Systems Research Research Articles

Scientometric review of emissions trading systems (ETS) research worldwide

Scientometric review of emissions trading systems (ETS) research worldwide

Designing research collaboratively: Socioenvironmental systems research in the French Basque Country

Designing research collaboratively: Socioenvironmental systems research in the French Basque Country

Wind Energy Siting Optimization in Fujian Province, China

The geographical distribution and scientific evaluation of wind energy potential are crucial for regional energy planning. Wind energy is a renewable energy that can mitigate climate change. Several open-access World Bank databases and the ESRI (Environmental Systems Research Institute) Global were used to gather and process data through wind energy siting optimization in Fujian Province. This paper uses the fuzzy quantifiers of the multi-criteria decision-making (MCDM) approach in arc geographic information system (ArcGIS Pro) and the analytical hierarchy process (AHP) to handle the associated wind data uncertainties to obtain wind energy technology siting optimization for nine cities in Fujian Province. The converted database options and characteristics used the weighted overlay tool (WOT) to reflect the importance of wind farm project objectives. The sensitivity analysis tested the robustness and resilience of the integrated MCDM design for feasibility or viability. The results revealed that 21.743% of the area of Longyan City is suitable for siting wind energy. Other cities’ suitable areas comprise 14.117%, 12.800%, 5.250%, 4.621%, 4.020%, 4.020%, 3.430%, and 2.300%, respectively (Sanming, Ningde, Quanzhou, Putian, Zhangzhou, Nanping, Xiamen, and Fuzhou cities). Furthermore, a considerable amount of wind power is needed to supply the current primary energy deficit (60.0–84.0%) and satisfy the carbon emission reduction target. Wind farm installation in Fujian province is an opportunity to provide inexhaustible energy, generally affected by generation volume and operational span. Wind power is highly acceptable to local Chinese. Reasonably high understanding and excitement for wind farm investments exist among local authorities. Future research should consider wind data of the identified onshore optimization sites and design wind farms for the respective output power for pessimistic, average, and optimistic scenarios for possible wind farm development. Similarly, the long shoreline of about 1680.0 miles (or 2700.0 km) is a considerable source of offshore wind power prospecting, future research, and energy exploitation and harvesting opportunities.

Transition cow health and management in pasture-based dairy herds: A farmers' survey.

Seasonal-calving pasture-based systems characterize Irish dairy production. During the dry period, cows are housed and offered predominantly grass silage, providing unique transition cow management opportunities. This study aimed to describe transition period disease incidence and management strategies reported by farmers, and to evaluate their associations with herd size and calving pattern to inform and guide research activities and national advisory. An online survey distributed amongst 3,899 Teagasc Technical Dairy Advisory clients yielded 525 responses suitable for analysis. Results are presented for all respondents, by herd size and by the two most common calving systems (spring- [84.3%; 439/521] and split-calving [12.9%; 67/521]). Disease incidence was reportedly highest in cows within their first 3 weeks postpartum (58%; 299/519), in cows calving at the end of the calving season (48%; 245/510) and in multiparous cows (52%; 266/513). Respondents reported treating >3% of their herd for milk fever (23%; 120/521) and retained placenta (13%; 68/518), and <1% of their herd for grass tetany (82.6%; 419/507) and ketosis (72.7%; 368/506). Regarding management, dry cow body condition monitoring (73%; 365/497), dry cow mineral supplementation (61%; 304/497), and Ca supplementation at calving (61%; 314/487) were most commonly reported. Other milk fever prevention strategies supported by research in other production systems were not commonly reported (low K [20%; 101/497] and negative dietary cation-anion difference diet [6%; 31/497]). The odds of reporting keeping records of antibiotic treatment for milk fever were higher (OR = 3.20) for farmers from small compared to large herds. In conclusion, responses to our survey suggest that milk fever is a transition cow health concern in Irish dairy farms. Efforts should be devoted to enhance farmers' uptake of existing research-supported prophylactic strategies for milk fever and to optimize commonly reported management strategies in the Irish dairy production context.

