Adaptive Tool Research Articles

СУЧАСНІ КОНЦЕПЦІЇ ТА ІНСТРУМЕНТИ АДАПТАЦІЇ ОРГАНІЗАЦІЙНИХ МОДЕЛЕЙ УПРАВЛІННЯ ЗОВНІШНЬОЕКОНОМІЧНОЮ ДІЯЛЬНІСТЮ

Introduction. In conditions of market destabilization, there is a growing need to define effective concepts and tools for adapting organizational models of foreign economic activity management in the context of increasing digitalization and increasing instability of the world economy. Changing regulatory conditions, rapid technological breakthroughs and increased competition require enterprises to be flexible and innovative. This is of particular importance for Ukrainian enterprises that are integrating into global markets. All this determines the relevance of defining effective approaches to increasing their competitiveness, efficiency and sustainability. The purpose of the article. The purpose of the study is identification of effective concepts and tools for adapting organizational models of foreign economic activity management to changes in the external environment, which ensure flexibility, competitiveness and sustainable development of the enterprise Methods. The research methodology is based on a comprehensive approach, including the analysis of scientific sources, economic data and modern approaches to the adaptation of foreign economic activity management. Comparative analysis methods were used to assess the effectiveness of organizational models, a systems approach to identify key adaptation tools, as well as modeling methods to develop recommendations. Particular attention is paid to the analysis of innovative technologies, such as artificial intelligence, blockchain and big data, to improve management efficiency. Results. The article examines modern concepts and tools for adapting organizational management models to the challenges of foreign economic activity. The impact of globalization, digitalization, and geopolitical instability on the efficiency of enterprises operating in international markets is examined. Key approaches to adapting foreign economic activity management models are analyzed, including decentralization, customer orientation, and integration of innovative technologies. Practical tools for increasing organizational flexibility and improving the decision-making process are identified. The problems faced by Ukrainian enterprises in the process of integration into global value chains are investigated. The need to develop adaptive organizational models that meet the principles of sustainable development is proven. The need to support the competitiveness and efficiency of Ukrainian enterprises in a dynamic global economic environment is identified. Conclusions. The importance of adapting organizational models of foreign economic activity management to ensure the competitiveness of enterprises in a globalized environment has been proven. It has been determined that the introduction of innovative technologies and flexible management structures will contribute to increasing the efficiency and integration of Ukrainian enterprises into world markets.

WHO public health laboratories webinar series – an online platform to disseminate testing recommendations and best practices during health emergencies

Laboratories play a central role in managing public health emergencies. The COVID-19 pandemic imposed unique challenges on global laboratory systems, including testing protocol uncertainties, supply shortages, rapid need for information dissemination, and disruptions to traditional training methods. In response, the WHO established the Public Health Laboratories (PHL) knowledge sharing webinar series whose goals were to respond to the increased demand in up-to-date and reliable information, which WHO is in a unique position to provide. It also aimed to enhance peer-to-peer exchanges across laboratories. This article outlines the PHL webinar series delivery format and presents how the webinar series was received and perceived by participants and how it evolved to support the response to other health emergencies. Contents of the knowledge sharing sessions, as well as attendance, participants’ satisfaction and application of learning were monitored over time using registration forms, satisfaction polls, an annual survey and focus group discussions. From May 2020 to December 2023, 48 sessions attracted 58,688 registrations from 204 countries and territories. Thirty-five sessions featured presentations of WHO guidance, tools or documents and 39 sessions featured country experience sharing. Initially focused on COVID-19, the series became a tool to rapidly disseminate guidance and best practices during new health emergencies and to address cross-cutting topics relevant to the laboratory workforce. Feedback data shows participants found the webinars very useful (86% respondents), reporting knowledge gains in biosafety, quality management, and laboratory practices. The series facilitated knowledge application, with foreseen changes in workplace procedures and training activities (43% respondents). Barriers such as resource limitations, additional training needs, and connectivity issues were frequently identified. Evidence that this knowledge was subsequently applied by participants, such as through changes in workflow, onwards training events and procedural changes further reinforces the efficacy with which the series was able support the laboratory workforce globally in addressing challenges of the COVID-19 pandemic and other health emergencies. The series utilized sessions on cross-cutting topics to run routinely and to keep a high level of engagement with laboratory professionals globally. This enabled it to act as an adaptable tool that was leveraged effectively and quickly during health emergencies for just-in-time learning.

