Ranking Research Articles

The Commemorability Principle in Akan Personal Name Construction

The movement from regular lexicon to onomasticon, especially anthroponomasticon, is often mediated by cultural principles which may determine which concepts could normally be selected for the formation of personal names. Restrictive traditions have guiding principles making some concepts acceptable or not, and some names central or peripheral. In this paper, I discuss the principle of commemorability as gatekeeping the selection of concepts for the formation of personal names in Akan; and, having established the restrictiveness of the Akan anthroponomastic system, I identify the two considerations of honourability and preservability as making up the commemorability principle. The study is inductive, establishing the theory that explains the principles for the selection of appropriate concepts for the construction of personal names, and it relies on ethnographic resources including observation, interviews, and focus group discussions supported by name content analysis to generate the theory. The paper establishes that commemorability is founded on a general philosophy that upholds the societal, effort and perseverance, and social cognitive value in the selection of concepts for constructing personal names. Guided by these considerations, concepts are placed within a value ranking system to determine their ‘commemorability’, with items that rank as ‘honourable’ normally selected and processed as personal names. In the construction itself, there is a preference for the cognitive over the physical and the general beyond the specific, and there is an overriding preference for the use of general commemorability concepts which represent excellence, prominence, fullness, abundance, inexhaustibility, strength, endurance, and resilience, among others, which are used both as base-concepts for family names or as ‘amplifier’ concepts in the construction of extension names.

Ensemble feature ranking approach for software fault prediction

Software fault prediction, which aims to find and fix probable flaws before they appear in real-world settings, is an essential component of software quality assurance. This article provides a thorough analysis of the use of feature ranking algorithms for successful software failure prediction. In order to choose and prioritise the software metrics or qualities most important to fault prediction models, feature ranking approaches are essential. The proposed focus on applying an ensemble feature ranking algorithm to a specific software fault dataset, addressing the challenge posed by the dataset’s high dimensionality. In this extensive study, we examined the effectiveness of multiple machine learning classifiers on six different software projects: jedit, ivy, prop, xerces, tomcat, and poi, utilising feature selection strategies. In order to evaluate classifier performance under two scenarios—one with the top 10 features and another with the top 15 features—our study sought to determine the most relevant features for each project. SVM consistently performed well across the six datasets, achieving noteworthy results like 98.74% accuracy on “jedit” (top 10 features) and 91.88% on “tomcat” (top 10 features). Random Forest achieving 89.20% accuracy on the top 15 features, on “ivy.” In contrast, NB repeatedly recording the lowest accuracy rates, such as 51.58% on “poi” and 50.45% on “xerces” (the top 15 features). These findings highlight SVM and RF as the top performers, whereas NB was consistently the least successful classifier. The findings suggest that the choice of feature ranking algorithm has a substantial impact on the fault prediction models’ predictive accuracy and effectiveness. When using various ranking systems, the research also analyses the trade-offs between computing complexity and forecast accuracy.

Spatiotemporal dynamics of forest fires in the context of climate change: a review.

Forest fires are sudden, destructive, hazardous, and challenging to manage and rescue, earning them a place on UNESCO's list of the world's eight major natural disasters. Currently, amid global warming, all countries worldwide have entered a period of high forest fire incidence. Due to global warming, the frequency of forest fires has accelerated, the likelihood of large fires has increased, and the spatial and temporal dynamics of forest fires have shown different trends. Therefore, the impact of climate change on the spatiotemporal dynamics of forest fires has become a hot issue in the field of forest fire research in recent years. Therefore, it is of great significance and necessity to conduct a review of the research in this area. This review delves into the interactions and impacts between climate change and the spatiotemporal dynamics of forest fires. To address this issue, scholars have mainly adopted the following research methods: first, statistical analysis methods, second, the establishment of spatiotemporal prediction models for meteorology and forest fires, and third, the coupling of climate models with forest fire risk forecasting models. The statistical analysis method relies on the analysis of historical meteorological and fire-related data to study the effects of climate change and meteorological factors on fire occurrence. Meanwhile, forest fire prediction models utilize technical tools such as remote sensing. These models synthesize historical meteorological and fire-related data, incorporating key meteorological factors such as temperature, rainfall, relative humidity, and wind. The models revealed the spatial and temporal distribution patterns of fires, identified key drivers, and explored the interactions between climate change and forest fire dynamics, culminating in the construction of predictive models. With the deepening of the study, the coupling of climate models and fire risk ranking systems became a trend in the prediction of forest fire risk trends. Moreover, as the climate warms, the increased frequency of extreme weather events like heatwaves, droughts, snow and ice storms, and El Niño-Southern Oscillation (ENSO) has accelerated forest fire occurrences and raised the risk of major fires. This review offers valuable technical insights by comprehensively analyzing the spatial and temporal characteristics of forest fires, elucidating key meteorological drivers, and exploring potential mechanisms. These insights serve as a scientific foundation for preventive measures and effective forest fire management. In the face of a changing climate, this synthesis contributes to the development of informed strategies to mitigate the escalating threat of forest fires.

