Comparison Of Rankings Research Articles

Microscopic adsorption study from coal rank comparison on the feasibility of CO2-rich industrial waste gas injection enhanced coal bed methane recovery

A new method of injecting CO2-rich industrial waste gas (CO2-rich IWG) to displace coal bed methane (CBM) is proposed for energy conservation and green growth. In this study, theadsorption mechanisms of this method were studied by the Giant canonical Monte Carlo and molecular dynamics methods in macromolecular coal models with three ranks (brown, bituminous, and anthracite coal). It is found that the proportion of gas molecules in the adsorbed state is higher in the anthracite coal slit than in the brown and bituminous slits, indicating that anthracite coal seams are more appropriate for waste gas sequestration. The adsorption selectivity of NO and CO2 is consistent among the three coal ranks, with the order of brown > bituminous > anthracite > 1.0, and that of N2 orders as 1.0 > bituminous > anthracite > brown.This is due to the different dominant factors affecting the competitive adsorption between different waste gas components and CBM, namely competition for adsorption sites in the NO and CO2 systems and thefilling effect in the N2 system. There is a positive correlation between the number of major competitive adsorption sites and the adsorption selectivity of theCO2(NO) system. CO2 and CH4 compete for COC structures in brown and bituminous coal and OH structures in anthracite coal, and OH structures in the three coals are the major adsorption sites for NO systems. Our work advances the understanding of the microscopic adsorption mechanisms of CO2-rich IWG in the CBM reservoirs, which provides a theoretical basis for CO2-rich injection-enhanced CBM recovery technology.

Peripartum Cardiomyopathy and Social Vulnerability: An Epidemiological Analysis of Mortality Outcomes.

Peripartum cardiomyopathy (PPCM) outcomes have been previously linked to demographic and social factors. The social vulnerability index (SVI) is a measure of social vulnerability in the United States. We explored PPCM disparities and the impact of SVI on PPCM mortality. Mortality from 1999 to 2020, SVI, and demographic data were obtained from CDC databases. County-specific SVI rankings were linked to PPCM age-adjusted mortality rates (AAMRs), allowing for a comparative analysis of AAMRs across both cumulative populations and subpopulations to identify disparities. All US counties were then stratified into low- and high-SVI groups, facilitating comparison of SVI rankings by estimation of excess-deaths per 1 000 000 person-years attributable to greater social vulnerability and rate ratios (RR) through univariable Poisson regression. We identified a total of 1026 deaths related to PPCM between 1999 and 2020. Overall AAMR increased from 0.180 in 1999 to 0.326 in 2020. Black populations (AAMR: 1.081) and Southern US counties (AAMR: 0.444) had the highest AAMRs compared with other racial and US census groups, respectively. Higher SVI accounted for 0.172 excess deaths per 1 000 000 person-years (RR=1.800). Among Black and White populations, higher SVI also accounted for 0.248 and 0.071 excess deaths per 1 000 000 person-years, respectively. Similar impacts of greater social vulnerability were observed when comparing the US census regions (Northeast RR=1.609, Midwest RR=1.819, South RR=1.934, West RR=1.776). PPCM mortality disparities exist across racial and geographic populations in the United States. A greater burden of social vulnerability is associated with higher PPCM mortality on a national level.

