Miracle-dz/UniFAR-FTUs huggingface dataset:
Preeclampsia and Its Maternal and Perinatal Outcomes in Pregnant Women Managed in Bahrain’s Tertiary Care Hospital

Objective: Hypertensive disorders during pregnancy being the leading causes of maternal and fetal morbidity and mortality remains a serious health issue worldwide due to the high rate of adverse maternal outcomes and close association with neonatal morbidity and mortality. The purpose of our study was to ascertain the perinatal outcomes of preeclampsia (PE) in a tertiary care hospital in Bahrain. Methods: A retrospective cohort study was conducted from January 2018 to December 2019 in the department of Gynecology and Obstetrics in Bahrain Defense Hospital. The process of data collection included a baseline review of all women who had delivered during the study period in order to identify those with PE. Additionally, the postdelivery records of the mothers and newborns were reviewed to identify relevant maternal and neonatal outcomes. Results: During the research period, records revealed 142 patients with PE with a rate of 1.95%. The mean gestational age at diagnosis was 35.61 (± 3.69) weeks, ranging between 20 and 42 weeks. The mean birth weight was 2.64 ± 0.79 kg, ranging from 0.5-4.5 kg. Furthermore, most babies had an Apgar score of 9 at 5 minutes. The preterm delivery rate was (16.3%) and intrauterine growth restriction (IUGR) was seen in 19 patients (13.5%) and it was significantly higher in patients who presented between 30 and 34 gestational weeks P < 0.001. Twenty-one infants were admitted to the NICU primarily for prematurity and low birth weight. There was only one early neonatal death of a hydrops baby. One infant was stillborn with extreme prematurity at 24 weeks+4 days. Maternal complications included five abruption placentae (3.5%) cases, five HELLP syndrome (hemolysis, elevated liver enzymes, and low platelet count) cases (3.5%), four eclampsia (2.8%) cases, and four patients had ICU admission. Other maternal complications included acute renal failure (ARF) in two patients (1.4%), pulmonary edema in one patient, and peripartum cardiomyopathy in one patient. Data showed that adverse pregnancy outcomes were significantly more common in those with PE as compared to other pregnant populations. Conclusion: Preeclampsia causes a remarkable increase in adverse maternal and perinatal outcomes as compared to the normotensive pregnant population. A regular goal-oriented clinical audit into perinatal morbidity and mortality associated with this condition and an active multidisciplinary approach to the management of pre-eclampsia patients in the hospital might improve the clinical outcomes.
Early Prediction of Students’ Final Grades in a Gamified Course

The main challenge in higher education is student retention. While many methods have been proposed to overcome this challenge, early and continuous feedback can be very effective. In this article, we propose a method for predicting student final grades in a course using only their performance data in the current semester. It assists students in analyzing how much effort they need to put into the course to obtain the desired grades while helping course instructors identify student types at the early stages of the course to provide better support for them. Our method, initially clusters students into several groups based on experience points (XP) that they obtain during a semester. Then, we estimate cluster size and balance clusters by generating and adding virtual students to the smaller clusters. Finally, we drop unimportant student attributes using a feature selection technique. We then predict their final grades via three different algorithms. We have compared the performance of our method with other approaches using data collected from a course for nine years, using data collected from 679 students. The results indicate that our method outperformed the others while achieving 78.02% average accuracy only four weeks after starting the course. It shows we can effectively predict final grades, which will potentially enhance students’ learning outcomes.
Protocatechuic Acid Induces Apoptosis in Human Osteosarcoma Cells by Regulating P 13 K / AKT/ROS Pathway

