Miracle-dz/UniFAR-FTUs huggingface dataset:
Out-of- Sample Stock Return Predictability of Alternative COVID-19 Indices

ABSTRACT We explore the predictive value of the various indices developed to capture COVID-19 pandemic for daily stock return predictability of 24 Emerging Market economies (based on data availability). We identify eight measures of COVID-19 indices, namely, the uncertainty due to pandemics and epidemics (UPE) index, Global Fear Index (GFI), COVID index, vaccine index, medical index, travel index, uncertainty index and aggregate COVID-19 sentiment index. We find that, out of the considered measures, the GFI consistently offers the best out-of-sample forecast gains followed by the aggregate COVID-19 sentiment index while the UPE index offers the least predictability gains. The outcome generally improves after controlling for oil price but the ranking of forecast performance remains the same and robust to multiple forecast horizons and alternative forecast evaluation methods. We infer that the relative predictive powers of the indices are proportional to the extent to which the indices truly measure the pandemic.
Knowledge Gaps and Research Priorities on the Health Effects of Heatwaves: A Systematic Review of Reviews

Although extreme weather events have played a constant role in human history, heatwaves (HWs) have become more frequent and intense in the past decades, causing concern especially in light of the increasing evidence on climate change. Despite the increasing number of reviews suggesting a relationship between heat and health, these reviews focus primarily on mortality, neglecting other important aspects. This systematic review of reviews gathered the available evidence from research syntheses conducted on HWs and health. Following the PRISMA guidelines, 2232 records were retrieved, and 283 reviews were ultimately included. Information was extracted from the papers and categorized by topics. Quantitative data were extracted from meta-analyses and, when not available, evidence was collected from systematic reviews. Overall, 187 reviews were non-systematic, while 96 were systematic, of which 27 performed a meta-analysis. The majority evaluated mortality, morbidity, or vulnerability, while the other topics were scarcely addressed. The following main knowledge gaps were identified: lack of a universally accepted definition of HW; scarce evidence on the HW-mental health relationship; no meta-analyses assessing the risk perception of HWs; scarcity of studies evaluating the efficacy of adaptation strategies and interventions. Future efforts should meet these priorities to provide high-quality evidence to stakeholders.
Geographic Mosaic of Extensive Genetic Variations in Subterranean Mole Voles Ellobius alaicus as a Consequence of Habitat Fragmentation and Hybridization

Restricted mobility, sociality, and high inbreeding—characteristic for subterranean mammals—lead to rapid changes in their genome structure. Up to now, the Alay mole vole Ellobius alaicus was a data-deficient species; its spatial and phylogenetic relationships with a sibling species, E. tancrei, were not clarified. We carried out a genetic analysis including differential G-banding of chromosomes and mitochondrial (cytb) and nuclear gene (XIST and IRBP) sequencing. The phylogenetic reconstruction based on cytb represented the expected phylogenetic relationships of two species. Using the XIST, we revealed two new lineages among E. alaicus from the Alay Valley (Southern Kyrgyzstan). Analysis of IRBP demonstrated presence of the specific genotype in most of E. alaicus specimens, but also revealed the haplotype, typical for E. tancrei, in some Alay mole voles. The results may be explained as persistence of ancestral gene polymorphism in E. alaicus or limited interspecific hybridization with E. tancrei. Several chromosomal forms were revealed in E. alaicus in the Alay Valley. We propose that ‘mosaic’ genetic polymorphism might appear in E. alaicus due to fragmentation of their habitats in highlands of the Alay Valley, Tien Shan, and Pamir-Alay as well as due to hybridization with E. tancrei or persistence of ancestral polymorphisms.
The Role of Gut-Derived, Protein-Bound Uremic Toxins in the Cardiovascular Complications of Acute Kidney Injury

