Miracle-dz/UniFAR-FTUs huggingface dataset:
A Preliminary Study on Prevalent Serovars of Leptospirosis among Patients admitted to Teaching Hospital, Kandy, Sri Lanka

Seroepidemiological data on leptospirosis in Sri Lanka is scarce. Hence, this study was conducted to identify circulating serovars among hospitalised patients with pyrexia for more than Þ ve days.From October 2002 to November 2003, all patients admitted to teaching hospital Kandy, with suspected leptospirosis were included in the study. IgM ELISA was performed on all suspected cases and positive samples were conÞ rmed using MAT. Twenty two reference strains belong to serovars australis, ballum, bataviae, bulgarica, canicola, celledoni, copenhgeni, cynopteri, djasiman, grippotyphosa, hardjo, hursbridge, javanica, kremastos, medenensis, pomona, panama, robinsoni, shermani, szwajizai, tarassovi, and zanoni were included in MAT analysis. Positive MAT was deÞ ned as a single titer of greater than or equal to 400. Out of 473 suspected cases, 74(15.6%) were positive, 25(5.3%) were equivocal and 374(79.1%) were negative for IgM ELISA test. Age distribution of the IgM positive cases showed an equal distribution among all age groups. Out of the 74 positives 48(64.9%) were males and 26(35.1%) were females. Around one third (35.1%) of these positive cases were either housewives or unemployed males. Common occupational categories were manual labourers (14.9%), agricultural workers of farmers (10.8%) and soldiers (5.4%). In MAT analysis, 31 serum samples showed anti-leptospira antibodies of which 18 (24.3%) had a MAT titer greater than or equal to 400. The serovars identiÞ ed included medenensis (4), australis (2), ballum (2), canicola (1), celledoni (1), cynopteri (2), hardjo (3), pomona (1) and robinsoni (2). Our Þ ndings showed that the predominant serovars among the study sample were serovar medenensis and hardjo. Interestingly serovars copenhegani, which belongs to serogroup icterohaemorrahgia was not detected in the samples. Previous studies have identiÞ ed serogroup icterohaemorrhagia as the commonly circulating serovar causing human infection in Sri Lanka.
Laparoscopic versus laparotomic appendectomy for generalisedperitinitis in children.

Laparoscopic appendectomy for appendicitis in its late stage with advanced generalised peritonitis does not show increased occurrence of early or late postoperative complications compared to classic laparotomic appendectomy. A null hypothesis expecting no differences was successfully confirmed using a statistical significance level. On the contrary, traditional open appendectomy is accompanied by more late complications, such as bowel adhesions. Based on this study, we can recommend laparoscopy as adequate for appendectomy also in its late stage with inflammation extending into the peritoneum.
PREDICTION OF PRESSURE AND ENERGY REQUIREMENT OF JATROPHA CURCAS L BULK SEEDS UNDER NON-LINEAR PRESSING

This article presents the theoretical evaluation of pressure and energy requirement of screw press FL 200 (Farmet Model, Czech Republic) for oil processing of Jatropha curcas L. bulk oilseeds. Both the linear and nonlinear compression information were analysed. The tangent curve mathematical model was applied which is appropriate for fitting of linear experimental data as the dependency between compressive force and deformation in relation to bulk seeds pressing height and vessel diameter. The integral of the tangent model represents energy. The non-linear pressing involving a mechanical screw press FL 200 geometric parameters namely screw shaft diameter (mm), inner and outer diameters (mm), screw thickness (mm) and screw pitch diameter (mm) were incorporated into the tangent curve mathematical model. The press designed with 44 lamellas at the oil outlet were divided into seven pressing sections or chambers. The determined amounts of pressure and energy substantially increased along the pressing sections. The results require validation to confirm the suitability of the tangent curve mathematical model for optimising the performance of screw press FL 200.
Burden sharing in families to children, adolescents and young adults with ADHD: Analysis of ADHD Helpline in Swedish Clinical Services

Abstract Background: ADHD causes impairment in several life contexts and may increase stress and burden of care amongst family members. There is a lack of studies regarding gender inequalities in burden sharing in families of individuals with ADHD. Objective: The aim of this study was to investigate gendered burden sharing in families who were in contact with an ADHD telephone helpline in Sweden. A further aim was to identify perceived difficulties that prompted contact with the helpline. Methods: During a period of 28 months (from January 2013 to April 2015), calls were consecutively registered by psychologists manning the helpline through an anonymous digital form. After exclusion of 60 incomplete forms out of 1,410 (4%), information on 1,350 calls was analysed. Results: The analysis indicated that mothers (82.7% of all callers) had a more important role as information-coordinators for children or adolescents with ADHD, as compared to fathers (13%) or other callers (4.3%). This pattern was also observed among the calls regarding young adults with ADHD. Helpline calls primarily concerned entitlement to academic support (57.9% of calls concerning children or adolescents) and healthcare services (80.6% of calls concerning young adults and adults). Conclusion: The study concludes that a perceived lack of accessibility to and/or coordination of the school and health care services may be a major stressor for parents of individuals with ADHD. The burden of care through coordination of services and information-seeking may be especially increased in mothers of children, adolescents, and young adults with ADHD.
Ignorance Is Bliss? Rent Regulation, Policy Awareness, and Labor Market Outcomes: Evidence from New York City

