Approaches used to model patient and carer health-related quality of life in economic models of rare disease treatments in NICE appraisals.

Waqf is a strategic Islamic social finance instrument that supports socio?economic development, particularly through productive waqf and waqf?based entrepreneurship (wakafpreneurship) models. In Malay communities, the economic thought of Tenas Effendy in Tunjuk Ajar Melayu offers a strong ethical and cultural foundation that has not yet been systematically integrated into waqf?based economic empowerment models. This article aims to formulate a conceptual model of Malay community economic empowerment based on wakafpreneurship rooted in Malay Islamic cultural values. The study employs a qualitative, conceptual approach through a literature review of productive waqf and Islamic social finance, waqf?based entrepreneurship and economic empowerment, and studies on Tunjuk Ajar Melayu and Tenas Effendy’s thought. The analysis involves literature selection, thematic coding, and conceptual synthesis oriented toward developing a model compatible with Partial Least Squares Structural Equation Modeling (PLS?SEM). The findings indicate that values such as trustworthiness, justice, social solidarity, and balance between worldly and hereafter benefits can be crystallized into the Malay Islamic Cultural Values (MICV) construct, which conceptually influences waqf literacy, wakafpreneur orientation, and waqf governance. The article proposes six reflective latent constructs MICV, Waqf Literacy, Wakafpreneur Orientation, Waqf Governance, Community Economic Empowerment, and Social Welfare as an initial framework for future empirical testing in Malay communities.

ABSTRACT Heralded as a pivotal move toward a low-carbon economy, Quebec’s sustainable mobility plan requires extensive mining projects and the construction of new hydroelectric dams, raising concerns about the feasibility and sustainability of the plan. This article employs a historical lens, examining Quebec’s economic model and hydroelectric infrastructure since the 1960s, to critically examine how green energy policies align with the province’s extractivism. Quebec’s green transition enhances the province’s resource nationalism, seen in three successive waves: nationalizing energy, liberalizing energy, and ‘greening’ energy. With every successive wave, resource nationalism entrenches its dependence on the growth of energy production. Quebec’s case study demonstrates that sustainable policies are rooted in a fundamental drive to growth and state-building, rather than a shift to a low-carbon economy.

The presented scientific research is relevant since it contains new information on the impact of the key rate of the Central Bank of the Russian Federation on the consumer price index in Russia. The purpose of the scientific work is to establish the relationship between the consumer price index in the domestic economy and the key rate of the Central Bank of the Russian Federation together with other external economic factors. In accordance with the stated goal, the following tasks were solved: the theoretical foundations of the monetary policy of central banks were considered; the corresponding research methodology was developed; economic and mathematical models with the function of forecasting the consumer price index in Russia depending on the key rate of the Central Bank of the Russian Federation and other external economic factors were built; shortcomings and directions of the monetary policy of the Bank of Russia were determined. The following scientific methods were used: analysis, synthesis, centered moving average method, ADF test, KPSS test, correlation and regression analysis, Koyk method. The scientific novelty of the study lies in the creation of principles that adjust the monetary policy of the Central Bank of the Russian Federation in modern conditions.

A systematic review of modeling approaches to evaluate diagnostics programs for stable coronary heart disease: suggestions for future health economic models.

The crisis of macroeconomic paradigms and core transformations of economic models bring to the fore the need for a reflection on the origins of the theoretical ideas about the regularities of economic development. The paper delves into the evolution of scientific ideas related to regional economics as an independent area of economic scholarship by providing a retrospective view of economic research within the Urals’ space. Based on the principal thrusts of the evolutionary-heuristic paradigm, the study particularly focuses on the origins of regional economic research and scholars’ contribution into the formation of scientific ideas about the Ural economy. The method of the study is a summarizing review of the literature coupled with comparative and historical analysis. The findings demonstrate that during the USSR period, regional research developed markedly – the soviet scholars promoted the theory and practice of long-term planning, justified the methodology of territorial-production complexes, investigated the problems of rational location of productive forces in the Urals. During the pre-war years, the state restored the awarding of academic degrees, including in economic sciences, which also stimulated the development of this scientific field. Regional economics as a new scientific discipline grew roots in the Ural region, extended its subject, and its research paradigm went far beyond the borders of material production and location of productive forces.