Previous investigations have demonstrated that protocatechuic acid (PCA) provides anti-tumour properties in different tumour cell types. It does, however, have an unknown cause on osteosarcoma cells. In this investigation, the underlying mechanism of the effect of PCA on osteosarcoma cells ( MNNG or HOS ) was investigated and established. The viability of the cell was assessed with the MTT test. Acridine orange/ethidium bromide staining and Western blot analysis were conducted for assessment of cell apoptosis. Western blot analysis was identified for cell cycle progression. In addition to establishing the above findings, the Western blot analysis demonstrated that PCA mediated osteosarcoma cellular apoptosis by triggering the apoptotic pathway of Caspase-9. Additionally, we found that PCA considerably stimulated osteosarcoma cell apoptosis and arrest of cell cycle proliferation by controlling a pathway involving P13K/Akt/ ROS signalling. In short, we observed that PCA prevented the advancement of osteosarcoma through the stimulation of apoptosis in osteosarcoma cells. The mechanism underlying this study also showed that PCA generated effective anti-tumour activity on osteosarcoma cells by controlling the signalling pathways of P13K/Akt/ROS. group was drastically enhanced by LY294002 compared with the PCA and LY294002 groups ( # P < 0.01) respectively. Three independent studies were conducted to represent the data as mean+SEM
Forecasting for Network Management with Joint Statistical Modelling and Machine Learning

Forecasting is a task of ever increasing importance for the operation of mobile networks, where it supports anticipatory decisions by network intelligence and enables emerging zero-touch service and network management models. While current trends in forecasting for anticipatory networking lean towards the systematic adoption of models that are purely based on deep learning approaches, we pave the way for a different strategy to the design of predictors for mobile network environments. Specifically, following recent advances in time series prediction, we consider a hybrid approach that blends statistical modelling and machine learning by means of a joint training process of the two methods. By tailoring this mixed forecasting engine to the specific requirements of network traffic demands, we develop a Thresholded Exponential Smoothing and Recurrent Neural Network (TES-RNN) model. We experiment with TES-RNN in two practical network management use cases, i.e., (i) anticipatory allocation of network resources, and (ii) mobile traffic anomaly prediction. Results obtained with extensive traffic workloads collected in an operational mobile network show that TES-RNN can yield substantial performance gains over current state-of-the-art predictors in both applications considered.
ManyTypes4TypeScript: A Comprehensive TypeScript Dataset for Sequence-Based Type Inference

In this paper, we present ManyTypes4TypeScript, a very large corpus for training and evaluating machine-learning models for sequence-based type inference in TypeScript. The dataset includes over 9 million type annotations, across 13,953 projects and 539,571 files. The dataset is approximately 10x larger than analogous type inference datasets for Python, and is the largest available for Type-Script. We also provide API access to the dataset, which can be integrated into any tokenizer and used with any state-of-the-art sequence-based model. Finally, we provide analysis and performance results for state-of-the-art code-specific models, for baselining. ManyTypes4TypeScript is available on Huggingface, Zenodo, and CodeXGLUE.
The Influencing Mechanism of Surface Wettability on Convective Heat Transfer in Copper Nanochannel

Non-equilibrium molecular dynamics simulation is employed to probe the convective heat transfer of water flowing through a nanochannel. The wall-fluid interaction is considered as different values to characterize nanochannel wall with various surface wettability. The atomic microstructure, flow behavior and heat transfer characteristics are investigated. The results show that wall-fluid interaction plays an important role in interfacial fluid structure, density distribution, velocity slip, velocity distribution and temperature distribution as well as interfacial heat transfer. Adjusting the surface wettability of nanochannel wall will bring a significant impact on the heat transfer performance and flow properties. The increase of wall-fluid interaction enhances the first peak value of density and the main peak value of static structure factor. Thus, the interface velocity slip decreases, which is not beneficial to the reduction of flow resistance. In contrast, the nanochannel wall with the strong wall-fluid interaction is more similar to hydrophilic surface, and the heat transfer performance is better.
Theory Building Through Corporate Social Responsibility 4.0 for Achieving SDGs: A Practical Step Toward Integration of Digitalization With Practice-Based View and Social Good Theory

