Search Results (33,204)

Digital transformation has become a central strategic priority as organizations increasingly rely on digital technologies to redesign business processes, governance structures, and value creation mechanisms in digitally evolving environments. However, existing approaches to digital transformation readiness often rely on additive maturity models or capability inventories that assume transformation capacity increases through cumulative capability development. Such approaches overlook how strategic emphasis must be distributed across transformation domains under governance and resource constraints. This study addresses this limitation by conceptualizing digital transformation readiness as a problem of strategic prioritization rather than cumulative capability accumulation. To operationalize this perspective, the study develops the Strategic Focus Index (SFI), a governance-aligned diagnostic instrument that evaluates how organizations distribute strategic attention across interdependent transformation domains. The index is constructed through a two-round Delphi study involving 53 experts from industry, academia, and the public sector, followed by statistical validation and an illustrative diagnostic application. The findings demonstrate how domain-level prioritization patterns can be systematically interpreted to identify potential imbalances in transformation efforts. By reframing readiness assessment as a prioritization-based diagnostic rather than a linear maturity measure, this study contributes a structured approach for evaluating digital transformation in digital business and platform-based environments. Full article

Monitoring dissolved carbon dioxide (CO₂) in aquatic and sediment systems is critical for understanding carbon cycling and climate feedback. This study develops and characterizes a compact, low-cost microbolometer-based attenuated total reflectance (ATR) mid-infrared sensor for direct dissolved CO₂ measurement in liquid and soil-water environments. The system integrates a ZnSe ATR crystal with custom suspended SiN membrane microbolometers and uses evanescent-wave absorption at 4.26 μm with a broadband LED source and computational spectral reconstruction, eliminating the need for an interferometer. Calibration shows excellent linearity (R² ≈ 0.99) over 50–1000 ppm CO₂, with a practical limit of detection (LOD) of ~26–35 ppm at 5–25 °C. UV-induced CO₂ generation from soil-water mixtures was investigated across UV wavelengths, revealing UV-C (254 nm) as optimal, producing net ΔCO₂ ≈ 339 ppm above ambient levels in 30 min. Environmental factors (temperature 5–35 °C, pH 5–11, pressure 1–1.5 ATM, dissolved organic carbon) were systematically evaluated, confirming robust sensor performance (accuracy >90%, correlation r > 0.98 with reference instrument). This sensor represents the first integration of MEMS microbolometer detectors with ATR evanescent-wave spectroscopy for liquid-phase dissolved CO₂, enabling real-time monitoring and rapid sediment organic carbon assessment in a field-deployable platform. Full article

The wake of artificial intelligence (AI) tools has witnessed a lot of changes at workplaces. Job crafting (JC) has also embraced the predictive quality of using AI tools such as ChatGPT. Drawing on Conservation of Resources theory, this study was conducted in is an effort to understand the role that ChatGPT plays in job crafting by enhancing work engagement (WE) in the presence of work-related curiosity (WRC). Time-lagged data from 314 employees from the information technology (IT) sector was used to test the relationship by using partial least square structural equation modeling. The results showed that ChatGPT and job crafting are linked to each other in the presence of work engagement. The results further showed that WE mediated and work-related curiosity moderated the relationship between ChatGPT and job crafting. These results are instrumental in understanding the significance of AI adoption in business and can be used as a potential tool for crafting jobs toward other work-related outcomes. The research holds significance for mangers and policymakers of the IT sector in terms of establishing AI adoption to Predict positive behaviors in employees, and it also highlights future avenues. Full article

Aiming at solving the detection problems caused by weak partial discharge signals of underground cable joints and random and variable spatial electromagnetic wave interference, a non-contact detection technology based on the dynamic multi-notch method is proposed. This technology synchronously collects pure interference signals and mixed signals containing partial discharge through a dual-position detection antenna. After converting to the frequency domain via Fast Fourier Transform (FFT), the notch frequency bands are dynamically determined based on the real-time interference spectrum, and interference suppression is achieved by frequency domain zeroing filtering. Finally, the partial discharge pulse signal is restored through Inverse Fast Fourier Transform (IFFT). A simulation experiment platform for 10 kV XLPE cable joints was built to verify the detection of typical defects such as metal debris, insulation scratches, and conductor burrs. Experimental results show that the average extraction success rate of this method for weak partial discharge signals reaches 94.7%, and the detection accuracy is ≥92.3% in a normal environment without strong interference, which is significantly better than the traditional ultra-high frequency (UHF) detection method (45.8%) and the fixed notch method (68.3%). This technology realizes the accurate detection of weak partial discharge signals in complex environments, provides a reliable solution for the early warning of insulation defects in underground cable intermediate joints, and has important engineering application value. Full article

