Miracle-dz/UniFAR-FTUs huggingface dataset:
Carbon Monoxide (CO) Pollution in the Niger Delta area of Nigeria and Its Impact on Foeto-Maternal Health

Background: Carbon monoxide is produced in abundance in the Niger Delta, a fact that was acknowledged in the World Bank study of the region in 1995 and the Environmental assessment of Ogoni land by UNEP in 2011. Objectives: To ascertain the extent of CO pollution in the Niger Delta, its impact on foeto-maternal health and to review the pathophysiology and the treatment of the poisoning. Methods: A mixed method study (observational-descriptive and systemic review). A literature review on the above objectives was carried out. The known foeto-maternal impact of CO exposure was extrapolated to the prevailing state of CO pollution in the Niger Delta. Questionnaires distributed to Doctors working in the tertiary Centres in the core Niger Delta focused on the prevalence, clinical presentations and foeto-maternal findings in patients who presented with CO poisoning. Results: There was no data on the prevalence and clinical presentations of CO pollution in the Niger Delta. The ambient and indoors air concentration of CO in the Delta range from 0 ppm to 191μg/m3 but in places within 60-200 metres from crude oil flow stations, the concentrations range from 100 to 5320 μg/m3. Maternal impact of CO pollution ranges from headaches at carboxyhaemoglobin (COHb) levels of 5-20% to maternal death at COHb levels of >66% while in the foetus, it causes birth defects, growth restriction, prematurity and sudden intrauterine and early neonatal death. Conclusion: The core Niger Delta is under perpetual siege of CO pollution and the ambient and indoors air concentration of it in the Delta range from 0 ppm to 191μg/m3.
Skilled migrant workplace integration: the choice between pragmatism and critical realism approaches

ABSTRACT This article provides a rationale for adopting the critical realism (CR) instead of pragmatism paradigm when researching skilled migrants' (SMs) workplace integration in Australia. While the extant SM literature has provided an abundance of ‘explanations' reflecting the difficulties SMs face, it appears almost impossible for SMs to overcome some challenges such as discrimination or lack of local work experience. However, there is not a sufficient explanation for why many SMs have successfully integrated within the host labour market despite facing such difficulties. This study was designed to challenge what may have been ‘taken-for-granted' in the literature and explore the causal relationship behind the SMs’ difficulties and success. The CR paradigm provides a new way to examine the problems SMs face and their strategies to overcome such issues. It also empowers researchers to look beyond the empirical layer of evidence and explore how and why things happen the way they do.
Effect of Social Media Personalization on Brand Strength: A Study of the Brand Advertised on Facebook

Personalization is now used at every corner and position of social media sites. Using Personalization in marketing communication is an effective communication strategy for many businesses to improve customer satisfaction, increase sales in a reduced advertising budget. This research is an attempt to measure the impact of personalized advertisement on customers' social media account. This empirical research develops and tests a conceptual model using the structural modeling technique of the data collected from Facebook users, who have seen any personalized advertisement of the preferred brand on their Facebook account. Results suggest that personalized advertisement of the brand in customers' social media accounts is positively related to brand experience. Brand experience is also positively related to brand equity and mediates the relationship between perceived personalization and customer-based brand equity. Both brand experience and brand equity collectively enhance the brand strength of the brand advertised on Facebook.
Fabrication and Characterization of Microfluidic Pedestal Nozzles Enabling Geometric Contact Line Pinning