Government-to-government peer pressure and air pollution: Causal evidence from an environmental ranking policy in China

This paper estimates the impact of peer governmental pressure on air quality using a regression discontinuity design inherent in China's air quality ranking system. Because air quality rankings are important for political evaluations, local officials who witnessed a decline in air quality ranking are motivated to enforce more stringent environmental standards compared to their counterparts with increased rankings. By exploiting this regulatory discontinuity with monthly air quality ranking data from 2012 to 2020 of 169 cities, we find that cities experiencing a lower air quality ranking in the current month compared to the previous month exhibit a subsequent improvement in air quality during the following month, as evidenced by decreased pollutant concentrations. Furthermore, our analysis reveals that in cities where pollutant rankings decline more sharply, officials are less likely to encounter fewer promotion opportunities. Importantly, we observe that the discontinuity in individual pollutant concentrations is not solely influenced by their respective rankings but is also impacted by the overall Air Quality Index (AQI) ranking. Linking the reduction in air pollutants concentration with the economic benefits, a back-of-the-envelope calculation indicates the decrease in premature deaths due to cardiovascular and respiratory diseases amounts to approximately 200 thousand, resulting in an associated economic saving of more than 600 billion Chinese yuan.

Webometrics ranking of Universities: fallacy or reality

In recent years, the utilization of webometrics as a tool for ranking universities has gained significant traction, purportedly offering a comprehensive assessment of institutions' digital presence and impact. However, amidst its growing popularity, questions arise regarding the validity and applicability of webometrics rankings, particularly concerning universities situated in the global south. This paper critically examines the webometrics ranking system, aiming to discern its strengths and weaknesses while scrutinizing its efficacy in evaluating universities, particularly those in regions with diverse socio-economic contexts and digital infrastructures. The analysis begins by delineating the fundamental principles underlying webometrics rankings, highlighting its reliance on web-based indicators such as web presence, visibility, and transparency. While these metrics ostensibly offer insights into universities' global reach and influence, they also engender methodological complexities and biases. Notably, the dominance of older well-endowed institutions in comparison with younger resource-constrained institutions impeding equitable evaluation. Furthermore, the paper investigates the specific challenges faced by universities in the global south within the webometrics framework. Issues of digital divide, limited internet penetration, and disparities in web accessibility compound the difficulties faced by these institutions in attaining favorable rankings. Moreover, the emphasis on quantitative metrics overlooks qualitative aspects of academic excellence, neglecting factors such as research impact, teaching quality, and societal relevance, which are integral to universities' roles in diverse contexts.Through a critical lens, this paper underscores the fallacies inherent in the uncritical adoption of webometrics rankings as a singular measure of university performance. It advocates for a nuanced approach that acknowledges the contextual nuances and challenges faced by universities, particularly in the global south. By fostering a dialogue on the limitations of webometrics and exploring alternative evaluation methodologies, this research aims to contribute to a more inclusive and equitable framework for assessing higher education institutions in an increasingly digitized world.

Prioritization of organic contaminants in China's groundwater based on national-scale monitoring data and their persistence, bioaccumulation, and toxicity

