Analytical Framework Research Articles

From conceptualising to modelling structural determinants and interventions in HIV transmission dynamics models: a scoping review and methodological framework for evidence-based analyses

Abstract Background Including structural determinants (e.g. criminalisation, stigma, inequitable gender norms) in dynamic HIV transmission models is important to help quantify their population-level impacts and guide implementation of effective interventions that reduce the burden of HIV and inequalities thereof. However, evidence-based modelling of structural determinants is challenging partly due to a limited understanding of their causal pathways and few empirical estimates of their effects on HIV acquisition and transmission. Methods We conducted a scoping review of dynamic HIV transmission modelling studies that evaluated the impacts of structural determinants, published up to August 28, 2023, using Ovid Embase and Medline online databases. We appraised studies on how models represented exposure to structural determinants and causal pathways. Building on this, we developed a new methodological framework and recommendations to support the incorporation of structural determinants in transmission dynamics models and their analyses. We discuss the data and analyses that could strengthen the evidence used to inform these models. Results We identified 17 HIV modelling studies that represented structural determinants and/or interventions, including incarceration of people who inject drugs (number of studies [n] = 5), violence against women (n = 3), HIV stigma (n = 1), and housing instability (n = 1), among others (n = 7). Most studies (n = 10) modelled exposures dynamically. Almost half (8/17 studies) represented multiple exposure histories (e.g. current, recent, non-recent exposure). Structural determinants were often assumed to influence HIV indirectly by influencing mediators such as contact patterns, condom use, and antiretroviral therapy use. However, causal pathways’ assumptions were sometimes simple, with few mediators explicitly represented in the model, and largely based on cross-sectional associations. Although most studies calibrated models using HIV epidemiological data, less than half (7/17) also fitted or cross-validated to data on the prevalence, frequency, or effects of exposure to structural determinants. Conclusions Mathematical models can play a crucial role in elucidating the population-level impacts of structural determinants and interventions on HIV. We recommend the next generation of models reflect exposure to structural determinants dynamically and mechanistically, and reproduce the key causal pathways, based on longitudinal evidence of links between structural determinants, mediators, and HIV. This would improve the validity and usefulness of predictions of the impacts of structural determinants and interventions.

Dementia caregiving during the COVID-19 pandemic: an interpretative phenomenological analysis of caregivers' experiences.

To explore the lived experience of informal dementia caregivers during the COVID-19 pandemic. Interpretative Phenomenological Analysis (IPA) was employed. Eight primary informal caregivers were recruited from a community mental health service for older people when attending in their role as caregiver of a service-user. Semi-structured interviews were conducted at home or in the clinic based on the participants' convenience and preference. IPA was completed following Smith and colleagues framework for analysis. Six group experiential themes, each with a number of subthemes, emerged from the cross-case interpretative analysis: the ambivalent experience of caregiving (subtheme: those complex emotional experiences); navigating lockdown: lived challenges and opportunities (subthemes: the pervasive fear, intensification of existing struggles, being prevented from caring for a loved one, and lockdown as a time for opportunity); transitioning out of lockdown (subthemes: regaining freedom, but restricted freedom after all and being in a lockdown of one's own); the present with COVID-19, but mostly with dementia (subthemes: dementia, a disease that does not pause, and 'takeaways' from the journey); looking into the future (subthemes: embracing COVID-19 and the true needs); and a word on coping (subtheme: managing it all as best one can). Findings demonstrate the significance of the meaning caregivers ascribed to their experiences on their wellbeing and ability to cope in times of COVID-19 and thereafter. Gaining an understanding of the caregivers' unique experiences is crucial to appreciate how to best support them.

Development and validation of the 5-Dimension Comprehensive Assessment Scale (5DCAS) for assessing physical function and health in axial spondyloarthritis.

