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The monitoring of patients with dementia who receive comprehensive care in day centers allows formal caregivers to make better decisions and provide better care to patients. For instance, cognitive and physical therapies can be tailored based on the current stage of disease progression. In the context of day centers of the Mexican Federation of Alzheimer, this work aims to design and evaluate Alzaid, a technological platform for assisting formal caregivers in monitoring patients with dementia. Alzaid was devised using a participatory design methodology that consisted in eliciting and validating requirements from 22 and 9 participants, respectively, which were unified to guide the construction of a high-fidelity prototype evaluated by 14 participants. The participants were formal caregivers, medical staff, and management. This work contributes a high-fidelity prototype of a technological platform for assisting formal caregivers in monitoring patients with dementia considering restrictions and requirements of four Mexican day centers. In general, the participants perceived the prototype as quite likely to be useful, usable, and relevant in the job of monitoring patients with dementia (p-value < 0.05). By evaluating and designing Alzaid that unifies requirements for monitoring patients of four day centers, this work is the first effort towards a standard monitoring process of patients with dementia in the context of the Mexican Federation of Alzheimer. [ABSTRACT FROM AUTHOR]

Background and Objectives: The increasing speed of environmental changes and the intensification of competition among organizations have caused organizations to seek solutions for greater flexibility in responding to environmental needs and changes. In fact, moving towards creating organizations that have a high degree of flexibility in adapting to a changing environment is a vital and effective solution. One of the effective factors in keeping pace with changes in the environment is the improvement of organizational performance. In this regard, the importance and attention to the development, and improvement of human resources leads to the improvement of organizational performance. There are various strategies and methods for the development and improvement of human resources. One of the ways to develop and improve human resources is coaching. In fact, coaching has created a new approach to staff learning and development. Since information technology is a link among all modern sciences and determines the development of human resources, it has created a new concept in coaching. This research focuses on coaching and information technology. In fact, the purpose of this study is to design a prototype of coaching software as one of the tools to optimize the performance of human resources and ultimately improve organizational performance . Methods: The information of this study was obtained using a mixed approach. The mixed approach benefits from two parts, namely qualitative and quantitative, to achieve the research result. Therefore, the present study used the phenomenological method in the qualitative part and the survey method in the quantitative part. The research instruments in the qualitative part was the focus group method. In the quantitative part of the research, a researcher-made questionnaire was used to collect the information. The statistical population of the study in the qualitative section were specialists in the field of education and human resources, from among them 10 people were selected using the method of snowball sampling. The statistical population of the study in the quantitative part were the top managers of Mashhad Power Distribution Company. From this statistical population, the top managers of the western part of the company, which included 20 people, were selected to perform a usability test . Findings: The data obtained from the qualitative part of the research included 4 components for designing the coaching software, which was based on the prototype model of software development. The data obtained from the research were quantitatively analyzed by SPSS software. Quantitative data analyzed by the software showed that the aforementioned software has the required usability to be implemented in organizations and used by individuals . Conclusion: The present study with laying emphasis on reducing the generation gap between managers and current employees and the individuals who will be employed in the organization and also; and with laying emphasis on technology design by education and human resources experts and examining the existing human resources software, sought to design a prototype of coaching software with features such as communication, cognition, problem facilitation process and problem coping, belief in the ability of individuals and motivational dimensions, and implementation of the selected solution and 360-degree evaluation. The aforementioned features were not seen in the Iranian software examined in the study. In addition to the above features, the distinguishing feature of the aforementioned software is attention to the Cohen and Bradford coaching model, and being process-oriented and feedback-oriented. [ABSTRACT FROM AUTHOR]