Anglicisms as a Tool for Adaptation to the Economic Realities of Modernity: Management Terminology.

Examines modern management terminology, especially the role of Anglicisms in this context, that is, how Anglicisms contribute to the adaptation of management to changing economic conditions, enrich its vocabulary and simplify communications in the business environment. Specific examples of Anglicisms, their significance and influence on modern management are considered. Anglicisms play a significant role in the adaptation of management to new economic realities, ensuring effective communication and rapid adaptation to changing requirements in the global business environment. They not only enrich the business vocabulary and provide a single professional language, but also reflect the influence of international trends, innovations and technological progress on the sphere of management. Anglicisms are becoming an integral element of adaptive management, contributing to the flexibility and competitiveness of modern organizations in the rapidly changing world of business. The results of the study will help to better understand the role of Anglicisms in modern business practice and their significance as a tool for adaptation to new economic realities. Key words: Anglicisms, Anglicisms in the field of management, business terminology, terminology of management processes, management terminology.

Integrating intuitionistic fuzzy and MCDM methods for sustainable energy management in smart factories.

Improving energy efficiency is crucial for smart factories that want to meet sustainability goals and operational excellence. This study introduces a novel decision-making framework to optimize energy efficiency in smart manufacturing environments, integrating Intuitionistic Fuzzy Sets (IFS) with Multi-Criteria Decision-Making (MCDM) techniques. The proposed approach addresses key challenges, including reducing carbon footprints, managing operating costs, and adhering to stringent environmental standards. Eight essential criteria are identified, such as the use of renewable energy, the efficiency of production, and the health and safety of workers, to evaluate energy performance. Using the entropy method for criterion weighting and the CRADIS technique for alternative ranking, we prioritize a range of energy-efficient solutions. The novelty of our approach lies in its comprehensive assessment of complex real-world energy management scenarios within smart factories, offering a robust and adaptable decision-support tool. Our empirical results, validated through sensitivity analysis, show that alternative 5 delivers the most significant improvement in energy efficiency. This study provides valuable information for industry practitioners seeking to transition to more sustainable production methods and supports the broader sustainability agenda.

Thina Curtis Amid Creative Disorders: Fanzines, Punk, Improvisation, and Critical Pedagogy

Thina Curtis, pedagogue and creator of fanzines in Brazil, has built a trajectory marked by resistance and the expression of a counter-hegemonic ethos that permeates all her production. From an early age, Thina became involved with punk culture, where she found in fanzines a means to express and amplify marginalised voices, challenging sexism, discrimination, and inequalities. Her work and performance stand out for a visceral opposition to fascism and intolerance, while seeking to build a transformative and inclusive pedagogy. Fanzines, in Thina’s practice, are a means of critical and anti-neoliberal pedagogy that not only questions the traditional educational system but also promotes participatory education. This approach places Thina and other social agents—women, youth, prisoners, and disadvantaged communities—as co-creators of knowledge, breaking with the idea of one-way teaching. Through a qualitative and biographical methodology, centred on the life trajectory of Thina Curtis, we examine fanzines as adaptable pedagogical tools that challenge curricular rigidity and encourage critical and participatory training, essential for the decolonisation of knowledge and for social transformation.

Conditional Split Inteins: Adaptable Tools for Programming Protein Functions

Split inteins are biological mechanisms for the operation of the spatiotemporal control of protein activities. They function through protein trans-splicing, in which their N- and C-terminal fragments are expressed contiguously with two protein halves. The subsequent self-excision upon recognition of the complimentary fragment yields a mature, complete, and functional protein. The conditional regulation of protein splicing through environmental factors or the attachment of regulatory modules can be used to determine when and where a protein will operate, providing potential novel approaches for engineering biology applications. This review will discuss current split intein applications and the mechanistic basis for novel species classification. These considerations can provide guidance in intein and extein engineering through activation strategies, in the design of spatial arrangements, and in taking advantage of unique reaction environments. This can pave the way for the future implementation of novel split intein discoveries and the selection of appropriate intein species and aid in designing novel protein engineering strategies.

