Search Results (1,139)

Background/Objectives: Family Integrated Care (FICare) is a model of care for preterm or critically ill infants in which families are considered equal partners with clinical teams and are fully integrated into all aspects of care and decision-making. In this study, we conducted a health economics study of FICare implementation in the UK, as part of the EU-funded international, interdisciplinary, and intersectoral project RISEinFamily. Methods: An economic evaluation of healthcare services and an audit of clinical outcomes for infants admitted to the Royal Sussex County Hospital and the Princess Royal Hospital neonatal units in 2021 (at the start of FICare) and 2024 (when FICare was fully integrated into clinical practice) were conducted. Anonymized data on hospital admissions were downloaded from the hospital database. Infants with a duration of stay in the NICU of more than 20 days were included in the analysis. The cost of NICU stay was estimated using the Health Resource Group codes. Results: The average duration of infants’ stay in NICU was similar before and after the implementation of FICare (47 days (SD 29) in 2021 and 47 days (SD 31) in 2024). However, the infants who received FICare spent fewer days in high-dependency care; on average, 10 days in 2024 and 13 days in 2021. The duration of invasive ventilation fell by 12% and the duration of CPAP by 26% after introducing FICare. The total cost per baby stay in NICU was GBP 63,279 (USD 87,021) in 2021 and GBP 59,284 (USD 75,777) in 2024. Conclusions: Although the changes did not reach statistical significance, the study suggests that FICare may be resource- and cost-saving due to reducing infants’ stays in high-dependency care. Full article

Cost code verification in state-funded construction projects remains a labor-intensive and error-prone task, particularly given the structural heterogeneity of project estimates and the prevalence of malformed codes, inconsistent units of measurement (UoMs), and locally modified price components. This study evaluates a deterministic GPT-based assistant designed to automate Vietnam’s regulatory verification. The assistant was developed and iteratively refined across four Action Research cycles. Also, the system enforces strict rule sequencing and dataset grounding via Python-governed computations. Rather than relying on probabilistic or semantic reasoning, the system performs strictly deterministic checks on code validity, UoM alignment, and unit price conformity in material (MTR), labor (LBR), and machinery (MCR), given the provincial unit price books (UPBs). Deterministic equality is evaluated either on raw numerical values or on values transformed through explicitly declared, rule-governed operations, preserving auditability without introducing tolerance-based or inferential reasoning. A dedicated exact-match mechanism, which is activated only when a code is invalid, enables the recovery of typographical errors only when a project item’s full price vector well matches a normative entry. Using twenty real construction estimates (16,100 rows) and twelve controlled error-injection cases, the study demonstrates that the assistant executes verification steps with high reliability across diverse spreadsheet structures, avoiding ambiguity and maintaining full auditability. Deterministic extraction and normalization routines facilitate robust handling of displaced headers, merged cells, and non-standard labeling, while structured reporting provides line-by-line traceability aligned with professional verification workflows. Practitioner feedback confirms that the system reduces manual tracing effort, improves evaluation consistency, and supports documentation compliance with human judgment. This research contributes a framework for large language model (LLM)-orchestrated verification, demonstrating how Action Research can align AI tools with domain expectations. Furthermore, it establishes a methodology for deploying LLMs in safety-critical and regulation-driven environments. Limitations—including narrow diagnostic scope, unlisted quotation exclusion, single-province UPB compliance, and sensitivity to extreme spreadsheet irregularities—define directions for future deterministic extensions. Overall, the findings illustrate how tightly constrained LLM configurations can augment, rather than replace, professional cost verification practices in public-sector construction. Full article

