Model Transformation Research Articles

Reachable set estimation of MASs with consensus performance under event-triggered scheme and semi-Markov switching topologies with partially unknown rates

This article focuses on the issue of reachable set estimation(RSE) with the consensus performance for multi-agent systems(MASs) under event-triggered scheme(ETS) and semi-Markov switching topologies with partially unknown rates(SMST-PUR). Firstly, through model transformation, the consensus research of MASs can be converted to the closed-loop stability analysis problem, and a periodic sampling ETS is employed to reduce the frequency of information broadcasting by the behavior of communicating with neighbors at the special moments. Secondly, the Lyapunov-Krasovskii functions(LKFs) with state information of time delay are constructed, whose goal is to capture more dynamics of time delay that impact on the controller’s design. And a group of sufficient conditions in the aspect of linear matrix inequalities(LMIs) is derived to guarantee that the states of error system can be confined within a finite union of ellipsoid-like sets corresponding to each mode with consensus manifestation under the action of switching topology randomly governed by SMST-PUR. Simultaneously, the method of co-designing the consensus controller and the triggered matrices of ETS with RSE performance is depicted to save communication resources availably. Finally, a study case is utilized to verify the validity of the proposed method and the comparative results illustrate the advantages and effectiveness of the control algorithm designed in this paper.

The Influence of Surface Fluxes on Export of Southern Ocean Intermediate and Mode Water in Coupled Climate Models

AbstractThe Southern Ocean (SO) plays a crucial role in the process of sequestering heat and carbon dioxide from the atmosphere and transferring them to the deep ocean. This process is intricately linked to the formation of Antarctic Intermediate Water (AAIW) and Subantarctic Mode Water (SAMW), which are pivotal components of the Meridional Overturning Circulation (MOC) and have a substantial impact on the global climate balance. AAIW and SAMW take shape in specific regions of the Southern Ocean due to the influence of strong winds, buoyancy fluxes, and their effects, such as convection, the development of thick mixed layers, and wind‐driven subduction. These water masses subsequently flow northward, contributing to the ventilation of the intermediate layers within the subtropical gyres. In this study, our focus lies on investigating the regional aspects of AAIW and SAMW transformation in CMIP6 models. We accomplish this by analyzing the relationship between the meridional transport of these water masses and air‐sea fluxes, particularly Ekman pumping, freshwater fluxes, and heat fluxes. Our findings reveal that the highest transformation rates occur in the Indian sector of the Southern Ocean, with notable values also observed in the southeast Pacific and south of Africa. Additionally, we assess the potential changes in these formation regions under future scenarios projected for the end of the 21st century. Although the patterns of formation regions remain consistent, there is a significant decrease in the transformation process.

A Novel Stereographic Semi-Circular Distribution and Enhanced Analysis of the Posterior Corneal Curvature of Eye

Circular distributions within the radians range describe two-dimensional directions by mapping points onto a unit circle. These distributions are vital in diverse fields such as medicine, ecology, and environmental studies, where measurements are expressed in terms of angles. However, when these distributions involve measuring angles within the radians range, they constitute axial or semi-circular data instead of circular data. This research seeks to introduce the semi-circular Marshall-Olkin extended Burr-XII distribution tailored for semi-circle datasets. Objectives encompass presenting its fundamental characteristics and applications. The inverse stereographic projection technique is applied for its development, deriving characteristics like trigonometric moments, mode, hazard function, and survival function. Five estimation techniques assess the distribution's parameters. Monte Carlo simulations evaluate parameter estimation methods for different sample sizes. Modeling the semi-circular Marshall-Olkin extended Burr-XII distribution with real-life semi-circle data of posterior corneal curvature of eye demonstrates its adaptability. Comparisons with existing distributions affirm its effectiveness. Extending to the l-axial model produces the Stereographic-l-axial Marshall-Olkin extended Burr-XII distribution, offering a distinct probability density function (pdf). This transformation gives rise to specific scenarios and new models. The proposed semi-circular Marshall-Olkin extended Burr-XII distribution proves adept at handling real-world semi-circular data. The extension to the l-axial model and subsequent transformations introduces innovative models, demonstrated by superior compatibility in both circular and semi-circular datasets.

