Miracle-dz/UniFAR-FTUs huggingface dataset:
Socioeconomic Disparities in the Prevalence, Diagnosis, and Control of Hypertension in the Context of a Universal Health Insurance System

A lower use of preventive intervention in low socioeconomic populations has been described in countries with universal coverage health care systems, but little is known about the possible socioeconomic inequalities in secondary prevention in a universal health insurance system. Data from the 2010-2013 Korea National Health and Nutrition Examination Survey, a nationwide survey, were analyzed. A total of 20,044 subjects older than 30 years of age were included after excluding subjects with missing data. Prevalence ratios were calculated using Poisson regression models with robust variance to explore factors associated with the prevalence, unawareness, and inappropriate control of hypertension. Hypertension prevalence decreased with increasing education and income level. We observed an inverse association between education level and undiagnosed hypertension among women, but not men. Socioeconomic level was not associated with inadequate control of hypertension among men or women. Future interventions should include primary prevention efforts targeted at lower socioeconomic populations to reduce disparities. There is substantial room for improvement in secondary prevention efforts. Monitoring strategies may highlight gaps in the preventive and care services offered to the most vulnerable individuals and encourage governments and practitioners to address these gaps.
Co-Array Fortran Experiences with Finite Differencing Methods

Partial differential equations are used to describe physical phenomena in many science and engineering fields. Finite differencing methods map these continuous equations into discrete space so that they may be solved on computers. Co-Array Fortran provides the means for implementing such solution methods in parallel processing computing environments. In this report we describe our experiences with several different implementations using Co-Array Fortran, supported by experiments run on the Cray X1E at ORNL.
Trends in New Zealand Bank Efficiency over Time

This paper explores the extent of efficiency improvements achieved by New Zealand banks over the period 1996 to 2002, using data envelopment analysis (DEA), on a time-series, rather than cross-sectional basis. Evidence is found for improvements in bank efficiency through time, some of which can be attributed to falls in the general level of interest rates, although a further portion may be due to either management effort to improve bank efficiency or technical progress. Because some of the results obtained appear to be a consequence of the methodology, rather than necessarily being consistent with other interpretations of the data, the paper also provides insights into complications that can arise with use of DEA.
“Go Away”: Participant Objections to Being Studied and the Ethics of Chatroom Research

In this article we present an empirical study aimed at better understanding the potential for harm when conducting research in chatrooms. For this study, we entered IRC chatrooms on the ICQ network and posted one of three messages to tell participants that we were recording them: a recording message, an opt-in message, or an opt-out message. In the fourth condition, we entered the chatroom but did not post a message. We recorded and analyzed how subjects responded to being studied. Results of a regression analysis indicate significantly more hostility in the three conditions where we said something than in the control condition. We were kicked out of 63.3% of the chatrooms we entered in the three message conditions compared with 29% of the chatrooms in the control condition. There were no significant differences between any of these three conditions. Notably, when given a chance to opt in, only 4 of 766 potential subjects chose to do so. Results also indicate significant effects for both size and the number of moderators. For every 13 additional people in a chatroom, the likelihood getting kicked out was cut in half. While legal and ethical concerns are distinct, we conclude by arguing that studying chatrooms constitutes human subjects research under U.S. law, but that a waiver of consent is appropriate in most cases as obtaining consent is impracticable.
High-technology clusters, networking and collective learning in Europe

High technology and SMEs, regional clustering and collective learning - an overview high-technology clusters and evolutionary trends in the 1990s regional institutional and policy frameworks for high-technology SMEs in Europe university and public research institute links with regional high-technology SMEs the role of inter-SME networking and links in innovative high-technology milieux large firm acquisitions, spin-offs and links in the development of regional clusters of technology-intensive SMEs collective learning, system competences and epistemically significant moments collective learning processes in European high-technology milieux concluding reflections - some policy implications.
Early diagnosis of temporomandibular joint involvement in juvenile idiopathic arthritis: a pilot study comparing clinical examination and ultrasound to magnetic resonance imaging

