Miracle-dz/UniFAR-FTUs huggingface dataset:
A Divergent View of the Impact of Digital Transformation on Academic Organizational and Spending Efficiency: A Review and Analytical Study on a University E-Service

With the aim of achieving a global ranking and academic distinction, a large number of universities have decided to focus on competition and greater academic quality on a global scale. During the course of such a journey, universities have to face numerous challenges, including the enhancement of organizational efficiency. In the context of organizational efficiency, the most significant pillar supporting this drive is recognized as being digital transformation. It is widely accepted that digital transformation allows electronic systems to be used in the process of teaching and learning. These electronic systems (e-services) enhance universities’ operational efficiency. Keeping this in mind, this research paper aims to analyze the impact of digital transformation on the organizational and spending efficiency of universities, with a special focus on one particular e-service provided by the Saudi University. For this, the study examines the effort made by the government to spread the culture of rationalization and improve the efficiency of spending through a case study involving a statistical analysis of real data from an electronic system. The results of the study state that an increase in the number of subject withdrawals will weaken the spending and organizational efficiency of the University.
Two distinct non-Arrhenius behaviors of hydrogen diffusivities in fcc aluminum, silver, and copper determined by 
ab initio
 path integral simulations

Nuclear quantum effects (NQEs) are highly important for understanding a host of kinetic processes that occur with the participation of H (e.g., H adsorption, diffusion, permeation, and trapping in materials). In this paper, ab initio path integral molecular dynamics simulations were used to investigate NQEs on the lattice diffusion of H in common face-centered cubic (fcc) metals such as Al, Ag, and Cu over a wide temperature range of 75--1200 K (75--900 K for Al). We determined that the dependence of H diffusivities on temperature in Ag and Cu has a ``reversed-S'' shape on Arrhenius plots, as confirmed for fcc Pd in our recent study [H. Kimizuka et al., Phys. Rev. B 100, 024104 (2019)]. This result illustrates that the phenomenon is common in many fcc metals in which H atoms prefer to occupy octahedral sites. On the other hand, in the case of Al, in which H atoms prefer to occupy tetrahedral sites, the dependence of H diffusivities on temperature exhibits a familiar ``C'' shape. Such counterintuitive behavior is ascribed to differences in the dependence on temperature of the activation barriers for H migration between both types of fcc metals; this is due to the NQEs involving a competition between deceleration of H migration, which becomes effective at high temperatures because of zero-point vibrations, and acceleration of H migration, which becomes effective at low temperatures because of quantum tunneling. The dominance of the two mechanisms is determined by the coupling of the NQEs and the site preference of H depending on the metal. This finding has important implications for the interpretation of kinetic processes involving the crossover from classical to quantum behavior of H atoms jumping between different types of interstitial sites.
Dynamic Stability of Orthotropic Viscoelastic Rectangular Plate of an Arbitrarily Varying Thickness

The research object of this work is an orthotropic viscoelastic plate with an arbitrarily varying thickness. The plate was subjected to dynamic periodic load. Within the Kirchhoff–Love hypothesis framework, a mathematical model was built in a geometrically nonlinear formulation, taking into account the tangential forces of inertia. The Bubnov–Galerkin method, based on a polynomial approximation of the deflection and displacement, was used. The problem was reduced to solving systems of nonlinear integrodifferential equations. The solution of the system was obtained for an arbitrarily varying thickness of the plate. With a weakly singular Koltunov–Rzhanitsyn kernel with variable coefficients, the resulting system was solved by a numerical method based on quadrature formulas. The computational algorithm was developed and implemented in the Delphi algorithmic language. The plate’s dynamic stability was investigated depending on the plate’s geometric parameters and viscoelastic and inhomogeneous material properties. It was found that the results of the viscoelastic problem obtained using the exponential relaxation kernel almost coincide with the results of the elastic problem. Using the Koltunov–Rzhanitsyn kernel, the differences between elastic and viscoelastic problems are significant and amount to more than 40%. The proposed method can be used for various viscoelastic thin-walled structures such as plates, panels, and shells of variable thickness.
Projected increase of Arctic coastal erosion and its sensitivity to warming in the 21st Century

