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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]

This study documented three domains of journal research quality using metrics from six major publishers and two major database services for a large sample of kinesiology-related journals: Rigor/soundness, usage, and prestige. All journal metrics were highly skewed and variable. Median acceptance rates and initial review time were consistent with rigorous peer-review. Four variables were strongly interrelated (0.849 < r < 0.963) and indicate typical usage of 1 to 3 citations for articles in these journals. The 5-year Eigenfactor Score had a relatively weaker association (0.510 < r < 0.758) with the usage metrics, supporting it as an estimate of the prestige afforded these kinesiology journals in Scopus instead of usage. Care must be taken to interpret multiple journal metrics; taking into account the skew, large variability, and confounding factors such as journal size and subject. Differences across quality domains, metrics, and bias from numerous contextual factors refute the insidious misuse of any single journal metric as quality indictor for ranking journals. [ABSTRACT FROM AUTHOR]

Faculty productivity and influence constitute an important aspect of doctoral program quality. Literature on faculty productivity of Criminology and Criminal Justice (CCJ) Ph.D. programs has not yet properly weighted the impact of journal publications in a standardized and objective manner, limiting their analyses to select CCJ journals or the CCJ discipline. This is problematic because CCJ is an interdisciplinary field, and many criminologists publish in highly influential non-CCJ journals. While past assessments have largely neglected citation-based data, the present study analyzes scholarly productivity for the years 2015 to 2021 using a more comprehensive and inclusive method for assessing influence. Based on this study's productivity measure, the top programs are Florida State University, Pennsylvania State University, Arizona State University, the University of Pennsylvania, and the University of Cincinnati. Findings are situated with prior research and the latest U.S News and World Report rankings. [ABSTRACT FROM AUTHOR]

Unlike prior studies that have examined the research productivity to develop various rank-order metrics of particular scholars or institutions, we seek to determine ways in which criminology and criminal justice faculty at the top 21 doctoral programs publish their research. To account for a potential diversity in faculty publication productivity, our study considers various outlets for faculty publications—journal articles, books, and book chapters—and develops composite profiles of publication productivity. Our intention is not to rank faculty and determine academic stars, but to distinguish groups of faculty similar in their patterns of faculty productivity. We analyze the publications of over 90% of all tenured and tenure-track faculty employed by the top 21 U.S. doctoral programs in criminology and criminal justice. Our latent profile analysis yielded five distinct profiles of productivity among the faculty in the top doctoral programs. Our study reaffirms the need for the use of multidimensional measures of publication productivity. [ABSTRACT FROM AUTHOR]

The Arkansas Department of Transportation (ARDOT) Maintenance Division is concerned about the use of certain aggregates in asphalt mixture because of their durability and performance issues. Good performance of the pavements can be ensured by selecting good-quality aggregates along with asphalt binders that can produce compatible aggregate–binder systems. The primary goal of this research was to determine proper asphalt binders and aggregates for the construction of highways in Arkansas. Three performance grade (PG) asphalt binders, namely PG 64-22, PG 70-22, and PG 76-22, prepared from two different crude sources, were investigated. This study also included four types of ARDOT-commissioned aggregates, namely gravel, sandstone, limestone, and dolomite, from four quarries throughout Arkansas. Selected properties of asphalt binders and aggregates (e.g., physical, mechanical, and chemical) were evaluated by performing a series of routine laboratory tests. To evaluate the performance of the asphalt mixtures, work of cohesion, work of adhesion, and boiling resistance tests were conducted. These aggregates, binders, and aggregate–binder systems were ranked based on the properties obtained from laboratory tests. In general, any combination of dolomite or limestone with a stiffer binder such as PG 76-22 or PG 70-22 is expected to be superior to an asphalt mixture with either sandstone or gravel. The outcomes of this research will help highway agencies and pavement professionals in selecting suitable asphalt binders and aggregates for long-lasting pavement construction. [ABSTRACT FROM AUTHOR]

The article focuses on enhancing contextual ranking models by proposing data augmentation methods to improve ranking performance effectively and robustly. It mentions by utilizing supervised and unsupervised augmentation schemes, along with contrastive losses adapted for ranking tasks, the study demonstrates significant performance improvements, particularly in sample efficiency and robustness across in-domain and out-of-domain benchmarks.

