Analytical Framework Research Articles

Enhance domestic tourists’ revisit intention in spiritual destinations originating in patriotism and religious orientation

PurposeThis study investigates the impact of religious orientation and patriotism on domestic tourists’ intention to revisit spiritual destinations through two distinct studies: (1) religious sites and historical landmarks and (2) cultural heritage locations.Design/methodology/approachUsing convenience sampling, Study 1 (religious orientation) collected data from 445 Vietnamese tourists, and Study 2 (patriotism) collected data from 492 Vietnamese tourists. Spiritual elements were examined through social identity theory (SIT) and patriotism through the theory of reasoned action (TRA). The cognitive-affective-behavioral (CAB) model serves as the framework for both analyses. The hypotheses were tested using structural equation modeling.FindingsBoth patriotism and religious orientation had a positive indirect impact on domestic tourists’ intention to return. While attitudes toward development served as the sole mediator between patriotism and revisit intention, multiple factors mediated the relationship between religious orientation and revisit intention.Practical implicationsReligious marketing campaigns can enhance the destination image of churches and temples, thereby strengthening domestic tourists’ intention to revisit. Programs emphasizing patriotism should be organized to encourage the intention to revisit cultural and historical heritage sites.Originality/valueThis study on spirituality tourism conducted a comparative analysis of two case studies by focusing on the interplay between religious orientation and patriotism regarding revisiting intention by employing frameworks of the SIT, TRA and CAB models. It enriches the existing literature and theoretical foundations of spiritual tourism and provides valuable insights for local policymakers by highlighting the distinctions between the effects of religion and patriotism.

Domestic Violence Against Women in Nepal

Violence, as defined by the WHO, is a pervasive issue globally, with the intentional use of force leading to harm, injuries, or death. In Nepal, gender-based violence is significant, affecting domestic settings and leading to societal acceptance of violence against women. A systemic issue, violence is often underreported due to cultural norms and societal expectations. The prevalence of domestic violence underscores the need for a comprehensive framework to combat this issue, emphasizing the role of patriarchy in perpetuating violence against women. Statistics indicate high levels of violence against women, stemming from deep-rooted patriarchal beliefs that reinforce male dominance and women’s subordination. The research focuses on exploring domestic violence in the Madhesh region, delving into the physical manifestations of violence against women. A critical analysis of theoretical frameworks, particularly patriarchy, reveals how societal norms shape unequal gender relations and perpetuate violence, hindering women’s autonomy. By addressing patriarchal structures and promoting gender equality, efforts can be made to combat domestic violence and create a safer environment for all individuals.

Care and Community in Euro-Atlantic Diplomacy: A Discourse Analysis

Traditional International Relations (IR) theories emphasise power politics, often overlooking human-centric socio-political factors like care and community. In contrast, recent approaches in other social sciences have compensated by overemphasising empathy, neglecting the complex security concerns critical to navigating modern geopolitical environments. This creates both a contextual gap—where IR models inadequately address human factors—and a disciplinary gap between IR and emotion-driven frameworks in social sciences, which blunt the strategic clarity essential for effective diplomacy. This research explores leadership psychobiography and geopolitical pragmatism through a foreign policy analysis framework. The study examines the public diplomacy discourse of female Euro-Atlantic leaders during the Russia-Ukraine War. Their leadership—marked by rational compassion and democratic values—deviates from conventional models. The scope and unity of this female cohort, shaped by their shared temporal and geographic context, present a unique contribution and address an existing gap in the literature. These leaders, opposing Russia's aggression, integrate dignity, solidarity, and resilience into their public diplomacy, challenging traditional paradigms. By blending compassion with strategic calculation, they transcend political alignment and advocate for a perspective that recognizes both the human and community aspects of geopolitical conflicts. This study demonstrates the value of incorporating gendered leadership perspectives in diplomacy, where care and community complement traditional strategic considerations in complex geopolitical situations. It paves the way for further exploration of female-led diplomacy and a gendered understanding of foreign policy, advocating for leadership models that stress both strength and humanity. Keywords: Female Leadership, Foreign Policy, Diplomacy, Trait Analysis, Discourse Analysis

