Background: Recent cases of spinal cord infarction combined with cerebral infarction have demonstrated improved walking ability through pharmacological treatment and rehabilitation. However, studies on the efficacy of multidisciplinary approaches remain limited. Objectives: This study aimed to investigate rehabilitation strategies and establish a foundation for clinical practice, focusing on physical and occupational therapy for patients with spinal cord and cerebral infarctions. Design: A case study. Methods: A 70-year-old woman with combined spinal cord and cerebral infarction underwent 20 weeks of rehabilitation. Functional outcomes were assessed using Grip Strength, Manual Muscle Test (MMT), Trunk Impairment Scale (TIS), Manual Function Test (MFT), Berg Balance Scale (BBS), 10-Meter Walking Test (10MWT), and Korean Modified Barthel Index (K-MBI). Results: Over 20 weeks, Grip Strength improved to 6 kg (left) and 13 kg (right), MMT increased from 97 to 103 points, and TIS improved from 2 to 10 points. MFT scores increased to 18 (left) and 25 (right). BBS improved from 1 to 23 points, and the 10MWT time decreased to 19.84 seconds. K-MBI scores rose from 12 to 39 points. Conclusion: A multidisciplinary approach, including robotic therapy, significantly improved functional recovery, facilitating reintegration into daily life.
This study investigates the cognitive characteristics and transition flow of team mental models in virtual reality environments (VRE) compared to Zoom-based collaboration during fashion design problem-solving processes. Using the VRE platform Spatial.io as a case study, the study examines how virtual reality technologies influence the formation of shared mental models among collaborators. The objective is to identify key cognitive features that VREs offer to support problem-solving in multidisciplinary fashion design collaborations. The study employed a comparative experimental design, involving professionals from fashion design, marketing, and production. Participants completed the design concept generation tasks in both VRE and Zoom environments, all interactions were recorded and coded, with the analysis focusing on cognitive transitions, verbal dynamics, and collaborative behavior patterns across both environments. The results reveal that VRE fosters higher frequencies of environmental interaction (EI-EI), cognitive integration (CIM-CI), and planning to execution transitions in team interactions (PP-PIM), forming multidirectional feedback loops. These features enhanced dynamic adaptation to environmental stimuli. In contrast, Zoom-based collaboration relied heavily on linear verbal communication, with fewer cognitive transitions and limited structural feedback loops, thereby reducing efficiency in idea evaluation and execution in team interaction. The study highlights the potential of VREs to transform collaborative practices in fashion design by enabling immersive and multidimensional interactions, contributing to advancing digital collaboration strategies in creative industries, with implications for education and interdisciplinary innovation.
Multidisciplinary Design Optimization(MDO) method that considers principles in various fields affecting big scale structure and system design at the same time is used. Because most variables are connected many engineering phenomena under the classic optimized design method(all-in-one design approach), it is hard to judge the meaning of final design solution obtained, and there are cases where all variables converge before reaching the optimal design value in large-scale design problems with many variables. Collaborative Optimization (CO) method, the most advanced MDO approach, is used to efficiently solve these optimum problems, to efficiently analyze design problems involving numerous design variables and constraints and in which various engineering phenomena occur. However, the application of the MDO problem to CO introduces a number of numerical problems by destroying the numerical properties of the original optimal design problem. Therefore, this study researches one solution by listing the problems of CO after organizing various approaches of MDO.
The most important aspect of the imaging role for indeterminate bile duct stricture is to make a differential diagnosis on whether the stricture is highly likely to be malignant or benign. Compared to benign stricture, malignant stricture is longer, thicker, and has indistinct outer border and irregularity of the lumen in contrastenhanced computed tomography and magnetic resonance (MR). Also, in the contrast-enhanced portal phase, malignant stricture has a stronger enhancement than the liver parenchyma. There are studies to differentiate between malignant and benign stricture in diffusion weighted image, a functional MR image, but there remains controversial. Sometimes, malignant biliary stricture may be caused by bile duct invasion of gallbladder cancer, pancreatic cancer, hepatocellular carcinoma, biliary metastasis, and lymphoma. Among the potential causes of indeterminate biliary stricture, the characteristics of multifocal biliary stricture mainly suggest benign sclerosing cholangitis, and various external compression factors that cause biliary stricture can be differentiated by radiologic imaging. There are causes of biliary dilatation without obstructive lesion, radiologic diagnosis can be made by considering various characteristics.
In system design, it is not always possible that all decision makers can cooperate fully and thus avoid conflict. They each control a specified subset of design variables and seek to minimize their own cost functions subject to their individual constraints. However, a system management team makes every effort to coordinate multiple disciplines and overcome such noncooperative environment. Although full cooperation is difficult to achieve, noncooperation also should be avoided as possible. Our approach is to predict the results of their cooperation and generate approximate Pareto set for their multiple objectives. The Pareto set can be obtained according to the degree of one's conceding coupling variables in the other's favor. We employ approximation concept for modelling this coordination and the mutiobjective genetic algorithm for exploring the coupling variable space for obtaining an approximate Pareto set. The approximation management concept is also used for improving the accuracy of the Pareto set. The exploration for the coupling variable space is more efficient because of its smaller dimension than the design variable space. Also, our approach doesn't force the disciplines to change their own way of running analysis and synthesis tools. Since the decision making process is not sequential, the required time can be reduced comparing to the existing multidisciplinary design optimization. This approach is applied to some mathematical examples and structural optimization problems.
