From Digital Human Modeling to Human Digital Twin: Framework and Perspectives in Human Factors

The human digital twin(HDT)emerges as a promising human-centric technology in Industry 5.0,but challenges remain in human modeling and simulation.Digital human modeling(DHM)provides solutions for modeling and simulating human physical and cognitive aspects to support ergonomic analysis.However,it has limitations in real-time data usage,personalized services,and timely interaction.The emerging HDT concept offers new possibilities by integrating multi-source data and artificial intelligence for continuous monitoring and assessment.Hence,this paper reviews the evolution from DHM to HDT and proposes a unified HDT framework from a human factors perspective.The framework comprises the physical twin,the virtual twin,and the linkage between these two.The virtual twin integrates human modeling and AI engines to enable model-data-hybrid-enabled simulation.HDT can potentially upgrade traditional ergonomic methods to intelligent services through real-time analysis,timely feedback,and bidirectional interactions.Finally,the future perspectives of HDT for industrial applications as well as technical and social challenges are discussed.In general,this study outlines a human factors perspective on HDT for the first time,which is useful for cross-disciplinary research and human factors innovation to enhance the development of HDT in industry.

Applications and research trends of digital human models in the manufacturing industry

Virtual reality(VR)has been widely used in various manufacturing industries,and VR-based virtual manufacturing has received significant attention in the current intelligent manufacturing era.Digital human models(DHMs)are essential for virtual manufacturing applications.Additionally,researching new applications of DHMs has developed into an important academic research field.This paper aims to identify the applications and research trends of DHMs in the manufacturing industry and to provide a reference for the continued development of virtual manufacturing and DHMs.We selected a total of 49 related articles from a large number of articles published between 2014 and 2019.The applications of DHMs in the manufacturing industry are analyzed from different perspectives and various relevant technical limitations are discussed.The results indicate that the applications of DHMs differ significantly between different types of fields.The automotive industry is the main application field for DHMs,and assembly/maintenance simulations and evaluations are the main application types.Additionally,there are still some limitations in the establishment of virtual environments,motion control,and DHM evaluation that should be addressed.Finally,research trends in the application of DHMs are illustrated and discussed,including the planning and assessment of human-robot collaboration systems,the combination of DHMs and augmented reality,and improved motion planning for DHMs.In summary,the application of DHMs can improve the realism and effectiveness of virtual manufacturing,and DHMs will be more widely and deeply studied and applied in various manufacturing industries in the near future.

Optimization of Biodynamic Seated Human Models Using Genetic Algorithms

Many biodynamic models have been derived using trial and error curve-fitting technique, such that the error between the computed and measured biodynamic response functions is minimum. This study developed a biomechanical model of the human body in a sitting posture without backrest for evaluating the vibration transmissibility and dynamic response to vertical vibration direction. In describing the human body motion, a three biomechanical models are discussed (two models are 4-DOF and one model 7-DOF). Optimization software based on stochastic techniques search methods, Genetic Algorithms (GAs), is employed to determine the human model parameters imposing some limit constraints on the model parameters. In addition, an objective function is formulated comprising the sum of errors between the computed and actual values (experimental data). The studied functions are the driving-point mechanical impedance, apparent mass and seat- to-head transmissibility functions. The optimization process increased the average goodness of fit and the results of studied functions became much closer to the target values (Experimental data). From the optimized model, the resonant frequencies of the driver parts computed on the basis of biodynamic response functions are found to be within close bounds to that expected for the human body.

Model-Based Systems Engineering Approach to Design a Human Settlement to Better Serve Displaced People

The challenge of transitioning from temporary humanitarian settlements to more sustainable human settlements is due to a significant increase in the number of forcibly displaced people over recent decades, difficulties in providing social services that meet the required standards, and the prolongation of emergencies. Despite this challenging context, short-term considerations continue to guide their planning and management rather than more integrated, longer-term perspectives, thus preventing viable, sustainable development. Over the years, the design of humanitarian settlements has not been adapted to local contexts and perspectives, nor to the dynamics of urbanization and population growth and data. In addition, the current approach to temporary settlement harms the environment and can strain limited resources. Inefficient land use and ad hoc development models have compounded difficulties and generated new challenges. As a result, living conditions in settlements have deteriorated over the last few decades and continue to pose new challenges. The stakes are such that major shortcomings have emerged along the way, leading to disruption, budget overruns in a context marked by a steady decline in funding. However, some attempts have been made to shift towards more sustainable approaches, but these have mainly focused on vague, sector-oriented themes, failing to consider systematic and integration views. This study is a contribution in addressing these shortcomings by designing a model-driving solution, emphasizing an integrated system conceptualized as a system of systems. This paper proposes a new methodology for designing an integrated and sustainable human settlement model, based on Model-Based Systems Engineering and a Systems Modeling Language to provide valuable insights toward sustainable solutions for displaced populations aligning with the United Nations 2030 agenda for sustainable development.