EyeDraw: Investigating the Perceived Effects of Shared Gaze on Remote Collaborative Drawing

Shared gaze, where collaborators can see each other's point of gaze visualized on their screen in real time, is a novel non-verbal mechanism that augments remote collaborations and increases shared awareness and common grounding. While past studies have focused on well-structured tasks and analyzed task performance and efficiency, our study explores the domain of collaborative drawing for recreational purposes and focuses on collaborators' own perceptions. We surveyed 75 users of online collaborative drawing platforms who mostly drew collaboratively for recreation and artistic growth; they reported the importance of communication but also of retaining individual space despite the collaborative setting. Informed by this and prior research on shared gaze, we evaluate collaboration by allowing two collaborators to draw synchronously on a shared canvas and share their point of gaze. We conducted a study with 24 pairs that drew collaboratively under all combinations of shared gaze and voice communication. Combining voice and shared gaze was perceived to reach the best balance between tightly coupled collaboration and parallel individual execution. Shared gaze led to higher spatial awareness and less turn-taking was observed in conditions that shared gaze was present. Surprisingly, many participants found the lack of any communication medium to afford the highest degree of divergent thinking. Our findings provide guidelines for adaptive tools that consider individual preferences as well as the nature of the task to better support remote collaborations that are open-ended and prize creativity.

Advanced Adiabatic Compressed Air Energy Storage Systems dynamic modelling: Impact of the heat storage device

Advanced Adiabatic Compressed Air Energy Storage (AACAES) is a technology for storing energy in thermomechanical form. This technology involves several equipment such as compressors, turbines, heat storage capacities, air coolers, caverns, etc. During charging or discharging, the heat storage and especially the cavern will induce transient behavior of operating points, notably temperature, pressure, and volume flow. In contrast, the optimal use of turbomachinery requires it to be as stationary as possible. AACAES technology therefore requires transient modelling to optimize its design. This paper presents a modular and adaptable numerical tool capable of simulating the dynamic behavior of different thermomechanical storage systems. This tool is then applied to an AACAES system to analyze the impact of various configurations on the variability of volume flow. The aim is to optimize Round Trip Efficiency (RTE) while limiting the maximum variation in volume flow. First, the effect of the size of fixed-bed Thermal Energy Storage (TES) is analyzed. Then, we analyze the behavior of the system with heat management based on a heat exchanger and a heat transfer fluid. In addition, the effect of adding pressure control at the cavern inlet/outlet on the two previous variants is studied.

Adaptive High-Performance Optimization Tool for Real-time Operation of Renewable-based Virtual Power Plants

Adaptive High-Performance Optimization Tool for Real-time Operation of Renewable-based Virtual Power Plants

Exploring the Relationship Between Transitional Object Attachment and Emotion Regulation in College Students.

Background/Objectives: Transitional attachment objects, such as blankets, play a critical role in childhood by helping children manage separation anxiety and regulate emotions. Although attachment to these objects often decreases as children grow older, it may persist into adulthood and influence emotion regulation and stress responses. Their influence on emotion regulation in adulthood remains uncertain. This study investigates the relationship between object attachment and emotion regulation, with a focus on responses to stress among college students. The study objectives include examining whether emotional regulation varies based on an individual's attachment to objects and investigating the role and significance of objects in the emotional regulation of adults with object attachment. Methods: Forty-five participants aged 18-22 were recruited to participate and completed the Object Attachment Security Measure (OASM) and the Emotional Regulation Questionnaire (ERQ). Participants were categorized into two groups based on their OASM scores: those with attachment objects (the OA group) and those without (the control group). The OA group was randomly assigned into two experimental groups: (1) Carry-but-cannot-touch (CBCT) and (2) Carry-and-touch (CAT). The CBCT group was not allowed to physically interact with their attachment objects during the recovery phase, whereas the CAT group could do so. Psychophysiological data, including Standard Deviation of NN Intervals (SDNN) and respiratory rate, were collected during three phases: baseline, stress, and recovery. Results: There were no differences in the ERQ scores between the OA and control groups, as well as between the CAT and CBCT subgroups. However, physiological indicators revealed that the CAT group exhibited higher SDNN during recovery than the CBCT group, suggesting that physical interaction with the attachment object enhanced stress regulation and promoted relaxation. Conclusions: While object attachment did not impact self-reported emotional regulation, it did influence physiological responses to stress, indicating that attachment objects may facilitate emotional recovery through tactile interaction. These findings highlight the potential of attachment objects as adaptive tools for stress management in young adults.

