Miracle-dz/UniFAR-FTUs huggingface dataset:
eLEARNING PERCEIVED USEFULNESS, SELF-EFFICACY AND ATTITUDE OF DISTANCE LEARNERS AND E-LEARNING UPTAKE AT THE COLLEGE OF DISTANCE EDUCATION, UNIVERSITY OF

This study has been reported on the extent to which Distance Learners are ready to take up the deployment of eLearning as an alternative mode to the fortnightly face to face sessions organized at the various study centres across the Country, Ghana. Specifically, this study sought to predict the rate of eLearning utilization taking into consideration determinants such as eLearning perceived usefulness, self-efficacy, and attitude of Distance Learners. The theory guiding this study was the Theory of Reasoned Action (TRA). According to Fishbein and Ajzen (1980), people behave in a certain direction, if they perceived that the outcome of the antecedent behavior will be beneficial to them. In this context, this study hypothesized that UCC Distance students will tend to use eLearning if they perceived usage to be beneficial to them. Three sets of questionnaires, with Cronbath’s Alpha reliability coefficients above 0.70, were used to collect data. Statistical Package for Social Sciences (SPSS) was used to analyze the data collected from 472 distance students of the University of Cape Coast. Regression and one way anova statistical tools were used to test the hypotheses. The results of the study indicated that there are regional differences shown by UCC distance students in relation to how they perceived the usefulness of eLearning, their self-efficacy and attitude towards eLearning. This study also revealed that the University of Cape Coast, distance students’ use of eLearning is not dependent on how they perceived eLearning to be useful. Again the study found that distance students’ use of eLearning cannot be predicted by their attitude towards eLearning. Rather, Distance learners’ perceived eLearning self-efficacy is a major predictor of eLearning usage at the College of Distance Education, university of Cape Coast. This study, therefore recommends that ICT-based training programmers should be periodically organized for the distance students, which should take cognizance of the regional differences established by this study.
Smart city based on community empowerment, social capital, and public trust in urban areas

BACKGROUND AND OBJECTIVES: Urbanization has been causing many problems for the environment and society. An ineffective and inefficient government also contributes to urban problems by increasing public dissatisfaction and distrust of government. Technological Improvements makes it possible for local governments in Indonesia to implement the concept of “Smart City” as a solution to solve urban problems. This study aims to fill the gap by examining the impact of smart city application on public trust towards the government. METHODS: A primary data collection was conducted in 2021 to profile the citizens’ behaviour in terms of smart city application. This study had surveyed four big cities in Indonesia that had built smart city applications well: Jakarta, Bandung, Semarang, and Surabaya. The primary data were analyzed through ordinary least squares regression. FINDINGS: This study founds that the fundamental factors of smart city applications that are statistically significant were on quality, satisfaction, and reliability. These factors had positive and significant impacts on the level of trust in the local government. Based on the regression model, the increase of application quality score by 1 affects the score of trust in the local government, which will rise by 0.440 (Jakarta), 0.269 (Bandung), and 0.245 (Semarang), and 0.212 (Surabaya). The increase in application satisfaction score by 1 affects the score of trust in local government, which will rise by 0.193 (Jakarta), 0.431 (Bandung), 0.07 (Semarang), and 0.186 (Surabaya). Also, an increase in application reliability score by 1 affects a rise in trust in local government by 0.187 (Jakarta), 0.204 (Bandung), 0.137 (Semarang), and 0.192 (Surabaya). CONCLUSION: Smart city applications can shape public trust by increasing the application’s quality, satisfaction, reliability and community empowerment. However, it should be noted that the number of community which uses smart city application is still low. Therefore, It is necessary to encourage a culture of using those applications to help build citizens’ trust in the government and improve urban quality.
NBER WORKING PAPER SERIES THE IMPACT OF EXPORTS ON INNOVATION : THEORY AND EVIDENCE

The authors would like to thank, without implicating Daron Acemoglu, Ufuk Akcigit, Elhanan Helpman, Giammario Impullitti, Thierry Mayer, Torsten Persson, Stephen Redding, Thomas Sampson, Dan Trefler, John Van Reenen, Daniel Xu, and participants at the 2017 AEA meeting, the NBER Summer Institute 2017, CIFAR and numerous seminars for useful discussions and advises. We are grateful to Connie Lee for excellent research assistance. This work is supported by a public grant overseen by the French National Research Agency (ANR) as part of the “Investissements d’Avenir” program (reference: ANR-10-EQPX-17 Centre d’accès securise aux donnees – CASD). The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
COVID-19 Detection via Silicon Nanowire Field-Effect Transistor: Setup and Modeling of Its Function