System of Monitoring the Financial Activity of the Enterprise

Monitoring of financial activity is one of the key functions of enterprise management, because it, in particular, ensures control of current costs and income; contributes to the analysis of the financial state of the enterprise; supports planning of future financial flows. The purpose of the article is the research of information systems for monitoring the financial activity of enterprises, the identification of problems of financial activity, the analysis of the ways of using the appropriate software and the development of the system for monitoring the financial activity of enterprises. The research methods are the main methodological approaches and technological tools for the development of financial monitoring systems. Such methods, in particular, are: systematic and comparative analyzes – to identify the peculiarities of the creation of systems for monitoring the financial activity of enterprises; the method of expert assessments, which involves the analysis of literary sources and information resources, conducting interviews and surveys of experts, as well as the processes of development and testing of scalable and high-performance financial monitoring systems. The novelty of the research is the creation of a complex system for monitoring financial activity, which includes an intuitive interface, a flexible database and the ability to generate various reports, giving users the opportunity to effectively manage their financial data, simplifying the process of entering, editing and analyzing information through the use of a stack of modern technologies. The conclusion of the research carried out in the article is that the work was: identified the main problems of monitoring the financial activity of enterprises, which are solved with the help of modern financial monitoring systems; an analysis of existing software solutions was carried out; the advantages and disadvantages of the existing software for monitoring the financial activities of enterprises were analyzed; the main so-called «bottlenecks» of the automation of financial monitoring, which need to be solved, have been identified. On the basis of the conducted analysis, an author’s system for monitoring the company’s financial activity was developed, focused on ease of use and efficiency of financial data management. The development of the software of the author’s system included: the selection of the appropriate technological stack; system architecture development; implementation of basic functional modules (for example, such as transaction management, categories and reports); system database development; system interface development. The results of the conducted research open up new opportunities for improving financial management and making informed decisions based on the received data.

Robert (Bob) T. Fraser (1946-2023).

This article memorializes Robert (Bob) T. Fraser (1946-2023), a dedicated advocate for people with disabilities. Bob's contributions were prolific; he authored or coauthored more than 140 peer-reviewed journal articles and book chapters and coedited five texts. He was awarded Federal grants by the National Institute on Disability, Independent Living, and Rehabilitation Research, the Rehabilitation Services Administration, and the Centers for Disease Control and Prevention. Bob was an integral part of a Traumatic Brain Injury Model Systems research team, specializing in outcomes and cost efficacy of return-to-work interventions (e.g., one-to-one placement, supported employment, and paid coworker as trainer) following moderate-to-severe traumatic brain injury. Highlights of Fraser's career and professional contributions are noted. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