Sociocultural and Digital Communication Challenges in AI Adoption for Classroom Communication: Insights from Nigerian Colleges of Education

The integration of Artificial Intelligence (AI) in education offers transformative possibilities, particularly in enhancing classroom communication. However, its adoption remains uneven, especially in developing countries like Nigeria, where sociocultural, linguistic, and infrastructural barriers persist. This study investigates the adoption of AI-mediated communication among academic staff at the Federal College of Education (Technical) Akoka, Nigeria. A mixed-methods approach was employed, combining quantitative survey data from 200 respondents with qualitative insights to explore the extent of adoption, challenges encountered, and sociocultural influences. Results indicate that while 19.2% of respondents extensively use AI tools, a significant portion faces challenges such as inadequate funding (42.3%), limited technical expertise (15.4%), and infrastructural deficiencies (25%). Moreover, sociolinguistic issues, including the mismatch between AI tools and local languages, hinder effective communication. Resistance to change, rooted in traditional teaching norms, further complicates adoption. The study contributes by highlighting the interplay between sociocultural norms and technological resistance, offering a multidisciplinary perspective on AI integration in education. Recommendations include targeted professional development, infrastructure improvements, and the creation of culturally adaptive AI tools. These findings provide a replicable framework for enhancing AI adoption in similar educational contexts globally. Future research should explore longitudinal impacts of AI integration on teaching outcomes and develop policies addressing ethical considerations in AI usage. This study underscores the critical need for inclusive and localized AI solutions to bridge the technological gap in education.

Development of Pintarin.Edu as a PTK Learning Application to Improve the Quality of Classroom Action Research Results

This study aims to develop the Pintarin.Edu application as a technology-based learning media to improve the competence of Classroom Action Research (PTK) in prospective teachers. The research method used is the 4D development model (Define, Design, Develop, and Disseminate). Application validation involved material and media experts, with material validation results reaching 93.38% in the valid category and 98% media validation results in the valid category. The readability test shows that the application is acceptable with a readability level of 72.43% in the category of valid enough to use. These results indicate that the Pintarin.Edu application is effective as an interactive and adaptive PTK learning tool, and can support prospective teachers in mastering PTK skills. The implementation of this application is expected to improve the quality of teachers in implementing PTK, which has an impact on improving the quality of education.

Role of horizontal gene transfer and cooperation in rhizosphere microbiome assembly.

Microbes employ a variety of mechanisms, encompassing chemical signaling (e.g., quorum-sensing molecules) and genetic processes like horizontal gene transfer (HGT), to engage in interactions. HGT, in particular, holds a pivotal role as it facilitates the generation of metabolic diversity, thus directly or indirectly influencing microorganisms' interactions and functioning within their habitat. In this study, we investigate the correlations between enhanced metabolic diversity through HGT and cooperative behavior in the rhizosphere. Despite the potential drawbacks of cooperative behavior, which renders it susceptible to exploitation by cheaters based on evolutionary theory, HGT emerges as a mitigating factor. It serves as a valuable and adaptive tool for survival in competitive environments, notably the rhizosphere. By initiating a comprehensive discussion on these processes combined, we anticipate achieving a profound understanding of the rhizosphere microbiome, ultimately enhancing soil microbiology management and the exploitation of this ecological niche.

