Abstract:Aim: This study aimed to evaluate the influence of shifting from traditional office-based employment to remote work from home on the prevalence and severity of musculoskeletal illnesses at the time of covid-19 outbreak among the working population. This research was conducted out in the Eastern Province of the Kingdom of Saudi Arabia. Methods: An online questionnaire survey was conducted, by distribution of Nordic Musculoskeletal Questionnaire in 980 participants. Subsequently, a thorough investigation of descriptive and inferential statistics was done, by focusing on two specific constituents. The first one relates to the existence of pain in specific regions of the body, while the second factor refers to the intensity of pain in each individual region as well as the cumulative pain experienced throughout all parts of the body. Results: Significant differences were observed between male and female employee with respect to the two variables. Furthermore, the regression models indicate that many demographic characteristics, such as age, sex, employment sector, working hours, changes in working hours, daily activity, medical visits, and frequency of exercise, do not have the same impact on the presence and intensity of pain. Conclusion: The COVID-19 pandemic has significantly influenced human behavior and work practices, resulting in significant implications for Occupational Safety and Health. These effects are illustrated by the increased sensation of pain experienced in different anatomical regions, which has led to the necessity for the establishment of medical and occupational initiatives specialized for individuals performing remote work.
Abstract:This article analyses studies in the field of digital public administration from a bibliometric perspective. Bibliometrics is a method that evaluates scientific developments by performing statistical and mathematical analyses on scientific publications. In the study, publications on digital public administration were scanned using Web of Science (WoS) scientific databases and bibliometric analyses were performed. As a result of the analyses, important topics in the field of digital public administration, the most cited publications, keywords and researchers in the field were identified. The article aims to contribute to the literature by presenting a bibliometric perspective on research in the field of digital public administration and to provide a basis for future studies. In this context, 1335 publications were identified and analysed with various restrictions. It is expected that the results of the study will serve as a compass for future studies in the field of digital public administration, especially as they aim to identify locomotive topics and niche areas.
Abstract:Hybridization of oligonucleotides is effectively used to manipulate transcription level of cells. Here we introduce the method of hybridizing complementary single strand DNA (cDNA) to the RNA strands. We call this namely, Anti-Sense Agonist DNA Application to RNA Strands (ASADARS) method. The purpose of our study is to determine the effects of hybridization of single strand DNA oligomer to RNA transcript, to show specific or holistic interference. It is similar to siRNA, but DNA oligomers are replaced for interference instead of small RNA molecules. Identical to the initial protocol in RT-PCR, Hek293 cells were lysed and their RNA transcripts and were separated to synthesize cDNA. The RNA was removed, to leave only complementary ‘single strand DNA’ oligomers. These DNA oligomers were then transfected back to 293 cells. For Controls, SH-Sy5y cDNA, 293 RNA, SH-Sy5y RNA, reagent and blank controls were treated. After 24 hours, the total RNA was decreased but the overall average microarray gene expression was up-regulated in 1.4 fold, in 30,926 genes. The single strand cDNA treatment, in specific gene target condition or holistic miscellaneous gene target was both evaluated. On the oligonucleotide treatment, either RNA or DNA delayed proliferation. Total protein level was not significantly altered. With this approach, primarily, the stability issues of siRNAs can be resolved by replacing it to DNA, which shows long term DNA-RNA hybridization. Cellular homeostasis and RNA compensation response is further postulated as a response of prolonged gene expression inhibitory or regulatory effects.
Abstract:This study was conducted to determine whether remote working causes an increase in job insecurity in Turkey. Qualitative and quantitative research methods were used in the study. In this study, a mixed-method approach, combining qualitative and quantitative research methods, was adopted. The quantitative method was used to measure the perception of job security among remote workers. To enhance the reliability of the findings, qualitative methods were also utilized. In the quantitative method, 235 people working in the private sector who had experience in teleworking were selected as a sample. Data were collected by the questionnaire method. Structural equation modeling was used to analyze the data. The qualitative method selected twenty people working as experts and managers who have experienced remote working as a sample. The content analysis method was used to analyze the data. Organizations that want to gain a competitive advantage should consider flexible working models and the concept of job security and implement the assured flexibility model. In this direction, they should implement the necessary human resources policies to ensure employees have positive perceptions of their job security.
Abstract:This paper investigates the mechanical behavior and buckling failure of SUS304 stainless steel oval square tubes with four different long/short axis ratios (1.5, 2.0, 2.5, and 3.0) under cyclic bending. The wall thickness is 0.7 mm for all oval square tubes, and cyclic bending loads are applied until buckling failure occurs. The moment-curvature relationships for all SUS304 stainless steel oval rectangular tubes eventually forms a stable elastic-plastic loop for every long/short axis ratio. Additionally, the relationships between short axis variation (the change in the length of the short axis divided by the original length of the short axis) and curvature demonstrate serrations, and a growth pattern as cycles progress. Moreover, a larger long/short axis ratio corresponds to a greater short axis variation. Regarding the curvature-number of cycles required to ignite buckling relationships, it can be observed that the four long/short axis ratios correspond to four straight lines when plotted on double logarithmic coordinates. Lastly, this study proposes theoretical equations to describe the aforementioned relationships. The theoretical analysis is compared with experimental data, revealing a close alignment between the two approaches. This indicates that the theory can reasonably describe the experimental results.