There has been increasing concern regarding the adverse environmental and health effects of organic pollutants. A list of priority control organic pollutants (PCOPs) can provide regulatory frameworks for the use and monitoring of organic compounds in the environment. In this study, 20,010 groundwater samples were collected from 15 “first level” groundwater resource zones in China. Fifty (50) organic compounds were analyzed based on their prevalence, occurrence, and physicochemical properties (persistence, bioaccumulation, and toxicity). Results showed that 16 PCOPs, including 12 pesticides, 3 aromatic hydrocarbons (AHs), and 1 phthalate ester, were recognized. Pesticides and AHs accounted for 75 % and 18.75 % of the high-priority pollutants, respectively. There were significant differences in PCOPs between confined and phreatic groundwater. Higher concentrations of pesticides were mainly detected in phreatic groundwater. PCOPs detected in samples from the 15 groundwater resource zones were mainly pesticides and AHs. The groundwater data indicate that the organic compounds detected in the Yellow River Basin (YRB), Yangtze River Basin (YZB), Liaohe River Basin (LRB), and Songhua River Basin (SRB) are mainly categorized as Q1 (high priority) and Q2 (medium priority) pollutants based on the contaminants ranking system in China. The findings from this study offer a snapshot of the wide distribution of PCOPs in the surveyed regions, and are expected to establishing treatment and prevention measures at both the regional and national levels in China.

An integrated multiple-criteria decision-making and data envelopment analysis framework for efficiency assessment in sustainable healthcare systems

Efficiency is critical in allocating sustainable healthcare resources to ensure that hospitals can effectively care for patients while maintaining high-quality care delivery. Hence, it is necessary to monitor efficiency carefully. This study aims to assess hospital unit effectiveness through a novel comprehensive approach integrating Multiple-Criteria Decision Making (MCDM) with Data Envelopment Analysis (DEA). The proposed MCDM-DEA framework involves allocating varying weights to distinct data categories. It harnesses the capabilities of the q-rung orthopair fuzzy (q-ROF) methodology to address the inherent uncertainties in healthcare performance assessment. The experimental results provide a comprehensively structured ranking system for specific hospital departments. This ranking system allows decision-makers to identify the strengths and weaknesses of each department, enabling them to make informed decisions regarding resource allocation and improvement strategies. Furthermore, the integration of MCDM-DEA provides a robust and objective assessment tool for monitoring and evaluating the performance of hospital departments over time. These rankings offer invaluable insights to decision-makers, equipping them with the strategic information needed to enhance the overall performance of hospital units.

Identifying spatio-temporal pattern of electric vehicles involved traffic accidents

The increasing popularity of electric vehicles (EVs) has given rise to concerns regarding emerging safety challenges. To address this, an enhanced spatio-temporal kernel density estimation (STKDE) method is developed, which leverages GIS technologies to analyze the temporal evolution of EV accidents across different locations. Our approach introduces several innovations: (1) The incorporation of network distance to address overestimation associated with the conventional Euclidean distance; (2) Integration of a Severity Index (SI) to rationalize accident weighting; (3) Utilization of a likelihood cross-validation method to determine optimal bandwidths for simplified computation. Additionally, statistical significance tests and a ranking system based on cluster strength are implemented to enhance the accuracy and stability of hotspot identification compared to the traditional kernel density estimation (KDE) method. Empirical analyses reveal spatial trends, indicating a higher likelihood of EV accidents occurring near city administrative centers and along arterial roads. Temporally, our findings show increased daytime hotspot density with distinct morning and evening peaks compared to nighttime. Furthermore, a total of 209 hazardous locations, containing 907 accidents, representing 23.4% of all accidents are filtered. Our improved STKDE approach demonstrates a mean hit rate of 0.553 and a PAI of 5.573, which are 3.5% and 27.5% higher, respectively, than those achieved with SKDEKDE. These insights can assist transportation agencies in implementing targeted interventions and resource allocation strategies.

University rankings: Time to reconsider

University rankings offer some benefits but also come with significant drawbacks. While they can encourage healthy competition, they often lead to unethical practices and prioritize short- term gains over long-term educational purposes. Relying on biased metrics like citations and journal impact factors is a major flaw, potentially misrepresenting the true value of scholarly work. The foremost focus of universities should be on educating proficient students, advancing dependable knowledge, and addressing societal needs. Annual rankings based on one year's criteria and output prove impractical, as research outcomes and educational impact require more time to materialize. It is crucial to consider abandoning or reevaluating ranking systems to prevent biased, financially-driven approaches from causing harm. An internal assessment, gauging satisfaction levels within the university community and the quality of education provided, could offer a more effective approach to ranking universities. Acknowledging the negative impact of journal rankings took decades. It is imperative to avoid subjecting educational systems to similarly detrimental effects from university rankings. The most effective method for ranking universities is through an internal system that takes into account the satisfaction levels of university community members regarding their work conditions and overall institution, as well as whether students are acquiring the education and skills they seek.