Vocational training and employment as a tool for professional adaptation of war veterans

Practice has proven that professional training of war veterans is one of the tools of war veterans adaptation policy, formation of adaptation skills and return of ex-servicemen to peaceful life. The authors, raising this current topic, consider the problem of resocialization of veterans and their return to the labor market as a component of the policy of forming an inclusive labor market. With the goal of the research being the development of specific proposals and algorithms for improving the mechanisms of professional training of war veterans and their further employment, the authors analyzed the available foreign experience and bases of sociological surveys. The article examines theoretical aspects and approaches to the professional adaptation of war veterans to civilian life in modern conditions. The theoretical constructions of the study are considered, the characteristics of war veterans and combatants who are persons with disabilities are determined. The possibilities of their adaptation to civilian life in the absence of general demobilization are summarized. It has been proven that the main tool of professional adaptation of war veterans is professional training, but the effectiveness of such training is determined by further employment after its completion. Taking into account the analysis of the situation regarding the professional training of war veterans, which is conducted by the state employment service, the authors highlight the main problems of such training and further employment of this population category. Ignoring the problems of organization, legal regulation of professional training of war veterans and their further employment will have a negative impact on the veterans themselves, their families and society as a whole, which is confirmed by the experience of other countries that dealt with issues of adaptation of war veterans to civilian life. Ways to eliminate the problems and obstacles of professional training of war veterans and their employment for their effective adaptation to civilian life are proposed, including: on the basis of conducting a questionnaire of war veterans, determine their needs in rehabilitation, educational, social, medical services, employment services and professional training; conducting professional training of war veterans taking into account modern military and individual needs of war veterans and others.

Brain-wide functional connectome analysis of 40,000 individuals reveals brain networks that show aging effects in older adults

Abstract The functional connectome changes with aging. We systematically evaluated aging-related alterations in the functional connectome using a whole-brain connectome network analysis in 39,675 participants in UK Biobank project. We used adaptive dense network discovery tools to identify networks directly associated with aging from resting-state functional magnetic resonance imaging (fMRI) data. We replicated our findings in 499 participants from the Lifespan Human Connectome Project in Aging study. The results consistently revealed two motor-related subnetworks (both with permutation test p-values <0.001) that showed a decline in resting-state functional connectivity (rsFC) with increasing age. The first network primarily comprises sensorimotor and dorsal/ventral attention regions from precentral gyrus, postcentral gyrus, superior temporal gyrus, and insular gyrus, while the second network is exclusively composed of basal ganglia regions, namely the caudate, putamen, and globus pallidus. Path analysis indicates that white matter fractional anisotropy mediates 19.6% (p < 0.001, 95% CI [7.6% 36.0%]) and 11.5% (p < 0.001, 95% CI [6.3% 17.0%]) of the age-related decrease in both networks, respectively. The total volume of white matter hyperintensity mediates 32.1% (p < 0.001, 95% CI [16.8% 53.0%]) of the aging-related effect on rsFC in the first subnetwork.

Adaptable Tool for Modeling the Benefits and Costs of Substance Use Disorder Recovery Programs

Abstract Substance use disorder (SUD) is a public health crisis in the United States associated with significant economic costs including healthcare, criminal justice, productivity, and mortality and morbidity costs. In this paper, we present a tool for a customizable economic analysis that can be utilized by different recovery program owners and operators within the SUD continuum of care that considers these program’s operating and capital costs, location, size, and success rate. The goal of this tool is to provide owners and operators with an accessible tool that can estimate their individual program’s economic costs, benefits, and return on investment. In applications of the tool, we find that there are significant benefits associated with SUD recovery-oriented services, even with more conservative modeling of recovery benefits. Specifically, we find that a representative recovery housing program in Florida yields a net benefit of $143 million over 20 years with an associated return on investment of $22.19 per dollar invested. Further, we find that the net benefits of different recovery-oriented modalities including a recovery house, a recovery campus, and a residential inpatient program are positive, with returns on investment varying from nearly $22 per dollar invested to $1 per dollar.

An Optimized GWO-BPNN Model for Predicting Corrosion Fatigue Performance of Stay Cables in Coastal Environments