Background: Internal evaluations (IEs) are associated with various obstacles, including time consumption, high study costs, and extensive data analysis, requiring some educational groups (EG). Therefore, it is essential to provide a suitable solution to overcome these obstacles. Objectives: This study aimed to design and use Internal Evaluation Analysis Software for basic science educational groups (IESEG) at Kermanshah University of Medical Sciences (KUMS). Methods: This study tried to implement all the procedures necessary to conduct the IE of Basic sciences EGs in a particular software format. For this purpose, the MATLAB programming environment and its graphical interface were used for implementation after preparing the necessary standard procedures. The evaluation of the designed software, IESEG, was performed based on the results of several EGs by traditional (manual) and new software approaches. Results: Internal Evaluation Analysis Software for basic science educational groups showed that the calculation errors were reduced to zero during the IE process with the software compared to the manual method. In addition, the designed software could draw graphs and related tables to display the evaluation results. Conclusions: The use of designed software, IESEG, creates a systematic, uniform, and regular method of conducting IE. In addition, speeding up the IE and providing an accurate analysis are the benefits which increase the capabilities of the internal evaluation committees of EGs. [ABSTRACT FROM AUTHOR]

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The rapid development of technology in today's times make business' survival a rather complex task. It is therefore necessary for the specialized organization and administration of each company to differentiate and strengthen its competitive advantages. Gamification is an established practice in many business domains and can enforce employees to engage in business processes and change aspects of their behavior. Even though numerous gamification patterns that are described in literature have been used so far by businesses to various working environments, the outcomes were not the best possible that we would expect in terms of their right utilization to business non-game contexts. Thus, there is need for concise gamification patterns that can offer right guidance to game designers in business. Gamification design patterns can provide a distilled knowledge of techniques of how to design object-oriented software. This paper aims to address this gap in existing literature by describing new gamification design patterns, classifying them according to specific criteria and providing new information to this research domain. Our study is a descriptive literature review and is based on review of previous works. This descriptive literature review tries to give a better understanding by proposing new gamification design patterns in the continuously evolving research domain of gamification design patterns [ABSTRACT FROM AUTHOR]

Agile software development is immensely popular in the industry, but most teams struggle to sustain its use. Human factors like management support, agile training, agile mindset, and team resilience are often neglected, hindering long-term success. However, research has not explored their underlying mechanisms in depth. Therefore, this study examines if management support impacts the sustained usage of agile methodologies within software development teams. It subsequently investigates the individual and serial mediating effects of agile training, the agile mindset, and team resilience on this relationship. Additionally, it compares the importance and performance of management support, agile training, the agile mindset, and team resilience in infusing agile practices. Finally, it determines these antecedents' necessity for the enduring success of agile application. Data collected from 391 agile software development professionals using a structured questionnaire. Partial-least-squares structural equation modelling, importance-performance map analysis and necessary condition analysis were used to investigate relationships. The findings underscore the pivotal role of management support in infusing agile practices. Agile training, mindset, and team resilience emerge as critical mediators, with a strong serial mediation effect. While management support is paramount, its practical implementation falls short within teams. All four antecedents are found to be necessary for optimal agile sustainment. Thus, this study significantly advances theoretical understanding by introducing a serial mediation model that elucidates their mechanisms in impacting agile infusion. It extends prior organisational-level findings to the team-level. The study's quantitative verification of qualitative findings strengthens their generalisability to a broader spectrum of teams. It pioneers in expounding the constructs' relative importance, performance and necessity, to offer actionable insights for agile practitioners. Finally, it provides methodological guidance to apply importance performance map analysis and necessary condition analysis in agile software development research., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2025 Wijesinghe et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

To improve mental health, diverse mobile applications (apps) have been developed to target those who actively use smartphones and in-phone apps. In this vein, this study developed a mobile app, eRAPPORT, to prevent suicide using ecological momentary assessment and intervention. A brief literature review and mobile app market search were conducted to determine the app's content and modality. The design and contents of eRAPPORT were developed through consulting with contextual and methodological experts for end-users' need assessment and technician review. For implementation, an experienced mobile app developer collaborated with the research team to create the app, which includes a safety plan, a feature to track suicidal risk and mental health status, evidence-based information from international and national authorised organisations, an outreach service with online/offline counselling and pop-ups displaying emergency contacts. Twenty-five general adults participated in the feasibility study. After using eRAPPORT for a month, they completed a self-reported questionnaire, followed by an in-depth interview of functionality, acceptability and safety. Both quantitative and qualitative evaluations assured the moderate level of usability and acceptability due to some features that should be improved before applying those with a high risk of suicide. No critical adverse event was reported. Thus, this eRAPPORT feasibility study provides fundamental information to describe the patient-centred processes on how to develop a mobile app for suicide prevention. Further study will be conducted to test the app's effectiveness and determine the application in clinical practice for monitoring and preventing suicide risk by collecting real-time and longitudinal data., (© 2025 The Author(s). International Journal of Mental Health Nursing published by John Wiley & Sons Australia, Ltd.)

