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The leaders of business are a continued focus of interest in management research and in the broader society. Their attributes speak to social mobility, inequality, and who holds positions of power and influence in society. This article examines the attributes of the ten highest-ranked executives of the largest corporate enterprises in the United States—the Fortune 100—and compares how they have changed over the past 40 years, a period when many assumptions about businesses and the people who run them have changed. While there has been significant change in some areas, such as the increase in the proportion of women and foreign-born executives and the rise in outside hiring, there is no evidence of an increase in younger leaders who advance faster than their predecessors and spend an ever-shorter time with their employer. In fact, top executives now are as old as their peers were in the 1950s, and their tenure with their employer is rising. [ABSTRACT FROM AUTHOR]

Real-world information is often characterized by uncertainty and partial reliability, which led Zadeh to introduce the concept of Z-numbers as a more appropriate formal structure for describing such information. However, the computation of Z-numbers requires solving highly complex optimization problems, limiting their practical application. Although linguistic Z-numbers have been explored for their computational straightforwardness, they lack theoretical support from Z-number theory and exhibit certain limitations. To address these issues and provide theoretical support from Z-numbers, we propose a Z-number linguistic term set to facilitate more efficient processing of Z-number-based information. Specifically, we redefine linguistic Z-numbers as Z-number linguistic terms. By analyzing the hidden probability density functions of these terms, we identify patterns for ranking them. These patterns are used to define the Z-number linguistic term set, which includes all Z-number linguistic terms sorted in order. We also discuss the basic operators between these terms. Furthermore, we develop a multi-criteria group decision-making (MCGDM) model based on the Z-number linguistic term set. Applying our method to predict the acceptance of academic papers, we demonstrate its effectiveness and superiority. We compare the performance of our MCGDM method with five existing Z-number-based MCGDM methods and eight traditional machine learning clustering algorithms. Our results show that the proposed method outperforms others in terms of accuracy and time consumption, highlighting the potential of Z-number linguistic terms for enhancing Z-number computation and extending the application of Z-number-based information to real-world problems. [ABSTRACT FROM AUTHOR]

Linear latent variable models such as principal component analysis (PCA), independent component analysis (ICA), canonical correlation analysis (CCA), and factor analysis (FA) identify latent directions (or loadings) either ordered or unordered. These data are then projected onto the latent directions to obtain their projected representations (or scores). For example, PCA solvers usually rank principal directions by explaining the most variance to the least variance. In contrast, ICA solvers usually return independent directions unordered and often with single sources spread across multiple directions as multiple sub-sources, severely diminishing their usability and interpretability. This paper proposes a general framework to enhance latent space representations to improve the interpretability of linear latent spaces. Although the concepts in this paper are programming language agnostic, the framework is written in Python. This framework simplifies the process of clustering and ranking of latent vectors to enhance latent information per latent vector and the interpretation of latent vectors. Several innovative enhancements are incorporated, including latent ranking (LR), latent scaling (LS), latent clustering (LC), and latent condensing (LCON). LR ranks latent directions according to a specified scalar metric. LS scales latent directions according to a specified metric. LC automatically clusters latent directions into a specified number of clusters. Lastly, LCON automatically determines the appropriate number of clusters to condense the latent directions for a given metric to enable optimal latent discovery. Additional functionality of the framework includes single-channel and multi-channel data sources and data pre-processing strategies such as Hankelisation to seamlessly expand the applicability of linear latent variable models (LLVMs) to a wider variety of data. The effectiveness of LR, LS, LC, and LCON is shown in two foundational problems crafted with two applied latent variable models, namely, PCA and ICA. [ABSTRACT FROM AUTHOR]

The U.S. News & World Report (U.S. News) law school rankings have impacted the perceptions and behaviors of everyone in the rankings ecosystem for decades. Commentators have almost universally condemned these ordinal rankings, yet they continue to influence the legal education market, often in highly detrimental ways. The influence of these rankings stems from legitimate market demands, for reasons that the psychology of choice literature makes clear. People want (or need) to efficiently acquire and digest information that could help them make consequential decisions. At a time when consumers of law school information did not have such choice-making assistance, U.S. News filled the void. Whether purportedly relevant information comes from U.S. News, different rankers of law schools, or other sources of information, the fundamental problem is that these sources are filling a void that exists because of law schools' inaction. The law school community is the only cohort of entities that can create data about certain relevant considerations that are currently missing, and they are best positioned to both refine the data categories that currently exist and communicate the potential significance of the generated data. Without a more comprehensive product, law school data consumers will continue to rely on incomplete and potentially misleading information, arbitrarily reduced to a single composite score and ordinal rank by commercial enterprises like U.S. News. This Article provides a blueprint for how the law school community can create an alternative product and reclaim legal education. Such a product would add considerable value to all law school data consumers, including prospective students, law professors, law school administrators, and legal employers. This is laudable in its own right, but such a product would also diminish the influence of rankers like U.S. News because its value would make the deficiencies of the current rankings too obvious for the market to ignore. [ABSTRACT FROM AUTHOR]

This study delves into the complex prioritization process for Autism Spectrum Disorder (ASD), focusing on triaged patients at three urgency levels. Establishing a dynamic prioritization solution is challenging for resolving conflicts or trade-offs among ASD criteria. This research employs fuzzy multi-criteria decision making (MCDM) theory across four methodological phases. In the first phase, the study identifies a triaged ASD dataset, considering 19 critical medical and sociodemographic criteria for the three ASD levels. The second phase introduces a new Decision Matrix (DM) designed to manage the prioritization process effectively. The third phase focuses on the new extension of Fuzzy-Weighted Zero-Inconsistency (FWZIC) to construct the criteria weights using Single-Valued Neutrosophic 2-tuple Linguistic (SVN2TL). The fourth phase formulates the Multi-Attributive Border Approximation Area Comparison (MABAC) method to rank patients within each urgency level. Results from the SVN2TL-FWZIC weights offer significant insights, including the higher criteria values "C12 = Laughing for no reason" and "C16 = Notice the sound of the bell" with 0.097358 and 0.083832, indicating their significance in identifying potential ASD symptoms. The SVN2TL-FWZIC weights offer the base for prioritizing the three triage levels using MABAC, encompassing medical and behavioral dimensions. The methodology undergoes rigorous evaluation through sensitivity analysis scenarios, confirming the consistency of the prioritization results with critical analysis points. The methodology compares with three benchmark studies, using four distinct points, and achieves a remarkable 100% congruence with these prior investigations. The implications of this study are far-reaching, offering a valuable guide for clinical psychologists in prioritizing complex cases of ASD patients. [ABSTRACT FROM AUTHOR]