Objectives. To study the validity of both rheumatological and orthodontic examinations and ultrasound (US) as screening methods for early diagnosis of TMJ arthritis against the gold standard MRI. Methods. Thirty consecutive juvenile idiopathic arthritis (JIA) patients were included in this pilot study. Rheumatological and orthodontic examinations as well as US were performed within 1 month of the MRI in a blinded fashion. Joint effusion and/or increased contrast enhancement of synovium or bone were considered signs of active arthritis on MRI. Results. A total of 19/30 (63%) patients and 33/60 (55%) joints had signs of TMJ involvement on MRI. This was associated with condylar deformity in 9/19 (47%) patients and 15/33 (45%) joints. Rheumatological, orthodontic and US examinations correctly diagnosed 11 (58%), 9 (47%) and 6 (33%) patients, respectively, with active TMJ arthritis, but misdiagnosed 8 (42%), 10 (53%) and 12 (67%) patients, respectively, as having no signs of inflammation. The best predictor for active arthritis on MRI was a reduced maximum mouth opening. Conclusion. None of the methods tested was able to reliably predict the presence or absence of MRI-proven inflammation in the TMJ in our cohort of JIA patients. US was the least useful of all methods tested to exclude active TMJ arthritis.
LEARNING EFFECTIVE BDD VARIABLE ORDERS FOR BDD-BASED PROGRAM ANALYSIS

Software reliability and security are in jeopardy. As software has become ubiquitous and its capabilities have become more complex, code quality has been sacrificed in the race for the next ”killer app. ” In response, program analysis researchers have mounted a revolution; they have developed new tools and methods, underpinned by traditional compilation techniques, in order to save software from its downward spiral. However, because these tools and analyses have also become more sophisticated, they too have suffered from scalability, reliability and complexity issues. Just as program analysis researchers have set out to solve the problems of software developers, we have set out to solve the problems of program analysis researchers. The bddbddb (Binary Decision Diagram-Based Deductive DataBase) system has recently made possible many advanced, context-sensitive program analyses. Such analyses can be expressed in bddbddb as Datalog queries, which are quantifiably easier to write than a traditional implementation. The bddbddb system’s unique compilation mechanisms also yield analyses of exceptional performance. The key to this performance is the use of Binary Decision Diagrams (BDDs), a compact representation that exploits repeated patterns in data, to represent the principle elements of an analysis. However, finding efficient BDD representations (i.e., BDD variable orders) for a particular analysis is nearly impossible to accomplish manually and, in some cases, is without a solution given an analysis and its formulation. This thesis presents an algorithm that helps automate the discovery of efficient BDD representations. Our technique reformulates the search for BDD variable orders as an active learning process over the space of BDD variable orders and their execution times. This technique revolves around an iterative process of carefully sampling new orders and then reducing the search space by extracting features from high performance orders. The dominant features of the sampled variable orders can then be used to generate new orders, refine existing orders, or even revise analysis formulations. The variable orders generated by our algorithm outperform those obtained after months of manual exploration. And, more importantly, our results make bddbddb a viable and valuable tool for program analysis researchers in their quest for better quality code.
Shareholder engagement in the extractive sector

The extractive industry sector has become one of the most prominent areas for shareholder engagement. Given its environmental and social impacts, and global nature, this sector's operations are particularly prone to financially material reputational risks. Large-scale investors and financial analysts concerned with reputational risk as a consequence of insufficient environmental, social and governance (ESG) standards in companies are increasingly turning to shareholder engagement as the preferred and most direct method of implementing, monitoring and advising companies. This article argues that shareholders have some impact on ESG issues with companies in the extractive sector. Their influence stems from the legitimacy they bring to the engagement process, with a high degree of knowledge in the sector and a pragmatic approach that recognizes the incremental pace of change in extractive companies. In this article we build on the work of both Mitchell and others, and Gifford on stakeholder saliency, in order to assess the results of engagement at the level of the firm, with particular reference to the extractive sector. Previous work has focused on the saliency of such engagement at the stakeholder level, with the investor as the unit of analysis. We investigate the impacts and perceptions of shareholder engagement in the extractive sector examining engagements NEI Investments with Canadian mining giant Barrick Gold from 2005 to 2009. We further quantify the results of the engagement using data from a third-party rating agency.
Dopamine Transporters in Striatum Correlate with Deactivation in the Default Mode Network during Visuospatial Attention