Microfluidic pedestal nozzles have been fabricated using self-aligned wafer-scale microfabrication methods. Through implementation of these novel fabrication strategies, nozzles with a concentric rim at the nozzle exit were made. The process allows to accurately vary the rim radius, and rim radii ranging between 36 μ m and 111 μ m are reported here. A unique and essential feature of the nozzle, which is made of hydrophilic silicon dioxide, is that the rim edge has an interior angle of 5 ∘ and a radius of curvature smaller than 20 nm. Due to this nanometrically sharp rim edge, geometric contact line pinning of polar liquids is facilitated. With hydrostatic and hydrodynamic measurements, the nozzle functionality is demonstrated for water and ethanol. Due to the un-precedentedly strong contact line pinning, macroscopic contact angles can be increased by more than 150 ∘ . These measurements reveal a pressure point at which the droplet starts to grow uninhibitedly, which is predicted by a thermodynamic model based on the Gibbs free energy of pinned droplets. It is reckoned that the nozzles are useful in applications where liquids with free surfaces have to be confined to a specific micron-sized surface area, as is the case in, e.g., inkjet printing and electrospinning. To show the functionality of the pedestal nozzles, electrohydrodynamic jetting of a typical electrospinning polymer solution is demonstrated.
Comparative Study of Conducted Common-Mode EMI in WBG-Enabled DC-Fed Three-Phase Current-Source Inverter

In pulsewidth-modulated (PWM) inverters, common-mode (CM) voltage and associated conducted CM electromagnetic interference (EMI) can cause motor bearing failures, ground leakage current, and audio susceptibility issues. When wide bandgap (WBG) devices are used to construct a voltage-source inverter (VSI), the CM EMI issues become more challenging. The current-source inverter (CSI) is an alternative, which produces more sinusoidal output voltage waveforms, making it a promising topology for reducing CM EMI in power converters. However, there is little systematic and comprehensive analysis of CSI’s CM EMI, especially when using WBG devices. The conducted CM EMI generation mechanisms of dc-fed two-level VSIs and CSIs are compared in this article. The analytical derivation and the circuit analysis are performed to identify the CM EMI generation mechanisms in both inverters, including CM voltage sources and the resulting CM current flowing paths. The effects of WBG devices on the CM EMI of both inverters are discussed. New CM EMI equivalent circuits (EQCs) of both inverters are analytically derived to reduce the computational time of full-circuit CM EMI simulation. Different filtering schemes and inverter topology variations’ impacts on CSI’s CM EMI are evaluated using the derived EQC. An effective CM EMI filter is designed to suppress the CSI’s CM EMI to be lower than EMI standards.
EAPB0503, an Imidazoquinoxaline Derivative Modulates SENP3/ARF Mediated SUMOylation, and Induces NPM1c Degradation in NPM1 Mutant AML

Nucleophosmin-1 (NPM1) is a pleiotropic protein involved in numerous cellular processes. NPM1 shuttles between the nucleus and the cytoplasm, but exhibits a predominant nucleolar localization, where its fate and functions are exquisitely controlled by dynamic post-translational modifications (PTM). Sentrin/SUMO Specific Peptidase 3 (SENP3) and ARF are two nucleolar proteins involved in NPM1 PTMs. SENP3 antagonizes ARF-mediated NPM1 SUMOylation, to promote ribosomal biogenesis. In Acute Myeloid Leukemia (AML), NPM1 is frequently mutated, and exhibits an aberrant cytoplasmic localization (NPM1c). NPM1c mutations define a separate AML entity with good prognosis in some AML patients, rendering NPM1c as a potential therapeutic target. SENP3-mediated NPM1 de-SUMOylation induces resistance to therapy in NPM1c AML. Here, we demonstrate that the imidazoquinoxaline EAPB0503 prolongs the survival and results in selective reduction in the leukemia burden of NPM1c AML xenograft mice. Indeed, EAPB0503 selectively downregulates HDM2 expression and activates the p53 pathway in NPM1c expressing cells, resulting in apoptosis. Importantly, we unraveled that NPM1c expressing cells exhibit low basal levels of SUMOylation paralleled with high SENP3 and low ARF basal levels. EAPB0503 reverted these molecular players by inducing NPM1c SUMOylation and ubiquitylation, leading to its proteasomal degradation. EAPB0503-induced NPM1c SUMOylation is concurrent with SENP3 downregulation and ARF upregulation in NPM1c expressing cells. Collectively, these results provide a strong rationale for testing therapies modulating NPM1c post-translational modifications in the management of NPM1c AML.
Germline Variants in Cancer Genes from Young Breast Cancer Mexican Patients