The impact of wind on disdrometer measurements has not yet been demonstrated through controlled reproducible physical experiments. This study aims to provide quantitative evidence of the deviation in raindrop trajectories approaching the sensing area of an optical disdrometer (the Thies Clima LPM) when immersed in a wind flow with a known velocity and direction relative to the sensor orientation. To this end, water drops with diameters between 0.9 mm and 1 mm were released in a wind tunnel and directed towards the instrument’s sensing area. Their trajectories were measured using a high-speed camera and compared with those expected in undisturbed conditions, as well as with the airflow field around the instrument body as measured in previous studies. This experiment provided the first direct measurement of the deviation in individual drop trajectories induced by wind near the Thies Clima LPM, a disdrometer commonly used in hydrological studies and applications. The effect of the non-radially symmetric geometry of the instrument on wind direction was observed, identifying the configuration most affected (parallel to the laser beam). The repeatability of the drop releasing system was checked by releasing multiple drops from the same position. This allowed attributing differences in the observed trajectories to a variation in the drop diameter. The collected dataset can be used to validate numerical models of the wind-induced bias of disdrometers and to develop adjustment functions for field measurements. Full article

Background/Objectives: The clinical decision between preserving periodontally compromised teeth and replacing them with dental implants represents a complex clinical dilemma influenced by biological, prosthetic, economic, and professional factors. The aim of this pilot study was to develop and preliminarily validate a questionnaire designed to assess dentists’ attitudes and therapeutic preferences regarding the use of periodontally compromised teeth as prosthetic abutments versus extraction and implant-supported rehabilitation. Methods: An observational cross-sectional study was conducted, among Romanian dentists, using a structured self-administered questionnaire consisting of 43 items organized into seven sections addressing clinical attitudes, decision-making factors, professional competence, prosthetic treatment preferences, and implant-related clinical practices. A total of 111 Romanian dentists completed the questionnaire. Responses were recorded using a five-point Likert scale. Statistical analysis was performed using IBM SPSS Statistics software. Internal consistency was evaluated using Cronbach’s alpha coefficient and intraclass correlation coefficient (ICC). Construct validity was assessed using exploratory factor analysis based on Principal Component Analysis with Varimax rotation. Results: The questionnaire demonstrated good internal consistency across most sections, with Cronbach’s alpha values ranging between 0.795 and 0.859 after scale optimization. Item–total correlations indicated adequate contribution of individual items to overall scale reliability. Intraclass correlation coefficients confirmed moderate reliability for individual items and good reliability for average section scores. Exploratory factor analysis showed satisfactory sampling adequacy (KMO = 0.709) and statistically significant Bartlett’s test of sphericity (p < 0.001), supporting the suitability of the data for factor analysis. The sample population was predominantly composed of early-career dentists with limited clinical experience, which should be considered when interpreting the findings. Conclusions: The developed questionnaire demonstrated satisfactory psychometric properties, including good internal consistency and acceptable construct validity, supporting its use as a research instrument for assessing Romanian dentists’ self-reported attitudes, therapeutic preferences, and perception-based decision patterns regarding the preservation of periodontally compromised teeth and implant-supported prosthetic rehabilitation. Full article

