Miracle-dz/UniFAR-FTUs huggingface dataset:
Growth inhibition in cucumber (Cucumis sativus L.) induced by Epilachna chrysomelina fabricius (Coleoptera: Coccinellidae)

Abstract Studies were conducted in screen and field cages on growth inhibition and fruit damage by Epilachna chrysomelina on cucumber. Six population densities (0, 1-, 2-, 3-, 4- and 5-pairs) of the beetle was introduced into separate cages containing 3-weeks old cucumber seedlings and arranged in Completely Randomised Design (CRD) with three replicates. Increased E. chrysomelina density resulted in increased number of days to 50% fruiting in both experiments. Fruit initiation was delayed by 12 days and 7 days in the screen and field caged cucumber respectively at the 5-pairs population density while the number of fruits produced was significantly lower (p < 0.05) as beetle population increased per cage. Regression analysis in both experiments showed that vine length, functional leaf area and number of cucumber produced were a linear function of E. chrysomelina population density. Chi-square (χ2) analysis revealed that the models obtained in both experiments were similar for the parameters tested.
Attitudes to poverty in Slovakia: a Q-methodology study

ABSTRACT The analysis of poverty is not the primary subject-matter of psychology but the way how it is perceived and what consequences it has is traditionally studied in psychology using constructs like attitudes to poverty and the attribution of causes of poverty. The aim of the present study was to examine the attitudes to poverty using a mixed methods perspective, employing Q-methodology and to find out to what extent the findings about the attitude to poverty correspond with the well-known theories on attitudes and attributions of poverty. 50 respondents, aged 19–40, participated in the study, 29 were university students with diverse study focus and 21 were employed of various professions. Respondents sorted 56 statements about poverty, which formed the Q-sort of a quasi-normal distribution in the response matrix. The PQMethod software was used to analyze individual Q-sorts. Factor analysis extracted four factors: Realists, Sympathizers, State facilitators, and Impartial radicals. The resulting differentiation of factors confirms the validity of the hitherto defined conceptualizations of attitudes to poverty and the attribution of causes of poverty; moreover, it allows for a better understanding of individual constructions reflecting the attitudes to poverty. Based on the performed analysis, it can be stated that attitudes to poverty are better viewed not as universal concepts present in the unsorted population but rather in the context of other characteristics of the persons themselves. The socioeconomic status has proven to be an important factor in differentiating attitudes towards poverty.
Lightning Impulse Breakdown Voltage of Rice Bran Oil for Transformer Application

Transformer oil does not only serve as an insulating liquid, but also in removing heat from the windings and cores. Mineral oil (MO) has been widely used in transformers for more than 150 years. Recently, researchers have attempted to search for alternative insulating oils due to the possibility that MO will run out in the future together with the concern on fire safety and environmental pollution. Among the potential oils is rice bran oil (RBO). This work presents the studies of the lightning impulse (LI) of RBO behavior under various electric fields, gap distances and testing methods. The electrical performances of LI tests show that RBO and Palm Oil (PO) have lower LI breakdown voltage than MO under both uniform and non-uniform electric fields. However, the difference in LI breakdown voltages between RBO, PO and MO are slightly small which is less than 20%. In addition, there is no significant effect in the various testing methods under both uniform field and non-uniform field where the percentages of difference are less than 12% and 8% respectively. The data of LI breakdown voltage were statistically analysed to predict the withstand voltage and 50% breakdown voltage of oil samples by using Weibull distribution. The Weibull distribution of MO, PO and RBO has well fit with the fitting line. Finally, the relationship between LI voltages under a non-uniform field with various parameters of PO and RBO was obtained and proposed. From this work, it can be concluded that RBO shows promising results to be considered as an alternative to MO in transformer applications.
Undergraduate students with musical training report less conflict in interpersonal relationships

Recent research has shown that formal musical training has a wealth of benefits in terms of cognition, mental health, social skills, and even speech perception. Of these benefits, there is strong support for a relationship between formal musical training and an improved ability to recognize emotions in speech prosody. Given this connection, interpersonal relationships stand to benefit from improved communication efficacy, which includes an improved ability to recognize emotions in speech. Interpersonal relationships rely on successful expression and interpretation of emotions in speech. If formal musical training can improve the perception of emotions in speech, it should indirectly benefit interpersonal relationship quality. The current study collected data from 197 undergraduate students about their formal musical training and interpersonal relationship quality through an online survey. The results showed that formal musical training accounted for 8% of the difference in relationship conflict but did not benefit relationship support or depth. While musical expertise does not necessarily improve relationship quality overall, it may help reduce conflict in relationships. Further research is needed, with participants who have greater musical expertise, to clarify the relationship between formal musical training and relationship conflict.
Insta(nt)famous? Visual self-presentation and the use of masculine and feminine issues by female politicians on Instagram