To describe the development and validation of a novel patient reported scale, which is a comprehensive assessment of the physical function and health specific for patients with axial spondyloarthritis (axSpA). This is a multiphase, mixed methods study. Based on opinion collection and discussions of multidisciplinary consensus meetings and patients, an initial item pool covering all of the ranges of functioning was generated. The item optimization, model fit, response category functioning, differential item functioning, reliability, structure validity, and unidimensionality were tested by confirmatory factor analysis and Rasch measurement theory framework. After the consensus meeting and the two rounds of surveys in patients with axSpA, the initial pool of 135 items was reduced to 25 items formed in five dimensions, which exhibited preferable item reliability, item fit, and person fit to the Rasch model. The Five-Dimensional Comprehensive Assessment Scale (5DCAS) had the best reliability and validity (Kaiser-Meyer-Olkin was 0.919, and the standardized Cronbach's α coefficient was 0.932). The final version of 5DCAS had good unidimensionality, and the Person Separation Index ranged from 0.77 to 0.85. 5DCAS significantly correlated with ASAS-HI, SF-36, BASFI, and disease activity with p values of < 0.001. 5DCAS is a novel patient-reported outcome specific to axSpA, and it forms five dimensions providing a linear sum score of 25 items. 5DCAS comprehensively and significantly represents the physical function and health status of patients with axSpA, although its performance needs further validation in future clinical practices. Key Points • The primary goal in the management of axial spondyloarthritis is to maximize health-related quality of life. Except for the current instruments of ASAS-HI, BASFI, or SF-36, the heterogeneous clinical symptoms and rapid updated treat-to-target concept require a new instrument which can comprehensive and significant evaluate the changes of physical function and health-related quality of life due to disease. • 5DCAS is a novel patient-reported outcome specific to axSpA, and it forms five dimensions providing a linear sum score of 25 items, which contained aspect of pain involvement, spine mobility, global body performance and activity, social participation and environment, and mental health. All of the items were set to a 4-point semantic rating scale measuring severity, frequency, or interference from score 0 to 3. Total 5DCAS score ranges from 0 to 75; higher scores represented greater symptom burden and worse physical function. • 5DCAS is a comprehensive, multidisciplinary, and convenient disease outcome measurement specific for axSpA. It provides a new evaluation instrument in clinical trial and treat-to-target clinical remission for patients and physicians, and also provides a sensitive and accurate assessment standard for optimized health benefits.

Migration scale, process, and impact in the Tiwanaku colonies: Paleomobility at the archaeological site of Omo M10.

Contemporary migrations show form and intensity of interaction between homeland and host communities to shape social dynamics and identities. We apply here a contemporary theoretical framework and biogeochemical analyses to elucidate the scale, processes, and impacts of migration in the Tiwanaku polity (6th-11th c. CE) by inferring the mobility of individuals interred at the Tiwanaku-affiliated site of Omo M10 (Moquegua Valley, Peru). For each of 124 individuals, we captured paleomobility across the life-course by analyzing up to four enamel and bone samples that formed during discrete developmental periods for radiogenic strontium (87Sr/86Sr) and stable oxygen (δ18Ocarbonate(VPDB)) isotopes. At Omo M10, archaeological human enamel and bone values range from 87Sr/86Sr = 0.70632-0.72183 and δ18Ocarbonate(VPDB) = -13.4‰ to +1.7‰, with a mean of 87Sr/86Sr = 0.70763 ± 0.00164 (1σ, n = 334) and δ18O = -7.8‰ ± 1.9‰ (1σ, n = 334). Together with archaeological evidence, we interpret these data as evidence for multigenerational interaction between communities in the high-altitude Tiwanaku heartland and at the site of Omo M10. Our results suggest that one-fourth of individuals spent some part of their life outside of Moquegua and one in eight individuals from Omo M10 were first-generation migrants. Greater mobility of females and juveniles at Omo M10 indicates that gender and family were important social constructs in maintaining relationships and cultural continuity in provincial Tiwanaku life, and communities maintained autochthonous migration streams with Tiwanaku-affiliated populations throughout the south-central Andes. Intra-individual biogeochemical analyses of migration at Omo M10 contribute a nuanced perspective on the diverse experiences of multigenerational Tiwanaku colonies.