Perpetual futures account for approximately 93% of cryptocurrency futures trading volume, yet funding rate dynamics across fragmented markets remain understudied. We construct a high-frequency panel dataset comprising 35.7 million one-minute observations across 26 cryptocurrency exchanges (11 centralized, 15 decentralized) spanning 749 symbols over eight consecutive days. Using time-series econometrics, correlation analysis, and Granger causality tests, we characterize funding rate dynamics, market integration, and information flow. We find evidence of a two-tiered market structure: centralized exchanges (CEX) dominate price discovery with 61% higher integration than decentralized exchanges (DEX), and all significant information flow runs CEX-to-DEX with zero reverse causality. While 17% of observations exhibit economically significant arbitrage spreads (≥20 basis points), only 40% of top opportunities generate positive returns after transaction costs and spread reversals. Delta-neutral portfolio simulations reveal that successful arbitrage requires both high spreads and sufficient duration before inevitable reversals, with forced exits occurring in 95% of opportunities. The findings show that cryptocurrency derivatives markets exhibit a persistent two-tiered structure in which centralized platforms dominate price discovery while transaction costs and spread reversal risks prevent arbitrage from eliminating large mispricings between platforms, resolving the apparent paradox of substantial price fragmentation coexisting with market efficiency. Full article

Objective: To analyse written submissions from individuals and families with lived experience of attention-deficit hyperactivity disorder (ADHD) to the 2023 Australian Senate Inquiry, using artificial intelligence (AI)-assisted thematic analysis. The aim was to identify priority concerns, service needs, and community-proposed solutions. Methods: A mixed-methods study of 505 publicly available submissions from individuals with ADHD and their families. Submissions were analysed using large language model (LLM)-assisted data extraction and thematic clustering, with human validation and review. Main Outcome Measures: Frequency and thematic distribution of (1) problems experienced; (2) services wanted; and (3) solutions suggested. Results: Thematic analysis of 480 eligible submissions revealed high costs and long wait times for assessment and treatment (each cited by 46%), lack of specialised care (39%), diagnostic delays (36%), and gender bias (27%). The most common service request was for affordable and accessible ADHD-specific care (71%), followed by services tailored to diverse populations and life stages. Proposed solutions focused on Medicare-funded access to psychological and psychiatric services (68%), expanded roles for general practitioners, improved provider training (39%), and recognition of ADHD under the National Disability Insurance Scheme. Submissions also highlighted misalignment between current clinical guidelines and public expectations. Conclusions: The findings highlight substantial unmet needs and systemic barriers in ADHD diagnosis and care in Australia. The AI-assisted analysis of consumer submissions offers a scalable method for integrating lived experience into policy development, providing numerical weighting to the individuals’ responses. Coordinated reforms in access, funding, and workforce training are needed to align services with both clinical evidence and community expectations. Full article

In recent years, the development of new diagnostic technologies, such as tandem mass spectrometry (MS/MS) and next-generation sequencing (NGS), has caused a veritable revolution in the diagnosis of genetic diseases, reducing time, cost, and invasiveness associated with prior diagnostic techniques. While MS/MS laid the foundation for the development of numerous, usually institutionally based, neonatal screening programs, NGS has gained traction in newborn screening (NBS), primarily through pilot projects and private funding across different countries. As a result, the traditional Wilson and Jungner criteria have been supplemented by additional criteria, including considerations of equity and access, in response to emerging technologies. This review aims to provide an up-to-date overview of the global landscape of metabolic screening panels, highlight the major ongoing genomic screening projects, and outline the current models for integrating these two screening systems. Substantial differences exist across countries in the numbers and types of diseases included in national NBS programmes. In this context, Italy represents a prominent case, as its neonatal screening framework has seen significant expansion and development in recent years, reaching a particularly comprehensive metabolic screening panel. Nonetheless, a number of initiatives to incorporate genomic technologies into the NBS pathway are currently underway, primarily involving high-income countries. Nonetheless, unlike metabolomic-based NBS programs, no country has a government-mandated NGS program as first-tier testing for newborns. New evidence is emerging from ongoing models of integration of multi-omics approaches into NBS, including the use of AI and machine learning. Identifying the most appropriate system for this integration to reduce the false-positive and false-negative rates associated with both screening types, ensure more equitable access to screening, and facilitate faster access to treatment may represent a useful and foresightful way to conceptualize NBS in the future. This transitional phase should promote rigorous improvements before full-scale adoption. Full article