Since the COVID-19 pandemic, considerable advances have been made to improve epidemic preparedness by accelerating diagnostics, therapeutics, and vaccine development. However, we argue that it is crucial to make equivalent efforts in the field of outbreak analytics to help ensure reliable, evidence-based decision making. To explore the challenges and key priorities in the field of outbreak analytics, the Epiverse-TRACE initiative brought together a multidisciplinary group of experts, including field epidemiologists, data scientists, academics, and software engineers from public health institutions across multiple countries. During a 3-day workshop, 40 participants discussed what the first 100 lines of code written during an outbreak should look like. The main findings from this workshop are summarised in this Viewpoint. We provide an overview of the current outbreak analytic landscape by highlighting current key challenges that should be addressed to improve the response to future public health crises. Furthermore, we propose actionable solutions to these challenges that are achievable in the short term, and longer-term strategic recommendations. This Viewpoint constitutes a call to action for experts involved in epidemic response to develop modern and robust data analytic approaches at the heart of epidemic preparedness and response., Competing Interests: Declaration of interests This Viewpoint was written by the attendees of a workshop held in December, 2022, hosted by Epiverse-TRACE at the Wellcome Trust (London, UK). Epiverse-TRACE is funded by Data.org, which is supported by The Rockefeller Foundation and Mastercard Center for Inclusive Growth. Data.org is also supported by the Wellcome Trust and the International Development Research Centre (IDRC). The authors of this study have not been paid to write this article by a pharmaceutical company or other agency. CTC received funding from Data.org. AC received funding from the UK National Institute of Health Research, UK Medical Research Council, Pfizer, and the Academy of Medical Sciences. ZMC received funding from the Ministry of Science and Technology of Colombia via the AGORA Research Grant and the IDRC via the TRACE-LAC Research Grant; a research grant for enhancing tools for response, analytics, and control of epidemics in Latin America and the Caribbean (Project ID 109848); a mathematical modelling and development of epidemiological analysis, estimates, and projections for priority public health diseases in the Americas region grant; and support for attending meetings and travel from WHO, Pan American Health Organization, and The Lancet Commission. AYB received funding from Medecins Sans Frontières. CC is supported by ETH Zurich and the Centers for Disease Control and Prevention. JAL received funding from Pfizer. JT received funding from the Yeotown Scholarship, awarded by New College, Oxford. DSQ received funding from the Pontificia Universidad Javeriana. AFS received funding from Epiverse-TRACE to attend meetings and travel. AJK received funding from the Wellcome Trust and Data.org. All other authors declare no competing interests., (Copyright © 2025 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background: Primary intracranial germ cell tumors (iGCTs) are highly malignant brain tumors that predominantly occur in children and adolescents, with an incidence rate ranking third among primary brain tumors in East Asia (8%-15%). Due to their insidious onset and impact on critical functional areas of the brain, these tumors often result in irreversible abnormalities in growth and development, as well as cognitive and motor impairments in affected children. Therefore, early diagnosis through advanced screening techniques is vital for improving patient outcomes and quality of life., Objective: This study aimed to investigate the application of facial recognition technology in the early detection of iGCTs in children and adolescents. Early diagnosis through advanced screening techniques is vital for improving patient outcomes and quality of life., Methods: A multicenter, phased approach was adopted for the development and validation of a deep learning model, GVisageNet, dedicated to the screening of midline brain tumors from normal controls (NCs) and iGCTs from other midline brain tumors. The study comprised the collection and division of datasets into training (n=847, iGCTs=358, NCs=300, other midline brain tumors=189) and testing (n=212, iGCTs=79, NCs=70, other midline brain tumors=63), with an additional independent validation dataset (n=336, iGCTs=130, NCs=100, other midline brain tumors=106) sourced from 4 medical institutions. A regression model using clinically relevant, statistically significant data was developed and combined with GVisageNet outputs to create a hybrid model. This integration sought to assess the incremental value of clinical data. The model's predictive mechanisms were explored through correlation analyses with endocrine indicators and stratified evaluations based on the degree of hypothalamic-pituitary-target axis damage. Performance metrics included area under the curve (AUC), accuracy, sensitivity, and specificity., Results: On the independent validation dataset, GVisageNet achieved an AUC of 0.938 (P<.01) in distinguishing midline brain tumors from NCs. Further, GVisageNet demonstrated significant diagnostic capability in distinguishing iGCTs from the other midline brain tumors, achieving an AUC of 0.739, which is superior to the regression model alone (AUC=0.632, P<.001) but less than the hybrid model (AUC=0.789, P=.04). Significant correlations were found between the GVisageNet's outputs and 7 endocrine indicators. Performance varied with hypothalamic-pituitary-target axis damage, indicating a further understanding of the working mechanism of GVisageNet., Conclusions: GVisageNet, capable of high accuracy both independently and with clinical data, shows substantial potential for early iGCTs detection, highlighting the importance of combining deep learning with clinical insights for personalized health care., (©Yanong Li, Yixuan He, Yawei Liu, Bingchen Wang, Bo Li, Xiaoguang Qiu. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 30.01.2025.)

