Ranking Research Articles

ABSTRACT Menstrual cycle (MC) phases may impact athletic performance due to the non-reproductive actions of 17-β-oestradiol and progesterone, which fluctuate across the MC. Research often includes recreational athletes, with findings generalised to elite athletes. To inform evidence-based practice and future research, the scope and quality of studies examining the relationship between athletic performance and MC phases in elite female athletes must be evaluated. This study audited these studies. Eleven studies, involving 218 athletes, were included. Of these studies, 91% (n = 198) of athletes were categorised as tier 4 (elite/international level) and 9% (n = 20) as tier 5 (world-class). The majority of studies (55%, n = 6) relied solely on calendar-based counting to delineate MC phases, while 45% (n = 5) incorporated calendar-based counting and biochemical methods. A methodological quality ranking system for MC phase determination revealed that one study achieved gold-tier status (9%); 18% achieved silver, 55% bronze, and 18% were ungraded. Research on the effects of MC phases on athletic performance in elite female athletes is of low methodological quality due to an overreliance on calendar-based counting without biochemical verification. Future research should verify MC phases to improve the research impact for elite female athletes.

We classify periodic $Y$-systems of rank 2 satisfying the symplectic property. We find that there are six such $Y$-systems. In all cases, the periodicity follows from the existence of two reddening sequences associated with the time evolution of the $Y$-systems in positive and negative directions, which gives rise to quantum dilogarithm identities associated with Donaldson-Thomas invariants. We also consider $q$-series called the Nahm sums associated with these $Y$-systems. We see that they are included in Zagier's list of rank 2 Nahm sums that are likely to be modular functions. It was recently shown by Wang that they are indeed modular functions.

This review paper provides a comprehensive comparative analysis of global university ranking systems, including Times Higher Education (THE), Academic Ranking of World Universities (ARWU), and the Center for World University Rankings (CWUR). The paper evaluates how these ranking agencies use different indicators such as teaching quality, research performance, international outlook, and industry income. It also highlights the limitations of these metrics and suggests how modern data analytics tools like Python and Power BI can improve the reliability of ranking outcomes. This study serves as a bridge between traditional ranking methodologies and advanced analytical approaches, offering insights for educational policymakers and researchers

The article comprehensively examines certain aspects of the functioning of the system of selection, personnel training, the system of state examinations and re-certifications of the civil service apparatus of medieval China during the Tang dynasty (618 – 907). The reasons for the emergence of the state examination system, its features, the system of ranks, and the features of appointment to positions are analyzed. The meritocratic system of state examinations, on the one hand, provided access to state positions to representatives of different social strata, and on the other hand, did not guarantee obtaining these same positions. It is proved that the outdated system of forming the civil service apparatus did not meet the interests of the Tang dynasty, when the territory and population increased, the emperor's power was strengthened, and therefore the centrifugal influences and confrontations of local elites deepened. The features of state examinations, their subject component and features of their conduct are considered. An analysis of official ranks, their functions and powers are carried out. It was found that the highest-ranking officials in the state were, as a rule, persons with the title of jinshi. The system of forming official cadres was complex, since candidates could pass exams and obtain positions through recommendations or bribes. The personnel policy of the rulers of the Tang dynasty created a dual structure of the bureaucracy and its career paths, interest groups, which left a clear imprint on the work of the Chinese bureaucracy. Many works on the history of the Tang dynasty bureaucratic apparatus mention mainly titles, positions, but almost do not describe “positions without responsibilities” and many other aspects. The imperial examination system alleviated acute social conflicts by fairly selecting talents in the localities, it optimized the traditional social structure and worked as a “social elevator” for young people from the provinces. The new system of formation of the bureaucratic apparatus encouraged people to study diligently and created a positive environment, maintaining a harmonious social order according to the traditional Confucian system of relationships and values in society.

