Miracle-dz/UniFAR-FTUs huggingface dataset:
Cross-institutional OSCE Quality Assurance in Europe using a mutual assessment strategy; are we equipped for it?

BackgroundUntil 2008, Objective Structured Clinical Examinations (OSCE) were well researched, laborious and costly paper based method of exam delivery restricting international comparison. Cross-institutional comparison of OSCE Quality Assurance in Europe has never been done and due to wide spread electronic assessment analysis is now available.MethodsTwenty educational institutions across Europe using an electronic OSCE Management Information System where invited of which 8 confirmed to join a mutual comparison of Quality Assurance outcome. Two theories evaluate the quality of the observed test scores, the Classical psychometric theory (Cronbach’s alpha) and the Generalizability theory. Outcomes for both were compared for all universities including the Standard Error of Measurement (SEM) as well as cut-scores, Pass/Fail score and Global Rating Scores, Cronbach’s Alpha and related SEM (68% and 95% CI) and G-theory Coefficients with related absolute and relative SEM (68% and 95% CI). ResultsOutcomes differ between participating universities and observed marks contradict global rating of fail, borderline and excellent performance. G-theory coefficients and Standard Error of Measurement were lower and smaller compared to the classical approach using Cronbach’s Alpha as measure of reliability. The Classical psychometric based SEM varies from 2.8% to 11.2% respectively whereas the 95% CI equivalent varied from 9.2% up to 22% (on a 0 - 100% scale). The relative SEM from G-theory analysis varied from 3.1% to 7.0% for criterion-referenced marks, and the absolute SEM for norm-referenced marks varied from 3.8% to 7.8% respectively. The 95% CI around the relative and absolute SEMs values varied from 7.3% to 15.3%. More students failed the examination if the 95% CI is applied to the observed scores.ConclusionTo protect society and to improve educational decision making, the Standard Error of Measurement and associated confidence intervals needs to be embedded in EU assessment strategies to rule out ‘false positive Pass decisions’.
Identification of a major quantitative trait locus, qGER4.2, conferring resistance to Gibberella ear rot in maize using a Chinese recombination inbred line population

Background: Gibberella ear rot (GER), a prevalent disease caused by Fusarium graminearum, can result in yield loss and mycotoxin contamination in maize. Despite that several QTLs related to GER resistance have been reported previously, few of them was identified in Chinese maize inbred lines. In this study, we employed a Chinese recombination inbred line (RIL) population comprising of 204 lines, developed from a cross involving a resistant parent DH4866 and a susceptible line T877. The population was phenotypically evaluated at three field trial locations under artificial inoculation with F. graminearum and genotyped with an Affymetrix microarray CGMB56K SNP Array to detect the quantitative trait loci (QTLs) for resistance to GER. Results: Based on the genetic linkage map constructed using 1,868 bins as markers, a total of 15 QTLs were identified, and both DH4866 and T877 alleles at these QTLs contributed toward resistance. Of these QTLs, five were stably expressed across multiple locations, including three co-localized with previously reported genomic regions. The largest-effect QTL located on chromosome 4, qGER4.2, which accounted for 5.66~17.10% of the phenotypic variation, was detected at all locations. Based on the phenotypic values of the alleles corresponding to the five stable QTLs, a significant correlation (r2 = 0.45) between resistance to GER and the number of resistant alleles was observed. Conclusions: QTL mapping was successfully employed to identify genetic loci conferring resistance to GER by a high-density genetic map constructed from two Chinese maize germplasms. The five stable QTLs identified, especially the large-effect QTL, qGER4.2, will be useful in maize breeding programs aimed at improving GER resistance.
Clinical and microbiological efficacy of medicinal maggots in the treatment of pressure ulcers in Egypt

Pressure ulcers are a significant public health problem, especially for patients in long term care facilities. This study aimed to assess the clinical and microbiological efficacy of maggot therapy in the treatment of pressure ulcers. The study was conducted on 14 bed-bound patients with 14 pressure ulcers at Alexandria Main University Hospital, Alexandria, Egypt. The blowfly Lucilia sericata was used for maggot therapy. Each ulcer was treated by one maggot cycle of 3 days per week. The ulcers were investigated weekly for changes in their size, the size of necrotic tissue, and the bacterial burden before and after each maggot cycle. Of the 14 ulcers treated with maggot therapy, three ulcers were completely debrided of which one ulcer needed only one cycle and two ulcers were debrided by two cycles. Nine ulcers had > 50% of their size occupied by a red healthy granulation tissue during a mean period of 2.14 weeks. The mean of the initial bacterial burden of ulcers was significantly decreased from 4.86  10 CFU/ml exudate to 1.92  10 CFU/ml exudate (p=0.01814) below the 10 thresholds of natural healing after the first maggot cycle. The clinical and microbiological outcomes demonstrate that maggot therapy is a rapid, simple, efficient, and cost-effective tool for treating pressure ulcers that do not respond to conventional treatment and surgical intervention.
Increasing Third Grade's Mastery of Simple Present Tense Using Flashcards.