Dynamic Modeling and Configuration Transformation of Origami with Soft Creases

Origami has attracted much attention from scientists and engineers in recent years. Classic origami only permits rotations around creases, while origami-like structures in nature can also undergo a certain degree of extension at creases. In this paper, an earwig-inspired origami with rotational symmetry is proposed and analyzed by introducing soft creases. Such a soft crease is equivalent to a combination of a rotational spring and an extensional spring. The motion of the earwig-inspired origami is described using spherical triangles. Based on Lagrange's Equation, the nonlinear dynamic equation of the system is formulated. It is then solved by using the fourth-order Runge-Kutta method. The results of theoretical calculations are consistent with those of simulations in ADAMS. With the established framework, the bifurcation behaviors of the equilibria of the proposed system, including supercritical pitchfork and saddle-node bifurcations, are investigated. Such origami can realize both mono-stable and bi-stable mechanisms, while the corresponding design parameters are demonstrated in the design map. In particular, the properties of the bi-stable origami can vary with different equilibria. The configuration transformation could be achieved using a continuous excitation. However, it is sometimes sensitive to the initial conditions. Inspired by the working mechanism of earwig wings, a simple control approach for origami configuration transformation is proposed. The key is to stop exciting the origami when its deformation crosses an energy barrier. This work lays a foundation for the design and study of novel multi-stable and morphing structures and provides an efficient approach for their configuration transformation.

The Role of the Merchant Class in Japanese History: A Case Study of the Mitsui Family (1639-1895)

The birth of the Mitsui family was a necessity in the historical development of Japan in the context of changes in social classes, in particular, the role of the merchant class is increasingly recognized by the government through the contributions of merchants to the economic development of the country, onward, the unstable political situation and complicated financial and monetary confusion when there are two types of money, old and new, circulating at the same time. The Mitsui family which specialized in foreign trade and monetary finance, was born to promptly meet the changing and developing needs of Japan at that time. The main research methods are historical and logical. Using historical methods, we began to research the origins of the Mitsui family and the process of development and transformation of the business model from feudal society to capitalism. The logical method is used to determine the characteristics and nature of the relationship between economics and political values when analyzing the role of the Mitsui family according to a system. This study clarifies the formation conditions, ownership characteristics, form of management, and fields of activity of the Mitsui family as well as analyzes the role of this family in the development of Japan during the period of capitalism.

The Growing Cybersecurity Crisis in Healthcare: A Call to Action

Electronic healthcare technology is pervasive throughout the globe, and it affords vast opportunities to enhance clinical outcomes, as well as for the transformation of models of care. Concerns are, however, growing, related to healthcare data and device security. Increased connectivity to legacy computer networks brought cybersecurity vulnerabilities for medical devices. Healthcare represents an attractive target for cybercrime because healthcare data is precious. This sector in present times is full of unique cybersecurity challenges, especially for susceptible kinds of patient information at stake. Second, many legacy systems will be prevalent—not adding more to that—with the changing face of cyber threats. Cybersecurity breaches have comprised stealing health information and focused ransomware attacks on hospitals; this could mean as vivid an attack as on implanted medical devices. This only points to the fact that ransomware attacks and other kinds of cyber-attacks against hospitals and other medical facilities are gaining ground; there is every reason to get alarmed and put in place stricter cybersecurity measures. An excellent healthcare cybersecurity strategy, therefore, has to consider access control, intrusion detection systems, encryption techniques, and periodic security testing. Data breaches and cyber-attacks are forcing any healthcare provider to invest in new state-of-the-art technologies related to keeping pace with trends regarding cybersecurity. The dangers that can be caused by cyber-attack include a considerable diminution in patient trust, potential health system collapse, human life threats, etc. On the whole, cybersecurity is strenuously linked with the question of patient safety.