Corporate social responsibility (CSR) has become a hot topic in recent years, especially following the introduction of the sustainable development goals (SDGs). Among various strategies for achieving SDGs, CSR has become a dominant practice by which managers eliminate corporate social impact and develop social responsibility and commitment. To improve the integration of CSR into organizational practices, companies began to explore various available options. Academic studies began to analyze drivers, barriers, and best practices in CSR. More recent organizational structures are being transformed with the advent of new industry 4.0 technologies. There is good evidence that these technological integrations can improve the organization's overall performance. This article attempts to consider such technologies in CSR management. Industry 4.0 technologies, integrated with CSR and their practices, have been analyzed as “CSR 4.0 practices. ” A theoretical framework has been proposed that links the practice-based view with the theory of social good. Further, the theory has been validated through a case study in which 23 CSR 4.0 practices that enhance better integration of digitization with the company's conventional CSR were collected from the literature and validated with experts for social good. These practices were further analyzed with DEMATEL, a multicriterion decision-making tool using case decision-makers’ responses. Case study methods have been adapted to this article, where the textile sector from one of the developing contexts, India, has been considered. Among 23 CSR 4.0 practices, “data ownership policy and rights” (P22) has been identified as the most influential CSR 4.0 practice, while “digital technology recycling” (P19) ranks as the least influential. The resulting influential practices have been correlated with CSR 4.0 performances and, further, those performances are connected with their respective SDGs. This article warrants several scientific and societal contributions to CSR; this article is groundbreaking and contributes to theory building in CSR through the identification and analysis of CSR 4.0 practices. Further expansion of this article may be more fruitful due to the digitized changes in organizational culture.
Trust and Trustworthiness in Human-Robot Interaction: A Formal Conceptualization

Abstract : The overarching objective of the effort was to explore the possibility of formally characterizing the concept of trust using tools from interdependence and game theory in complex and dynamic social environments. This effort evaluated algorithms for characterizing trust during interactions between a robot and a human and employed strategies for repairing trust during emergency evacuation scenarios. Our results demonstrate that there is a high correlation between our characterizations of trust in a situation and the judgments of people, that timing is a key element necessary for trust repair, and that people tend to overtrust robots, potentially putting themselves in dangerous situations. We have examined human-robot trust in a variety of simulated and live experiments across several different types of risk including both financial and physical risk. These results generally support the conclusion that people will tend to overtrust robots because they believe that the systems are incapable of failure or capable of performing actions or has knowledge which the system cannot perform or does not have.
RATES OF MULTIVARIATE NORMAL APPROXIMATION FOR STATISTICS IN GEOMETRIC PROBABILITY

We employ stabilization methods and second order Poincaré inequalities to establish rates of multivariate normal convergence for a large class of vectors ( H (1) s ,. ,H ( m ) s ) , s ≥ 1 , of statistics of marked Poisson processes on R d , d ≥ 2 , as the intensity parameter s tends to inﬁnity. Our results are applicable whenever the functionals H ( i ) s , i ∈ { 1 ,. ,m } , are expressible as sums of exponentially stabilizing score functions satisfying a moment condition. The rates are for the d 2 -, d 3 -, and d convex -distances and are in general unimprovable. When we compare with a centered Gaussian random vector, whose covariance matrix is given by the asymptotic covariances, the rates are governed by the rate of convergence of s − 1 Cov( H ( i ) s ,H ( j ) s ) , i,j ∈ { 1 ,. ,m } , to the limiting covariance, shown to be at most of order s − 1 /d . We use the general results to deduce rates of multivariate normal convergence for statistics arising in random graphs and topological data analysis as well as for multivariate statistics used to test equality of distributions. Some of our results hold for stabilizing functionals of Poisson input on suitable metric spaces.
Design and development of an optical fiber sensor for hydrogen detection

