Search Results (294)

Overpressure prediction is critical for safe and efficient drilling, yet remains challenging in complex basins with multiple genetic mechanisms. This study systematically investigates the overpressure origins in the Xihu Sag, East China Sea, a prolific hydrocarbon-bearing sag with widespread overpressure and complex pressure regimes. By integrating well logging data and direct pore pressure measurements from nine wells across three major structural units, the Western Slope Belt, the Western Sub-sag and the Central Inversion Belt, a multi-method diagnostic framework is employed. This combines Bowers’ effective stress analysis with sonic-density cross-plots to discriminate between loading and unloading mechanisms. Results show obvious vertical zoning of pore pressure—normal-pressure zone, overpressure zone, and pressure reversal zone—with distinct horizontal heterogeneity. Results reveal a distinct spatial differentiation in dominant overpressure mechanisms. In the Western Slope Belt, overpressure in the deep Pinghu Formation primarily results from a composite of undercompaction (creating initial pressure seals) and subsequent hydrocarbon generation-induced fluid expansion. In contrast, in the Central Inversion Belt and Western Sub-sag, overpressure is predominantly driven by hydrocarbon charging along faults coupled with tectonic compression, with minimal undercompaction signatures. Previous studies on overpressure genesis in the Xihu Sag have largely focused on the Western Slope Belt. This study expands the analytical scope to the Western Sub-sag and Central Inversion Belt, and conducts a systematic comparative analysis of overpressure genesis across multiple tectonic units. The value of this work lies in the systematic application of classical diagnostic methods to fill the regional research gap regarding the overpressure characteristics of the Huagang Formation and the composite nature of overpressure. With accurately constrained genetic mechanisms, the findings can provide support for optimized drilling fluid design and wellbore stability management, and effectively mitigate deep hydrocarbon exploration risks in this sag and analogous overpressured basins. Full article

Stresses of climate change, urbanization, and segregation make the City of Norfolk in Virginia’s Tidewater region a fitting context for qualitative research into coastal resilience, urban nature, and residents’ perceptions of the environment. Dissertation research into sea level rise and urban development provided a rich environment for developing a practical multi-method system for community-engaged investigations of flooding effects, gentrification, and the loss of urban nature. Multi-method research illuminates social, racial, and economic dynamics in Norfolk residents through participant observation, archival research, semi-structured interviews, and walking interviews. The data generated by archival content analysis and semi-structured interviews can offer insights into citizens’ roles and experiences regarding climate change, urban development and redevelopment, and distressed nature in the city. Innovative use of participant observation and the walking interview can engage with questions of respondents’ personal beliefs about nature and the city, highlighting new possible applications of these methods. This research adds to the literature on the effects of climate change and displacement in Norfolk’s planning policies. It supersedes discussions of the mechanics of climate change to assess a range of residents’ perceptions on their own terms. The article provides a clear framework for engaging with residents around issues on climate, urbanization, and environmental stress. It therefore offers a methodological contribution to the field of qualitative research in coastal climate change science and the human experience of the dynamic, modern city. The article’s findings and methods may not be applicable in rural areas or in areas which are not facing acute climate change. Full article

This systematic review investigates the application of artificial intelligence (AI) and machine learning (ML) in journalism and media practice from 2020 to 2026. Following PRISMA guidelines, we analysed 121 peer-reviewed articles from Scopus and Web of Science using a multi-method approach that combined qualitative thematic analysis, structural topic modelling (STM), and bibliometric network analysis. Four primary research domains emerged: news production and automation (38.0%), audience perception and content analysis (24.8%), ethical and legal considerations (19.8%), and meta-research and implementation studies (17.4%). Publication output accelerated sharply from 2023 onward, driven by the emergence of large language models and generative AI. The STM analysis confirmed the four-domain structure and revealed that legal-regulatory vocabulary pervades the literature across all categories, indicating a field-wide preoccupation with the institutional implications of AI. Key findings demonstrate that successful AI adoption depends on workflow redesign and human–machine collaboration rather than full automation; that audience evaluations of AI-generated content vary significantly across cultural contexts, with the machine heuristic—originating from Sundar’s MAIN model—playing a central mediating role; and that copyright frameworks for AI-generated news remain contested across jurisdictions. This study develops an integrated theoretical framework that maps directional relationships among the four research domains, identifies cultural context and disclosure practices as key moderators, and generates testable propositions for future investigation. Full article