An Integrated Framework of Critical Metaphor Analysis and Multi-level View with an Application to Metaphors for the Vietnam War

Since Conceptual Metaphor Theory (CMT) (Lakoff &amp; Johnson, 1980) was introduced, methods of studying conceptual metaphor have kept improving to respond to methodological criticisms. Critical Metaphor Analysis (CMA) proposed by Charteris-Black (2004) has been considered as a “thought-provoking contribution” to metaphor analysis (Deignan, 2005) when approaching metaphor from various perspectives: critical discourse analysis, corpus analysis, pragmatics and cognitive linguistics. CMA is originally applied to one conceptual level in metaphor – domain. However, this paper argues that CMA can be exploited at four conceptual levels in Multi-level View of conceptual metaphor (Kövecses, 2017b) - image schema, domain, frame, and mental space. The combined framework of Critical Metaphor Analysis – CMA (Charteris-Black, 2004) and Multi-level View of conceptual metaphor – MLV (Kövecses, 2017b) can gain deeper insights into ideologies motivating metaphorical concepts for the Vietnam war as well as elucidate the conceptual structure of metaphor via the four levels. Hence, this combination fills the gap of lacking a framework with optimal balance of semantic, pragmatic, cognitive and critical dimensions. It also features the intriguing relationship between ideologies and conceptual structure, i.e., ideologies are embedded in all the four conceptual levels and systematically develop with increasing specificity from image schema to domain, frame and mental space. The focus of this paper is on our argument for an integrated framework of conceptual metaphor and the newspaper articles written by American war correspondents during the Vietnam war are used for illustration of how the integrated framework can help us better understand the conceptual metaphors in the articles.

A Framework for Agricultural Intelligent Analysis Based on a Visual Language Large Model

Smart agriculture has become an inevitable trend in the development of modern agriculture, especially promoted by the continuous progress of large language models like chat generative pre-trained transformer (ChatGPT) and general language model (ChatGLM). Although these large models perform well in general knowledge learning, they still have certain limitations and errors when facing agricultural professional knowledge about crop disease identification, growth stage judgment, and so on. Agricultural data involves images and texts and other modalities, which play an important role in agricultural production and management. In order to better learn the characteristics of different modal data in agriculture, realize cross-modal data fusion, and thus understand complex application scenarios, we propose a framework AgriVLM that uses a large amount of agricultural data to fine-tune the visual language model to analyze agricultural data. It can fuse multimodal data and provide more comprehensive agricultural decision support. Specifically, it utilizes Q-former as a bridge between an image encoder and a language model to achieve a cross-modal fusion of agricultural images and text data. Then, we apply a Low-Rank adaptive to fine-tune the language model to achieve an alignment between agricultural image features and a pre-trained language model. The experimental results prove that AgriVLM demonstrates great performance in crop disease recognition and growth stage recognition, with recognition accuracy exceeding 90%, demonstrating its capability to analyze different modalities of agricultural data.

A Comparative Analysis of International Drug Price Negotiation Frameworks: An Interview Study of Key Stakeholders.