The article focuses on addressing the inefficiency of dual-encoder-based dense retrieval models in information retrieval (IR) by proposing Fast-Forward indexes, which leverage semantic matching capabilities for efficient re-ranking. By enhancing computational efficiency and optimizing memory footprint, Fast-Forward indexes achieve low latency and competitive results in IR tasks without requiring hardware acceleration like GPUs.

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]

Community based question and answer websites; such as, Yahoo Answers, Stack Overflow, Stack Exchange and Quora are briskly generating content in the form of questions and answers posted by users. These online discussion forums allow the users to append and edit the content easily. Therefore, a huge amount of content has accumulated over the time, which is beneficial for the search engine users for addressing their queries to the related content. On the other hand, the task of maintaining the answer quality and ranking of retrieved results has always been a challenging task for the websites that accumulate user's generated data. Here, the problem of ranking the answers based on the user's satisfaction is investigated. The best answers based on their ranking are identified. Three techniques are proposed, which are Relevance Features (REL_FS), Readability Features (RED_FS), and Weighted Answer Rank WEIGHTED ANS_RANK. REL_FS performs a summation of relevance features, RES_FS sums the readability features and WEIGHTED ANS_RANK performs a summation of REL_FS and RED_FS to deal with the task. Proposed methods compute the rank of answers according to both the relevance and readability of answers. Experimental results show proposed methods ability of providing effective ranking of answers for the selection of best answers. Moreover, it also measures the consistency of ranked answers with the help of a detailed correlational analysis. [ABSTRACT FROM AUTHOR]

We investigate three related problems concerning sampling minorities in attributed networks. This is guided by a general attributed network model which can incorporate several levels of homophily and heterophily, and whose degree and Page-rank distributions have known properties. The first problem investigates sampling schemes that favor the representation of the minority over majority nodes and give preference to "more popular" minority nodes (i.e. higher degree/Page-rank) for a given homophily scenario. We show that (in-)degree and Page-rank sampling schemes increase the probability of sampling a minority node. The second problem concerns the relative ranking of minorities compared to majorities in degree and Page-rank based sampling schemes for several homophily and heterophily scenarios. We provide analytical conditions for the minority nodes to rank higher as a function of the model parameters for the degree based samplings and investigate the problem numerically for Page-rank based sampling schemes. The third problem considers subgraph sampling schemes and the bias of the proportion of minority nodes in top ranked degree nodes in several homophily and heterophily scenarios. Finally, the results and findings obtained from the sampling analysis are assessed on real-world networks. [ABSTRACT FROM AUTHOR]

The aim of this study was to investigate the modification of mechanical, rheological, and sensory properties of chickpea pastes and gels by incorporating other ingredients (olive oil or quinoa flour), to develop plant‐based alternatives that meet consumer demands for healthy, natural, and enjoyable food products. The pastes and gels were made with different amounts of chickpea flour (9% and 12%, respectively). For each product, a first set of products with different oil content and a second set with quinoa flour (either added or replaced) were produced. The viscoelastic properties of the pastes and the mechanical properties of the gels were measured. Sensory evaluation and preference assessment were carried out with 100 participants using ranking tests. The study found remarkable differences in rheological, mechanical, and sensory properties of chickpea products upon the inclusion of oil and quinoa flour. The addition of oil increased the viscosity and decreased the elastic contribution to the viscoelasticity of the pastes, while it improved the firmness and plasticity in gels. It also increased the creaminess and preference of both pastes and gels. Replacing chickpea with quinoa flour resulted in less viscous pastes and gels with less firmness and more plasticity. In terms of sensory properties, the use of quinoa as a replacement ingredient resulted in less lumpiness in the chickpea paste and less consistency and more creaminess in both the pastes and gels, which had a positive effect on preference. The addition of quinoa increased the viscosity of pastes and the firmness and stiffness of gels. It increased the consistency and creaminess of both pastes and gels. Quinoa flour and/or olive oil are suitable ingredients in the formulation of chickpea‐based products. They contribute to the structure of the system, providing different textural properties that improve acceptance. [ABSTRACT FROM AUTHOR]