Background Dopamine and dopamine transporters (DAT, which regulate extracellular dopamine in the brain) are implicated in the modulation of attention but their specific roles are not well understood. Here we hypothesized that dopamine modulates attention by facilitation of brain deactivation in the default mode network (DMN). Thus, higher striatal DAT levels, which would result in an enhanced clearance of dopamine and hence weaker dopamine signals, would be associated to lower deactivation in the DMN during an attention task. Methodology/Principal Findings For this purpose we assessed the relationship between DAT in striatum (measured with positron emission tomography and [11C]cocaine used as DAT radiotracer) and brain activation and deactivation during a parametric visual attention task (measured with blood oxygenation level dependent functional magnetic resonance imaging) in healthy controls. We show that DAT availability in caudate and putamen had a negative correlation with deactivation in ventral parietal regions of the DMN (precuneus, BA 7) and a positive correlation with deactivation in a small region in the ventral anterior cingulate gyrus (BA 24/32). With increasing attentional load, DAT in caudate showed a negative correlation with load-related deactivation increases in precuneus. Conclusions/Significance These findings provide evidence that dopamine transporters modulate neural activity in the DMN and anterior cingulate gyrus during visuospatial attention. Our findings suggest that dopamine modulates attention in part by regulating neuronal activity in posterior parietal cortex including precuneus (region involved in alertness) and cingulate gyrus (region deactivated in proportion to emotional interference). These findings suggest that the beneficial effects of stimulant medications (increase dopamine by blocking DAT) in inattention reflect in part their ability to facilitate the deactivation of the DMN.
Sharing Interdepartmental Knowledge using Collaboration Technologies : Action Research Study

Organizational processes today are marked by a growing fragmentation of knowledge and responsibilities. Rarely a process is found that is entirely carried out by one small group of people housed in the same department and physically close to each other. The most likely picture are processes encompassing activities carried out by two or more separate departments that are physically isolated from each other, and whose members have their own "culture" and follow their own schedules. While this configuration has its advantages, it also leads to a number of problems stemming from the fact that members of one department have very little knowledge about what members of other collaborating departments do. This paper discusses a study in which an email-based collaboration technology is used to support knowledge communication among people from different departments. The findings of this study are generally positive and contradict most of the empirical research conducted so far. Yet, these findings are plausibly explained based on a combination of social influences and compensatory adaptive behavior.
Solution-focused support of people with intellectual disabilities

The aim of this thesis was to investigate the effects of Solution-Focused Therapy (SFT) in people with intellectual disabilities (ID) and the effects of Solution-Focused Coaching (SFC) of staff supporting people with ID. Clients receiving SFT, and staff receiving SFC, were compared with clients and staff receiving care-as-usual, and coaching-as-usual respectively. After SFT, the SFBT-clients almost all reached their goals and performed better on psychological, social functioning, and resilience. After SFC, SFC-staff progressed towards their team goals and improved on proactive thinking and on the quality of client-caregiver relationships. This strengths-based SF-approach was valued positively by both clients and staff.
Meet homological mirror symmetry

In this paper, we introduce the interested reader to homological mirror symmetry. After recalling a little background knowledge, we tackle the simplest cases of homological mirror symmetry: curves of genus zero and one. We close by outlining the current state of the field and mentioning what homo- logical mirror symmetry has to say about other aspects of mirror symmetry.
The International Handbook of School Effectiveness Research

Part One: The Historical and Intellectual Foundations of School Effectiveness Research 1.An Introduction to School Effectiveness Research 2.Current Topics and Approaches in School Effectiveness Research: The Contemporary Field Part Two: The Knowledge Base of School Effectiveness Research 3.The Methodology and Scientific Properties of School Effectiveness Research 4.The Processes of School Effectiveness 5.Context Issues within School Effectiveness Research Part Three: The Cutting Edge Issues of School Effectiveness Research 6.Some Methodological Issues in School Effectiveness Research 7.School Effectiveness and School Improvement 8.School Effectiveness: The International Dimension 9.School Effectiveness and Education Indicators 10.Theory Development in School Effectiveness Part Four: The Future of School Effectiveness Research 11. School Effectiveness Research and the Social and Behavioural Sciences 12.The Future Agenda for School Effectiveness Research
Home Bias in Equity Portfolios, Inflation Hedging, and International Capital Market Equilibrium

We test whether the home bias in equity portfolios is caused by investors trying to hedge inflation risk. The empirical evidence is consistent with this motive only if investors have very high levels of risk tolerance and equity returns are negatively correlated with domestic inflation. We then develop a model of international portfolio choice and equity market equilibrium that integrates inflation risk and deadweight costs. Using this model we estimate the levels of costs required to generate the observed home bias in portfolios consistent with different levels of risk aversion. For a level of risk aversion consistent with standard estimates of the domestic equity market risk premium, these costs are about a few percent per annum, greater than observable costs such as withholding taxes. Thus, the home bias cannot be explained by either inflation hedging or direct observable costs of international investment unless investors have very low levels of risk aversion. Article published by Oxford University Press on behalf of the Society for Financial Studies in its journal, The Review of Financial Studies.
Biodegradability of Plastics

