Miracle-dz/UniFAR-FTUs huggingface dataset:
ACE inhibitor-based blood pressure lowering - first line therapy among individuals with hypertension?

INTRODUCTION By the mid 1990's, systematic overviews (meta-analyses) of unconfounded randomised controlled trials of blood pressure lowering had demonstrated that reductions in blood pressure of about 10-12 mmHg systolic and 5-6 mmHg diastolic conferred relative reductions in stroke risk of about 38% and in coronary heart disease risk of about 16% [1-3]. The sizes of these effects were broadly consistent with those anticipated from observational studies of the long-term associations of blood pressure with stroke and coronary heart disease risk [4-6]. However, the trials included in these overviews were of blood pressurelowering regimens based mainly on diuretics and beta-blockers. Since large-scale randomised trials of the effects of ACE inhibitors compared to placebo among hypertensive patients had not been completed, the overviews provided no direct evidence about their effects. At the time, evidence about the effects of ACE inhibitors on major cardiovascular outcomes was restricted to indirect data from two randomised controlled trials that compared the effects of ACE inhibitor-based regimens with diureticor beta-blockerbased regimens [7, 8]. These two trials identified no differences in the effects of the regimens on stroke or coronary heart disease risk but even in combination were too small to exclude anything but very large differences. Evidence about the clinical effects of ACE inhibitors in hypertensive patients was therefore largely restricted to information about intermediate outcomes such as blood pressure [7, 8] and surrogate endpoints such as renal function [9, 10] and left ventricular hypertrophy [11], although clear benefits had been demonstrated on major cardiovascular outcomes in patients with heart failure [12] and acute myocardial infarction [13].
Engaging Malaysian Modernity 50 Years and Beyond

A case study of a ‘blogwar’ centred on a short-lived ‘hateblog’ that occurred mostly in the Singaporean blogosphere, with some input from Malaysia. In this case, the renown of the protagonists, and the viciousness of the attack, combined to make the hateblog a ‘productive’ temporary locus of online discursive activity. Theoretically, the approach taken shall draw upon Bourdieu’s concepts of field, social capital and practice; Bakhtin’s concept of dialogics; Appadurai’s concept of “commodity candidacy”, and discussions of value and authenticity. Miller & Slater, as well as Latour, are important in shaping the ethnographic approach to the internet, rooting online practices in offline contexts. It is argued that through the posts and comments of those who condemn, support, or merely wish to be entertained by, the blogwar, it is possible to explore the underlying practices and norms of blogging. Methodologically, the short timeframe enabled the gathering of most – possibly all – related blog posts and comments. These were subjected to content analysis, and the results analysed statistically and with social network analysis tools.
SUPPLEMENT TO “THE EFFECTS OF HEALTH INSURANCE AND SELF-INSURANCE ON RETIREMENT BEHAVIOR” (Econometrica, Vol. 79, No. 3, May 2011, 693–732) BY ERIC FRENCH

Individuals pay federal, state, and payroll taxes on income. We compute federal taxes on income net of state income taxes using the Federal Income Tax tables for “Head of Household” in 1998. We use the standard deduction, and thus do not allow individuals to defer medical expenses as an itemized deduction. We also use income taxes for the fairly representative state of Rhode Island (27.5% of the Federal Income Tax level). Payroll taxes are 7.65% up to a maximum of $68,400, and are 1.45% thereafter. Adding up the three taxes generates the following level of post-tax income as a function of labor and asset income (Table B.I).
Factors Influencing Directors’ Remuneration Disclosure in Malaysia PLCs

This study is intended to examine the levels of directors’ remuneration disclosure among public-listed companies in Malaysia. It further aims to examine the relationship among total directors’ remuneration, directors’ education level, size of external auditors, and proportion of managerial ownership and directors’ remuneration disclosure. The analysis is conducted based on three models, which are constructed from the Malaysian Code on Corporate Governance (Model 1), Global Practices (Model 2), and a combination of both Malaysian Code on Corporate Governance and Global Practices (Model 3). This study found that the size of external auditors had a positive significant relationship, while the proportion of managerial ownership had a negative significant relationship with the disclosure. This study contributes to the improvement of policymaking and body of knowledge by highlighting the relationship between the selected corporate governance characteristics and directors’ remuneration disclosure in the context of Malaysia.
Preventive antibiotic treatment in agriculture: emergence of dysbiosis and propagation of obese state associated and mobile multidrug resistance carrying bacteria. Dobrzanska