The handling of missing attribute values remains a challenging and problematic issue in data analysis. Imputation techniques are key procedures used to deal with missing attribute values. However, although these methods are widely used, they cause data bias. Rough set theory, a unique mathematical tool for decision making under uncertainty, overcomes this problem by properly adjusting the relationships. Rough sets are often preferred in both classification and sorting problems. The aim of sorting problems is to sort the objects in the decision table (DT) from best to worst and/or to select the best one. For this purpose, it is necessary to obtain a pairwise comparison table (PCT) from the DT. However, in the presence of missing values, the transformation from DT to PCT is not feasible because there are no ranking methods in the literature for sorting problems based on rough sets. To address this limitation, this paper presents a way to transform from DT to PCT and introduces a generalization of the relation belonging to the "do not care" type of missing values in the dominance-based rough set approach (DRSA) to the decision support tool jRank. We also adapted the DomLem algorithm to enable it to work in PCT with missing values. We applied our method step by step to a decision table with 11 objects and investigated the effect of missing values. The experimental results showed that our proposed approach captures the semantics of 'do not care' type missing values. [ABSTRACT FROM AUTHOR]

The 21st century has been accompanied by significant global changes that confound traditional diplomacy. This article focuses on modern diplomacy and the four main challenge areas it faces. These challenges necessitate diplomatic adaptation to remain relevant and effective. To achieve this modernization, the author suggests the implementation of a newly created hierarchy for the selection, training, deployment, ranking, and promotion of a more specialized diplomatic corps. This process is envisioned to occur within four streams of specialization, each with its own type of expert diplomat. This new diplomatic tool is called the Specialist Diplomatic Hierarchy (SDH). [ABSTRACT FROM AUTHOR]

The circular economy is important in implementing EU Green Deal targets, climate change mitigation commitments, and pursuing sustainable development. A circular economy allows the reduction of waste and environmental damages linked to waste to save natural resources and mitigate climate change. The transition from linear to circular economy models provides many economic and environmental benefits and is a priority for most countries, especially developed ones. There is a need to measure and monitor the circular economy's progress. In this context, indicators can be useful tools to assess progress achieved by countries in pursuing circular economy development. The paper developed an indicators framework to measure circular economy development progress in the EU and applies the developed framework for Visegrad countries. The Visegrad Group (V4) includes four Central European countries, Poland, the Czech Republic, Slovakia, and Hungary, linked by similar geographical and geopolitical situations and common history and culture. MCDM tool ARAS was applied to ranking four Visegrad countries in 2010 and 2021 based on the progress achieved in circular economy development. [ABSTRACT FROM AUTHOR]

The number of mobile applications ("Apps") has grown significantly in recent years. App Stores rank/recommend Apps based on factors such as average star ratings and the number of installs. Such rankings do not focus on the internal artifacts of Apps (e.g., security vulnerabilities). If internal artifacts are ignored, users may fail to estimate the potential risks associated with installing Apps. In this research, we present a framework called E-SERS (Enhanced Security-related and Evidence-based Ranking Scheme) for comparing Android Apps that offer similar functionalities. E-SERS uses internal and external artifacts of Apps in the ranking process. E-SERS is a significant enhancement of our past evidence-based ranking framework called SERS. We have evaluated E-SERS on publicly accessible Apps from the Google Play Store and compared our rankings with prevalent ranking techniques. Our experiments demonstrate that E-SERS, leveraging its holistic approach, excels in identifying malicious Apps and consistently outperforms existing alternatives in ranking accuracy. By emphasizing comprehensive assessment, E-SERS empowers users, particularly those less experienced with technology, to make informed decisions and avoid potentially harmful Apps. This contribution addresses a critical gap in current App-ranking methodologies, enhancing the safety and security of today's technologically dependent society. [ABSTRACT FROM AUTHOR]

Apples are a healthy and environmentally friendly snack, but the consumption of apples in many countries, including Norway, has decreased in the last fifteen years. This trend has a potential negative impact on public health and the environment. In this paper, we use a consumer survey and a random effect ordered logistic regression model to find out what is most important for people when they buy apples. Ten different values are considered and ranked according to individual's importance. We find that taste and safety are the most important values for the average individual's choice of apples, while the appearance and type of apple rank third. The least important values are wrapping size and regional origin. Everyday apple eaters are more concerned about pesticide use and less concerned about price than the average consumers. Furthermore, compared to the average consumer, those with low levels of trust in apple producers and authorities care more about pesticides and environmentally friendly production methods, while consumers with a high level of trust care less about these aspects. Our results indicate that to increase the consumption of Norwegian apples, it is important to maintain or improve their reputation as being tasty and safe to eat. [ABSTRACT FROM AUTHOR]

Smart cities and information and communications technology is a rapidly growing field in both research and real-world implementation, but it is one that is still new and with many different ideas. Unfortunately, there is less cooperation and knowledge sharing across the field, and research often fails to move into real-world applications, which holds it back from becoming fully realized. This paper aims to provide an overview of the current state of smart cities, its definitions, technologies, and technical dimensions, from architectural design to standards and data handling, and how they are handled in the real world and its impact on society. Additionally, it examines important smart city projects, their applications, and ranking systems. This text aims to forecast the future of the field, its impact, the challenges it faces, and what should be addressed to help it reach its full potential. [ABSTRACT FROM AUTHOR]

A social planner wants to rank people. Utilitarianism implies that a natural ranking which orders people from most to least sensitive to their rank is the best ranking. But people's feelings toward the social planner, like blame or gratitude, can depend both on their assigned rank, and on the alternatives they might have been assigned. As a result, the social planner needs to do pairwise comparisons and there may not be a best ranking due to intransitive cycles. This paper shows the possibility of the coexistence of a best choice and non-transitivity. It illustrates how to tell when a best ranking exists, and that when it exists, it is indeed the natural ranking. When this best does not exist, an alternative second-best group ranking strategy is proposed. [ABSTRACT FROM AUTHOR]

Since independence is the most important characteristic of an auditor, we want to expand and develop this characteristic in auditing institutions, so our goal is to provide a practical and practical solution to maintain independence in auditing institutions. We collected and summarized. The experts stated that out of 34 characteristics of auditor independence, except 8 cases are applicable in audit institutions. If these features are not collected in one place and are dispersed and individually under the title of auditor independence, we will rarely see the independence of audit institutions. Currently, the only place where the characteristics of independence can be summarized and considered under a practical and operational model is in the ranking of audit institutions, which is done by the public accountants community. If these characteristics and criteria are taken into account and used in a practical way in the ranking of auditing institutions, we can increase and maintain the independence of auditing institutions. The ranking of auditing institutions can be more appropriate by considering the independence characteristics and bringing fair distribution of work. [ABSTRACT FROM AUTHOR]

Goodhart's Law describes the phenomenon where a measure becomes a target, leading to behaviors aimed at optimizing that measure rather than achieving the true underlying goals. In the context of university rankings, excessive focus on attaining higher ranks can incentivize universities to manipulate metrics rather than genuinely improving educational quality. Analyzing this behavioral shift, research highlights the negative impacts of Goodhart's Law in higher education, particularly in Vietnam. Instead of enhancing teaching and research quality, universities often prioritize ranking advancement through opaque methods. This competitive race results in high costs for students and families without commensurate educational benefits. Addressing these issues requires raising awareness, establishing new evaluation approaches, and promoting genuine educational practices.

