Search Results (22,934)

The effect of reversible addition–fragmentation chain transfer (RAFT) polymerization on the structure, morphology, and thermal degradation behavior of polypropylene glycol maleate–acrylic acid copolymers (p-PGM:AA) was investigated using 2-cyano-2-propyl dodecyl trithiocarbonate (CPDT) as the RAFT agent. Copolymers synthesized at different CPDT concentrations were characterized by ¹H/¹³C NMR spectroscopy, gel permeation chromatography (GPC), transmission electron microscopy (TEM), thermogravimetric analysis coupled with mass spectrometry (TG–MS), isoconversional kinetic methods, and density functional theory (DFT) calculations. ¹H NMR spectroscopy revealed a progressive decrease in the relative intensity of vinyl proton signals with increasing CPDT concentration, indicating enhanced conversion of unsaturated fragments during copolymerization. Alkaline hydrolysis followed by ¹H NMR and GPC analysis of the degradation products confirmed cleavage of polyester segments and yielded low-molecular-weight fragments with M_n = 1370 g mol⁻¹ and narrow dispersity (Đ = 1.035), providing additional information on the architecture of the vinyl-polymerized segments. Increasing CPDT concentration resulted in lower molecular weights and narrower molecular weight distributions of the soluble copolymer fractions. TEM analysis demonstrated broader domain size distributions and increased morphological heterogeneity in RAFT-modified samples, accompanied by an increase in swelling degree. Thermogravimetric analysis showed that RAFT-modified systems undergo multi-stage thermal degradation with the appearance of an additional low-temperature stage associated with thermolabile fragments. TG–MS revealed earlier evolution of CO₂ and oxygen-containing species and changes in the distribution of volatile products. DFT calculations indicated a decrease in the HOMO–LUMO energy gap and suggested the participation of RAFT-derived fragments in the energetic characteristics of decarboxylation processes. Isoconversional and nonlinear kinetic analyses demonstrated increased kinetic heterogeneity for branched copolymer s synthesized at elevated CPDT concentrations, whereas cross-linked systems exhibited more uniform degradation behavior. The combined experimental and theoretical results demonstrate that RAFT polymerization provides an effective route for tuning the macromolecular architecture, morphology, and thermal degradation pathways of p-PGM:AA copolymers. Full article

A recurring challenge in the development of information systems (ISs) across complex organizational domains is the lack of integration and alignment between strategic, tactical, and operational levels, resulting in methodological fragmentation that constrains traceability, innovation, and organizational value generation. This study proposes and applies to the Integrated Innovation Framework for Information System Development (IIF-ISD) to overcome this gap. The research was structured through a systematic literature review, following the PRISMA and ROSES protocols, and validated through an exploratory single-case study involving the development of an IS supporting the Selo Casa Azul (SCA) environmental certification process in a Brazilian construction company, a context chosen for its multi-level organizational complexity and ESG compliance requirements, representative of broader certification IS development challenges. The framework integrates DSRM, agile methodologies, Design Thinking, and Lean Startup through three governing principles—Hierarchical Embedding, Functional Complementarity, and Traceability by Design—achieving cross-level alignment between strategic objectives, tactical performance monitoring, and operational execution. Empirical evaluation (n = 9; 14 weeks) yielded SUS scores of 76.8–82.1/100, a 76% reduction in data entry error rates, and a 78% stakeholder engagement rate, providing initial support for the framework’s practical effectiveness. Full article

Background: Since 2014, all Australian jurisdictions have progressively amended legislation to authorise pharmacists to administer vaccines, evolving from restricted pilots to an essential public health pillar. Objective: This review analyses the longitudinal evolution of pharmacist-administered vaccinations (PAVs), documenting changes in authorised vaccines, age eligibility, and regulatory frameworks across all Australian jurisdictions. Methods: A retrospective review of Australian jurisdictional legislation, regulations, and policy documents was undertaken. Searches included official legislative registers, Government Gazettes, Health Department protocols, and professional guidance published by Pharmaceutical Society of Australia (PSA) and The Pharmacy Guild of Australia between 2014 to 2026. Documents were independently reviewed by five authors, followed by secondary verification and consensus-based adjudication to resolve discrepancies and confirm findings. Results: PAVs scope was expanded from a single influenza pilot in 2014 to include over 21 vaccine-preventable diseases by 2026. The COVID-19 pandemic catalysed rapid reform, leading to the standardisation of age eligibility (largely ≥5 years). A landmark milestone occurred in 2025 when South Australia enabled pharmacists to administer any vaccine within their professional scope. Conclusion: Legislative reforms have significantly enhanced vaccine accessibility. However, jurisdictional fragmentation persists. National harmonisation, using a competency-based model similar to South Australia, is recommended to streamline delivery and optimise public health outcomes. Full article