The security of the global Certification Authority (CA) system has recently been compromised as a result of attacks on the Public Key Infrastructure (PKI). Although the CA/Browser (CA/B) Forum publishes compliance requirements for CAs, there are no guarantees that even a commercially successful CA is complying with these recommendations. In this paper, we propose the first systematic CA ranking mechanism that ranks CAs in terms of their adherence to the CA/B Forum and X.509 certificate standards. Unfortunately, there is no consolidated and widely accepted parameter to rank the CAs so we have proposed formula-based rating models and introduced different ranking techniques like Direct, Bayesian, and MarkovChain Ranking. These rankings are applied to a comprehensive dataset of X.509 trust chains gathered during the time period of 2020 to 2023. Our proposed ranking scheme can serve as a criterion for both consumers and enterprises for selecting and prioritizing CAs based on performance as well as adherence to the certificate standards. [ABSTRACT FROM AUTHOR]

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]

The relation between objectivity and subjectivity has been explored for many centuries in many aspects of fields. Most of the approaches used to study their relationship focus on the qualitative research, which is very difficult to resolve a decision problem regarding the closeness of their relation. In this article, we devise a non-parametric statistical mechanism to resolve such decision problem. The mechanism utilises the notion of granular knowledge which is regarded as the product of subjective perception toward objective notions. To measure the degree of conversion, we associate the perception with three metrics, which in turn derive three norms. These norms would measure the degree of the conversion from objectivity to subjectivity. Then by taking the set of Bell partitions as our sample space, and three norms as our statistics, we could then construct their non-parametric distributions. Based on these distributions, we could then conduct the statistical testing whether the subjectivity of a given notion (or target) is significantly related to the objectivity of that notion (or target). [ABSTRACT FROM AUTHOR]

In this present work, a new approach for ranking generalized trapezoidal fuzzy numbers has been introduced. This new proposed method is based on a left and right deviation and fuzzyness measure of the generalized trapezoidal fuzzy numbers. Some propositions have been introduced corresponding to the new proposed method. The proposed method has been compared with the different existing methods of ranking generalized trapezoidal fuzzy numbers. Also, it has been shown that the proposed technique succeeds in overcoming the drawbacks of the existing methods. The proposed method has been applied to a risk analysis problem in the selection of a production house by a retailer. [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]

This paper shows how the leading Higher Education Institutions (HEIs) in the UI GreenMetric World University Ranking communicate their environmental sustainability policies through their websites. Specifically, this paper analyses the presence of sustainability‐related sustainable development goals on the websites of the top 100 universities in the UI GreenMetric World University Ranking (2021). In the area of university social responsibility, sustainability is less commonly communicated, hence the need to delve deeper into the presence of these messages, carrying out a descriptive study using content analysis as a form of data extraction. The conclusion is that neither position in the ranking nor geographic area are decisive for developing better communication about sustainability. In terms of content, sustainability features on the websites are in three key dimensions of the communication of HEIs worldwide (Climate change, Efficiency of sustainable cities and communities and Striving for peace and justice). Thus, the areas for improvement are around the positioning of this sustainability‐related content on their home pages, improving location and format (especially video). Moreover, reinforcing reputational messages, through plans or programmes, as well as improving engagement working on the multi‐directionality to other social media, is required. [ABSTRACT FROM AUTHOR]

Destination sustainability indices, designed to facilitate benchmarking, ranking, and direct competition, are increasingly employed by destinations to showcase their sustainability achievements, meet stakeholder expectations, and attract visitors. Consequently, these indices play a pivotal role in influencing how destinations strategically prioritize their sustainability initiatives. Despite the burgeoning research on sustainability measures, research on market-centric destination benchmarks and rankings remains limited. This letter aims to underscore the distinction between measures that apply a minimum standard approach, for example certifications, and those that allow for benchmarking/ranking in assessing destination sustainability. It argues that the latter holds significant potential to impact sustainable destination development. Thus, it investigates the question of what happens when destination sustainability becomes a point of competition and demonstrates that even meticulously designed indices can encourage counterproductive behaviors, potentially undermining sustainability progress at destinations. Based on this, the letter advocates for a comprehensive investigation into market-oriented sustainability indices and rankings. [ABSTRACT FROM AUTHOR]