Objective: To rank diagnostic features of childhood pulmonary tuberculosis; and to determine the effect of working in tuberculosis Directly Observed Treatment Short Course (DOTS) facilities on the ranking of these features by medical doctors. Methods: A cross sectional descriptive study, using structured questionnaires to collect data from medical doctors whose daily routine included attending to sick children in 34 selected children outpatient clinics and TB DOTS centers in southeastern Nigeria. Results: Approximately, one quarter (25.3% or 56 of 221) of respondents worked in Directly Observed Treatment Short course (DOTS) clinics, while three quarters (74.7% or 165 of 221) worked in nonDOTSclinics. Majority of the respondents (69.7%) ranked chronic persistent cough (1), 42.5 % ranked weight loss and failure to thrive (2), another 27.7% ranked weight loss and failure to thrive (3), while 17.6% and 21.7% ranked History of contact with adult index case and radiographic abnormalities, (4) and (5), respectively. Conclusions: The study found that the percentage of doctors working in DOTS clinics who ranked weight loss and failure to thrive (2) was statistically and significantly higher than those of non-DOTS respondents. The most important symptoms/signs on which medical doctors based their diagnosis of childhood pulmonary tuberculosis include cough, weight loss and failure to thrive, history of contact with adult with smear positive pulmonary tuberculosis, and r adiogr aphicabnormalities consistent with active tuberculosis. There was statistically significant difference between the ranking of weight loss and failure to thrive by doctors working in DOTS clinics and their counterparts in non DOTS clinics. This study showed a decline in the percentage of ranking in both DOTS and Non DOTS respondents as they moved from the first to the fifth.

Water distribution networks (WDNs) are critical infrastructures prone to vulnerabilities which lead to failures. Identifying vulnerable components, especially multiple pipe failure combinations, is crucial for effective management and ensuring high reliability. Hydraulic simulations are commonly used for analysing the criticality of WDN, but are time-consuming and highly data-reliant, limiting the number of testable combinations. To address these limitations and constraints, a graph-based method is proposed to quantify the impact magnitude of multiple pipe failure scenarios on performance, enabling the identification of critical combinations. The proposed graph-based approach utilizes structural and topological characteristics of WDNs as well as spatial demand distribution to replicate hydraulic behaviour. The accuracy of the approach is assessed by testing it on three case studies with various pipe failure combinations, and the results are compared with hydraulic analyses. The results demonstrate a strong correlation (Spearman coefficient > 0.75) between graph-based ranking and state-of-the-art hydraulic-based ranking. Additionally, the method exhibits a significant computational gain factor of greater than 30 compared with the hydraulic-based method, rendering it valuable for actively exploring a wide range of critical pipe failure combinations and devising countermeasures. Furthermore, a hybrid-based method that integrates both the graph and hydraulic-based methods is proposed for enhanced accuracy and robust assessments. HIGHLIGHTS An innovative graph-based ranking method for fast and accurate pipe criticality analysis is developed.; The results show a high correlation with the hydraulic-based ranking method with a computational gain factor of more than 30.; A hybrid-based ranking method is presented, combining the advantages of two approaches to address the limitations of the graph-based ranking method and robust assessment of the impact.;

Objetivo: Analisar o desempenho dos municípios brasileiros nas dimensões do Ranking da Qualidade da Informação Contábil e Fiscal no Siconfi (Ranking) e avaliar a percepção dos profissionais contábeis sobre o tema. Metodologia: Para analisar o desempenho dos municípios nas dimensões do Ranking, foi efetuada coleta de dados no sítio da Secretaria do Tesouro Nacional (https://www.tesourotransparente.gov.br/visualizacao/Ranking-da-qualidade-da-informacao-contabil-e-fiscal-estadual) relativos aos exercícios de 2020 a 2023. Para avaliar a percepção dos profissionais contábeis municipais sobre o tema, foi aplicado questionário estruturado com quatro perguntas, elaboradas com o objetivo de capturar a percepção desses profissionais sobre a existência do Ranking, o conhecimento deles quanto aos dados relativos aos municípios em que trabalhavam e eventuais medidas tomadas pelo município para melhorar a nota atribuída pela STN. Os Municípios foram contatados pela equipe de Call Center da Confederação Nacional de Municípios, devidamente instruída pela equipe de pesquisa. Resultados: A pesquisa mostra que a Dimensão IV (que compara a Declaração de Contas Anuais, Matriz de Saldos Contábeis e relatórios da Lei de Responsabilidade Fiscal) apresentou o menor percentual de acertos no triênio, revelando problemas na consistência dos dados quando as informações entre relatórios diferentes são comparadas. Com a realização do questionário foi colhido como achado que 40% dos respondentes desconheciam o Ranking e mesmo entre os que não o conhecia 46% não realizaram ações para melhorar a colocação do município no Ranking, revelando o desinteresse dos profissionais ou dos gestores municipais sobre a sua importância no contexto de indicadores da qualidade da informação contábil. Contribuições do Estudo: Este artigo indica a necessidade de ampliar as pesquisas empíricas sobre a qualidade dos dados contábeis municipais, buscando aperfeiçoar as questões apresentadas no questionário realizado, incluindo, por exemplo, itens que avaliam a melhoria no sistema contábil.