Background: Since 2015, the Complex Reviews Synthesis Unit (CRSU) has developed a suite of web-based applications (apps) that conduct complex evidence synthesis meta-analyses through point-and-click interfaces. This has been achieved in the R programming language by combining existing R packages that conduct meta-analysis with the shiny web-application package. The CRSU apps have evolved from two short-term student projects into a suite of eight apps that are used for more than 3,000 h per month., Aim: Here, we present our experience of developing production grade web-apps from the point-of-view of individuals trained primarily as statisticians rather than software developers in the hopes of encouraging and inspiring other groups to develop valuable open-source statistical software whilst also learning from our experiences., Key Challenges: We discuss how we have addressed challenges to research software development such as responding to feedback from our real-world users to improve the CRSU apps, the implementation of software engineering principles into our app development process and gaining recognition for non-traditional research work within the academic environment., Future Developments: The CRSU continues to seek funding opportunities both to maintain and further develop our shiny apps. We aim to increase our user base by implementing new features within the apps and building links with other groups developing complementary evidence synthesis tools., Competing Interests: Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Background: In medical imaging, 3D visualization is vital for displaying volumetric organs, enhancing diagnosis and analysis. Multiplanar reconstruction (MPR) improves visual and diagnostic capabilities by transforming 2D images from computed tomography (CT) and magnetic resonance imaging into 3D representations. Web-based Digital Imaging and Communications in Medicine (DICOM) viewers integrated into picture archiving and communication systems facilitate access to pictures and interaction with remote data. However, the adoption of progressive web applications (PWAs) for web-based DICOM and MPR visualization remains limited. This paper addresses this gap by leveraging PWAs for their offline access and enhanced performance., Objective: This study aims to evaluate the integration of DICOM and MPR visualization into the web using PWAs, addressing challenges related to cross-platform compatibility, integration capabilities, and high-resolution image reconstruction for medical image visualization., Methods: Our paper introduces a PWA that uses a modular design for enhancing DICOM and MPR visualization in web-based medical imaging. By integrating React.js and Cornerstone.js, the application offers seamless DICOM image processing, ensures cross-browser compatibility, and delivers a responsive user experience across multiple devices. It uses advanced interpolation techniques to make volume reconstructions more accurate. This makes MPR analysis and visualization better in a web environment, thus promising a substantial advance in medical imaging analysis., Results: In our approach, the performance of DICOM- and MPR-based PWAs for medical image visualization and reconstruction was evaluated through comprehensive experiments. The application excelled in terms of loading time and volume reconstruction, particularly in Google Chrome, whereas Firefox showed superior performance in viewing slices. This study uses a dataset comprising 22 CT scans of peripheral artery patients to demonstrate the application's robust performance, with Google Chrome outperforming other browsers in both the local area network and wide area network settings. In addition, the application's accuracy in MPR reconstructions was validated with an error margin of <0.05 mm and outperformed the state-of-the-art methods by 84% to 98% in loading and volume rendering time., Conclusions: This paper highlights advancements in DICOM and MPR visualization using PWAs, addressing the gaps in web-based medical imaging. By exploiting PWA features such as offline access and improved performance, we have significantly advanced medical imaging technology, focusing on cross-platform compatibility, integration efficiency, and speed. Our application outperforms existing platforms for handling complex MPR analyses and accurate analysis of medical imaging as validated through peripheral artery CT imaging., (©Mohammed A. AboArab, Vassiliki T. Potsika, Alexis Theodorou, Sylvia Vagena, Miltiadis Gravanis, Fragiska Sigala, Dimitrios I. Fotiadis. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 09.12.2024.)