Transformation of e-commerce business models in the digital economy

Purpose. Research on the transformation of e-commerce business models in the conditions of the digital economy, analysis of the main directions of changes in business processes, as well as the determination of key differences between Internet commerce, e-commerce and online commerce, substantiation of the difference in the sources of generation of added value and identification of the factors that facilitate the transition from traditional e-commerce business models to digital ones. Methodology. When conducting the research, the trends of the development of electronic commerce and the factors contributing to their transformation in the conditions of the digital economy were revealed by the method of formal analysis. Findings. This study presents an analysis of trends and factors affecting the development of digital commerce and the transformation of digital commerce business models. The directions of integration of digital technologies into business processes and strategic aspects of the implementation of digital solutions into business practice are substantiated. The key factors that contribute to the transformation of e-commerce business models into digital commerce business models are identified, in particular, in the creation and implementation of new business models that allow for effective adaptation to the conditions of the digital economy. It is found that the economic basis of transformations of business models is the sources of creation of added value. It has been proven that digital technologies, which form the basis of e-business, are carriers and main sources of added value creation, which is reflected in business monetization models. The impact of artificial intelligence on the prospects and further development of digital commerce business models is analyzed. Originality. The scientific novelty obtained as a result of this research consists in the definition and substantiation of a new factor – added value, which is the main factor influencing the transformation of e-commerce business models into a digital commerce business model, which takes place under the influence of the digital economy. The novelty of the obtained research results in terms of substantiation of added value as a factor of transformation is proven by confirming the hypothesis that the formation of e-commerce business models and their transformation into digital commerce models take place under the influence of digital sources of added value creation.

Bio-inspired Design and Performance Evaluation of Lawnmower Cutter Blade

This study presents a bio-inspired design approach for the engineering applications of agricultural implements, with practical implications for the field. The CAD modeling of bio-inspired serrated lawnmower cutter blades was followed by structural and fatigue analysis with a comparative evaluation of the performance of conventional plain cutter blades. This method involved the bionic transformation of a biological model of the serrated leg of the grasshopper, traced using MATLAB edge detection and image processing software. The solid modeling CAD software for the Bionic Blade lawnmower cutter blade converts this biological model into an engineering model. After designing the geometric shape of the bionic tooth profile's serrated cutting edge, the boundary conditions are evaluated for numerical simulation based on the machine specifications of the conventional lawnmower cutter. After analyzing the power of the motor, the rotational speed, and the torque, the static structural and fatigue analysis was carried out in numerical simulation software to synthesize the performance of the bionic lawnmower cutter blade for engineering analysis of deformation, shear stress, and fatigue life. The bionic design of the blade and conventional plain blades were manufactured using an Amada CO2 laser cutting machine and sheet metal bending processes for Stainless Steel (SS 304) material. The experimental validation of software simulation was carried out by field trials using the Bionic design of a lawnmower cutter blade to evaluate the performance improvement in cutting time and yield of grass cut in kg for 60 to 100 meters distance cutting. After comparing the performance of the plain blade and the design of the bionic blade, there was a reduction in abrasive wear, a 12.87% improvement in the cutting time, and a 14.8% increase in the yield of grass compared to the conventional blade. This performance improvement was attributed to the unique bionic design of serrated cutting-edge and ground clearance. The bio-inspired design approach has immense practical applications in designing agricultural implements, as confirmed by this performance evaluation of this case study of bio-inspired lawnmower cutter blades.