МЕТОДОЛОГІЧНИЙ ІНСТРУМЕНТАРІЙ ДОСЛІДЖЕННЯ ПЕНІТЕНЦІАРНОЇ СИСТЕМИ УКРАЇНИ: ПОНЯТТЯ ТА ЗМІСТ

This article presents the author’s own position regarding the methodology of the study of the penitentiary system of Ukraine, since there is no single point of view in penitentiary science regarding the needs of methodological support for the study of the penitentiary system of Ukraine. The methodology of the study of the penitentiary system of Ukraine is considered by us as the cognitive basis of the subject of research, and therefore we show the methodology as a system that combines: theoretical principles, general scientific and private scientific methods of cognition, combining dialectics, epistemology and logic. It is certain that the research methodology of the penitentiary system of Ukraine is included in the system of scientific knowledge not only of law, but also of pedagogy and psychology. This can be explained by the fact that the knowledge of these sciences fully corresponds to the order and conditions of execution/serving of punishment. European rules and international standards for the treatment of convicts and prisoners are based on this conceptual basis. At the same time, the methodology of the study of the penitentiary system of Ukraine not only creates effective and optimal conditions for learning the content of the object and the subject of the study, but is also necessary for conducting such a scientific search, since this study is designed to accompany the reforms carried out by the Ministry of Justice of Ukraine under the conditions of the legal regime martial law. At the same time, the outlined problems show the existence of methodological approaches in penitentiary science and provide not only recognition of methodological knowledge about the penitentiary system, but also adequate solution of the problems of the criminal-executive direction. Taking into account the fact that the state policy in the field of execution of punishments and probation belongs to complex system objects of research, therefore their complexity, multifacetedness and social nature require a comprehensive study of the methodology of research of the penitentiary system of Ukraine, since it is the methodology in scientific sources that is interpreted differently. Therefore, the methodology of the study of the penitentiary system of Ukraine is carried out by us using general philosophical, general scientific and special legal methods. The combination of different types and levels of methods in the scientific research made it possible to objectively and comprehensively highlight certain aspects of the problems of the penitentiary system of Ukraine in the state mechanism of socialization, resocialization and reintegration of convicts in places of imprisonment of the State Criminal Enforcement Service of Ukraine. Therefore, the understanding of various research methods of the penitentiary system of Ukraine is extremely necessary for future applicants and postgraduate students. After all, for them, knowledge of research methods is a guarantee of quality scientific research of the research subject. The author’s definition of the methodology of the study of the penitentiary system of Ukraine is formulated – it is a pluralistic system of scientific knowledge about the order and conditions of execution/serving of punishment through the use of general scientific, special scientific and individual preventive methods, which can ensure the completeness of the objective penitentiary analysis of the studied subject. Key words: methodology, toolkit, penitentiary system, research, problems, cognition, places of imprisonment, State Criminal Enforcement Service, punishment, personnel.

Study on the Regulatory Model of Cross-border Flows of Personal Data: Chinas Perspective

Personal data has become a crucial component of today's digital economy and trade. In recent years, nations have been proactively investigating the problem of cross-border data flows from a global viewpoint. China has gradually introduced relevant laws and regulations, including the Network Security Law of the PRC and the Personal Information Security Law of the PRC to protect personal information, among which are avenues for resolution that deal with the safeguarding of private information. Despite the internal circumstances in China, it is important to further explore the top-level design system and practical research in this area. This paper uses the literature research method and comparative research method as its main research methods, in accordance with the current views of relevant scholars both domestically and abroad, presents the US and Europe's effective implementation of legislative regulations to control data flow in China, and researches the specific practical issues of the Chinese legal framework governing the transfer of personal data across borders, to help guide how to regulate transnational personal data issues in China.

Understanding user experience, task performance, and task interdependence in symmetric and asymmetric VR collaborations

Asymmetric collaboration is an important topic for the research of multiuser collaborative systems. Previous works have shown that by providing different abilities, devices or content to different users, users can take advantage of the unique features of each side and collaborate effectively with each other. However, there is limited work comparing the differences between asymmetric and symmetric Virtual Reality (VR) collaboration systems. How task complexity may affect symmetric and asymmetric VR collaboration is also unclear. In this paper, we present a comparative study that investigated how user experiences and task performance vary in symmetric and asymmetric VR collaboration. In addition, we also explored how task interdependence correlates with user experience and task performance. Participants were asked to collaboratively perform 3D object selection and manipulation tasks in pairs. A within-subjects study was conducted, where participants used PC and PC, VR and VR, and PC and VR, respectively in three conditions. Our results revealed that the asymmetric collaboration using both PC and VR showed the best results in closeness of relationship, social presence and task performance; the PC symmetric collaborative system showed the worst user experiences and task performance. Both user experience and task performance showed a positive correlation with task interdependence. We discussed the effects of the collaborativ mode and device on the user experience and task performance, and the implications for future symmetric and asymmetric VR collaboration systems.Graphical abstract

The Digital Economy as a Complex System

The digital economy is a complex system, but orthodox economic theory is unable to handle such complexity. For some decades economists have realized that the conventional theoretical models are not consistent with data on what people and institutions actually do, and a new behavioral economics is emerging. The science of complex systems developed over the last 50 years has developed many new ideas and methods for analyzing the non-linear non-equilibrium dynamics of complex systems. Responding to the failures of orthodox economics, those managing the global economy are willing and able to embrace and lead in this new way of looking at economic systems. Thus, economics is evolving and better able to inform decision making in the public and private sectors. This offers new ways of sthinking about the digital economy for entrepreneurs and policy makers which in turn will provide many new example of real-world complexity. The digital economy will drive the creation of future wealth and prosperity, co-evolving with the science of complex systems. We postulate that the research in complex systems will enable better understanding of the digital economy, augment existing economic models and improve their prediction powers.