Biomolecular detection methods have evolved from simple chemical processes to laboratory sensors capable of acquiring accurate measurements of various biological components. Recently, silicon nanowire field-effect transistors (SiNW-FETs) have been drawing enormous interest due to their potential in the biomolecular sensing field. SiNW-FETs exhibit capabilities such as providing real-time, label-free, highly selective, and sensitive detection. It is highly critical to diagnose infectious diseases accurately to reduce the illness and death spread rate. In this work, a novel SiNW-FET sensor is designed using a semiempirical approach, and the electronic transport properties are studied to detect the COVID-19 spike protein. Various electronic transport properties such as transmission spectrum, conductance, and electronic current are investigated by a semiempirical modeling that is combined with a nonequilibrium Green’s function. Moreover, the developed sensor selectivity is tested by studying the electronic transport properties for other viruses including influenza, rotavirus, and HIV. The results indicate that SiNW-FET can be utilized for accurate COVID-19 identification with high sensitivity and selectivity.
ENERGY OPTIMIZATION ON THE SPHERE

In the present paper we discuss several issues connected by the common theme of optimizing energy integrals and discrete energy on the sphere. These include various versions, gen-eralizations and applications of the Stolarsky identity, which relates optimal energy and discrepancy, Riesz-type energies based on geodesic distances, properties of minimizers of the p -frame energy, as well as a conjecture of Fejes T´oth on the sum of angles between lines.
Attribute Theories of Memory ∗

Attribute theories propose that a cognitive system constructs representations with constituent elements that reﬂect the attributes, features, properties, or characteristics of the world and the things in it. These theories are ﬂexible; Attributes may be used to describe tangible physical things in one’s environment, but also intangible things like plans and concepts. In the domain of memory, attribute theories describe how representations of one’s experience are stored, retrieved, and manipulated by the cognitive system. The mathematical language of linear algebra is central to these theories. Vector operations are used to deﬁne various measures of representational distance and similarity. Matrices are used to deﬁne associative structures like synaptic weights in neural network models, and sets of memories in instance theory models. We examine some foundational attribute-based approaches to memory theory, including early attempts to deﬁne psychological similarity, and the inﬂuential stimulus-sampling theory. We review important empirical phenomena involving memory attributes, including proactive interference, encoding speciﬁcity, and source memory. Finally, we consider how attribute-based approaches have inﬂuenced modern cognitive neuroscientiﬁc investigations and theory.
MOBILE PAYMENT ADOPTION AMONG YOUTH: GENERATION Z AND DEVELOPING COUNTRY PERSPECTIVE

This paper aims to understand the factors that influence mobile payment adoption among youth concerning Generation Z customers, who are the most significant drivers of mobile payments, specifically in developing countries. Data was collected through a questionnaire accomplished by 365 undergraduate students between 18 to 22 years of age. The partial least square structural equation modelling (PLS-SEM) analysis instituted the behavioural intention to adopt mobile payments was substantially and positively affected by social influence, performance expectancy, and effort expectancy. In contrast, the facilitating conditions and price value were insignificant. The negative effect of price value on the intention to adopt mobile banking suggests the irrelevance of promotional offers (discounts, cash-backs) for adoption. The marketers can use the suggestions provided in the study to craft suitable strategies for the sustainable adoption of mobile payments by Generation Z customers in a developing country.
study into the use lean to reduce

Purpose: Medication errors are a significant cause of injury in Norwegian hospitals. The purpose of this study is to explore how Lean Six Sigma has been utilised in the Norwegian public healthcare context to reduce medication errors. Design/Methodology/Approach: A mixed method approach was used to gather data from participants working in the four regions served by the Norway Health Authorities. A survey questionnaire was distributed to 38 healthcare practitioners and semi-structured interviews were conducted with 12 healthcare practitioners. Findings: The study finds that the implementation of Lean Six Sigma in the Norwegian public healthcare context is still in its infancy. This is amidst the several challenges faced by Norwegian hospitals, such as a lack of top management support, lack of LSS training and coaching and a lack of awareness around the benefits of LSS in healthcare. Research limitations/Implications: Due to the large geographical area, it was difficult to reach participants from all health regions in Norway. However, the study managed to assess the current status of LSS implementation through the participants’ perspectives. This is a fruitful area for future research whereby an action research methodology could be employed. Originality/Value: To the best of the authors’ knowledge, this is the first empirical study into the use of LSS methodology in reducing medication errors. In addition, this study is valuable for healthcare practitioners and professionals as a guideline to achieve the optimal benefit of Lean and Six Sigma implementation in order to reduce medication errors.
Deep Learning Training Procedure Augmentations

