Miracle-dz/UniFAR-FTUs huggingface dataset:
Retinoids As Teratogens

Vitamin A (retinol) is an essential vitamin in the daily functioning of human beings that helps regulate cellular differentiation [2] of epithelial tissue. Studies have shown that an excess of vitamin A can affect embryonic development and result in teratogenesis, or the production of birth defects [3] in a developing embryo. Excess intake of vitamin A and retinoids by pregnant women often results malformations to fetuses' skulls, faces, limbs, eyes, central nervous system [4]. Additionally, doctors often use derivatives of vitamin A, known as retinoids, as medicine to treat a number of skin conditions and carcinomas, the most common form of human cancers.
Female Mice Show Increased V1 Inhibitory Neuronal Activity When Viewing Novel and Familiar Visual Stimuli Compared to Male Mice

The primary visual cortex (V1) is the first area of visual stimuli integration, the perception and processing of stimuli through the optic tract and associated brain regions. V1 recording data showed increased inhibitory neuronal activity in mice viewing novel images compared to viewing familiar images. The V1 area has also been suggested to show a correlation between endogenous estrogen and neuronal activity. Despite these findings, female mice remain generally underrepresented in research, leading to a gap in the understanding of sex-specific differences in stimuli integration. In this paper, we examine 2-photon calcium imaging data from the Allen Institute, consisting of V1 area neuronal activity of two mouse models with identified inhibitory neurons; VIP-IRES-Cre x Ai148 and Sst-IRES-Cre x Ai148. Prior review led to our initial hypothesis that female mice V1 activity will show a greater response to novel images and generally similar responses to familiar images. After filtering the data for sex and the specific image displayed to the mice using Python 3, change in fluorescence over baseline fluorescence (dF/F) traces were analyzed for individual cells from each sex. Cell traces were quantified by their frequency of significant response peaks throughout a five-minute period. We found that when viewing both novel and familiar images, female mice exhibited a significantly higher amount of inhibitory neuronal activity compared to male mice. These findings suggest inherent neurophysiological differences between the sexes affecting the integration of visual stimuli, which would have previously gone unnoticed as a consequence of the lack of use of sex as a biological variable
Send Orders of Reprints at Bspsaif@emirates.net.ae Fertility Preference Inversely Related to 'legacy Drive' in Women, but Not in Men: Interpreting the Evolutionary Roots, and Future, of the 'childfree' Culture

Online survey results for a university sample population indicated that both male (n=361) and female (n=764) participants had a mean desired lifetime fertility of 2.2 offspring. For females, desired fertility had a significant negative relationship with level of interest in life course goals associated with a rewarding career, acquiring fame, and making contribution to ideas and discoveries, but a significant positive relationship with the goal of inspiring others with one's religious beliefs. In contrast for males, none of these life goals was related to variation in lifetime fertility preference. We interpret these data in the context of the 'transmission competition' hypothesis—an evolutionary explanation for decreasing fertility in developed countries, where for females, gene transmission is limited by competition from 'meme transmis-sion', the latter represented in modern times by the pursuit and achievement of life course goals perceived as providing an enduring personal legacy. This accounts, we suggest, for the origin of the now popular 'childfree' culture. Attraction to accomplishment-based memetic legacy and the childfree lifestyle will eventually be eclipsed, we predict—again because of the effects of natural selection—by an emerging culture driven to a large extent by an intrinsic attraction to parenthood—'parenting drive'.
Politique de clusterisation et systèmes sectoriels d’innovation en Pologne: le cas des TIC à Gdansk CLUSTERING POLICY AND SECTORAL SYSTEMS OF INNOVATION IN POLAND: THE CASE OF THE ICTS IN GDANSK

Si les clusters sont consideres comme des moyens pratiques permettant d'accroitre l'avantage concurrentiel des economies locales (Porter, 1994) c'est aussi grâce a leur capacite a encourager l'innovation sectorielle, ce qui participe a l'efficacite (performance) du systeme sectoriel d'innovation (SSI). Nous allons chercher a tester ce constat en prenant l'exemple de la politique de clusterisation en Pologne qui vise a favoriser le developpement de l'innovation dans les differents secteurs de haute technologie. En raison de son intensite en technologie et en ressources humaines hautement qualifiees, nous centrons notre analyse sur le cluster des TIC (Technologies de l'Information et de la Communication) dans la region de Gdansk. Nous nous interessons enfin aux innovations creees au sein de ce cluster pour determiner si elles sont benefiques pour l'ensemble du secteur des TIC en Pologne. If clusters are considered as practical means allowing to increase the competitive advantage of local economies (Porter, 1994) it is also due to their capacity to boost sectoral innovation, which participates to the efficiency (performance) of the sectoral system of innovation. We will test this statement by taking the example of the cluster policy in Poland which aims to facilitate the development of innovation in the various high-technology sectors. Because of his intensity in technology and in highly qualified human resources, we focus our analysis on the ICT cluster (information and communication technologies) in the region of Gdansk. We particularly study the innovations created within this cluster to determine if they are beneficial for the whole ICT sector in Poland.
Organizational Behavior and Human Decision Processes