As in many countries, neoliberal policies have affected the field of education in Turkey. The competitive school ranking system and its meritocratic narratives have shaped students’ aspirations and their understanding the sources of success and failure. This study reveals the resonance of these policies on individuals. Through in-depth interviews with high-school students in Istanbul, this phenomenological qualitative study engaged with 29 students intensely. It is found that individuals aspired to reach top positions within the neoliberal system. Which corresponds to entering Anatolian High Schools in the Turkish education system. Often influenced by parents who helped to deliver the system’s messages, students themselves ignore their abilities and strive for promising positions in the market. They viewed themselves as solely responsible for their academic failures. However, this article suggests that student failure results from an educational system that encourages all students to pursue the same goals while ignoring their unique talents and predispositions.

Abstract Background Speech intelligibility is the degree to which the speaker’s intended message is recovered by the listener. There are several measures available for speech intelligibility assessment. Multiple studies have examined speech intelligibility assessments across different languages and populations. However, there remains a lack of specific speech intelligibility tests for Indian languages. The present study aims at the development of test stimuli and content validation of language-free word stimuli to assess speech intelligibility. Method The study was conducted in four phases which includes the following: enumerating consonants available in the Dravidian language family and content validation; development and content validation of language-free word stimuli to assess speech intelligibility; content validation of audio-recorded language-free word stimuli, and development and content validation of rating scale and administration of test stimuli in neurotypical individuals . Results Initially, a total of 17,756 words using combination generation in Excel, which was narrowed down to 4000 trisyllabic words with the vowel /a/. Further refinement resulted in 348 trisyllabic words based on the frequency of phonemes in Dravidian languages, considering all consonant positions. Content validation was conducted using the Delphi technique. The final selection of trisyllabic words was based on the content validation ratio (CVR) and content validation index (CVI) scores, resulting in 119 relevant words. The recording of those words was carried out by four speakers (two male and two female). Those recordings were validated by two speech-language pathologists using a ranking system. Based on the ranking, the investigator selected a male speaker who had the best clarity as a source of recording. The investigator administered the prerecorded trisyllabic word stimulus to the participants (30 neurotypical individuals; the age range of 19–65 years) bilaterally. The investigator asked the participant to repeat those words, whatever they heard through the headphones, and those responses were transcribed and analysed by the primary investigator. Out of a total of 119 words, 45 were eliminated from the list because they were (neurotypical individuals) produced incorrectly. The final word list contains 74 trisyllabic words. Conclusion The language-free stimuli can be used for the speech intelligibility assessment of native Dravidian language speakers with dysarthria, neurological conditions like Parkinson’s disease, bulbar palsy, post-glossectomy patients, etc. Future studies can focus on the clinical validation of the stimuli among disorder populations such as dysarthria.

Land-clearing and soil-amendment strategies play a crucial role in determining agricultural productivity, sustainability, and environmental resilience. This study appraised the preferences of aspiring agriculturists for ten land-clearing and soil-amendment technologies using a preference ranking system and two-way analysis of variance (ANOVA). Data were collected from final-year agronomy students at Southern Delta University, Ozoro, who had completed the Farm Practical Year Programme (FYP). Statistical analyses were performed using the Statistical Analysis System (SAS Institute, 2002). Results indicated a strong preference for organic-based amendments (e.g., cattle dung, sugarcane peelings) and conservation-oriented land-clearing techniques (e.g., slash-and-mulch), whereas conventional practices such as ploughing and slash-and-burn were least preferred. The opinions of aspiring agriculturists are particularly critical because university exposure shapes their technical competence, environmental awareness, and innovative capacity. As the next generation of farm managers, extension agents, and policy influencers, their preferences can serve as predictors of future technology adoption trends and sustainability-oriented practices. Ethical approval for this study was obtained from the Institutional Review Board of Southern Delta University, Ozoro. The study was limited by its small sample size and single-institution scope, which may affect the generalizability of the findings. Future research should include larger, multi-institutional samples and comparative analyses across regions, genders, and socio-economic backgrounds to provide broader insights into the determinants of technology preference and adoption among emerging agricultural professionals.