Mastering the simple present tense can be very difficult for EFL young learners because tenses contain abstract concepts that do not exist in the first language of EFL learners. The third graders at Permai Elementary School, North Jakarta, also encountered problems in mastering the tense when they are taught using the lecture method. To solve the problem, action research was conducted by using flashcards. The action research was carried out in two cycles in August to October 2019. Involving 30 third graders, quantitative and qualitative data were collected employing tests, observation, and questionnaires. The findings revealed that flashcards use managed to increase the students’ achievement in learning the simple present tense. The mean scores of the three tests administered during the action research increased from 36.69 to 65.73 and to 75.00. The use of flashcards also changed the students’ attitude from mainly negative to mainly positive. The mean of the positive responses increased from 20.4% in the pre-action survey to 83.89% in the post-action survey.
Modified Reciprocal Teaching: Cooperative Learning Technique for Enhancing Communication Skills of First Year Engineering Students

With the advancement of technology and globalization, Communication skills as a life-long learning skill is an essential component in engineering education. Communication is one of 12 graduate attributes, defined by ABET (Accreditation Board for Engineering and Technology). The engineering classroom is currently experiencing a shift from teacher-centred teaching where teacher focused on what they are teaching, to studentcentred learning through innovative teaching-learning techniques. Active learning has become a significant process in outcome-based education (OBE). It comprises various approaches such as cooperative and collaborative learning techniques, PBL (problem/project/puzzle-based Learning), TBL (Task based learning), Peer instructions, TP-S (ThinkPairShare), Flipped Classroom and Reciprocal Teaching and many others. The Reciprocal Teaching is an instructional strategy specially designed for comprehension purpose. The present work offers some insights after successful implementation of modified reciprocal teaching for improving communication skills of First Year B. Tech. students at Kasegaon Education Society’s Rajarambapu Institute of Technology, Rajaramnagar (RIT). It was an attempt to develop all four basic language skills: Listening, Speaking, Reading and Writing. This research was conducted for four weeks during practical sessions. After successful implementation the students of experimental group were assessed by qualitative and quantitative methods. The results reflected increase in CO attainment of experimental group as compared to control group. The structured implementation of modified reciprocal teaching as an active learning tool helped to enhance students’ presentation skills, team work, leadership skills, and ultimately communication skills.
Machine-Learning-Based Approach to Differential Diagnosis in Tuberculous and Viral Meningitis

Background Tuberculous meningitis (TBM) is the most severe form of tuberculosis, but differentiating between the diagnosis of TBM and viral meningitis (VM) is difficult. Thus, we have developed machine-learning modules for differentiating TBM from VM. Material and Methods For the training data, confirmed or probable TBM and confirmed VM cases were retrospectively collected from five teaching hospitals in Korea between January 2000 - July 2018. Various machine-learning algorithms were used for training. The machine-learning algorithms were tested by the leave-one-out cross-validation. Four residents and two infectious disease specialists were tested using the summarized medical information. Results The training study comprised data from 60 patients with confirmed or probable TBM and 143 patients with confirmed VM. Older age, longer symptom duration before the visit, lower serum sodium, lower cerebrospinal fluid (CSF) glucose, higher CSF protein, and CSF adenosine deaminase were found in the TBM patients. Among the various machine-learning algorithms, the area under the curve (AUC) of the receiver operating characteristics of artificial neural network (ANN) with ImperativeImputer for matrix completion (0.85; 95% confidence interval 0.79 - 0.89) was found to be the highest. The AUC of the ANN model was statistically higher than those of all the residents (range 0.67 - 0.72, P <0.001) and an infectious disease specialist (AUC 0.76; P = 0.03). Conclusion The machine-learning techniques may play a role in differentiating between TBM and VM. Specifically, the ANN model seems to have better diagnostic performance than the non-expert clinician.
Numerical and Theoretical Studies of Radiation from Plasma Dipole and its Applications

Localized plasma dipole oscillation technique was first proposed by Kwon K. et al in 2016 as an efficient terahertz radiation source [1]. This can be achieved by cross-shooting two-color ultrashort laser pulses into plasma and can be applied for diagnostic purposes as well. Ensemble of charged particles oscillating like plasma dipoles radiate EM waves at plasma frequency ( p) with narrowband spectrum and carry meaningful information about the bulk plasma. In particular, by measuring the frequency of radiated signals, local plasma density at the focused point can be detected. Comparing the new idea with the conventionally utilized techniques such as interferometry, reflectometry and Langmuir probes [2-4], we insist that our method has numerous advantages as a technique for measuring the density [5]. Theoretical estimations accompanied by 1D, 2D, and 3D PIC simulations indicated that embedded plasma dipole oscillators show complex behavior leading to harmonic generations and many nonlinear effects that require further investigation. In this thesis, THz radiation scheme and density reconstruction measurements are reported and the investigations about magnetic field effects and harmonic generations are introduced briefly.
Perspectives From Underserved African Americans and Their Health Care Providers on the Development of a Diabetes Self-Management Smartphone App: Qualitative Exploratory Study