Acute kidney injury (AKI) is a frequent disease encountered in the hospital, with a higher incidence in intensive care units. Despite progress in renal replacement therapy, AKI is still associated with early and late complications, especially cardiovascular events and mortality. The role of gut-derived protein-bound uremic toxins (PBUTs) in vascular and cardiac dysfunction has been extensively studied during chronic kidney disease (CKD), in particular, that of indoxyl sulfate (IS), para-cresyl sulfate (PCS), and indole-3-acetic acid (IAA), resulting in both experimental and clinical evidence. PBUTs, which accumulate when the excretory function of the kidneys is impaired, have a deleterious effect on and cause damage to cardiovascular tissues. However, the link between PBUTs and the cardiovascular complications of AKI and the pathophysiological mechanisms potentially involved are unclear. This review aims to summarize available data concerning the participation of PBUTs in the early and late cardiovascular complications of AKI.
Assessing the effect of steel fibres on the load bearing capacity of RC beams through the use of artificial neural networks

Current work sets out to investigate the effect of steel fibres on the behaviour of simply supported reinforced concrete (RC) beam specimens approaching their ultimate limit state (ULS) through the use of appropriately trained Artificial Neural Networks (ANNs). The training process of the ANNs is based on the use of four databases, which are formed from the available test data. Each database is associated with a specific type of beam specimen: (i) with no stirrups or fibres, (ii) with stirrups but no fibres, (iii) with fibres but no stirrups and (iv) with both fibres and stirrups. The ANNs are employed to directly assess the available test data. The input parameters are selected on the basis of the physical models adopted by the current design codes for describing the mechanisms underlying RC structural response at the ULS and are associated with the specimen design details. For each specimen-type considered a different combination of input parameters is used. The validated ANNs are then employed in order to conduct a parametric investigation to determine the effect of various parameters associated with the steel fibres, the material properties as well as the geometry and reinforcement details of the beams on the exhibited load-bearing capacity. Based on the analysis of the predictions it is concluded that the ANNs are capable of realistically quantifying the effect of the above parameters on the load carrying capacity of RC beams.
PEMBERDAYAAN MASYARAKAT KOTA DALAM MENINGKATKAN KESADARAN BERAGAMA DAN KEMAKMURAN MASJID

Pemberdayaan masyarakat di Kelurahan Pasir Mulya Kecamatan Bogor Barat Kota Bogor melalui program pendampingan pendidikan berbasis masjid merupakan layanan sosial keagamaan untuk meningkatkan keasadara beragama dan keimanan. Masjid Al Barokah dan masjid lainnya yang berlokasi di Kelurahan Pasir Mulya tidak hanya sebagai tempat ibadah shalat saja namun dapatdifungsikan sebagai pusat kegiatan sosial keagamaan dan Pendidikankeagamaan bagi warga sekitar mengingat mayoritas mereka komunitas muslim. Bentuk-bentuk program pendampingan antara lain: (1) Kegiatan Pengajian Jamaah Masjid, (2) Taman Pendidikan Al-Qur’an (TPQ), (3) Musyawarah Kegiatan Kaum Muslimin, (4) Layanan Pengurusan Zakat, Dan (5) Santunan Anak Yatim, dan lainnya. Dengan demikian, keberadaan masjid Al-Barokah berfungsi sebagai sentral perkembangan pengetahuan dan kebudayaan kaum muslimin. Masjid al-Barokah dan masjid lainnya yang berlokasi Kelurahan Pasir Mulya, Kecamatan Bogor Barat melalui peningkatan peran DKM telah mampu menanamkan pendidikan keagamaan bagi jamaah masjid di semua tingkatan usia dan mampu menuntun perkembangan kebudayaan masyarakat sekitarnya. Pemberdayaan masyarakat di Kelurahan Pasir Mulya melalui program pendampingan pendidikan keagamaajnberbasis masjid telah melahirkan kesadaran perilaku positif pada penerima manfaatnya dan berimplikasi pada meningkatnya keimanan dan akhlak mulia warga Kelurahan Pasir Mulya.
Microinstabilities and turbulent transport in the reversed field pinch