Trophoblast retrieval from the cervix (TRIC) is a non-invasive approach that enables access to fetal-derived extravillous trophoblast (EVT) cells as early as the first trimester of pregnancy, offering a unique opportunity for early placental and fetal assessment. Although TRIC has been reported to be feasible between 5 and 20 weeks of gestation, systematic evaluation of EVT recovery across early gestation using complementary analytical approaches remains limited. This study aimed to provide a multi-method assessment of EVT recovery across early gestation. Endocervical samples were collected from 53 pregnant women between 5 and 19 weeks of gestation. EVT cells were isolated by immunomagnetic separation using human leukocyte antigen-G (HLA-G)-specific antibodies and assessed by β-hCG immunofluorescence, fluorescence in situ hybridization (FISH) and fluorescence-activated cell sorting (FACS). Immunofluorescence and FISH analyses showed no significant differences in β-hCG-positive or fetal cell proportions among gestational age groups, supporting stable TRIC-based recovery across early gestation. Exploratory FACS analyses identified HLA-G-positive trophoblast populations, including in samples obtained at 5 weeks of gestation. Because FACS analyses were performed in a subset of the cohort, these findings should be considered exploratory and require validation in larger cohort-wide studies. Overall, our findings support the feasibility of TRIC throughout early gestation and confirm the successful recovery of fetal-derived EVT cells from as early as 5 weeks of gestation. Further studies using larger cohorts and standardized quantitative approaches are required to more comprehensively characterize EVT recovery across early gestation and to optimize the application of TRIC in placental and prenatal research. Full article

Background/Objectives: Youth are increasingly engaged in mental health research, but many models remain consultative rather than participatory. We examined the Technology and Adolescent Mental Health Internship (TAMI) as an implementation-focused instrumental case study of a structured youth participatory action research internship for high school students recruited through schools serving Chicago’s West and South Sides. Methods: The case study included an embedded multimethod formative evaluation with participatory interpretation by a post-program youth advisory board (n = 8). In Year 3, 18 participants completed baseline surveys, and 16 provided matched pre–post surveys (matched survey completion = 89%). Measures included a study-developed five-item research-task self-efficacy indicator, post-program attitudes and intentions, and four open-ended items. We conducted one exploratory paired-samples t-test and an inductive descriptive content analysis. Results: In exploratory analyses, mean research-task self-efficacy scores increased from 21.8 (SD = 2.1) at baseline to 23.8 (SD = 1.4) post-program, t(15) = 4.09, p = 0.001, d_z = 1.02. Among the 15 respondents who responded to each of these post-program items, all reported being confident or very confident explaining youth mental health research, and all reported being at least somewhat likely to participate in future research, advocacy, or mental health activities. Participants described learning related to literature review, research design, ethics, data interpretation, and science communication. They recommended a longer program, additional applied practice, and more guest speakers. Conclusions: The TAMI was delivered within one program cycle and was viewed favorably by respondents. This case illustrates how youth-generated questions, adult scaffolding, collaborative interpretation, and youth co-authorship can be incorporated into a structured research internship. Larger, independent evaluations are needed to assess outcomes, sustainability, and transferability. Full article

Although smart city strategies increasingly employ emerging technologies to improve urban services, existing research often treats these technologies in isolation from broader socio-technical systems. Similarly, urban resilience scholarship conceptualises cities as complex adaptive systems but rarely integrates digital infrastructure into formal resilience frameworks. This study examined how digital technologies can be holistically integrated into urban systems to support sustainable, adaptive, and resilient smart cities. It also developed a systems-thinking–based framework to guide the governance and design of inclusive and environmentally responsive urban systems. The study was conducted using a qualitative multi-method approach combining literature review and comparative case analysis of digitally advanced cities, including Singapore, Amsterdam, Wuhan, Copenhagen, Barcelona, and cities in Karnataka, India. The findings indicate that resilience depends less on the scale of technological deployment and more on the integration of digital infrastructure with adaptive governance, interoperability, and citizen participation. Drawing on systems thinking and system dynamics, the study proposes a digital feedback framework in which reinforcing loops enhance sensing, decision intelligence, inclusivity, and sustainability, while balancing loops that regulate risks related to privacy, inequality, technological lock-in, and environmental rebound effects. The study contributes a systems-based framework linking smart city development with adaptive urban resilience. Full article