Orchestrating Digital Resilience: A Clinical IS Study of an Everything-as-a-Service Technology Strategy

ABSTRACT Organisations must build digital resilience to effectively safeguard their business operations against environmental, economic, or socio-political disruptions. One approach involves adaptation – using Information Technology (IT) to design business operations that can withstand and recover from such disruptions. A second approach involves mitigation – using IT to advance environmental, social, or economic objectives that reduce the root causes and likelihood of future disruptions. However, both approaches to building digital resilience are challenging to implement. Our clinical Information Systems (IS) research article examines and reflects on how Beta Bank, an Australian fintech firm, developed an Everything-as-a-Service (EaaS) technology strategy and achieved digital resilience throughout its business operations. We explain how Beta Bank strategically leveraged EaaS to adapt to the significant disruptions caused by the Australian wildfire disaster and the global COVID pandemic of 2019–2021. We then unpack how Beta Bank further leveraged EaaS to enhance its digital resilience via a mitigation approach. Our work delineates a typology of four EaaS pathways for pursuing digital resilience, discusses the scholarly implications of EaaS as a future IS research area, and provides actionable managerial guidance through an EaaS roadmap, a strategic planning tool for those aiming to implement and benefit from this technology strategy.

Learning sites for health systems research: Reflections on five programs in Africa, Asia, and Central America

AbstractIntroductionLearning sites have supported intervention development and testing in health care, but studies reflecting on lessons relating to their deployment for health policy and system research (HPSR) in low‐ and middle‐income settings are limited.MethodsThis experience report draws from learning over three continents and five research and community engagement programs—the oldest starting in 2010—to reflect on the challenges and benefits of doing embedded HPSR in learning sites, and how those have been managed. Its objective is to generate better understanding of their potential and constraints. The report draws from team members' experiential insights and program publications.ResultsChallenges relating to initial engagement in the sites included building and maintaining trust, managing partner expectations, and negotiating priority topics and stakeholders. Once the embedded research was underway, sustaining engagement, and managing power dynamics within the group, supporting all participants in developing new skills and managing rapidly changing settings were important. Finally, the complexity of reflecting on action and assessing impact are outlined, along with potential approaches to managing all of these challenges and the variety of gains that have been noted across the programs.ConclusionsWe highlight the potential of learning sites to develop relationships, capacities, and local innovations which can strengthen health systems in the long term and some lessons in relation to how to do that, including the importance of stable, long‐term funding as well as developing and recognizing facilitation skills among researchers. Supporting spaces for learning is particularly important when health systems face resource constraints and everyday or acute stressors and shocks.

Research and design of multiple gas mixing system in modified atmosphere packaging

Despite the abundant production of fruits and vegetables in Xinjiang, there is an increasing trend in waste rates. Gas-controlled packaging techniques are employed post-harvest to enhance freshness and extend shelf life. However, the multi-gas mixing system at the core of this equipment often encounters challenges such as insufficient stability, limited precision, high costs, and inadequate intelligence. In this context, we have developed and designed a multi-gas mixing system for gas-conditioned packaging. The system integrates Internet of Things technology, uses a programmable controller as the core, proposes a ternary gas distribution model based on the ideal gas equation and Dalton’s law of partial pressures, and utilizes RS-485 bus, TCP/IP protocol, among others. This ensures communication between the equipment and data transmission with the cloud server while enabling remote control of the gas mixing and blending process via a mobile phone terminal. The system runs stably through testing, with the average relative deviations of CO2 and O2 gas concentrations being 0.86% and 0.72%, respectively. This fulfills the technical prerequisites for achieving a gas concentration precision of less than 1%, addressing challenges related to inadequate precision in gas blending, unstable performance, and limited visual representation. Moreover, it significantly reduces equipment costs and operational complexities while serving as a valuable reference for advancing multivariate gas mixing and blending technology in Xinjiang’s fruit and vegetable gas-conditioned packaging.