Scopus Citation Metrics for Top and Bottom Quintile Kinesiology-Related Journals

ABSTRACT Journals are often ranked by citation metrics to classify them into ordinal categories (e.g. quartiles or quintiles) of prestige. This study compared five journal metrics and their associations for the top and bottom quintiles of a large sample of kinesiology-related journals. Top and bottom quintiles (n = 70) based on SCImago Journal Rank (SJR) for 2023 were identified. Descriptive data and associations between SJR, total documents, total citations, external citations per document, and percentage of uncited documents were calculated. All journal metrics in both quintiles were highly variable, and most were positively skewed. Most median metrics differed across quintiles by a factor of 3.6 to 7.8 times, although median total citations to top quintile journals were 30 times larger than bottom quintile journals due to more total documents in top quintile journals. Most (5 and 7) of the 10 associations between the journal metrics were significant (p < .01) for the top and bottom quintiles, respectively. Results confirm previous research that SJR is a positively skewed, highly variable, and unrealistically precise proxy estimate of the prestige of kinesiology-related journals. Several prestige metrics might be carefully interpreted to approximate general perceptions of journal prestige. Current evidence does not, however, support the precise ranking or numerical comparison of kinesiology journals into clear top-tier prestige status given the coverage and subdisciplinary bias, skew, and variability in most journal metrics.

Beyond directed hypergraphs: heterogeneous hypergraphs and spectral centralities

Abstract The study of hypergraphs has received a lot of attention over the past few years, however up until recently there has been no interest in systems where higher order interactions are not undirected. In this article, we introduce the notion of heterogeneous hypergraphs from an algebraic point of view, which have traditional directed hypergraphs as a particular case. We furthermore analytically study the spectral centralities associated to some types of heterogeneous hypergraphs, extending previously defined eigenvector-like centrality measures to this new realm. We supplement the analytical arguments with some numerical comparisons of pairwise and higher order rankings, and we construct directed higher order networks from real data, which we then use for discussion and analysis.

CN108 Comparison of symptom distress ranking between oncology nurses and pediatric patients receiving chemotherapy

CN108 Comparison of symptom distress ranking between oncology nurses and pediatric patients receiving chemotherapy

FEATURES OF SAFETY CULTURE ASSESSMENT BY USING THE METHOD OF ANALYSIS OF HIERARCHIES BASED ON THE SURVEY OF TEACHERS OF CLINICAL DEPARTMENTS OF THE DENTAL PROFILE

Aim. Determining the features of safety culture, the assessment by using the method of analysis of hierarchies based on the survey of teachers of clinical departments of the dental profile and establishing its main stages. Materials and methods. The research was conducted on the basis of departments of stomatological profile O. O. Bogomolets National Medical University using hygienic, medical sociological and statistical methods, which should be considered a prerequisite for the implementation of the method of analysis of hierarchies (methodology of group examination followed by ranking and pairwise comparison). Results. Based on the application of the method of analysis of hierarchies based on a survey of teachers of clinical departments of the dental profile, the leading components of safety culture were determined, namely: the degree of influence on the level of safety culture and the patient's body of the leading characteristics of dangerous actions of medical personnel related to the operation of equipment, the organization of medical and diagnostic process, use of means of individual and collective protection (component No. 1); the degree of influence on the level of safety culture and the patient’s organism of both strengths and weaknesses in creating the safety of the treatment environment through the culture of awareness, reporting, justice, training (component No. 2), the degree of influence on the level of safety culture and the patient's organism of hygienic and safe working conditions at the workplace of medical personnel (component No. 3), as well as a scientifically based algorithm for assessing the level of safety culture in modern health care institutions. Conclusions. The created algorithm for analytical assessment of the level of safety culture in modern health care institutions provides for the implementation of the following stages: determination of the structural features of the leading components of safety culture and the development of a scoring scale for their evaluation; carrying out an expert assessment of the leading components of the safety culture and establishing the degree of consistency of experts' opinions; calculation of the weighting coefficients of the influence of various components on the formation of a certain level of safety culture; justification of objective statistical approaches to assessing the level of safety culture.