Methane emissions from underground coal mines are a significant source of greenhouse gases (GHGs) and a major safety concern. In highly methane-prone operations, a large proportion of emissions comes from low-content abandoned mine methane (LCAMM) accumulated in post-mining goafs, where concentrations usually stay below 30% CH₄. Building on the Research Fund for Coal and Steel (RFCS) REM project, this paper presents a cost–benefit analysis of a comprehensive scheme for capturing, transporting, and utilising LCAMM from post-mining goafs for electricity generation. The concept involves long-reach directional boreholes drilled behind isolation dams, a dedicated methane-reduced drainage system connected to a surface methane drainage station, and four 2 MWe gas engines designed to run on a 20–40% CH₄ mixture. Greenhouse gas performance is evaluated by comparing a “business-as-usual” scenario in which post-mining methane is combusted in gas engines to produce electricity without further GHG cost–benefit consideration. The results indicate that the project can achieve a positive net present value, highlighting the role of LCAMM utilisation for methane-intensive coal mines. The paper also explores the monetisation of non-emitted methane using the European Union Emissions Trading System (EU ETS), as well as social cost benchmarks and penalty levels consistent with the emerging EU Methane Emissions Regulation (EU MER). Full article

Exchange-traded funds (ETFs) provide low-cost, liquid access to broad equity and fixed-income exposures, including rapidly growing Asian and Asia-focused markets. Yet the academic evidence on Asian ETF portfolio construction remains fragmented, often limited to narrow country samples and centered on mean–variance trade-offs and standard performance statistics, with comparatively less emphasis on downside tail risk and on implementable long-only versus long–short designs under leverage constraints. This study examines the performance and risk characteristics of 29 Asian and Asia-focused ETFs over 2014–2025 and evaluates whether optimization using variance-based and tail-sensitive risk measures improves portfolio outcomes relative to a simple, implementable benchmark. We construct Markowitz mean–variance and conditional value-at-risk (CVaR) efficient frontiers and implement six optimized portfolios at the 95% and 99% tail levels under long-only and long–short configurations with leverage up to 30%. Performance is evaluated relative to an equally weighted Asian ETF benchmark using the Sharpe ratio and tail-sensitive measures, including the Rachev ratio and the stable tail adjusted return (STARR), complemented by fat-tail diagnostics based on the Hill tail-index estimator. The empirical results show that optimization improves efficiency relative to equal weighting in risk-adjusted terms and that moderate leverage can increase returns but typically amplifies volatility, dispersion, and drawdowns. Taken together, the evidence indicates that risk-measure choice materially affects portfolio composition and realized outcomes, with tail-based optimization generally producing more robust allocations than mean–variance approaches when downside risk is a primary concern. Full article

Between 2018 and 2025, alternative finance expanded while micro-, small- and medium-sized enterprises in emerging economies continued to face a substantial funding gap. This study examines how entrepreneurial frugality articulates frugal ecosystems, access to alternative finance, resilience and SME performance within a single explanatory framework. Following PRISMA 2020 and PRISMA-S, we conduct a systematic review of Scopus, Web of Science and Cairn; out of 1483 records, 106 peer-reviewed studies are retained and assessed using the Mixed Methods Appraisal Tool and a narrative synthesis approach. The findings show that frugal ecosystems characterized by pooled assets, norms of repair and modularity, and lightweight digital tools reduce experimentation costs and develop frugal innovation as an organizational capability. This capability enhances access to alternative finance by generating readable quality signals, while non-bank channels provide a financial buffer that aligns liquidity with operating cycles and strengthens entrepreneurial resilience. The article proposes an operationalized conceptual model, measurement guidelines for future quantitative surveys, and public policy and managerial implications to support frugal and inclusive innovation trajectories in emerging contexts. Full article

This study examines the financial resilience of small enterprises in Ukraine during the wartime crisis, addressing the lack of quantitative evidence on how regional military risks and adaptive strategies jointly shape SME stability. The analysis is based on a sample of 30 small agricultural enterprises from the eastern, central, and western regions of Ukraine using annual data for 2022–2024. To capture multidimensional resilience patterns, the study applies factor analysis, cluster analysis, and taxonomic assessment methods to evaluate financial performance, operational adaptability, and access to external resources. The findings show that resilience variation across the sample is strongly associated with enterprises’ ability to sustain revenue flows, control operating costs, and maintain a balanced capital structure. Three distinct resilience profiles were identified: high resilience in western regions (KT = 0.89), moderate resilience in central regions (KT = 0.81), and low resilience in eastern frontline regions (KT = 0.49). These results indicate substantial regional asymmetry linked to differentiated exposure to military threats. Building on these empirical insights, the study proposes a hybrid risk-management approach that integrates digitalization of financial operations, diversification of funding sources, and enhanced social engagement as mechanisms supporting adaptation under prolonged instability. The novelty of the research lies in combining regional risk exposure with multidimensional financial indicators to develop an evidence-based framework for assessing SME resilience in wartime conditions. Full article