In 2022, Congress passed the Inflation Reduction Act, which allowed Medicare, for the first time, to begin negotiating the prices for certain high-cost brand-name prescription drugs. Many other industrialized countries negotiate drug prices, and we sought to compare and contrast key features of the negotiation process across several health systems. We focused, in particular, on the criteria for selecting drugs for price negotiation, procedures for negotiation, factors that influence negotiated prices, and how prices are implemented. We included four G7 countries in our analysis (Canada, France, Germany, and the United Kingdom [England]), two Benelux countries (Belgium and the Netherlands), and one Scandinavian country (Norway) with long-established frameworks for drug price negotiation. We also analyzed the Veterans Affairs Health System in the United States. For each system, we gathered relevant legislation, government publications, and guidelines to understand negotiation frameworks, and we reached out to key drug price negotiators in each system to conduct semistructured interviews. All interviews were recorded, transcribed, and coded, and data were analyzed based on an internal assessment tool that we developed. All eight systems negotiate the prices of brand-name prescription drugs soon after approval and rely on formal clinical assessments that compare newly approved drugs with existing therapies. Systems in our study differed on characteristics such as whether the body performing clinical assessments is separate from the negotiating authority, how added health benefit is assessed, whether explicit willingness-to-pay thresholds are employed, and how specific approaches for priority disease areas are taken. High-income countries around the world adopt different approaches to conducting price negotiations on brand-name drugs but coalesce around a set of practices that will largely be absent from the current Medicare negotiation framework. US policymakers might consider adding some of these characteristics in the future to improve negotiation outcomes.

The Hybrid Modality Model in Higher Education Institutions

The aim of the article is to provide a research result to support the process of consensual and collegiate decision-making in order to mix study models in undergraduate degree courses and postgraduate projects in higher education. The deductive method was used as a starting point and a mixed phenomenological-hermeneutic approach was applied for the methodological design, based on the use of quantitative and qualitative techniques, for which a sample of undergraduate and postgraduate students was selected from the active student population in the year 2021. A structured survey was applied as a technique and a nominal scale was used to collect and analyse the data, which made it possible to determine the students' preferences according to the face-to-face or virtual modality, as well as the incidence of the mixture of both modalities for learning. The results of the research show that undergraduate students show a preference for the face-to-face modality, while postgraduate students prefer the virtual modality. From the examination of the problem, the analysis of the theoretical framework and the applied methodology, it is concluded that the results of the research can help in the process of collegiate decision making by the management agents of higher education institutions, to adequately dose the time load of the face-to-face or virtual modalities, as appropriate to the degree courses and projects.

Mining industry development, enforcement intensity of security policy and intra-city development disparity

China, the world's largest developing country, is rich in mineral resources, albeit unevenly distributed geographically. Some cities with a surplus of mineral resources may form path dependence on these natural resource industries, leading to imbalanced urban development and widening development disparities within cities. However, in the event of safety incidents in the mining industry, local governments are compelled to regulate the excessive development of the mining sector and enhance the enforcement intensity of safety production policies. This study, based on the measurement of the Gini coefficient using nighttime light data for 281 prefecture-level cities in China, manually compiled the locations and death tolls of mining industry production safety incidents from 2001 to 2020, established an empirical analysis framework based on the instrumental variable two-stage least squares method. The research findings indicate: (1) Since the beginning of the 21st century, China's mining industry has experienced significant growth propelled by market-oriented reforms. However, it has also played a notable role in widening development disparities within cities. Robust results were obtained through instrumental variable estimation using the standard deviation of urban ground slope as a geographical indicator. (2) The occurrence of safety incidents in the mining industry will immediately escalate the enforcement intensity of regional safety policies, creating a significant inhibitory impact on alleviating the widening development disparities within cities caused by the expansion of the mining industry. In the case of larger safety incidents with a death toll of 3 or more, this impact will become even more pronounced. (3) Heterogeneity analysis reveals that the outlined mechanism is prominently present in the middle area, where the mining industry is relatively developed. In contrast, there is no significant correlation between the occurrence of safety accidents and the escalation of safety policy implementation intensity in the economically developed eastern region and the western region with lower levels of infrastructure development. However, in cities with a higher proportion of the mining industry, the aforementioned relationships remain stable. (4) Once a mining accident involving fatalities occurs in a prefecture-level city, local governments generally strengthen the enforcement of safety policies, comprehensively eliminate hidden dangers in production safety. This shift leads to a reversal in the impact of the mining industry on the development disparity within the city, changing from an expansion to a reduction effect. Moreover, this reduction effect persists for five years. In the case of a serious safety production incident resulting in 10 or more deaths, the impact of increased implementation of safety policies also extends for a prolonged period of five years. This article makes a clear marginal contribution to enrich the study on the effects of China's mining industry safety policies.