Adaptive multi-criteria decision making for electric vehicles: a hybrid approach based on RANCOM and ESP-SPOTIS

In today’s globalized technological area, aligning decisions with customer preferences is crucial yet challenging due to the complexities and uncertainties involved. Multi-Criteria Decision Analysis (MCDA) serves as a vital tool for constructing support systems that cater to customer-centric trends. While existing MCDA methods vary in their calculation concepts, some prioritize ideal solutions, while others accommodate personalized preferences within dynamic decision contexts. Moreover, determining the relevance of criteria based on expert knowledge adds another layer of personalization to the evaluation process, further individualizing decision-making. However, current decision models often fail to integrate these concepts, leaving a gap in how recommendations can be enhanced when both are combined. To address these challenges, this paper introduces an innovative approach integrating Ranking Comparison and Expected Solution Point Stable Preference Ordering Towards Ideal Solution methods. This hybrid model incorporates personalization into multi-criteria evaluation, catering to individual preferences. By representing customer preferences through two distinct measures, the proposed approach ensures personalized recommendations aligned with decision-makers’ needs. The efficacy of the hybrid model was validated through its application to the electric vehicle selection problem. The verification process highlighted potential disparities compared to other multi-criteria approaches, establishing a consumer preference-based Decision Support System approach for more precise and personalized selection recommendations.

Optimal truss design with MOHO: A multi-objective optimization perspective.

This research article presents the Multi-Objective Hippopotamus Optimizer (MOHO), a unique approach that excels in tackling complex structural optimization problems. The Hippopotamus Optimizer (HO) is a novel approach in meta-heuristic methodology that draws inspiration from the natural behaviour of hippos. The HO is built upon a trinary-phase model that incorporates mathematical representations of crucial aspects of Hippo's behaviour, including their movements in aquatic environments, defense mechanisms against predators, and avoidance strategies. This conceptual framework forms the basis for developing the multi-objective (MO) variant MOHO, which was applied to optimize five well-known truss structures. Balancing safety precautions and size constraints concerning stresses on individual sections and constituent parts, these problems also involved competing objectives, such as reducing the weight of the structure and the maximum nodal displacement. The findings of six popular optimization methods were used to compare the results. Four industry-standard performance measures were used for this comparison and qualitative examination of the finest Pareto-front plots generated by each algorithm. The average values obtained by the Friedman rank test and comparison analysis unequivocally showed that MOHO outperformed other methods in resolving significant structure optimization problems quickly. In addition to finding and preserving more Pareto-optimal sets, the recommended algorithm produced excellent convergence and variance in the objective and decision fields. MOHO demonstrated its potential for navigating competing objectives through diversity analysis. Additionally, the swarm plots effectively visualize MOHO's solution distribution of MOHO across iterations, highlighting its superior convergence behaviour. Consequently, MOHO exhibits promise as a valuable method for tackling complex multi-objective structure optimization issues.

Converting estimated breeding values from the observed to probability scale for health traits

Dairy cattle health traits are paramount from a welfare and economic viewpoint, and modern breeding programs therefore prioritize the genetic improvement of these traits. Estimated breeding values for health traits are published as the probability of animals staying healthy. They are obtained using threshold models, which assume that the observed binary phenotype (i.e., healthy or sick) is dictated by an underlying normally distributed liability exceeding or not exceeding a threshold. This methodology requires significant computing time and faces convergence challenges, as it implies a nonlinear system of equations. Linear models have more straightforward computations and provide a robust approximation to threshold models; thus, they could be used to overcome these challenges. However, linear models yield estimated breeding values on the observed scale, requiring an approximation to the liability scale analogous to that from threshold models to later obtain the estimated breeding values on the probability scale. In addition, the robustness of the approximation of linear to threshold models depends on the amount of information and the incidence of the trait, with extreme incidence (i.e., ≤5%) deviating from optimal approximation. Our objective was to test a transformation from the observed to the liability, and then to the probability scale, in the genetic evaluation of health traits with moderate and very low (extreme) incidence. Data comprised displaced abomasum (5.1 million), ketosis (3.6 million), lameness (5 million), and mastitis (6.3 million) records from a Holstein population with a pedigree of 6 million animals, of which 1.7 million were genotyped. Univariate threshold and linear models were performed to predict breeding values. The agreement between estimated breeding values on the probability scale derived from threshold and linear models was assessed using Spearman rank correlations and comparison of estimated breeding values distributions. Correlations were at least 0.95, and estimated breeding value distributions almost entirely overlapped for all the traits but displaced abomasum, the trait with the lowest incidence (2%). Computing time was ∼3 times longer for threshold than for linear models. In this Holstein population, the approximation was suboptimal for a trait with extreme incidence (2%). However, when the incidence was ≥6%, the approximation was robust, and its use is recommended along with linear models for analyzing categorical traits in large populations to ease the computational burden.

