Miracle-dz/UniFAR-FTUs huggingface dataset:
Triangulating evidence on the role of perceived versus objective experiences of childhood adversity in psychopathology

Childhood adversities, such as maltreatment, bullying, and socioeconomic deprivation, are well‐established risk factors for psychopathology. Recent evidence suggests that it is the perceived, rather than objective (i.e., actual) experience of childhood adversity which is associated with psychopathology (Danese &Widom, 2020). However, it is unclear whether perceptions of childhood adversity cause psychopathology, as this cannot be tested ethically or feasibly with randomised controlled trials. Triangulation can instead be used to improve causal inference in observational research, by integrating evidence across multiple approaches with different sources of bias. In this perspective, we describe three different approaches— measurement comparisons, within‐family comparisons, and cross‐ context comparisons—that can be used to test the role of perceived versus objective experiences of childhood adversity in psychopathology. We review current evidence from each approach, before triangulating findings to strengthen causal inference. A summary of each approach and its potential sources of bias is in Table 1.
The “Idea Advantage”: How Content Sharing Strategies Impact Engagement in Online Learning Platforms

In recent years, online learning platforms (e.g., Coursera, edX) have experienced massive growth and have reached nearly 200 million learners. Although their reach is quite large, the impact of these platforms is constrained by a low level of learner engagement. In traditional face-to-face classrooms, educators aim to engage learners by asking them to participate in class discussions and share information about their identity and ideas. However, the effectiveness of these strategies in online learning platforms is uncertain. The authors examine this issue by assessing the impact of two different types of content sharing on learner engagement. The authors conduct a textual analysis of over 12,000 text postings during an 18-month period (Study 1) and a field experiment among over 2,000 learners (Study 2) in a popular Coursera offering by a large U.S. university. The results indicate that asking learners to share ideas (vs. their identity) has a stronger effect on their video consumption and assessment completion. The authors explain this “idea advantage” by suggesting that learners who share ideas (vs. identity) exhibit a greater degree of elaboration. This idea advantage is strongest for learners from English-speaking countries and those new to online learning.
Relationship Between Gender and Performance on Emotion Perception Tasks in a Latino Population

Abstract. Basic emotions are universally recognized, although diﬀerences across cultures and between genders have been described. We report results in two emotion recognition tasks, in a sample of healthy adults from Chile. Methods: 192 volunteers (mean 31.58 years, s.d. 8.36; 106 women) completed the Emotional Recognition Task, in which they were asked to identify a brieﬂy displayed emotion, and the Emotional Intensity Morphing Task, in which they viewed faces with increasing or decreasing emotional intensity and indicated when they either detected or no longer detected the emotion. Results: All emotions were recognized at above chance levels. The only sex diﬀerences present showed men performed better at identifying anger (p = .0485), and responded more slowly to fear (p = .0057), than women. Discussion: These ﬁndings are consistent with some, though not all, prior literature on emotion perception. Crucially, we report data on emotional perception in a healthy adult Latino population for the ﬁrst time, which contributes to emerging literature on cultural diﬀerences in aﬀective processing.
The Role of New Public Management (NPM) on the Relation of Government Internal Control System (SPIP) With Public Organizational Performance

This study aims to provide empirical evidence about the effect of clear and measurable objectives, decentralization, government internal control systems, performance measurement and incentives on public organization performance moderated by the New Public Management orientation. This research was conducted in the Sampang Regency area with reference to the research of Nitzl et al (2018) in Italy. The sample in this study was 30 Regional Apparatus Organizations (OPD) in Sampang District with 144 respondents consisting of OPD officials who have the authority to make decisions. This number of respondents has met the criteria for using SmartPLS analysis. The conclusion in this study is clear and measurable objectives have an effect on performance, then decentralization has no effect on performance. The government internal control system has an effect on performance while for performance measurement and incentives it does not affect performance. In addition, the results of the analysis of Moderated Structural Equation Modeling (MSEM) conclude that the New Public Management orientation does not strengthen the relationship between: clear and measurable goals, decentralization, government internal control systems, performance measurement, and performance incentives.
Applying the Multidimensional Ethics Scale to a Microtasking Crowdsourcing scenario

