutinize the two opposing questions; 1) are filler words intentionally produced by the students as the planning process of communicative strategies, and 2) are they the results of the interference which cause speech disfluencies? Responding to the first question, this paper tries to look at the role of filler words if they are considered as the communicative strategies. Meanwhile, to respond to the second question this paper tries to determine the sources of the occurrences of those filler words. The subject for this study are the the Indonesian learners of English at the Language Training Center (UMY) The spoken data was derived largely during the dialogue sessions.
Pa ge 3 0 5 FACTORS INFLUENCING KNOWLEDGE TRANSFER AMONG INTERNSHIP STUDENTS USING FACEBOOK
Year: 2016

Keeping in contact with and sharing knowledge ubiquitously among peer students and teachers during professional internship are utmost important in supporting students both cognitively and affectively to overcome difficulties in their new workplaces. This paper examines the potential factors and its relative impact on influencing the effectiveness of using Facebook as a knowledge sharing tool during students' professional education. A case study was implemented to study a group of university students' perspectives on using Facebook in their internship. The findings are presented in 4 dimensions, ranging from Human, Policy, Technology, and Knowledge aspects as the theoretical framework with 17 potential factors identified. Among the findings, Social Tie got the highest impact in Human aspects as Facebook could create a peer support network among students. Scaffolding reflections has the highest impact among Policy factors because guidance can assist students to formulate content for their reflective journals. Facebook's News Feed function has been recognized as the highest influence among Technology factors because this function enables students to be updated instantly and frequently on the latest development within the internship activities. Explicit knowledge transfer reached the highest impact among Knowledge factors as students can apply Information Management related model into their working situations. All in all, the findings of the study also proved that factors from the literature are applicable to the professional experience internship context. This study provides insights for universities to better utilize Facebook to support knowledge transfer in students' internships. The theoretical framework used in this study may serve as a basis for further research on the use of Facebook for knowledge transfer.
Exercise Based Cardiac Rehabilitation for Coronary Heart Disease: Cochrane Systematic Review and Meta Analysis.
Venue: Journal of the American College of Cardiology
Year: 2016

Although recommended in guidelines for the management of coronary heart disease (CHD) concerns have been raised about the applicability of evidence from existing meta analyses of exercise based cardiac rehabilitation (CR) OBJECTIVES The goal of this study is to update the Cochrane systematic review and meta analysis of exercise based CR for CHD.  The Cochrane Central Register of Controlled Trials, MEDLINE, EMBASE, CINAHL, and Science Citation Index Expanded were searched to July 2014. Retrieved papers, systematic reviews, and trial registries were hand searched. We included randomized controlled trials with at least 6 months of follow up, comparing CR to no exercise controls following myocardial infarction or revascularization, or with a diagnosis of angina pectoris or CHD defined by angiography. Two authors screened titles for inclusion, extracted data, and assessed risk of bias. Studies were pooled using random effects meta analysis, and stratified analyses were undertaken to examine potential treatment effect modifiers.  A total of 63 studies with 14,486 participants with median follow up of 12 months were included. Overall, CR led to a reduction in cardiovascular mortality (relative risk: 0.74; 95% confidence interval: 0.64 to 0.86) and the risk of hospital admissions (relative risk: 0.82; 95% confidence interval: 0.70 to 0.96) There was no significant effect on total mortality, myocardial infarction, or revascularization. The majority of studies (14 of 20) showed higher levels of health related quality of life in 1 or more domains following exercise based CR compared with control subjects.  This study confirms that exercise based CR reduces cardiovascular mortality and provides important data showing reductions in hospital admissions and improvements in quality of life. These benefits appear to be consistent across patients and intervention types and were independent of study quality, setting, and publication date.
Java Swing Modernization Approach Complete Abstract Representation based on Static and Dynamic Analysis
Venue: ICSOFT EA
Year: 2016

GUIs are essential components for today software. However, legacy applications do not benefit from the advantages of user interfaces new technologies that enhance the interaction and the quality of the system. Building a new system from another existing one is more requested and a very complex process. So, we opted for an ADM approach based on the development of separate models capturing various aspects such as tasks, presentation and structures of system dialogue and behavior. For this purpose, the software artifacts should be analyzed and corresponding behavioral and structural models must be created. Two forms of this analysis were developed: a static analysis that provides the ability to retrieve information from the application using the source code and a dynamic analysis for extracting information about application behavior in run mode. This paper presents the automation of the extraction process, which permits understanding and analyzing the behavior of the legacy system, and compares the models generated to deduce the best solution for an abstract representation of existing GUI's models.
Efficient Blockchain Synchronization for Internet of Things using Signature Amortization
Venue: ArXiv
Year: 2019

We study the problem of efficiently disseminating authenticated blockchain information from blockchain nodes (servers) to Internet of Things (IoT) devices, through a wireless base station (BS) In existing blockchain protocols, upon generation of a new block, each IoT device receives a copy of the block header, authenticated via digital signature by one or more trusted servers. Since it relies on unicast transmissions, the required communication resources grow linearly with the number of IoT devices. We propose a more efficient scheme, in which a single copy of each block header is multicasted, together with the signatures of servers. In addition, if IoT devices tolerate a delay, we exploit the blockchain structure to amortize the authentication in time, by transmitting only a subset of signature in each block period. Finally, the BS sends redundant information, via a repetition code, to deal with the unreliable wireless channel, with the aim of decreasing the amount of feedback required from IoT devices. Our analysis shows the trade off between timely authentication of blocks and reliability of the communication, depending on the channel quality (packet loss rate) the block interaction, and the presence of forks in the blockchain. The numerical results show the performance of the scheme, that is a viable starting point to design new blockchain lightweight protocols.