Background Type 2 diabetes mellitus (T2DM) affects approximately 10% of the US population, disproportionately afflicting African Americans. Smartphone apps have emerged as promising tools to improve diabetes self-management, yet little is known about the use of this approach in low-income minority communities. Objective The goal of the study was to explore which features of an app were prioritized for people with T2DM in a low-income African American community. Methods Between February 2016 and May 2018, we conducted formative qualitative research with 78 participants to explore how a smartphone app could be used to improve diabetes self-management. Information was gathered on desired features, and app mock-ups were presented to receive comments and suggestions of improvements from smartphone users with prediabetes and T2DM, their friends and family members, and health care providers; data were collected from six interactive forums, one focus group, and 15 in-depth interviews. We carried out thematic data analysis using an inductive approach. Results All three types of participants reported that difficulty with accessing health care was a main problem and suggested that an app could help address this. Participants also indicated that an app could provide information for diabetes education and self-management. Other suggestions included that the app should allow people with T2DM to log and track diabetes care–related behaviors and receive feedback on their progress in a way that would increase engagement in self-management among persons with T2DM. Conclusions We identified educational and tracking smartphone features that can guide development of diabetes self-management apps for a low-income African American population. Considering those features in combination gives rise to opportunities for more advanced support, such as determining self-management recommendations based on data in users’ logs.
Can an ontology really support the development of more accurate data quality assessment models? : A survey

Data is considered to be of high quality if it satisﬁes the requirements of intended use. There is a colossal amount of linked data available on the web. However, it is diﬃcult to know how well the linked data ﬁt the modeling tasks due to the defects present in the data. Faults present in the linked data spread far and wide, aﬀecting all the services designed for it. Addressing linked data quality deﬁciencies requires functions such as the identiﬁcation of quality problems, quality assessment and the reﬁnement of data to improve its quality. This study aims to identify existing end-to-end frameworks for quality assessment and improvement of data quality. One important ﬁnding is that most of the work deals with only one aspect rather than a combined approach. Another ﬁnding is that most of the framework aims at solving problems related to DBpedia. Therefore, a standard scalable system is required that integrates the identiﬁcation of quality issues, the evaluation and the improvement of the quality of the linked data. This survey contributes to the understanding of the state of the art of data quality evaluation and data quality improvement. A solution based on ontology is also proposed to build an end-to-end system that analyzes the root causes of quality violations.
Versatility of the gold nanoparticle

Gold is a noble metal, and it is commonly used because of its resistance to oxidation and electrical, magnetic, and physical properties. Forming gold into nanoparticles allows researchers to use gold in areas that are too small for bulk gold to reach and brings with it new capabilities. Gold nanoparticles have been utilized for centuries by artists due to the vibrant colors produced by their interaction with visible light. Gold nanoparticles, exhibit good chemical stability, and they can be surface functionalized with almost every type of electron-donating molecule including biomolecules. Gold nanoparticles are undoubtedly very versatile. Gold nanoparticles have played an important and severe role in medicine since ancient times. Also, gold nanoparticle is the most suitable for drug delivery applications. Drug delivery using gold nanoparticles, in combination with their intrinsic capability for photothermal therapy, should be explored in the future.
Study on the job performance of Chinese physicians: a moderated mediation model

Background:To explore the mechanisms between achievement motivation and job performance among physicians of public hospitals in China, this article researched the influence of different personality traits on physicians' job performance. Methods: A survey conducted in 2017, containing samples of 1,523 physicians from eight tertiary grade A hospitals in Harbin, China.A cross-sectional study was applied to data collection about physicians’ achievement motivation, job performance, organizational commitment, personality traits and other demographic variables. This paper also analyzed the relationships between physicians’ job performance and achievement motivation using a moderated mediation model.Independent t-test and ANOVA were applied to describe and compare the demographic data. Pearson correlation coefficients were used to examine the correlation among the variables. To test the correlation of the eight variables, moderated mediation analysis was performed in this study. Results:Achievement motivation directly affects job performance of Chinese physicians, and organizational commitment partially mediates the direct effects of achievement motivation on job performance. Additionally, we also found that agreeableness and conscientiousness moderate the strength of the relationships between achievement motivation and job performance mediated by organizational commitment. Conclusions:Managers in Chinese public hospitals should pay attention to increase physicians’ level of achievement motivation, and we recommend to enhance organizational commitment through a reasonable compensation system and active organizational culture. And they should also tend to be conscientiousness or agreeableness in the arrangement. Key Words job performance; hospital management; achievement motivation; psychology; moderated mediation model
Multidimensional Information and Rational Inattention*