In agriculture, antibiotics are often used to prevent livestock disease. Antibiotic treatment perturbs the bacterial composition of the gut but the extent of these changes and potential consequences for animal and human health are still debated. Six calves were housed in a controlled environment receiving the same diet. Three animals received an injection of the antibiotic florfenicol (Nuflor) and three received no treatment. Faecal samples were collected from each animal 0, 3 and 7 days after treatment and bacterial communities profiled to assess the impact of a standard antibiotic therapy on the gut microbiota over time. Phylogenetic analysis of 16S-rRNA genes established that at day 7 the microbiota of calves given Nuflor showed a 10-fold increase in facultative anaerobic Escherichia spp, a signature of imbalanced microbiota, dysbiosis. Analysis of the antibiotic resistome revealed a high background of antibiotic resistance genes, the abundance and diversity of which did not significantly change in response to Nuflor. However, the maintenance of Escherichia coli plasmidencoded quinolone, oqxB and propagation of mcr-2, colistin resistance genes was observed and confirmed by Sanger sequencing of PCR fragments of the metagenomic DNA. The microbiota of animals treated with antibiotics had a higher population of energy harvesting bacteria, including H2producing Prevotellaceae and H2-oxidising methanogenic Archaea, common to the obese microbial community. We propose that antibiotic treatment of healthy animals leads to unbalanced, diseaseand obese related microbiota that promote growth of mobile-resistance carrying E. coli, increasing the risk of spread and transmission of resistant bacteria to humans. Significance Statement. Antibiotics, the most important tool in fighting bacterial infections, are widely used in livestock as a prophylactic therapy and/or to enhance growth. Here we show that preventive antibiotic treatment of healthy calves resulted in unbalanced intestinal microbiota, termed dysbiosis, with two major outcomes. Firstly, the preferential growth of bacteria with high energy harvesting capacity, a key obesity determinant. Secondly, the selective growth of bacteria carrying a range of highly transmissible, clinically significant antibiotic resistance genes, crucially to antibiotics that have not been administered. We propose that the primary outcome of antibiotic treatment is dysbiosis that predisposes the host to a myriad of diseases, significantly increasing the risk of spread and transmission of multidrug-resistant bacteria to humans.
INTERACTIONS BETWEEN FUNDAMENTAL ANALYSIS AND MARKET PERFORMANCE FOR ROMANIAN COMPANIES: A PANEL DATA APPROACH

We investigate non-financial Romanian companies listed on the Bucharest Stock Exchange during 2002-2009 and conduct our research in two main directions: (1) an understanding of dynamic trade-offs among efficiency, profitability and leverage across companies using the Du Pont model, market ratios and market-based performance measures; (2) a balanced panel data analysis that considers the heterogeneity in companies’ performance. We find the performance of Romanian companies was highly fluctuating from one year to the other, suggesting that firms do not employ over the years the same tools to boost or maintain their overall performance. The market performance of Romanian companies follows their financial performance and was also fluctuating, no company being able to offer investors constantly good risk-adjusted returns. Fundamental analysis influences companies’ performance in the capital market, but such influence is observed only at the level of simpler indicators, which might indicate a rather low financial maturity of investors present on the Romanian market.
Defining agroecology: exploring the circulation of knowledge in FAO's Global Dialogue.