Rent regulation is central to the a↵ordable housing policies of local municipalities and is on the rise in the United States and worldwide. In this paper I explore the unintended consequences of rent regulation on tenant labor market outcomes, along with the impact that policy awareness has on those outcomes, using a novel data set on rent stabilization in New York City. Recognizing the potential endogeneity of living in a rent-stabilized unit, I construct an instrumental variable that leverages variation in the availability of rent-stabilized units across New York boroughs over three decades of data. I then use the sorted e↵ects method in Chernozhukov, Fernández-Val, and Luo (2018) to investigate heterogeneous effects. I find that rent-stabilized tenants are more likely to be unemployed compared with tenants in private market-rate units, particularly among white and high-skilled tenants. Furthermore, I identify policy awareness using a unique feature of the data, and show that a large share of rent-stabilized tenants are either misinformed or unaware of their rent regulation status. The impact of rent stabilization on unemployment only exists among tenants who are aware of their regulation status.
Mining an "Anti-Knowledge Base" from Wikipedia Updates with Applications to Fact Checking and Beyond

We introduce the problem of anti-knowledge mining. Our goal is to create an "anti-knowledge base" that contains factual mistakes. The resulting data can be used for analysis, training, and benchmarking in the research domain of automated fact checking. Prior data sets feature manually generated fact checks of famous misclaims. Instead, we focus on the long tail of factual mistakes made by Web authors, ranging from erroneous sports results to incorrect capitals. We mine mistakes automatically, by an unsupervised approach, from Wikipedia updates that correct factual mistakes. Identifying such updates (only a small fraction of the total number of updates) is one of the primary challenges. We mine anti-knowledge by a multi-step pipeline. First, we filter out candidate updates via several simple heuristics. Next, we correlate Wikipedia updates with other statements made on the Web. Using claim occurrence frequencies as input to a probabilistic model, we infer the likelihood of corrections via an iterative expectation-maximization approach. Finally, we extract mistakes in the form of subject-predicate-object triples and rank them according to several criteria. Our end result is a data set containing over 110,000 ranked mistakes with a precision of 85% in the top 1% and a precision of over 60% in the top 25%. We demonstrate that baselines achieve significantly lower precision. Also, we exploit our data to verify several hypothesis on why users make mistakes. We finally show that the AKB can be used to find mistakes on the entire Web.
EFFECTS OF DIFFERENT CONVERSATION TILLAGE SYSTEMS ON SOIL PHYSICAL PROPERTIES IN WEST MEDITERRANEAN IN TURKEY

The study was conducted during two summer seasons (2012 and 2013) under Mediterranean area conditions (South of Turkey) to determine the effect of four tillage system (conventional tillage (T1) “Plough + disc harrowing + float + pneumatic seeding machine”, reduced tillage I (T2) “rotovator + float + pneumatic seeding machine”, reduced tillage II (T3) “rotary tiller combination + pneumatic seeding machine” and no tillage (T4) “seeding by direct seeding machine”) on the soil physical properties in the area. The soil of the experimental parcel was classified as silty. There was no significant different statistically among soil porosities of tillage systems in all depths at after tillage and harvesting operation. For variation though conversation tillage methods, tillage methods X measuring time, tillage methods X depth and tillage methods X measuring time X depth interactions were significant statistically for four tillage systems (p<0.001).
University of Birmingham Did the reporting of prognostic studies of tumour markers improve since the introduction of REMARK guideline?

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Improvement of the Quality of Business Environment Model: Case of the SME Segment

The aim of this article is to define important factors which determine the quality of the business environment and construct a structural model of causal relationships between quality of business environment and its determinants in small and medium sized enterprises. This model was constructed on the basis of extensive empirical research. A questionnaire was designed and delivered to SMEs operating in the Czech and Slovak Republics. The sample consists of 641 enterprises from both countries. Data were evaluated using statistical methods such as confirmation factor analysis and structural equation modeling. The structural model showed very interesting findings. The most important factors, which determine the quality of business environment are macroeconomic environment, monetary policy and interest rates and legal environment. In our model, we also pointed out the importance of political, social and technological factors. The research results pointed to the need to adjust the legislative environment in a more appropriate way, to minimize state bureaucracy and to improve media access to business environment assessment. These results are useful for the academic researchers in the area of entrepreneurship, policymakers, and non-profit institutions and organizations whose effort is to improve the business environment and boost entrepreneurship.
A Fiscal Theory of Monetary Policy with Partially-Repaid Long-Term Debt