Assessment of Sustainable Aviation Fuel Production Methods: A Promethee II Approach

Sustainable aviation fuels (SAF) present a feasible solution to decarbonize modern aviation. Unlike traditional jet fuels, SAFs are produced in a variety of ways, thereby choosing one of these processes as a complicated Multi-Criteria Decision challenge that involves conflicting priorities. This study evaluates SAF production processes using a multicriteria methodology, PROMETHEE-2. With SAF technology in its nascent stage and limited data, several stakeholders in the aviation sector were enlisted to assist in the collection of data and preferences. The suggested framework’s strength lies in its adaptability to suit the subjective opinions of diverse stakeholders, selection of ranking system, and robustness of outcomes. This research engaged stakeholders in a participative manner to rank 11 (A1 to A11) SAF production paths based on 24 parameters categorized into social, environmental, economic, and technological evaluation criteria. Industry professionals were given a form to rate SAF production methods according to a performance criterion. Data is validated using fuzzy TOPSIS and fuzzy VIKOR and PROMETHEE-II to reduce professionals’ judgmental personal prejudice. Results indicate the optimal feedstock for SAF production is the direct transition process of CO2 to SAF (A11) in the gasification or Fischer-T synthesis group.

Integrated Selection of Permanent Teacher Appointments Recommended MCDM-AHP and WASPAS Methods

The teacher's role is very important in improving the national learning system. Many honorary teachers are empowered in curriculum development in a number of schools who want to collaborate in improving the quality of their students. The purpose of this research is to provide rewards to honorary teachers who have long served for the progress of the nation in the world of education to be appointed as permanent teachers. The selection method was carried out through a criteria weighting technique with the MCDM-AHP method which was integrated with the WASPAS method. The technique of developing the MCDM-AHP method as an eigenvector measurement concept with proof of optimization through mathematical algebra matrices that is correlated with the Expert Choice application to get optimal values. The result optimization value is integrated with the WASPAS method as a determinant of the ranking system for permanent teacher candidates. This method is a unification of the concepts of the weight product model and weight sum model methods, so that it has special stages to support decision making with the WASPAS method. The results of selecting twelve honorary teachers for appointment as permanent teachers can be seen from the acquisition of the Qi optimization value as a ranking. The results of support for decision making for permanent teacher appointments with the highest optimization value were given to TC04 with a weight of 0.878; followed by a significant difference in the next rank. The findings of this study provide evidence that the integration of the MCDM-AHP and WASPAS methods provides continuous optimization results for decision-making support.

Transcriptomics- and Genomics-Guided Drug Repurposing for the Treatment of Vesicular Hand Eczema.

Vesicular hand eczema (VHE), a clinical subtype of hand eczema (HE), showed limited responsiveness to alitretinoin, the only approved systemic treatment for severe chronic HE. This emphasizes the need for alternative treatment approaches. Therefore, our study aimed to identify drug repurposing opportunities for VHE using transcriptomics and genomics data. We constructed a gene network by combining 52 differentially expressed genes (DEGs) from a VHE transcriptomics study with 3 quantitative trait locus (QTL) genes associated with HE. Through network analysis, clustering, and functional enrichment analyses, we investigated the underlying biological mechanisms of this network. Next, we leveraged drug-gene interactions and retrieved pharmaco-transcriptomics data from the DrugBank database to identify drug repurposing opportunities for (V)HE. We developed a drug ranking system, primarily based on efficacy, safety, and practical and pricing factors, to select the most promising drug repurposing candidates. Our results revealed that the (V)HE network comprised 78 genes that yielded several biological pathways underlying the disease. The drug-gene interaction search together with pharmaco-transcriptomics lookups revealed 123 unique drug repurposing opportunities. Based on our drug ranking system, our study identified the most promising drug repurposing opportunities (e.g., vitamin D analogues, retinoids, and immunomodulating drugs) that might be effective in treating (V)HE.

Customer Satisfaction Towards Maruti Suzuki Car in Gorakhpur City

The vehicle industry in India rose to become the fourth biggest globally. Maruti Suzuki is one of the few automakers with extensive knowledge of the Indian market. As of December 2023, it has a 36.50 percent market share, making it the biggest automotive maker. Customer decision-making is a complicated process. Choosing the goods or services to purchase requires a number of steps. The researcher has tried to find out which Maruti Suzuki vehicle brand the customers prefer and to examine consumer satisfaction in study area. This research covers the ways for raising consumer awareness of Maruti Suzuki vehicles, the variables affecting consumers' purchasing decisions, and the degree of customer satisfaction with these vehicles. By computing the weighted average score for each influential aspect, the ranking system based on positive responses is used to assess the degree of consumer satisfaction with Maruti Suzuki cars. The customers express dissatisfaction with the air cooler facility, interior decorating, and after-sale support. Positively, the majority of buyers express great satisfaction with the engine performance, driving comfort, style/color, and safety. Key words: Maruti Suzuki Car, Customer Satisfaction, Factors Affecting, After Sales Service.