Second Language Writing Anxiety among Faculty Scholars of a State University in the Philippines and Its Sex-Disaggregated Data

The study investigated the causes and the nature of writing anxiety specifically in the use of English as the second official language of the Philippines. Further, it accounted and analyzed its sex-disaggregated data. This was done among faculty scholars of Central Luzon State University. The respondents were randomly chosen from among the purposively identified faculty scholars of the university pursuing their graduate degrees - master’s and doctorate, in the different graduate curricular offerings in various universities in the Philippines and abroad, that require a thesis or dissertation as the final requirement for obtaining a graduate degree. The Second Language Writing Anxiety Inventory (SLWAI) of Cheng (2004), a questionnaire composed of 22 items with three open-ended questions was used to collect responses. The responses were scored and measured on a five-point Likert response scale. The differences in Second Language Writing Anxiety (SLWA) between male and female participants were analyzed using the Mann-Whitney Test, which is ideal for analyzing statistically the difference between the distributions of data of unparalleled groups with the comparison of ranks and scores. Based on the study findings, the most prominent nature of SLWA among participants is cognitive anxiety. Other sources of anxiety include the availability of external and internal resources and environmental elements. In relation to sex, males scored higher in terms of the level of anxiety compared to females. Lastly, it is forwarded that educators and the pedagogical approach may utilize a positive feedback mechanism as negative evaluation promotes anxiety even in composing in a second language.

A Probabilistic Evaluation of Surface Loading and Concentration as Metrics for Post Structural Fire Assessment Soot Sampling Data

Surface sampling and laboratory analysis for soot/combustion particulates was conducted following a fire at an education/research facility in the southwest United States. This provided a bank of data by which to probabilistically evaluate the behavior of soot loading (counts/mm2) and relative soot concentration (percent ratio; %R) as useful metrics for quantifying differences in soot impact across a building. Surface tape sampling and analysis via light microscopy were conducted via industry standard protocols, and resulting data from various building zones were selected to construct various comparisons. The performance of counts/mm2 and %R as metrics to identify differences in soot impact for each comparison was assessed by comparing inference generated by traditional Student’s t test, Mann Whitney U rank comparison (MW), and the directly calculated axiomatic probability associated with difference in detection (pΔfd). The fourteen (14) comparisons in which a significant difference was inferred via pΔfd was similarly indicated via Student’s t and/or MW in only four (4) instances. Further, approximately one half of the comparisons generated different inference via pΔfd for counts/mm2 and %R, with the former demonstrating better discriminatory ability. In broad view, the heuristic concept of comparing numerical “soot levels” (e.g., average) by either metric was not generally suitable for the distribution of the data. In contrast, pΔfd avoids the statistical bias imposed by traditional statistical inference, and ultimately the efficacy of post fire comparative surface sampling is as dependent upon the metric and inference model utilized as it is on the sampling and laboratory analytical protocols.