Recent advances in Deep Learning have greatly improved performance on various tasks such as object detection, image segmentation, sentiment analysis. The focus of most research directions up until very recently has been on beating state-of-the-art results. This has materialized in the utilization of bigger and bigger models and techniques which help the training procedure to extract more predictive power out of a given dataset. While this has lead to great results, many of which with real-world applications, other relevant aspects of deep learning have remained neglected and unknown. In this work, we will present several novel deep learning training techniques which, while capable of offering significant performance gains they also reveal several interesting analysis results regarding convergence speed, optimization landscape smoothness, and adversarial robustness. The methods presented in this work are the following: 1. Perfect Ordering Approximation; a generalized model agnostic curriculum learning approach. The results show the effectiveness of the technique for improving training time as well as offer some new insight into the training process of deep networks. 2. Cascading Sum Augmentation; an extension of mixup capable of utilizing more data points for linear interpolation by leveraging a smoother optimization landscape. This can be used for computer vision tasks in order to improve both prediction performance as well as improve passive model robustness. Key words— Deep Learning, Convergence, Data Augmentation, Adversarial Attacks Robustness
Heaviside-Maxwellian Gravity form Local U(1) Phase/ Gauge Invariance of the Lagrangian for Massive Neutral Dirac Particle

Starting with Dirac Lagrangian for free massive electrically neutral Dirac particles and demanding local phase invariance, we are forced to introduce a massless vector field ( ) and to find a complete Lagrangian that generates all of Heaviside's Gravity (HG) of 1893 as well as the relativistic Maxwellian Gravity (MG) which specifies the current produced by massive electrically neutral Dirac particles. The resulting spin-1 vector gravitational theory, named here as Heaviside-Maxwellian Gravity (by establishing the equivalence of HG and MG), is shown to produce attractive force between like masses under static condition, contrary to the prevalent view on vector gravitational theory.
Summative and Formative Assessments in Mathematics Supporting the Goals of the Common Core Standards

Being proficient in mathematics involves having rich and connected mathematical knowledge, being a strategic and reflective thinker and problem solver, and having productive mathematical beliefs and dispositions. This broad set of mathematics goals is central to the Common Core State Standards for Mathematics. High-stakes testing often drives instructional practice. In this article, I discuss test specifications and sample assessment items from the two major national testing consortia and the prospects that their assessments will be positive levers for change. For more than 20 years, the Mathematics Assessment Project has focused on the development of assessments that emphasize productive mathematical practices, most recently creating formative assessment lessons (FALs) designed to help teachers build up student understandings through focusing on student thinking while engaging in rich mathematical tasks. This article describes our recent work.
Building an Interpretable Machine Learning Classifier for the Prediction of Brain Tumour Survival

Prognosis of a brain tumour is often poor, and the prediction of survival is one of the most challenging tasks physicians face. An accurate prognosis is essential for patient support and has a decisive impact on potential treatment regimens. This project uses a hand-curated brain tumour dataset to compare interpretable rule list models to a number of popular machine learning approaches for survival prediction. The performance of the interpretable models will be evaluated against “black box” machine learning models and the cost of transparency will be assessed. We investigate two rule list algorithms, Bayesian rule lists and falling rule lists, and qualitatively assess their interpretabiliy and clinical utility with the help of domain experts. We show that interpretable rule list models are able to predict survival on par with opaque machine learning models and have the added benefit of interpretability.
M ALAYSIAN J OURNAL OF A NALYTICAL S CIENCES EFFECT OF SILVER ON THE PHYSICAL AND STRUCTURAL PROPERTIES OF LEAD NEODYMIUM BOROTELLURITE GLASS SYSTEM

Neodymium doped borotellurite glass is well known to be one of the most promising candidate due to it various applications. Nd 3+ doped lead borotellurite glasses containing silver were successfully been prepared by conventional melt-quenching method with the chemical composition (69.5- x )TeO 2 -20B 2 O 3 -10PbO-0.5Nd 2 O 3 - x AgNO 3 (where x = 0, 0.5, 1.0, 1.5, 2.0 and 2.5 mol %). The physical properties such as density, molar volume and oxygen packing density were measured. Their structural properties of the glass system were studied via X-Ray Diffraction (XRD) analysis and Fourier Transform Infrared (FTIR) spectroscopy. From the result, the amorphous nature of the prepared glass samples have been confirmed through X-ray diffraction spectral analysis. The presence of Te-O-Te or O-Te-O, Ag-O, Te-O-Pb and B-O and characteristic of the hydrogen bond in the prepared glasses were explored through the FTIR spectral studies recorded in the 400-4000 cm -1 wave number range at room temperature. Meanwhile, the results of physical properties are found to vary with respect to concentration of AgNO 3 content. Some other results will be reported and discussed.
Subliminal mere exposure effects on the ageist attitude change among young adults