Abstract This study delves into the complex prioritization process for Autism Spectrum Disorder (ASD), focusing on triaged patients at three urgency levels. Establishing a dynamic prioritization solution is challenging for resolving conflicts or trade-offs among ASD criteria. This research employs fuzzy multi-criteria decision making (MCDM) theory across four methodological phases. In the first phase, the study identifies a triaged ASD dataset, considering 19 critical medical and sociodemographic criteria for the three ASD levels. The second phase introduces a new Decision Matrix (DM) designed to manage the prioritization process effectively. The third phase focuses on the new extension of Fuzzy-Weighted Zero-Inconsistency (FWZIC) to construct the criteria weights using Single-Valued Neutrosophic 2-tuple Linguistic (SVN2TL). The fourth phase formulates the Multi-Attributive Border Approximation Area Comparison (MABAC) method to rank patients within each urgency level. Results from the SVN2TL-FWZIC weights offer significant insights, including the higher criteria values "C12 = Laughing for no reason" and "C16 = Notice the sound of the bell" with 0.097358 and 0.083832, indicating their significance in identifying potential ASD symptoms. The SVN2TL-FWZIC weights offer the base for prioritizing the three triage levels using MABAC, encompassing medical and behavioral dimensions. The methodology undergoes rigorous evaluation through sensitivity analysis scenarios, confirming the consistency of the prioritization results with critical analysis points. The methodology compares with three benchmark studies, using four distinct points, and achieves a remarkable 100% congruence with these prior investigations. The implications of this study are far-reaching, offering a valuable guide for clinical psychologists in prioritizing complex cases of ASD patients.

Existing research suggests that elite clubs exist in venture capital markets, but a standard for determining their size and composition is lacking. This paper addresses this challenge by using the weighted k-means sorting algorithm to construct a research framework for elite clubs. Validating the framework with investment events data from China’s venture capital market (2001–2018), intriguing findings emerge. The ranking of Venture Capitalists (VCs) follows a power-law distribution, providing evidence for elite clubs’ existence. The analysis identifies a turning point in the score curve, serving as a valuable indicator for club boundaries. Elite clubs demonstrate relatively high stability, maintaining advantages and elite status in future competitions. Empirical validation confirms the proposed framework’s superior stability compared to existing methods. Importantly, elite club members outperform non-elites significantly. This paper effectively identifies elite clubs in the Chinese venture capital market, helping other VCs recognize potential partners, access high-quality information, and enhance investment performance.

The COVID-19 pandemic was responsible for the cancellation of both the men's and women's 2020 National Collegiate Athletic Association (NCAA) Division I basketball tournaments. Starting from the point when the Division I tournaments and unfinished conference tournaments were canceled, we deliver closed-form probabilities for each team of making the Division I tournaments, had they not been canceled, under a simplified method for tournament selection. We also determine probabilities of a team winning March Madness, given a tournament bracket. Our calculations make use of conformal win probabilities derived from conformal predictive distributions. We compare these conformal win probabilities to those generated through linear and logistic regression on college basketball data spanning the 2011–2012 and 2022–2023 seasons, as well as to other publicly available win probability methods. Conformal win probabilities are shown to be well calibrated, while requiring fewer distributional assumptions than most alternative methods. [ABSTRACT FROM AUTHOR]

Purpose: Analyze the performance of Brazilian municipalities in the dimensions of the Accounting and Fiscal Information Quality Ranking in Siconfi (Ranking) and evaluate the perception of accounting professionals on the topic. Methodology: To analyze the performance of municipalities in the Ranking dimensions, data was collected on the website of the National Treasury Secretariat (https://www.tesourotransparente.gov.br/visualizacao/Ranking-da-qualidade-da-informacaocontabil-e-fiscal-state) relating to the years 2020 to 2023. To evaluate the perception of municipal accounting professionals on the topic, a structured questionnaire was applied with four questions, designed with the aim of capturing the perception of these professionals about the existence of the Ranking, the their knowledge of data relating to the municipalities in which they worked and any measures taken by the municipality to improve the score given by the STN. The Municipalities were contacted by the Call Center team of the National Confederation of Municipalities, duly instructed by the research team. Results: The research shows that Dimension IV (which compares the Declaration of Annual Accounts, the Accounting Balances Matrix and reports from the Fiscal Responsibility Law) presented the lowest percentage of correct answers in the three-year period, revealing problems in the consistency of this data when the information between different reports are compared. With the completion of the questionnaire, it was found that 40% of respondents were unaware of the Ranking and even among those who did not know it, 46% did not take actions to improve the municipality's placement in the Ranking, revealing the lack of interest of professionals or municipal managers about its importance in the context of accounting information quality indicators. Contributions of the Study: This article indicates the need to expand empirical research on the quality of municipal accounting data, seeking to improve the questions presented in the questionnaire, for example, by adding items that evaluate the improvement in the accounting system. [ABSTRACT FROM AUTHOR]

In this work, we systematize several implementations of the Gray code over an alphabet with m ≥ 2 elements, which we present in C code so that they can be used directly after copying from the text. We consider two variants—reflected and modular (or shifted) m-ary Gray codes. For both variants, we present the ranking and unranking functions, as well as algorithms for generating only a part of the code, more precisely the codewords between two given vectors. Finally, we give algorithms that generate a maximal set of non-proportional vectors of length n over the given alphabet in a Gray code. [ABSTRACT FROM AUTHOR]

Aeolianites and cemented beach deposits on South Africa's Cape coast preserve evidence of events that transpired on them when they were composed of unconsolidated sand. Over the past decades, numerous Pleistocene vertebrate tracksites have been identified on aeolianite palaeosurfaces in the Garden Route National Park, West Coast National Park, and Addo Elephant National Park. In the Garden Route National Park alone, 57 Pleistocene vertebrate tracksites have been discovered. An equilibrium exists, whereby new sites become exposed through cliff-collapse events, while known sites slump into the ocean, are eroded through the action of wind and water, or are destroyed through wave action. Engraved graffiti poses a further threat. These sites complement the traditional body fossil record, and have significant palaeoenvironmental and palaeoanthropological implications. Hominin sites are of global importance: one contains the oldest tracks attributed to Homo sapiens, others contain patterns made in sand by ancestral humans and constitutes a form of early palaeoart. Collectively, these sites have substantial geoheritage value. The discoveries create management questions: which sites require active management, and how should they be ranked in importance? Factors which need to be considered in developing a management strategy include the scientific and heritage value of the sites, whether recovery or replication is preferable, the presence or absence of suitable repositories, the level of the threat to site integrity, the accessibility of the site, and the feasibility of recovery. Checklists containing appropriate criteria and questions can form tools in assessing the importance of these ichnosites. [ABSTRACT FROM AUTHOR]