ABSTRACT This study examines how female politicians are using Instagram to present themselves to the electorate and how this affects audience engagement. A manual content analysis was conducted to explore how female politicians, compared to male politicians (N = 40), use Instagram in terms of visual self-presentation, the use of masculine and feminine issues, and how this may lead to increased engagement (i.e., likes and comments). In total, N = 762 posts were manually analyzed. The study shows that female politicians receive more likes when they are visible in a picture compared to male politicians. It also reveals that male and female politicians both refer more to feminine issues than to masculine issues, although the use of feminine issues resulted in less likes. We find that some issues lead to more discussion amongst Instagram users, and that this differs between male and female politicians. The study sheds light on how politicians use Instagram and offers insights into how (female) politicians can use the platform to their advantage.
The Impact of Higher Education Institutions in Low-Density Territories

This article highlights the relevance of the location of HEIs in low-density territories in Portugal, using the Polytechnic Institute of Portalegre as a case study. Based on the American Council Education model and following a surveying approach to faculty, staff, and students, this research accounts for the total spending of incoming academics, other nonlocal university members and their visitors, that positively impacts regional development. A demand-side approach was followed so that indirect and induced effects could also be estimated. The main aim of this research paper is to quantify the total impact arising from the location of the Polytechnic in a given region, measured by economic and social indicators such as the financial return from public funds invested in the region, the number of jobs created, and the impact on the local gross domestic product. The results show an impact of more than EUR 17 million in the territory where the Polytechnic operates, representing 3.68% of the local GDP. The institution was also found to be the third major employer in the region, responsible for the creation of 471 jobs that account for 2.25% of the local economically active population.
Toward Predicting Flood Event Peak Discharge in Ungauged Basins by Learning Universal Hydrological Behaviors with Machine Learning

: In the hydrological sciences, the outstanding challenge of regional modeling requires to capture common and event-speciﬁc hydrologic behaviors driven by rainfall spatial variability and catchment physiography during ﬂoods. The overall objective of this study is to develop robust understanding and predictive capability of how rainfall spatial variability inﬂuences ﬂood peak discharge relative to basin physiography. A machine-learning approach is used on a high-resolution datasetofrainfallandﬂoodingeventsspanning10years, withrainfall eventsandbasinsofwidelyvarying characteristics selected across the continental United States. It overcomes major limitations in prior studies that were based on limited observations or hydrological model simulations. This study explores ﬁrst-order dependencies in the relationships between peak discharge, rainfall variability, and basin physiography, and it sheds light on these complex interactions using a multidimensional statistical modeling approach. Among different machine-learning techniques, XGBoost is used to determine the signiﬁcant physio- graphical and rainfall characteristics that inﬂuence peak discharge through variable importanceanalysis. A parsimonious model with low bias and variance is created that can be deployed in the future for ﬂash ﬂood forecasting. The results conﬁrm that, although the spatial organization of rainfall within a basin has a major inﬂuence on basin response, basin physiography is the primary driver of peak discharge. These ﬁndings have unprecedented spatial and temporal representativeness in terms of ﬂood characterization across basins. An improved understanding of subbasin scale rainfall spatial variability will aid in robust ﬂash ﬂood characterization as well as with identifying basins that could most beneﬁt from distributed hydrologic modeling. SIGNIFICANCE STATEMENT: To improve understanding of the effect of precipitation on ﬂoods, a machine- learning workﬂow is designed to scrutinize hydrological processes and is applied on a database of ﬂood events over the UnitedStates.The model accurately reproducesobservedmaximum streamﬂow. It reﬂectsphysicalhydrologicbehavior that is consistent across basins, thereby addressing the challenge of regional modeling and improving upon traditional hydrological models. Rainfall spatial variability has a major inﬂuence on ﬂood peak discharge, although basin geo- morphology is the primary driver. This grants an improved understanding of the conditions under which ﬂoods are generated, allowing for better predictions and warning.
Optimal closed-loop wake steering, Part 2: Diurnal cycle atmospheric boundary layer conditions