This article traces how ‘agroecology’ is co-produced as a global socio-technical object. The site of co-production, the Global Dialogue on Agroecology, was convened by the Food and Agriculture Organization of the United Nations (FAO) in different cities around the world between 2014 and 2018 (Rome 2014; Brasilia, Dakar, Bangkok 2015; La Paz, Kunming, Budapest 2016; Rome 2018). We analyze these ‘expert’ symposia and regional meetings by exploring how knowledge about agroecology circulates and frames the terms of debate. Our analysis is based on an ethnography carried out by the first author since 2013 and participant observations by both authors in the Global Dialogue. We focus on three key processes that contribute to the stabilization of a global agroecology: 1) the work carried out to define ‘agroecology’, 2) actors’ interests and strategies that are revealed through the politics of circulation, and 3) the emergence of the ‘evidence based’ logic within this dialogue and the ‘experts’ who are legitimized. We argue that the version of ‘agroecology’ that was stabilized through the Global Dialogue is one that has been highly influenced by civil society actors, even though they were not recognized as ‘experts’ in the process. We conclude with reflections upon the politics of ‘agroecological’ knowledge and what this means for the institutionalization of agroecology.
External Crisis Prediction Using Machine Learning: Evidence from Three Decades of Crises Around the World1

As external crises can be economically disruptive events for advanced economies, emerging markets, and low-income economies alike, predicting such crises is an important task, yet a somewhat inglorious one. In this paper, we generate crisis lists for two types of external crises―sudden stops with growth impact, and exchange market pressure events―for 169 countries over 27 years, and we then evaluate the performance of signal extraction and machine learning techniques for the prediction of such crises. Bearing in mind the potentially sharp divergence between in-sample and out-of-sample performance, we design a rigorous testing procedure attuned to the temporal dependence of macro data and the manner in which the models would be used in practice. We find that for sudden stops with growth impact, the performance of signal extraction and machine learning techniques is comparable, and signal extraction sometimes performs better. For exchange market pressure events, which are more heterogeneous than sudden stops, we find that machine learning techniques do appear to perform better than signal extraction and binary regression models. We use the output of the models to shed light on variable importance rankings and on some of the important non-monotonicities and interactions that machine learning uncovers from the historical data. JEL Classification Numbers: C53, E37, F47
An Early Warning Model for School Dropout: a Case Study in E-learning Class

Dropping out of school is a real challenge for educational specialists. Considering distance education classes, we have to deal with a huge number of students’ disengagement with social and economic consequences. In order to solve the early drop out problem, this paper proposes the use of an Early Warning System capable of predicting the disengagement of students along the class and notify teachers about this behavior, enabling them to intervene in an effective way and make student’s success possible. In order to evaluate our proposal, we carried out a case study which showed the feasibility of the proposal and the use of its technologies. The results pointed out a significant increase of gain in accuracy along the course, reaching 93% of precision at the end.
Teachers' Perceptions on Traditional and Non-Traditional Data Visualization for Pedagogical Decision-Making

From 2012 until 2016, the number of US students enrolled in an online course increased 14.68%, resulting in more work for online teachers, who are responsible for planning and making pedagogical decisions to guide students. Interactions in such courses can generate data (quantity and variety), where relevant information in the educational context can be extracted, assisting teachers managing their classes. However, to present these data in spreadsheets, tables and graphics, is not enough. In this context, some authors suggest using data visualization to communicate information clearly and efficiently from the point of view of users, helping them analyze and reason about the data. However, people react differently to different types of visualization, which we categorized in two broad groups: traditional or non-traditional. We evaluated how users reacted to these types of visualizations and what users’ features are associated with their preferences for one category or the other. In this paper, we surveyed 235 teachers to evaluate how these two categories of visualizations affect the way participants evaluate data from an online course. They had to check the visualizations and identify which item contributed the most, and which item contributed the least to the performance of the students. The answers (correct or incorrect) were evaluated regarding the teachers’: age, gender, experience, education and perception on the usefulness of each visualization. Our ultimate purpose was to create a model to recommend visualizations according to the teachers’ profile.
The Effect of Consumer Attitudes on Credit Card Usage in Kenya

Despite the fact that credit card services have been provided in Kenya for some time, the growth in usage has been rather slow. The purpose of this paper is to find out how consumer attitudes towards credit cards affects their usage. A cross-sectional survey was conducted by administering a structured questionnaire to 395 respondents. Stratified random sampling was used and the respondents were picked at large shopping malls in Nairobi. The findings reveal that consumer attitudes – cognitive aspects, affective aspects and behavioural aspects affect credit card usage. The findings provide information that bank managers can use to guide them as they work towards influencing consumer attitudes towards credit cards. This paper makes a valuable contribution since very few studies have been done on attitudes and credit card usage in Kenya.
Effect of Financial Management Practices on Performance of Savings and Credit Co-Operative Societies in Mombasa County, Kenya

