Miracle-dz/UniFAR-FTUs huggingface dataset:
The Determinants of Profitability in the Nigerian Deposit Money Banks

: The study aims to evaluate the Determinants of Profitability in the Nigerian Deposit Money Banks. The population of the study comprised of 20 Banks listed on the Nigerian stock exchange with a working population of 6 Banks using filter as a sampling technique to select the working population, and which a period of five (5) years was used from 2012-2016. The data generated from the Bank’s annual report and account was analyzed by means of Descriptive statistics, Correlation and Regression analysis using Eviews 8.0. The result of the analysis was tested at 0.05 (5%) level of significance. The findings of the study show that Capital Adequacy has a significant relationship with return on equity; it also revealed that Asset Quality and Management Efficiency have no significant relationship with Return on Equity of Deposit Money Banks. Therefore, the study recommended that, the management of the Deposit Money Banks should endeavour to intensify effort to increase their Capital Adequacy by issuing more shares to the public for subscription more especially at premium to generate additional capital in form of share premium, and should decrease their asset especially non-current assets through leasing in order to increase their profitability, it is also recommended that the management of the deposit money banks should seek for other means that will increase their profitability other than management efficiency such as liquidity by increasing their current assets more than their current liabilities, and also should not consider the age of the bank as one of the factors that will increase their profitability and consider other factors that has significant on the banks profitability such as capital adequacy and liquidity as found in this study.
Weight-normative messaging predominates on TikTok—A qualitative content analysis

Tiktok is a social media platform with many adolescent and young adult users. Food, nutrition, and weight-related posts are popular on TikTok, yet there is little understanding of the content of these posts, and whether nutrition-related content is presented by experts. The objective was to identify key themes in food, nutrition, and weight-related posts on TikTok. 1000 TikTok videos from 10 popular nutrition, food, and weight-related hashtags each with over 1 billion views were downloaded and analyzed using template analysis. The one-hundred most viewed videos were downloaded from each of the ten chosen hashtags. Two coders then coded each video for key themes. Key themes included the glorification of weight loss in many posts, the positioning of food to achieve health and thinness, and the lack of expert voices providing nutrition information. The majority of posts presented a weight-normative view of health, with less than 3% coded as weight-inclusive. Most posts were created by white, female adolescents and young adults. Nutrition-related content on TikTok is largely weight normative, and may contribute to disordered eating behaviors and body dissatisfaction in the young people that are TikToks predominant users. Helping users discern credible nutrition information, and eliminate triggering content from their social media feeds may be strategies to address the weight-normative social media content that is so prevalent.
Tolerating Risk: Professional Judgment in Suicide Risk Assessment

As a leading cause of death among those suffering from mental health problems, suicide is an issue that challenges policy makers, organizations, and practitioners alike. One outcome has been the implementation of standardized decision-making tools, developed through actuarial methods and aimed at limiting risks inherent in professional judgments. However, despite legislative and policy attempts to standardize the outcomes of risk assessment, professional judgments in specific client scenarios remain highly divergent. This article presents an exploration of the practice-level implementation of policies related to suicide risk assessment and decision-making. Findings suggest that once a judgment regarding risk has been made, ultimately organizational dynamics and resource availability determine disposition. Although attempts to improve outcomes for suicidal clients should include ongoing professional development for practitioners, the findings point to the requirement for community-based and hospital-based services that provide the greatest range of options for addressing client needs and facilitating safety.
Conceptualizing the Marginalized Context in Information Systems Research

The idea of "intersectionality" seeks to capture both the structural and dynamic consequences of the interaction between two or more forms of discrimination or systems of subordination. It specifically addresses the manner in which racism, patriarchy, economic disadvantages and other discriminatory systems contribute to create layers of inequality that structures the relative positions of women and men, races, and other groups. Moreover, it addresses the way that specific acts and policies create burdens that flow along these intersecting axes contributing actively to create a dynamic of disempowerment. (United Nations, 2000)
Explore to Learn

Explorative information systems behaviors are the ways in which individuals actively revise their usage and discover creative means of applying the system, extending the potentials of the system, and enhancing task performance. This study has developed a specific concept of explorative system behavior-explorative information technology (IT) learning-to describe users' post-training learning behavior-novel use. Adapting a herding lens, we study the individual and team-level triggers of explorative learning cognitions. The study tests the proposed cross-level model and collects data from 225 individuals who are divided into 51 teams. The results indicate that individuals tend to innovatively use a system through developed exploration cognitions in team settings as a response to examined herd behavior triggers. The study uncovered that members of cohesive teams and learners with high uncertainty perceptions are more likely to imitate the observed explorative learning behaviors of their peers and reproduce such behaviors in the long term.
Early Exit Ensembles for Uncertainty Quantification