Many aspects have to be considered concerning the digital economy. Work through online platforms is increasingly stronger in the current global scenario. One of these types of work is known as Microtasking crowdsourcing. These platforms rely on Artificial Intelligence (AI), which provides full support for it. Task assignment and task recommendation are applications of this intelligence. Even though AI has proven to be an ally for this type of work, some ethical aspects emerge from this and have to be studied. The general objective of this thesis is to study the ethical judgment of individuals regarding the use of AI in these online platforms. For this purpose, a hypothetical scenario about Microtasking crowdsourcing through online platforms where there is a working relationship with AI, was created. For this, the Multidimensional Ethics Scale (MES) developed by Reidenbach and Robin (1990) was chosen, and a survey was applied (N=118). Results showed that participants tended to judge as unethical as per the (i) Moral Equity and (ii) Relativistic dimensions. For (iii) Contractualism, the individuals perceived as ethical. Furthermore, significant correlation (p-value = 0.022) was found between people’s fear of computers and the perception of an unwritten contract being violated. The respondents also differ in their perception of an unspoken promise being violated (p-value = 0.033) and an unwritten contract being violated (p-value = 0.005) among their level of education. The participants' perception of justice (p-value = 0.019) and fairness (p-value = 0.026) diverge according to their company roles. Key-words: Crowdsourcing, Microtasking, Artificial Intelligence, Digital Labour, Online Platforms, Digital Challenges, Ethical Aspects, Multidimensional Ethics Scale.
Medidas de Tendência Central: Análise da Qualidade das Questões do ENEM de 2016 a 2018

ResumoO Exame Nacional do Ensino Medio (ENEM) tem se constituido como uma das principais politicas de avaliacao da qualidade da educacao basica brasileira. A expansao do exame e as atribuicoes a ele investidas tornaram imprescindiveis as discussoes acerca da sua estrutura e qualidade. Com o intuito de contribuir para esta tematica, este artigo tem o objetivo de analisar a qualidade de 11 itens de Matematica das provas do ENEM de 2016 a 2018, que se referem as Medidas de Tendencia Central: media aritmetica simples e ponderada, mediana e moda. Para isto, adotou-se uma metodologia predominantemente quantitativa e exploratoria, desenvolvida a partir da aplicacao de tecnicas psicometricas a uma amostra representativa de participantes do exame. Os resultados apontaram para itens adequados e bem estruturados, que privilegiam o raciocinio logico e a interpretacao. A analise pedagogica indicou para a comum confusao entre os conceitos de media aritmetica simples e ponderada, que representam a grande maioria dos itens analisadas. Espera-se que os resultados obtidos possam esclarecer alguns conceitos da psicometria e auxiliar no processo de ensino e aprendizagem de estatistica na educacao basica. Palavras-chave: Medidas de Tendencia Central. Psicometria. Analise de Itens. ENEM. AbstractThe National High School Examination (ENEM) has become one of the most of the main Brazilian quality evaluation policies in the field of basic education. The expansion and attributions invested in the test make indispensable the discussions about its structure and quality. In order to contribute to this theme, we propose to analyze 11 Maths questions to ENEM from 2016 to 2018 and related to Measures of Central Tendency: arithmetic mean; weighted arithmetic mean, median and mode. It was used a quantitative and exploratory methodology, developed through psychometrics methods applied to a significant sample of students that made the exam. The results pointed to well-structured items, that favor logical reasoning and interpretation and that have an excellent ability discriminate groups with different levels of. Its highlight the confusion between concepts of arithmetic mean and weighted arithmetic mean, that represent the most of the questions analyzed. It is hoped that this research may help clarify some concepts of psychometry and can assist in the teaching-learning process of statistics in basic education.Keywords: Measures of Central Tendency. Psychometry. Item Analysis. ENEM.
Productivity and workload analysis between manual and motor-manual pruning of Pinus patula at two different lifts

ABSTRACT Tree pruning is integral to sawtimber production in South Africa, the main purpose being the production of knot-free wood and access for fire protection. Although handheld pruning tools have been used for decades, motor-manual tools have recently been introduced. However, knowledge of possible ergonomic risks and possible productivity associated with either pruning method is limited in the literature. Hence the objective of this study was to assess human workload associated with, and possible productivity gains of, motor-manual pruning against manual operations in 2.0 m and 3.5 m pruning lifts in Pinus patula stands. The study was completed in two stands in the KwaZulu-Natal Midlands of South Africa. Information collected included time study and heart rate data. Time study results showed that motor-manual operations were more productive than manual operations in both the 2.0 m and 3.5 m pruning lifts. Pruning operations fall under the “medium to heavy” workload classification. These results show promise as the first steps in investigating the effect of manual and motor-manual operations on productivity and workload of pruning operations in South Africa. However, it is recommended for this study to be repeated with gender, terrain conditions, temperature, and musculoskeletal efforts as additional factors to workload and productivity.
Pattern Recognition using Support Vector Machines as a Solution for Non-Technical Losses in Electricity Distribution Industry