The study sought to establish effect of financial management practices on financial performance of Saccos in Mombasa county, Kenya. The study used descriptive research design and data was collected by administering questionnaires to a sample of target population. Data analysis was done using correlation and regression analysis. The research used regression analysis to investigate the association of cash management, financial planning, financial reporting and analysis and number of Sacco members on financial performance of Saccos in Mombasa county. Based on correlation matrix, cash management had a huge effect on financial performance of Saccos with the highest score of 0.637 followed by financial reporting and analysis at 0.299. In this study, cash management practices were found to have big effect in the financial performance of Saccos as was demonstrated by a strong regression coefficient. The regulator should also ensure all Saccos embrace financial reporting and analysis throughout their operations as per financial reporting standards. Number of Sacco members was also found to have an effect on profitability of Saccos. Sacco management should come up with ways of registering more members to join their Saccos through vigorous campaign. To attract more members, management can consider issues like proper loan policies, better returns in the form of dividends, and open membership to any adult citizen. The study recommended that researchers and scholars should carry out a research on other factors affecting financial performance of Saccos in Kenya not covered in this study.
On one-stage recovery for Σ∆-quantized compressed sensing

Compressed sensing (CS) is a signal acquisition paradigm to simultaneously acquire and reduce dimension of signals that admit sparse representations. When such a signal is acquired according to the principles of CS, the measurements still take on values in the continuum. In today’s "digital" world, a subsequent quantization step, where these measurements are replaced with elements from a finite set is crucial. We focus on one of the approaches that yield efficient quantizers for CS: Σ∆ quantization, followed by a one-stage tractable reconstruction method, which was developed in [20] with theoretical error guarantees in the case of sub-Gaussian matrices. We propose two alternative approaches that extend the results of [20] to a wider class of measurement matrices including (certain unitary transforms of) partial bounded orthonormal systems and deterministic constructions based on chirp sensing matrices.
INVESTIGATION ON PERFORMANCE OF EPOXY COATED STEELS WITH NANO-SIO2 AND POLYANILINE COMPOSITE USING COMPLEX IMPEDANCE SPECTROSCOPY

This study was conducted to characterize an anti-corrosive epoxy coating for steel with NanoSiO2-Polyaniline (PANI) composites using low impedance spectroscopy. The epoxy coating was modified using a varying concentration of nano-filler combination. Coated steels were dipped in 3.5 wt% NaCl solution to induce corrosion. Impedances were measured from 20 Hz to 20 MHz. The electrical characterization was related to the coating performance of epoxy coating with varying concentration. The Nyquist and Bode plots were displayed and related to the graphs with the coating resistance and capacitance. Based on Nyquist plots, 40-60% combination of Nano-SiO2 and PANI has the largest semi-circle curve, while on Bode plots, still, the 40-60% combination has the largest magnitude of impedance and phase angles. Equivalent circuit model was fitted to measure directly the coating resistance and coating capacitance of the coated steel. Based on the equivalent circuit model, the 40-60% of Nano-SiO2 to PANI combination had the highest coating resistance equal to 9.50E7 ohms, and lowest coating capacitance of 2.0E-12 Farads. The results presented that all combinations have better corrosion protection performance compared to that of pure epoxy coated steel.
A.Golejewska, Foreign Direct Investment and Employment in a Host Country: ... 97

The paper presents potential effects of foreign direct investment (FDI) on the quantity, quality and location of employment in a host country. Empirical analysis shows direct impact of FDI on employment creation or preservation in Polish manufacturing during transition. In 1993-2000 employment growth in foreign investment enterprises did not compensate for the decline in domestic controlled employment. The most interested in investing in Poland are European investors. Foreign presence has a positive impact on performance of domestic industry as a whole in terms of both usage of capital-intensive technologies and labour productivity. Further econometrical research and more data are necessary to show indirect and spillover-effects of FDI in this area. These effects can have an impact equal or even higher than the direct creation of jobs in foreign firms.
Spinal reflexes exploit muscle characteristics: goal-directed arm movements in humans and bioinspired robotics

