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.

A Systems Approach to Assessing Sustainability Capacity in Kalobeyei Refugee Settlement in Turkana County, Kenya

Refugee settlements face several challenges in transitioning from a temporary planning approach to more sustainable settlements. This is mainly due to an increase in the number of forcibly displaced people over the last few decades, and the difficulties of sustainably providing social services that meet the required standards. The development of refugee settlements assumed that forcibly displaced people would return to their places or countries of origin. Unfortunately, displacement situations are prolonged indefinitely, forcing these people to spend most of their lives in conditions that are often deplorable and substandard, and therefore unsustainable. In most cases, the establishment of refugee settlements is triggered by an emergency caused by an influx of forcibly displaced people, who need to be accommodated urgently and provided with some form of international assistance and protection. This leaves little or no time for proper planning for long-term development as required. In addition, the current approach to temporary settlement harms the environment and can strain limited resources with ad hoc development models that have exacerbated difficulties. As a result, living conditions in refugee settlements have deteriorated over the last few decades and continue to pose challenges as to how best to design, plan, and sustain settlements over time. To contribute to addressing these challenges, this study proposes a new methodology supported by Model-Based Systems Engineering (MBSE) and a Systems Modeling Language (SysML) to develop a typical sustainable human settlement system model, which has functionally and operationally executed using a Systems Engineering (SE) approach. To assess the sustainability capacity of the proposed system, this work applies a matrix of crossed impact multiplication through a case study by conducting a system capacity interdependence analysis (SCIA) using the MICMAC methodology (Cross-impact matrix multiplication applied to classification) to assess the interdependency that exist between the sub-systems categories to deliver services at the system level. The sustainability analysis results based on capacity variables influence and dependency models shows that development activities in the settlement are unstable and, therefore, unsustainable since there is no apparent difference between the influential and dependent data used for the assessment. These results illustrate that an integrated system could improve human settlements’ sustainability and that capacity building in service delivery is beneficial and necessary.

A goal-based approach for modeling and simulation of different types of system-of-systems

A system of systems(SoS)composes a set of independent constituent systems(CSs),where the degree of authority to control the independence of CSs varies,depending on different SoS types.Key researchers describe four SoS types with descending levels of central authority:directed,acknowledged,collaborative and virtual.Although the definitions have been recognized in SoS engineering,what is challenging is the difficulty of translating these definitions into models and simulation environments.Thus,we provide a goal-based method including a mathematical baseline to translate these definitions into more effective agent-based modeling and simulations.First,we construct the theoretical models of CS and SoS.Based on the theoretical models,we analyze the degree of authority influenced by SoS characteristics.Next,we propose a definition of SoS types by quantitatively explaining the degree of authority.Finally,we recognize the differences between acknowledged SoS and collaborative SoS using a migrating waterfowl flock by an agentbased model(ABM)simulation.This paper contributes to the SoS body of knowledge by increasing our understanding of the degree of authority in an SoS,so we may identify suitable SoS types to achieve SoS goals by modeling and simulation.

Nutritional Support under the Neuman Systems Model for Stroke Patients

Objective: To explore nutritional support under the Neuman systems model in treating dysphagia in stroke patients. Methods: In this retrospective study, we enrolled 97 patients with dysphagia after stroke admitted to our hospital, and randomly divided them into the Neuman group (n = 51) given nursing intervention based on Neuman systems model and a control group (n = 46) given routine nursing intervention. Both groups received nutritional support for 3 months. Nutritional indexes (serum total protein, plasma albumin, serum albumin, hemoglobin and transferrin levels) and immune indexes (immunoglobulin (Ig) A, IgG, IgM and total lymphocyte count (TLC) in both groups were recorded and compared. Pulmonary function recovery, video fluoroscopic swallowing study score, water swallowing test score, complication rate, and health knowledge mastery level were also compared between the two groups. Results: After the intervention, the Neuman group showed less decrease in the nutritional and immune index scores (serum total protein, plasma albumin, hemoglobin, serum albumin;IgA, IgG, IgM, and TLC;all P Conclusion: For patients with stroke and dysphagia, comprehensive nursing intervention (e.g., nutritional support) under theNeuman systems model can promote the recovery of immune, swallowing, and pulmonary function, reduce complication incidence and facilitate comprehensive rehabilitation, ensuring adequate nutritional intake.