INVESTIGATING THE EFFECTS OF COVID-19 ON TOURISM IN THE G7 COUNTRIES

Natural and human-made crises can significantly impact the development of countries’ tourism industries. The susceptibility of countries to these crises depends on their policies, planning, and management in facing diverse challenges. This article aims to investigate the effects of the COVID-19 pandemic on the tourism industry in G7 countries by comparing rankings and positions on indices in 2016 and 2020. Data collected from the RANking COMparison (RANCOM), Proximity Indexed Value (PIV), and Double Normalization Compromise Ranking of Alternatives from Distance to Ideal Solution (DNCRADIS) models have been utilized for data analysis. The research findings indicate noticeable differences in using different models, as the rankings and positions of G7 countries for the years 2016 and 2020, except for two countries, the United States and France, have been different. The research results demonstrate that the COVID-19 crisis had significant impacts on the tourism industries of G7 countries. Countries like the United States, France, and the United Kingdom appear as leading nations in the tourism industry, while Japan and Canada faced challenges, and Germany and Italy experienced changes in their positions. Based on these results, officials and planners in the tourism industry of G7 countries can make appropriate decisions for the development and improvement of tourism under similar crisis conditions. Moreover, these findings can serve as a valuable guide for other countries in managing similar crises in the tourism industry.

A comprehensive approach to enhance wood cutting productivity: Integration of spherical fuzzy DEMATEL and artificial neural networks

Productivity plays a pivotal role in profitability and success of business. In this study, the wood cutting activity in Indian sawmills is selected. This study replicates the novel approach by integrating spherical fuzzy DEMATEL (Decision Making Trial and Evaluation Laboratory) and artificial neural networks (ANN) to improve the wood cutting productivity in Indian sawmills. The measure of betterness is selected as net productivity rate (NPR), a time-based labor productivity measure. The methodology unfolds in two crucial steps. First, SF-DEMATEL is employed to unearth influential factors affecting wood cutting, delving into their interrelationships through fuzzy logic. This process provides relationships between key determinants and their interconnected dynamics. Secondly, an ANN, a machine learning algorithm, is harnessed to predict wood cutting performance based on these identified factors. The ANN is trained using historical or simulation data, paving the way for predictions under diverse scenarios. The novelty of this approach lies in its holistic precision. The results showcase that lifting index and log weight emerge as primary influencers on productivity, with NPR, occupational risk index, and perceived exertion ranking lower. In the grand tapestry of factors, the study unveils universal driving forces, such as the weight of the log and lifting index. The ANN model, attaining a remarkable RMSE = 0.0478 and R2 = 0.9783 for training set and for training data and RMSE = 0.0487 and R2 = 0.9727 for testing data. This contributes to the comprehensive ranking comparison of factors derived from both Fuzzy DEMATEL and ANN. In summation, the fusion of Fuzzy DEMATEL and ANN unravels the intricacies of wood cutting dynamics. By identifying key factors and predicting performance, this approach provides a transformative gateway to enhance wood cutting quality and efficiency, thereby elevating the overall productivity of the woodworking industry.

Application in environmental art design practice based on a fuzzy evaluation system

Environmental art design (EAD) has recently encouraged creative thinking by investigating novel materials, technologies, and techniques for designing environmental art that advances sustainability. EAD faces challenges in integrating novel materials and technologies while promoting sustainability. Environmental art design is targeted at human living areas; here, adequate and excessive utilization of resources is minimized, and the social and natural environments are utilized aesthetically. Aesthetic excellence in environmental art design, along with growing technological accomplishments and cultural heritage, is concentrated on meeting the demands of human aesthetic pursuits in the new era, which lacks earlier techniques. Hence, an algorithm named environmental art design using fuzzy (EADF) to evaluate the environmental criteria for better decision-making is introduced. Initially, a fuzzy-based technique for order preference similar to the ideal solution (FTOPSIS), which considers multiple variables such as visual appeal, environmental impact, sustainability, and audience involvement in the community, was employed in the design process. Environmental art designers utilize fuzzy TOPSIS to assess works of art using several criteria. It seeks to make accurate decisions and accomplish desirable creative effects by considering ambiguity and subjectivity. The approach utilizes fuzzy variable entropy analysis to determine questionable attribute weightings and employs triangular fuzzy numbers to represent criteria and analyze preference values. Artworks are evaluated for deviation from ideal results using the Euclidean distance measure, enabling logical ranking evaluation and comparison. The EADF model outperforms the other models when considering different input factors. EADF excels in color (83.74), composition (82.37), emotion (85.61), contrast (97.52), clarity (98.16), harmony (95.49), and sensitivity (96.44) when evaluated in environmental art design, showcasing its usefulness. This work has implications for directing artists, designers, and decision-makers toward environmentally sustainable and artistically impactful art practices. Hence, the performance of this EADF model is validated using audience involvement, environmental impact, sustainability, and a visual appeal score.