In recent years, researchers have focused on the Intuitionistic Fuzzy Transportation Problem (IFTP) due to its significant and indispensable role in the Transportation Problem (TP). An endeavour is performed in this paper to establish a new technique. This technique works with IFTP based on "Geometric Mean-Ranking(GM-R)"method. To provide a comprehensive understanding of the proposed method, we present and solve extensively discussed numerical examples. The acquired outcomes are subsequently subjected to numerical comparison with those of established methods, confirming the effectiveness of the proposed technique. This study validates the flexibility and simplicity of applying the method to real-life IFTPs for decision-makers. [ABSTRACT FROM AUTHOR]

Tourism is a worthy catalyst for development in emerging economies and supports growth in most developing countries. Consequently, countries continuously strive to enhance tourism competitiveness to magnetize worldwide tourists. However, due to significant environmental changes and intense competition, tourism organizations are compelled to adopt new strategies. A literature review demonstrates a broad spectrum of possible and available strategies for countries to choose from, necessitating the prioritization of strategies appropriate to the host country's situation and conditions. In this study, we implemented the Antifragility Analysis Algorithm (AAA) to address the research problem (identifying and prioritizing tourism strategies in the western region of Mazandaran province, Iran). We also collected experts' verbal judgments using Neutrosophic Sets (NSs), which can effectively address ambiguity and uncertainty. Initially, with the help of experts in the field, we identified eleven available strategies. Then, we identified five influential environmental indicators and possible states for each, defining thirteen alternative scenarios (one current scenario and twelve future scenarios). Subsequently, the performance of strategies in each indicator state was estimated using NSs. Then, considering the future scenarios, the antifragility scores of the strategies were determined. The results indicate all listed strategies are antifragile, meaning that adopting and implementing each could yield more significant benefits than the current situation. According to the findings, market research, infrastructure development, community engagement, diversification, and monitoring strategies should be implemented in the initial stage. Following them, destination branding, halal tourism, and crisis management strategies should be implemented in the next stage, and the remaining strategies can be executed in the final stage. [ABSTRACT FROM AUTHOR]

The aim of this study is to analyse the variables related to knowledge (Talent Management and Training) as a source of human capital in the companies listed in the ranking of the most attractive organisations within the Spanish labour market, published annually by the journal Actualidad Económica (period 2016–2022). We seek to determine the socio-economic variables impacting this assessment, while also exploring the sustainability of the companies in the ranking. Ten hypotheses are thus examined by descriptive statistics, ANOVA, and multiple linear regression models. The results show a significant relationship between permanence, nationality, professional–scientific–technical sector, size, stock market listing, and both variables representative of knowledge in the ranked companies. Focusing on Talent Management, it is noted that permanence in the ranking (>4 years), Anglo-Saxon nationality, being active in the professional, scientific, and technical sector, and being listed on the stock market all play a part. However, Training differs in that size is a factor that positively influences valuation, whereas the international area is irrelevant. Our findings are a key contribution, as there are no previous applied studies that correlate knowledge in the business environment, the valuation of organisations from the employee's perspective, and several socio-economic variables. [ABSTRACT FROM AUTHOR]

The progressing globalization of the contemporary economy impacts its volatility and unpredictability. The directions of changes in the socioeconomic development of the contemporary global economy are determined by a number of interrelated diverse factors. Factors clearly influencing the development of the modern international economy include innovation, digitization processes, instability of the economy caused by armed conflicts or pandemic outbreaks, the concept of sustainable development, climate policy, as well as issues related to the depletion of energy resources and the necessity of ensuring global energy security. The purpose of the article is to identify the factors of the development of the contemporary economy along with the analysis and evaluation of their impacts on changes in the level of renewable energy sources (RESs) in the EU countries. The time scope of the analysis covers the years 2013 and 2022 (a 10-year perspective). The study used the methods of literature study, literature criticism, statistical data analysis (statistical databases: EUROSTAT and IRENA), and linear ordering methods (TOPSIS and EDAS). The study results indicate that the levels of the RESs have changed in response to the factors diagnosed in the study. In the years studied, the leaders in terms of levels of RES development were France, Spain, and Denmark. [ABSTRACT FROM AUTHOR]

Universities nowadays engage in fierce competitive battles, both for students and funding. Among the competitive advantages addressing both people and money counts potent internationalization, opening possibilities to study abroad or work with foreign specialists. Providing joint degrees with foreign partner universities has emerged as a viable path to a higher attractiveness of university study options. Nevertheless, after almost two decades of joint degree offers in the European higher education area, the joint degree popularity seems to be stagnating at best. Based on an overview of Czech universities, this study seeks to answer whether universities providing joint degrees rank better in international assessments and whether individual faculties running joint degrees at Czech universities rank better in the national Czech Universities Ranking. As a mixed-method study, it applies the methods of content and correlation analyses to analyze and compare the national and international quality ranking of higher education institutions in the Czech Republic in relation to providing joint or double degree programmes. While no statistically significant relationship has been found between the Czech national ranking of individual faculties and their offer of double degrees, the findings suggest a statistically significant relationship between the joint degree offer and international university ranking. Nevertheless, the direction of the relationship remains obscure. [ABSTRACT FROM AUTHOR]

Workload management is a cornerstone of contemporary human resource management with widespread applications in private and public sectors. The challenges in human resource management are particularly pronounced within the public sector: particularly in task allocation. The absence of a standardized workload distribution method presents a significant challenge and results in unnecessary costs in terms of man-hours and financial resources expended on surplus human resource utilization. In the current research, we analyze how to deal with the "race condition" above and propose a dynamic workload management model based on the response time required to implement each task. Our model is trained and tested using comprehensive employee data comprising 450 records for training, 100 records for testing, and 88 records for validation. Approximately 11% of the initial data are deemed either inaccurate or invalid. The deployment of the ANFIS algorithm provides a quantified capability for each employee to handle tasks in the public sector. The proposed idea is deployed in a virtualized platform where each employee is implemented as an independent node with specific capabilities. An upper limit of work acceptance is proposed based on a documented study and laws that suggest work time frames in each public body, ensuring that no employee reaches the saturation level of exhaustion. In addition, a variant of the "slow start" model is incorporated as a hybrid congestion control mechanism with exceptional outcomes, offering a gradual execution window for each node under test and providing a smooth and controlled start-up phase for new connections. The ultimate goal is to identify and outline the entire structure of the Greek public sector along with the capabilities of its employees, thereby determining the organization's executive capacity. [ABSTRACT FROM AUTHOR]