ChatModeler:基于大语言模型的人机协作迭代式需求获取和建模方法

需求获取和建模是需求工程中的关键步骤,影响后续系统设计与实现.传统的需求获取和建模方法通常由需求提供者、需求分析师等多类干系人共同协作、反复迭代完成,需要耗费大量的人力.如何减轻需求提供者与需求分析师的负担、提高获取和建模的效率有着重要意义.现有工作中有的使用知识库来提供更多知识,以辅助获取或者建模,有的利用自然语言处理等技术对获取或者建模过程进行自动化,但是它们并没有减轻需求提供者的负担.利用大语言模型(large language models,LLMs)的生成能力,提供了一种人机协作的迭代式需求获取和建模框架ChatModeler.具体来说,根据真实世界中需求团队的分工及协作关系,将部分需求提供者、需求分析师等角色的工作由大语言模型承担,而需求提供者只需要进行确认.为大语言模型扮演的各种角色进行了提示词设计,该提示词会随需求的元模型而变化.ChatModeler在7个需求案例上与3种需求模型的自动建模方法进行了14组对比实验,证明了ChatModeler在降低需求提供者的负担和生成高质量需求模型2个方面上的优越性.

Progress,implications,and challenges in using humanized immune system mice in CAR-T therapy-Application evaluation and improvement

In recent years,humanized immune system(HIS)mice have been gradually used as models for preclinical research in pharmacotherapies and cell therapies with major breakthroughs in tumor and other fields,better mimicking the human immune system and the tumor immune microenvironment,compared to traditional immunodeficient mice.To better promote the application of HIS mice in preclinical research,we se-lectively summarize the current prevalent and breakthrough research and evaluation of chimeric antigen receptor(CAR)-T cells in various antiviral and antitumor treat-ments.By exploring its application in preclinical research,we find that it can better reflect the actual clinical patient condition,with the advantages of providing high-efficiency detection indicators,even for progressive research and development.We believe that it has better clinical patient simulation and promotion for the updated design of CAR-T cell therapy than directly transplanted immunodeficient mice.The characteristics of the main models are proposed to improve the use defects of the existing models by reducing the limitation of antihost reaction,combining multiple models,and unifying sources and organoid substitution.Strategy study of relapse and toxicity after CAR-T treatment also provides more possibilities for application and development.

Extraction of Feature Points for Non-Uniform Rational B-Splines(NURBS)-Based Modeling of Human Legs

Methods of digital human modeling have been developed and utilized to reflect human shape features.However,most of published works focused on dynamic visualization or fashion design,instead of high-accuracy modeling,which was strongly demanded by medical or rehabilitation scenarios.Prior to a high-accuracy modeling of human legs based on non-uniform rational B-splines(NURBS),the method of extracting the required quasi-grid network of feature points for human legs is presented in this work.Given the 3 D scanned human body,the leg is firstly segmented and put in standardized position.Then re-sampling of the leg is conducted via a set of equidistant cross sections.Through analysis of leg circumferences and circumferential curvature,the characteristic sections of the leg as well as the characteristic points on the sections are then identified according to the human anatomy and shape features.The obtained collection can be arranged to form a grid of data points for knots calculation and high-accuracy shape reconstruction in future work.

Building 3-D Human Data Based on Handed Measurement and CNN

3-dimension(3-D)printing technology is growing strongly with many applications,one of which is the garment industry.The application of human body models to the garment industry is necessary to respond to the increasing personalization demand and still guarantee aesthetics.This paper proposes amethod to construct 3-D human models by applying deep learning.We calculate the location of the main slices of the human body,including the neck,chest,belly,buttocks,and the rings of the extremities,using pre-existing information.Then,on the positioning frame,we find the key points(fixed and unaltered)of these key slices and update these points tomatch the current parameters.To add points to a star slice,we use a deep learning model tomimic the form of the human body at that slice position.We use interpolation to produce sub-slices of different body sections based on the main slices to create complete body parts morphologically.We combine all slices to construct a full 3-D representation of the human body.

Assessing the impacts of human activities and climate variations on grassland productivity by partial least squares structural equation modeling(PLS-SEM)

The cause-effect associations between geographical phenomena are an important focus in ecological research. Recent studies in structural equation modeling(SEM) demonstrated the potential for analyzing such associations. We applied the variance-based partial least squares SEM(PLS-SEM) and geographically-weighted regression(GWR) modeling to assess the human-climate impact on grassland productivity represented by above-ground biomass(AGB). The human and climate factors and their interaction were taken to explain the AGB variance by a PLS-SEM developed for the grassland ecosystem in Inner Mongolia, China. Results indicated that 65.5% of the AGB variance could be explained by the human and climate factors and their interaction. The case study showed that the human and climate factors imposed a significant and negative impact on the AGB and that their interaction alleviated to some extent the threat from the intensified human-climate pressure. The alleviation may be attributable to vegetation adaptation to high human-climate stresses, to human adaptation to climate conditions or/and to recent vegetation restoration programs in the highly degraded areas. Furthermore, the AGB response to the human and climate factors modeled by GWR exhibited significant spatial variations. This study demonstrated that the combination of PLS-SEM and GWR model is feasible to investigate the cause-effect relation in socio-ecological systems.