Abstract This study analyzed energy system impacts of technological carbon dioxide removal (CDR) deployment in Finland. We modeled long-term scenarios up to 2050 for four CDR technologies: bioenergy with carbon capture and storage (BECCS), biochar soil amendment, direct air carbon capture and storage (DACCS), and enhanced weathering of mining rock waste (EW). An integrated energy economic model compiled using the TIMES-model generator was used to produce cost-minimal development scenarios for Finland’s energy system, including CDR technologies. Three scenarios were modeled: one without a specific CDR target and two with low- and high CDR targets. The results show that CDR targets primarily affect the deployment of biochar, BECCS, and DACCS, whereas EW potential was fully utilized in all scenarios. Most of the growth in the CDR deployment originated from DACCS, while BECCS and biochar remained relatively insensitive to the CDR targets. The limited availability of sustainable biomass and its allocation across competing sectors played a central role in shaping the complex interactions between BECCS, biochar, and DACCS in the Finnish energy system. Regarding national net greenhouse gas (GHG) emissions, the findings indicate that the net-zero GHG target is more easily achieved under any binding CDR target than without one. However, substantial CDR deployment would still be required for Finland to achieve climate neutrality even by 2050. The impacts of CDR technologies extend more broadly throughout the energy system than shown in earlier studies due to interconnections between the energy-consuming and producing sectors.

ABSTRACT Growing awareness of unsustainable linear production, consumption and waste economic models is prompting exploration of circular economy and bioeconomy models. The ‘circular bioeconomy’, sitting at the nexus of these concepts, is of particular importance to agrifood systems, which play a critical role in producing biologically based materials and services, and converting waste streams into safe and sustainable resources. A systematic mapping protocol was applied to develop a broad overview of ‘circular bioeconomy’ research in Australian and New Zealand agrifood systems. Sixty‐nine full‐text publications were coded to catalogue studies by domain, methodology, and categories of inputs, technologies and products (for biophysical studies). The circular bioeconomy is an emerging research area, currently experiencing inconsistent definitions of key terms, a high proportion of review papers, and limited engagement with key concepts in certain research areas. There were key differences between Australian and New Zealand research, particularly in terms of science domain, research methodology and dominant perspectives on key circular economy and bioeconomy principles. Recommendations for future studies include standardising circular bioeconomy definitions, increasing social science applications, mapping potential circular bioeconomy assessment tools, and applying circular bioeconomy principles and guidelines to develop cross‐sectoral strategies. Coordinated research efforts can support circular bioeconomy approaches for sustainable agrifood systems in Australia and New Zealand.

The purpose of the article is to conduct a comprehensive analysis of the current state of the domestic machine-building complex, due to complex well-known geopolitical conditions and a number of internal systemic problems hindering the development of the domestic real economy and the social sphere. Russia is steadily moving towards technological renewal and achieving technological leadership, as well as increasing the efficiency of the domestic machine-building industry, meeting the modern requirements of an innovative economic model. The success of the implementation of the technological program of modern Russian engineering in the future is determined by solving a number of problems, which will require a large-scale mobilization of the country's resource potential.

ABSTRACT Motivated by the dynamic interdependence of global economic cycles, this study proposes a dual-market economic condition-based model switching (DMEC-MS) method. The method aims to enhance the predictive ability of economic policy uncertainty (EPU) for stock market volatility by incorporating evolving dual-market economic scenarios. In this method, we introduce a new international-domestic economic condition (IDEC) proxy to measure different dual-market economic scenarios. The core mechanism of the DMEC-MS method is to capture the time-varying relationship between EPU and volatility based on the proposed IDEC. The method employs a model selection procedure to extract specific IDEC scenarios that substantially influence the EPU-volatility relationship in real time, facilitating the switch of prediction models. The empirical analysis demonstrates that the DMEC-MS method offers enhanced forecasting power and economic value.

