Miracle-dz/UniFAR-FTUs huggingface dataset:
BURDEN OF CARE, PERCEIVED SOCIAL SUPPORT AND EMOTIONAL INTELLIGENCE AS CORRELATES OF PSYCHOLOGICAL HEALTH AMONG CAREGIVERS OF MENTALLY ILL PATIENTS.

Purpose: Psychological health has been reported as an important factor influencing individual’s various behaviors, activities, happiness and performance. This study examined burden of care, social support and emotional intelligence among caregivers of mentally ill patients as correlates of psychological health Materials and Methods: The research sample included two hundred (200) caregivers that were selected from the Federal Neuro-psychiatric hospital Yaba, Nigeia, using simple random sampling. They were individually administered the Zarit Burden Interview (ZBI), multidimensional scale of perceived social support (MSPSS), emotional intelligence scale (EI) and General Health Questionnaire. The study adopted a correlational design. A multiple regression analysis was used to analyze the data. Four hypotheses were tested using statistical package for social sciences version 23. Findings: The results indicate that there was significant inverse relationship between burden of care and psychological health (r= -.643, df = 200, p<.01). Also, there was positive significant relationship between emotional intelligence and psychological health (r= .172, df = 200, p<.05). There was significant positive relationship between social support and psychological health (r= .322, df = 200, p<.01). Finally, caregivers’ burden of care, emotional intelligence and perceived social support jointly predicted psychological health (R2 = 0.44, F (3,196) = 51.63, p < . 01). Burden of care (β = -.595, t=-10.64, p<.05) and perceived social support (β = .210, t=2.39, p<.05) were significant independent predictors of psychological health. While emotional intelligence (β = .052, t=0.61, p>.05) found to have no independent significant prediction on the psychological health. The findings of the study were discussed and it suggested the need for caregiver education and support programs. Recommendation: The study recommends that family support groups should be created for assisting caregivers and advocating for the promotion of their well-being in society.
Corporate reputation and market reaction: evidence from FinTech industry

ABSTRACT In this paper, we examine the impact of corporate reputation on FinTech firms. Using a unique hand-collected dataset of customer complaints, violations, hacks/data breaches, and lawsuits; we find that markets negatively react to violation announcements, especially for lawsuits. Our findings show that despite their popularity, corporate wrongdoing is skyrocketing and can negatively impact FinTech firms. These findings have implications for FinTech management, stakeholders, and investors.
ISSUES FOR THE ASSESSMENT AND MEASUREMENT OF STATISTICAL UNDERSTANDING IN A TECHNOLOGY-RICH ENVIRONMENT

As diverse technology use increases in education a number of issues are raised for assessment. This is true in all subjects, but may be particularly pertinent to statistics because students can now use large data sets and deal with multiple variables as part of their learning experiences. The issues are of two kinds. In classrooms, how do teachers assess work that has been produced through the use of technology? Using criteria that were developed for pencil-and-paper assessment may not be sufficient to capture the nature of students’ thinking when the burden of computational data analysis and data display are removed. Outside assessment processes are also challenged with the advent of tools such as Computer Adaptive Testing, and complex interactive data displays. The implications of using technology as part of assessment processes, both inside and outside the classroom, are explored.
Coordination Experience and Team Performance

In cross-functional teams, team performance depends on how skillfully function managers carry out the cross-function coordination of team members' complementary expertise and activities. In this paper, we argue (i) that function managers' coordination skills develop in part through the coordination experience gained from interacting with managers from other function, (ii) that coordination experience has general and firm-specific dimensions, and (iii) that coordination experience leads to better team performance. Using data on development teams in the electronic games industry, we show that coordination experience and its general and firm-specific components have a positive impact on the commercial success of electronic games. Our results have implications for the theory of learning and coordination in teams and for the practice of team design in project-based organizations.
Quo Vadis, earnings management? Analysis of manipulation determinants in Central European environment

Research background: The paper investigates the earnings management phenomenon in the context of Central European countries, attempting to identify the factors and incentives that can influence earnings management behavior on a sample of 8,156 enterprises from Slovakia, the Czech Republic, Hungary, and Poland. Purpose of the article: The main purpose of the manuscript is to prove that there are significant differences in earnings management practices (measured by discretionary accruals) across the countries and to find the firm-specific features that influence the way enterprises manage their earnings. Methods: The modified Jones model was used to calculate the discretionary accruals, which are further analyzed across the countries. The statistically significant differences were confirmed across the countries. Thus, the impact of the economic sector, firm size, firm age, legal form, and ownership structure on earnings management behavior is studied by the Kruskal-Wallis test. The Dunn-Bonferroni post hoc tests then revealed the significant differences across the categories of the investigated earnings management determinants. To find the association between the particular earnings management practice (income-increasing or income-decreasing manipulation), correspondence analysis was used to visualize the mutual relations. Findings & value added: The results of the realized investigation revealed that the economic sector is one of the most important earnings management determinants, as its statistical significance was confirmed in each analyzed country. The correspondence analysis determined specific sectors, where income-increasing manipulation with earnings is practiced (NACE codes F, J, K, M, N), and vice versa, income-decreasing earnings management is characteristic for enterprises in sectors A, C, D, G or L. In specific economic conditions, firm size is also a relevant indicator (Hungary), or firm age and legal form and ownership structure (Poland). The recognition of crucial earnings management incentives may be helpful for authorities, policymakers, analysts and auditors when identifying various techniques and practices of earnings manipulation which could vary across the sectors and taking necessary measures to mitigate potential financial risks.
Supporting Quality Jobs in Tourism