Deep learning is increasingly used for decision-making in health applications. However, commonly used deep learning models are deterministic and are unable to provide any estimate of predictive uncertainty. Quantifying model uncertainty is crucial for reducing the risk of misdiagnosis by informing practitioners of low-confident predictions. To address this issue, we propose early exit ensembles, a novel framework capable of capturing predictive uncertainty via an implicit ensemble of early exits. We evaluate our approach on the task of classification using three state-of-the-art deep learning architectures applied to three medical imaging datasets. Our experiments show that early exit ensembles provide better-calibrated uncertainty compared to Monte Carlo dropout and deep ensembles using just a single forward-pass of the model. Depending on the dataset and base-line, early exit ensembles can improve uncertainty metrics up to 2 × , while increasing accuracy by up to 2% over its single model counter-part. Finally, our results suggest that by providing well-calibrated predictive uncertainty for both in-and out-of-distribution inputs, early exit ensembles have the potential to improve trustworthiness of models in high-risk medical decision-making.
Cognitive Factors in Elite Handball: Do Players’ Positions Determine Their Cognitive Processes?

Abstract For an athlete to be successful at the professional level, he or she should be characterized by extraordinary preparation in four areas: physical, technical, cognitive (related to game strategy, perception, and decision-making), and emotional (coping, emotional control). This study aimed to determine the level of selected cognitive traits in handball players while considering their sports level and assigned position on the court. Fifty handball players participated in the study. Participants consisted of 35 national team players, six first-division players, and nine second-division players. There were no significant differences between players from the elite (national team) and the sub-elite (I and II divisions) group. The results identified major differences in selective attention and short-term memory between handball players assigned to different positions (goalkeepers, compared to players in other positions, had lower attention and short-term memory). Thus, it is possible to develop a more effective psychological training program. However, it must be remembered that the results showed great variability among handball players. With this in mind, individual differences should be taken into account when planning psychological interventions.
Historical analysis (2001–2019) of low‐level wind shear at the Hong Kong International Airport

This paper analyses over 10,000 quality‐controlled pilot reports of low‐level wind shear (‘wind shear’) at the Hong Kong International Airport (HKIA; ICAO code: VHHH) between 2001 and 2019. HKIA is well known for its susceptibility to wind shear, which is a potential hazard for aircraft during landing and take‐off. Wind shear at HKIA exhibits strong seasonality with double peaks in the middle of the spring and summer months. There is a strong diurnal cycle in report numbers, peaking towards the afternoon, as modulated by air traffic at HKIA. On average, there are 115 days per year with wind shear reported, with possible power law distribution in the number of days with different number of reports. By comparing the background wind distribution during those minutes with pilot reports against the climatological distribution, wind shear is observed to be, on average, favoured under higher wind speeds (≥6 m s−1) and reduced under lower speeds with shifted frequency peak and heavier tail, although statistical behaviour can differ significantly across individual runway corridors. Preferred background wind directions for wind shear occurrence highlight the role of terrain influence upstream of HKIA. While positive shear (65.6%) is more often reported than negative shear (34.4%), both types of wind shear events appear to follow an exponential distribution in shear magnitude, with similar rates of decay. This is by far the largest statistical study of low‐level wind shear at an airport. Results can serve as an important local reference in addition to being a useful example for airports around the world.
Towards Equitable Patient Subgroup Performance by Gene-Expression-Based Diagnostic Classifiers of Acute Infection

Host-response gene expression measurements may carry confounding associations with patient demographic characteristics that can induce bias in downstream classifiers. Assessment of deployed machine learning systems in other domains has revealed the presence of such biases and exposed the potential of these systems to cause harm. Such an assessment of a gene-expression-based classifier has not been carried out and collation of requisite patient subgroup data has not been undertaken. Here, we present data resources and an auditing framework for patient subgroup analysis of diagnostic classifiers of acute infection. Our dataset comprises demographic characteristics of nearly 6500 patients across 49 studies. We leverage these data to detect differences across patient subgroups in terms of gene-expression-based host response and performance with both our candidate pre-market diagnostic classifier and a standard-of-care biomarker of acute infection. We find evidence of variable representation with respect to patient covariates in our multi-cohort datasets as well as differences in host-response marker expression across patient subgroups. We also detect differences in performance of multiple host-response-based diagnostics for acute infection. This analysis marks an important first step in our ongoing efforts to characterize and mitigate potential bias in machine learning-based host-response diagnostics, highlighting the importance of accounting for such bias in developing diagnostic tests that generalize well across diverse patient populations.
Northern Raglai voicing and its relation to Southern Raglai register: evidence for early stages of registrogenesis