Artificial intelligence-integrated ‘buy now, pay later’ (BNPL) platforms are diffusing rapidly across the Middle East and North Africa (MENA), raising concerns about consumer financial vulnerability. Drawing on choice architecture, payment decoupling, and financial literacy literatures, this study examines how three platform-level features—algorithmic nudging, AI personalization intensity, and perceived ease of credit—are associated with impulsive buying tendency and downstream financial outcomes, and whether BNPL-specific financial literacy attenuates these associations. A multi-method design combined cross-sectional partial least squares structural equation modeling (N = 1247 active BNPL users in seven MENA countries) with a six-month longitudinal follow-up (N = 847, 68% retention). Algorithmic nudging was positively associated with impulsive buying tendency, which in turn was associated with elevated financial stress and longitudinal debt accumulation. The ‘loyalty trap’—a paradoxical state in which financially stressed consumers maintain high platform loyalty—is provisionally documented via piecewise longitudinal trajectories. We emphasize that this pattern is consistent with but not causally established by the present design, and we outline specific experimental and quasi-experimental research designs needed for causal identification. BNPL-specific financial literacy moderated the associations between algorithmic nudging, impulsive buying, and adverse financial outcomes, with the highest-literacy quartile exhibiting substantially attenuated debt trajectories. We discuss boundary conditions, alternative explanations, and the limits of causal inference in non-experimental panel data. Findings inform evolving BNPL regulatory frameworks in MENA, with particular relevance to nudge-transparency disclosures, contractual cooling-off periods, and credit-bureau reporting standards. Full article

Previous studies examining the link between urban health and land use have predominantly relied on qualitative or descriptive approaches, lacking comprehensive quantitative frameworks capable of systematically identifying influential factors and prioritizing interventions. This research introduces a multi-method analytical framework combining qualitative content analysis, Factor Analysis, and Importance–Performance Map Analysis (IPMA). In the first phase, MAXQDA was used to conduct qualitative content analysis and identify urban health indicators most influenced by land use. These indicators were assessed through a structured questionnaire comprising 41 items, distributed among residents of three neighborhood units within Phase 2 of Parand New Town, a rapidly growing planned settlement in the Tehran Metropolitan Area, with a minimum residency requirement of five years to ensure data reliability. Factor Analysis was employed to reduce the broader set of indicators into a smaller number of latent constructs, each reflecting a distinct dimension and forming the basis for the composite Urban Health Index. Subsequently, IPMA was applied to evaluate the importance and performance of each indicator within individual neighborhoods, enabling the identification of local intervention priorities. The findings show a substantial influence of the land use system on urban health. The second neighborhood unit, characterized by superior accessibility and a broader range of land uses, achieved the highest score of 3.062. This analytical framework offers urban planners a replicable and practical tool for identifying and prioritizing interventions that promote health-oriented and sustainable urban development. Full article

The safe disposal of spent fuel and high-level radioactive waste has become a critical bottleneck restricting the sustainable development of nuclear energy, and 3D geological modeling serves as a core technology for repository siting and safety assessment. Taking the upper member of the Lower Cretaceous Bayingobi Formation in the Tamusu area as the research object, this study focuses on sedimentary facies identification, lithofacies prediction, 3D geological modeling, and candidate site optimization. A convolutional neural network (CNN) + attention algorithm is proposed for high-precision lithofacies identification, and a Geo-CVAE-GAN model is constructed to address data sparsity and reconstruct 3D geological models. Following the workflow of single-well fine analysis, multi-method fusion prediction, and 3D geological modeling, the Sequential Indicator Simulation (SIS) algorithm is improved to build a 3D lithofacies model, and four-property parameter modeling is completed under facies control. Optimal sites are delineated via 3D spatial superimposition based on parameter thresholds. The results show that favorable mudstone layers display a dual-layer structure: stable thick layers in deep strata and thin superimposed layers in shallow strata. A preliminary total area of approximately 165 km² is identified in Preselected Sections I and II, with target intervals at a 400–800 m depth, mud content exceeding 75%, and excellent physical properties, including low porosity, low permeability, and low water saturation. This study reveals the spatial distribution of favorable mudstone in the Tamusu area, and the preferred zones fully meet the siting criteria for high-level radioactive waste repositories, providing a reliable geological basis and technical support for subsequent exploration and engineering design. Full article