The tourism sector is highly dependent on quality human resources to develop and deliver a competitive tourism offering. This report examines approaches to encourage the creation of more and better tourism jobs, with a particular emphasis on enhancing the skills and career development opportunities of people employed in tourism SMEs. The contribution quality jobs can make to building a competitive and sustainable tourism sector is discussed. This is followed by analysis of the sector's labour intensity and labour market characteristics, and the implications for attracting, retaining and developing a skilled workforce. Policies and programmes introduced to respond to these challenges and boost workforce development in tourism SMEs are examined and a number of key policy considerations highlighted. The report was reviewed and approved by the OECD Tourism Committee on the 14 January 2015.
Progress in the measurement of lattice spacing d(220) of silicon

X-ray and optical interferometry is applied to the measurement of silicon lattice spacing. The previously reported standard deviation 0.16/spl times/10/sup -6/ has been reduced to 0.05/spl times/10/sup -6/. The d(220) is 192015.593(0.01) fm after correction of lattice strain by carbon and oxygen.
Investigating the interplay between social presence, motivation, and knowledge sharing behaviour in virtual learning environment

This study investigates the interplay between social presence, motivation, and knowledge sharing behaviour in the virtual learning environment. Sample for this research were 150 university students participated in online class sessions. A quantitative analysis was conducted by Structural Equation Modelling (SEM) with Partial Least Square (PLS) methods. The result showed that (1) there are positive effects between social presence on intrinsic motivation and knowledge sharing behaviour, (2) there is a positive effect between intrinsic motivation and knowledge sharing behaviour, (3) intrinsic motivation partially mediated the relationship between social presence and knowledge sharing behaviour, and (4) extrinsic motivation acts as predictor moderator on the relationship between social presence, intrinsic motivation, and knowledge sharing behaviour. These results implied the importance of students’ motivation and social presence perception to foster knowledge sharing in the mediated learning environment.
Knowledge, Attitude, and Perception of COVID-19 Pandemic in Enugu, Southeast Nigeria- The Initial Experience

Background: The world is experiencing a global corona virus (COVID-19) pandemic. As of 9th June 2020, over 7 million confirmed cases of coronavirus disease (COVID-19) and more than 400,000 deaths had been reported in more than 30 countries of the world according to World Health Organization. Aim: We aimed to assess the knowledge, attitudes, and vulnerability perception of Enugu state residents during the coronavirus outbreak in order to facilitate better health care outcomes. Methodology: A prospective Web-based cross-sectional survey was designed for this study which was conducted in March 2020 among Enugu state residents. The obtained data were coded, validated, and analyzed using Statistical Package for the Social Sciences SPSS software, version 24. Descriptive analysis was applied to calculate the frequencies and proportions and Chi-Square Test was also used. A preliminary phase was conducted to assess the validity and reliability of the questionnaire before its use. Results: The study showed that significant number (99.6%) of the respondents had heard about Covid-19 and the most stated source of knowledge was social media (57.6%), followed by Newspaper and television shows (50.2%) while the least was from General Practitioner (GP) (8.9%). There was over 75% agreement with, and practice, of all known covid precautionary measures and less than 35% responses for wrong claims and practices about covid -19. Conclusion: The overall knowledge, attitude, and perception are high in Enugu state population although few still has background combined superstitious believes. Social media and internet are the highest used facility for acquisition of knowledge and information in Enugu, Nigeria.
Aging Management Model at Dayakan Village—Kulon Progo District, Yogyakarta Special Province