Simple Summary Young, Mexican women are more susceptible to breast cancer compared to other populations. However, studies on germline young, Mexican women are scarce and limited to a panel of 143 genes. This is partially due to the lack of gene annotation tools and difficulties in determining the causal genes in understudied populations. Here, we used whole exome sequencing combined with a powerful annotation tool to analyze 862 cancer genes in 115 young, Mexican women diagnosed with breast cancer. Our results showed well-known genes and many barely reported variants in our population. Moreover, we were able to assign candidate causal genes to 34% of patients, surpassing previous studies. These results suggest that deeper bioinformatic analyses could inform medical decisions to improve diagnosis, treatment, and life expectancy in young women with breast cancer. Abstract Breast cancer (BC) is one of the most frequent cancer types in women worldwide. About 7% is diagnosed in young women (YBC) less than 40 years old. In Mexico, however, YBC reaches 15% suggesting a higher genetic susceptibility. There have been some reports of germline variants in YBC across the world. However, there is only one report from a Mexican population, which is not restricted by age and limited to a panel of 143 genes resulting in 15% of patients carrying putatively pathogenic variants. Nevertheless, expanding the analysis to whole exome involves using more complex tools to determine which genes and variants could be pathogenic. We used germline whole exome sequencing combined with the PeCanPie tool to analyze exome variants in 115 YBC patients. Our results showed that we were able to identify 49 high likely pathogenic variants involving 40 genes on 34% of patients. We noted many genes already reported in BC and YBC worldwide, such as BRCA1, BRCA2, ATM, CHEK2, PALB2, and POLQ, but also others not commonly reported in YBC in Latin America, such as CLTCL1, DDX3X, ERCC6, FANCE, and NFKBIE. We show further supporting and controversial evidence for some of these genes. We conclude that exome sequencing combined with robust annotation tools and further analysis, can identify more genes and more patients affected by germline mutations in cancer.
The Influence of Quality of Service and Satisfaction on Word of Mouth

: This study is a survey study using inpatients in hospitals. Data were collected from 200 respondents using non-probability sampling techniques. This study aims to analyze word of mouth which is influenced by service quality and patient satisfaction. The quality of service in this study is divided into three dimensions, namely responsiveness, assurance and empathy. This study uses inpatient respondents in hospitals in Timor Leste and Yogyakarta, Indonesia. The results showed that all proposed hypotheses could be accepted. Quality of service can influence Word of mouth by mediating patient satisfaction.
Model-based decision-making and its metacontrol in 1 childhood

Human decision-making is underpinned by distinct systems that differ in their flexibility and 13 associated computational cost. A widely accepted dichotomy distinguishes a flexible but 14 costly model-based system and a cheap but rigid model-free system. Optimal decision- 15 making requires adaptive arbitration between these two systems depending on 16 environmental demands. Previous developmental studies suggest that model-based 17 decision-making only emerges in adolescence. Here, we show that when using a paradigm 18 more conducive to model-based decision-making, children as young as 5 years show 19 contributions from a model-based system to their behaviour. Furthermore, we find that 20 between the ages 5 to 11, children demonstrate increasing metacontrol, which is the 21 engagement of cost-benefit arbitration over decision-making systems on a trial-by-trial basis. 22 Our results suggest that model-based decision-making emerges much earlier than 23 previously believed, while adaptive arbitration between computationally cheap and costly 24 systems continues to undergo developmental changes during childhood.
X-ray powder diffraction study on bulk Cupric Oxide (CuO) below room temperature