The work presented in this thesis is concerned with addressing the nature of drift wave microturbulence in the reversed field pinch (RFP). Microturbulence is an important phenomenon and contributor to heat and particle transport in tokamaks, where it has been studied for several decades, but its role in the RFP is a rather new topic of study. As such, the nature of RFP drift waves and their relationship to their tokamak counterparts is still developing, and many of the results in this work are focused on addressing this challenge. Fundamental advances in microturbulence research have been made in recent decades through two parallel developments: the theoretical framework encompassed in the gyrokinetic model, and the computational power offered by massively-parallel, high-performance computing systems. Gyrokinetics is a formulation of kinetic theory in such a way that the fast timescale gyromotion of particles around magnetic field lines is averaged out. The implementation and use of RFP equilibrium models in gyrokinetic codes constitutes the bulk of this thesis. A simplified analytic equilibrium, the toroidal Bessel function model (TBFM), is used in the gyrokinetic code Gyro to explore the fundamental scaling properties of drift waves in the RFP geometry. Two drift wave instabilities, the ion temperature gradient (ITG) mode and the microtearing mode (MTM) are found to occur, and the relationship of their critical threshold in driving gradients and plasma β is explored. The critical values in these parameters are found to be above those of similar tokamak cases by roughly a factor of the flux surface aspect ratio. The MTM is found to be stabilized by increasing the RFP pinch parameter Θ, making it unlikely for it to unstable in the high-Θ improved confinement pulsed poloidal current drive (PPCD) discharges. Efforts are also made to address microinstabilities in specific experimental discharges of the Madison Symmetric Torus (MST). A semi-analytic equilibrium, the adjusted circular model (ACM), is developed and implemented in the gyrokinetic code Gene to investigate representative PPCD discharges. The flexibility of the ACM enables it to be used for the high-Θ PPCD discharges where the TBFM breaks down. The dominant linear instabilites
The effect of 8 weeks of block and traditional periodization training models on practical factors in volleyball players

The aim of this study was to investigate the effect of 8 weeks of traditional and block periodization training models on practical factors in volleyball players. 13 male volleyball players (mean ± SD; age: 17 ± 0.70 years; body mass: 68 ± 12.13 kg; stature: 181 ± 17.13; BMI: 20 ± 3.03) from the same team were divided in two groups (BP: 6; TP: 7). The subjects performed 3 training sessions in volleyball court per week for 8 weeks. The subjects implemented 3 testing stages (before starting, mid and after 8 weeks) including Vertical Jump, Illinois, Pro-agility and T Agility Tests, Shuttle run 300-yard, Side jumps in 60 second and, finally, Hand grip. Between-group changes were assessed using repeated measure analysis. There were not significant differences between group-time interaction effect, in Vertical jump (p ˃ .05), Agility time (p ˃ .05), Power endurance (p ˃ .05) and Special aerobic endurance (p ˃ .05). This means that there were not significant differences between the groups in improving practical training factors; but Time effect was significant (p ˂ .05). In addition, Block periodization showed higher means in the strength of arm and forearm at the end of protocol.
Improving learning experiences in software engineering capstone courses using artificial intelligence virtual assistants

Students of Software Engineering Capstone Courses face situations and challenges that grant them valuable experiences. However, as this knowledge is acquired through real‐life exposure, it is difficult to transmit it across different generations. To deal with this problem, it has been proposed that students record their learnings through a lesson learned model. But the question of how future students can best benefit from these records remains unanswered. This study addresses this problem through the use of Artificial Intelligence (AI) Virtual Assistant combined with a recommender system. Artificial Intelligence Virtual Assistants, as conversational chatbots, are a manifestation of AI via the simulation of conversation with human users. The technology has the potential to provide personalized service to a range of stakeholders. Thus, we seek to move this trend forward by now pushing these capabilities into the field of higher education. Consequently, we aim to assist software engineering students by leveraging collective knowledge to enhance learning experiences.
SOCIAL AND TECHNOLOGY FACTORS AFFECTING KNOWLEDGE SHARING AMONG ARCHITECTS IN ARCHITECTURAL FIRMS IN IBADAN, NIGERIA