Prospects for solving problems of organizational management in the instrumental selection and ranking system "SVIR"

Prospects for solving problems of organizational management in the instrumental selection and ranking system "SVIR"

A framework for evaluation of construction and demolition waste management alternatives using MCDA techniques in the context of Dhaka City

Landfilling and dumping are the common strategies to manage generated construction and demolition waste (C&DW) in Dhaka City. These strategies of C&DW management (C&DWM) affect the environment adversely and fill the old landfill sites quickly. Besides, there isn’t any framework to manage C&DWs effectively. This study introduces a Multi-criteria Decision Analysis (MCDA)-based C&DWM framework for Dhaka City by incorporating the expanded Waste Management Hierarchy (E-WMH). The E-WMH principles are considered as the C&DWM alternatives. Through a comprehensive literature review, the criteria are determined and grouped into social, economic, environmental, and technical criteria to achieve sustainability and effectiveness. To construct the initial decision matrix, the ordinal data (i.e. rating) is collected through interviews with the subject-matter experts of Dhaka City. Also, the ranking system method is used to determine the weight of the criteria. Finally, the ELECTRE I and ELECTRE II MCDA methods are employed to rank the alternatives. Results show that reuse and recovery are suitable strategies for managing C&DWs in Dhaka city. Future studies may consider the hybridization of MCDA tools, quantitative data to form the initial decision matrix, and other mathematical models to weigh the criteria so that the performance of the framework can be enhanced.

Holistic comparison of environmental barrier coating material candidates through design of a figure of merit

AbstractThe first figure of merit for environmental barrier coating (EBC) materials was designed through a ranking system for material properties pertaining to established EBC failure modes in service. Seven past, present, and novel EBC candidate materials were used in the figure of merit design: SiO2, Ba0.75Sr0.25Al2Si2O8 (BSAS), HfSiO4, Yb2Si2O7, Yb2SiO5, Yb2O3, and YbPO4. Utilizing compiled data from the literature, the presented figure of merit verified Yb2Si2O7 as the state‐of‐the‐art candidate with optimal EBC properties and inferred that YbPO4 should be considered as a potentially viable EBC material candidate. The figure of merit allows for a holistic comparison of EBC candidates and informs experimental and computational search efforts for next‐generation complex EBCs. Clear knowledge gaps found through this work include CaO–MgO–Al2O3–SiO2 (CMAS)‐resistant coatings, EBC lifetimes before delamination, and oxidant diffusion rates in relevant EBC microstructures. It was shown that while some materials show promise for solving a single key failure mode for EBCs (i.e., CMAS reactivity), a community‐wide goal should be placed on materials development to achieve acceptable resistance against all major failure modes, which are interconnected. Novel compositionally complex EBC materials, in addition to layered EBC architectures, show promise for the optimization of material properties for long‐lifetime EBCs in combustion environments.

Performability Evaluation of Autonomous Underwater Vehicles Using Phased Fault Tree Analysis

This paper presents a phased fault tree analysis (phased-FTA)-based approach to evaluate the performability of Autonomous Underwater Vehicles (AUVs) in real time. AUVs carry out a wide range of missions, including surveying the marine environment, searching for specific targets, and topographic mapping. For evaluating the performability of an AUV, it is necessary to focus on the mission-dependent components and/or subsystems, because each mission exploits different combinations of devices and equipment. In this paper, we define a performability index that quantifies the ability of an AUV to perform the desired mission. The novelty of this work is that the performability of the AUV is evaluated based on the reliability and performance of the relevant resources for each mission. In this work, the component weight, expressing the degree of relevance to the mission, is determined using a ranking system. The proposed ranking system assesses the performance of the components required for each mission. The proposed method is demonstrated under various mission scenarios with different sets of faults and performance degradations.

Exploration of a Potential DOOR Endpoint for Hospital-acquired Bacterial Pneumonia and Ventilator-associated Bacterial Pneumonia Using Six Registrational Trials for Antibacterial Drugs.