: The differential scanning calorimetry (DSC) and x-ray powder diffraction (XRD) measurements were carried out on CuO powder samples below room temperature. The DSC measurement unambiguously confirms two magnetic transitions at T N2 ~ 230 K and T N1 ~ 213 K. I reconfirms C2/c space group for CuO at room temperature by the Rietveld analysis of x-ray powder diffraction (XRD) data. The structural analysis proves Cc space group for CuO below T N2 ~ 230 K. The Cc space group is non- centrosymmetric. The magnetic transition below T N2 ~ 230 K breaks inversion symmetry of CuO and induced polarization of ~ 10 -1 µC/cm 2 . The ferroelectric phase again transforms into paraelectric phase below magnetic T N1 ~ 213 K. The x-ray diffraction data collected below 213 K is refined well by C2/c space group. The plot of structural parameters with temperature show clear evidence for ferroelectric transition at T C ~ 230 K.
Exploring interpretability in deep learning prediction of successful ablation therapy for atrial fibrillation

Background: Radiofrequency catheter ablation (RFCA) therapy is the first-line treatment for atrial fibrillation (AF), the most common type of cardiac arrhythmia globally. However, the procedure currently has low success rates in dealing with persistent AF, with a reoccurrence rate of ∼50% post-ablation. Therefore, deep learning (DL) has increasingly been applied to improve RFCA treatment for AF. However, for a clinician to trust the prediction of a DL model, its decision process needs to be interpretable and have biomedical relevance. Aim: This study explores interpretability in DL prediction of successful RFCA therapy for AF and evaluates if pro-arrhythmogenic regions in the left atrium (LA) were used in its decision process. Methods: AF and its termination by RFCA have been simulated in MRI-derived 2D LA tissue models with segmented fibrotic regions (n = 187). Three ablation strategies were applied for each LA model: pulmonary vein isolation (PVI), fibrosis-based ablation (FIBRO) and a rotor-based ablation (ROTOR). The DL model was trained to predict the success of each RFCA strategy for each LA model. Three feature attribution (FA) map methods were then used to investigate interpretability of the DL model: GradCAM, Occlusions and LIME. Results: The developed DL model had an AUC (area under the receiver operating characteristic curve) of 0.78 ± 0.04 for predicting the success of the PVI strategy, 0.92 ± 0.02 for FIBRO and 0.77 ± 0.02 for ROTOR. GradCAM had the highest percentage of informative regions in the FA maps (62% for FIBRO and 71% for ROTOR) that coincided with the successful RFCA lesions known from the 2D LA simulations, but unseen by the DL model. Moreover, GradCAM had the smallest coincidence of informative regions of the FA maps with non-arrhythmogenic regions (25% for FIBRO and 27% for ROTOR). Conclusion: The most informative regions of the FA maps coincided with pro-arrhythmogenic regions, suggesting that the DL model leveraged structural features of MRI images to identify such regions and make its prediction. In the future, this technique could provide a clinician with a trustworthy decision support tool.
Locally convex inductive limits of normed algebras Locally Convex Inductive Limits of Normed Algebras.

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Relevance of Segmenting, Targeting, and Positioning to Stimulate Product Performance of Traditional Woven Industry in North Sumatera

: North Sumatra has experienced a decline in the number of craftsmen and entrepreneurs of traditional North Sumatra woven industries. If this condition continues, the existence of this traditional distinctive fabric culture will disappear. Many craftsmen and business people have shifted because of the low market appeal of traditional woven industries products. This condition is debatable because other woven industries such as Batik actually have a very high appeal in the market. This study aims to map the marketing strategies and market performance of woven industries business players who still survive. A total of 300 traditional cloth business and craftsmen participated in this study. Interviews were conducted to obtain data needed in the study. The results indicate that there is a positive relationship between the implementation of marketing strategies with market performance. Market appeal perceived to fade by the craftsmen, in this study, can be improved through the application of a good marketing strategy. For businesses that have implemented marketing strategies well, the potential and market demand for their products is maintained. This research suggests that there is a synergy between academics, government, and business to strengthen marketing strategies, maintaining markets and woven industries demand, and maintaining the existence of traditional North Sumatra woven industries where academics and government help absorb and implement marketing strategies from MSMEs.
Exemplar Teaching Practices in STEM Courses in U.S. Universities