It is common for organizations to offer awards to motivate individual behavior, yet few empirical studies evaluate their effectiveness in the field. We report a randomized field experiment ( N =15,329) that tests the impact of two common types of symbolic awards: pre-announced awards (prospective) and surprise awards (retrospective). The context is U.S. schools, where we explore how awards motivate student attendance. Contrary to our pre-registered hypotheses and organizational leaders’ expectations, the prospective awards did not on average improve behavior, and the retrospective awards decreased subsequent attendance. Moreover, we find a significant negative effect on attendance after prospective incentives were removed, which points to a crowding-out effect. Survey experiments probing the mechanisms suggest that awards may cause these unintended effects by inadvertently signaling that the target behavior (perfect attendance) is neither the social norm nor institutionally expected. In addition, receiving the retrospective award suggests to recipients that they have already outperformed the norm and what was expected of them, hence licensing them to miss school. Exploratory analyses shed further light on differential effects of awards by age and performance.
Prospective memory : from intention to action

This chapter addresses the question of whether and how repeated practice of intentions facilitates prospective memory. The influence of practice on the execution of postponed actions was examined in three experiments. In Experiment 1, a detection task was used. Practice led to faster responses and fewer omissions. After practice, performance was also no longer influenced by manipulations of attentional resources, suggesting automation. A discrimination task was used in Experiment 2. Speed acquired through practice was dependent on goal activation, suggesting that any automaticity acquired through practice is still goal-dependent. In Experiment 3, an event-based prospective memory task was used. Here, a negative practice effect was observed. Seemingly, mere practice of an action given an event does not necessarily lead to habitual prospective remembering with automatic properties. It is argued that automaticity in habitual prospective remembering is dependent on
Brain Drain, Brain Gain and Its Net Effect

With a total of 272 million migrants worldwide in 2019, the world has seen an absolute increase in their flows over the past decades. Today, more than half of such flows are composed of movements between developing countries. While literature on the impact of migration is abundantly present, the associated works largely focus on the impact of high-skilled immigration. Instead, relatively few empirical studies have analysed the impact of high-skilled emigration, especially on low-income countries of origin. Consequently, this paper aims to contribute to the recent effort of identifying the pathways through which a country of origin might benefit from the emigration of high-skilled individuals. To do so, it provides an overview of literature outlining the determinants of high-skilled migration, and the impacts that these have in relation to the human capital, labour market and macro-economic development of low-income countries of origin. Based on the insights gathered, a conceptual framework on measuring the net brain gain effect is proposed; one that draws on three established theories the human capital theory, migration theory and brain circulation theory. This subsequently results in the formulation of an empirical methodology to assess the net brain gain effect. * This paper was produced and funded by KNOMAD’s Thematic Working Group (TWG) on Labor Migration. KNOMAD is headed by Dilip Ratha; the Labor Migration TWG is co-chaired by Ibrahim Awad of The American University in Cairo and Michelle Leighton of ILO. Ms. Sandra Berger is a Junior Technical Officer at International Labor Organization (ILO). The analysis and proposals expressed in this paper are the author's personal views and do not represent the positions of their current or former employers.
Journal of Information Technology Education a Model and Sample Case for Teaching the Business Value of Information Technology

Executive Summary Because it is a strategic resource that is complex, costly and permeates all functions of the modern organization , information technology (IT) is closely scrutinized for its contributed value, particularly in relation to resources expended. From this perspective, understanding the business value of information technology is a requirement not only for CIO's and CEO's, but also for non-managers working in IT, as well as many others in the organization. It is important that models for learning about IT value are clearly defined, easy to use, and supportive of active learning. This paper proposes an Information Technology Business Value (ITBV) model for teaching discovery of value as applied to common information technology-enabled organizational processes. The model is comprised of 1) a two-dimensional application matrix, which focuses on what business value is and where it can be applied in the organization; and 2) a set of action " triggers " that focus on the " how to " of discovering value opportunities. The horizontal axis of the matrix (the what) identifies five value parameters: quality, cost, speed, innovation and relationship. The vertical matrix identifies five functional areas where IT-enabled value propositions can be applied. The action triggers, based on principles of process re-engineering, activate the process to guide students through the discovery of meaningful value opportunities. A recommended process for using the model suggests initial discussions about business value, value added functions in the organization, and the enabling role of IT via process re-engineering. The application of the model follows this and includes case analysis and documentation. A suggested schema for documenting uncovered opportunities includes identification of proposed activities (action items), a description of the value added and where it will be applied, and the appropriate technology for each action. A sample case, with sample completed action items, is included. As a basic learning tool, the model is not intended as a structure for the thorough, complex analysis of opportunities, although it can appropriately be used as the initial step in that process. Rather, its contribution is in illuminating and strengthening the fundamental connectivity between IT and business value contribution in a simple active-learning approach that is accessible to those learning about the value and organizational impact of information technology.
First-Time Prescribing of GLP-1 Receptor Agonists from 2018-2023: A Descriptive Analysis

