Small-molecule donor:polymer acceptor (SMD:PA) organic solar cells have garnered attention due to their excellent active layer stability, yet their efficiency remains significantly lower than other OSC types. This study addresses the challenge of morphology control in SMD:PA systems via a layer-by-layer (LBL) process to optimize the donor–acceptor interpenetrating network. Using small-molecule donor B1 and polymer acceptor PY-IT with chloroform as a universal solvent, we systematically investigated the impact of LBL processing on the active layer morphology and device performance. The inverted LBL device (ITO/ZnO/PY-IT/B1/MoO3/Ag) achieved a power conversion efficiency of 8.6%, significantly outperforming the bulk heterojunction devices (inverted 2.91% and normal 6.11%) and previously reported LBL SMD:PA cells (1.12%). Static and femtosecond transient absorption spectra, time-resolved photoluminescence, and grazing incidence X-ray diffraction analyses revealed that the LBL and nonorthogonal solvent strategy facilitated effective B1 infiltration into the PY-IT layer, forming an optimized active layer with refined phase separation and improved donor/acceptor interfaces, thus resulting in enhanced exciton dissociation and charge transport while reducing recombination losses. This work validates the feasibility of LBL processing for high-efficiency SMD:PA OSCs, offering a novel strategy to overcome the efficiency limitations of this class of OSCs.

In applications requiring uncertain, imprecise, and multi-dimensional data, where traditional distance measures frequently fall short of capturing the full complexity of interactions among elements, a distance measure for complex intuitionistic fuzzy sets (DMCIFSs) becomes essential. Although DMCIFSs have been developed, most of them do not account for the hesitation degree, which is crucial for capturing ambiguity and uncertainty in human reasoning. As extensions of the normalized Hamming and Euclidean distance measures, this work proposes two new measures namely the Hesitance DMCIFSs (HDMCIFSs) and the Euclidean Hesitance DMCIFSs (EHDMCIFSs). These newly proposed measures provide a more comprehensive framework for modeling uncertainty by explicitly incorporating the hesitancy component. In addition to the proposed measures, several fundamental procedures and theoretical results are also presented. Furthermore, a novel decision-making method utilizing these distance measures is developed and applied to multi-criteria decision-making (MCDM) problems. The effectiveness of the proposed methods is demonstrated through a comparative study, highlighting their potential for improved sensitivity and accuracy in practical decision-making scenarios.

The genus Ovobates (Oribatida, Oribatulidae) comprises two species distributed in the Oriental region. A new species— Ovobates ochrocarpicus sp. nov.—is described, based on adult and nymphal instars, collected from branches of the ochrocarp tree in southern Vietnam. The adult of the new species is characterized by the presence of the five pairs of notogastral porose areas and the epimeral formula 3-1-3-3. The nymphs of the new species are characterized by presence of clavate bothridial seta; setiform interlamellar seta; short, setiform, thin gastronotic setae c1, c2, da, la; medium-sized to long, setiform, gastronotic setae dm c3, lm, p2, and p3; medium-sized, bacilliform gastronotic setae dp, h1, and h3; long, subflagellate, gastronotic setae lp, h2, and p1; epimeral formula 3-1-2-2 in tritonymph; and seven setae on the leg tarsus IV in protonymph. The generic diagnosis and a morphological comparison of adults and juvenile instars of the known species of Ovobates are presented.

Forest fires are gaining attention as a climate issue because they release greenhouse gases—mainly CO2—and because the forests that burn lose their ability to store carbon. In Hungary, the direct CO2 emissions from forest fires make up only about 0.29% of the country’s yearly emissions, but they still matter in the bigger climate picture. However, the long-term cumulative impact, the high emission rate per hectare and the resulting reduction in CO2 removal capacity are strategically important issues in achieving the 2050 climate neutrality goals. This research fills a research gap. It provides a quantitative analysis of forest fire emissions and removal losses using data from the European Forest Fire Information System (EFFIS) and national forestry statistics. The total CO2-related climate burden is projected to be approximately 4,300 kt by 2050. Despite modest absolute values, forest fires represent an under-recognized but growing risk in national climate planning. The results support the need for long-term policy integration of fire mitigation, afforestation and forest management strategies. This study provides a replicable methodology and practical knowledge for shaping climate policy in smaller EU Member States.