Abstract. The European Food Safety Authority (EFSA) has been conducting horizon scanning (HS) activity in the field of plant health, in collaboration with the EC Joint Research Centre (JRC) and the French Agency for Food, Environmental and Occupational Health and Safety (ANSES), since 2017. As of 2024, this activity has produced 130 reports, named newsletters. The aim of this activity is to capture signals from the web about potential threats caused by plant pests from all around the world and to convey them to European Union risk managers in support of their preparedness and timely reactions. The tool used was the Medical Information System (MedISys), a public health surveillance system that continuously monitors the content of more than 3200 scientific and media sources worldwide. The items selected for inclusion in the monthly newsletters are reviewed and validated by a team of experts, while another team carries out further analysis on specific “not-listed” pests. This analysis, PeMoScoring (short for pest and monitoring scoring), is a fast procedure based on a ranking system that warns risk managers of the potential new threats by unknown or not-listed pests. These signals can then trigger actions by risk managers: requests for more assessments by EFSA or facilitation of preventive measures. Recently, a series of workshops and webinars have been organised to foster collaboration among institutions engaged in horizon scanning activities in the field of plant health and to broaden the applicability of this service to other contexts and areas of focus. This article presents an analysis of the data collected from the newsletters, along with a detailed examination of the PeMoScoring outcomes and potential directions for future development. The results highlight the potential of horizon scanning tools in the prevention of emerging threats for plant health and their capacity to support risk management decisions by anticipating challenges and facilitating timely interventions.

In an era dominated by information overload, effective recommender systems are essential for managing the deluge of data across digital platforms. Multi-stage cascade ranking systems are widely used in the industry, with retrieval and ranking being two typical stages. Retrieval methods sift through vast candidates to filter out irrelevant items, while ranking methods prioritize these candidates to present the most relevant items to users. Unlike studies focusing on the ranking stage, this survey explores the critical yet often overlooked retrieval stage of recommender systems. To achieve precise and efficient personalized retrieval, we summarize existing work in three key areas: improving similarity computation between user and item, enhancing indexing mechanisms for efficient retrieval, and optimizing training methods of retrieval. We also provide a comprehensive set of benchmarking experiments on three public datasets. Furthermore, we highlight current industrial applications through a case study on retrieval practices at a specific company, covering the entire retrieval process and online serving, along with practical implications and challenges. By detailing the retrieval stage, which is fundamental for effective recommendation, this survey aims to bridge the existing knowledge gap and serve as a cornerstone for researchers interested in optimizing this critical component of cascade recommender systems.

Critical biological systems linking early-life stress to later-life outcomes: A systematic review of animal models.

Purpose This study aims to investigate how the classical academic resources of universities contribute to their innovation and entrepreneurship performance. Academic inputs such as the total number of academic publishing, citation scores, scientific documents, number of PhD studies and faculty-to-student ratios are used for this analysis. The criteria used for innovation and entrepreneurship rating are competence in scientific and technological research, intellectual property pool, cooperation and interaction and economic contribution and commercialization. Design/methodology/approach Two ranking systems for Turkish universities are used in this study. Academic performance (URAP) is used as input, and entrepreneurial performance (TUBITAK) is the output. A sample of 48 Turkish universities (32 public universities and 16 private universities) is evaluated via data envelopment analysis (DEA). Findings The results of the DEA show that 23% of the selected universities are fully efficient, while 62% are partially efficient – of which 81.7% are public universities and 44% are private universities. Furthermore, the study’s slack analysis of outputs indicates that although the academic performance of the selected universities is relatively high, these universities have difficulty converting the outcomes of their academic studies into real-life socioeconomic applications. Originality/value The goal of higher education institutions has traditionally been purely academic, focusing on teaching and scientific research. However, contemporary universities are expected to consistently focus on innovation and entrepreneurship in addition to their traditional roles of teaching and research. This study examines the relationship between classical academic resources and the contemporary entrepreneurial aspect of the universities in a sample of 48 Turkish universities. Two well-established university ranking systems are used to evaluate performance and efficiency, constituting a novel contribution to the academic entrepreneurship field.