Development of a human rotavirus induced diarrhea model in Chinese mini-pigs

AIM: to establish a new animal model for the research of human rotavirus(HRV) infection, its pathogenesis and immunity and evaluation of potential vaccines.METHODS: 5-d, 30-d and 60-d-old Chinese mini-pigs, Guizhou and bamma, were inoculated with a single oral dose of attenuated strain Wa, G1, G3 of HRV, and PbS(control), respectively, and fecal samples of pigs from 0 to 7 d post infection(DPI) were collected individually. Enzyme linked immunosorbent assay was used to detect HRV antigen in feces. the HRV was tested by real-time PCR(Rt-PCR). the sections of the intestinal tissue were stained with hematoxylin and eosin to observe the morphologic variation by microscopy. Immunofluorescence was used to determine the HRV in intestinal tissue. HRV particles in cells of the ileum were observed by electron micrography.RESULTS: When inoculated with HRV, mini-pigs younger than 30 d developed diarrhea in an agedependent manner and shed HRV antigen of the sameinoculum, as demonstrated by Rt- PCR.Histopathological changes were observed in HRV inoculated mini-pigs including small intestinal cell tumefaction and necrosis. HRV that was distributed in the small intestine was restricted to the top part of the villi on the internal wall of the ileum, which was observed by immunofluorescence and transmission electron microscopy. Virus particles were observed in Golgi like follicles in HRV-infected neonatal minipigs. Guizhou mini-pigs were more sensitive to HRV than bamma with respect to RV antigen shedding and clinical diarrhea.CONCLUSION: these results indicate that we have established a mini-pig model of HRV induced diarrhea. Our findings are useful for the understanding of the pathogenic mechanisms of HRV infection.

Human Health Risk Assessment Model of Organic Pollution in Groundwater:Shijiazhuang Industrial Zone

在这研究，一个基于风险的管理模型被开发并且适用于一个工业地区。模特儿由美国环境保护机构和汉被在在半衰期煮并且删除相关参数以后增加不稳定的有机化合物(VOC ) 的剩余比率一直在改进求婚了。用这个改进模型，一个综合过程被用来在学习区域估计人的健康风险水平。与水质量分析相比，结果强调在风险层次和水保护上为决策使用一条综合途径的重要性。这研究的结果表明了那：(1 ) 与在中国(GB 38382002 ) 和美国的国家的主要喝酒水规定的这些可允许的水平标准相比，居民的日常生活没被地下水在这个区域影响了(除了 HB34 和 HB36 的相对的坏水质量) ；(2 ) 所有地下水样品的典型检测器官的沾染物是氯仿，碳四氯化物， trichloroethylene 和 tetrachloroethene，并且污染来源主要是由初步的调查的工业来源；(3 ) 至于地下水，所有样品的 non-carcinogenic 风险价值不超过 1.0 的可允许的水平， carcinogenic 风险价值比对 1.00E-04 的 1.00E-06 的可允许的水平相对低；(4 ) 喝 trichloroethylene 和 tetrachloroethylene 的水小径主要贡献在学习区域增加居民的健康风险；(5 ) 以 non-carcinogenic，风险和 carcinogenic 冒险，为喝水小径的健康风险顺序和真皮的接触小径：喝的水小径 > 真皮的接触小径。

An In Vivo Experimental Validation of a Computational Model of Human Foot

Reliable computational foot models offer an alternative means to enhance knowledge on the biomechanics of human foot.Model validation is one of the most critical aspects of the entire foot modeling and analysis process.This paper presents an invivo experiment combining motion capture system and plantar pressure measure platform to validate a three-dimensional finiteelement model of human foot.The Magnetic Resonance Imaging(MRI)slices for the foot modeling and the experimental datafor validation were both collected from the same volunteer subject.The validated components included the comparison of staticmodel predictions of plantar force,plantar pressure and foot surface deformation during six loading conditions,to equivalentmeasured data.During the whole experiment,foot surface deformation,plantar force and plantar pressure were recorded simultaneouslyduring six different loaded standing conditions.The predictions of the current FE model were in good agreementwith these experimental results.

