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The purpose of this study is to discuss the principles and factors that influence the site selection of emergency medical facilities for public health emergencies. This paper discusses the selection of the best facilities from the available facilities, proposes the capacity of new facilities, presents a logistic regression model and establishes a site selection model for emergency medical facilities for public health emergencies in megacities.

Using Guangzhou City as the research object, seven alternative facility points and the points' capacities were preset. Nine demand points were determined, and two facility locations were selected using genetic algorithms (GAs) in MATLAB for programing simulation and operational analysis.

Comparing the results of the improved GA, the results show that the improved model has fewer evolutionary generations and a faster operation speed, and that the model outperforms the traditional P-center model. The GA provides a theoretical foundation for determining the construction location of emergency medical facilities in megacities in the event of a public health emergency.

First, in this case study, there is no scientific assessment of the establishment of the capacity of the facility point, but that is a subjective method based on the assumption of the capacity of the surrounding existing hospitals. Second, because this is a theoretical analysis, the model developed in this study does not consider the actual driving speed and driving distance, but the speed of the unified average driving distance and the driving distance to take the average of multiple distances.

The results show that the method increases the selection space of decision-makers, provides them with stable technical support, helps them quickly determine the location of emergency medical facilities to respond to disaster relief work and provides better action plans for decision makers.

The results show that the algorithm performs well, which verifies the applicability of this model. When the solution results of the improved GA are compared, the results show that the improved model has fewer evolutionary generations, faster operation speed and better model than the intermediate model GA. This model can more successfully find the optimal location decision scheme, making that more suitable for the location problem of megacities in the case of public health emergencies.

The research findings provide a theoretical and decision-making basis for the location of government emergency medical facilities, as well as guidance for enterprises constructing emergency medical facilities.

The purpose of this paper is to generate facsimiled rapid prototyping (RP) models for medical analysis that demands an answer about the accuracy of medical models.

The RP technology for anatomical biomodeling is the accurate RP procedure of milling and joining, a method that is used to produce high accurate functional prototypes. To fabricate medical prototypes with RP, there is a need to get appropriate data information. Along that process, image data will be taken by computer‐tomography (CT) images as data basis. The key process is to generate a digital three‐dimensional (3D) model that represents the original object as best as possible. To be able to make a statement about the accuracy of such a model the necessary parameters run along a CT scan are of interest.

A case study using a generated test model is presented in order to show the process accuracy in relation to the chosen scan parameters. The quality of editing CT images for a 3D‐reconstruction as a necessary pre‐process for RP is, to an important degree, based on the used scan parameters.

This paper represents a cutting‐edge analysis that gives answers about the constrictive accuracy that is achievable for medical RP models.

This study aims to provide an overview of rapid prototyping (RP) and shows the potential of this technology in the field of medicine as reported in various journals and proceedings. This review article also reports three case studies from open literature where RP and associated technology have been successfully implemented in the medical field.

Key publications from the past two decades have been reviewed.

This study concludes that use of RP-built medical model facilitates the three-dimensional visualization of anatomical part, improves the quality of preoperative planning and assists in the selection of optimal surgical approach and prosthetic implants. Additionally, this technology makes the previously manual operations much faster, accurate and cheaper. The outcome based on literature review and three case studies strongly suggests that RP technology might become part of a standard protocol in the medical sector in the near future.

The article is beneficial to study the influence of RP and associated technology in the field of medicine.

The purpose of this paper is to unpack the tenuous relationship between medical sociology and disability studies, particularly as it relates to the work of Irving Zola.

Many attribute the division between these disciplines to their starkly different and oft competing approaches to disability; however, I argue that a closer examination reveals a number of commonalities between the two.

I use Irving K. Zola’s extensive body of scholarship to demonstrate the connections between these divergent approaches to disability, and imagine what his legacy has to offer to the advancement of a diverse sociology of disability.

Neither focus is more correct than the other, as considering these bodies of work together presents a number of opportunities to advance a more comprehensive sociological theory – not just of disability – but of ableism and its intersections with other forms of oppression as well.

The purpose of this paper is to analyze the influencing factors of patients’ financial burden through a case study of hospital on public‒private partnerships (PPP) model (Chaonan Minsheng Hospital of Guangdong Province) and provide some useful information to policymakers for better development of hospitals on PPP model.

There are total six indicators that are defined as patients’ financial burden, basing on the policy of “indicators of medical quality management and control on the third level large general hospital (2011 edition),” issued by Chinese Government. In total, 23 potentially influencing factors of patients’ financial burden for hospital on PPP model were chosen from the above policy. The five-year (2007‒2011) data for the above 29 indicators come from statistic department of hospital on PPP model. Grey relational analysis (GRA) was applied to analyze the influencing factors of patients’ financial burden for hospital on PPP model.

