Spatial Optimization of Urban Cellular Automata Model

Although cellular automata (CA) offer a modelling framework and set of techniques for modelling the dynamic processes of urban growth, determining the optimal value of weights or parameters for elements or factors of urban CA models is challenging. This chapter demonstrates the implementation of a calibration module in a fuzzy cellular urban growth model (FCUGM) for optimizing the weights and parameters of an urban CA model using three types of algorithms: (i) genetic algorithm (GA), (ii) parallel simulated annealing (PSA) and (iii) expert knowledge (EK). It was found that the GA followed by EK produced better and more accurate and consistent results compared with PSA. This suggests that the GA was able to some extent to understand the urban growth process and the underlying relationship between input factors in a way similar to human experts. It also suggests that the two algorithms (GA and EK) have similar agreement about the efficiency of scenarios in terms of modelling urban growth. In contrast, the results of the PSA do not show results corresponding to those of the GA or EK. This suggests that the complexity of the urban process is beyond the algorithm’s capability or could be due to being trapped in local optima. With this satisfactory calibration of the FCUGM for the urban growth of Riyadh city in Saudi Arabia by using CALIB-FCUGM, these calibrated parameters can be passed into the SIM-FCUGM to simulate the spatial patterns of urban growth of Riyadh

Spatial Assessment of COVID-19 First-Wave Mortality Risk in the Global South

The coronavirus disease (COVID-19) that appeared in 2019 gave rise to a major global health crisis that is still topping global health, socioeconomic, and intervention program agendas. Although the outbreak of COVID-19 has had substantial and devastating impacts on developed countries, the countries of the Global South share a higher proportion of the epidemic’s effects as shown particularly in morbidity and mortality rates in low-income countries. Modeling the effects of underlying factors and disease mortality is essential to plan effective control strategies for disease transmission and risks. The relationship between COVID-19 mortality rates and sociodemographic and health determinants can highlight various epidemic fatality risks. In this research, geographic information systems (GIS) and a multilayer perceptron (MLP) artificial neural network (ANN) were adopted to model and examine variations in COVID-19 mortality rates in the Global South. The model’s performance was tested using statistical measures of mean square error (MSE), root mean square error (RMSE), mean bias error (MBE), and the coefficient of determination (R2). The findings indicated that the most important variables in explaining spatial mortality rate variations were the size of the elderly (sixty-five and older) population, accessibility to handwashing facilities, and hospital beds per 1,000 population. Mapping the explanatory variables and estimated mortality rates and determining the importance of each variable in explaining the spatial variation of COVID-19 death rates across countries of the Global South can shed light on how public health care and demographic structures can offer policymakers invaluable guidelines to planning effective intervention strategies.Open Access funding was provided by the Qatar National Library

Analytical and numerical investigation of beam-spring systems with varying stiffness: a comparison of consistent and lumped mass matrices considerations

This study examined the vibration behavior of a beam with linear spring attachments using finite element analysis. It aims to determine the natural frequency with both consistent/coupled mass and lumped mass matrices. The natural frequencies and corresponding mode shapes were correctly determined which formed the basis of any further noise vibration and severity calculations and impact or crash analysis. In order to obtain eigenfrequencies subject to the attached spring, the characteristic equation was obtained by eigenfunctions expansion whose roots were extracted using the root-finding technique. The finite element method by coupled and lumped mass matrices was then used to determine complete mode shapes against various eigenfrequencies. The mode shapes were then analyzed subject to supports with varying stiffness thereby comparing the analytical and numerical results in case of consistent and lumped masses matrices so as to demonstrate how the present analysis could prove more valuable in mathematical and engineering contexts. Utilizing a consistent mass matrix significantly enhanced accuracy compared to a lumped mass matrix, thereby validating the preference for the former, even with a limited number of beam elements. The results indicated that substantial deflection occurred at the beam's endpoints, supporting the dynamic behavior of the spring-beam system

Factors Associated with Patient Satisfaction in Outpatient Department

Background: Patient satisfaction is an important and direct indicator of quality of health care which is essential for providers to fill their gaps. Outpatient care is made up of medical procedures, tests, and services that can be provided to the patient in a setting that doesn’t involve an overnight hospital stay. When patients visit health care facilities, they express a clear desire for high-quality ser¬vices. The aim of this study is to investigate factors associated with patient satisfaction in adult outpatient department. Methods: Cross-sectional study design with a total sample of 200 patients was conducted from Auguest to October 2022. All patients who visited the outpatient departments of the chosen health centers were consid-ered the source population, and all patients who visited the outpatient departments during the study period were the study population. Data were collected structured validated questionnaire. Data analysis was conducted with SPSS version 20 to identify predictor variables, applying bivari¬ate and multivariate logistic regression analysis to determine variables that most signifi¬cantly predicted the outcome variable of the level of patient-satisfaction at 5% level of significance and 95% confidence interval. Results: There were 200 participants in the study. the present study display the relation between participants’ sociodemographic characteristics and total level of satisfaction. There is highly statistical significant with age, gender, educational level and monthly income. While no statistical significant with social status. Also,  the outpatient service characteristics and perceptions of study participants. Nearly (45%) of respondents reported the outpatient department they visited was convenient to ask questions. Related to privecy (88%) of them reported that their privacy at the out-patient department was maintained. Inrelation to dialogue with outpatient service providers, the study participants declared to have had a good dialogue with outpatient service providers were (65%). Regarding, politeness (73%) of respondents described outpatient service providers were polite during service provision. The overall patient satisfaction rate of the study were (22%) very satisfied, (35%) satisfied, (21%) neutral, (15%) dissatisfied and (7%) very dissatisfied. Conclusion: The study\u27s results revealed that the outpatient service characteristics and perceptions of study participants were low of respondents with convenient to ask questions. While, high percentage reported that their privacy at the out-patient department was maintained. Also, Related to dialogue with outpatient service providers, the study participants declared to have had a good dialogue with outpatient service providers. Related to politeness of outpatient service providers who served the respondents were high. The overall patient satisfaction rate of the study were good