Exploration and innovative application of digital technology in pediatric dentistry

Pediatric dentistry treats patients aged 0-18 years, encompassing the characteristics of general dentistry. The clinical techniques are closely related to restorative dentistry, endodontics, orthodontics, and maxillofacial surgery, while also possessing unique aspects. It particularly focuses on the growth and development patterns of children's dentition and maxillofacial structures. Currently, digital technology has deeply integrated with various clinical disciplines of dentistry, and pediatric dentistry has made significant progress with pediatric-specific digital applications. On one hand, the introduction of mature digital technologies is enabling the digital transformation of pediatric dental treatment models; on the other hand, there is innovative development of new digital technologies tailored to the specific needs of pediatric dental care, filling gaps in the field. Based on years of research in digital technology for pediatric dentistry, our team details the current innovative applications and scientific explorations in this area from these two perspectives. Additionally, we anticipate the potential expansion of digital technologies not yet applied in pediatric dentistry, providing a reference for clinical scholars in the field to conduct exploratory research.

Effectiveness of ethnomathematics-based learning on students’ mathematical literacy: a meta-analysis study

This study aims to determine the effectiveness of ethnomathematics-based learning on students’ mathematical literacy through a meta-analysis study. Primary studies were collected from Google Scholar and ERIC databases based on the inclusion criteria. The results of the literature review obtained 16 studies, either from theses, proceedings, or journal articles. Furthermore, the effect sizes were combined according to the Random Effects Model (REM) and data analysis using CMA v3 and R Studio (Meta Package). The calculation results obtained an overall effect size which indicates that ethnomathematics-based learning has a “strong” effect on students’ mathematical literacy when compared to conventional learning. As a result of the moderator category analysis, it was found that the effect sizes differed significantly according to students’ regional demographics, independent variables, and subject matter. However, it does not show significant differences when based on the duration of the meeting, education level, sample size, experimental design, type and year of publication. Thus, it can be said that ethnomathematics-based learning can be an effective learning model for increasing students’ understanding of mathematical literacy, especially in the Kalimantan Island region, recommended to be integrated with the Ethnomathematics Pop Up Book and Visual Thinking learning model, and Probability & Sets and Transformation Geometry materials, using Nonequivalent Control Group Design are recommended to be taught through this learning model.

Research and Design of Digitally Empowered Teaching Model Transformation

Traditional offline teaching models, particularly in courses like Data Structures and Algorithm Design, struggle to meet the demands of modern education due to limited classroom time, lack of personalized instruction, and insufficient real-time feedback. To address these issues, this paper proposes a digitally empowered teaching model that integrates big data, cloud computing, and artificial intelligence. By extending learning beyond the classroom with online platforms like MOOC, PTA, and Rain Classroom, and using a Student Concentration Analysis System, the deep learning model collects and analyzes data on students' learning behaviors. This enables personalized feedback and dynamic adjustments to teaching content, improving both engagement and learning outcomes. Additionally, a Blockchain-based Student Record System ensures secure data management, making the approach more adaptive, data-driven, and student-centered.

Models2Code: Autonomous model‐based generation to expedite the engineering process

AbstractInsufficient resources and high costs are hindering industrial development, potentially impeding adaptation to market demands. Overcoming this challenge necessitates advancements in software engineering techniques to streamline processes and meet industrial requirements. Crucially, automating manual tasks and enhancing interoperability between engineering stages can yield efficiency gains. This paper presents a model‐based system engineering approach aimed at automating the transition from design to implementation, incorporating autonomous generation and validation features. Implemented as plugins and utilizing model transformation techniques, this solution targets reducing engineering time and facilitating the adoption of new technologies. Developed, implemented, and tested within the Arrowhead framework, the approach is followed by a discussion on its benefits and limitations.

Towards a transformation approach from SecureUML to ‎Alloy

In critical information systems, Role-Based Access Control (RBAC) has been frequently used. The specification of access control policies is an essential step in securing information systems. This article presents a transformative approach for addressing design challenges within these specifications using Model-Driven Architecture (MDA). A method is introduced for specifying and verifying model-based access control (RBAC) rules by combining SecureUML and Alloy, referred to as SecureUML2Alloy. This approach leverages transformation techniques based on metamodels to express the SecureUML source model in the Alloy target model. The SecureUML2Alloy framework allows for the generation of an initial Alloy code that can be extended with facts, functions, and predicates depending on the case. The transformative framework offers a reliable, automated mechanism for verifying security specifications in critical systems, promoting both theoretical and practical advancements in model transformation and formal verification. This method provides a pathway for future automation tools in secure system design and analysis, contributing to the reliability and security of software systems across multiple fields.