BioLake: an RNA expression analysis framework for prostate cancer biomarker powered by data lakehouse

BioLake: an RNA expression analysis framework for prostate cancer biomarker powered by data lakehouse

Manufacturing process analysis framework for process mining: case study of fully automated factory applications

Manufacturing process analysis framework for process mining: case study of fully automated factory applications

Multifractal Structures and the Energy-Economic Efficiency of Chinese Cities: Using a Classification-Based Multifractal Method

Improper urban spatial structure can lead to problems such as traffic congestion, long commuting times, and diseconomies of scale. Evaluating the efficiency of urban spatial structure is an important means to enhance the sustainable development of cities. The fractal method has been widely used in the identification and efficiency evaluation of urban spatial structure due to its sufficient characterization of urban complexity. However, the identification of urban fractal structures has expanded from monofractal structures to multifractal structures, while the efficiency evaluation of urban fractal structures remains limited to the single-dimensional efficiency evaluations of single fractals, seriously affecting the reliability of urban fractal structure evaluation. Therefore, this study identifies and evaluates urban spatial structure within the unified framework of multifractal analysis. Specifically, a classification-based multifractal method is introduced to identify the multifractal structure of 290 cities in China. An iterative application of the geographic detector method is used to evaluate the comprehensive energy-economic efficiency of urban multifractal structures. The results indicate that the 290 Chinese cities include 6 typical multifractal structures. The explanatory power of these six typical multifractal structures for urban energy-economic efficiency is 16.27%. The advantageous multifractal structures of cities that achieve higher energy-economic efficiency rates satisfy a cubic polynomial form. By comparing them with the advantageous multifractal structures, the main problems affecting the efficiency of urban multifractal structures in the other five types of cities are shown to include overly strong or weak concentration capacity of high-level centers, weak hierarchical structures among centers, and the spreading of low-level centers.

Assessing Vulnerability and Resilience to Climate-Induced Saltwater Intrusion of Smallholder Vegetable Farmers in The Gambia

Saltwater intrusion represents an increasingly significant challenge for smallholder vegetable farmers in The Gambia, particularly in the Lower River Region (LRR) and North Bank Region (NBR). This study therefore examines the demographic, vulnerability of agricultural landscape to saltwater intrusion, and the resilience of 35 smallholder vegetable farming households in the North Bank (NBR) and Lower River (LRR) regions, using the Composite Index of Climate Resilience (CICR) specific to saltwater intrusion and the Resilience Index Measurement and Analysis (RIMA) framework. Given that 91% of households derive their livelihoods from agricultural production, the study identifies high levels of awareness regarding climate change (94%) and indicate that 89% of farmers have experienced a decline in crop yields and income as a result of saltwater intrusion. There are regional and gender differences, the NBR exhibits a higher Resilience Capacity Index (RCI) than the LRR. While female-headed households demonstrate greater access to essential services, yet face more significant barriers to agricultural assets. In contrast, male-headed households exhibit stronger adaptive capacities. In sum, the findings indicate that saltwater intrusion exacerbates vulnerabilities and threatens food security. This highlights the necessity for targeted, region-specific, and gender-sensitive interventions, including improved agricultural inputs, social safety nets, and literacy support, to strengthen resilience among Gambian smallholder farmers and support sustainable livelihoods.

Human behavioral dynamics and stock return movements: Evidence from China

This paper develops an analysis framework based on the principle of human behavior dynamics and the jump-diffusion process. Based on empirical tests on Chinese stock markets, the paper reveals a negative correlation between jump levels in the previous month and stock returns in the following month. On average, an increase of each 1 unit in the value of the jump component results in a lower subsequent stock return of 58 basis points. Moreover, the long-short arbitrage portfolios based on jump levels perform better than the market portfolio; the Sharpe ratio is 4 times that of the market index, indicating that jump-based trading strategies have a great ability to pursue abnormal returns.