Aims: Limited recent data exist on prescribing patterns and patient characteristics for glucagon-like peptide 1 receptor agonists (GLP-1 RAs), an important drug class for patients with type 2 diabetes mellitus (T2D) and/or overweight or obesity. We describe trends in first-time prescribing of GLP-1 RAs. Materials and Methods: Using aggregated US electronic health record data, we identified first-time prescriptions of GLP-1 RAs between January 2018 and June 2023 for adults receiving regular care. We describe prescribing volumes stratified by patient characteristics, specific drug, and FDA-labelled indication. The 5.5-year analysis period was divided into six-month periods. Results : In total, 274,562 patients were newly prescribed a GLP-1 RA, with a significant increase over time (January to June, 2018: 9,642 versus 2023: 66,569; p < 0.001). Overall, 181,860 (66.2%) patients had T2D and 229,715 (83.7%) had obesity or overweight. The proportion with T2D decreased over time (January to June, 2018: 84.1% versus 2023: 49%; p < 0.001), while the proportion with overweight or obesity increased (January to June, 2018: 75.9% versus 2023: 90.7%; p <.001). Of prescriptions with a known FDA-labelled indication (74.2%), 87% were labelled for T2D and 13% were labelled for overweight or obesity. Patients first prescribed a GLP-1 RA labelled for T2D were 59.1% female with a mean (SD) age of 58.6 (13) years, while those prescribed a GLP-1 RA labelled for overweight or obesity were 82.9% female, with a mean (SD) age of 48.2 (12.2) years. Conclusions: We observed an increase in first-time prescribing of GLP-1 RAs overall, and a shift away from a predominately T2D population.
The Influence of Environmental Value Orientation and Climate Change Beliefs on the Firewise Behaviors of Central Oregon Residents

Over the past two decades, the western United States has experienced many of the costliest and most severe wildfires in history. To mitigate the effects of the growing threats posed by wildfires, residents in at-risk communities are encouraged to protect their homes and property by adopting Firewise recommendations. This article examines the influence of environmental value orientation and climate change beliefs on resident’s decisions to participate in Firewise behaviors. The population was drawn from six counties in Central Oregon that are prone to wildfires. Using previous empirical research and the tenets of the cognitive hierarchy, a path model that connected environmental value orientation, climate change beliefs, risk perceptions and Firewise behaviors was created. Multiple path analysis models determined that environmental value orientation significantly influenced climate change beliefs, the belief that climate change caused wildfires made one more likely to participate in Firewise behaviors, and the relationship between beliefs and behaviors was partially mediated by risk perception. These results confirmed the hypotheses and were consistent with both previous literature and the theoretical assumptions of the cognitive hierarchy.
Clinical needs assessment to inform development of a new assay to detect antimalarial drugs in patient samples: A case study

Point-of-care assays have greatly increased access to diagnostic information and improved healthcare outcomes globally, especially in the case of tropical diseases in rural settings. Increased recognition of the impact of these tools and increased funding, along with advances in technology have led to a surge in development of new assays. However, many new tools fail to fulfill their intended purpose due to a lack of clinical impact, operational feasibility, and input from envisioned operators. To be successful, they must fit into existing clinical decision-making models and be designed in collaboration with end users. We describe a case study of the development of a new low-cost sensor for antimalarial drugs, from initial planning through collection and incorporation of design feedback to final assay design. The assay uses an aptamer-based sensor to detect antimalarial drugs from patient samples for tracking antimalarial use in Southeast Asia, a region with a long history of emerging antimalarial drug resistance. Design and use-case input was collected from malaria control experts, researchers, and healthcare workers to develop target product profiles. Data was collected via surveys and in-person interviews during assay development and ultimately informed a change in assay format. This aptamer sensor platform can be easily adapted to detect other small molecule and protein targets and the design process described here can serve as a model for the development of effective new assays to improve access to healthcare technology.
Youth focused life skills training and counselling services program–An inter-sectoral initiative in India: Program development and preliminary analysis of factors affecting life skills