The quality of research has become a crucial measure of quality, impactful and innovative scientific results in the contemporary knowledge-based age. This paper gives an in-depth examination of research tools, techniques, applications, and solutions that help in the realization of research excellence. The systematic literature review and bibliometric methodology were used, however, with the help of the Dimensions.ai database, where 705 relevant articles were identified after inclusion and exclusion criteria were followed. The research analyzes quantitative, qualitative, mixed-method, and bibliometric methods, as well as sophisticated digital applications and AI-related methodologies. The results show that the volume of research and citations has increased especially since 2020, which is evidence of the growing importance of data analytics, cross-disciplinary teamwork, and open science practices. Moreover, the paper determines the major challenges, such as the dependency on the metric, resource constraints, and complexity of the methods. This paper suggests a merged system of tools, methodologies and ethical practices that can improve the quality of research, its visibility and impact on society and provides good knowledge to researchers, institutions, and policymakers.

Background: Entrepreneurial education (EE) and institutional support mechanisms such as Business Incubation Programmes (BIPs) play critical roles in shaping entrepreneurial intentions among university students. However, in Bangladesh, the relationship between EE, BIPs, and Entrepreneurial Intention (EI) remains underexplored, particularly from the perspective of resource-based and behavioural theories. Objective: Grounded in the Theory of Planned Behaviour (TPB) and drawing on the Resource-Based View (RBV), this study examines the role of BIPs in amplifying the impact of EE on EI among business students in Bangladeshi universities. Methodology: The study employed a quantitative research design, utilising a structured questionnaire administered to 388 business students from four leading universities in Dhaka. Data were analysed using SmartPLS 4.1.0.9 and SPSS 27 to test the proposed model and hypotheses. Results: The findings reveal that EE and BIP have a positive and significant influence on EI. Moreover, BIP substantially moderates the relationship between EE and EI, indicating that incubation programmes strengthen the effect of educational inputs on students’ entrepreneurial intentions. Conclusion: Integrating entrepreneurial education with institutional support mechanisms such as incubation programmes fosters a stronger entrepreneurial mindset and intention among students. Unique contribution: This study enriches entrepreneurship literature by integrating TPB and RBV perspectives to explain how cognitive and resource-based factors jointly shape entrepreneurial intention in an emerging South Asian economy. It also provides practical implications for educators, policymakers, and ecosystem stakeholders seeking to address graduate unemployment through entrepreneurship development. Key Recommendation: Universities should integrate business incubation Programmes with entrepreneurship education to provide practical support and enhance students’ entrepreneurial readiness.

Background: The adoption of technology in the tourism industry has become a worldwide trend aimed at enhancing effectiveness and efficiency in this sector. Objectives: This study investigates the drivers influencing e-tourism adoption in Bangladesh by extending the Unified Theory of Acceptance and Use of Technology (UTAUT) model with the addition of digital literacy and vacation packages. Methodology: This research proposes and tests a conceptual model grounded in complexity and configuration theory. We employ a mixed-method analytical approach, integrating Fuzzy-Set Qualitative Comparative Analysis (fsQCA) as a complementary tool to Structural Equation Modelling (SEM). Empirical validation was conducted using data from 297 online tourists. Results: Structural Equation Modelling (SEM) revealed that e-tourism adoption intention was significantly influenced by vacation packages, effort expectancy, performance expectancy, facilitating conditions, and digital literacy, whereas social influence did not show a significant effect. Furthermore, Fuzzy-Set Qualitative Comparative Analysis (fsQCA) identified five sufficient configurations of these causal conditions that lead to high levels of e-tourism adoption. Conclusion: The findings confirm the primary drivers of e-tourism adoption in Bangladesh and identify five specific, high-adoption pathways. Practically, these results enable e-tourism service providers and policymakers to strategically allocate resources, optimise platform design, and implement targeted digital literacy initiatives to accelerate e-tourism adoption rates in the region. Unique Contribution: This research provides a significant methodological advancement by integrating SEM and fsQCA to move beyond testing net effects and establish a detailed, configurational understanding of e-tourism adoption. Theoretically, it extends the UTAUT model by identifying new context-specific causal conditions relevant to travellers in Bangladesh. Key Recommendation: It is suggested that online travel service providers, marketers, and digital platform executives utilise the detailed findings of this study. Specifically, they should consider developing and implementing strategies that focus on optimising the five sufficient causal configurations identified by fsQCA and prioritise investments in the factors (e.g., performance expectancy, digital literacy) that significantly influence e-tourism adoption among Bangladeshi travellers.