Abstract. The magnitude of wake interactions between individual wind turbines depends on the atmospheric stability. We investigate strategies for wake loss mitigation through the use of closed-loop wake steering using large eddy simulations of the diurnal cycle, where variations in the surface heat flux in time modify the atmospheric stability, wind speed and direction, shear, turbulence, and other atmospheric boundary layer flow (ABL) features. The closed-loop wake steering control methodology developed in Part 1 (Howland et al., Wind Energy Science, 2020, 5, 1315–1338) is implemented in an eight turbine wind farm in large eddy simulations of the diurnal cycle. The optimal yaw misalignment set-points depend on the wind direction, which varies in time during the diurnal cycle. To improve the application of wake steering control in transient ABL conditions with an evolving mean flow state, we develop a regression-based wind direction forecast method. We compare the closed-loop wake steering control methodology to baseline yaw aligned control and open-loop lookup table control for various selections of the yaw misalignment set-point update frequency, which dictates the balance between wind direction tracking and yaw activity. Closed-loop wake steering with set-point optimization under uncertainty results in higher collective energy production than both baseline yaw aligned control and open-loop lookup table control. The increase in wind farm energy production for closed- and open-loop wake steering control compared to baseline yaw aligned control, is 4.0–4.1 % and 3.4–3.8 %, respectively, with the range indicating variations in the energy increase results depending on the set-point update frequency. The primary energy increases through wake steering occur during stable ABL conditions. Open-loop lookup table control decreases energy production in the convective ABL conditions simulated, compared to baseline yaw aligned control, while closed-loop control increases energy production in convective conditions.
Equilibrium Modeling for Environmental Science: Exploring the Nexus of Economic Systems and Environmental Change

Equilibrium models (EMs) are frequently employed to examine the potential impacts of economic, energy, and trade policies as well as form the foundation of most integrated assessment models. Despite their central role coupling economic and environmental systems, environmental scientists are largely unfamiliar with the structure and methodology underpinning EMs, which serves as a barrier to interdisciplinary collaboration and model improvement. In this study we systematically extract data from 10 years of published EMs with a focus on how these models have been extended beyond their economic origins to encompass environmentally relevant sectors of interest. The results indicate that there is far greater spatial coverage of high income countries compared to low income countries, with notable gaps in Central America, Africa, the Middle East, and Central Asia. We also find a high degree of aggregation within production inputs and sectoral outputs, particularly within the context of global socioeconomic scenarios. For example, we were unable to identify a single temporally dynamic study that distinguished between products arising from managed versus natural forest, or pastures relative to natural grasslands. Due to the necessary breadth and associated knowledge gaps within a model of the entire global economy, we see considerable potential for cross‐disciplinary innovation as natural scientists gain familiarity into the role these models play in bridging the nexus between socioeconomic systems and environmental change.
Analysis of Temperature Extremes over India Using Sheffield & IMD Dataset

Temperature extremes significantly contribute to climate change; therefore, the analysis of temperature extremes is essential in detecting and attributing climate change. The present study aims to analyze the spatiotemporal variations in the temperature extremes over India, using 0.25° × 0.25° high-resolution Sheffield temperature gridded dataset for a period of 62 years (1951–2012). In addition, the spatial distribution, statistical relation and trend pattern of Sheffield’s temperature dataset is compared with 1°×1°, gridded temperature dataset of Indian Meteorological Department (IMD). The mean of temperature indices show nearly similar spatial distribution in both datasets; however trend pattern of extreme indices show significant differences over different homogeneous temperature regions of India. There is mostly disagreement between the two datasets, for trend patterns of extreme indices at different homogeneous regions, but few grids show reasonable agreement for similar trend pattern. Both datasets reported a significant decreasing trend in TX10p (amount of cool days) and TN10p (amount of cold nights) at maximum grids for the 1951–2012 period. In addition, a significant increasing trend in TX90p (amount of hot days) and WSDI (warm spell duration indicator) at maximum grids during post-1981 and 1951–2012 is observed in both datasets. A comprehensive insight into different characteristics (spatial distribution, statistical relation and trend patterns) of Sheffield’s temperature dataset will help in understanding the applicability of Sheffield temperature dataset for climate modeling and prediction studies over India.
Comparing abnormal accruals models: a non-parametric approach

The purpose of this study is to compare the distribution of discretionary accruals produced by the Standard and Modified Jones models using a non-parametric approach. Evidence is provided that discretionary accruals produced by the two models have an almost identical distribution. Moreover, it is found that whether or not an intercept is included in the model produces more intra-distribution mobility than the use of the standard or the modified version of the model.
Fashion Rental: Smart Business or Ethical Folly?