Multi-objective transportation problems (MOTPs) are mathematical optimization problems that involve simultaneously considering multiple, often conflicting objectives in transportation planning. Unlike traditional transportation problems, which typically focus on minimizing a single objective such as cost or distance, MOTPs aim to balance multiple objectives to find the optimal solution. These problems appear in various real-world applications such as logistics, supply chain management, and transportation, where decision-makers need to consider multiple criteria when designing transportation networks, routing vehicles, or scheduling deliveries. The primary challenge lies in the uncertainty in real-world transportation scenarios, where logistics involve factors beyond cost and distance. We investigated a multi-choice solid fractional multi-objective transportation problem (MCSF-MOTP) based on supply, demand, and conveyance capacity, where the coefficients of the objective functions were of the multi-choice type due to uncertainty. To address this uncertainty, the proposed model employed the Newton divided difference interpolation polynomial method, and the suitability of this model was validated through a numerical illustration employing a ranking approach. [ABSTRACT FROM AUTHOR]

The neighborhoods of the historical context of the cities have been disintegrated over time; So that it has put a lot of pressure on the cities and made them suffer from premature fragility. The aim of this research was to analyze the fragility in 24 neighborhoods of the historical context of Urmia city. The type of research is applied and the research method is descriptive-analytical. The analyzed data were collected through a survey and using a questionnaire from a statistical sample consisting of 30 experts. 14 indicators have been selected based on the opinions of elites and the availability of information, and information layers have been created for them in GIS software. FUCOM method was used to calculate the weight of indicators and CoCoSo decision method was used for data analysis. The results show that in the historical context of Urmia city, 8% of the range is located in the very low fragility zone, 21% in the low fragility zone, 29% in the medium fragility zone, 28% in the high fragility zone and 14% in the very high fragility zone. Darvishlar, Aghdash, Doshabchikhana, Khanbaghi and Khanbabakhan neighborhoods are in the zone of very high fragility, Sahiyeh, Jarchibashi, Tandirchilar, Shurshora and Hezaran neighborhoods are in the high fragility zone, Bazarbash, Argh, Delgosha, Yurdshahi and Nogechar neighborhoods are in the medium fragility zone, Yedidarman, Agh Zamilar, Seyedjavad, Mahdi-ul-Ghadam and Yunjaligh are located in the low fragility zone and Nayeb Asghar, Khatib, Qara-Aghaj and Davchilar neighborhoods are located in the very low fragility zone. [ABSTRACT FROM AUTHOR]

The International Chess Federation (FIDE) imposes a voluminous and complex set of player pairing criteria in Swiss-system chess tournaments and endorses computer programs that are able to calculate the prescribed pairings. The purpose of these formalities is to ensure that players are paired fairly during the tournament and that the final ranking corresponds to the players' true strength order. We contest the official FIDE player pairing routine by presenting alternative pairing rules. These can be enforced by computing maximum weight matchings in a carefully designed graph. We demonstrate by extensive experiments that a tournament format using our mechanism (1) yields fairer pairings in the rounds of the tournament and (2) produces a final ranking that reflects the players' true strengths better than the state-of-the-art FIDE pairing system. [ABSTRACT FROM AUTHOR]

The decathlon consists of ten events with scores which are then aggregated to determine the final ranking. We develop a decathlon scoring method which is far simpler than the existing standard (IAAF1984) tables, as there are only 9 parameters instead of 30 which have an impact on the overall rank. We first identify athletes who are on the Pareto-efficient frontier i.e. those who are not dominated by anyone else. We then remove these frontier athletes and again pick all non-dominated athletes to obtain a second dominating group/Pareto frontier and iterate this procedure for the decathlon data from 1986 to 2020. Each of these groups are then characterized by their set of ten median performances. Improving from the last to the top group can then be seen as a path of progress, leading from the lowest to the highest set of median performances. Every event should have the same importance, so we normalize the data such that the path of progress follows as much as possible a space diagonal of a ten dimensional hypercube. Furthermore, any adjustment of a benchmark does not change any actual decathlon performance, hence there cannot be any unwanted rank reversals. This allows a smooth adjustment of these tables in the future, if for instance a new type of javelin needs to be introduced to reduce the range. We normalize such that current performances between 7000 and 9000 points still fall into the same range with our point tables. [ABSTRACT FROM AUTHOR]

Ranking and rating methods for preference data result in a different underlying organization of data that can lead to manifold probabilistic approaches to data modelling. As an alternative to existing approaches, two new flexible probability distributions are discussed as a modelling framework: the Discrete Beta and the Shifted Beta-Binomial. Through the presentation of three real-world examples, we demonstrate the practical utility of these distributions. These illustrative cases show how these novel distributions can effectively address real-world challenges, with a particular focus on data derived from surveys concerning environmental issues. Our analysis highlights the new distributions' capability to capture the inherent structures within preference data, offering valuable insights into the field. [ABSTRACT FROM AUTHOR]

Objective: The goal of this pilot study was to present a new index system (GFsa©) based on two variables, the total citations and "scientific age", to evaluate the best-ranked researchers in dentistry. Methods: All researchers included were cited in the AD Scientific Index (2024, dentistry field) and had their Google Scholar page accessible for a manual consultation. Two authors retrieved this information. A dataset was prepared (name, H-index, i10 index, and publications). The formula applied was GFsa = (total number of citations)/("scientific age")2. The Pearson correlation statistically evaluated the data obtained; the confidence interval was 95%. Results: A total of 1020 were included. The mean "scientific age" was 34.18 ± 13.34. The GFsa© index was calculated, presenting a minimum value of 0.2186 and a maximum of 154.8. The data were organized and sorted following the ranking obtained. The Pearson correlation showed that the H-index had a weakly positive association with the researcher's "scientific age"; thus, the H-index increased according to the increase in "scientific age". By contrast, a moderately negative correlation between GFsa and "scientific age" was demonstrated. Moreover, a positive correlation was observed between both indexes. Conclusions: The variable reported ("Scientific age") provided a better evaluation among the researchers in dentistry. [ABSTRACT FROM AUTHOR]