Greece’s National Climate Law, enacted under L. 4936, mandates the development of Municipal Emission Reduction Plans (MERPs) by local authorities. Publicly available MERP procurement data contains valuable information that can be utilized to provide an overview and insights into MERP procurement and development. The main objective of this study is to perform a comparative analysis of Greek MERP procurement data and identify patterns in the contract cost estimation of mitigation action plans in Greek municipalities. For this purpose, MERP procurement data was collected from the official procurement register, KIMDIS, and subsequently analyzed through a bivariate approach comparing the collected data with selected independent variables. The results are stratified by population range and official municipal classification to enable comparison between different sizes and types of municipalities. The results indicate that a total of 44% of municipalities in Greece procured their MERP, with significant delays in adherence to official deadlines and only after the MERP became a prerequisite for funding-related matters. Additionally, the procurement process was highly characterized by single bidding. Average contract duration ranged from 110 to 220 days, with an average contract value between EUR 18,000 and EUR 33,000. The difference between tender budget and contract value averaged between 0 and 5%. Full article

Improving the energy efficiency of buildings is a highly desirable investment in the context of implementing the sustainable development paradigm, as it reduces the building’s energy demand. Consequently, the economic costs of heating the building are diminished. Reducing the building’s negative environmental impact is also crucial. This article presents programs that subsidize thermal modernization investments for single-family buildings in Poland. Particular attention was paid to the Clean Air program. A methodology for the economic and ecological assessment of thermal modernization investments eligible for funding under this program was proposed. The methodology is based on the Net Present Value indicator, whereas the ecological analysis utilized the Life Cycle Assessment method. A case study was conducted for a model single-family building using the introduced methodology. The scope of the thermal modernization investment included replacing windows and doors, replacing the heat source, and thermal insulation of the vertical external walls. The analyzed thermal modernization investment brings substantial ecological benefits, significantly reducing the building’s negative environmental impact. Unfortunately, the economic viability for the investor is not so obvious and depends primarily on the level of subsidy. Full article

The quality of human capital is pivotal to the promotion of economic growth and development. In this regard, the quality of education and of academic, practice-based research systems plays a crucial role. The authors conducted an analysis of the systemic framework for financing higher education and science in Poland, with a particular focus on the economic and financial situation of the 21 largest Polish universities from 2019 to 2024. In order to assess whether the current financial basis of these entities facilitates conducting research, bridges the gap between academia and industry, and thus supports their sustainable development, a taxonomic composite indicator and cluster analysis were employed. The results obtained indicated unfavourable trends in the domain of higher education and research and development (R&D) activity among Polish universities. These include, in particular, the exceeding of operating costs over operating revenues, the deterioration of financial results, insufficient funding from the state budget in relation to the scale of operations, and relatively high volatility of the economic and financial situation in subsequent years. Full article

To achieve the “dual carbon” goals, green construction technologies (GCTs) are in transition from pilot projects to full-scale promotion in the Chengdu–Chongqing Economic Circle. Previous studies have largely overlooked the quantitative analysis of parameters influencing stakeholder decision-making and the consideration of risk preferences in the process of GCTs of application. Based on evolutionary game and prospect theory, this study establishes a tripartite evolutionary game model involving the government, owners, and constructors. Through model derivation and numerical simulation, it analyzes the strategic evolution and parameter sensitivity of each stakeholder at different lifecycle phases of GCTs. Results uncover a three-stage path: strategy adjustment range, fast convergence range, and slow convergence range. Government funds achieve peak efficiency in the fast convergence range. Owners react most strongly to incentives, contractors to cost changes. State-owned enterprises rely on policy signals, whereas private enterprises focus on market returns and risk expectations. Targeted promotion mechanisms and policy recommendations are proposed, offering a theoretical basis and practical route for precise government intervention and low-carbon transformation of the construction industry. Full article