A Methodological Framework for AI-Driven Textual Data Analysis in Digital Media

The growing volume of textual data generated on digital media platforms presents significant challenges for the analysis and interpretation of information. This article proposes a methodological approach that combines artificial intelligence (AI) techniques and statistical methods to explore and analyze textual data from digital media. The framework, titled DAFIM (Data Analysis Framework for Information and Media), includes strategies for data collection through APIs and web scraping, textual data processing, and data enrichment using AI solutions, including named entity recognition (people, locations, objects, and brands) and the detection of clickbait in news. Sentiment analysis and text clustering techniques are integrated to support content analysis. The potential applications of this methodology include social networks, news aggregators, news portals, and newsletters, offering a robust framework for studying digital data and supporting informed decision-making. The proposed framework is validated through a case study involving data extracted from the Google News aggregation platform, focusing on the Israel–Lebanon conflict. This demonstrates the framework’s capability to uncover narrative patterns, content trends, and clickbait detection while also highlighting its advantages and limitations.

Kebijakan Nota Kesepahaman Pengawasan Partisipatif BAWASLU dan JPS Sumatera Barat pada Pemilihan Umum Tahun 2024

The General Election Supervisory Agency (BAWASLU) has several limitations in achieving electoral justice technically, namely personnel limitations and the vast geographical scope of the supervisory area. Then the challenge becomes even more complicated in the simultaneous 2024 elections, which place digital media as the primary space for political campaigns. Also, in the policy of the Memorandum of Understanding for participatory oversight with the West Sumatra Editors' Network (JPS), 10 out of 16 JPS media outlets placed political advertisements on their respective websites or news portals, indicating that the media have political tendencies. The goal of this research is to examine the implementation of the policy and the news coverage it generates. The research method used is quasi-qualitative with a policy analysis framework. Data collection was conducted through observation, interviews, and document studies with key informants from BAWASLU West Sumatra and JPS. In addition, this research is supported by the framing analysis method to see how the news in participatory oversight policies is framed and constructed to encourage active public participation in election oversight. The results of this study show the role of each institution, with BAWASLU West Sumatra playing the role of agenda-setting in news coverage by determining and providing information, while JPS constructs and publishes the news. Then, the results of the framing analysis show that the JPS media predominantly uses event frames (43%) and idea frames (43%), while the low figurative frame (14%) indicates the media's independence from political interests. However, the tone or mood of the news coverage is dominated by a hopeful tone (73.5%) compared to an advisory tone (21.8%), thus tending to build optimism rather than encouraging direct public participation. In general, this news pattern directs JPS more towards the public relations function of BAWASLU rather than the educational function to encourage active public participation in election supervision.

Public contributions to R&D of medical innovations: A framework for analysis.

Article 57 of the proposed European Union (EU) Pharmaceutical Legislation (PL, Directive) will require market authorization applicants to publicly declare any direct financial support for R&D received from public authorities. Our research aims to identify the categories needed to capture direct or indirect public contributions to R&D, provide a framework for standardized reporting of public contributions, and reduce ambiguity in the interpretation of "direct" and "indirect" public contributions. An iterative mixed-methods approach is applied: a targeted literature review was conducted, complemented by interviews with representatives of different stakeholder groups to identify categories of public contributions to R&D, followed by searches for relevant data sources. 26 publications on primary data relevant to analyses of public contributions were identified, finding that between half of all drugs approved and >90 % of drug targets are associated with public sector institutions and/ or their spin-outs. Eight categories of public contributions to medical innovations were identified along the value chain (from basic research to post-market surveillance). The framework offers a structured and systematic approach for identifying data on public and philanthropic contributions to developing medical products (medicines and devices). This information is often not comprehensively documented. Therefore, aligned public policies enforcing transparent and standardized reporting in sufficient granularity on R&D investments and conditions are key.

A modelling framework to analyze climate change effects on radionuclide aquifer contamination

Non-stationarity of climatic variables (e.g., temperature and precipitation) due to Climate Change (CC) can affect the migration processes of radionuclides released from nuclear activities. In this paper, a framework of analysis is developed to predict the evolution in time of contaminant concentration and fluence under different Climatic Boundary Conditions (CBCs) of precipitation scenarios provided by a climate model integrated with an accurate physical coupled hydraulic-transport model. A case study is worked out with respect to the migration of a radioactive contaminant (232Th) at Kirtland Air Force Base (Albuquerque, New Mexico, USA), for which the different CBCs considered are: i) stationary and ii) non-stationary precipitation. The effects of such alternative hypotheses on the physical modelling results are analysed, using a cross-wavelet analysis. It is shown that fluence is strongly affected by precipitation extremes, more than concentration, and it is claimed that a daily scale on the information and data of CBCs is necessary to model, with sufficient accuracy, the migration process and properly assess the impact of future CC on groundwater contamination.