Mathematical Constraints in Multiscale Subgrid-Scale Modeling of Nonlinear Systems

To shed light on the subgrid-seale （SGS） modeling methodology of nonlinear systems such as the Navier-Stokes turbulence, we define the concepts of assumption and restriction in the modeling procedure, which are shown by generalized derivation of three general mathematical constraints for different combinations of restrictions. These constraints are verified numerically in a one-dimensional nonlinear advection equation. This study is expected to inspire future research on the SGS modeling methodology of nonlinear systems.

QoE Modeling and Applications for Multimedia Systems

Ireproving the quality and experience perceived by the user is fundamental when de- veloping multimedia technologies, products, and services. Quality of experience （QoE） involves subjective perception, user behavior and needs, appropriateness, con- text, and usability of delivered content. Modeling QoE is critical for enhancing QoE in various nmhimedia applications. In this special issue,

Mechatronic Modeling and Domain Transformation of Multi-physics Systems

The enhanced definition of Mechatronics involves the four underlying characteristics of integrated,unified,unique,and systematic approaches.In this realm,Mechatronics is not limited to electro-mechanical systems,in the multi-physics sense,but involves other physical domains such as fluid and thermal.This paper summarizes the mechatronic approach to modeling.Linear graphs facilitate the development of state-space models of mechatronic systems,through this approach.The use of linear graphs in mechatronic modeling is outlined and an illustrative example of sound system modeling is given.Both time-domain and frequency-domain approaches are presented for the use of linear graphs.A mechatronic model of a multi-physics system may be simplified by converting all the physical domains into an equivalent single-domain system that is entirely in the output domain of the system.This approach of converting(transforming)physical domains is presented.An illustrative example of a pressure-controlled hydraulic actuator system that operates a mechanical load is given.

A Triple Nexus Water-Energy-Housing (WEH) Framework Modelling towards Improved Decision-Making in Humanitarian Operations

Given the challenges facing most humanitarian operations worldwide, a change of approach is needed to ensure greater sustainability of humanitarian settlements right from the planning stage. Some studies attribute unsustainability to inadequate provision of basic resources and highlight the apparent bottlenecks that prevent access to the meaningful data needed to plan and remedy problems. Most operations have relied on an “ad hoc ism” approach, employing parallel and disconnected data processing methods, resulting in a wide range of data being collected without subsequent prioritization to optimize interconnections that could enhance performance. There have been little efforts to study the trade-offs potentially at stake. This work proposes a new framework enabling all subsystems to operate in a single system and focusing on data processing perspective. To achieve this, this paper proposes a Triple Nexus Framework as an attempt to integrate water, energy, and housing sector data derived from a specific sub-system within the overall system in the application of Model-Based Systems Engineering. Understanding the synergies between water, energy, and housing, Systems Engineering characterizes the triple nexus framework and identifies opportunities for improved decision-making in processing operational data from these sectors. Two scenarios illustrate how an integrated platform could be a gateway to access meaningful operational data in the system and a starting point for modeling integrated human settlement systems. Upon execution, the model is tested for nexus megadata processing, and the optimization simulation yielded 67% satisfactory results, demonstrating that an integrated system could improve sustainability, and that capacity building in service delivery is more than beneficial.