The Bears &amp; Bulls of Fundamental Analysis Vs Technical Analysis

In the intriguing realm of the Indian Stock Market, significant fortunes are amassed and aspirations materialize. In the realm of financial markets, two predominant methodologies govern the analysis of markets: fundamental analysis and technical analysis. This discussion aims to delve into the core principles of each approach, elucidate their respective merits and limitations, and underscore the advantages of amalgamating them to form a comprehensive market analysis framework.  Biography of the Author I am Vansh Thirani, a high school student from New Delhi, India. Stock Market is something I have a lot of interest in. I am very passionate about building a career in this field and with my continuous learning and self- improving skillset, I am confident enough to excel in this field. This paper can help a lot of young teenagers who aspire to gain knowledge and pursue a career in the field of Stock Market Analysis. Being a teenager myself, I understand how challenging it might be for students to start analysing at first, but I believe after students go through this paper, it might become easier for them to analyse and make investment decisions.

Partial Imaginary Transition State (ITS) Graphs: A Formal Framework for Research and Analysis of Atom-to-Atom Maps of Unbalanced Chemical Reactions and Their Completions

Atom-to-atom maps (AAMs) are bijections that establish the correspondence of reactant and product atoms across chemical reactions. They capture crucial features of the reaction mechanism and thus play a central role in modeling chemistry at the level of graph transformations. AAMs are equivalent to so-called “imaginary transition state” (ITS) graphs, making it possible to reduce tasks such as the computational comparison of AAMs to testing graph isomorphisms. In many application scenarios, nonetheless, only partial information is available, i.e., only partial maps or, equivalently, only subgraphs of the ITS graphs, are known. Here, we investigate whether and how, and to what extent, such partial chemical data can be completed and compared. The focus of this contribution is entirely on the development of a solid mathematical foundation for the analysis of partial AAMs and their associated partial ITS graphs.

东盟中文学习者画作中的中文教师角色：基于隐喻的分析

&lt;p&gt;With the implementation and promotion of the "Belt and Road" initiative, economic and trade cooperation and humanistic exchanges between China and ASEAN are going deeper, and Chinese language education in ASEAN has shown a booming development. As a core participant of international Chinese language education in the region, the role of Chinese language teachers is an important conceptual source of ASEAN youth's perception of China, which has a crucial impact on Chinese language learners. Based on the creation of visual metaphors, this study uses the teacher metaphor analysis framework to summarize the ASEAN Chinese teacher role metaphor categories and explore the ASEAN Chinese teacher traits from the learners' perspective. We selected 60 graphic works created by ASEAN Chinese learners as the research material, extracted 31 Chinese teacher role metaphors, and delineated six metaphorical conceptual categories. This study aims to arouse the attention of international Chinese teacher educators, social organizations, and Chinese teachers themselves to the developmental changes of Chinese teacher roles, and to provide a reference for the professional development of international Chinese teachers.&lt;/p&gt;

La ortodoxia del modelo económico clásico y neoclásico: en hombros de gigantes

The objective of this reflection article is to vindicate great thinkers in economics who shaped the main theoretical postulates, philosophy and methodology of science, exposing their conceptual and theoretical framework for a comprehensive understanding of their most relevant contributions. In the development of the article, a historical description of the evolution of orthodox economic thought is offered, within a framework of analysis of recognition of economic doctrines from their historical, institutional, political, cultural and social situation, where their contributions are still significant for the interpretation of current reality, not in an absolute way due to the limitations of the assumptions, methods and historical interpretation of the authors, but with inputs that, objectively analyzed, provide validity and usefulness to economics professionals, and in general to all social scientists, for the exercises of positive economics of description, analysis and systematization of economic phenomena and of normative economics of intervention of reality through economic policy. The historical framework of the exhibition is until the 19th century, keeping in mind that, if the economy was built from classical and neoclassical orthodoxy, the alternative and subsequent currents are necessarily heirs, direct or indirect, of these giants of thought.