Arctic coastal erosion damages infrastructure, threatens coastal communities, and releases organic carbon from permafrost. However, the magnitude, timing and sensitivity of coastal erosion increase to global warming remain unknown. Here, we project the Arctic-mean erosion rate to roughly double by 2100 and very likely exceed its historical range of variability by mid-21st century. The sensitivity of erosion to warming also doubles, reaching 0.4-0.5 m year-1 oC-1 and 2.3-2.8 TgC year-1 oC-1 by the end of the century under moderate and high-emission scenarios. Our first 21st-century pan-Arctic coastal erosion rate projections should inform policy makers on coastal conservation and socioeconomic planning. Our organic carbon flux projections also lay out the path for future work to investigate the impact of Arctic coastal erosion on the changing Arctic Ocean, on its role as a global carbon sink, and on the permafrost-carbon feedback.
Post-Cross-Linked Molecular Imprinting with Functional Polymers as a Universal Building Block for Artificial Polymeric Receptors

A post-cross-linked molecular imprinting (PC-MI) technique utilizing a functional polymer (FP) with interacting and post-cross-linking groups was developed to create molecularly imprinted polymeric (MIP) receptors. Molecular recognition cavities were formed in the cross-linked polymer matrix by a posteriori cross-linking of the FP with template molecules using photoirradiation. These cavities could be easily tuned to recognize the target molecules by changing the template using a common FP as a universal building block. Thus, precise chiral recognition cavities were successfully created using PC-MI and optimizing the molar ratio of the functional groups between the FP and the target molecules, which suppressed the nonspecific binding of the off-target molecules. Furthermore, the morphology of the MIPs could be changed from bulk to particles. This study provides a facile and efficient synthetic route for MIPs with tailor-made properties. Thus, PC-MI can be utilized to create molecular recognition elements .
Linking Personal Experience to Global Concern: How Zoo Visits Affect Sustainability Behavior and Views of Climate Change

Globally, many species are threatened by habitat loss and are impacted by climate change due to human activities. According to the IUCN Red List, nearly 9000 animal species are now endangered or critically endangered. Yet, humans are largely ignorant to the impact they have on the environment due to lack of effective sustainability education. Currently, one of the most practical ways to connect with our global natural world is by visiting a local zoo. Zoos engage people with numerous species that they would otherwise never have the opportunity to see. Environmental education at zoos has come to address issues such as sustainability, personal green habits, and global climate change. Given the important role of zoos in sustainability education, there is a surprising lack of research on the topic. Due to its innovative nature, the research shown in this study acts as a pilot study set to gauge the impact of zoos on sustainability and climate change perspectives. This article investigates the extent to which adult survey respondents believe their current sustainability behaviors and their perceptions of global climate change have been influenced by their childhood visits to zoos and the environmental education topics learned during these visits. To investigate the long-term impact that zoos have on common sustainability behavior, a survey of 136 university students from various academic fields was conducted. The analysis found that 76% of respondents believe they act sustainably in their daily lives through actions such as sustainable shopping and recycling, with only 35% of individuals indicating that they learned their sustainable behaviors at zoos. Yet, 65% of respondents indicated that they believe zoos impact their overall level of environmental concern, primarily regarding knowledge of animal welfare and endangered species. Results suggest that individuals who are very concerned about climate change spent time at zoos, more than just one annual visit, and those zoo visits encourage global sustainability learning for the individual. This study suggests that zoos should expand visitor engagement through environmental education that encourages meaningful sustainability behavior and climate change knowledge.
Motherhood as a School Psychological Counselor during Coronavirus Disease Outbreak