Corrosion and fatigue damage of high-strength steel wires in cable-stayed bridges in coastal environments can seriously affect the reliability of bridges. Previous studies have focused on isolated factors such as corrosion rates or stress ratios, failing to capture the complex interactions between multiple variables. In response to the critical need for accurate fatigue life prediction of high-strength steel wires under corrosive conditions, this study proposes an innovative prediction model that combines Grey Wolf Optimization (GWO) with a Backpropagation Neural Network (BPNN). The optimized GWO-BPNN model significantly enhances prediction accuracy, stability, generalization, and convergence speed. By leveraging GWO for efficient hyperparameter optimization, the model effectively reduces overfitting and strengthens robustness under varying conditions. The test results demonstrate the model’s high performance, achieving an R2 value of 0.95 and an RMSE of 140.45 on the test set, underscoring its predictive reliability and practical applicability. The GWO-BPNN model excels in capturing complex, non-linear dependencies within fatigue data, outperforming conventional prediction methods. Sensitivity analysis identifies stress range, average stress, and mass loss as primary determinants of fatigue life, highlighting the dominant influence of corrosion and stress factors on structural degradation. These results confirm the model’s interpretability and practical utility in pinpointing key factors that impact fatigue life. Overall, this study establishes the GWO-BPNN model as a highly accurate and adaptable tool, offering substantial support for advancing predictive maintenance strategies and enhancing material resilience in corrosive environments.

Imitation as an adaptation tool in pottery making in New Spain

Ceramics produced in the Viceroyalty of New Spain in the 16th – 18th centuries serve as a valuable source for studying the history of intercultural contacts and colonization of the American continent. This article focuses on tableware ceramics and their significance in the sociocultural adaptation of colonial populations. The production of pottery on the Iberian Peninsula prior to colonization is described, and the function of ceramic vessels during the initial stages of conquest is explored. The article also examines questions of continuity and innovation in pottery production technology, and presents models for the emergence of new ceramic types in New Spain. Additionally, connections are established between the external appearance of tableware and the social identity of its owner. Particular attention is paid to the study of Tonala Polychrome ceramic type, which is an excellent example of local potters adapting to new standards of tableware. The work is based on the study of collections of Tonaltec pottery from the 17th to 18th centuries found in museums across Russia, Spain, and France.

The recombination efficiency of the bacterial integron depends on the mechanical stability of the synaptic complex.

Multiple antibiotic resistances are a major global health threat. The predominant tool for adaptation in Gram-negative bacteria is the integron. Under stress, it rearranges gene cassettes to offer an escape using the tyrosine recombinase IntI, recognizing folded DNA hairpins, the attC sites. Four recombinases and two attC sites form the synaptic complex. Yet, for unclear reasons, the recombination efficiency varies greatly. Here, we established an optical tweezers force spectroscopy assay to probe the synaptic complex stability and revealed, for seven combinations of attC sites, significant variability in the mechanical stability. We found a strong correlation between mechanical stability and recombination efficiency of attC sites in vivo, indicating a regulatory mechanism from the DNA structure to the macromolecular complex stability. Taking into account known forces during DNA metabolism, we propose that the variation of the integron in vivo recombination efficiency is mediated by the synaptic complex stability. We anticipate that further recombination processes are also affected by their corresponding mechanical stability.

Development of algorithms for early detection of cyberattacks on networks using machine learning

Critical infrastructure protection and national security are enhanced by the security and reliability of networks. Various types of information circulate on these networks, ranging in classification from open to closed. The consequences of cyberattacks on these networks can be severe, including reputational damage, financial loss, operational disruption and data leakage. Traditional security methods, such as firewalls and anti-virus software, are becoming less effective against modern and ever-changing cyber threats. As a result, powerful network intrusion detection systems (IDS) have become indispensable for proactive detection and mitigation of cyber attacks. Machine learning has become a viable method for creating adaptive intrusion detection tools that can detect new and complex attack patterns. By learning from huge labelled network traffic datasets, ML models can understand the subtle patterns and differentiating features of normal and abnormal or malicious traffic flows. This allows them to detect possible cyber threats and intrusions that traditional signature-based IDSs cannot detect. Extracting discriminative features and training appropriate classification models from such data is a challenging task. In the presented study, we analyse the effectiveness of ML algorithms for detecting cyberattacks, in particular distributed denial of service (DDoS) attacks, in network traffic data. In the presented study, a network attack detection system is developed using ML and deep learning (DL) models and experimented on the CICIDS2017 dataset. The main objectives of the study are to develop a strategy for extracting valuable information from raw network streams; to study the impact of data preparation on the false positive rate; and to conduct a comparative analysis of ML models for cyberattack detection. The main goal of the study is to provide an understanding of the development of a reliable adaptive network intrusion detection system using ML approaches that increase cybersecurity capabilities and protect against future cyberattacks.