Educational assessment is inherently uncertain, where physiological, psychological and social factors play an important role in establishing judgements which are assumed to be "absolute". AI and other algorithmic approaches to grading of student work strip-out uncertainty, leading to a lack of inspectability in machine judgement and consequent problems of trust and reliability. The technique of Adaptive Comparative Judgement (ACJ), in focusing on small-stakes binary comparisons provides an alternative approach to dealing with uncertainty in grading. Rankings can be produced which codify uncertainty, rendering machine judgements inspectable. However, ACJ demands resources in terms of time and the number of people making comparisons. Machine learning trained to make binary comparisons can help to make the process of human comparison more efficient. In combining ACJ and AI, we argue that the result is an analogue-digital system where the physiological/analogue processes of assessment can be coordinated with digital services which steer human assessment to those judgements which are most uncertain requiring most human deliberation. Drawing on our design of such a system developed for medical judgements, we describe a general architecture for human–machine assessment in education and discuss its potential in bridging the gap between analogue human cognition and digital machine learning. [ABSTRACT FROM AUTHOR]

Most images in real life have multi-label attributes. For multi-label images, ideally, the retrieved images should be ranked in descending order of similarity to the query image, namely their numbers of labels shared with the query image decrease sequentially. However, most hashing algorithms are mainly designed for the single label image retrieval, and the existing deep supervised hashing algorithms for multi-label image retrieval ignore the ranking performance of hash codes and do not fully utilize the label category information. To solve this problem, this paper proposed a deep supervised hashing with performanceaware ranking method(PRDH), which could effectively perceive and optimize the performance of the model and improve the effect of the multi-label image retrieval. In the hash learning part, this paper designed a ranking optimization loss function to improve the ranking performance of hash codes. At the same time, this paper adopted a spatial partition loss function to divide images with different numbers of shared labels into corresponding Hamming spaces. In order to fully utilize label information, this paper also explicitly proposed using predictive label for Hamming distance calculation in the retrieval stage, and designed a loss function for multi-label classification to achieve supervision and optimization of Hamming distance ranking. A large number of results of the retrieval experiments conducted in three multi-label benchmark datasets show that the evaluation metrics of PRDH outperform the state-of-the-art hashing approaches. [ABSTRACT FROM AUTHOR]

Lexicographic methods to rank fuzzy numbers present the advantages of simplicity, consistency with human intuition, and power of discrimination. In this paper, we tackle the problem of finding the conditions for these methods to produce a rank in specific steps. Our main results are twofold. First, we prove that a necessary and sufficient condition for a ranking function to be a total order is that this function is either injective, surjective, or bijective. Second, we provide further insight into the required steps for a lexicographic order to rank same-type and different-type fuzzy numbers. A counterexample refutes a conjecture in the literature about the maximum number of steps needed to rank different-type fuzzy numbers. [ABSTRACT FROM AUTHOR]

Atanassov's intuitionistic fuzzy sets (IFSs) are a very convenient tool for describing alternatives/options while making decisions because they make it possible to naturally represent the pros, cons, and hesitation. The IFSs have attracted a significant interest and have been applied in various fields. Of course, their use poses some challenges. One of the main challenges is the ranking of alternatives/options described by the intuitionistic fuzzy sets, to be called for brevity the intuitionistic fuzzy alternatives. This is a crucial issue, notably for the applications, for instance, in decision making. We first present in detail and analyze the benefits of a method we introduced previously (cf. Szmidt and Kacprzyk [1]). For this method, we augment the original assumptions with an additional assumption, which is justified and inherently reasonable. As a result, we obtain formulas which are better justified than those previously used as they explicitly consider the arguments in favor (pro), against (con), and hesitance. Since the intuitionistic fuzzy alternatives can not be linearly ranked, then the additional assumptions during the ranking process are necessary. We address these issues and analyze examples to clarify our new approach. We examine some other methods discussed in the literature and analyze their results, and show that the new assumptions reconcile some misconceptions raised by those other papers. [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]