Integrating Quantum Computing into Business Analytics: Opportunities and Challenges

This article explores the transformative potential of quantum computing in the field of business analytics. It begins with an introduction to quantum computing, explaining its fundamental principles and recent advancements. The study highlights the limitations of current business analytics methods and demonstrates how quantum computing could address these limitations by offering enhanced data processing capabilities, advanced algorithms, and solutions to complex optimization problems. A comprehensive literature review is conducted to provide context and identify gaps in the existing research. The article then outlines a research design that incorporates both real-world and simulated data, using online datasets and quantum computing frameworks for analysis. The findings reveal significant opportunities for quantum computing to revolutionize business analytics, including improved efficiency, accuracy, and the ability tosolve previously intractable problems. However, the article also addresses key challenges such as technical limitations, cost, accessibility, and integration issues. The discussion highlights emerging trends and provides strategic recommendations for businesses considering the adoption of quantum computing. The article concludes with a summary of the implications of integrating quantum computing into business analytics and reflects onfuture potential and challenges.

Sexual behavior is linked to changes in gut microbiome and systemic inflammation that lead to HIV-1 infection in men who have sex with men

Pathogenic changes in gut microbial composition precede the onset of HIV-1 infection in men who have sex with men (MSM). This process is associated with increased levels of systemic inflammatory biomarkers and risk for AIDS development. Using mediation analysis framework, in this report we link the effects of unprotected receptive intercourse among MSM prior to primary HIV-1 infection to higher levels of proinflammatory cytokines sCD14 and sCD163 in plasma and a significant decrease in the abundance of A. muciniphila, B. caccae, B. fragilis, B. uniformis, Bacteroides spp., Butyricimonas spp., and Odoribacter spp., and a potential increase in the abundance of Dehalobacterium spp. and Methanobrevibacter spp. in stools of MSM with the highest number of sexual partners. These differences in microbiota, together with a reduction in the pairwise correlations among commensal and short-chain fatty acid-producing bacteria with a number of sexual partners, support an increase in gut dysbiosis with the number of sexual partners. These results demonstrate the interconnectedness of sexual behavior, immune response, and microbiota composition, notably among MSM participating in high-risk sexual behaviors.

Affective incapacity of the depressed self: Evidence from a narrative study of an online depression community on Weibo

With the increasing prevalence of depression worldwide, there is a noticeable number of online depression communities (ODCs) flourishing in cyberspace. This phenomenon offers a discursive platform for observing and discerning people’s mental and affective struggles. Under the overarching framework of narrative analysis, we coded the most salient emotions expressed in 2000 pieces of comments by the top 20 core participants of ‘Zoufan’, an ODC space on China Weibo. We analyze how the members construct their emotive struggles and depressed self in self-talk (disengagement) and interactions (engagement) via linguistic deixis. Based on this communication mapping, this study offers a new notion of affective incapacity as an epistemological insight into depressive emotions. The observed phenomena of both inward-centered (self-talk) emotions and outward-centered (dialogue) emotions point to members’ reduced capacity to affect and to be affected, to intervene and to be intervened. This research is expected to educate both the public and social professionals in recognizing more nuanced emotional deliberation of self-reported depression and take early measures if need be.

CO2 Electrolysis Technologies: Bridging the Gap toward Scale-up and Commercialization.