Abstract Northern and Southern Raglai are two closely related Austronesian dialects (Chamic branch) spoken in south-central Vietnam. Although they are mutually intelligible, Northern Raglai is described as having a voicing contrast in onset stops, while Southern Raglai is assumed to have replaced the Chamic voicing contrast with a register contrast realized on the whole syllable (but primarily on its vowel). A production study of the two dialects confirms that Northern Raglai preserves a voicing contrast, even if most women exhibit partial devoicing of their voiced stops, and that Southern Raglai has developed a register contrast based on F1 and phonation cues at the beginning of vowels. The weights of the acoustic properties of voicing and register are similar across ages and genders, suggesting that the two laryngeal contrasts are phonetically stable. Even if there is little evidence of change in progress, a close inspection of the Northern Raglai voicing contrast reveals voicing-conditioned modulations of F1 and perturbations of phonation after partially devoiced stops that could be precursors of a register system similar to that of Southern Raglai. We argue that this is a pathway to registrogenesis and speculate about the articulatory laryngeal mechanisms that could trigger registrogenetic changes. Our data also show that the Northern Raglai voicing contrast is unstable in aspirated stops and that voiced aspirated stops typically have a partially voiceless and partially voiced aspiration.
Evaluating Domain Generalization for Survival Analysis in Clinical Studies

Machine learning models are often required to generalize to new populations (domains) unseen during training, which may lead to model un-derperformance. So far, most research has focused on Domain Generalization methods for image classification tasks, which address the problem by learning domain invariant predictors. In this study, we assess the efficacy of domain generalization methods in survival analysis. The goal is to predict time-to-events such as death or disease progression based on base-line demographic and clinical variables of individuals exposed to medical treatment. We benchmark four domain generalization methods and several conventional/established methods on real world scenarios encountered in clinical practice. This includes tasks such as generalizing between randomized controlled trials to real world data, identification of prognostic models regardless of treatment or disease subtypes. We find that the generalization issue is often not as severe as reported in synthetic scenarios. Furthermore, our results corroborate previous findings that domain generalization often does not consistently outperform classical empirical risk minimization baselines also on low-dimensional data. Finally, to better understand when domain generalization methods can lead to performance gains and thus better outcomes for patients, we quantify the influence of different types of shifts occurring in the data.
When Do Team Members Share the Lead? A Social Network Analysis

Shared leadership is not only about individual team members engaging in leadership, but also about team members adopting the complementary follower role. However, the question of what enables team members to fill in each of these roles and the corresponding influence of formal leaders have remained largely unexplored. Using a social network perspective allows us to predict both leadership and followership ties between team members based on considerations of implicit leadership and followership theories. From this social information processing perspective, we identify individual team members’ political skill and the formal leaders’ empowering leadership as important qualities that facilitate the adoption of each the leader and the follower role. Results from a social network analysis in a R&D department with 305 realized leadership ties support most of our hypotheses.
Permafrost Thermal Dynamics and Cryostratigraphy at Villum Research Station, Station Nord, Eastern North Greenland (81°N)

We provide the northernmost permafrost thermal analysis in Greenland through the ground temperature time series (2014–2021) and cryostratigraphy of two 20‐m deep boreholes (SN1 and SN2) at Villum Research Station, Station Nord (81°N). Three sedimentary units are identified in the stratigraphy: glacial, glaciomarine, and beach deposits. These sandy and gravelly deposits are interpreted to comprise a deglaciation and isostatic emergence sequence. Ice‐poor epigenetic permafrost grew downwards into the deposits following subaerial exposure. Relatively high salinity values (up to 70 ppt) are observed in the glaciomarine unit, resulting in freezing point depressions between 0 and −4°C. The Prinsesse Ingeborg Halvø study area has a polar tundra climate and is unique compared to other high Arctic areas because of a thick (>1 m), long‐lasting snow cover. This snow cover results in relatively high permafrost temperatures for the climate and latitude and the warmest known permafrost north of 80°N. Over the seven‐year study period, average 20 m permafrost temperature was −7.87°C at SN1 and −7.06°C at SN2. The warming rate at 20 m depth was 0.07°C/year at SN1 and 0.05°C/year at SN2, rates which are similar to those of other high Arctic sites. Active layer thickness, extrapolated from the temperature measurements, varied between 0.5 and 1.16 m. The interplay between snow dynamics and seasonal air temperature controls ground thermal regime in the study area. Air temperatures during autumn and midwinter, the fastest warming seasons, influence the ground thermal regime through the gradually developing, dense snowpack.
The Benefits of Being Proactive While Working Remotely: Leveraging Self-Leadership and Job Crafting to Achieve Higher Work Engagement and Task Significance