The coronavirus disease (COVID-19), which affected the whole world and caused millions to be locked at their homes, brought many difficulties in domestic life. Especially, women are the leading group that has been affected the most negatively due to the workload during the days staying at home and experiencing the constraints of traditional roles. In this study, in which descriptive phenomenology analysis was used, the aim was to reveal how mothers working as psychological counselors in schools experienced motherhood during the days staying at home during the epidemic, and how their professional skills reflected on their role as mothers. In this study, in which the criterion sampling was used, semi-structured interviews were conducted with 15 mothers who are school psychological counselors and could not continue their work since schools shut down during the pandemic. The data were analyzed by Giorgi’s descriptive phenomenological method. Analysis results revealed six main themes that define the experiences of the participants: adaptation to the new order, parenting codes, introspection during the pandemic, distribution of parenting roles, professional reflections in motherhood, and complex motherhood experiences. It is believed that the results obtained from this study conducted with psychological counselor mothers will contribute to parenting practices and to the content of in service trainings for school psychological counselors.
Adapted water wave optimization for integrated bank customer service representative scheduling

In modern banks, establishing efficient and quality customer services plays a crucial role to achieve the business success. There are a large number of customers to be served daily; however, required service resources (in particular, customer service representatives) can be rather limited. Therefore, customer service representative scheduling is a challenging problem for bank managers. In the present paper, we focus on a customer service representative scheduling problem considering the stochastic customer arrival time and service duration to minimise the total cost including two parts: (i) the loss concerning the customer waiting and (ii) cost of providing service representatives. We formulate this scheduling problem as an integer programming problem and employ an adapted water wave optimization (WWO) algorithm to solve this problem efficiently. We adapt the propagation and refraction operators of WWO according to the solution space of this problem. The results of the conducted computational experiments demonstrate that the adapted WWO algorithm outperforms the considered state-of-the-art evolutionary algorithms in solving a set of test instances.
Sedentary Screen Time as a Coping Strategy of Distance Learning-induced Distress during COVID-19 Pandemic

During the COVID-19 pandemic, medical students might be vulnerable to excessive screen time exposure to cope with distance learning-induced distress. This study aimed to evaluate the distress and screen time before and after distance learning was initiated. Data were collected from 215 subjects. Statistical significance was accepted at P <0.05. The prevalence of distress among medical students was 25.61% and 27.06% before and after distance learning was executed, respectively. Academic-related stressor (ARS) was reported by 49.28% and 63.29% of students during the first and second surveys. The proportion of students with daily screen time ≥7 hours was 51.21% and 63.77% for the first and second surveys, respectively. ARS, interpersonal and intrapersonal-related stressor (IRS), social-related stressor (SRS), and average daily screen time significantly rose in 3-month-time ( P <0.0001, P =0.0014, P =0.0261, P =0.0022). There was a significant association between distress and screen time ( P=0.0313 ). ARS was the leading cause of distress. The majority of respondents had a daily screen time ≥7 hours. Both distress and screen time levels significantly increased as distance learning kept progressing. Keywords: COVID-19; distance learning; mental distress; medical students ; screen time .
Spatio-temporal prediction of soil deformation in bucket excavation using machine learning

This paper proposes a prediction model for three-dimensional spatio-temporal soil deformation in bucket excavation. The prediction model for soil deformation (PMSD) consists of two machine learning processes: the long short-term memory (LSTM) and convolutional autoencoder (Conv-AE). These processes use datasets obtained from an experimental apparatus for bucket excavation developed in this work. The apparatus equips multiple depth cameras that precisely capture time-series data of soil deformation in bucket excavation. The LSTM, an extension of a recurrent neural network, successively predicts three-dimensional soil deformation. The Conv-AE is incorporated to both ends of the LSTM in order to quasi-reversibly compress and reconstruct the datasets so that the computational burden of the LSTM is relaxed. Qualitative and quantitative evaluations of the PMSD confirm the feasibility of time-series prediction of three-dimensional soil deformation. The Conv-AE shows sufficient accuracy equivalent to the measurement accuracy of the depth camera. The prediction accuracy of the PMSD is about 10 mm in most of the cases. GRAPHICAL ABSTRACT
In Vitro Digestibility and Antioxidant Activity of Plant Protein Isolate and Milk Protein Concentrate Blends