Effective knowledge sharing among project members is crucial for project-based organizations in order to avoid past mistakes, improve work efficiency, and reduce failure risk of projects. Making appropriate design knowledge accessible to the right architects at the right time is central to team building and for sustaining competencies. However, despite the importance of knowledge sharing culture among design teams, members are not likely to share knowledge because of the potential threat associated with providing critical information to other design team members. This study provides answers to six research questions. Data were collected from 25 architects using one-on-one interviews, ranging from the principal architects to the trainee architects in thirteen architectural firms in the Ibadan metropolis. The study findings revealed that knowledge recovery, synergy and reciprocity are the major factors motivating knowledge sharing among the architects, while the factors inhibiting knowledge sharing are distrust, superiority complex, unwillingness to learn, over-criticism, mediocrity, treachery, and abuse of knowledge. This study therefore recommends attitudes of conflict avoidance, and suggested also that conservative habits should be eliminated to enhance effective sharing of architectural design knowledge; especially design knowledge containing some new thoughts or innovative ideas. The study further recommends that architectural firms should deploy more ICT infrastructure and services that can promote effective knowledge sharing amongst architects.
A Collaborative Implementation Strategy to Increase Falls Prevention Training Using the Age-Friendly Health Systems Approach

Falls in the home and in community environments are the leading cause of injuries and long-term disabilities for the aging population. The purpose of this study was to examine outcomes of a partnership among an academic institution, government agency, community organizations, and emergency management services to implement a falls prevention training program using an Age-Friendly Health Systems approach. In this prospective study, partners identified gaps in services and targeted and non-targeted delivery areas for implementation of an evidence-based falls prevention intervention addressing the 4Ms of Age-Friendly Health Systems—Mobility, Medications, Mentation, and What Matters. Descriptive statistics were calculated for program implementation and participant demographic variables, and paired t-test analysis compared scores for self-assessed general health and falls efficacy prior to and after program participation. Twenty-seven falls prevention classes were implemented, with over half (52%) in targeted areas. A total of 354 adults aged 50 and older participated, with N = 188 participants (53%) completing the program by attending at least five of eight sessions. Of completers, 35% resided in targeted areas. The results showed a statistically significant improvement in falls efficacy by program completers in targeted and non-targeted areas. However, there was no statistically significant difference in self-rated health. Overall, the findings of this study indicate that collaboration to deliver falls prevention training can be effective in reaching at-risk older adults. By mobilizing collaborative partnerships, limited resources can be allocated towards identifying at-risk older adults and improving community-based falls prevention education.
A Strong Anthropogenic Black Carbon Forcing Constrained by Pollution Trends Over China

Estimates of the effective radiative forcing from aerosol‐radiation interaction (ERFari) of anthropogenic Black Carbon (BC) have been disputable and require better constraints. Here we find a substantial decline in atmospheric absorption of −5.79Wm−2decade−1 over eastern central China (ECC) responding to recent anthropogenic BC emission reductions. By combining the observational finding with advances from Coupled Model Intercomparison Project phase6 (CMIP6), we identify an emergent constraint on the ERFari of anthropogenic BC. We show that across CMIP6 models the simulated trends correlate well with simulated annual mean shortwave atmospheric absorption by anthropogenic BC over China. Making use of this emergent relationship allows us to constrain the aerosol absorption optical depth of anthropogenic BC and further provide a constrained range of 2.4–3.0 Wm−2 for its top‐of‐atmosphere ERFari over China, higher than existing estimates. Our work supports a strong warming effect of BC over China, and highlights the need to improve BC simulations over source regions.
Sentiment and Style: Evidence from Republican Managers