Objectives This paper describes the methodology of developing and implementation of a youth focused life skills training and counselling services programme (LSTCP) and assessment of factors associated with life skills of participants pre-training. Design Development of all aspects of LSTCP (modules, methods and evaluation) was through a consultative process. Experiential learning based facilitation was decided as the approach for training participants. A quasi-experimental design with pre, post and follow-up assessment post-training was finalised. Data collection was done using specifically developed semi-structured self-administered questionnaire. Results Multivariable logistic regression with life skills as outcome and various exposure variables was performed. About 2/3rd of participants had high level of life skills (68%). Increased score of extraversion (AOR = 1.57,95% CI = 1.32–1.85), agreeableness (AOR = 1.42,95% CI = 1.16–1.73), conscientiousness (AOR = 1.9,95% CI = 1.55–2.33), physical (AOR = 1.03,95% CI = 1.01–1.04), environmental (AOR = 1.02,95% CI = 1.004–1.03) and social quality of life (AOR = 1.01,95% CI = 1.006–1.02) were associated with high life skills score. Higher score of neuroticism (AOR = 0.66,95% CI = 0.53–0.79) was associated with low life skills score. Conclusion The results presented provide an opportunity to understand the evolution of factors affecting life skills during the follow-up of this study. This study throws light on development of LSTCP for apparently healthy population in a setting like India and its states.
Comparing feedforward neural networks using independent component analysis on hidden units

Neural networks are widely used for classification and regression tasks, but they do not always perform well, nor explicitly inform us of the rationale for their predictions. In this study we propose a novel method of comparing a pair of different feedforward neural networks, which draws on independent components obtained by independent component analysis (ICA) on the hidden layers of these networks. It can compare different feedforward neural networks even when they have different structures, as well as feedforward neural networks that learned partially different datasets, yielding insights into their functionality or performance. We evaluate the proposed method by conducting three experiments with feedforward neural networks that have one hidden layer, and verify whether a pair of feedforward neural networks can be compared by the proposed method when the numbers of hidden units in the layer are different, when the datasets are partially different, and when activation functions are different. The results show that similar independent components are extracted from two feedforward neural networks, even when the three circumstances above are different. Our experiments also reveal that mere comparison of weights or activations does not lead to identifying similar relationships. Through the extraction of independent components, the proposed method can assess whether the internal processing of one neural network resembles that of another. This approach has the potential to help understand the performance of neural networks.
Antimicrobial resistance- and pathogen patterns in the fecal microbiota of sows and their offspring in German commercial pig farms

Reducing antibiotic use is one of the biggest challenges in pig farming, as antibiotics have been used for years to control typical problems such as newborn or post-weaning diarrhea. The pressure a one health approach has created on animal production regarding antimicrobial resistance is an opportunity to find other strategies against enterobacterial pathogens in suckling and weaned piglets. A farm-specific approach could have a good success due to the individual farm structures in Germany and other countries. In this study, non-metric multidimensional scaling, hierarchical clustering, and latent class analysis were used to determine the impact of antibiotic use on antibiotic resistance patterns and pathogen prevalence in 20 German pig farms. This may help to develop individualized health strategies. 802 fresh fecal samples were collected from sows and piglets from 20 piglet production and rearing farms at different production times (sows antepartum and postpartum, suckling piglets, weaned piglets). In addition, the use of antibiotics was recorded. DNA extracts were subjected to quantitative real-time qPCR with primers specific for antibiotic resistance genes (int1, sul1-3, dfrA1, mcr-1, blaCTX-M), and virulence factors of relevant bacteria (C. difficile, C. perfringens, Salmonella, Escherichia/Shigella/Hafnia, E. coli). Linear and logistic regression models were used to analyze the relationship between different antibiotics and the major genes contributing to the clustering of observations for the different animal groups. Clustering revealed different farm clusters for sows, suckling piglets, and weaned piglets, with the most remarkable diversity in antibiotic use among weaned piglets. Amoxicillin, lincomycin, and enrofloxacin were identified as the most probable cause of increased odds of the presence of relevant antibiotic resistance genes (mcr1, dfrA1, blaCTX-M). Still, direct effects of a specific antibiotic on its associated resistance gene were rare. Enrofloxacin and florfenicol favored the occurrence of C. difficile in sows. The E. coli fimbriae genes were less affected by antibiotic use in sows and piglets, but the F4 fimbriae gene could be associated with the integrase 1 gene in piglets. The results confirm that multidrug-resistant enterobacteria are widespread in German pig farms and give awareness of the impact of current antibiotic use while searching for alternative health strategies.