The replacement of animal with plant proteins in human diets has been increasing in recent years. The impact of blending milk protein concentrate (MPC) with protein isolates from soy (SPI), rice (RPI) and pea (PPI) on the in vitro digestibility and antioxidant activity of the resultant blends was investigated. Different plant protein–MPC blends (i.e., SPI–MPC (25:75), RPI–MPC (50:50) and PPI–MPC (25:75)) were analyzed. The lowest protein digestibility corrected amino acid score (PDCAAS) was associated with RPI (0.70), while the blends had PDCAAS values above 1.00 demonstrating the high digestibility of the proteins in the blends studied. An in vitro simulated gastrointestinal digestion was carried out on the samples. The degree of hydrolysis and gel permeation high performance liquid chromatography profiles showed that the SPI–MPC blend was more extensively digested in the gastric phase compared with the two other blends, while the PPI–MPC and RPI–MPC blends were mainly digested during the intestinal phase. The SPI–MPC digested blend had the highest 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) radical scavenging activity having a half maximal effective concentration (EC50) of 0.10 ± 0.01 mg/mL. The findings show that blends of plant protein with MPC had higher in vitro digestibility and antioxidant activity compared to the individual plant protein isolates.
ASSOCIATIONS BETWEEN THE CHARACTERISTICS OF LARGE NATIONAL REGIONS, INDIVIDUAL ALCOHOL CONSUMPTION AND TOBACCO SMOKING: A SYSTEMATIC REVIEW PROTOCOL

Introduction: Tobacco smoking and hazardous alcohol consumption significantly contribute to the burden of diseases worldwide. Characteristics of the environment has been consistently shown to be associated with the patterns of tobacco smoking and alcohol consumption patterns. This evidence has been previously summarized on country- and neighbourhood-level reviews although the evidence on the associations on the regional level is still scarce. Aim: to present a protocol of the systematic review of available evidence on the associations between certain characteristics of large national regions and alcohol consumption and tobacco smoking. Methods: A systematic search of PubMed, Google Scholar, OpenGrey, CrossRef, and eLibrary) will be conducted to identify original studies with no date or language restrictions. Only studies with territorial characteristics as exposure variables and with tobacco smoking and alcohol consumption as the outcomes will be selected. The studies have no restrictions regarding participant characteristics, that is, gender, age, socioeconomic criteria, or health status. Titles, abstracts, and full text of articles retrieved from the search will be screened and read independently by two reviewers for eligibility. Articles selected for inclusion will be critically and independently appraised by two reviewers. The full-text of the selected studies will be assessed in detail, and findings and their illustrations will be extracted and aggregated. Any disagreements between the reviewers that may arise at any stage will be resolved through discussion, or mediated by a third reviewer. Systematic review registration number: PROSPEROCRD42021234874.
Identity Sharing and Adaptive Personalization Influencing Online Repurchases

ABSTRACT Adaptive personalization systems are becoming common in online retail. These systems use dynamically generated data and advanced data analytic techniques to infer customer preferences and recommend products or services best suited to a customer’s tastes. However, the adaptive personalization system’s ability to continue delivering valuable personalized content relies heavily on return customers’ willingness to continue sharing their identity information. By applying identity theory and the action-cognitive processing-decision model, cognitive and behavioral processes are theorized whereby customers who willingly share identity information favorably assess the value of product or service recommendations provided by adaptive personalization systems relative to their self-identity needs. The effects of willingness to share identity information and perceived personalization value on repurchase intention are examined. The results empirically demonstrate that a willingness to share identity information increases repurchase intention; further, this relationship is partially mediated by the perceived value of adaptive personalization.
Expression Analysis and Nuclear Import Study of Full-length Isoforms Importin α as 6x Histidin-tagged Fusion Protein on the Intracellular Localization of Recombinant HBV Core Protein