This study examines the relationship between corporate managers’ political ideology and corporate leverage policies conditional on investor sentiment. Based on a minimum of 21,884 observations over the 1992–2008 period, the authors show that Republican managers significantly reduce leverage during periods of high investor sentiment. To the best of the authors’ knowledge, this paper is the first to document that Republican managers are not swayed by the general tendency to increase leverage in high-sentiment periods. Overall, the empirical evidence from this study indicates that personal characteristics of managers have a consistent impact on corporate policies, providing support for the “behavioral consistency” theory. Further, the results of this study imply that internal and external stakeholders of a corporation should take into account manager personality in their decisions. For example, the board of a highly indebted company may consider hiring a conservative manager to reduce its financial risk.
Desistance from Crime among Chinese Delinquents: The Integrated Effects of Family Bonding, Prosocial Models, and Religious Bonding

Desistance from crime is a popular topic in global criminological research; however, few studies have focused on desistance among delinquent youth, particularly in non-Western societies. This study extends the current knowledge by examining pathways of youth desistance in Hong Kong. Thirty delinquent youth and six parent–child dyads were interviewed, and the study found that filial piety significantly impacts the process of youth desistance. Three main forms of social capital were closely associated with youth desistance: the revival of reciprocal family bonding, the presence of a prosocial role model, and religious bonding. An interactive model was constructed to illustrate the seven stages of desistance and highlight the key elements for successful desistance among youth delinquents in Hong Kong.
Predicting the Next-Day Perceived and Physiological Stress of Pregnant Women by Using Machine Learning and Explainability: Algorithm Development and Validation

Background Cognitive behavioral therapy–based interventions are effective in reducing prenatal stress, which can have severe adverse health effects on mothers and newborns if unaddressed. Predicting next-day physiological or perceived stress can help to inform and enable pre-emptive interventions for a likely physiologically and perceptibly stressful day. Machine learning models are useful tools that can be developed to predict next-day physiological and perceived stress by using data collected from the previous day. Such models can improve our understanding of the specific factors that predict physiological and perceived stress and allow researchers to develop systems that collect selected features for assessment in clinical trials to minimize the burden of data collection. Objective The aim of this study was to build and evaluate a machine-learned model that predicts next-day physiological and perceived stress by using sensor-based, ecological momentary assessment (EMA)–based, and intervention-based features and to explain the prediction results. Methods We enrolled pregnant women into a prospective proof-of-concept study and collected electrocardiography, EMA, and cognitive behavioral therapy intervention data over 12 weeks. We used the data to train and evaluate 6 machine learning models to predict next-day physiological and perceived stress. After selecting the best performing model, Shapley Additive Explanations were used to identify the feature importance and explainability of each feature. Results A total of 16 pregnant women enrolled in the study. Overall, 4157.18 hours of data were collected, and participants answered 2838 EMAs. After applying feature selection, 8 and 10 features were found to positively predict next-day physiological and perceived stress, respectively. A random forest classifier performed the best in predicting next-day physiological stress (F1 score of 0.84) and next-day perceived stress (F1 score of 0.74) by using all features. Although any subset of sensor-based, EMA-based, or intervention-based features could reliably predict next-day physiological stress, EMA-based features were necessary to predict next-day perceived stress. The analysis of explainability metrics showed that the prolonged duration of physiological stress was highly predictive of next-day physiological stress and that physiological stress and perceived stress were temporally divergent. Conclusions In this study, we were able to build interpretable machine learning models to predict next-day physiological and perceived stress, and we identified unique features that were highly predictive of next-day stress that can help to reduce the burden of data collection.
Standard Modern Greek and Cypriot Greek vowels: a sociophonetic study

This study is a comparative analysis of Standard Modern Greek (SMG) and Cypriot Greek (CG) vowels. Specifically, the study examines the effects of vowel (/e i a o u/), language variety (SMG vs CG), and stress (stressed vs unstressed vowels) on vowel formants F1 and F2, vowel duration, and fundamental frequency (f0). 45 female speakers were recorded: 20 SMG speakers and 25 CG speakers from Athens and Nicosia respectively. The results showed significant effects of vowel, stress, and language variety on formants, duration and f0. The study confirms the findings of earlier studies on SMG vowels, provides the first report on CG vowels’ acoustic structure, and constitutes the first comparative sociophonetic research on SMG and CG vowels.