Muhammad Dawam, Ph.D., MPA, Senior Researcher for the Center for Research and Development on Population, BKKBN, Jakarta, Indonesia. Sri Sugiharti, Mkes, Senior Researcher for the Center for Research and Development on Population, BKKBN, Jakarta, Indonesia. Dwi Endah, MPH, Director for Indonesia Ramah Lansia (Indonesia Elderly Friendly), Respati University of Yogyakarta, Indonesia. Center for Research and Development on Population, BKKBN, Jakarta, Indonesia Sri Sugiharti Center for Research and Development on Population, BKKBN, Jakarta, Indonesia Dwi Endah Kurniasih Indonesia Ramah Lansia (Indonesia Friendly Elderly), Respati University of Yogyakarta, Indonesia
Relationship between fractal dimensions of stream and morphometric characteristics of basin for the soil conservation from water erosion

ABSTRACT The network of streams continuously changes its location based on time, environmental factors and human interventions. It is very important to study the stream changes in order to provide management solutions for soil conservation. One of the new methods in this regard is to use fractal geometry. The purpose of this study was to investigate the relationship between fractal and morphometric characteristics of the basin and the possibility of fast, low-cost and accurate management of the stream network based on this relationship. For this purpose, using data basic maps, drainage networks map and digital elevation model (10 m) of the ground by ArcGIS 10.7 was prepared. Then applying the rules of the Horton–Strahler river network, fractal dimensions were calculated to examine the relationship between fractal dimensions, and some rivers’ geomorphic features were investigated. Finally, by entering the data obtained from the calculations in SPSS 22 and Curve Expert software, the morphometric characteristics of the basin associated with the fractal dimensions were investigated. In the Curve Expert software, the exponential, logarithmic, linear and power models of the dependent variable (fractal dimension) and the independent variable (morphometric characteristics) were investigated and the model that had the higher determination coefficient and was significant in SPSS 22 software for the nonlinear univariate regression was selected and introduced as the appropriate model for the relationship between the two studied variables. Results showed that the fractal dimension of stream branch, the fractal dimension of drainage density and the fractal dimension of total basin area were 1.84, 0.71 and 1.46, respectively. The results also showed that the fractal dimension of watersheds has meaningful relations with factors such as shape form, area, bifurcation ratio and length ratio in the watersheds. Due to the importance of stream characteristics in the management of watersheds in terms of flood, erosion and soil conservation, the fractal models can be used to make quick and accurate decisions about the stream management.
A palynological perspective on the tribe Viteae of the grape family (Vitaceae)

Abstract The tribe Viteae comprises about 200 species and is represented by the genera Vitis and Ampelocissus. Vitis is the most studied genus within the grape family (Vitaceae) because of the global economic importance of its fruits and derived products. This study examined the palynology of Ampelocissus and Vitis species belonging to the tribe Viteae to identify pollen characters that may contribute to the taxonomic and morphological characterisation of Ampelocissus. Pollen specimens were obtained from herbaria, treated by the acetolysis method, measured, photographed, and described using light and scanning electron microscopy. In the analysed species, pollen grains were isopolar or heteropolar, medium-sized, tricolporate, oblate spheroidal to subprolate. Ornamentation patterns differed among species, with examples of bireticulate, microreticulate, perforate, reticulate, and rugulate sexine. These characters were used for the development of a pollen key to the genera. Principal component analysis revealed that quantitative pollen characters were the most important for group discrimination. This study contributes to the palynological knowledge of some undescribed species and provides novel palynotaxonomic information on the family Vitaceae.
A new sampling capability for uncertainty quantification in the Ice-sheet and Sea-level System Model v4.19 using Gaussian Markov random fields

Abstract. Assessing the impact of uncertainties in ice-sheet models is a major and challenging issue that needs to be faced by the ice-sheet community to provide more robust and reliable model-based projections of ice-sheet mass balance. In recent years, uncertainty quantification (UQ) has been increasingly used to characterize and explore uncertainty in ice-sheet models and improve the robustness of their projections. A typical UQ analysis involves first the (probabilistic) characterization of the sources of uncertainty followed by the propagation and sensitivity analysis of these sources of uncertainty. Previous studies concerned with UQ in ice-sheet models have generally focused on the last two steps but paid relatively little attention to the preliminary and critical step of the characterization of uncertainty. Sources of uncertainty in ice-sheet models, like uncertainties in ice-sheet geometry or surface mass balance, typically vary in space and potentially in time. For that reason, they are more adequately described as spatio(-temporal) random fields, which account naturally for spatial (and temporal) correlation. As a means of improving the characterization of the sources of uncertainties in ice-sheet models, we propose in this paper to represent them as Gaussian random fields with Matérn covariance function. The class of Matérn covariance functions provides a flexible model able to capture statistical dependence between locations with different degrees of spatial correlation or smoothness properties. Samples from a Gaussian random field with Matérn covariance function can be generated efficiently by solving a certain stochastic partial differential equation. Discretization of this stochastic partial differential equation by the finite element method results in a sparse approximation known as a Gaussian Markov random field. We solve this equation efficiently using the finite element method within the Ice-sheet and Sea-level System Model (ISSM). In addition, spatio-temporal samples can be generated by combining an autoregressive temporal model and the Matérn field. The implementation is tested on a set of synthetic experiments to verify that it captures well the desired spatial and temporal correlations. Finally, we demonstrate the interest of this sampling capability in an illustration concerned with assessing the impact of various sources of uncertainties on the Pine Island Glacier, West Antarctica. We find that both larger spatial and temporal correlations lengths will likely result in increased uncertainty in the projections.
Biochemical profile of ‘Niagara Rosada’ grapes under different rootstocks and training system