Hydrogen detection is an environmental priority. Numerous hydrogen sensors have been developed, but none of them meet the industry requirements. Optical fiber sensors, electrically isolated, are excellent candidates for operating in explosive environments. Our goal is to develop an intrinsic optical fiber sensor based on Surface Plasmon Resonance. In this thesis, we study two optical fiber hydrogen sensors. The first sensor, based on amplitude modulation, consists of a thin Pd layer deposited on the multimode fiber core, after removing the optical cladding. The second design, based on wavelength modulation, consists of replacing the single Pd layer by a Au/ SiO2/ Pd multilayer stack. We demonstrate in this thesis that plasmonic sensors may be a solution to develop fast and reliable fiber hydrogen sensors. Finally, we study Mg alloys as hydrogen sensitive material in order to improve the detection range of hydrogen sensors.
Inclusive Leadership, Workplace Spirituality, and Job Performance in the Public Sector: A Multi-Level Double-Moderated Mediation Model of Leader-Member Exchange and Perceived Dissimilarity

Abstract Although inclusive leadership as an essential leadership style for a diverse workforce has attracted increasing attention in business management research, little is known about how and when it may improve subordinates’ job performance in the public sector where civil servants are expected to have high levels of workplace spirituality. Therefore, this study theorizes a multi-level double-moderated model where inclusive leadership impacts civil servants’ job performance with workplace spirituality as a mediator and leader-member exchange (LMX) and perceived dissimilarity as moderators based on the conservation of resources theory. A sample of 392 civil servants nested within 72 local functional government departments in China’s western multi-ethnic regions through a three-wave survey was used to examine our proposed model by multi-level structural equation modeling analysis. The results demonstrate that the positive relationship between inclusive leadership and civil servants’ job performance is transmitted through the workplace spirituality. LMX and perceived dissimilarity serve as two moderators of the above mediated positive relationship. Theoretical and practical implications, limitations, and future research directions are also discussed.
Beyond risk: Communitas, flow and embodiment in the practices of paragliding

This consumer behavior study investigates paragliding, a little studied form of engineless free flight in which a pilot uses naturally occurring air currents to ascend, stay aloft, and fly across distances while seated under a frameless nylon canopy. Purpose of the Study This study seeks to understand the practices of paragliding, through an examination of its web of practice-arrangements, and how paraglider pilots experience them. By extension, I ask what role embodied cognition may play in these practices; and whether practice theory or embodiment help expand our understanding of a risky-sport experience Methodology Ontologically this study is grounded in practice theory. The research method utilizes videography, participant observation and interviews. The findings are presented via a rhetorical collage alternating ethnographic thick description with theoretical analysis utilizing theories of flow, embodied cognition and practices. Findings The practices of paragliding offer an ever changing experience in which pilots navigate the invisible in a dance of total attention that engenders flow, communitas with other pilots, and a spiritual sense of union with a higher natural order that leads them to endure regular sacrifices to realize and maintain their dreams to fly like a bird. Paragliding shows some parallels to the Celsi et al (1993) model of high-risk consumption, however a completely different web of practices and interlinked embodied experiences result in a distinct framing of the experience outside of considerations of risk, adrenaline or social rebellion. Embodied cognition is tacitly incorporated into training regimes as a critical component of learning and doing the practices that help paragliders not only to achieve transformative states but to conceive of, and understand them. Theories of embodiment and practice theory have a strong affinity. Practice theory is an effective ontological tool for studying activities with elements of risk that allows researchers to drop restrictive framing biases in favor of seeing a phenomenon in all its multi-layered, intersecting dimensions.
Citizenship, self-efficacy and education: A conceptual review