The research presented here illustrates the spectrum of fashion rental PSS firms and business strategies within the New Zealand fashion rental market. The evidence collected suggests that there is a market for fashion rental; however, this market is underdeveloped in regard to its potential as a benefit exchange medium that encourages alternative consumption practice. This study finds that there is, indeed, enormous potential in PSSs as a means to divert fashion-conscious consumers away from ownership behaviours; however, the current systems fall short of this goal. This study offers a taxonomy to create and develop fashion rental PSSs that achieve central aims of circular economy fashion systems, enhancing the collective, social aspects of access, value-sharing and continuing development of mutual gain within the system. It is anticipated that this taxonomy could be further refined and extended through research in other countries, including those with more established, larger fashion rental organisations. Further, there is potential for action research approaches to the design and analysis of alternative fashion rental PSSs.
Perception of undergraduates and postgraduates pertaining online Learning during the COVID-19 Pandemic: a Cross-sectional Study amongst Sudanese Health Professional Students

Background: The novel coronavirus (COVID-19) pandemic has impacted all aspects of life including educational services due to partial and complete lockdown. In Sudan, education is based on the traditional method of learning (face-to-face lectures) in a classroom. However, the sudden outbreak of COVID-19 made some educational institutes especially Universities and colleges resort to online learning. This study aimed to assess the Perception of Health professional students included under and postgraduates concerning the possible application of online learning during the COVID-19 pandemic in Sudan 2020.Methods: A Cross-Sectional study was conducted amongst Sudanese Health professional Students, included Undergraduates and postgraduates. A convenient sample collection method was used via a self-administrated online structured questionnaire of nineteen questions, which were validated by a medical education expert. The perception was assessed and data were analyzed using a statistical package for social science (SPSS). Results: A total of 133 Health Professional students responded to the web questionnaire.97 (73%) were undergraduates and 36(27%) were postgraduates. Among undergraduates, 58(59.8%) were expressing positive perception, while 39(40.2%) had a negative perception. Whereas 24 (66.7%) of Postgraduates had positive perceptions and 12(33.3%) of them expressed a negative perception about online learning.Conclusions: Postgraduate health professionals are more familiar and stating a higher level of perception compared to the undergraduates, furthermore, several students already were exposed to hybrid online learning during the current COVID-19 Pandemic. Several obstacles to the implementation of online learning in Sudan were noticed by the participating students in this study, which must be appropriately managed for the successful implantation of this mode of learning.
A child‐centered health dialogue for the prevention of obesity in child health services in Sweden – A randomized controlled trial including an economic evaluation

Prevention of child obesity is an international public health priority and believed to be effective when started in early childhood. Caregivers often ask for an early and structured response from health professionals when their child is identified with overweight, yet cost‐effective interventions for children aged 2–6 years and their caregivers in Child Health Services are lacking.
Alliance Management Practices for Higher Trust, Commitment and Inter-Organizational Relationship Performance: Evidence from Travel Companies in Vietnam

Vietnam tourism experienced impressive growth from 2008–2019, but it has weakened due to the impact of the pandemic up to the present. So, what should the travel companies and their partners do to overcome the crisis caused by the COVID-19 pandemic? This paper aims to identify what alliance management practices (AMP) factors help improve the inter-organizational relationship performance (IORP) between travel companies and their partners through the mediating roles of trust and commitment. A quantitative approach was applied with data collection from representatives of 319 SMEs of travel companies and the PLS-SEM was used to test the hypotheses. The findings indicated that trust, commitment, coordination, and frequency of interaction directly affect IORP, and simultaneously, communication and participation have indirect impacts on IORP. This study provides suggestions for all tourism companies to be aware of the need to form relationships with other partners to sustainably survive and develop together.
The Effect of Research Evidence-Based Teaching Practices in Science Classrooms on Student Teachers' Attitudes towards Educational Research

Research in the field of education plays a pivotal role in developing evidence-based practices in teaching and improving the quality of education. However, research conducted in recent years has highlighted the unwillingness of teachers to benefit from scientific studies. This study set out to assess whether Research Evidence-Based Practices in Science Teaching (EBPST) influences the teaching practices of student teachers and their attitudes towards education research. Mixed methods research design was used in this study. The study was conducted through Quasi-experimental methods and focus group interviews. The data were collected with the "Teachers Attitude Scale towards Educational Research (TASTER)" and focus group interviews. Participants of the study included 106 third-year undergraduate student teachers. The experimental group applied EBPST during their teaching, while the control group applied existing traditional teaching at primary schools. The Quantitative findings showed that student teachers in the experimental group had significantly increased positive attitudes towards educational research when compared with student teachers in the control group. In addition, qualitative findings revealed that several factors negatively and positively influence the understanding and use of educational research for student teachers on the applicability of EBPST. Considering the results of this study, student teachers' EBPST effect on improving their attitudes, understanding, and the use of educational research in teaching.