Grapevines are used to be trained to different systems, while there is a paucity of literature on the main cordon disposition with regards to grape quality, especially grafted on to different rootstocks. Therefore, a field experiment took place in the city of São Manuel, state of São Paulo, Brazil. This study aimed to evaluate the quality of the ‘Niagara Rosada’ grapes by training them to vertical shoot position (VSP) system with unilateral and bilateral cordons grafted on to rootstocks during two crop seasons (2015 and 2016). To assess the data, a 22 factorial setup organized in a randomized complete block design was used, corresponding to two rootstocks (‘IAC 766 Campinas’ and ‘IAC 572 Jales’) and two cordons (unilateral and bilateral cordon). The variables assessed were the content of soluble solids, titratable acidity, fruit-ripeness index, reducing sugars, total phenolic compounds, total flavonoids, anthocyanins, antioxidant activity via DPPH and FRAP. Results indicated that ‘IAC 766 Campinas’ rootstock and bilateral cordon improved the chemical quality in grapes, especially the contents of anthocyanins and sugars. This management practice should be selected when growing ‘Niágara Rosada’ grapes, provided that there is an influence in the quality of the final product.
Early onset type 1 diabetes mellitus in an infant during COVID-19 pandemic: case report

Type 1 diabetes mellitus (T1DM) is an endocrine disorder, marked by elevated blood glucose level caused by autoimmune process destroying the β-cells of the pancreas which mostly affects children. It is an often-overlooked condition, with low awareness among clinicians and parents alike which led to late diagnosis and patients often presenting with acute complications. Often triggered by a viral infection, here we presented an interesting case of early onset T1DM presenting with Diabetic ketoacidosis (DKA) during a COVID-19 pandemic. A female infant, aged 1 years and 2 days old, presented with dyspnea and fever. Physical examination was otherwise normal, without any rhonchi or wheezing found during pulmonary auscultation. Nasopharyngeal swab and SARS-CoV-2 antigen test was found negative. Laboratory workup found random blood glucose level of 577 mg/dl accompanied by acidosis and ketonuria. The patient also had elevated white blood cells and platelet counts. She was admitted for treatment in the Pediatric intensive care unit (PICU) with therapeutic regiments consisting of slow intravenous insulin infusion, potassium chloride intravenous fluid, antibiotics, and antipyretics. Close monitoring of blood glucose ensues and the patient was treated for 5 days followed by outpatient therapy with mixed insulin treatment twice per day. This case was interesting as T1DM usually manifested in older children with median age of diagnosis ranging from 8 to 13 years old, depending on population. T1DM diagnosed in children younger than 6 years old are classified early onset and it is especially rare to found in infants. Although the patient tested negative for SARS-CoV-2 antigen, the onset of the case coincides with a recent surge of cases locally. It meant that we cannot rule out possibility of prior unknown exposure or infection which may precipitate the condition.
A Study on Design, Development, Implementation, and Evaluation of Severe Drug-Drug Interaction Alert System in ICU

Background and objective: The overridden rate of Drug-Drug Interaction Alerts (DDIAs) in the Intensive Care Unit (ICU) is very high. Therefore, this study aimed to design, develop, implement, and evaluate a severe Drug-Drug Alert System (DDIAS) in ICU and measure the override rate of DDIAs. Methods This is a cross-sectional study for the design, development, implementation, and evaluation of severe DDIAs into a Computerized Provider Order Entry(CPOE) system in the ICUs of Nemazee general teaching hospitals in 2021. The patients exposed to the volume of DDIAs, acceptance and overridden of DDIAs, and usability of DDIAS have been collected. Results The knowledge base of DDIAS contains 9,809 severe DDIs. A total of 2672 medications were prescribed in the population study. The volume and acceptance rate for severe DDIAs were 81 and 97.5%, respectively. However, the override rate was 2.5%. The mean System Usability Scale (SUS) score of the DDIAS was 75. Conclusion This study demonstrated that the implementation of high-risk DDIAs at point of prescribing in ICU improved adherence to alerts. In addition, the usability of DDIAS was reasonable. Further studies are need to investigate the establishment of severe DDIAS and measure the physician's response to DDIAS on a larger scale.