College teaching is one of the most important aspects of student outcomes in higher education (Mayhew et al., 2016), yet it receives comparatively little attention in the higher education literature base (Pallas & Neumann, 2019). Additionally, there is evidence that many courses in science, technology, engineering, and mathematics (STEM) do not use best educational practices, which causes students to drop out of STEM, causing pipeline problems for STEM occupations. In the United States, the National Science Foundation (NSF) has created funding streams to improve teaching in STEM courses in universities. Although there have been many studies of students’ views of college teaching through course evaluation surveys and national surveys, such as the National Survey of Student Engagement, few studies have examined college teaching from the perspective of expert observers. Observational studies demonstrate that student and faculty surveys typically overestimate the effectiveness of the teaching compared to expert observers (Campbell et al., 2018). The purpose of this article is twofold. First, this article describes four foundational teaching practices in higher education that have applications to STEM courses. Second, the article describes an observational study of college teaching and how engineering courses fare compared to non-engineering courses with regard to use of the exemplary practices, considering engineering as an interdisciplinary STEM field. Based on the largest multiinstitutional observational study of undergraduate courses in the United States, this article describes exemplar teaching practices in engineering courses as an interdisciplinary science field. The College Educational Quality (CEQ) research project studied 587 courses in nine different U.S. colleges and universities. This article reports on findings from engineering courses in the study. The article describes in-depth subject-matter teaching, using students’ prior knowledge and cognitive complexity, and also discusses the course contexts (e.g., size, faculty, mode) in which there is a greater likelihood of using exemplary practices in U.S. engineering courses. Four exemplary teaching practices
The unexamined philosophy is not worth doing: An introduction to
 New Directions in Metaphilosophy

Recently there has been an increasing interest in metaphilosphy. The aim of philosophy has been examined. The development of philosophy has also been scrutinised. With the development of new approaches and methods, new problems arise. This collection revisits some of the metaphilosophical issues, including philosophical progress and the aim of philosophy. It sheds new light on some old approaches, such as naturalism and ordinary language philosophy. It also explores new philosophical methods (e.g., digital philosophy of science, conceptual engineering, and the practice-based approach to logic) and their prospects.
Segmentation of Palm Oil Leaf Disease using Zoning Feature Extraction

: Oil palm (Elaeis) is an industrial plant that produces large proﬁts, especially in Indonesia. One of the factors that can affect the yield of this plant is destructive pests including Limacodidae and Psychidae. Delay in dealing with pest problems can cause poor results. This study uses the help of digital image processing to inentify two types of pests found on palm oil leaves of pests. Segmentation will be carried out to determine the characteristics of Limacodidae and Psychidae pests. The image processing method used is the zoning feature ecstasy. It is expected that knowing the types of pests suffered by oil palm trees can accelerate the recovery of oil palm trees so as to produce good quality of fruit.
Structural Biases for Improving Transformers on Translation into Morphologically Rich Languages

Machine translation has seen rapid progress with the advent of Transformer-based models. These models have no explicit linguistic structure built into them, yet they may still implicitly learn structured relationships by attending to relevant tokens. We hypothesize that this structural learning could be made more robust by explicitly endowing Transformers with a structural bias, and we investigate two methods for building in such a bias. One method, the TP-Transformer, augments the traditional Transformer architecture to include an additional component to represent structure. The second method imbues structure at the data level by segmenting the data with morphological tokenization. We test these methods on translating from English into morphologically rich languages, Turkish and Inuktitut, and consider both automatic metrics and human evaluations. We find that each of these two approaches allows the network to achieve better performance, but this improvement is dependent on the size of the dataset. In sum, structural encoding methods make Transformers more sample-efficient, enabling them to perform better from smaller amounts of data.