Lexicographic orders produce a total order over a set of fuzzy numbers by comparing several real-valued functions of each fuzzy number under consideration following a strictly hierarchical method. Lexicographic orders present advantages such as simplicity, consistency with human intuition, and power of discrimination. In this paper, we move one step forward in the search for simplicity by proposing a simplified version of lexicographic orders that focuses on the defining parameters of fuzzy numbers instead of using more complex functions as is common in the existing methodologies. More precisely, we show that two lexicographic methods described in the literature for trapezoidal and triangular fuzzy numbers are equivalent to the lexicographic order of a reorganization of the vector of defining parameters, reducing the complexity of the methods. We illustrate our approach through numerical examples and a case study about capital adequacy in the banking sector. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of the study is to measure the performance level of halal compliance practices by the halal-certified restaurants in Malaysia and rank and rate them based on several dimensions of halal compliance. Design/methodology/approach: A total of 320 halal restaurants were surveyed. The absolute measurement approach of the analytic hierarchy process (AHP) was applied to rank and rate the restaurants. Finally, ANOVA and independent t-test were applied to assess if there is any significant difference in halal compliance performance between different groups of the respondents. Findings: The AHP application resulted in only 19 restaurants (5.94%) achieving an "Excellent" rating. A significant difference has been observed between different groups of the respondents regarding their halal compliance performance. Research limitations/implications: An onsite audit and ranking of all the restaurants in Malaysia were beyond the scope of the study. The research was able to rank only 320 restaurants across Malaysia. Practical implications: The findings and methodology of the study will provide policymakers with a clear roadmap for establishing a comprehensive rating system in the fields of the halal food industry to enhance the quality and integrity of the halal food management system. Originality/value: To the best of the authors' knowledge, this is the first time an empirical approach, like AHP, has been used to determine how Malaysia's halal-certified restaurants stack up against one another. Similar studies can be carried out in other sectors of the halal industry as well as in similar context. [ABSTRACT FROM AUTHOR]

Effective summarization of long documents is a challenging task. When addressing this challenge, Graph and Cluster-Based methods stand out as effective unsupervised solutions. Graph-Based Unsupervised methods are widely employed for summarization due to their success in identifying relationships within documents. Cluster-Based methods excel in minimizing redundancy by grouping similar content together before generating a concise summary. Therefore, this paper merges Cluster-Based and Graph-Based methods by applying language models for Unsupervised Extractive Summarization of long documents. The approach simultaneously extracts key information while minimizing redundancy. First, we use BERT-based sentence embeddings to create sentence clusters using k-means clustering and select the optimum number of clusters using the elbow method to ensure that sentences are categorized based on their semantic similarities. Then, the TextRank algorithm is employed within each cluster to rank sentences based on their importance and representativeness. Finally, the total similarity score of the graph is used to rank the clusters and eliminate less important sentence groups. Our method achieves comparable or better summary quality and reduced redundancy compared to both individual Cluster-Based and Graph-Based methods, as well as other supervised and Unsupervised baseline models across diverse datasets. [ABSTRACT FROM AUTHOR]

Composite materials obtained by sintering glass microspheres are considered the promising ones for the underwater technology. The high indicators of the hydrostatic strength combined with the heat and sound insulation properties are due to the microspheres maintaining their shapes as close to the spherical as possible. The computer model of the temperature distribution is developed based on the physical and chemical conceptions of the glass composites structure formation by sintering the glass microspheres of sodium borosilicate composition and processing the experimental results of the temperature measurements. The modeling methodology is based on the principles of decomposition of the task by the researcher and ranking the temperature and time parameters. The ratio of the hydrostatic strength to the density of the samples is taken as a functional criterion and the software application is written in the Python language. The experimental setup that is used for sintering the glass microspheres enables to study the temperature fields and thermal deformation processes in real-time conditions. The coefficients of thermal conductivity of sintering are determined by the regular mode method. The results obtained are aimed at solving one of the most important scientific and practical issues of developing technologies for manufacturing glass composites for strategic purpose. [ABSTRACT FROM AUTHOR]

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.