Hepatocellular carcinoma (HCC) imposes a major health and economic burden worldwide, with disproportionate effects in low- and middle-income countries (LMICs). Surveillance in high-risk populations, typically using semiannual ultrasound and alpha-fetoprotein testing, has been shown to be cost-effective by enabling earlier detection and improving survival. Yet, its overall value is reduced by poor adherence and the limited sensitivity of ultrasound, particularly in patients with metabolic-associated steatotic liver disease. Emerging approaches-including abbreviated magnetic resonance imaging, multi-biomarker models (e.g., gender, age, AFP, AFP-L3, and DCP), and liquid biopsy assays such as methylated DNA markers-demonstrate greater diagnostic accuracy and potential economic advantages compared with conventional methods. Integration of artificial intelligence into imaging may further enhance efficiency and reduce downstream costs. Moving toward precision surveillance, guided by individualized risk stratification that incorporates etiology, fibrosis stage, and molecular profiles, can optimize allocation of resources and maximize cost-effectiveness at the population level. Interventions to improve adherence, including mailed outreach and behavioral economic incentives, have shown both clinical benefit and cost savings, underscoring the role of implementation science. Because socioeconomic disparities influence both access and outcomes, economic models must explicitly address equity to achieve sustainable impact. Future research should prioritize prospective trials that evaluate not only clinical performance but also the real-world cost-effectiveness of novel technologies and stratified surveillance strategies. For LMICs, adapting proven models into affordable, context-appropriate programs is essential. By combining prevention, precision risk assessment, innovative technologies, and equitable implementation, HCC surveillance can deliver both clinical and economic value, reducing the global burden of disease.

When developing health economic simulation models, individual-level and cohort state-transition model types are commonly used. However, heterogeneity and the extent to which it is taken into account is thought to affect simulation outcomes differently in individual-level and cohort simulations, even when model structures are identical. This study aimed to investigate the conditions under which the use of different model types may lead to different outcomes and therefore potentially different policy decisions. A microsimulation model was used to reflect an individual-level simulation, simulating patient characteristics and, artificially, a cohort-level simulation of identical patients, using the exact same model structure. Four scenarios were analyzed: heterogeneity in age (scenario 1) influencing progression and recovery probabilities when on treatment, heterogeneity in sex (scenario 2) influencing progression and recovery probabilities when on treatment, combined heterogeneity in age and sex (scenario 3) influencing progression and recovery probabilities when on treatment, and heterogeneity in age when including age-dependent all-cause mortality (scenario 4). In every scenario, heterogeneity impact was varied, and health state occupancy, incremental costs, incremental effects, and the net monetary benefit of treatment versus no treatment were compared between the individual-level and cohort simulations. When introducing heterogeneity in age, sex, and age and sex combined, all scenarios showed differences between outcomes of individual-level and cohort simulations. However, these differences did not change the cost-effectiveness conclusions. When age influenced only age-dependent mortality, there were differences between the outcomes for the individual-level and cohort simulations when heterogeneity in age was introduced. Patient heterogeneity can affect the outcomes of individual and cohort simulations differently, but reflecting more heterogeneity does not necessarily increase differences in simulation outcomes. However, age-dependent mortality affected analytic outcomes differently, suggesting a need for caution when developing cohort models if age is heterogeneous.

Forecasting hospitality revenue with economic wave models: A trigonometric approach to science and non-science labor elasticity

Multi-Time-Scale Low-Carbon optimal scheduling for Electric-Hydrogen integrated energy systems incorporating flexible Vehicle-to-Grid technology

Extract of endophytic fungus Cepalotheca foveolata (N11) inhibits lytic bacteriophage: a study on activity, cytotoxicity, and chemical profiling.