Background Violence against women and against children are human rights violations with lasting harms to survivors and societies at large. Intimate partner violence (IPV) and sexual violence against children (SVAC) are two major forms of such abuse. Despite their wide-reaching effects on individual and community health, these risk factors have not been adequately prioritised as key drivers of global health burden. Comprehensive x§and reliable estimates of the comparative health burden of IPV and SVAC are urgently needed to inform investments in prevention and support for survivors at both national and global levels. Methods We estimated the prevalence and attributable burden of IPV among females and SVAC among males and females for 204 countries and territories, by age and sex, from 1990 to 2023, as part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2023. We searched several global databases for data on self-reported exposure to IPV and SVAC and undertook a systematic review to identify the health outcomes associated with each of these risk factors. We modelled IPV and SVAC prevalence using spatiotemporal Gaussian process regression, applying data adjustments to account for measurement heterogeneity. We employed burden-of-proof methodology to estimate relative risks for outcomes associated with IPV and SVAC. These estimates informed the calculation of population attributable fractions, which were then used to quantify disability-adjusted life-years (DALYs) attributable to each risk factor. Findings Globally, in 2023, we estimated that 608 million (95% uncertainty interval 518–724) females aged 15 years and older had ever been exposed to IPV, and 1·01 billion (0·764–1·48) individuals aged 15 years and older had experienced sexual violence during childhood. 18·5 million (8·74–30·0) DALYs were attributed to IPV among females and 32·2 million (16·4–52·5) DALYs were attributed to SVAC among males and females in 2023. IPV and SVAC were among the top contributors to the global disease burden in 2023, particularly among females aged 15–49 years, ranking as the fourth and fifth leading risk factors, respectively, for DALYs in this group. Among the eight health outcomes found to be associated with IPV, anxiety disorders and major depressive disorder were the leading causes of IPV-attributed DALYs, accounting for 5·43 million (–1·25 to 14·6) and 3·96 million (1·71 to 6·92) DALYs in 2023, respectively. SVAC was associated with 14 health outcomes, including mental health disorder, substance use disorder, and chronic and infectious disease outcomes. Self-harm and schizophrenia were the leading causes of SVAC-attributed burden, with SVAC accounting for 6·71 million (2·00 to 12·7) DALYs due to self-harm and 4·15 million (–1·92 to 13·1) DALYs due to schizophrenia in 2023. Interpretation IPV and SVAC are substantial contributors to global health burden, and their health consequences span a variety of individual health outcomes. Importantly, mental health disorders account for the greatest share of disease burden among survivors. Investing in prevention of these avoidable risk factors has the potential to avert millions of DALYs and considerable premature mortality each year. Our findings represent strong evidence for global and national leaders to elevate IPV and SVAC among public health priorities. Sustained investments are needed to prevent IPV and SVAC and to implement interventions focused on supporting the complex social and health needs of survivors. Funding Gates Foundation.

This research develops and assesses a model based on capabilities that explains how platform-based open innovation networks enhance sustainability through sequential mediation processes. By relying on concepts of reflexive innovation, ecosystem learning, and knowledge co-creation, the research shows that participation in platforms enhances the maturity of the circular learning ecosystems; therefore, promoting collaborative reflexive practice. Reflexivity leads to two outcomes: (a) an individual-level increase in circular literacy, which implies an increase in knowledge, skills, and behavioral orientation to circularity, and (b) system-level sustainable platform-based innovation outcomes, comprising the social and environmental impacts of the innovational processes. The outcomes endorse the proposed mediation directions. Interestingly, the digital inclusivity orientation was not associated with the reflexivity-literacy relationship, signifying that inclusion requires a deeper organizational integration in order to generate high capability impacts. The study enhances the literature on circular economy and innovation by introducing the concepts of reflexivity and circular literacy as the strategic abilities of a company and providing managers and policymakers with insights on how to build inclusive and sustainability-oriented platform ecosystems.