Daniel F.B. Haeuflea, Christina Pleya, Katrin Stollenmaiera, Winfried Ilga, Simon Wolfenb, Syn Schmittb aHertie Institute for Clinical Brain Research, University of Tübingen, Germany {daniel.haeufle}, {christina.pley}, {katrin.stollenmaier}, {winfried.ilg}@uni-tuebingen.de b Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Germany {schmitt},{simon.wolfen}@simtech.uni-stuttgart.de
The Pathways to College

We estimate the returns to college by school type using data from the Italian Participation Labor and Unemployment Survey. We find that returns are lower for vocational than for academic high school graduates in terms of employment probability (−4%), hourly wages (−3.1%), and the probability of finding the first job less than 1 year after graduation (−9.2%). The wage penalty associated with high school vocational education is lower when we consider college majors such as engineering and economics and business, for which the complementarity with the vocational skills developed in high school is presumably higher.
Skip intravenous thrombolysis―is direct intra-artery thrombectomy feasible for acute ischemic stroke?

刘建民 博士,海军军医大学(第二军医大学)长海医院临床神经医学中心主任、神经外 科和脑血管病中心教授、主任医师、博士生导师,全军脑血管病研究所所长,上海市脑卒中临 床救治中心主任,国家卫生健康委员会脑卒中防治专家委员会秘书长,中国医师协会介入医师 分会副会长。 长期从事脑血管病、脑肿瘤、癫疒间、脑外伤等神经系统疾病的医疗与研究,以脑 卒中诊治为特色,开展颅内动脉瘤、脑血管狭窄或闭塞、脑(脊髓)动静脉畸形等脑血管病治 疗万余例,首创颅内支架血管成形术等 11 项技术。 主持国家重点研发计划重点专项、国家科 技支撑计划、国家自然科学基金及军队临床高新技术重大项目等项目 21 项。 以第一作者或通 信作者发表论文 526 篇,其中 SCI 收录 115 篇;主编专著 4 部,撰写《中国神经外科学学科发 展报告》1 部,主持制定脑血管病相关指南 3 部;授权国家发明、实用新型专利 21 项。 先后应 邀在牛津大学、纽约大学、加利福尼亚大学、多伦多大学等 7 所国际知名大学讲学并进行手术 演示,在国际大会专题发言 30 余次。 获教育部科学技术进步奖一等奖、上海市科学技术奖一等奖、上海市医学科技奖一等 奖、军队医疗成果奖一等奖等奖项 11 项,获神经外科最高奖项——王忠诚神经外科医师奖,获总后勤部军队院校育才奖银 奖,先后被评为上海市优秀学科带头人、上海市领军人才、总后勤部优秀共产党员。
Classifying Alzheimer’s from fMRI Data using Convolutional Networks

Alzheimer’s disease is a neurodegenerative disorder that causes 60 – 70% of dementia and affects 5.3 million Americans. Symptoms begin mild but progressively worsen, leading many to go undiagnosed until late stages. Alzheimer’s has no cure, but early diagnosis leads to better patient care and planning before full cognitive impairment. Current diagnostic procedures involve a combination of medical records, cognitive tests, and hours of skilled doctors’ time. An automated method of diagnosing Alzheimer’s would be cheaper and faster than current diagnostic methods. Recently, machine learning algorithms have been developed to diagnose Alzheimer’s from fMRI data. However, these algorithms have only achieved high accuracies for binary classification, rather than classifying the stages of cognitive impairment. This paper presents a machine learning model that classifies five stages of cognitive impairment. The proposed algorithm achieves a state-of-the-art subject-level classification accuracy of 85.1%. Additionally, by analyzing the brain regions of interest to the model, the model indicates the hippocampus region, areas of white matter, and straight sinus are most important for diagnosing Alzheimer’s.