基于WordCloud技术的MBSE发展态势研究

基于IEEE及国际系统工程协会(International Council on Systems Engineering,INCOSE)社区会刊,提取与基于模型的系统工程(model based systems engineering,MBSE)领域相关的167篇顶刊的关键词和摘要。采用Python及其第三方库WordCloud技术,以可视化形式展示MBSE领域研究内容并对MBSE发展态势进行研究。研究结果表明,MBSE在产品研发全生命周期,应用建模技术来支持系统需求、设计、分析、验证与确认等活动,在系统架构设计方面具有重要作用,将MBSE与安全性分析、可靠性分析方法结合也是MBSE的重要研究内容;系统建模语言(system modeling language,SysML)和对象过程方法(object process method,OPM)分别是目前MBSE研究领域中最受欢迎的建模语言和建模方法;将MBSE方法与本体进行结合是规范MBSE模型表达的重要手段,将MBSE与信息物理系统、数字孪生、并行工程领域进行融合研究是MBSE的重要发展方向。所提研究为使用WordCloud文本分析技术来探索当前的MBSE研究提供了技术路线参考,有助于对MBSE的未来发展态势进行预测。

Spatiotemporal characteristics of water exchange between the Andaman Sea and the Bay of Bengal

A high-resolution customized numerical model is used to analyze the water transport in the three major water passages between the Andaman Sea(AS)and the Bay of Bengal,i.e.,the Preparis Channel(PC),the Ten Degree Channel(TDC),and the Great Channel(GC),based on the daily averaged simulation results ranging from 2010 to 2019.Spectral analysis and Empirical Orthogonal Function(EOF)methods are employed to investigate the spatiotemporal variability of the water exchange and controlling mechanisms.The results of model simulation indicate that the net average transports of the PC and GC,as well as their linear trend,are opposite to that of the TDC.This indicates that the PC and the GC are the main inflow channels of the AS,while the TDC is the main outflow channel of the AS.The transport variability is most pronounced at surface levels and between 100 m and 200 m depth,likely affected by monsoons and circulation.A 182.4-d semiannual variability is consistently seen in all three channels,which is also evident in their second principal components.Based on sea level anomalies and EOF analysis results,this is primarily due to equatorial winds during the monsoon transition period,causing eastward movement of Kelvin waves along the AS coast,thereby affecting the spatiotemporal characteristics of the flow in the AS.The first EOF of the PC flow field section shows a split at 100 m deep,likely due to topography.The first EOF of the TDC flow field section is steady but has potent seasonal oscillations in its time series.Meanwhile,the first EOF of the GC flow field section indicates a stable surface inflow,probably influenced by the equatorial Indian Ocean’s eastward current.

Cognitive dissonance and mindset perturbations during crisis:“ecosocio-psycho-somatic”perspectives

Mandatory and restrictive health regulations during the corona pandemic caused psychic disorders in many people,which even led to clinically relevant mental disorders.At the same time,there was gradually a polarization of opinions among the population.In order to improve future pandemic management,an integrative understanding of these psychosocial processes therefore seems useful.Here we start theoretically with the mental effects of inconsistencies of the information environment by referring to concepts such as the theory of cognitive dissonance.In a next step,we use the psychodynamic theory to understand the affective-motivational defense mechanisms underlying these cognitive states and processes.However,a broader theoretical framework of psychoanalysis seems to make sense,because self-referential processing also influences the style of thinking.For this reason,we use a more comprehensive psychological systems theoretical framework model to integrate these different perspectives.This integrative view refers in part to basic knowledge of health psychology regarding the resistance of unhealthy ways of thinking and behaviors and the possibilities for interventions for change.We then extend this model to a broader picture that also covers the relationship between men and their environment.This results in the perspective of a multidimensional socioecological theoretical framework,which as a heuristic reference model and related to other ecological approaches could also be helpful for various theoretical questions for public health,and could provide a better public understanding of health issues.In line with this perspective,we hypothesize that with regard to the coronavirus disease 2019 pandemic,the acceptance of public health narratives could be increased if a more consistent picture of the scientific descriptions and explanations of the pandemic-similar to the model proposed-could be provided,which would enable the understanding of the origin,course and countermeasures,and thus could have positive collective psycho-hygienic effects.