Competition law is ordinarily complex and multi-dimensional requiring detailed analysis and balancing of economic efficiencies, innovation, productivity, and consumer costs. However, competition law has an additional dimension of complexity in eras of strategic conflict as national security becomes a factor for regulators. The complexity in the era of China-US strategic rivalry is particularly acute for three reasons. One, the expanding conceptualization of national security means that security is no longer relegated solely to defence from armed attack but encompasses economic, technological, and ideological power. Two, large and strategic corporations are the leading economic actors globally, inextricably connected to economic, technological and ideological power, and therefore constitute paramount national security assets. Three, the two great powers have contrasting economic governance models. China’s distinct political-economic governance raises speculation that Chinese corporations are under the influence of a corporate parent, the Party-state, and utilized to advance Party-state objectives. This paper endeavours to outline and discuss competition law in the era of strategic conflict from a US and EU regulatory perspective and offers some pathways on analysing the issues.

The tumor and node metastasis (TNM) staging and pathological grading systems are currently insufficient for accurately predicting recurrence-free survival (RFS) in patients with pathological stage (p-stage) I lung adenocarcinoma (LUAD). Therefore, there is an urgent need for a more economical and applicable clinical prediction model to assess the risk of recurrence and guide clinical postoperative care. This retrospective study included 544 patients with p-stage I LUAD who were randomly allocated to development (272 patients) and validation (272 patients) cohorts. Cox regression and backward model selection were used to develop the prediction model. The predictive performance of the model was then compared with that of the current TNM staging system and two major pathological grading systems. The primary endpoint was RFS. A total of 79 out of 544 patients with p-stage I LUAD experienced recurrence after surgery. Four risk factors were incorporated into a weighted risk index-high-grade patterns ratio, epidermal growth factor receptor mutation status, spread through air spaces status and consolidation tumor ratio-to establish the "CEHS" RFS prediction model. This model demonstrated superior predictive accuracy compared with existing staging and grading systems. High-risk patients had significantly shorter RFS than low-risk patients did. An online algorithm based on the CEHS model was also developed. We established and validated a novel model that integrates radiological, molecular and pathological features to predict RFS in patients with p-stage I LUAD. This new model exhibited excellent discriminatory power for classifying early-stage LUAD patients at different risks of recurrence.

Technology breakthrough borders: impact of cross-border green patents on firms’ environmental performance

Economic model predictive moisture control of a horizontal fluidized bed dryer for continuous pharmaceutical manufacturing

The current linear economic model has led to the creation of low-priced and short-lived products at the cost of shaping fast and unsustainable consumption. Product repair, the process of maintaining the functionality of items by correcting a defect, should, in theory, retain product value and improve material efficiency. However, the transformation of current repair practices requires the comprehensive engagement of consumers and different business stakeholders, including manufacturers, retailers and repair service providers. In particular, the repair journey that consumers go through when deciding whether (and how) to repair an item involves a set of complex decisions and actions. This paper aims to provide a synthesis of this sequence and address the complexity of the consumer's repair journey, considering different product sectors. To achieve this aim, the research consisted of a set of consumer focus groups to gather insights into consumers' repair journeys, considering four stages: identification of product faults and repair need, information search and evaluation of alternatives, repair in action and post-repair evaluation. The paper contributes to the field by developing a holistic 'consumer repair journey' framework and presents findings on the factors that influence consumer intentions, how these intentions translate into behaviour at each stage, and overall satisfaction during the journey. Additionally, it provides guidance to industry professionals on how to implement interventions that could positively impact consumer repair intentions and their translation into behaviour. These interventions could align with companies' strategic efforts to embrace customer experience, 'right to repair' initiatives, and the growth of sustainable, repair-focused enterprises across various product industries, as advocated by the European Commission (2020) and, more recently, Right to Repair Europe (2023).