Isoform importin α molecules play a central role in the classical nuclear import pathway, that occurs through the nuclear pore complex (NPC) and typically requires a specific nuclear localization signal (NLS). In this study, it was investigated the role of isoforms importin α in the nuclear import of wild type recombinant hepatitis B virus core protein (WT rHBc), phosphorylated recombinant HBV core (rHBc) and recombinant HBV core without NLS by co-immunoprecipitation. Four recombinant full-length isoforms importin α as 6x histidin-tagged fusion protein were expressed and analysed from expression plasmid vectors Rch1, pHM 1969, pHM 1967 and pHM 1965. The results indicated that importin α-1, importin α-3, importin α-4 and importin α-5 can be expressed and isolated from E. coli transformed recombinant DNA plasmid as protein in size around 58-60 kDa. By the nuclear transport study shown that isoforms importin α are involved in the nuclear import of WT rHBc, phosphorylated rHBc and rHBc without NLS. It also indicated that they have an important role for nuclear transport of from cytoplasm into the nucleus. Keywords: NPC, NLS, importin α, importin β, isoforms importin α as 6x histidin-tagged fusion protein, WT rHBc, SV40 Tag, co-immunoprecipitation, westernblotting.
Site Development Knowledge for Entry-Level Construction Professionals: Academic Perceptions

Site development activities are crucial to construction projects, yet construction management (CM) programs typically focus instruction on building structures rather than the associated site development. Previous studies have evaluated key skills and topics being taught in CM programs yet these studies have failed to examine instruction as it relates specifically to site development. This study bridges the gap in research by evaluating the perceptions of CM academics regarding site development instruction. A survey was administered to CM faculty teaching in Associated Schools of Construction (ASC) affiliated programs in the United States. The survey included eighteen site development topics and was validated by four general contracting industry professionals and three site development industry professionals before distribution. Participants were asked to classify each of the topics within the six levels of the revised Bloom’s taxonomy. The survey was completed by 35 respondents representing all seven ASC regions in the United States. When aggregating results of all the site development topics, the majority of respondents felt that students should achieve the “understand” level (Level II) of cognition by the time they graduate. The highest ranking and lowest ranking topics are also identified along with recommendations based on the findings.
Anomaly Detection Approach to Identify Early Cases in a Pandemic using Chest X-rays

The current COVID-19 pandemic is now getting contained, albeit at the cost of more than 2.3 million human lives. A critical phase in any pandemic is the early detection of cases to develop preventive treatments and strategies. In the case of COVID-19, several studies have indicated that chest radiography images of the infected patients show characteristic abnormalities. However, at the onset of a given pandemic, such as COVID-19, there may not be sufficient data for the affected cases to train models for their robust detection. Hence, supervised classification is ill-posed for this problem because the time spent in collecting large amounts of data from infected persons could lead to the loss of human lives and delays in preventive interventions. Therefore, we formulate the problem of identifying early cases in a pandemic as an anomaly detection problem, in which the data for healthy patients is abundantly available, whereas no training data is present for the class of interest (COVID-19 in our case). To solve this problem, we present several unsupervised deep learning approaches, including convolutional and adversarially trained autoencoder. We tested two settings on a publicly available dataset (COVIDx) by training the model on chest X-rays from (i) only healthy adults, and (ii) healthy and other non-COVID-19 pneumonia, and detected COVID-19 as an anomaly. After performing 3-fold cross validation, we obtain a ROC-AUC of 0.765. These results are very encouraging and pave the way towards research for ensuring emergency preparedness in future pandemics, especially the ones that could be detected from chest X-rays.