CO2 electroreduction (CO2E) converts CO2 into carbon-based fuels and chemical feedstocks that can be integrated into existing chemical processes. After decades of research, CO2E is approaching commercialization with several startups, pilot plants, and large initiatives targeting different products. Here, we analyze the global efforts in scaling up CO2E, addressing implementation challenges and proposing methods for acceleration. We present a comparative analysis of key performance indicators (KPIs) between laboratory and industrial settings and suggest a stepwise technoeconomic analysis (TEA) framework, supported by industrial data, exploiting interactions within the academic and industrial communities. We identify the lack of systems-oriented standardization and durability as the main bottlenecks slowing down progress in the lab-to-prototype-to-market pathway of CO2E technologies. Inspired by electrolysis and fuel cell technologies, we outline protocols to advance fundamental research and aid catalyst development progress in performance, upscaling, and technology readiness level of CO2E.

A theoretical model for the load-transfer analyses of load distributive compression anchor integrating DSC-based interface nonlinear model

An innovative anchorage technology named load distributive compression anchor (LDCA) has recently been employed in a multitude of geotechnical engineering. The anchoring structure comprises multiple anchor bodies, thereby overcoming the bearing defects associated with conventional load-concentrated anchors and providing superior bearing performance. The complex structural configuration of LDCA considerably complicates the process of load-transfer theoretical modeling. A lack of relevant studies from theoretical solution perspective is yet evident in previous works. In this paper, a theoretical model was proposed for the load-transfer analyses of LDCA, of which the soil-anchor interface mechanical behavior was specially characterized by a disturbed state concept (DSC)-based nonlinear model. The mechanical simulation for the connections in different anchor bodies was incorporated into the theoretical analysis framework through the utilization of finite difference method. Three groups of 3D finite element (FE) models were established to simulate the load-transfer behaviors of LDCAs with different numbers of anchor bodies. The theoretical calculations agree well with the FE numerical results and the in-situ pullout test data, thereby confirming the applicability of the load-transfer theoretical model. The axial force and interface shear stress distributions, as well as the bearing capacity for LDCAs, were discussed based on theoretical calculations and FE simulations. Sensitivity analysis of several key design parameters was conducted to investigate their effects on the bearing capacity of LDCAs. The findings achieved in this study can provide insights into the understanding of the load-transfer behaviors of LDCA, and contribute to the bearing performance evaluation.

How to facilitate in-depth digitalization in enterprises?

ABSTRACT Digitalization is the new engine for enhancing long-term production efficiency in enterprises. However, as a high-investment, high-risk, and long-duration activity, the returns from digitalization are fraught with considerable uncertainty. This paper begins from the perspective of maximizing corporate profits and constructs a static equilibrium analysis framework to explore the digitalization strategies of enterprises under varying degrees of return uncertainty. It is discovered that as the uncertainty of digital investment returns gradually decreases, the optimal strategies for industrial enterprises evolve from ‘not undergoing digitalization’ to ‘undergoing preliminary digitalization’, and finally to ‘undergoing in-depth digitalization’. Based on these findings, this paper proposes corresponding policies to promote in-depth digitalization in enterprises.

Robustness of hypergraph under attack with limited information based on percolation theory

Hypergraphs serve as a representative form to display higher-order interactions that persist in the community structure of ecological and social systems. A significant characteristic of these entities is their critical behaviours and robustness in response to aggressive assaults. However, in reality, the network structure may be partially observable, meaning that it is distinct from the assumption of global accessibility under random and deliberate assaults. In this work, we provide a theoretical framework to analyse the changes in the giant component in a hypergraph when subjected to limited information disintegration. Percolation theory is employed to derive the size of the giant component and the critical point. Specifically, we apply the message-passing method based on factor graphs to establish a framework for percolation analysis under limited information attacks. On this basis, the hypergraph structure is accurately described. The advantages lie in avoiding the redundant demands of multiple repetitive experiments. Our study demonstrates the relationship between the diversity of the attacked network and the critical condition. By conducting numerical simulations and theoretical research, we also conclude that controlling the observed size of the network and moderately increasing the average hyperdegree can enhance the robustness of the hypergraph. These findings further indicate the impact of hypergraph topology on the resilience of systems and provide analytical insights for optimizing systems with cost-effectiveness and robustness.