A ROBUST ADAPTIVE VIDEO ENCODER BASED ON HUMAN VISUAL MODEL

A Robust Adaptive Video Encoder (RAVE) based on human visual model is proposed. The encoder combines the best features of Fine Granularity Scalable (FGS) coding, framedropping coding, video redundancy coding, and human visual model. According to packet loss and available bandwidth of the network, the encoder adjust the output bit rate by jointly adapting quantization step-size instructed by human visual model, rate shaping, and periodically inserting key frame. The proposed encoder is implemented based on MPEG-4 encoder and is compared with the case of a conventional FGS algorithm. It is shown that RAVE is a very efficient robust video encoder that provides improved visual quality for the receiver and consumes equal or less network resource. Results are confirmed by subjective tests and simulation tests.

Computational Models to Synthesize Human Walking

The synthesis of human walking is of great interest in biomechanics and biomimetic engineering due to its predictive ca- pabilities and potential applications in clinical biomechanics, rehabilitation engineering and biomimetic robotics. In this paper, the various methods that have been used to synthesize human walking are reviewed from an engineering viewpoint. This involves a wide spectrum of approaches, from simple passive walking theories to large-scale computational models integrating the nervous, muscular and skeletal systems. These methods are roughly categorized under four headings: models inspired by the concept of a CPG (Central Pattern Generator), methods based on the principles of control engineering, predictive gait simulation using optimisation, and models inspired by passive walking theory. The shortcomings and advantages of these methods are examined, and future directions are discussed in the context of providing insights into the neural control objectives driving gait and improving the stability of the predicted gaits. Future advancements are likely to be motivated by improved understanding of neural control strategies and the subtle complexities of the musculoskeletal system during human locomotion. It is only a matter of time before predictive gait models become a practical and valuable tool in clinical diagnosis, rehabilitation engineering and robotics.

Experimental primates and non-human primate(NHP) models of human diseases in China: current status and progress

Non-human primates(NHPs) are phylogenetically close to humans, with many similarities in terms of physiology, anatomy, immunology, as well as neurology, all of which make them excellent experimental models for biomedical research. Compared with developed countries in America and Europe, China has relatively rich primate resources and has continually aimed to develop NHPs resources. Currently, China is a leading producer and a major supplier of NHPs on the international market. However, there are some deficiencies in feeding and management that have hampered China's growth in NHP research and materials. Nonetheless, China has recently established a number of primate animal models for human diseases and achieved marked scientific progress on infectious diseases, cardiovascular diseases, endocrine diseases, reproductive diseases, neurological diseases, and ophthalmic diseases, etc. Advances in these fields via NHP models will undoubtedly further promote the development of China's life sciences and pharmaceutical industry, and enhance China's position as a leader in NHP research. This review covers the current status of NHPs in China and other areas, highlighting the latest developments in disease models using NHPs, as well as outlining basic problems and proposing effective countermeasures to better utilize NHP resources and further foster NHP research in China.

Gray Model of Human Body Shape

In order to determine the control dimensions of human body in pattern construction and provide the basis for size specification in clothing industry, a gray model is described and established in the application of predicting size specification. By comparing the features of gray model and regression model, it is proved that the former has many advantages over the latter, i.e. more practical and more effective in this application. So it is strongly suggested to apply the innovative gray model instead of the traditional regression model to facilitate the calculation procedure in pattern construction.

Integrated Framework for Vehicle Interior Design Using Digital Human Model

Evaluating the human friendliness of vehicles is essential for designing new vehicles since large numbers of human-machine interactions occur frequently inside vehicles. In this research, we develop an integrated framework for vehicle interior design using a digital human model (DHM). In this framework, the knowledge-based parametric modelling function of vehicles is implemented using a commercial computer-aided design (CAD) system. The combination of the DHM and the CAD system enables designers into carry out ergonomic evaluations of various human-vehicle interactions and understand the effects of modifications of vehicle design parameters on occupants during designing. Further, the information on human-vehicle interaction obtained using this system can be transmitted to dedicated biomechanical analysis software. By analysing human motions inside vehicles using such software, we can obtain optimized interior design parameters.

Research on Dynamic Model of the Human Body

After summarizing the current situation of the research on human body modeling, a new dynamic model containing 5 equivalent masses has been proposed and the corresponding dynamic equations has been deduced too. By using this new model, more detailed information about the situation of the human body under impact and vibration can be obtained. The new model solves the problem that transmission functions of forces inside the human body can’t be deduced by using 3-equivalent-mass model. It will find its usage in many applications.

Kinematic simulation of human gait with a multi-rigid-body foot model

The paper builds a multi-rigid-body model of human with a 4-rigid-body foot in the 3D CAD software Solidworks,based on human anatomy.By controlling the rotation of the ankle and major joints of human body while walking,the Kinematic simulation was performed in the dynamics simulation software ADAMS.The paper analyzes the simulate results and points out deficiencies in the current work and the direction of research efforts in future.