Abstract I construct a simple model with sticky prices and interest rate targets, closed by fiscal theory of the price level with long-term debt and fiscal and monetary policy rules. Fiscal surpluses rise following deficits, to repay accumulated debt, but surpluses do not respond to all values of unexpected inflation and deflation. This specification avoids common puzzles and produces reasonable responses to fiscal and monetary policy shocks. It allows an easy translation of any new-Keynesian model, and it allows one to study a whole sample with active fiscal policy.
Integrating Human Ecology into Sustainable Development to Address Potencies and Challenges of the City of Batam as a Port City

Social development is frequently marginalized in infrastructure and technology-based development. This paper attempts to portray the importance of the study of human ecology in a social environment to mediate the transformation efforts in social environment development that increase aspects of social-cultural life quality. An observation and mixed method analysis within the context of a case study is used to show the interaction between human ecology and sustainable development with respect to the potential and changes during a disruption in the City of Batam as a port city. The results show that innovation and transformation related to human development are still more favorable in strategic human development despite the need for modern smart port city
Systematic Review with Meta-analysis: Association of Helicobacter pylori Infection with Esophageal Cancer

Background Helicobacter pylori is an important carcinogenic factor in gastric cancer. Studies have shown that Helicobacter pylori infection is inversely associated with certain diseases such as esophageal cancer and whose infection appears to have a “protective effect. ” At present, the relationship between Helicobacter pylori infection and esophageal cancer remains controversial. This study was designed to investigate the relationship between Helicobacter pylori infection and the risk of esophageal cancer in different regions and ethnicities. Methods Systematic search of the articles on the relationship between Helicobacter pylori infection and esophageal cancer from the database with the duration time up to December 2018. This systematic review was performed under the MOOSE guidelines. Results This meta-analysis included 35 studies with 345,886 patients enrolled. There was no significant correlation between Helicobacter pylori infection and esophageal squamous cell carcinoma in the general population (OR: 0.84; 95% CI: 0.64-1.09/OR: 0.74; 95% CI: 0.54-0.97). However, a significant correlation was found in the Middle East (OR: 0.34; 95% CI: 0.22-0.52/95% CI: 0.26-0.44). There was no significant difference in the prevalence of Helicobacter pylori between the case group and the control group in esophageal adenocarcinoma (8.87% vs. 9.67%). The pooled OR was 0.55 (95% CI: 0.43-0.70) or 0.23 (95% CI: 0.15-0.36). When grouped by match or not, the pooled OR of the nonmatching group and the matching group was 0.48/0.21 (95% CI: 0.36-0.65/95% CI: 0.13-0.36) and 0.73/0.71 (95% CI: 0.57-0.92/95% CI: 0.60-0.84), respectively. Conclusion In the general populations, no significant association was found between Helicobacter pylori infection and the risk of esophageal squamous cell carcinoma. However, lower risk was found in the Middle East. Helicobacter pylori infection may reduce the risk of esophageal adenocarcinoma, but such “protection effect” may be overestimated.
CFD Analysis of Ship Propeller Thrust Breakdown

The variation of propeller performance with respect to cavity extent over the blade surface is investigated by DES with a cavitation model. INSEAN E779A propeller is considered as a test case, because the cavitation tunnel test results of thrust and torque breakdowns with respect to cavitation number and cavity extent are available for several loading conditions (Pereira et al 2004a). Cavitation simulation results are validated against the experimental result at two cavitation numbers in the highest loading condition among those considered in the experiment. In the validation, the effects of the transition model and the seed density on cavity extent and propeller performance are examined and the propeller inflow is adjusted to reach the measured thrust instead of modeling the blockage effect of the cavitation tunnel. Cavitation simulations are made with varying cavitation number. The comparison of the CFD and experimental results shows a reasonable agreement in the variations of cavity extent, thrust and torque in moderate cavitation. Thrust and torque breakdowns are simulated at higher cavitation numbers and larger cavity extents in CFD, as cavity area is overestimated especially in extensive cavitation.
A comparison of methodologies for the staining and quantification of intracellular components of arbuscular mycorrhizal fungi in the root cortex of two varieties of winter wheat