Palm Oil Production in Malaysia: An Analytical Systems Model for Balancing Economic Prosperity, Forest Conservation and Social Welfare

Since the late 1950’s, the Malaysian human population has nearly quadrupled, increasing pressure on natural resource exploitation to meet domestic needs and to earn foreign exchange from exports. Global demand for Malaysian palm oil in particular had steeply increased since the mid-1970s and by 2013, the commodity was the leading foreign exchange earner. To fulfill and sustain this demand, the country’s economy has steadily shifted bias towards production and associated value addition of palm oil products for export. However, as a consequence, many of Malaysia’s natural tropical forests have been converted to palm oil farming resulting in loss of approximately 10,000 km2 of forest cover over the past twenty-five years, and biodiversity has been displaced or lost. To provide a deeper insight into the interplay amongst key interrelated environmental and socio-economic variables, and a forecast of possible future balance, we used a systems dynamism modeling tool, STELLAR (structural thinking, experiential learning laboratory with animation), to simulate and project how Malaysia could achieve a medium-term sustainable balance or optimization between palm oil production and forest conservation without compromising on human social welfare. The model consisted of four main modules (environmental, economic, social development and human welfare) each with component parameters, and interconnected by input and output loops. Model calibrations, testing and preruns involved existing official 30-year time-series datasets. Subsequently, four scenarios: Environmental conservation;Economic growth under increased global palm oil demand;Economy decline under decreased palm oil demand;and Control condition with little or no change, were selected for simulated projections of future possibilities. Simulation results showed that scenarios and variable interactions that reduce environmental damage would offer the best chance for optimizing the palm oil economy while also minimizing forest loss and promoting citizen social welfare.

Effect of pH,temperature and heating time on the formation of furan in sugar–glycine model systems

Furan(C4H4O)has been classified as a possible animal and human carcinogen by many international agencies.The formation of furan in three sugar–glycine models using glucose,fructose,and sucrose was investigated using headspace gas chromatography mass spectrometry method(HSGC–MS)with various dual combinations of three important heat processing conditions,i.e.pH,temperature,and heating time.Results indicated that furan levels from sugar–glycine model systems during the thermal processing can be attributed to selective sugar types,pH,temperature,and heating time.In glucose–glycine and fructose–glycine system,the lowest furan level was detected in acid condition but in sucrose–glycine system furan formed significantly lower(P<0.05)in acidic conditions the lowest furan level was found in alkaline conditions.The furan levels were observed to increase with heating time in all three model systems.Furthermore,less furan was generated in non-reducing sugar system(sucrose)than in reducing sugar system(glucose and fructose).Therefore,they demonstrate the possibility of limiting the formation of furan in heat processed foods by both the careful selection of carbohydrates(i.e.non-reducing sugars and reducing sugars)ingredients and appropriate processing conditions.©2013 Beijing Academy of Food Sciences.Production and hosting by Elsevier B.V.All rights reserved.

Hepatitis C Virus Experimental Model Systems and Antiviral drug Research

An estimated 130 million people worldwide are chronically infected with hepatitis C virus (HCV) making it a leading cause of liver disease worldwide. Because the currently available therapy of pegylated interferon-alpha and ribavirin is only effective in a subset of patients, the development of new HCV antivirals is a healthcare imperative. This review discusses the experimental models available for HCV antiviral drug research, recent advances in HCV antiviral drug development, as well as active research being pursued to facilitate development of new HCV-specific therapeutics.