Glioblastoma (GBM) is an aggressive tumor type known to recur after maximal safe surgical resection followed by concurrent radiation therapy (RT) and chemotherapy (temozolomide—TMZ), and adjuvant TMZ maintenance chemotherapy. It exhibits high intratumor heterogeneity within a single specimen, and thus clinical management remains a challenge due to its rapid progression and high recurrence rate. Machine learning algorithms are currently being implemented in biomarker discovery to develop accurate predictive models that can guide clinical decision making. Emerging evidence identifies metabolomics as a critical player in understanding tumor metabolism and progression. Machine learning computation models have been instrumental in GBM classification and biomarker discovery, as well as the evaluation of tumor staging. Metabolomic profiling of biogenic amines in the setting of surgery, chemoradiation, and understanding relapse also suggests a coordination between metabolic pathways and tumor stage. Many challenges in machine learning and metabolomics-based approaches for disease classification remain due to the dimensionality of datasets, as well as identifying more streamlined panels of metabolite biomarkers. The purpose of this review is to showcase the recent developments in the applications of machine learning in metabolomics as a promising approach to enhancing the biomarker discovery process for future classification and interpretation of patient response to therapies for GBM management in the clinical setting. It also presents the major challenges of implementing machine learning approaches in GBM management and its future directions. Full article

Background/Objectives: Financial toxicity (FT) is increasingly recognised as a critical dimension of the cancer care continuum, reflecting both objective financial burden and subjective financial distress arising from cancer-related care. Head and neck cancers (HNC) may be particularly vulnerable to FT because treatment often involves multimodal care, functional morbidity, prolonged rehabilitation, and disruption to employment. This scoping review mapped and synthesised the literature on FT in a focused subset of head and neck cancers (HNC), namely malignancies of the oral cavity, oropharynx, nasopharynx, sinonasal tract, and major and minor salivary glands. Methods: A scoping review was conducted in accordance with the methodological guidance of the Joanna Briggs Institute for scoping reviews to identify and synthesise studies addressing FT in the selected HNC subsites. Searches were undertaken in MEDLINE, Embase, Scopus, Web of Science, CINAHL, EconLit, and Global Index Medicus for English-language studies published between 1 January 2015 and 1 January 2025. The search window was restricted to this period to capture the more contemporary evolution of FT as a distinct research construct in oncology. Eligible studies included adult patients and reported patient-level FT outcomes, including direct costs, indirect costs, out-of-pocket expenditure, financial hardship, financial distress, employment disruption, or related economic strain. Findings were synthesised narratively and organised thematically. Results: Twenty-five studies published between 2015 and 2025 were included. The evidence base was dominated by cross-sectional and retrospective designs, with limited prospective follow-up and very little intervention-focused research. FT was conceptualised heterogeneously across studies, spanning direct expenditure, indirect and non-medical costs, subjective financial distress, and coping-related consequences. Questionnaire-based approaches were used in 13 studies, but only a smaller subset employed FT-specific instruments such as COST. Across the literature, FT was most commonly associated with lower income, weaker financial protection, employment disruption, rural residence in some settings, and more intensive treatment. Reported downstream associations included poorer quality of life, psychological distress, care alteration, and work-related burden, although evidence for treatment delay or survival effects was more limited and should be interpreted cautiously. Conclusions: In this focused HNC subset, FT appears multidimensional, socially patterned, and clinically relevant. However, the literature remains methodologically fragmented, with inconsistent measurement and sparse longitudinal evidence. Future work should prioritise validated and tumour-specific assessment strategies, prospective study designs, and evaluation of mitigation interventions that address both direct and indirect burden across the cancer continuum. Full article

Industrial tunnel pasteurizers are widely used for bottled liquid products because they provide a robust and continuous thermal treatment. However, operating conditions are often conservatively selected to ensure microbiological safety, which may result in excessive energy consumption and limited thermal efficiency. This study experimentally investigates the thermal behavior and energy performance of an industrial tunnel pasteurizer used for a sealed bottled herbal-based high-viscosity liquid formulation under both nominal and modified operating conditions. An instrumented bottle was developed to measure temperature evolution at different locations inside the bottle, including the product core. In parallel, the overall heat capacity of the bottle–product system was determined by differential scanning calorimetry, enabling the estimation of the thermal energy absorbed by the bottles. Mass and energy balances were applied to quantify the heat exchanged in each process stage and to estimate phase-specific and overall heat-transfer efficiencies. Under nominal conditions, the pasteurization requirement, defined as a temperature above 72 °C for at least 12 min at the coldest point, was fully satisfied, with the temperature remaining above 72 °C for approximately 22 min near the bottle wall and 17–18 min at the product core. The energy analysis showed that overall process efficiency was limited, indicating room for improvement. Three additional experimental tests were therefore carried out under modified temperature and flow-rate conditions. In all cases, the pasteurization target was maintained. The results demonstrate that the process complies with the prescribed pasteurization target while offering significant opportunities for energy savings through optimization of the operating parameters. Full article