User interface is an essential element of an information system from the user perspective. The use of text in the user interface presents a challenge to some users, such as illiterate, elderly, non-local language speakers, or users with any disabilities. Numerous studies have proposed text-free user interfaces based on non-textual aids such as pictograms, audio, video, or specialized hardware. Such rich elements in the user interface have implications for an information system’s storage and processing requirements. We propose using concept hierarchies to present a dynamic interface to a user based upon user characteristics. A drill-down approach may present more specific interface elements to a user, and a roll-up scheme can identify more generalized interface elements. The proposed scheme can be used to manage internal data of large user interfaces with a rich set of features more effectively as it is computationally inexpensive than sequential processing techniques. We also explore various physical and psychological characteristics of elements and evaluate user preference for them. The results of a survey of 200 respondents show that users consider the use of various colors, alignments, mental models, and look & feel to be essential criteria in interface design. We also conclude that size of interface elements and the use of characters for expressing emotions are significantly important characteristics in interface design. The future work will apply the proposed scheme to a full spectrum of applications ranging from enterprise systems to mobile applications.

It is becoming common practice to push interactive and location-based services from remote datacenters to resource-constrained edge domains. This trend creates new management challenges at the network edge, not least to ensure resilience. These challenges now need to be investigated and overcome. In this paper, we explore the use of open-source programmable asset orchestration at edge cloud systems to guarantee operational resilience and a satisfactory performance level despite system incidents such as faults, congestion, or cyber-attacks. We discuss the design and deployment of a new cross-level configurable solution, Resilient Edge Cloud Systems (RECS). Results from appropriate tests made on RECS highlight the positive effects of deploying novel service and resource management algorithms at both data and control planes of the programmable edge system to mitigate against disruptive events such as control channel issues, service overload, or link congestion. RECS offers the following benefits: i) the switch automatically selects the standalone operation mode after its disconnection from the upper-level controllers; ii) deployment of edge virtualized services is made, according to client requests; iii) the client requests are served by edge services and the related traffic is balanced among the alternative on-demand routing paths to the edge location where each service is available for its clients; iv) the TCP traffic quality is protected from unfair competitiveness of UDP flows; and v) a set of redundant controllers is orchestrated by a top-level multi-thread cluster manager, using a novel management protocol with low overhead.

Software modeling is a creative activity in which software components and their relationships are identified based on customer requirements. Based on the literature, object-oriented software modeling is based on four fundamental pillars which are abstraction, encapsulation, decomposition, and inheritance. However, despite the existence of guidelines and recommendations for implementing the object-oriented approach, novice software designers do not make good design decisions, leading to inefficient designs that cannot be modifiable, understandable, or user-friendly distribute at the development level. The literature reveals that the most common difficulties faced by software designers is a lack of understanding and confusion of concepts related to the object-oriented approach, as well as difficulties in creating Unified Modeling Language diagrams, especially class diagrams. The work presented in this article uses a qualitative and quantitative approach to determine, in a group of university students, what are the most recurrent difficulties and their persistence during the time. The qualitative case study is the method that allowed to generate the documents: diagnostic and evaluation tests. Additionally, a thematic analysis was used to identify, analyze and report patterns within the data. In order to know the occurrences of the problems in the case study, as part of our quantitative approach, a comparative study was applied to compare the results obtained between the diagnostic and evaluation tests and thus establish the similarities and differences among the cases observed, through the hierarchical clustering technique. The findings of this study show us 16 difficulties identified after the qualitative analysis, while the quantitative analysis shows us the number of occurrences and their persistence over time. The difficulties reported in both analyzes focus on these three difficulties: a) Definition of attributes that could be a class, b) Classes with inadequate or insufficient behavior and, c) Incorrect use of multiplicity between classes. Each of these difficulties is analyzed in depth in this study.