The unprecedented rate of technological advances, accelerated industry disruptions and social and environmental sustainability crises require very different business organizations from the traditional paradigm. The main research question for this paper is: What change (paradigm shift) is needed for South African business organizations to be future-fit? The paper introduces an integrated, transdisciplinary paradigmatic model of an emerging, progressive future business organization in South Africa, as mostly influenced by Western futurists, and proposes an understanding of the paradigm shift required in our socially constructed reality for such organizations to emerge. A multi-method methodology, based on complexity theory and a transdisciplinary approach, was developed and applied. The researcher’s conceptualization of a ‘paradigm’, focusing on language-based representations, is explicated as a theoretical foundation. Textual analyses, including corpus linguistics, of practitioner-focused literature were used to elicit concept maps (or domain models) of the shared, societal-level mental models of a South African business organization for two periods: (1) the Traditional Business Organization, and (2) a Progressive Future Business Organization. The outcomes were compared using a novel qualitative method, resulting in a proposed set of societal-level ontological shifts needed for a progressive organizational future. The study shows a paradigm shift to complexity and social responsibility, and the need for transdisciplinarity to reflect complex, integrated organizational realities. Full article

The relationship between environmental, social and governance (ESG) performance and corporate financial performance (CFP) remains an open question, particularly in capital-intensive sectors exposed to regulatory pressures and long-term transition costs. This study analyses the relationship between ESG ratings and financial performance using accounting data from 59 listed European energy companies over the period 2014–2023. ESG ratings were obtained from standardised sustainability scores available on Yahoo Finance and are therefore used as proxies for corporate sustainability performance. Financial data were extracted from Orbis Europe Full. The empirical design adopts an exploratory multi-method approach combining correlation analysis, multiple linear regression (OLS) and structural equation modelling (SEM). In the SEM model specification, ROE, ROA and ROCE are modelled as reflective indicators of a latent construct termed ‘economic performance’, whilst financial leverage is treated as a distinct observed variable representing firms’ financing structure. The results show that traditional linear models have limited explanatory power in explaining ESG ratings. The SEM analysis indicates that the latent construct of economic performance has a positive but statistically insignificant association with ESG ratings, whilst financial leverage shows a marginally significant positive association. Factor loadings confirm that ROE, ROA and ROCE consistently represent the common dimension of economic performance. Overall, the results suggest that ESG ratings in the European energy sector are explained not solely by short-term accounting profitability but also by broader strategic, organisational, governance, and financing conditions. The study contributes to research on the ESG-CFP relationship by proposing an exploratory structural equation modelling approach to modelling economic performance as a latent accounting construct. It offers food for thought for managers and policymakers evaluating sustainability strategies in capital-intensive transition contexts. Full article

The research scope comprises the analysis of disjunctions between photographic representations, architectural landmarks, tourist icons, and urbanized surroundings. Given the problem posed by imagery distortions in human cognition, the guiding hypothesis is that the perception of scenes of constructed touristic attractions is distorted with respect to their associated built vicinities. Therefore, the general objective is to systematize guidelines for integrating public policies on visual communication and urban management. Using multi-method, applied, qualitative–quantitative, and exploratory approaches, an investigation is conducted in four main parts: a literature review highlighting knowledge gaps on the topic; procedural methods involving the selection of study areas (cities) and objects (architectures) from those most visited worldwide in the pre-pandemic period followed by submitting their representative photographs for interpretation by experts and the public; analysis involving interpreting respondents’ feedback in association with specific criteria; and an integrated discussion leading to the formulation of directives. As a synthesis of the answers to the research question, the results diagnose a misrepresentation of the immediate and nearby surroundings of architectural sites due to the exclusive observation of images published on official tourism websites, confirming the proposed hypothesis and concluding that the methodological essay is feasible, with case-specific adaptations, as a reference for adequately conveying touristic landscapes in contemporary cities. Full article