The cosmetic industry has been rapidly expanding over the last decades. The industry itself generates about $230 billion each year and is consumed daily by 90% of female consumers. Despite its weight in the economy, consumer research has largely neglected the specificity of beauty products and consumption. The first aim of this paper is thus to offer an integrative conceptual framework to better understand beauty consumption from a consumer psychology point of view, incorporating findings from evolutionary, cognitive and cultural psychology. The second aim is to encourage consumer research on the topic by offering a research agenda taking into consideration different dimensions of beauty perception. This working paper is based on a critical and systematic literature review conducted on the topic of beauty in cognitive, evolutionary and cultural psychology. Whilst the beauty industry is booming, a gap exists in the consumer research literature in terms of understanding the applications of traditional evolutionary, cognitive and crosscultural research on the topic. This working paper introduces a framework and agenda to understand, frame, and study beauty in consumer research. On the basis of the literature reviewed, we propose a model with two decision-making systems related to beautyrelated cognition and behaviors: an impulsive decision-making system and a socially constructed decision-making system. In the impulsive decision-making system, sexual selection and cognitive mechanisms function simultaneously. We expect impulsive buying behavior to occur when consumers are exposed to highly aesthetic packaging of beauty products. In the socially constructed decision-making system, consumers choose certain brands depending on the brand image being aligned with the consumer’s cultural perception of beauty. We argue that decision-making behavior is reflective, as opposed to impulsive. Finally, we argue that both systems are mutually reinforcing and need to be better integrated into further studies looking at beauty consumption.
전 세계적으로 기후변화와 저탄소 소비행태를 향한 움직임이 일어남에 따라 이에 대한 대처가 요구되고 있으며, 국제적인 유가상승은 그린카에 대한 소비자들의 니즈를 촉발시키고 있다. 본 논문은 그린카 산업 플랫폼 구축 정책과 기업전략을 도출하기 위한 선행 연구로서 이를 위해 정책프레임 및 실증분석, 개념적/수리적 모델링, 시스템 다이내믹스, ABM 등의 다양한 방법론을 사용하여 다각적으로 접근, 통합하여 플랫폼 관점에서의 학제적 연구 프레임워크를 제시하고자 한다. 먼저 그린카 사례 분석을 위한 산업플랫폼 분석 프레임워크를 도출하고, 필요한 구성 요소들을 제시하였으며 계량경제학 모형을 적용하여 그린 플랫폼(양면시장)에 관련된 기본 모델을 수립하였다. 또한 동태적인 관점에서의 분석을 위해 시스템 다이내믹스 모형을 그린카 환경에 접목하여, 특정 그린카 산업분석에 적용할 수 있는 시스템 다이내믹스 분석 모델을 수립하였다. 마지막으로 보다 미시적 관점에서 한국의 하이브리드 자동차 시장의 활성화 방안에 대하여 ABM을 이용하여 개별 소비자 관점에서 연구하였다. 이를 기반으로 현 한국시장에서 실행 중 혹은 실행 예정인 하이브리드 자동차 정책에 대한 분석 방안을 제시하였다.
By means of the model competition, this research analyzed the factor of patient management, the factor of policy support, and the factor of medical treatment system. Concretely, the factor of policy support forms a positive effects on the factor of medical treatment system. Practically, well-established healthcare policy provide and facilitate the effective medical treatment system. of the hospital. And, in the effective medical treatment system, hospitals try to develop the patient management of the chronic disease. From the empirical research, this paper concluded that the factor of medical treatment system. mediated by the factor of policy support. Also, the factor of medical treatment system promotes the development of patient management in the chronic disease.
다분야 통합 시스템의 설계문제는 다량의 설계변수와 구속조건으로 구성되며 다수의 공학적 현상으로 연관되어 있다. 다분야 통합 최적설계 문제를 효과적으로 다루기 위해서는 다양한 해석분야의 공학적 설계원리를 동시에 고려하여 균형 있고 유기적인 방법으로 최적의 설계를 결정하는 체계적인 설계자동화기술이 요구된다. 다분야 통합 설계문제를 위한 효율적인 설계방법론으로 분리기반 최적화 기법이 적용되는데 이 방법은 한 단위의 대규모 설계문제를 여러 개의 하부시스템으로 분리하여 독립적으로 최적화를 수행하고 각 하부 시스템으로부터의 설계해 사이의 중재 및 통합화를 거쳐 최종적으로 수렴된 최적설계를 찾는 방법이다. 본 논문에서는 분리기반 최적화기법을 다분야 통합최적 설계문제에 적용하는데 필요한 시스템분리기법을 유전알고리즘 및 다층 역전 파 신경회로망을 이용하여 정립하였다. 시스템분리기법을 검증하기 위해 최근 미국 Boeing사에서 개발중인 고속 민간항공기인 HSCT의 시뮬레이션기반 설계문제를 이용하였다. 대규모 설계시스템의 분리결과는 전체 설계문제의 특성을 파악하기 위한 자료로 활용되며 향후, 분리기반 최적화과정에서 최종적으로 통합된 최적설계를 탐색하는데 필요한 기반구조를 제공한다.