Heuristics-based anti-phishing systems are the most deployed solutions in cyberspace. This is due to their generalization feature which is capable of preventing zero-day attacks. However, this promising anti-phishing countermeasure is faced with the problem of managing the feature corpus for scale and complexity. In addition, managing the redundant feature during an upgrade is another factor. In this paper, an incremental component system is proposed to this problem. The proposed framework consists of atomic units and composite units. These units provide encapsulations through which feature corpus is built with ease of management and upgrade. The scheme provides both generic and specific frameworks for designing an anti-phishing scheme with effective management of feature vectors. Therefore, maintenance and updates can be integrated without the total collapse of the system. Hence, the proposed framework can be described as being fault tolerant.

Applications architecture is the baseline of any organizational activity, which main goal is to provide the executional environment for business processes in order to deliver products or services to satisfy customer needs and generate revenue. Nowadays, large software engineering projects always begin with the architecture design phase, despite the waterfall or agile methodology is used by a software development team. Applications architecture design is the most important and, at the same time, error-prone stage of the whole software engineering project. It is well-known that design shortcomings made on the design phase may increase drastically to testing and maintenance phases. Further costs to defects fixing may be hundred times higher in the later project stages in compare to the design stage on which applications architecture is defined. Common system design solutions, which were proven on practice and used in many projects, are known as architectural patterns. Software architecture patterns are considered as building block for system implementation. The most popular and efficient way to share architectural patterns are graphical models that used as any other blueprints of engineering solutions. Applications architecture models are built to represent system design, whereas, such models are already based on certain patterns as the industry best practices. Hence, in this paper we consider a relevant problem of applications architecture models analysis, which relevance is defined by those fact that designed blueprints of information systems and other software solutions should be carefully checked for all presumable inefficiencies in order to avoid extra efforts and related costs for defects fixing in the later project stages. It is proposed to use ArchiMate enterprise architecture modeling language, since it can be used not only to represent applications architecture, but is connection to business and technology layers. In order to evaluate applications architecture models, respective ArchiMate metamodel is considered and represented as labeled directed graph, and coupling software metric is selected for analysis. Sample calculations are demonstrated, obtained results are discussed, conclusion and future work directions are formulated.

Purpose. Nowadays, it is difficult to imagine a person who would not use a smartphone. The main direction in creating many applications are such operating systems as iOS and Android. One of the essential stages of the life cycle of cross-platform applications for iOS and Android is building architecture. It is important not only to be able to build an architecture using well-known «tools», but also to understand to which extent this should be implemented and what impact it will have on the software product in the future. The aim of the work is to analyze approaches to development with excessive or insufficient use of design principles and templates, as well as analysis of the results of the final product, cross-platform software for iOS and Android operating systems. Methodology. To improve the existing software, a static analyzer has been designed and implemented, which is focused on the development of architecture in software of different sizes and types. Only the necessary templates and design approaches which allowed implementing the necessary functionality without complicating the system and guarantee easy support, testing and extension of functionality if it is needed, were used to create the software product. Findings. During the experiments, it was found that when designing cross-platform software for iOS and Android operating systems, not only neglect of patterns and common design approaches, but also their excessive use complicates the development, expansion, maintenance and testing of software. Originality. The extent and consequences of using the design templates, the benefits and examples of using the patterns and approaches in the design of cross-platform applications were determined. For the first time, the necessary degree of use of design templates for mobile applications of different sizes and purposes was analyzed. Practical value. The results of the work will allow the programmer to better understand the principles of designing the applications for iOS and Android operating systems, as well as the conditions of use of the known design templates. The information obtained can be used by teachers of higher education institutions as a means of providing practical examples and demonstrations for higher education students in performing practical work and programmers on real commercial projects.