How different levels of semantic segmentation affect human perception of driving scenes

As automated vehicles continue to advance, teleoperation has emerged as a critical support system for navigating complex and unpredictable environments that exceed the vehicles' current autonomous capabilities. A main issue in the implementation of teleoperation is latency caused by the high bandwidth required to transmit the video feed from the vehicle to the remote teleoperation station. A possible approach for addressing the latency problem is the transfer of lower-resolution or compressed videos between the vehicle and the teleoperation station. When applying semantic segmentation on the video feed, many pixels are mapped to a limited set of possible colors according to the types of objects that they represent. This concept has been commonly used in autonomous driving algorithms and has the potential to enable the transferring of smaller-sized videos thus reducing bandwidth. In this study, we examine how presenting semantically segmented driving scenes to humans affects their perception of the scene, and specifically, how it affects their hazard perception and situation awareness. We conducted two user studies comparing the effects of using different levels and types of semantic segmentation. Our results indicate that viewing partly segmented scenes, such that only a selected set of object types are colored, commonly achieves the same effect, and sometimes even outperforms a realistic view. Our study and its insights may pave the way for future research, development, and design of teleoperation systems of automated vehicles.

An In vitro Caco2‐Based Model for Measuring Intestinal Bioadhesion Comparable to Ex vivo Models

This study presents an in vitro model using Caco‐2 cells that can mimic the bioadhesion properties of the human intestinal epithelium, aiming to reduce the use of animal tissues, in line with the 3Rs principle—replacement, reduction, and refinement. Specifically, a texture analyzer was used to assess the bioadhesive strength of hydrogels (i.e., alginate (Alg), chitosan (Chit), and gelatin (Gel)) under various applied forces (20–200 mN) and contact times (120–420 s). The results demonstrate that the in vitro model effectively predicts the bioadhesive strength of the tested hydrogels to ex vivo tissues (i.e., from mice, sheep, and pigs), including the effects of applied force and contact time. Also provided is an analysis of the effect of microvilli morphology on bioadhesion where an inverse relationship was observed between microvilli linear density and bioadhesion strength, explaining the variability in results across animal models. This Caco‐2‐based model offers a practical, accessible, and cost‐effective alternative to current ex vivo methods used for measuring bioadhesion fracture strength. It can be integrated into standardized testing protocols, providing a more ethical and scientifically robust approach to advancing bioadhesive drug delivery system research.

Engaging stakeholders in embedded newborn health services/systems research in Kenya; a continuous process involving multiple actors.

Background Engaging relevant stakeholders throughout the research cycle is increasingly recognised as critical to conducting quality health systems research. There are few descriptions and analyses of stakeholder engagement in practice for embedded health systems research especially those that must navigate multi-level decentralised health systems. We describe and reflect on the stakeholder engagement activities of an international multi-disciplinary programme of research focused on newborn care in hospitals in Kenya. Methodology Our experienced project stakeholder engagement group coordinated engagement activities across multiple stakeholders with differing interests in the research. We conducted a stakeholder mapping and analysis using an engagement matrix to include national and county-level policymakers, professional communities, associations and regulators, health managers, frontline healthcare workers, patients, families and patient representative groups. Our engagement group maintained a log of engagement activities and had regular programme feedback meetings and discussions. As part of our analysis of stakeholder engagement, we drew on project documents and meeting minutes, and on a conceptual framework which distinguishes between the moral, strategic and practicaldimensions of stakeholder engagement. Results Stakeholder engagement was essential but complex in practice. Although we had significant prior engagement experience and relationships at the hospitals and the counties, introducing new staff into NBUs triggered complexities that required careful consultation along the bureaucracies at the counties. Despite the counties having similar hierarchical architectures, engagement processes varied and achieved different outcomes across counties. There were also multiple officeholder transitions over the research period, occasioned by factors in our external environment, often necessitating engaging afresh. Conclusion Even with a carefully developed stakeholder engagement plan, an experienced team, and a landscape backed by long-term embeddedness, health research stakeholder engagement can unfold in unexpected ways and requires continuous effort, resources, and adaptability. Meeting the moral, strategic, and practical potential of engagement requires flexibility, responsiveness, and commitment, including adequate resources.