This study investigated the impact of early success in cadet and junior World Championships on career longevity among elite judo athletes, focusing on the critical transition from junior to senior levels. Using survival analysis, we examined dropout rates and career durations for medalists and non-medalists, defining career termination as a period of at least two consecutive years without international competition. The results from the Cox regression showed that medalists exhibited significantly lower risks of career termination in certain years (e.g., 2011, 2013, 2014, 2015, and 2016), with reductions ranging from 43% to 75%. However, this protective effect was inconsistent, with no significant differences observed in other years. Factors such as injuries, performance stagnation, and structural changes in the International Judo Federation's ranking system likely contributed to these variations, particularly during years of significant policy shifts. Our findings highlight the importance of early success in extending career duration while emphasizing that it is not a guaranteed predictor of long-term success. These insights indicate the need for tailored athlete development programs that address physical, psychological, and social dimensions, as well as further research to understand the mechanisms supporting career longevity and inform policies aimed at sustaining elite judo athletes.

Context This study focuses on the Lalehzar and Hezar Mountains within the Yazd-Kerman Endemism Hotspot in Iran, part of the Irano-Turanian region, which includes five of the world’s 34 endemism hotspots. Aims The study aims to assess the conservation status and categorize endemic and rare plants in the area by using modified IUCN 2019 criteria. Methods Over 3 years (2017–2019), we conducted an extensive study of the floristic composition and plant diversity. We developed a localized ranking system (L-Rank) based on IUCN Criterion B (area of occupancy, AOO) for small-scale habitats (<2000 km2). By using 1 × 1 km grid cells and field surveys, we mapped species distributions. GIS analysis and statistical validation were employed to quantify AOO, including subcriteria such as the number of locations and extent of decline, and the L-Rank system classified species by their distribution range. The criteria were aligned with the corresponding IUCN 2019 categories. Key results In total, 306 plant species were identified, covering 195 genera and 49 families. Of these, 64 species were classified as threatened, including 15 Critically Endangered (CR), 16 Endangered (EN), and 33 Vulnerable (VU). Conclusions Findings highlighted the urgent conservation needs of species with restricted ranges (e.g. L1-ranked taxa) facing elevated extinction risks because of habitat fragmentation and climate change. Implications This approach connects global (IUCN) and local conservation frameworks, providing actionable insights for botanists, land managers, and policymakers to prioritize protection efforts in vulnerable ecosystems.

This study proposes a new method to assess researcher expertise using publication data. The quality of research publications is an important indicator in the ranking of universities that are undergoing diversification. Research publications have become an important indicator in the university ranking system and have a major impact on the reputation of universities as a lens for the study of expertise and prestige for human resources. Expertise is often difficult to verify objectively, as a result, many people claim to be experts or are considered experts without evidence and correct data. To ensure the expertise of researchers, it must be proven with valid data support through measurable and presentable expertise parameters. The model built uses the cosine similarity and association rule approaches. The publication variables attached to the researcher are formulated in the collaboration of the algorithm to assess the level of researcher expertise. Validation of important points of publications as parameters for measuring expertise has been identified as the main factor contributing to the measurement of researcher expertise and its impact on university reputation. The model built successfully validated researcher expertise up to 72% which is relevant to its support for university rankings up to 75%.

A comprehensive framework of health risk assessment for antibiotic resistance in aquatic environments: Status, progress, and perspectives.