Desirability of outcome ranking (DOOR) is an innovative approach to clinical trial design and analysis that uses an ordinal ranking system to incorporate the overall risks and benefits of a therapeutic intervention into a single measurement. Here we derived and evaluated a disease-specific DOOR endpoint for registrational trials for hospital-acquired bacterial pneumonia and ventilator-associated bacterial pneumonia (HABP/VABP). Through comprehensive examination of data from nearly 4000 participants enrolled in six registrational trials for HABP/VABP submitted to the Food and Drug Administration (FDA) between 2005 and 2022, we derived and applied a HABP/VABP specific endpoint. We estimated the probability that a participant assigned to the study treatment arm would have a more favorable overall DOOR or component outcome than a participant assigned to comparator. DOOR distributions between treatment arms were similar in all trials. DOOR probability estimates ranged from 48.3% to 52.9% and were not statistically different. There were no significant differences between treatment arms in the component analyses. Although infectious complications and serious adverse events occurred more frequently in ventilated participants compared to non-ventilated participants, the types of events were similar. Through a data-driven approach, we constructed and applied a potential DOOR endpoint for HABP/VABP trials. The inclusion of syndrome-specific events may help to better delineate and evaluate participant experiences and outcomes in future HABP/VABP trials and could help inform data collection and trial design.

Education Policy of 3rd Generation Universities

Background: One of the tasks of the education policy of any state is the spread of its influence in the international arena. Today, universities are striving to take and strengthen their positions in the world ranking systems, demonstrating the status and reputation of universities in the global market of educational services. This ranking serves as a guideline for future students and their parents when choosing a place to receive a prestigious education and in the formation of individual trajectories of vocational training. Approach: There are several approaches in the world to determining the criteria for assessing a state's education policy. But despite the differences, they all document the growing role of modern universities in the development of society. In many respects, it is important both in terms of guaranteeing the sustainability of society and in terms of ensuring a breakthrough direction in its development. In contrast to recent times, this role has grown significantly. Due to the fairly conservative and limited social system in its function, such universities become a central link in the development of innovative economies and social spheres - the science that produces the socio-economic development of a particular region, Education, innovation centers, national or as well as global processes. Results: It covers all areas of the university, from cooperation with students to financial and scientific activities. A prime example of such an association is the International Strategy Advisory Service (ISAS 2.0) of the International Association of Universities or Universities (IAU). Conclusions: Around the world, states are trying to stimulate and support these processes. In many countries, this is facilitated by opposition from high-tech companies to the reduction of the final amount of independent basic and applied research, in favor of collaborating with universities on basic research projects. As part of its innovative activities, University 3.0 is involved in supporting business activities, analysis and consultation by experts from local governments and local authorities, opening facilities, and infrastructure for citizens, monitoring regional development, services to citizens are provided for lifelong learning and support student entrepreneurship projects that take into account the interests of the community.

Hazard Analysis and Vulnerability Assessment of Cultural Landscapes Exposed to Climate Change-Related Extreme Events: A Case Study of Wachau (Austria)

The present paper aims to study the Wachau Valley in Austria as a representative Cultural Landscape under threat from extreme hydrometeorological hazards linked to climate change. The primary objective is to investigate the impacts and assess the vulnerability associated with the events of heavy rain and flooding. The methodology employed consists of an investigation of recorded past events impacting the Wachau; a vulnerability ranking system; a climate time series analysis based on earth observation products; and future hazard maps at territorial level, developed with outputs from regional and global climate models. The investigation we carried out provides a vulnerability assessment of two terraced areas with a surface of about 10,000 m2 in total, characterized by the presence of dry stone walls, with different state of conservation in the Municipality of Krems (Wachau). In addition, climate projections at territorial level for the extreme climate indices R20mm, R95pTOT, and R×5day—selected for investigating the likelihood of increases/decreases in events of heavy rain and large basin flooding—are provided, with a spatial resolution of ~12 km for the near and far future (2021–2050; 2071–2100) under stabilizing (RCP 4.5) and pessimistic (RCP 8.5) scenarios. The results indicate a general increase for the three indices in the studied areas during the far future under the pessimistic scenario, suggesting a heightened risk of heavy rain and flooding. These findings aim to inform policymakers and decision-makers in their development of strategies for safeguarding cultural heritage. Furthermore, they serve to assist local stakeholders in enhancing their understanding of prioritizing interventions related to preparedness, emergency response, and recovery.