Contending with Non-Technical Losses (NTL) is a major problem for electricity utility companies. Hence providing a lasting solution to this menace motivates this and many more research work in the electricity sector in recent times. Non-technical losses are classed under losses incurred by the electricity utility companies in terms of energy used but not billed due to activities of users or malfunction of metering equipment. This paper therefore is aimed at proffering a solution to this problem by first detecting such loopholes via the analysis of consumers’ consumption pattern leveraging Machine learning (ML) techniques. Support vector machine classifier was chosen and used for classifying the customers’ energy consumption data, training the system and also for performing predictive analysis for the given dataset after a careful survey of a number of machine learning classifiers. A classification accuracy (and subsequently, class prediction) of 79.46% % was achieved using this technique. It has been shown, through this research work, that fraud detection in Electricity monitoring, and hence a solution to non-technical losses can be achieved using the right combinations of Machine Learning techniques in conjunction with AMI technology.
Analysis of Personal-Professional Status of Women Managers for Sustainable School Management in Turkey

For a sustainable education, it is imperative to empower women in the education process. This study aims to evaluate and describe women's personal and professional characteristics in school management in Turkey. In the study, the opinions of woman school managers about the goals of becoming a manager in line with their images of self-efficacy, self-esteem and organizational justice and their perspectives on the problems arising in the process were discussed. Mixed method research was carried out and a total of 288 women school managers working in the different provinces in Turkey participated in this study. An evaluation of the findings of the research found that the women school managers’ self-esteem and self-efficacy levels were high in contrast to the organizational justice level. This shows that the promotion of women school managers’ organizational justice image is significant in the context of building sustainable school management in Turkey.
Modifikasi Alat Ukur Interpersonal Reactivity Index (IRI) pada Subjek dengan Identitas Sunda

This study aims to modify the instrument interpersonal reactivity index (IRI) made by Davis (1980) which consists of 4 dimensions into 2 dimensions. This research uses quantitative approach, the respondents is 318 students of UIN Sunan Gunung Djati Bandung who were of Sundanese ethnicity and lived in Islamic boarding schools with simple random sampling. The result of modification IRI instrument from 28 items to 26 items. Based on the results, it is known that content validity shows that all items are valid, the item differences shows that 24 items have a good difference, and confirmatory analysis shows that 23 items are valid. The result of the multidimensional validity test shows that perspective taking aspect has r value . 81 and concern for other aspect has r value . 71. While the alpha reliability obtained value . 903 and reliability CR . 96, and the model for empathy instrument of this modification is fit.
PVA-coated activated carbon for aerobic biological treatment of concentrated refractory organic wastewater

The treatment characteristics of concentrated p-phenol sulfonic acid (PSA) wastewater in a submerged bioreactor and a solid phase bioreactor packed with ACP particles (polyvinyl alcohol particles coated with powered activated carbon) were compared experimentally. The changes in biomass and microbial community with the degradation of PSA at both bioreactors were also evaluated using microbial quinones as an index. Greater than 95% of influent PSA was mineralized at the solid phase bioreactor under the volumetric loading of PSA ranging from 0.3 to 1.8 kg-C·m-3·d-1 at the steady state, but less than 10% of the influent PSA was mineralized in the submerged bioreactor. The solid phase aerobic biological treatment process was more effective for the treatment of concentrated refractory chemicals such as PSA than the submerged bioreactor. The dominant quinone species in the solid phase bioreactor were ubiquinone-10 and menaquinone-8(H4), while those in the submerged bioreactor were ubiquinone-8 and menaquinone-8. This suggests hat different microbes had contributed to the degradation in the two bioreactors.
Comparing Recognition Performance and Robustness of Multimodal Deep Learning Models for Multimodal Emotion Recognition

Multimodal signals are powerful for emotion recognition since they can represent emotions comprehensively. In this article, we compare the recognition performance and robustness of two multimodal emotion recognition models: 1) deep canonical correlation analysis (DCCA) and 2) bimodal deep autoencoder (BDAE). The contributions of this article are threefold: 1) we propose two methods for extending the original DCCA model for multimodal fusion: a) weighted sum fusion and b) attention-based fusion; 2) we systemically compare the performance of DCCA, BDAE, and traditional approaches on five multimodal data sets; and 3) we investigate the robustness of DCCA, BDAE, and traditional approaches on SEED-V and DREAMER data sets under two conditions: 1) adding noises to multimodal features and 2) replacing electroencephalography features with noises. Our experimental results demonstrate that DCCA achieves state-of-the-art recognition results on all five data sets: 1) 94.6% on the SEED data set; 2) 87.5% on the SEED-IV data set; 3) 84.3% and 85.6% on the DEAP data set; 4) 85.3% on the SEED-V data set; and 5) 89.0%, 90.6%, and 90.7% on the DREAMER data set. Meanwhile, DCCA has greater robustness when adding various amounts of noises to the SEED-V and DREAMER data sets. By visualizing features before and after DCCA transformation on the SEED-V data set, we find that the transformed features are more homogeneous and discriminative across emotions.
Emergency remote education in foreign and second language teaching