Abstract:This paper explores the intersection between gamification and mathematics education, aiming to assess its effectiveness in enhancing mathematics skills. Given the pervasive influence of digital technology in education, gamification emerges as a promising method to captivate young learners in mathematical concepts within a lively and interactive learning environment. Specific research on applying gamification across primary mathematics education. The study conducts a review of existing literature on gamification techniques and their impact on mathematics education, emphasizing both the potential advantages and obstacles associated with integrating gaming elements. With various gamification strategies, including game-based learning, rewards systems, and interactive platforms, this study aims to provide insights into the effectiveness and impact of gamified approaches on mathematical proficiency, student engagement, and overall learning outcomes. Moreover, this paper also explores the role of technology, design elements, and psychological factors in shaping the gamified learning environment and influencing student attitudes toward mathematics. Additionally, it investigates the roles of intrinsic and extrinsic motivation in fostering engagement and positive learning outcomes among students. By investigating the potential of gamification in education, this study contributes to ongoing discussions on innovative pedagogical approaches aimed at improving mathematics proficiency and nurturing a lifelong love for learning among students.
Abstract:Aspiration pneumonia is a type of lung infection that occurs when food, liquid, saliva, or vomit is inhaled into the lungs instead of being swallowed into the esophagus. This condition is more common in people with difficulty swallowing, a weakened immune system, or compromised gag reflexes. When foreign materials enter the lungs, they can introduce bacteria, viruses, or fungi that lead to inflammation and infection. The severity of aspiration pneumonia depends on the type of material aspirated, the volume, and the individual's overall health. Early diagnosis and treatment are crucial for managing symptoms and preventing complications like respiratory failure or abscess formation. Understanding the risk factors, symptoms, and potential complications is key to effective prevention and management of this condition.
Abstract:The aim of these investigations is to provide a stochastic deep neural network optimization procedure for the numerical solutions of the fractional order influenza disease system. The fractional order form of the derivatives to solve the nonlinear models provide more realistic solutions as compared to integer order derivatives. The mathematical system based on the influenza model is categorized into population of birds (susceptible, infected) and humans (susceptible, infected with avian and mutant strains, recovered after avian and mutant strains). A stochastic platform is constructed using the feed-forward deep neural network with two hidden layers having 20 and 32 numbers of neurons, sigmoid activation function in both layers and optimization is performed through a competent Bayesian regularization for solving the model. A dataset is created using the traditional explicit Runge-Kutta solver, which is performed to lessen the mean square error by separating the data into training as 70%, while 15% for both authentication and testing. The accuracy is observed through different statistical operators including regression and state transitions, while correctness is achieved based on the results overlapping and minor absolute error.
Abstract:Space science has been developed through past and current missions of the International Space Station (ISS) and Tiangong Space Station (TSS) in low Earth orbit and on the lunar surface. Numerous missions have used animals on test flights to better understand the physiological dangers of space flight for humans. A contemporary focus of space exploration is long-duration crewed travel to establish a Moon station and reach Mars. The astrotechnology of the human-less spaceflights (USA, Russia, ESA, UAE, China, and India) launched in 1965 (Mariner 4), has advanced enough to support the progressive colonisation of the Red Planet with investigating equipment (Perseverance rover, Ingenuity helicopter, Hope orbiter, Tianwen-1 orbiter, and Chinese lander-rover). Are humans, then, ready to explore for Mars soon? What are major hazards that still need to be solved? Can animals play a novel role for humans in deep space travel? While the five factors of altered gravity, radiation, confinement (isolation), distance from Earth, and unknown hostile environments have been analysed in the scientific field of space medicine, this paper explores the biological ripple effects of animal astronauts to mitigate risks for human astronauts. The countermeasures of the psychological well-being and space community security are determined considering the potential role of animals in reducing the emergence rate of behavioural health and performance decrements (loneliness, mental and emotional strain, fear, lethargy, lack of enthusiasm, and violence). This paper argues a new hypothesis that if the engineering aspects of animal (dog) support does not reduce the scientific capabilities, the cognitive policy of a �human-pet companionship� apart from the historically traditional pattern of �experimental animal� can benefit the mental, social, and physical resilience of the Martian astronauts during the return mission (2.5�3 years).
Abstract:Hourly-based improved prediction of present air quality state (PM10, PM2.5, and NO2) with 15 input independent variables (3 hours\' earlier PM, gas and meteorological data of a Korean city affected by 2 days\' earlier PM and gas data of Beijing city in the Yellow Dust route was performed using Machine Learning (ANN-Tanh) and Multivariate Regression techniques. ANN-tanh model of multilayer perception (MLP) structure with a feed-forward input data and backpropagation training process for error calculation with 15 nodes in a single hidden layer was adopted to calculate present urban air quality. Root mean square error (RMSE) and the coefficient of determination (R2; Pearson R) evaluated the performance ability of the model between the predicted and measured values before, during, and after the Yellow Sand event at the Korean coastal city. Multivariate regression technique was also used to predict the urban air quality with the same input data. The prediction accuracies of the two models were compared before, during, and after the Yellow Dust period and regardless of the event, Pearson R correlation coefficients using the ANN-tanh model (multivariate regression model) were quite high as 0.935 (0.961), 0.943 (0.948) and 0. 947 (0.920) for PM10, 0.942 (0.909), 0.969 (0.977) and 0.938 (0.947) for PM2.5, and 0.925 (0.860), 0.853 (0.875) and 0.886 (0.903) for NO2, respectively. Their prediction ability overall was quite excellent, showing a slightly higher R in the ANN-Tanh. Their hourly distributions of predicted and measured values of 3 outputs were drawn to compare their model performance.