Comparative efficacy of antioxidant therapies for sepsis and septic shock in the intensive care unit: A frequentist network meta-analysis

BackgroundAntioxidant therapy is gaining traction in managing sepsis and septic shock, owing to its perceived positive impact on patient outcomes. This study sought to compare the efficacy of five antioxidant therapies (melatonin, vitamin C, vitamin E, selenium, and N-acetylcysteine, both individually and in combination with other compounds such as vitamin B1, hydrocortisone, propolis, and glutamine) in treating sepsis or septic shock in the intensive care unit (ICU). MethodsThe study involved randomized and multi-arm trials with sepsis or septic shock patients using melatonin, vitamin C, vitamin E, selenium, or N-acetylcysteine. Studies were sourced from PubMed, Embase, Cochrane Library, ClinicalTrials.gov, and WHO - Clinical Trials Registry Platform for the frequentist network meta-analysis on 28-day mortality and Sequential Organ Failure Assessment (SOFA) scores. The risk of bias was assessed using the Physiotherapy Evidence Database scale. Therapies were compared directly and indirectly using R software. ResultsThe study of 56 trials involving 9,366 patients was included. Bias assessment revealed that 89.3 % of trials achieved excellent or good quality. Based on treatment ranking and pairwise comparisons, melatonin with propolis (SUCRA = 93.29 %) is effective in improving SOFA scores, statistically significant, with no publication bias (p= 0.73). High-dose vitamin C (SUCRA = 83.97 %), vitamin C with vitamin B1 (SUCRA = 78.72 %), and melatonin (SUCRA = 67.03 %) are potential therapies for organ dysfunction. Melatonin (SUCRA = 88.22 %) and high-dose vitamin C (SUCRA = 80.75 %) were the most effective in reducing 28-day mortality rates. However, analysis indicated that the results for 28-day mortality rates were not statistically significant. Also, these results contained publication bias (p= 0.02). ConclusionThe study offers fresh perspectives on antioxidant therapy treatments for sepsis or septic shock in ICU, emphasizing the combination of melatonin and propolis notably reduces SOFA scores for those patients.

The Attitude of the Criminogenic Individual Social Environment

Social environment of a person has a significant impact on criminalization of a person . Scientific literature analyzes the criminogenic influence of its individual participants — family members and relatives, members of informal groups and communities . Consequently, its structural organization, key functions of relations with social environment, possibilities of their change for decriminalization and post-penitentiary reintegration are unclear . Objective of the study: to examine relationship of a criminogenic person with social environment . Methods: method of data collection is a survey . Parameters of social environment that are studied: volume, stability, homogeneity, limitations of autonomy and reference; studied characteristics of interaction: received support and assistance, effectiveness of interaction, influence . The methods of processing results are descriptive statistics and rank comparison criterion (Mann-Whitney U-criterion) .The study sample consists of 388 people, 171 of whom are classified as persons with law-abiding behavior (Mean age — 36,3 years, SD — 12,3 years; men — 77 %) . The remaining part is made up of persons under administrative supervision, of whom 114 persons were under criminal punishment for the first time (Mean age — 31 .5 years, SD — 8 .42 years; men — 84 %); 103 persons who had been previously subjected to criminal punishment (Mean age — 37 .7 years, SD — 11 .13 years; men — 73 %) .Results and novelty: new information was obtained about parameters of social environment of a person with criminogenic behavior (small volume, high stability of composition and homogeneity of participants, low referentiality, selectivity of social relations) . The influence of parameters of social environment of a person and relations with it on post-penitentiary re-integration is noted.