This study aims at tracing the effects of emergency remote education due to Covid-19 on foreign/second language teaching documented in research papers and reports Employing document analysis, it identifies the research contexts and key findings reported in the studies published between 1 January and 28 October 2020 The findings indicate that a significant number of publications consist of reports presented by practitioners, i e schools, governmental authorities and educational foundations, and that the tertiary level is the most frequently covered context in the papers The analysed publications report slightly more Emergency Remote Teaching (ERT)-driven affordances for teachers than constraints and suggest that both teachers and students are able to turn challenges of ERT into affordances when they receive sufficient support from governmental authorities, schools or peers and benefit from already acquired digital skills and technical infrastructure available The findings also indicate a gap of research based on classroom data, which would more effectively contribute to an understanding of the challenges and affordances of ERT in language teaching
Effects of vegetation and topography on biomass patterns post-pinewood nematode disturbance in forest landscapes of southern Jiangxi Province, China

Background: Assessing changes in forest ecosystems, especially forest biomass changes that occur due to disturbances, is essential for improving global carbon estimates.Bursaphelenchus xylophilus is an important pest that harms Pinus thunbergii forests, causing a large number of pine trees to wither and resulting in great losses in Pinus thunbergii forest biomass. Studying the factors affecting P. thunbergii) biomass losses caused by Bursaphelenchus xylophilus is of great significance in research on forest ecosystem health and climate change. In this study, taking Nankang District, Ganzhou City, Jiangxi Province as the research area, based on field survey data combined with a random forest model, the relative importance of influencing factors on the biomass loss of P. thunbergii due to the Bursaphelenchus xylophilus-caused disease was analyzed.Results: The results revealed the following conclusions: (1) topographic and slope conditions significantly affected the P. thunbergii) biomass losses caused by the Bursaphelenchus xylophilus-related disease; (2) the two studied stand factors, vegetation type and vegetation coverage, had little effect on the P. thunbergii) biomass losses caused by Bursaphelenchus xylophilus; and (3) the marginal effect diagram showed that the elevation and slope were obviously related to biomass loss; biomass loss was positively related to elevation and negatively related to slope.Conclusions: Our study demonstrated that topographical factors dominantly affect the spread of the Bursaphelenchus xylophilus-caused disease, in turn causing large P. thunbergii forest biomass losses. Therefore, topographic factors affect the prevention and control of the disease caused by Bursaphelenchus xylophilus.
The Effectiveness of Video Blog (VLOG) on Students’ Speaking Skill

As speaking requires the students to perform orally, this skill is considered difficult by some students. This study aims at investigating the effectiveness of Video Blog (Vlog) on students’ speaking skill. It used pretest-posttest control group research design. It was conducted at SMKS PGRI Pakisaji. The sample of the study were the ten grades of AKL students as the experiment class and the ten grades of OTKP students as the control class. The total of both classes were 36 students. The researcher used a speaking test as the instrument to collect the data. The result of post-test indicated that the students in experimental class has higher score than the control class on their speaking test. The result of statistical analysis reported that there was a significant difference scores between experimental and control class. According to the finding of this study, it could be concluded that vlog can be one of the best new media in teaching speaking and it is recommended to applied on teaching speaking process, because the students who are taught by using Vlog have better achievement in speaking skill. Therefore, Vlog is an effective media in teaching speaking skill. Keywords—Video Blog (Vlog), speaking, video recording, effectiveness, 21st century education
Impact of Assimilating Ground-Based Microwave Radiometer Data on the Precipitation Bifurcation Forecast: A Case Study in Beijing

In this study, the temperature and relative humidity profiles retrieved from five ground-based microwave radiometers in Beijing were assimilated into the rapid-refresh multi-scale analysis and prediction system-short term (RMAPS-ST). The precipitation bifurcation prediction that occurred in Beijing on 4 May 2019 was selected as a case to evaluate the impact of their assimilation. For this purpose, two experiments were set. The Control experiment only assimilated conventional observations and radar data, while the microwave radiometers profilers (MWRPS) experiment assimilated conventional observations, the ground-based microwave radiometer profiles and radar data into the RMAPS-ST model. The results show that in comparison with the Control test, the MWRPS test made reasonable adjustments for the thermal conditions in time, better reproducing the weak heat island phenomenon in the observation prior to the rainfall. Thus, assimilating MWRPS improved the skills of the precipitation forecast in both the distribution and the intensity of rainfall precipitation, capable of predicting the process of belt-shaped radar echo splitting and the precipitation bifurcation in the urban area of Beijing. The assimilation of the ground-based microwave radiometer profiles improved the skills of the quantitative precipitation forecast to a certain extent. Among multiple cycle experiments, the onset of 0600 UTC cycle closest to the beginning of rainfall performed best by assimilating the ground-based microwave radiometer profiles.