A clear rank of influencing factors of patients’ financial burden is obtained and suggestions are provided from results of GRA, which provide reference for policymakers of hospital on PPP model. The five main influencing factors of patients’ financial burden for hospital on PPP model, in sequence, are rescuing critical ill patients on emergency, rescuing critical ill inpatients, inpatient bed occupancy rate, working days per bed and medical building area.

The study on the influencing factors of patients’ financial burden for hospital on PPP model not only provides decision-making for policymaker of hospital and controlling of medical expenditure but also contributes to release patients’ financial burden for hospitals on PPP model.

Rapid prototype models are directly integrated into non‐engineering applications such as medicine. Medical models are used to plan complex procedures prior to surgery with potential to optimise patient treatment in the operating theatre. This paper presents results following a 12 month National Health Service Executive research project to assess the feasibility of using rapid prototype medical models. A total of 16 medical models were created. Nine anatomical sites were reconstructed from patient data acquired from five London hospitals. The purpose of the models is described and the commissioning surgeons as part of a questionnaire assessed their usefulness. Future developments are discussed and conclusions about the use of medical models are made.

This chapter reviews qualitative research on parenting children with disabilities published over the last 50 years to explore whether shifts in academic discourse and changes in professional training have affected research on parenting and/or the experiences of parents who are the subject of such research.

An extensive literature search was conducted, and 78 peer-reviewed, qualitative studies on the experience of parenting a child with a disability were included in the sample. Themes were extracted from the reviewed literature and compared across decades.

The findings of the present review suggest that some aspects of the parenting experience have changed very little. In particular, parents continue to experience negative reactions such as stress and anomie, especially early in their children’s lives, and socially imposed barriers such as unhelpful professionals, and a lack of needed services continue to create problems and inspire an entrepreneurial response. In addition, stigmatizing encounters with others continue to be a common occurrence. In contrast to earlier decades, studies conducted in more recent years have begun to use the social model of disability as an analytic frame and also increasingly report that parents are questioning and challenging the concept of “normal” itself.

Additional improvements are needed in professional education and services to reduce the negative reactions experienced by parents of children with disabilities.

The findings of this meta-analysis can serve as a guide to future research on parenting children with disabilities.

Blacks are more likely than white, in the United States, to experience a stillbirth. In this study, I use a structural perspective of race to create a heuristic model that combines medical and social epidemiological explanations to understand the racial disparity in stillbirths. Using data from the National Maternal and Infant Health Survey 1988 (NMIHS), I examine whether racial disparities in stillbirths can be explained by medical and social epidemiological variables. My findings show that medical and social epidemiological explanations do little to reduce the racial disparity. However, many medical model variables were important predictors of stillbirths including multiple gestations, being overweight, obesity, vaginal bleeding, advanced maternal age, and parity.

The purpose of this study is to identify, analyse and model the post-processing barriers of 3D-printed medical models (3DPMM) printed by fused deposition modelling to overcome these barriers for improved operational efficiency in the Indian context.

The methodology used interpretive structural modelling (ISM), cross-impact matrix multiplication applied to classification (MICMAC) analysis and decision-making trial and evaluation laboratory (DEMATEL) to understand the hierarchical and contextual relations among the barriers of the post-processing.

A total of 11 post-processing barriers were identified in this study using ISM, literature review and experts’ input. The MICMAC analysis identified support material removal, surface finishing, cleaning, inspection and issues with quality consistency as significant driving barriers for post-processing. MICMAC also identified linkage barriers as well as dependent barriers. The ISM digraph model was developed using a final reachability matrix, which would help practitioners specifically tackle post-processing barriers. Further, the DEMATEL method allows practitioners to emphasize the causal effects of post-processing barriers and guides them in overcoming these barriers.

There may have been a few post-processing barriers that were overlooked by the Indian experts, which might have been important for other country’s perspective.

The presented ISM model and DEMATEL provide directions for operation managers in planning operational strategies for overcoming post-processing issues in the medical 3D-printing industry. Also, managers may formulate operational strategies based on the driving and dependence power of post-processing barriers as well as the causal effects relationships of the barriers.

This study contributes to identifying, analyzing and modelling the post-processing barriers of 3DPMM through a combined ISM and DEMATEL methodology, which has not yet been reviewed. This study also contributes to decision makers developing suitable strategies to overcome the post-processing barriers for improved operational efficiency.