This study presents a GIS-based decision support system (DSS) for prioritizing forest road network maintenance to enhance wildfire prevention and suppression in Mediterranean forest regions. The research focuses on low-volume roads (LVRs), which play a critical role in fire response operations but often suffer from limited maintenance resources and accessibility constraints. Using GIS-based network analysis, the study integrates road hierarchization, wildfire risk modeling, and optimal route determination to develop a structured approach for forest road maintenance prioritization. The methodology involves segmenting and evaluating road networks based on travel time, slope, and fire risk exposure, enabling a data-driven ranking system that identifies critical access routes for emergency response. The study applies the Closest Facility method to determine optimal routes from firefighting vehicle stations to various locations within the network. Results indicate that a targeted maintenance strategy, prioritizing high-risk road sections, significantly improves fire response efficiency while optimizing resource allocation in financially constrained forest management frameworks. This approach introduces a sustainable and cost-effective framework for forest road infrastructure planning, offering a practical tool for decision-makers in fire-prone regions. By ensuring proactive maintenance scheduling, the proposed method enhances wildfire resilience, reduces emergency response delays, and supports long-term forest sustainability.

Elections in the twenty-first century are not only fought in parliaments, or television studios; they unfold across digital platforms shaped by invisible algorithms. Every scroll, click, and swipe is guided by ranking and recommendation systems that determine what information citizens see, what advertisements reach them, and how political messages spread. While some portray algorithms as all-powerful tools capable of swinging entire elections, a closer look suggests a more complicated picture. Algorithms are better understood as amplifiers: they structure visibility, accelerate certain narratives, and suppress others, but their effects depend heavily on context, user behaviour, and broader social dynamics.This paper critically reviews the role of algorithms in shaping electoral outcomes, drawing on research from computer science, political communication, and political economy. It examines three main pathways: (1) how algorithms filter and rank information, (2) how they enable personalization and political microtargeting, and (3) how they facilitate or hinder the spread of misinformation. In addition, the paper introduces three theoretical perspectives—computational propaganda, media ecology, and the political economy of communication—to frame how algorithms interact with politics at structural, cultural, and systemic levels.The evidence shows that algorithms do matter, and their effects are uneven. Most studies suggest modest average impacts on individual opinions, though targeted campaigns and sustained exposure may have larger, cumulative consequences. Blind spots remain: short-term experiments cannot capture long-term influence, researchers rarely have access to raw platform data, and vulnerable subgroups remain underexplored.The conclusion argues that algorithms do not decide elections alone, but they have become inseparable

This study introduces a circularity ranking system at the meso-level, specifically targeting industrial parks, through the development of the Circular Economy Sustainability Index (CESI). The index comprises five economic-environmental indicators: energy intensity, emission intensity, water intensity, waste intensity, and recycling ratio, as well as a social indicator as a sixth dimension. We utilize CESI to evaluate the circular economy performance of 22 manufacturing firms in the Adana Hacı Sabancı Organized Industrial Zone (AOSB). AOSB, one of the most prominent industrial parks in Türkiye, serves as an excellent case study to assess companies' circularity performance and identify areas for improvement in the country's green industrial transformation endeavor. Our findings reveal that waste and recycling indicators are pivotal in determining circularity, contributing 34.6% to the overall score, while the social indicator adds another 16.3%. These results underscore the significance of effective waste management and social responsibility in enhancing circularity.

Semiconductor photocatalysis has gained recognition for its sustainability and has seen considerable advancements in recent decades. Despite this progress, the critical role of solvents in influencing photocatalytic performance remains underexplored, particularly in the context of safe and sustainable solvent systems. This perspective advocates for a systematic shift toward the use of safe and sustainable solvents and proposes a rational workflow for their selection, moving beyond conventional trial-and-error methods. Key challenges in adopting this approach are discussed, along with future directions that call for coordinated efforts across academia and industry. Central to this vision are the development of a comprehensive solvent database, predictive models for solvent effects, and a standardized safety and sustainability ranking system that integrates both green chemistry metrics and life cycle assessments.

Urolithin A-laden functional nanoparticles alleviate cisplatin-induced cardiotoxicity in mice by inhibiting inflammation-induced lymphangiogenesis.