Structured Acyclic Nets

The concept of structured occurrence nets is an extension of that of occurrence nets which are directed acyclic graphs that represent causality and concurrency information concerning a single execution of a distributed system. The formalism of structured occurrence nets has been introduced to facilitate the portrayal and analysis of the behaviours, and in particular failures, of complex evolving systems. Such systems are composed of a large number of sub-systems which may proceed concurrently and interact with each other and with the external environment while their behaviour is subject to modification by other systems. The purpose of this paper is to provide an extension of structured occurrence nets to include models built up of acyclic nets rather than occurrence nets

Role of Stem Cells in Orthopaedic Surgery: Theoretical Survey

This study aims at analyzing the Stem cell application is a burgeoning field of medicine that is likely to influence the future of orthopaedic surgery. Stem cells are associated with great promise and great controversy. For the orthopaedic surgeon, stem cells may change the way that orthopaedic surgery is practiced and the overall approach of the treatment of musculoskeletal disease. Stem cells may change the field of orthopaedics from a field dominated by surgical replacements and reconstructions to a field of regeneration and prevention. This review will introduce the basic concepts of stem cells pertinent to the orthopaedic surgeon and proceed with a more in depth discussion of current developments in the study of stem cells in orthopaedic surgery. Keywords: Stem cell, orthopaedic, surgery

Mathematical analysis and numerical simulations of the piecewise dynamics model of Malaria transmission: A case study in Yemen

This study presents a mathematical model capturing Malaria transmission dynamics in Yemen, incorporating a social hierarchy structure. Piecewise Caputo-Fabrizio derivatives are utilized to effectively capture intricate dynamics, discontinuities, and different behaviors. Statistical data from 2000 to 2021 is collected and analyzed, providing predictions for Malaria cases in Yemen from 2022 to 2024 using Eviews and Autoregressive Integrated Moving Average models. The model investigates the crossover effect by dividing the study interval into two subintervals, establishing existence, uniqueness, positivity, and boundedness of solutions through fixed-point techniques and fractional-order properties of the Laplace transformation. The basic reproduction number is computed using a next-generation technique, and numerical solutions are obtained using the Adams-Bashforth method. The results are comprehensively discussed through graphs. The obtained results can help us to better control and predict the spread of the disease

Heat Stroke in Emergency Department: Diagnosis and Management

Background: Heat stroke is a severe health concern with the potential for multi-organ failure, necessitating rapid and effective management. With rising global temperatures, there is increasing concern regarding the vulnerability of populations in high-heat areas, notably in Saudi Arabia, especially during the annual Hajj pilgrimage. Objective: This paper aims to review the epidemiology, evaluation and management techniques of heat stroke, emphasizing the situation during Hajj pilgrimages in Saudi Arabia, and to outline the best practices for emergency management. Methodology: A comprehensive review of literature and studies related to heat stroke, both globally and specific to Saudi Arabia, was undertaken. An in-depth analysis of emergency management, including initial assessment, cooling methods, organ support, medication, and prevention strategies, was conducted. Results: Heat stroke remains a significant cause of emergency department visits, with specific groups, such as men and the elderly, being more susceptible. During the Hajj in 2016, 267 patients were diagnosed with heat-related illnesses, with heatstroke accounting for 29% of these cases. With the threat of global warming, studies indicate a potential tenfold increase in heat stroke risk with a 2°C rise in temperatures. Swift and comprehensive cooling is pivotal for recovery. Management emphasizes rapid recognition, assessment, and varied cooling methods, along with targeted treatments for organ dysfunctions. Prevention strategies play a vital role, given the higher efficacy and practicality over treating organ dysfunctions. Conclusion: Heat stroke is a pressing health challenge, particularly in high-risk environments like Saudi Arabia during the Hajj pilgrimage. While effective emergency management protocols exist, an emphasis on prevention is crucial. It is imperative to incorporate a comprehensive approach to address both the immediate threat and long-term risks of heat stroke, especially with the looming challenge of global warming