Nonlinear adaptive switching control for a class of non-affine nonlinear systems

An improved nonlinear adaptive switching control method is presented to relax the assumption on the higher order nonlinear terms of a class of discrete-time non-affine nonlinear systems. The proposed control strategy is composed of a linear adaptive controller, a neural network(NN) based nonlinear adaptive controller and a switching mechanism. An incremental model is derived to represent the considered system and an improved robust adaptive law is chosen to update the parameters of the linear adaptive controller. A new performance criterion of the switching mechanism is designed to select the proper controller. Using this control scheme, all the signals in the system are proved to be bounded. Numerical examples verify the effectiveness of the proposed algorithm.

PRACTICAL AND PREDICTIVE MODELLING OF ORE DEPOSITS IN HYDROTHERMAL SYSTEMS

Over the pastfive years,we have been making efforts to develop a practical and predic- tive tool to exploreforgiantore deposits in hydrothermal systems. Towards this goal,a sig- nificant progress has been made towards a better understanding of the basic physical and chemical processes behind ore body formation and mineralization in hydrothermal systems. On the scientific developmentside,we have developed analytical solutions to answerthe fol- lowing scientific questions:(1) Can thepore- fluid pressure gradientbemaintained atthe val- ue of the lithostaticpressure gradientin the uppercrustof the Earth?and(2 ) Can convective pore- fluid flow take place in the uppercrustof the Earth ifthere is a fluid/mass leakage from the mantle to the upper crustof the Earth?On the modelling developmentside,we have developed numerical methods to model the following problems:(1) convective pore- fluid flow in two- dimensional hydrothermal systems;(2 ) coupled reactive pore- fluid flow and multiple species transport in porous media;(3) precipitation and dissolution of minerals and rock al- teration in the upper crust of the Earth;(4 ) double diffusion driven reactive flow transport in deformable fluid- saturated porous media with particular consideration of temperature- de- pendentchemical reaction rates;(5 ) pore- fluid flow patterns neargeological lenses in hydro- dynamic and hydrothermal systems;(6 ) dissipative structures for nonequilibrium chemical reactions in fluid- saturated porousmedia;(7) convectivepore- fluid flow and the related min- eralization in three- dimensional hydrothermal systems;(8) fluid- rock interaction problems associated with the rock alteration and metamorphic process in fluid- saturated hydrothermal/ sedimentary basins;and (9) various aspects of the fully coupled problem involving material deformation,pore- fluid flow,heattransferand species transport/ chemical reactionsin pore- fluid saturated porous rock masses. The above- mentioned work has significantly enriched our knowledge about the physical and chemical processes related to ore body formation and mineralization in the upper crustof the

Fifth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Nonlinear Systems (5th-CASAM-N): I. Mathematical Framework

This work presents the mathematical framework of the “Fifth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Nonlinear Systems (5th-CASAM-N),” which generalizes and extends all of the previous works performed to date on this subject. The 5th-CASAM-N enables the exact and efficient computation of all sensitivities, up to and including fifth-order, of model responses to uncertain model parameters and uncertain boundaries of the system’s domain of definition, thus enabling, inter alia, the quantification of uncertainties stemming from manufacturing tolerances. The 5th-CASAM-N provides a fundamental step towards overcoming the curse of dimensionality in sensitivity and uncertainty analysis.

Visual analysis of the research hotspots of Neuman systems model in recent 20 years

Background:This paper uses information visualization software to sort out the relevant research of Neuman systems model at home and abroad in the past 20 years,and discusses the research hotspots and development trend in the field of Neuman systems model,so as to provide scientific and reliable reference for the future work and research.Methods:By using CiteSpace V software,this paper analyzes the literatures about the Neuman systems model collected in the core web of science database and CNKI database from 2001 to 2020,and analyzes the time distribution,research power distribution,research hotspots,research frontier and development trend of the Neuman systems model at home and abroad in the past 20 years.Results:The development trend of research in this field in foreign countries is relatively stable.The core strength of research is mainly in the United States,and the research hotspots are health,quality of life,caregivers,spirituality,etc;the research in this field in China is gradually on the rise,and there is no obvious research force,and the research hotspots are mainly quality of life,complications,anxiety,stressors,perioperative period,hypertension,etc.Conclusions:It has been proved that the model has a certain guiding effect on the development of nursing discipline in China.In China,there is still room for development in the research of this model.It is suggested that Chinese scholars can learn from foreign leading research forces to carry out in-depth research and expand its application scope.