Research on the Functions and Obstacles of Rural Social Organizations in Rural Governance from the Perspective of Structural Functionalism

Since the reform and opening up, with the transformation of the national governance model, my country's rural social structure has undergone earth-shaking changes. The multi-center governance subject structure has gradually replaced the traditional single governance subject structure and has become the main model for the management of rural social public affairs in my country. As an important subject in governance activities, rural social organizations play a key role in promoting farmers' collective actions and nurturing grassroots democracy. As an important part of the rural social structure, rural social organizations not only have their structure and functions rooted in the transformation of the social structure, but their changes and development also play an important role in the transformation of the social structure. From the perspective of structural functionalism, analyzing the role and function of rural social organizations in the rural social structure has positive theoretical value and practical significance for achieving the effective fit of the structure and function of rural social organizations and building a benign management order in rural society under the background of the rural revitalization strategy.

Learning protocols for the fast and efficient control of active matter

Exact analytic calculation shows that optimal control protocols for passive molecular systems often involve rapid variations and discontinuities. However, similar analytic baselines are not generally available for active-matter systems, because it is more difficult to treat active systems exactly. Here we use machine learning to derive efficient control protocols for active-matter systems, and find that they are characterized by sharp features similar to those seen in passive systems. We show that it is possible to learn protocols that effect fast and efficient state-to-state transformations in simulation models of active particles by encoding the protocol in the form of a neural network. We use evolutionary methods to identify protocols that take active particles from one steady state to another, as quickly as possible or with as little energy expended as possible. Our results show that protocols identified by a flexible neural-network ansatz, which allows the optimization of multiple control parameters and the emergence of sharp features, are more efficient than protocols derived recently by constrained analytical methods. Our learning scheme is straightforward to use in experiment, suggesting a way of designing protocols for the efficient manipulation of active matter in the laboratory.

Adhesive lipophilic gels delivering rapamycin prevent oral leukoplakia from malignant transformation

Oral leukoplakia (OLK) is the most emblematic oral potentially malignant disorder that may precede the diagnosis of oral squamous cell carcinoma (OSCC) and has an overall malignant transformation rate of 9.8 %. Early intervention is crucial to reduce the malignant transformation rate from OLK to OSCC but the lack of effective local pharmaceutical preparations poses a challenge to clinical management. Rapamycin is speculated to prevent OLK from carcinogenesis and its inherent lipophilicity facilitates its penetration into stratum corneum. Nevertheless, hydrophilic hydrogels frequently encounter challenges when attempting to deliver lipophilic drugs. Furthermore, the oral cavity presents a complex environment defined by oral motor functions, saliva secretion cycles, dynamic fluctuations, and protective barriers comprising mucus and lipid layers. Consequently, addressing issues of muco-penetration and muco-adhesion is imperative for developing an effective drug delivery system aiming at delivering rapamycin to target oral potentially malignant disorders.Here, a dual-function hydrogel drug delivery system integrating adhesion and lipophilicity was successfully developed based on polyvinyl alcohol (PVA) and dioleoyl phosphatidylglycerol (DOPG) via dynamic boronic ester bonds. Rheological experiments based on orthogonal design revealed that PVA-DOPG hydrogels exhibited ideal adhesive strength (around 6 kPa) and could adhere to various surfaces in both dry and wet conditions. PVA-DOPG hydrogels also significantly promoted lipophilic molecules’ penetration into stratum corneum (integrated fluorescence density of 6.95 ± 0.52 × 106 and mean fluorescence depth of 0.96 ± 0.07 mm) of ex-vivo porcine buccal mucosa (p < 0.001). Furthermore, PVA-DOPG hydrogels incorporating rapamycin inhibited malignant transformation of OLK mouse model induced by 4-Nitroquinoline N-oxide (4-NQO), distinct improvements in survival (the neoplasm incidence density at the 40th day is 0.0091) (p < 0.05), decrease in neoplasm incidence density of 36.36 % and inhibition rate in neoplasm volume of 75.04 ± 33.67 % have been demonstrated, suggesting the hydrogels were valuable candidates for potential applications in the management of OLK.