The structural safety of polar ships is critically dependent on local ice loads acting in the ship–ice interaction area. Ice conditions and ship speeds play dominant roles in influencing local ice loads. Field measurement serves as a crucial approach for accurately assessing and scientifically understanding local ice loads and ice conditions. The instrumentation for the field measurement on RV Xuelong-2 is discussed in this study. In the 12th Chinese National Arctic Research Expedition, digital processing technologies are employed for image recognition and statistical analysis of ice concentrations and thicknesses. The influence coefficient matrix method is validated by a physical experiment and applied to identify local ice loads from ice-induced strains. Subsequently, the relationship between local ice loads, ice conditions, and ship speeds is statistically analyzed and mechanistically explained. The results show that the coupling effect between ship speeds and ice parameters, along with the competition between ice failure modes, may cause ice load peaks to transition from increasing to decreasing at a specific ship speed and ice thickness. A prolonged ice load duration under high ice concentrations is an important factor contributing to the positive correlation between ice load peaks and ice concentrations. Full article

Public participation in planning, though a foundational democratic principle, faces persistent implementation challenges across diverse planning systems. This paper examines participatory planning practice in Ireland and Serbia—two countries representing distinct planning traditions (discretionary and conformance-based, respectively) yet confronting shared structural pressures. Through comparative analysis of four local land use planning instruments (the Development Plan and Local Area Plan in Ireland; the Municipal Spatial Plan and General Regulation Plan in Serbia), the study investigates how institutional design and legislative frameworks shape the depth and quality of participatory practice. Methodologically, the research triangulates statutory regulations, public hearing documentation, and non-statutory participation records across two planning scales (county/municipal and local/sub-municipal). A four-dimensional analytical framework—informing, consultation, collaboration, and monitoring—guides the systematic comparison of participatory mechanisms across the selected cases. Findings reveal that, while both systems remain predominantly at the informing and consultation levels, critical differences emerge in how participation is structured and documented in institutional practice. Ireland’s discretionary system enables multi-channel information dissemination, feedback-oriented consultation, and non-statutory collaborative experimentation beyond legal minimums. Serbia’s conformance-based system confines participation largely to statutory procedures, with objection-based consultation and limited collaborative mechanisms, though distinctive features, such as the public hearing session, provide direct opportunities for deliberation absent in the Irish context. The study contributes to European comparative planning scholarship by demonstrating that participatory depth is shaped less by the formal existence of legal provisions than by the interplay between institutional design, procedural arrangements, transparency, and responsiveness. Full article

Heart inflammation and oxidative stress are pivotal pathological drivers in the pathophysiology of various cardiovascular diseases. The present study aims to investigate the beneficial effects induced by extracts derived from edible plants, such as Olea europaea, and sugar cane on heart health. In particular, we investigated the effects of a novel combination constituting Olea europaea, Scutellaria baicalensis, and policosanol extracts on heart, in in vitro and ex vivo models. Olea europaea, S. baicalensis, policosanol extracts and their combination prevented H₂O₂-induced reduction in H9c2 cell (immortalized myoblasts, isolated from rat heart tissue) viability. Moreover, pre-incubation with the combination significantly reduced H₂O₂-induced ROS levels in the same cells. Our present findings also showed that Olea europaea, S. baicalensis and policosanol extracts, as well as their combination, increased lipopolysaccharide (LPS)-induced catalase gene expression at all concentrations tested, in mouse heart specimens. In addition, we also observed that Olea europaea, S. baicalensis and policosanol extracts, as well as their combination, significantly inhibited LPS-induced inducible nitric oxide synthase, cyclooxygenase-2, nuclear factor-kB, and tumor necrosis factor-α gene expression, in the same experimental model. Interestingly, the combination was more effective at decreasing the mRNA levels of all pro-inflammatory markers investigated. Finally, the combination was also able to suppress LPS-induced B-type natriuretic peptide and cardiac troponin I gene expression ex vivo. In conclusion, these findings suggest that this plant-based combination could offer potential benefits for cardiovascular health and support overall heart function in humans. Full article