Coarse-graining bistability with the Martini force field

An increasing interest in molecular structures whose long-term dynamics resemble those of bistable mechanical systems promotes the search of possible candidates that may operate as two-state switching units. Of particular interest are the systems that are capable to exhibit such bistable effects as spontaneous vibrations, stochastic resonance, and spontaneous synchronization. Previously, in all-atom molecular dynamics simulations, it has been demonstrated that short pyridine–furan springs show these bistable phenomena. In this article, we introduce a coarse-grained model of such springs and investigate the possibility to observe the bistability effects, such as spontaneous vibrations. Our findings allow the studies of short pyridine–furan springs at large time and length scales and open field for further computational research of large bistable systems.

Applicability of soil health assessment dominated by biological indicators in facility agriculture

The minimum data set (MDS) is widely used for soil health index (SHI) assessment, with the selection of indicators being crucial. However, biological indicators are less frequently used compared to physical and chemical indicators. This study aimed to establish a biologically-centered MDS for assessing soil health in tomato facility agriculture in Ningbo. Using biochemical, microbiological, and nematode data from 60 continuous cropping soils, we identified key indicators for the MDS. Principal component analysis revealed a strong correlation between the MDS and the total data set (TDS), with the final MDS including available phosphorus, electrical conductivity, β-glucosidase, urease, bacterial Chao1 index, bacterial Shannon index, Ralstonia solanacearum, nematode Shannon index, structure index, and channel index. Random forest modeling showed that the predicted SHI had a high fit with the MDS-SHI, with bacterial and nematode Shannon indices being the most influential predictors, emphasizing the critical role of biological communities in maintaining soil health. Furthermore, the study identified three distinct phases in soil health during long-term continuous cropping: healthy (0–10 years), sub-healthy (11–15 years), and recovery (16–20 years), demonstrating the soil's potential for self-recovery. By incorporating biodiversity as a core component, this biologically-focused MDS provides a more comprehensive and precise method for evaluating soil health in facility agriculture. The findings suggest that this MDS could inform future research and applications in similar agricultural systems. Moreover, the results highlight the vital role of biodiversity in agroecosystem stability, suggesting that future soil health assessments should place greater emphasis on biological indicators to better capture the complexity of soil functions.

МОЖЛИВОСТІ ТА ОБМЕЖЕННЯ ВЕЛИКИХ МОВНИХ МОДЕЛЕЙ

The work is dedicated to the study of large language models (LLMs) and approaches to improving their efficiency in a new service. The rapid development of LLMs based on transformer architecture has opened up new possibilities in natural language processing and the automation of various tasks. However, fully utilizing the potential of these models requires a thorough approach and consideration of numerous factors. A review of the evolution of large language models was conducted, highlighting leading companies engaged in the research and development of efficient systems. The structure of these models and ways of representing internal knowledge were examined. Key approaches to training were described, including data collection, preprocessing, and selecting appropriate neural network architectures used in large language models. It was noted that the greatest breakthrough was achieved with the Transformer neural network, which is based on the attention mechanism. A comparison of popular transformer-based chatbots was presented, namely: ChatGPT, Claude AI, and Gemini AI. Their metrics, capabilities, and limitations were identified. The relevance of the topic lies in the rapid development of natural language processing technologies and the growing demand for large language models across various industries. The effective use of these models has tremendous potential to improve productivity and the quality of work with textual data. However, due to the complexity of the architecture and the large amounts of data required for training, selecting and configuring the optimal model for a specific task is a challenging process. As a result of the study, recommendations for developers were provided on the use of popular open-source models in the new service or integration with third-party programs. The characteristics of the models, their strengths, limitations, and certain caveats regarding trust in the generated results were indicated. Keywords: large language models, transformer architecture, neural networks, chatbot, content generation.

Design and Research of High-Performance Optical Bus Control System

Design and Research of High-Performance Optical Bus Control System