Primary and secondary schools across the world are expected to contribute to the citizenship development of their pupils. Most citizenship curricula focus on the acquisition of knowledge and the cultivation of skills and attitudes. Citizenship-related self-efficacy beliefs are often neglected in the literature on citizenship education, although they appear to play a crucial role in learning processes, among others as explanatory factors for the inequalities between students in different educational tracks. As such, studies on the development of citizenship-related self-efficacy beliefs have the potential to inform practice in a way that fosters greater equality of opportunity. However, as the literature on civic and political self-efficacy uses different dimensions and conceptualizations, this poses challenges to both the scientific accumulation of knowledge and translation to teaching practices. Here, we analyse the conceptual challenges and propose a framework for the study of self-efficacy in citizenship education research that incorporates social and political tasks of citizens and distinguishes the variety of communities in which citizens perform those tasks on two axes, namely formality and size. In doing so, we argue for fine-grained distinctions based on context instead of the all-encompassing notions of civic and political self-efficacy political theorists appear to prefer. We end by discussion two normative issues.
Effects of Supplementation with Rumen-Protected Choline and Methionine on Metabolic Profile and Some Reproductive Parameters in Dairy Cattle During Transition Period

Effects of Supplementation with Rumen-Protected Choline and Methionine on Metabolic Profile and Some Reproductive Parameters in Dairy Cattle During Period. Abstract This study conducted to determine effect of the rumen-protected choline and methionine supplementation to peripartum dairy cattle on metabolic profile, metabolic disorders and some reproductive parameters. For this, 3-6 year-old, multiparous, healthy and pregnant 32 high-yield Holstein dairy cows were divided into 4 different groups during trial as: a control (CON) group with no supplementation to the ration; a 75 gr/day rumen-protected choline chloride (CHOL) supplemented group, 42 gr/ day methionine (MET) supplemented group, 75 gr/ day choline chloride and 42 gr/ day methionine (MET + CHOL) supplemented group were during three weeks before and after parturation. Blood samples were taken at wk -3, calving, wk 3 and wk 10 and were analyzed. Health problems and reproductive data were recorded during treatment. Statistically significant differences were detected in non-esterified fatty acids (NEFA), insulin like growth factor-1 (IGF-1), glucose, total protein, albumin, direct bilirubin, total cholesterol and very low density lipoproteins (VLDL). Results of this study suggested that rumen-protected choline and methionine supplementation to the rations of dairy cattle affected some metabolic profile parameters. The statistical differences in metabolic profile tests did not affect metabolic diseases and reproductive parameters. non-esterified fatty acids, beta-hydroxy butyric insulin like growth factor-1 paraoxonase-1, B100, transferase, aspartate aminotransferase,
ANTI-MONEY LAUNDERING REGULATIONS AND BANKING SECTOR STABILITY IN Africa

Abstract The study econometrically analysed anti-money laundering regulations and banking sector stability in Africa. A panel data on 51 African countries over the period of 2012 to 2019 were used. Secondary data were sourced from the World Bank’s indicators, the IMF, the Basel Institute on Governance other financial websites. The two-staged Generalised Moment Method (GMM) was used to analyse the effect of AML regulations on banking sector stability and the effects of the different levels of AML effectiveness and its impact on the banking sector stability in Africa. The study discovered that AML regulations had a significant positive effect on the stability of banking sectors in African countries. This indicated that whether there was high effectiveness or low effectiveness of the AML regulations, it would still have a positive impact on the stability of the banking sector of the country.
Counterion distribution around a polyelectrolyte confined in a metal–organic framework

ABSTRACT Recently, polyelectrolytes confined in metal–organic frameworks (MOFs) are reported to demonstrate superior ion exchange with high selectivity. To reveal the counterion distribution around spatially confined polyelectrolytes without direct experimental measurements, we perform molecular dynamics simulations of ionic solution in equilibrium with a polyelectrolyte–MOF composite in explicit water. In contrast to the reported qualitative work on linear polymer conformation in vacuum, polyelectrolytes behave as stiff-like polymers after threading into the one-dimensional channels of MIL-53(Al). Consequently, the counterions tend to be uniformly distributed and locally condensed around the linearised polyelectrolyte chain. In addition to the high ion exchange performance properties of polyelectrolyte–MOF composites, the unique distribution of counterions and the structural dynamics of the confined polyelectrolyte would lead to other potential applications in membranes and interfacial technologies.