Location selection for offshore wind power station using interval-valued intuitionistic fuzzy distance measure-RANCOM-WISP method

The development opportunities and high-performance capacity of offshore wind energy project depends on the selection of the suitable offshore wind power station (OWPS) location. The present study aims to introduce a decision-making model for assessing the locations for OWPS from multiple criteria and uncertainty perspectives. In this regard, the concept of interval-valued intuitionistic fuzzy set (IVIFS) is utilized to express uncertain information. To quantify the degree of difference between IVIFSs, an improved distance measure is proposed and further utilized for deriving the objective weights of criteria. Numerical examples are discussed to illustrate the usefulness of introduced IVIF-distance measure. The RANking COMparison (RANCOM) based on interval-valued intuitionistic fuzzy information is presented to determine the subjective weights of criteria. With the combination of objective and subjective weights of criteria, an integrated weighting tool is presented to find the numeric weights of criteria under IVIFS environment. Further, a hybrid interval-valued intuitionistic fuzzy Weighted integrated Sum Product (WISP) approach is developed to prioritize the OWPS locations from multiple criteria and uncertainty perspectives. This approach combines the benefits of two normalization tools and four utility measures, which approves the effect of beneficial and non-beneficial criteria by means of weighted sum and weighted product measures. Further, the developed approach is applied to the OWPS location selection problem of Gujarat, India. Sensitivity and comparative analyses are presented to confirm the robustness and stability of the present WISP approach. This study provides an innovative decision analysis framework, which makes a significant contribution to the OWPS locations assessment problem under uncertain environment.

Possibilities for ranking business schools and considerations concerning the stability of such rankings.

In this article, we discuss possibilities for ranking business schools and analyse the stability of research rankings using different ranking methods. One focus is set on a comparison of publication-based rankings with citation-based rankings. Our considerations and discussions are based on a (small) case study for which we have examined all (six) business schools at public universities in Austria. The innovative aspect of our article is the chosen mix of methods and the explicit comparison of the results of a publication analysis with those of a citation analysis. In addition, we have developed a new indicator to check the stability of the obtained ranking results with regard to the individual business schools. The results show that the ranks of the individual business schools are quite stable. Nevertheless, we found some differences between publication-based and citation-based rankings. In both cases, however, the choice of the data source as well as switching from full to adjusted counting only have little impact on the ranking results. The main contribution of our approach to research in the field of university rankings is that it shows that focusing on a single (overall) indicator should be avoided, as this can easily lead to bias. Instead, different (partial) indicators should be calculated side by side to provide a more complete picture.

Safety assessment of existing glass curtain wall based on fuzzy entropy and comprehensive cloud

The occurrence of safety incidents for existing glass curtain walls (EGCWs) pronounced menace to the security of both lives and property. Undertaking safety assessment for EGCWs carries essential practical significance. However, current fuzzy evaluation methods overlook the uncertainty of indicator weights and the intricacies of rank attribution. In response, this paper proposes a novel approach to the safety assessment of EGCWs. This research establishes a framework of evaluation indicators for EGCWs and divides the safety ranks of each indicator into four tiers: Safe, Mild risk, Moderate risk, and High risk. Quantitative and qualitative indicators are quantified via the variable fuzzy cloud algorithm and cloud model. The information cloud combination weighting method is introduced to determine the weight clouds of indicators. Finally, a two-dimensional assessment result is derived using an improved fuzzy comprehensive evaluation method and fuzzy entropy. The exemplified outcomes demonstrate that this approach captures the safety status of evaluation subjects based on risk ranks, and fuzzy entropy addresses two issues: inconsistent level attribution and the comparison of identical risk ranks. The appraisal method further unveils the safety details of EGCWs, with findings that align consistently with the actual situation.

Comparison of the Representation Rankings of Social Harms Threatening the Family Institution in Iranian Cinema during the 1990s and 2000s

Comparison of the Representation Rankings of Social Harms Threatening the Family Institution in Iranian Cinema during the 1990s and 2000s