Introduction: The development of sustainable animal husbandry plays an important role in establishing food security, improving welfare, increasing the income of rural households, improving productivity, creating job opportunities, creating links with other economic sectors, and rural development. In Iran, the issue of sustainable development of the animal husbandry industry and creating sustainability is one of the most important issues of the country because the animal husbandry industry is one of the most important sub-sectors of the agricultural industry, which produces the most important basic food of the country, i.e., red meat. The main goal of this research is to identify and prioritize the obstacles and problems of sustainable animal husbandry development in Guilan province. The development of the agriculture and animal husbandry industry is necessary to access a sufficient amount of food and energy and to cover the ever-increasing demand due to the increase in the population. Guilan province has a suitable capacity for the development of animal husbandry activities. Paying attention to the existing research gaps, by summarizing findings in this field, using the opinion of animal husbandry industry experts, and the application of the multi-indicator decision-making model, this study identified the obstacles and problems for the development of sustainable animal husbandry in Guilan province. Materials and methods: Various criteria have been introduced in previous research as key factors for the sustainable development of animal husbandry, the most important of which included structural, institutional, economic, cultural, social, environmental, macro goals and strategies, the process and cycles of providing inputs, and selling livestock products. The decision tree was drawn using the findings of similar studies and the opinions of provincial experts in this industry. The data collection tool is a questionnaire for pairwise comparisons of decision tree criteria and sub-criteria. To determine the weight of the criteria and sub-criteria included in the decision tree, the opinions of 10 experts in this field in Guilan province were collected and analyzed using the Fuzzy Hierarchy Process (FAHP). Fuzzy set theory is a mathematical theory designed to model the ambiguity of processes related to human knowledge. The decision maker can freely choose the range of desired values. Also, the uncertain judgment of the expert can be expressed by a fuzzy number. In this method, fuzzy numbers are used for the pairwise comparison of options, and the decision maker can express the pairwise comparisons of the elements of each level in the form of triangular fuzzy numbers. The decision tree for this research has five main criteria including institutional, environmental, social and cultural, structural, and economic factors, and 31 different sub-criteria. FAHP is a systematic method that uses the concepts of fuzzy set theory and hierarchical structure analysis. The calculated weights are a suitable basis for prioritizing the main obstacles and problems in the sustainable animal husbandry industry development of Guilan province. Modeling and obtaining the results were done in the MATLAB software. Results and discussion: The results of the research showed that from the point of view of experts, institutional and economic obstacles with the weights of 29.71% and 19.23%, respectively, are considered to be the most important obstacles to the development of sustainable animal husbandry in Guilan province. On the other hand, the sub-criteria of low attention to the animal husbandry sector in the provincial policies from the institutional criterion, the inappropriateness of the materials used, considering the weather conditions from the environmental criterion, the low status and job position of animal husbandry from the social and cultural criterion, the lack of high-yielding breeds consistent with the conditions of the region from the structural criterion, and the lack of adequate insurance coverage from the economic criterion have the highest rank among the sub-criteria. Conclusions: The obtained results indicated the high level of obstacles and problems for the development of sustainable animal husbandry in Guilan province, which requires the attention of policymakers and the development of a policy package that fits the priorities determined in this study. [ABSTRACT FROM AUTHOR]

Multi-objective transportation problems (MOTPs) are mathematical optimization problems that involve simultaneously considering multiple, often conflicting objectives in transportation planning. Unlike traditional transportation problems, which typically focus on minimizing a single objective such as cost or distance, MOTPs aim to balance multiple objectives to find the optimal solution. These problems appear in various real-world applications such as logistics, supply chain management, and transportation, where decision-makers need to consider multiple criteria when designing transportation networks, routing vehicles, or scheduling deliveries. The primary challenge lies in the uncertainty in real-world transportation scenarios, where logistics involve factors beyond cost and distance. We investigated a multi-choice solid fractional multi-objective transportation problem (MCSF-MOTP) based on supply, demand, and conveyance capacity, where the coefficients of the objective functions were of the multi-choice type due to uncertainty. To address this uncertainty, the proposed model employed the Newton divided difference interpolation polynomial method, and the suitability of this model was validated through a numerical illustration employing a ranking approach.

Objective. The noticeable interest in aircraft such as drones for various purposes puts forward certain requirements for their characteristics. Characteristics can be divided into information technology and consumer characteristics from a financial point of view. At the same time, they have their own units of measurement. In this regard, the task of selecting and ranking drones according to some criterion or numerical metric arises. Considering that this problem is quite relevant, this paper considers a certain heuristic approach to sorting a sample of drones by the key of the proposed metric.Method. In the heuristic approach, there is a certain variability in determining the attractiveness of a particular drone in the opinion of the person making the decision to purchase or a specific choice from the existing line of drones available for review based on their characteristics.Result. It is proposed to identify several groups in the existing characteristics, heterogeneous in their properties, both obvious and intuitively created: “good”, “very good”, “less attractive”, “least attractive”. Assuming that several models of drones with the same characteristics are being considered, divided into the specified groups, numerical coefficients are introduced to form a metric by which a given line or selection of drones will be ranked according to the calculated metrics.Conclusion. The proposed heuristic algorithm is based on the transition to the reduced values of numerical characteristics relative to the maximum of each group of characteristics with the calculation of the arithmetic mean of the given values. Depending on the type of specified groups, the coefficients entered into consideration are added or subtracted from the difference between the current characteristic and its average or the difference between the average and the current characteristic. On this basis, metrics are calculated by which the given sample of drone models is ranked.

The article's subject is models and methods for ranking candidates for an IT project team with uncertainty regarding competencies and requirements. The aim is to improve the quality of the IT project team by creating and applying models and a method for formalizing the task of multi-criteria ranking of candidates for the team, taking into account the uncertainty of the initial information. Tasks: to analyze the relevance of the task of creating models and methods for ranking candidates for the IT project team under conditions of uncertainty; to develop a method for multi-criteria ranking of candidates for the IT project team in a fuzzy formulation; and to solve an example of the task of multi-criteria ranking of applicants for further formation of the IT project team. The methods used are the analytic hierarchy process, the line method, and the fuzzy arithmetic method. The following results have been obtained. A method of multi-criteria ranking of candidates for an IT project team has been developed, which differs from existing methods by using fuzzy numbers to set the preferences of candidates and assess the generalized competence of each candidate based on comparisons with the reference competence, which improves the ability to evaluate candidates. This method can be used in the first stage of creating an IT project team when candidates for the team are ranked. The task of selecting candidates for further formation of the IT project team has been solved. Conclusions. The scientific novelty of the method of multi-criteria ranking of candidates for the project team is that, unlike existing methods, it uses fuzzy ideas about the preferences of candidates when assessing the generalised competence of each candidate based on comparisons with the reference competence, which allows to improve the ability to evaluate candidates. This article considers an example of using the proposed method to solve the problem of selecting candidates to further solve the problem of forming an IT project team under fuzzy evaluation.