The rising deployment of artificial intelligence in public services is constrained by computational costs and limited domain-specific data, particularly in multilingual contexts. This study proposes a generalizable Agentic AI pipeline for developing question–answer chatbot systems using small language models (SLMs), demonstrated through a case study on the Thai Student Loan Fund (TSLF). The pipeline integrates four stages: OCR-based document digitization using Typhoon2-3B, agentic question–answer dataset construction via a clean–check–plan–generate (CCPG) workflow, parameter-efficient fine-tuning with QLoRA on Typhoon2-1B and Typhoon2-3B models, and retrieval-augmented generation (RAG) for source-grounded responses. Evaluation using BERTScore and CondBERT confirmed high semantic consistency (F_BERT = 0.9807) and stylistic reliability (F_BERT = 0.9839) of the generated QA corpus. Fine-tuning improved the 1B model’s domain alignment (F_BERT: 0.8593 → 0.8641), while RAG integration further enhanced factual grounding (F_BERT = 0.8707) and citation transparency. Cross-validation with GPT-5 and Gemini 2.5 Pro demonstrated dataset transferability and reliability. The results establish that Agentic AI combined with SLMs offers a cost-effective, interpretable, and scalable framework for automating bilingual advisory services in resource-constrained government and educational institutions. Full article

High-risk human papillomavirus (HPV), including types 16–18, is the established cause of cervical intraepithelial neoplasia (CIN) and invasive carcinoma of the cervix. While preventive vaccination is highly effective in preventing infection from becoming reconstituted following treatment of existing disease, its use among cervical intraepithelial neoplasia (CIN)-positive females has remained sporadic. The following review provides an update on the current state of evidence about the acceptance, awareness, or perception of HPV vaccination by women following a diagnosis or treatment of CIN. Methods: A narrative synthesis of literature from the publication period of 2010 to 2025 was performed on PubMed, Scopus, and Google Scholar. Surveys that quantified literature on post-CIN vaccination attitudes, risk perceptions, or behavioral factors were considered. Results: Acceptance levels varied from 20–95% across all continents. The highest acceptance levels (≥80%) among the populations belong to the European and Oceanian groups, followed by moderate acceptance among the North Americans (60–80%), which was influenced by financial costs, misconceptions, and sociocultural stigmas. Several systemic-level features in Europe and Oceania have been shown to be consistently associated across these regions with high acceptance rates. These features include public funding of HPV vaccine delivery universally in these regions and reminder and recall systems established in their electronic health records. In these two regions, provider recommendation demonstrates particular significance because there is follow-up care after treatment of CIN. In these regions, mass awareness about HPV conducted in conjunction with their cervical screening programs increases baseline knowledge and favorability towards HPV vaccination. The lowest levels (20–70%) of awareness of HPV diseases and vaccination programs among Asians and Africans can be attributed to obstacles that include misconceptions about fertility concerns. In the case of Asia, there are various socially ingrained stigma factors that contribute to the poor awareness and acceptance levels. These factors include the possibility of being perceived as promiscuous, embarrassment linked to STI conditions, as well as the possibility of rejection from partners and in-laws. In particular regions, there might be stigmas attached to HPV vaccination that cause tension within married women who perceive the vaccine as an indicator of being unfaithful. Also, distrust from the general community has been driven by past incidents, including the halting of proactive HPV vaccine recommendations in Japan in 2013. Moreover, there are numerous myths concerning infertility and menstruation linked to poor vaccine acceptance. The key determinant of acceptance levels was physician endorsement, lack of knowledge of the association of HPV-CIN, or the belief that there is no need for vaccination after treatment. Conclusion: The acceptance of HPV vaccination among women following CIN is influenced by educational level, the structure of the healthcare system, and sociocultural factors. Incorporating evidence-based cervical vaccination counseling into follow-up care after biopsy could help increase its acceptance and prevent recurrent high-grade lesions. Full article