Developing a Workflow for Transforming BIM Models into Immersive Virtual Reality Experiences

Abstract. The integration of Extended Reality (XR) and Building Information Modelling (BIM) has emerged as a promising approach for enhancing interaction with spatial data in the built environment. While the potential of BIM for advanced visualization has been recognized, there remains a need for standardized workflows that facilitate the transformation of BIM models into immersive virtual reality (VR) experiences. This research contributes to the ongoing development of BIM-VR integration by presenting a workflow that leverages Revit, Twinmotion, and Datasmith to create visually rich and interactive VR environments. The established process focuses on enhancing textures, incorporating dynamic lighting and weather simulations, and populating the virtual space with realistic elements. The workflow also addresses the integration of interactable objects to elevate user engagement and the use of cutting-edge VR headsets for an immersive experience. By providing a structured approach to bridging complex BIM data with VR, this research aims to support architects, engineers, construction professionals, and clients in design collaboration, project review, and decision-making across the building lifecycle. The workflow's potential for facilities management and training applications is also explored. Through a case study, the research demonstrates the workflow's effectiveness in facilitating a deeper understanding of architectural spaces before construction, highlighting its potential for improving efficiency and reducing rework. The paper also discusses the challenges and opportunities associated with integrating BIM with GIS and sensor data to create comprehensive digital twins. This research contributes to the growing body of knowledge on BIM-VR integration and underscores the importance of continued development in this field to enhance the design, communication, and experience of the built environment.

The Role of ESG Strategy Implementation in Long-Term Value Creation for Companies

In the context of increasing global focus on sustainable development, companies face new challenges and opportunities in creating long-term value. As a core framework for sustainable development, ESG (Environmental, Social, and Governance) strategies are gradually becoming key factors in enhancing long-term value for businesses. This paper systematically explores the role of ESG strategies in long-term value creation, with a focus on analyzing their impact on financial performance, brand reputation, innovation capability, and emerging market opportunities. Through an in-depth analysis of ESG strategy implementation, this paper reveals new opportunities arising from green finance and investment, sustainable supply chain development, policy support, and digital transformation, and proposes specific application strategies for businesses in these areas. The research findings indicate that ESG strategies can not only optimize financial performance and brand image but also drive technological innovation and business model transformation, thus laying a solid foundation for long-term value creation.

Challenges of student-centered education in China: A Review

This review paper discussed the various challenges faced by Chinese universities in implementing student-centered education. Through an analysis of these challenges, this paper aimed to provide valuable insights for educational decision-makers, university administrators, and educational practitioners, helping them to address these issues systematically and fundamentally. This is not only a transformation of the educational model but also an exploration of cultivating innovative strategies who can adapt to future societal challenges, aiming to contribute to the development of Chinese educational system.

Expert consensus on the application of big data on rehabilitation medicine (2024 edition)

With the development and progress of technology, the transformation of biomedical models, and the application of digital technology, the field of rehabilitation medicine has also generated massive and diversified big data. However, the current level of utilization of rehabilitation medicine is relatively low. Empowering the development of rehabilitation medicine through big data is crucial. In order to better promote the standardized development of rehabilitation big data in China, the Rehabilitation Big Data Working Committee of the Chinese Rehabilitation Medical Association organized an expert plan on the concept, significance, and necessity of rehabilitation big data; Rehabilitation big data source; Priority areas for rehabilitation big data application research; Basic research methods for rehabilitation big data; The standards and principles for establishing a rehabilitation database; Consensus has been developed on six aspects of clinical application scenarios for rehabilitation big data, providing reference for healthcare workers and researchers related to rehabilitation big data.