To compare tolerance and sensitivity indices of sesame genotypes to water stress in Ahvaz (south-west of Iran) conditions, an experiment was conducted in Research Farm of Agricultural Sciences and Natural Resources University of Khuzestan, south-west of Iran, in summer 2018. The experimental design was split plot based on a randomized complete block design with four replicates. Experimental factors were three levels of irrigation (I1; fully irrigated, I2: changing altered irrigated and I3: fixed altered irrigated) in main plots and six sesame genotypes in subplots. The yield of studied genotypes showed a significant difference in different levels of irrigation. Genotype Shushtar produced the highest grain and oil yield and showed good performance in both normal and low irrigation conditions. The examined genotypes had significant differences in terms of Stress Sensitivity index (SSI), Tolerance Index (TI), Productivity Mean (PM), Harmonic Mean (HM), Yield Stability Index (YSI), Geometric Productivity Mean (GPM), Stress Tolerance Index (STI), Stress Damage Index (SDI), Modified Stress Tolerance for appropriate conditions (MSTI1), Modified Stress Tolerance for non-appropriate conditions (MSTI2), and Yield Reduction Index (YRI). In general, the best indicator for evaluation of tolerance and susceptibility of sesame genotypes was stress tolerance index (STI). The most tolerant and sensitive genotypes were Shushtar and Halil genotypes, respectively.

Introduction. In the modern world, educational organizations have to face the increasing competition in the field of education, research and innovation, meaning they need to improve their position, achieve sustainability, and develop the implementation of the “third mission”, which implies interaction with the microenvironment. Limited resources in the broad sense of the word lead to the need to rank various groups of stakeholders in order to satisfy demands so that they support the development strategy of an educational facility. Materials and methods. A number of foreign and domestic sources, representing the development of the stakeholder management theory in relation to educational organizations, have been selected and individual theses, ideas and proposals are shown. Based on the available scientific developments of the theory and practice of stakeholder management and the “third mission” management of an educational organization, the article presents the author’s methodology for ranking stakeholders of an educational organization, aimed at including the axiological foundations of interaction in the field of parameters, when analyzing stakeholders of an educational organization with the adaptation of the “cité theory” by Thévenot and Boltanski. Results. Approbation of the author’s ranking methodology is presented using the example of a specific educational organization, as a result of which, the balance and intensity of connections between stakeholders in the system of relationships have been studied, and the predominance of project and reputational value principles of interaction in stakeholder groups of an educational organization has been revealed; distribution by quadrants or strategic portfolios scheme has been formed for the further proposals formation and relationships development programs design, taking into account leading values. Discussion. Value-driven interaction considering stakeholders’ “exchange units” can define a strategy to meet stakeholders’ needs and expectations. In the context of educational institutions, the development of stakeholder interaction can lead to competitive advantages and support for strategic decisions of the organization in conditions of local and global restrictions, particularly when focusing on the search for non-financial interaction and meeting the needs.

Abstract Antimicrobial/antibiotic de-escalation (ADE) is a key feature of antimicrobial stewardship programs (ASP) that relies mainly on individual panels for determining ADE events based on subjective ranking of antibiotics’ spectrum activity. The lack of consensus among ASP experts leads to reproducibility issues in the measure of this clinical outcome, making difficult to assess its real impact on patient care. The S3 score (Simplified Spectrum Score) app was developed to allow an objective ranking of antibiotics. Ranking was achieved by developing a database harboring pairs of bacteria-antibiotics for which each molecule was assigned a score based on published and clinically validated data from a recognized international committee. S3 score shows a strong correlation relationship and substantial agreement to a clinically validated spectrum score, and its framework enables any person to use it for ADE detection without assuming prior knowledge or training. In addition, its design enables regular updates and sustainability.

The aim of this work was to rank the territory of the Caspian sandy natural plague focus (43) by the risk of epizooty emergence using the MaxEnt model.Materials and methods. The archival data on epizootic manifestations of plague over the past 35 years, aggregated by the Stavropol Anti-Plague Institute of the Rospotrebnadzor, the Dagestan, Elista, Astrakhan PCSs of the Rospotrebnadzor, were used for model design. 615 archive plague detection points were converted into the coordinate system (1980–2015). 87 publicly available bioclimatic variables BioClim were deployed to construct the MaxEnt model. Applied weather and climatic factors of the BioClim database are averaged over a multiyear period.Results and discussion. The MaxEnt model has a very high degree of reliability (AUC=0.975), with a sufficiently high predictive ability (AUC=0.973). According to the generated model, the Caspian sandy natural plague focus has a heterogeneous structure in terms of the probability of epizooty registration and can be divided into five zones. The most significant factors for the model are the following indicators: the average temperature of the wettest quarter, solar radiation in November, the average temperature of the driest quarter, the amount of precipitation in the coldest quarter, wind speed in May, the amount of precipitation in the wettest quarter, and the average air temperature in September. The data obtained allow for targeted search for plague epizootics and can be used to adjust boundaries of a surveyed natural focus in the future.

Population ageing is a major challenge affecting the future of science and technology policy and governance in industrialised societies. In this context, a key element is ensuring adequate protection, safety and care for older people when needed. The solution to enable active and healthy ageing is innovative technologies called gerontechnologies, which support older people. However, there is a knowledge gap regarding the systematic analysis and evaluation of gerontechnologies, which requires research in theoretical and empirical aspects. There is a need to focus on developing and supporting gerontechnologies to help older people reach their full potential in different spheres of life. Research should focus on analysing these technologies, their effectiveness and their impact on the quality of life of older people. This paper evaluates, analyses and builds a ranking of several selected technologies: (1) the wheelchair based on artificial intelligence Wheelie7, (2) the humanoid Rudy Robot, and (3) the wristband/watch VitalBand. The research was conducted in Poland. Based on a literature review, the authors identified relevant technologies to improve the quality of life of older people. These technologies were then assessed by people over 40 against various criteria. This age group was chosen because the issues of gerontechnology concern these people now in the context of their parents using the technology and being potential users of gerontechnology in 20–30 years. The study answered the following research questions: (1) What are the criteria for evaluating technologies that enhance the quality of life for older individuals? (2) How were the selected gerontechnologies evaluated? (3) How should the TOPSIS method be applied to build a ranking of gerontechnologies? (4) Which of the selected gerontechnologies was rated the highest by potential users?

With the development of the Scientific, Transparent and Applicable Rankings tool for clinical practice guidelines(STAR), the publication of evaluation and ranking for scientificity, transparency and applicability of Chinese guidelines and consensus published in the medical journals in 2021and 2022, as well as the publication of the STAR evaluation and ranking for some specialities, the STAR evaluation and ranking has received widespread attention in the medical community. In order to further enhance its scientificity and transparency, Methodology and Technology Specialization Committee of the STAR Working Group presents this article to introduce sample identification and speciality assignment in the evaluation and ranking process.