This paper studies a rational inattention model in which a principal communicates with an uninformed agent about correlated multidimensional information. The principal agrees with the agent about appropriate actions to be taken given the states, though the players have potentially different preferences about relative importance of each dimension. I show that if the agent’s loss from suboptimal actions in one of the dimensions could be influenced by the principal, it would benefit the principal to increase the weight that agent places on the loss of this dimension when agent’s cost of processing information is either low or high, regardless of the principal’s weight on the loss. If cost is in the intermediate range, extra incentive provision on the dimension important to the agent could be harmful, particularly at the lowest cost such that decision quality of the other dimension would be affected. In this case, I characterize the condition under which it benefits the principal to provide (only) information about the dimension that is more important from her perspective but withhold information about the dimension more important to the agent. Withholding information of either dimension will not favor the principal when the agent’s cost is low or high. I find that the principal could be better off if the dimension important to the agent involves more complex information, but always gets a weakly lower payoff if the dimension important to the principal has more information. The model has implications for controlling incentives and information available in organizations.
Heart Rate Measurement Combining Motion and Color Information

Daily monitoring of the heart rate can facilitate detection of heart-related diseases in their early stages. Therefore, providing an easy-to-use and noninvasive heart rate monitoring system has been a very popular research topic in the field of healthcare. One of good candidate methods is to use commonly available cameras and extract information that can help to estimate heart rate from a human face. Generally, such information can be retrieved using two different approaches: photoplethysmography (PPG) and ballistocardiography (BCG). PPG exploits slight color changes caused by blood volume variations during heartbeats; thus, it tends to be vulnerable to unstable lighting conditions. BCG exploits subtle head motions caused by pumped blood travelling through the carotid artery during heartbeats; thus, it is vulnerable to the voluntary head movements that are not related to heartbeats. Nevertheless, most related works use either to estimate the heart rate. In this paper, we propose to combine two approaches to be robust to challenging conditions. Specifically, we explore possible ways to combine raw signals obtained from two approaches and verify that the proposed combination shows better accuracies under challenging conditions, such as voluntary head movements and ambient lighting changes.
Analysis of land cover changes using the Change Detection Toolbox: a case study of suburbanisation in the Senec district, Slovakia

Land cover changes are currently being monitored very closely as they affect climate change, habitat disappearance and other related phenomena. One of the socio-economic processes manifested by significant land cover changes is suburbanisation. In terms of the land cover, suburbanisation is reflected in an increase of built-up areas in the hinterland of cities. In Slovakia, the process of suburbanisation is most pronounced in the hinterland of the capital Bratislava, with the most dynamic expansion of built-up areas in the district of Senec. We evaluated the land cover changes in the Senec district from 2000 to 2018 on the base of Urban Atlas data layers and satellite images. For these purposes, we designed a conversion table based on the Urban Atlas 2006 legend, which identifies nine types of changes within the urbanisation process. The conversion table allows effective visualization of landscape changes to assess their spatial distribution. Since the detection and evaluation of changes from multiple time horizons requires the repetition of several steps, we developed the Change Detection Toolbox (CDT) to automate this process. The toolbox consists of four tools that enable change detection, classification of change types, determination of hierarchical level of change and statistical evaluation of changes. Similar tools have not yet been available for the vector-based change detection. The toolbox was created using Python scripting language and it works in ArcGIS Desktop, the most widely used proprietary GIS software. The results produced by the CDT toolbox showed that in the years 2000-2018, almost 2000 ha of agricultural land were lost in favour of residential construction (especially in the municipality of Chorvátsky Grob), construction of logistics parks and the Bratislava motorway bypass. However, in the last evaluated period 2012-2018, there was a slight slowdown in the intensity of residential construction, which may be related to persistent problems with transport to and from the capital during the morning and afternoon peak hours.
Analysis of Factors Influencing the Effectiveness of Village Financial Information System in Semarang Regency

The purpose of this study is to analyze the factors influencing the effectiveness of village financial information system. This study conducted according to a model proposed by Gupta et al. (2007). The Primary data used is based on the questionnaire distributed to the village government organization in Semarang Regency. There are 100 copies of the questionnaire has been sent, and returned 100% because it was delivered directly by the researchers. The data were analyzed using multiple regression with SPSS 16 software. The result showed that top management, information system management and user of information systems did not statistically influence the effectiveness of village financial information system. Meanwhile, user satisfaction and organizational culture had positive influence on the effectiveness of village financial information system.