Plastic is a broad name given to different polymers with high molecular weight, which can be degraded by various processes. However, considering their abundance in the environment and their specificity in attacking plastics, biodegradation of plastics by microorganisms and enzymes seems to be the most effective process. When plastics are used as substrates for microorganisms, evaluation of their biodegradability should not only be based on their chemical structure, but also on their physical properties (melting point, glass transition temperature, crystallinity, storage modulus etc.). In this review, microbial and enzymatic biodegradation of plastics and some factors that affect their biodegradability are discussed.
The use of heart rate variability measures to assess autonomic control during exercise

Heart rate variability (HRV) is a non‐invasive indicator of cardiac autonomic modulation at rest. During rhythmic exercise, global HRV decreases as a function of exercise intensity. Measures reflecting sympathovagal interactions at rest do not behave as expected during exercise. This makes interpretation of HRV measures difficult, especially at higher exercise intensities. This problem is further confounded by the occurrence of non‐neural oscillations in the high‐frequency band due to increased respiratory effort.
The Effect of Unobservable Efforts on Contractual Efficiency

An interesting puzzle in business practices is that although many researchers emphasize the benefits of a revenue-sharing contract, a wholesale contract has remained to be the most common contractual form. By introducing the concept of unobservable efforts, we examine the contractual efficiency of a wholesale contract and a revenue-sharing contract. The multi-task agency model and experimental design approach are used to analyze the relationship between the contractual efficiency and parameters. A major finding of our study is that a wholesale contract coordinates unobservable efforts, while it fails to coordinate the order quantity decision. Because unobservable efforts have mixed effects on the contractual efficiency, the superiority of contract type depends on parameters. This finding implies that a wholesale contract can be a competitive contract, especially when unobservable efforts are heavily involved. Our conclusion is that the current popularity of a wholesale contract is manager’s rational response to complex supply chain environments rather than irrational behaviors.
Relational Stacked Denoising Autoencoder for Tag Recommendation

Tag recommendation has become one of the most important ways of organizing and indexing online resources like articles, movies, and music. Since tagging information is usually very sparse, effective learning of the content representation for these resources is crucial to accurate tag recommendation. Recently, models proposed for tag recommendation, such as collaborative topic regression and its variants, have demonstrated promising accuracy. However, a limitation of these models is that, by using topic models like latent Dirichlet allocation as the key component, the learned representation may not be compact and effective enough. Moreover, since relational data exist as an auxiliary data source in many applications, it is desirable to incorporate such data into tag recommendation models. In this paper, we start with a deep learning model called stacked denoising autoencoder (SDAE) in an attempt to learn more effective content representation. We propose a probabilistic formulation for SDAE and then extend it to a relational SDAE (RSDAE) model. RSDAE jointly performs deep representation learning and relational learning in a principled way under a probabilistic framework. Experiments conducted on three real datasets show that both learning more effective representation and learning from relational data are beneficial steps to take to advance the state of the art.
Central bank independence in Central and Eastern Europe on the eve of EU-enlargement

The EU-enlargement in mid-2004 will probably be followed by the accession to the European Monetary and Economic Union (EMU), depending on the individual state of convergence of the accession candidates. In this paper, we argue that institutional convergence, in particular central bank independence (CBI), is equally – if not more – important for a successful common monetary policy in an enlarged Euroland than nominal and real convergence, as it indicates an appropriate policy assignment and thereby fosters real and nominal convergence. The paper starts with an assessment of the state of convergence of CEE countries in nominal and real terms. Based on a constitutional political economy framework and the additional requirement for future EMU members to give their central banks an independent status, we then assess the degree of central bank independence in CEE. We apply a measure, namely the index of monetary commitment, which includes external criteria such as convertibility and exchange rate regimes. It can be shown that the degree of central bank independence in CEE countries is considerably high; however, there is a gap to the ECB’s independence with respect to external aspects of CBI. 1 This paper was initiated following a discussion on central banks’ independence at the ACE Phare research project „Alternative exchange rate regimes in transition economies“ second workshop in Strunjan, 15-16 June 2001, organized by the Institute for Economic Research (IER), Ljubljana. 2 University of Cologne, Robert-Koch-Str. 4, D-50931 Cologne, Germany, Tel. : ++49 221 470 4879, Fax: ++49 221 470 5187, e-mail: andreas.freytag@uni-koeln.de. This paper is part of a research project entitled “Economic Order and CBI in the Enlarged EMU“, the author is conducting for the Otto-Wolff-Institute for Economic Policy. In addition, the author gratefully acknowledges very helpful comments by Sandra Dvorsky, Ferdinand Fichtner, Marianne Keudel and Philipp Paulus.