The macro–micro-coupling tool (MaMiCo) is an open source C++ research software framework, designed to create molecular-continuum flow simulations in a modular way, i.e. with exchangeable solvers. It can be used to couple discrete particle dynamics codes with computational fluid dynamics solvers while retaining performance, especially for parallel execution on supercomputers. We present a new version of MaMiCo that extends its functionality by a multitude of new features, notably with dynamic handling of molecular dynamics simulation instances, automated error estimation, coupling interfaces to the community codes ls1 mardyn and OpenFOAM, a Python interface, support for machine learning modules and enhanced two-way coupling.These features of the new MaMiCo version impact several fields of computational science and can be employed to tackle open research questions in the future, such as efficient multiscale numerical simulation of multi-phase flows, or fault tolerance of coupled simulations on large-scale cluster systems.

Agricultural vehicles, such as tractors, combines, and harvesters, are following the trend of commercial vehicles with a transition from diesel to electric propulsion. Seen as an integrated system, a full-electric tractor is a complex machine with many systems that have to be interconnected for efficient functionality; thus, the need for a central control unit arises. The purpose of this article is to present an electronic control unit that interconnects the powertrain, the hydraulic systems, and the auxiliary systems of a full-electric tractor, with an emphasis on optimization through software design. The article describes the hardware of the electronic control unit and the software state diagrams necessary to implement the functions required by the electric tractor. The results of this article show how, through software optimization, the performances of the tractor can be improved, with parameters such as the response time of the various equipment being a useful indicator of such an improvement. Furthermore, the implementation of trip memory and an easy-to-use human–machine interface allows for easy diagnostic of the electric tractor.

Graph convolutional networks (GCNs) have become a powerful deep learning approach for graph-structured data. Different from traditional neural networks such as convolutional neural networks, GCNs handle irregular input graph data, and GCNs are both computation-bound and memory-bound. How to efficiently utilize the underlying computation and memory resource becomes a critical issue. The emerging 3D-stacked computation-in-memory (CIM) architecture can reduce the data movement between computing logic and memory, thereby presenting a promising solution for the processing of GCNs. An unsolved key challenge is how to allocate GCNs to take advantage of fast near-data processing of the 3D-stacked CIM architecture. This article presents GCIM, a software–hardware co-design approach to exploit the efficient processing of GCNs on the CIM architecture. At the level of hardware design, GCIM integrates lightweight computing units near memory banks to fully exploit bank-level bandwidth and parallelism. At the level of software design, a locality-aware data mapping algorithm is proposed to partition the input graph and achieve workload balancing. GCIM is evaluated through a set of representative GCN models and standard graph datasets. The experimental results show that GCIM can significantly reduce the processing latency and data movement overhead compared with representative schemes. [ABSTRACT FROM AUTHOR]

Developers of the many promising quantum computing applications that currently exist are urging companies in many different sectors seriously consider integrating this new technology into their business. For these applications to function, not only are quantum computers required, but quantum software also. Accordingly, quantum software engineering has become an important research field, in that it attempts to apply or adapt existing methods and techniques (or propose new ones) for the analysis, design, coding, and testing of quantum software, as well as playing a key role in ensuring quality in large-scale productions. The design of quantum software nevertheless poses two main challenges: the modelling of software quantum elements must be done in high-level modelling languages; and the need to further develop so-called "hybrid information systems", which combine quantum and classical software. To address these challenges, we first propose a quantum UML profile for analysing and designing hybrid information systems; we then demonstrate its applicability through various structural and behavioural diagrams such as use case, class, sequence, activity, and deployment. In comparison to certain other quantum domain-specific languages, this UML profile ensures compliance with a well-known international standard that is supported by many tools and is followed by an extensive community. [ABSTRACT FROM AUTHOR]

Copyright of Smart Rail Transit is the property of Smart Rail Transit Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of East China University of Science & Technology is the property of Journal of East China University of Science & Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)