Background/Objectives: The coronavirus disease 2019 (COVID-19) pandemic presented significant psychosocial challenges to intensive care unit health care workers (ICU HCW). Prior studies typically used single cross-sectional samples to focus on elements of burnout and psychological stress. We sought to serially assess quality of life and willingness to work before, during, and after the first peak of COVID-19. Methods: Two survey instruments were prospectively administered at regular intervals to multidisciplinary ICU HCWs, initiating at the local onset of COVID-19 and ending 6 months after the first peak ICU census of COVID-19 patients. Results: ICU HCWs reported high levels of compassion satisfaction, burnout, and secondary traumatic stress before, during and after the first peak of COVID-19. Motivation to work declined, and hesitation to work increased from study initiation to the peak ICU census of COVID-19 patients. Hesitation to work was greater in female HCWs and cardiothoracic ICU HCWs. Motivation to work was higher in those working in operating rooms compared to those in the ICU. Concerns about becoming infected, feelings of isolation, and exhaustion were associated with high hesitation to work. Feeling protected by the government and hospital was associated with decreased hesitation and increased motivation to work. Conclusions: ICU HCWs experienced high levels of stress throughout the first year of COVID-19, while satisfaction with work remained high. Willingness to work was associated with gender, work location, ICU subtype, concerns about infection risk, feelings of exhaustion, and feelings of institutional protection. Because the study methodology precludes causal inference and low survey response rates indicate that findings should be interpreted with caution, these results are best viewed as hypothesis-generating for future work aimed at improving stress mitigation in ICU HCWs. Full article

Background: Haitian immigrants in the United States face health literacy challenges related to recent migration, language discordance, and unfamiliar healthcare systems, yet no general health literacy instrument has been psychometrically validated in Haitian Creole. This study translated, culturally adapted, and evaluated the Haitian Creole HLS₁₉-Q12 (HLS₁₉-Q12-HC). Methods: Haitian Creole-speaking adults without cancer diagnoses in South Florida (n = 168) completed the HLS₁₉-Q12-HC and the Haitian Creole Brief Health Literacy Screen. Translation included forward–backward procedures, expert review, and cognitive interviews (n = 7). Psychometric evaluation used confirmatory factor analysis, reliability testing, and assessment of convergent and known-groups validity. Results: Cognitive interviews supported clarity and cultural appropriateness with minor refinements. Reliability was excellent (ω = 0.949; α = 0.944; AVE = 0.584). The unidimensional model showed good fit (CFI = 0.951; TLI = 0.944; RMSEA = 0.065; SRMR = 0.048), whereas multi-factor models showed limited discriminant validity. Convergent and known-groups validity were supported. Using provisional European-derived cutpoints, 70.2% of participants were classified as having inadequate or problematic health literacy. Conclusions: The HLS19-Q12-HC showed evidence of reliability and validity as a unidimensional measure of general health literacy and may support research, needs assessment, and culturally responsive interventions for Haitian Creole-speaking populations. Findings should be interpreted in light of the convenience sample from South Florida and the predominantly female composition of the cohort. Full article

The intersection of digital citizenship, sustainable education, and community belonging represents an emerging yet underexplored area of inquiry, particularly within Arab higher education contexts where institutional digitalization is accelerating alongside distinct sociocultural expectations around academic identity. This study aims to investigate the mediating role of sustainable education in the relationship between digital citizenship and community belonging among Egyptian university students. A quantitative cross-sectional survey design was employed with a main sample of 819 university students. Participants completed three validated instruments: the Revised Digital Citizenship Scale, the Sustainable Education Scale, and the Where I Belong Survey. Mediation analysis was conducted using Hayes’ PROCESS macro with 5000 bootstrap resamples. Results reveal that digital citizenship is significantly and positively associated with both sustainable education and community belonging. Sustainable education, in turn, significantly predicts community belonging after controlling for digital citizenship, with the indirect effect accounting for approximately 38% of the total effect, consistent with partial mediation. These findings demonstrate that responsible digital engagement is associated with community belonging not only directly but also in a pattern statistically consistent with partial mediation through sustainability-oriented values including equity, inclusiveness, and democratic participation. These findings suggest theoretically informed directions for future intervention design, wherein integrating sustainable education principles into digital learning environments may warrant empirical investigation as a potential approach to cultivating ethically grounded, socially cohesive academic communities. Full article