Given the growing number of remote and hybrid working arrangements, this research investigates the process and outcomes of proactivity during remote work. We approach proactivity during remote working as a resource-building process and integrate self-leadership and job crafting literature. We propose that employees’ self-leadership allows them to regulate their resources optimally, enabling resource availability that can be used to arrange remote working demands and resources proactively. We collected three-wave data from remote workers (n = 329 observations) and tested our hypotheses using multilevel analyses. Results differed by level of analysis. Specifically, at the between level, comparing behaviors between participants, social expansion mediated the relationship between self-goal setting and task significance. In contrast, at the within level (analyzing differences in behavior within the same person), social expansion mediated the relationship between self-goal setting and work engagement. Overall, these findings suggest that self-leadership allows higher availability of resources enabling the proactive initiation of social interactions, which, at the within level enhance work engagement, and at the between level improve task significance during remote work. We discuss these findings considering the implications for interventions to foster more positive remote-work experiences.
How and why we run: investigating the experiences of blind and visually-impaired runners

Running offers a convenient and affordable method of keeping fit and maintaining good cardiovascular health. In this paper, we describe the experiences of a group of runners whose practices are rarely profiled: individuals who identify as legally-blind, some of whom run competitively, while others run for purposes of leisure. We specifically focus on planning strategies undertaken, experiences running both with and without sighted guides, the impact of situational and environmental factors, and the ways in which technology is utilized. The study has revealed a set of insights which if capitalized upon could offer considerable promise to support independent running. These include examining ways to reduce levels of uncertainty faced by runners, supporting autonomy, providing greater levels of environmental awareness, and aiding socialization when running. Findings from the work offer promise to interface designers to improve inclusiveness when developing technologies to support runners.
Virally Mediated Connexin 26 Expression in Postnatal Scala Media Significantly and Transiently Preserves Hearing in Connexin 30 Null Mice

Non-sensory cells in the sensory epithelium of the cochlea are connected extensively by gap junctions. Functionally null mutations in GJB6 (encoding Cx30) cause hearing loss in humans. In this study, we injected AAV1-CB7-Gjb2 into the scala media between P0-2 in the cochlea of Gjb6 −/− mice. The injection increased Cx26 expression and significantly preserved auditory functions. However, the hearing preservation gradually declined and essentially disappeared 3 months after the injections. In contrast, the morphological preservation was still significant at 3 months post-injection. We found that the expression of Cx26, at both the mRNA and protein levels, showed substantial decreases during the 3-month period. Curiously, treatments by injecting AAV1-CB7-Gjb6 with the identical approach failed to yield any hearing preservation. Our results demonstrated the first successful cochlear gene therapy treatment in mouse models by virally expressing a companion gene of Gjb6.
Heterogeneous Impact of Land-Use on Climate Change: Study From a Spatial Perspective

Studies have shown that land and climate interact in complex ways through multiple biophysical and biogeochemical feedbacks. In this interaction mechanism, the carbon fixation effect among different land-use types and objective conditions among different regions have significant gaps, leading to the heterogeneous impact of land-use on climate change. This study takes temperature change as the observation index to reflect climate change, and analyzes the process of land use type adjustment affecting vegetation cover and climate change. Based on the data of 214 countries from 1990 to 2018, this paper uses the spatial Durbin model with temperature lag to verify the heterogeneous impact of land-use on climate change in two dimensions of land-use type (Agriculture, forestry and their subdivision structure) and region (latitude and land-sea difference). The following conclusions are drawn: 1) The impact of different land-use types on climate change is heterogeneous. The impact of agricultural land on climate change is not significant, but the increase of the forest land proportion will help to restrain the rise of national temperature. 2) The impact of land-use on climate change has regional heterogeneity. There is heterogeneity in the impact on climate change among sample countries of different latitudes. The geographical differences make the mechanism of land-use affecting climate change between island countries and mainland countries also have heterogeneity, mainly in that island countries are not affected by the land-use structure adjustment of neighboring countries. 3) A country’s climate change is affected by both its own land-use structure and the land-use structure of neighboring countries, and the latter is more critical. The conclusions in this study provide helpful supplementary evidence for the importance of international climate cooperation and provide a reference for proposing international initiatives to address climate change or establishing an international convention to address climate change.