Facile synthesis of hierarchically flower-like hollow covalent organic frameworks for enrichment and metabolic analysis of benzophenone derivatives in mouse serum.

Benzophenone derivatives (BPs), as synthetic chemicals widely used in personal care products, have drawn increasing attention due to their potential health risks. However, monitoring BPs in biological samples remains challenging due to their complex matrices and the deficiency in sensitivity and selectivity in current methods. Herein, a method combining hierarchically flower-like hollow covalent organic frameworks (HFH-COFs) with high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) was established for the enrichment and detection of BPs in serum samples. The HFH-COFs were synthesized at room temperature and employed as an adsorbent due to their advantageous properties. The as-prepared HFH-COFs exhibited high specific surface area (2286.53 m²/g), excellent chemical stability, and good thermal stability, making them ideal for efficient enrichment applications. Under optimized experimental conditions, five BPs were effectively enriched and quantified by HPLC-MS/MS in the range of 50.0-5000.0 ng/L with good linearity (r > 0.9992). The limit of detections was 0.5-10.0 ng/L. Furthermore, HFH-COFs showed high enrichment factors even over multiple adsorption-desorption cycles. This study proposed a reliable and efficient method for monitoring endocrine-disrupting compounds in complex biological samples and highlighted the potential of HFH-COFs as a superior adsorbent material for BP.

An integrated framework for prediction and sensitivity analysis of water levels in front of pumping stations

An integrated framework for prediction and sensitivity analysis of water levels in front of pumping stations

I-CLTP: Integrated contrastive learning with transformer framework for traffic state prediction and network-wide analysis

i-CLTP: Integrated contrastive learning with transformer framework for traffic state prediction and network-wide analysis

Multilayer network framework and metrics for table tennis analysis: Integrating network science, entropy, and machine learning

Multilayer network framework and metrics for table tennis analysis: Integrating network science, entropy, and machine learning

A novel large language model enhanced joint learning framework for fine-grained sentiment analysis on drug reviews

A novel large language model enhanced joint learning framework for fine-grained sentiment analysis on drug reviews

System outage fragility for power systems: A robust data-driven framework for disparity analysis using multiple hurricane events

System outage fragility for power systems: A robust data-driven framework for disparity analysis using multiple hurricane events

Simulating concrete cracking and failure under impact loading using a novel constitutive integration paradigm in non-ordinary state-based Peridynamics

Concrete cracking and failure under external loads are common in infrastructure, particularly under impact conditions where the variability of loads and the complexity of the cracking process present significant challenges. While the Bond-Based Peridynamic (BBPD) and Ordinary State-Based Peridynamic (OSBPD) models are widely used in concrete damage analysis due to their low computational cost, their simple constitutive laws limit their effectiveness in simulating concrete’s response to impact loading. To overcome this limitation, we propose a novel approach that integrates classical constitutive models into the Peridynamics (PD) framework. Specifically, we reformulate the Concrete Damage Plasticity Model 2 (CDPM2) within a non-ordinary state-based PD (NOSBPD) framework, resulting in the CDPM2-PD model. This model incorporates factors such as strain rate effects and strain hardening and introduces a bond damage criterion for both tensile and compressive damage. Through three numerical examples, the CDPM2-PD model demonstrates its ability to accurately capture the cracking and failure process of concrete under impact, showing strong agreement with experimental observations in areas such as failure mode transitions and crack patterns. These results validate the model’s effectiveness and offer a versatile method for integrating classical constitutive models into the NOSBPD framework for complex material analysis.

Analysis of the Italian regulatory framework on the welfare of aquatic organisms, with a focus on live crustaceans

Analysis of the Italian regulatory framework on the welfare of aquatic organisms, with a focus on live crustaceans