Arbuscular mycorrhizal (AM) fungi are one of the most common fungal organisms to exist in symbiosis with terrestrial plants, facilitating the growth and maintenance of arable crops. Wheat has been studied extensively for AM fungal symbiosis using the carcinogen trypan blue as the identifying stain for fungal components, namely arbuscles, vesicles and hyphal structures. The present study uses Sheaffer blue ink with a lower risk as an alternative to this carcinogenic stain. Justification for this is determined by stained wheat root sections (n=120), with statistically significant increases in the observed abundance of intracellular root cortical fungal structures stained with Sheaffer blue ink compared to trypan blue for both Zulu (P=0.003) and Siskin (P=0.0003) varieties of winter wheat. This new alternative combines an improved quantification of intracellular fungal components with a lower hazard risk at a lower cost.
Gender Peer Effects in the Workplace: A Field Experiment in Indian Call Centers

Several theories suggest that gender integration in the workplace may have negative effects in gender-segregated societies. This paper presents the results of a randomized controlled trial on the effect of gender integration on work productivity. The study was implemented in call centers located in five Indian cities. A total of 765 employees were randomized to either mixed gender teams (30-50% female peers) or control groups of same gender teams. I find precisely estimated zero effects on both productivity (intensive margin) and share of days worked during the study period (extensive margin) of being assigned to a mixed gender team. However, there is an overall increase in the secondary outcome of peer monitoring and team support for women assigned to mixed gender teams relative to the control team. For male employees, I find that conditional on being assigned to mixed gender teams, men with progressive gender attitudes have higher productivity than men with regressive gender attitude. There is an overall increase in the secondary outcomes of knowledge sharing, dating and comfort with the opposite gender for male employees in mixed gender teams, relative to all male teams. *I am grateful for the invaluable guidance, immense support and unwavering encouragement over the course of this project from my advisors, Anil Deolalikar, Sarojini Hirshleifer and Joseph Cummins. This paper has also benefitted from helpful comments from Steven Helfand, Michael Bates, Carolyn Sloane, Bree Lang, Matthew Lang, Gordon Dahl, Jonas Hjort and the faculty mentors as well as the faculty mentors and selected workshop participants at the Ronald Coase Institute. I would like to thank the International Growth Center (IGC), BLUM Initiative at UC Riverside and Graduate Division, UC Riverside (Dissertation Year Program Fellowship) for funding this project. I am grateful to the CEOs and center heads of partner call centers, Anil Sinha, Rajeev Jha and Sujit Sharma of Call-2-Connect and Kapil Sharma, Lakhan Joshi and Soham Ghosh of Five Splash for believing in the project and offering their support. I appreciate the help of Ministry of Electronics and IT: Government of India, Software Technology Parks of India and Bihar Industries Association for introducing and recommending this project to call centers. Thanks also to Anil Kumar Vaishnav, Daizzy Sharma, Prabudh Rao Kaushal, Rajat Kumar and Priyanka Jadhav for their outstanding assistance in data collection. The RCT was pre-registered at the AEA registry with ID # AEARCTR-0003932.
An Analysis and Comparison of Adoption of E-learning Systems in Higher Education by Lecturers at Largest Universities in Estonia and Turkey

In this study, for the first time, we analysed and compared adoption of e-learning by lecturers in three largest universities in Estonia and Turkey. Total number of students and academic staff in the Estonian universities is 39,259 and 3,991, respectively, and 1,194,735 and 9,076, respectively, in the Turkish universities. The extended Technology Acceptance Model (TAM2) was used to analyse results of acceptance and usage of e-learning by 923 lecturers (298 from Estonia and 625 from Turkey) or 22% from the sample subject, took part in the research from the studied universities. Total number of respondents subjected to the questionnaire distribution was 4,198 (1,423 in Estonia and 2,775 in Turkey). We found and analysed strong and weak sides of e-learning and main barriers, which hinder adoption of e-learning in Estonian and Turkish largest universities. Immediate measures to support development and improvement of e-learning system at higher education in these universities were suggested.
A Neural Network Model for Wildfire Scale Prediction Using Meteorological Factors

A forest fire is a natural disaster that destroys forest resources, thus having a severe impact on humans and on the animals and plants that depend on the forest environment. This paper presents a model for predicting the scale of forest wildfires of Alberta, Canada. A fire’s scale is determined by the combination of the fire’s duration and the size of the area it burns. Our prediction model enables fire rescuers to take appropriate measures to minimize damage caused by a wildfire based on its predicted scale in the fire’s early stages. The modeling data were collected from the Canada National Fire Database (CNFDB) published by Natural Resources Canada, which includes wildfire and meteorological data for Alberta, Canada. The size of the burned area and the fire’s duration were used to estimate the scale of a wildfire. After multi-collinearity testing and feature normalization, the data were divided into training and testing sets. Taking the meteorological factors as input values, a backpropagation neural network (BPNN), a recurrent neural network (RNN), and long short-term memory (LSTM) were implemented to establish prediction models. Of these classification methods, LSTM exhibited the highest accuracy, 90.9%. The results indicate that it is feasible to predict the scale of a forest wildfire at the beginning of its occurrence using meteorological information.