This study examines how the concept of academic success is constructed and represented both in international scientific literature and in the perceptions of higher education students, using the OPSA 2.0 project at the Polytechnic University of Leiria as a case study. Adopting an exploratory multimethod approach, the research combines bibliometric analysis of publications indexed in Scopus (2020–2025) with qualitative content analysis of students’ responses collected through participatory workshops. The bibliometric results reveal that academic success is increasingly conceptualised as a multidimensional construct, structured around institutional, pedagogical, psychological, and identity-related dimensions. However, the analysis of students’ perceptions shows a predominance of instrumental and performance-oriented representations, particularly associated with grades, course completion, and employability. At the same time, emerging references to well-being, resilience, and personal fulfilment suggest a gradual shift towards more holistic understandings of success. By articulating global research trends with local student narratives, the study highlights the coexistence of traditional and emergent conceptualisations of academic success in higher education. The findings underline the relevance of institutional strategies, such as OPSA 2.0 Project, that promote a comprehensive and preventive approach to student success. Methodologically, the study demonstrates the potential of combining bibliometric mapping with qualitative analysis to bridge macro-level scientific developments and micro-level lived experiences. Full article

Landscape Visual Assessment (LVA) has long examined how landscape elements influence visual perception and aesthetic response, yet the question of which elements attract attention remains underexplored in historic parks. Compared with urban parks, streetscapes, or natural landscapes, historic parks are shaped by a distinctive combination of natural features, cultural structures, and historically embedded symbolic meanings. In this study, we categorize landscape elements in historic parks into Natural Landscape Elements (NLE) and Cultural Landscape Elements (CLE), and investigate their relative visual salience in three historic parks in Beijing: Taoranting Park, the Summer Palace, and Beihai Park. We adopt a multi-method exploratory framework integrating cognitive maps, eye-tracking experiments, computational vision analysis, and GIS/UGC-based spatial analysis. The study draws on 30 cognitive maps, participant-level eye-tracking data from 30 valid participants, supplementary heatmap-based computational image analysis, and large-scale geotagged photo-density data. The results show that, within the exploratory sample, CLE were more frequently associated with strong memory impressions than NLE. In the pooled eye-tracking analysis, CLE showed higher attention scores overall, but this pattern was not stable across all parks and was strongly context-dependent. The computational and spatial analyses further suggest that attention distribution is influenced not only by the presence of specific elements, but also by color contrast, the spatial coupling of CLE and NLE, and the broader organization of park scenes and visitor activity zones. Rather than proposing a universal model of visual attention in historic parks, this study offers an exploratory, context-sensitive account of how cultural and natural landscape elements jointly shape attention across perceptual and spatial scales. The findings contribute to landscape visual assessment research by extending it into the specific setting of historic parks and by demonstrating the value of combining perceptual, computational, and spatial methods in a complementary framework. Full article

The study applies a multiphase, multimethod research approach based on participatory methodology. It integrates the perspectives of professionals from the tourism and hospitality industry and academic experts with the aim of developing an integrated conceptual model of the influence of AI and IoT technologies on work processes, skill development, and job attractiveness in the industry. The research provides a comprehensive understanding of how digital technologies indirectly shape employment through changes in work organization and the development of transferable digital and socio-emotional skills. The paper aims to contribute to redefining the perception of work in tourism and hospitality by emphasizing the sector not only as a career choice, but also as a platform for acquiring skills transferable to other industries. The findings revealed that employees’ intentions to enter or remain in the industry are not directly influenced by AI and IoT technologies; rather, these effects are mediated through changes in work processes and, more importantly, through skill development. The study contributes theoretically by developing and empirically validating an integrated conceptual model that connects technology implementation, work transformation, skill development, and employment outcomes. From a practical perspective, the results highlight the importance of human-centered implementation strategies based on training, communication, and employee inclusion in order to maximize the benefits of digital technologies. Full article