Ageism is a concept of age stereotype, in which an ageist attitude dictates how young people perceive the old. A negative ageist attitude gravitates to discrimination and condemnation towards the aged. Stereotypes are reinforced by frequent exposure to media contents. Since media contents have a significant impact on individual’s attitude, this experimental research aims to study the subliminal media in posing change on the ageist attitude of young adults between ages 18 and 25, where such attitude change is due to mere exposure effect (MEE). In contrast to the norm of past studies using explicit self-report tests, this study delves into the implicit element of ageist attitude conducted using an experimental approach. Data was collected from 72 young adults as they are highly exposed to contents of the media frequently. Participants were randomly assigned to positive and negative media stimulus groups. Results of paired t-test verified the hypothesis that both positive and negative subliminal contents have a large effect on the ageist attitude change of the participants. When young adults are exposed to positive interventions, their perception positively affects ageist attitude and vice versa. Thus, findings imply that attitudes of young adults can be altered by media contents.
Superior Performance of Ca(OH) 2 -CaO-H 2 O System Doped with Cerium and Lithium for Thermochemical Energy Storage

Thermochemical energy storage is a next generation technology and also an efficient solution for large-scale use of solar energy. Lime (CaO) doped with cerium nitrate (Ce(NO 3 ) 3 ) and lithium hydroxide (LiOH) has been demonstrated to be an excellent energy storage material via the dehydration-hydration process. The heat–storage rate is massively enhanced, by 173–fold. The dehydration conversion ratio increases by 98% (65.3-fold increase) in 28 min. The cycling stability of Ca(OH) 2 -Ce(NO 3 ) 3 -LiOH composites in the process of thermal storage and release has also been greatly improved. The peak temperature of dehydration is reduced significantly from 418 to 341 0 C. The activation energy and the pre-exponential factor ln A for Ca(OH) 2 dehydration decrease by 34.6% and 29.4%, respectively. The crystal parameters and the crystal volume of Ca(OH) 2 are enlarged. Particle size and agglomeration are decreased. The kinetic equations for dehydration could be leveraged in future for the purpose of informing reactor design and simulations.
Determination of potassium bromade in bread samples from Gashua and Nguru communities of Yobe state, Nigeria

This study was aimed at determining the level of potassium bromate in some selected bread samples consumed in Gashua and Nguru areas council of Yobe State-Nigeria, with the view of ascertaining the level of dietary exposure of consumers of bread in Gashua and Nguru to the risk of Potassium bromate. Breads was collected from fourteen (14) different bakeries in Two local government (Nguru and Bade local government area): Bread samples were bought directly from the bakeries in the selected areas of Gashua (Bade) and Nguru local government area) of Yobe State. Sample collection and preparations were conducted using standard procedures. Studies were conducted between the period of three months (October, December and March). Bread sample from study areas were collected and the levels of potassium bromate (KBrO 3 ) was determined. The results of potassium bromate in bread samples obtained in this study were 12.16 μg/g and 0.0001μg/g for highest and the lowest level of KBrO3 found in bread samples consumed in Nguru and Gashua town. The potassium bromate levels in the bread samples were determined using a spectrophotometer at 620 nm. The concentration was calculated from the linear regression curve obtained from the standard solutions of Potassium bromate. The overall Results of the studies for the three months showed that potassium bromate was detected in all the months and was highest among samples collected in Gashua having 0.75±1.76 mg/g and Nguru 0.66 ±1.98 mg/g. For the three month not detected the highest value was found in Gashua with -0.23 ±0.41 mg/g, while the least value is found in Nguru -0.33 ±0.41 mg/g. The mean and standard deviation showed the following values in Nguru 3.01 ±3.41 mg/g and 2.47 ± 2.54 mg/g in Gashua for the first month and 0.00 ±0.00 mg/g for both Nguru and Gashua for the third month. The quality of bread in Gashua and Nguru local government area of Yobe state have not been monitored, thus there is no information concerning the level of potassium bromate in this area, since there is high rate of consumption of bread. Routine monitoring of potassium Bromate in these study areas is necessary for the prevention, and control of the intake, so as to minimize health risks.