A multidimensional examination of performances of HSR (High-Speed Rail) systems

This paper deals with a multidimensional examination of the infrastructural, technical/technological, operational, economic, social, and environmental performances of high-speed rail （HSR） systems, including their overview, analysis of some real-life cases, and limited （analytical） modeling. The infrastructural performances reflect design and geometrical characteristics of the HSR lines and stations. The technical/technological performances relate to the characteristics of rolling stock, i.e., high-speed trains, and supportive facilities and equipment, i.e., the power supply, signaling, and traffic control and management system（s）. The operational performances include the capacity and productivity of HSR lines and rolling stock, and quality of services. The economic per- formances refer to the HSR systems＇ costs, revenues, and their relationship. The social performances relate to the impacts of HSR systems on the society such as congestion, noise, and safety, and their externalities, and the effects in terms of contribution to the local and global/country social- economic development. Finally, the environmental performances of the HSR systems reflect their energy consumption and related emissions of green house gases, land use, and corresponding externalities.

Quantifying major sources of uncertainty in projecting the impact of climate change on wheat grain yield in dryland environments

Modelling the impact of climate change on cropping systems is crucial to support policy-making for farmers and stakeholders.Nevertheless,there exists inherent uncertainty in such cases.General Circulation Models(GCMs)and future climate change scenarios(different Representative Concentration Pathways(RCPs)in different future time periods)are among the major sources of uncertainty in projecting the impact of climate change on crop grain yield.This study quantified the different sources of uncertainty associated with future climate change impact on wheat grain yield in dryland environments(Shiraz,Hamedan,Sanandaj,Kermanshah and Khorramabad)in eastern and southern Iran.These five representative locations can be categorized into three climate classes:arid cold(Shiraz),semi-arid cold(Hamedan and Sanandaj)and semi-arid cool(Kermanshah and Khorramabad).Accordingly,the downscaled daily outputs of 29 GCMs under two RCPs(RCP4.5 and RCP8.5)in the near future(2030s),middle future(2050s)and far future(2080s)were used as inputs for the Agricultural Production Systems sIMulator(APSIM)-wheat model.Analysis of variance(ANOVA)was employed to quantify the sources of uncertainty in projecting the impact of climate change on wheat grain yield.Years from 1980 to 2009 were regarded as the baseline period.The projection results indicated that wheat grain yield was expected to increase by 12.30%,17.10%,and 17.70%in the near future(2030s),middle future(2050s)and far future(2080s),respectively.The increases differed under different RCPs in different future time periods,ranging from 11.70%(under RCP4.5 in the 2030s)to 20.20%(under RCP8.5 in the 2080s)by averaging all GCMs and locations,implying that future wheat grain yield depended largely upon the rising CO2 concentrations.ANOVA results revealed that more than 97.22% of the variance in future wheat grain yield was explained by locations,followed by scenarios,GCMs,and their interactions.Specifically,at the semi-arid climate locations(Hamedan,Sanandaj,Kermanshah and Khorramabad),most of the variations arose from the scenarios(77.25%),while at the arid climate location(Shiraz),GCMs(54.00%)accounted for the greatest variation.Overall,the ensemble use of a wide range of GCMs should be given priority to narrow the uncertainty when projecting wheat grain yield under changing climate conditions,particularly in dryland environments characterized by large fluctuations in rainfall and temperature.Moreover,the current research suggested some GCMs(e.g.,the IPSL-CM5B-LR,CCSM4,and BNU-ESM)that made moderate effects in projecting the impact of climate change on wheat grain yield to be used to project future climate conditions in similar environments worldwide.