Grotto Buddhist Niches are important spatial carriers of Buddhist cave art, containing rich architectural, artistic, and historical information. However, image data of these Buddhist niches are fragmented across multiple scales, including visual features, cultural semantics, and spatial structures, which significantly hinders cross-scale correlative analysis. To address this issue, this paper proposes a multi-scale knowledge representation method based on image semantics and ontology. Specifically, we establish a five-tier semantic description model, comprising the visual feature layer, image data layer, entity layer, cultural semantics layer, and relational layer. Furthermore, using Protégé and the classical Seven-Step Method, we develop a domain ontology named Grotto Buddhist Niche Ontology (GBNOnto) to enable unified semantic modeling of multi-scale information. Based on this ontology, a knowledge graph focusing on cave imagery is constructed, with typical caves such as Cave 38 at the Yungang Grottoes selected as case studies. The resulting graph contains 892 entity nodes and 2621 semantic relations, effectively capturing the complex interconnections among architectural typology, artistic characteristics, and cultural semantics within the selected niche instances. The proposed method enables structured and associative integration of multi-scale information in grotto Buddhist niche images. It thus provides a foundational data infrastructure and modeling framework to support effective management, knowledge retrieval, and semantic reasoning. Full article

Wildfires pose serious risks to ecosystems, air quality, and human health. Effective wildfire monitoring requires accurate detection and timely validation, but current approaches are often constrained by fragmented data sources, false alarms, and delays in field verification. This study presents WildfireGO, a multi-source wildfire detection and validation system that integrates crowdsourced observations, satellite hotspot data, and image-based classification in a geospatial monitoring environment. The system combines user-submitted images, Sentinel-2 imagery, and Moderate Resolution Imaging Spectroradiometer (MODIS) hotspot data processed through Google Earth Engine (GEE) to support wildfire detection and verification. Four classification models, namely Convolutional Neural Network (CNN), Random Forest (RF), K-Nearest Neighbors (KNN), and Gradient Boosting (GB), were evaluated using 10-fold cross-validation and an independent test dataset of 800 wildfire-related images. The CNN model produced the best result, with an accuracy of 97.5% on the independent test dataset. By combining image-based classification with crowdsourced reporting, the system helps screen user-submitted wildfire information and reduce false detections. Satellite-derived hotspot data provide spatial evidence for cross-checking reported events and improving spatial situational awareness for wildfire monitoring and response planning. WildfireGO supports near real-time data submission, automated processing, and interactive map-based visualization through a web-based interface. The findings indicate that combining crowdsourced reports, satellite observations, and image classification in a single geospatial system has the potential to support more reliable wildfire detection and provide practical support for environmental monitoring, disaster response, and spatial decision-making. Full article

Rosmarinic acid (RA), a naturally occurring polyphenolic compound, has demonstrated promising anticancer activity; however, its combinatorial potential with conventional chemotherapeutic agents remains incompletely characterized. This study investigated the cytotoxic, pro-apoptotic, oxidative stress-associated, and cytokine-associated effects of RA alone and in combination with doxorubicin (DOX) in 4T1 murine breast cancer cells and HaCaT human keratinocyte cells as a non-cancerous control model. Cellular viability, apoptosis, cell cycle progression, oxidative stress, mitochondrial function, cytokine responses, and apoptosis-associated molecular alterations were evaluated using complementary cellular and molecular approaches. In addition, three-dimensional (3D) tumor spheroid experiments were performed to assess treatment responses under physiologically relevant tumor-like conditions. Results demonstrated that RA synergistically enhanced DOX-induced cytotoxicity in 4T1 cells while exhibiting comparatively lower toxicity toward HaCaT cells. Combination treatment significantly increased apoptotic cell death, mitochondrial depolarization, intracellular reactive oxygen species (ROS) accumulation, apoptotic DNA fragmentation, and G₂/M-phase accumulation. N-acetylcysteine (NAC)-mediated rescue experiments partially reversed ROS elevation and treatment-associated cytotoxicity in both monolayer and 3D spheroid models. Furthermore, the RA+DOX combination markedly disrupted spheroid integrity and reduced spheroid viability compared with monotherapies. Collectively, these findings indicate that RA enhances the anticancer activity of DOX and support further investigation of this combination strategy in breast cancer models. Full article

This study explores the similarity of the fragmentation effect of a reactive inner core PELE (RIC-PELE) when penetrating a steel plate by measuring the broken length of the jacket after perforating the steel plate and the dispersion radius of the jacket fragments behind the steel plate. Based on the dimensional theory, the dimensionless functions of these two physical quantities were analyzed and established. On the basis of verifying the validity of numerical simulation, the penetration and deflagration damage effects of five scale models were simulated on the ANSYS/Autodyn 17.0 software platform, and the dimensional analysis was verified. In the obtained dimensionless functions, the independent variables are all geometric dimensionless quantities. The simulation results reveal that, within the impact velocity range of 900–1900 m/s, the dimensionless broken length of the jacket and the dimensionless dispersion radius of jacket fragments behind the target are approximately equal in different scale models at the same velocity; these values fall within error margins of ±7% and ±9% of the reference model, respectively, and both dimensionless quantities exhibit an approximately linear positive relationship with impact velocity. This indicates that when ignoring the size effect caused by the strain rate effect of the materials, the geometric similarity law of the fragmentation effect of a RIC-PELE penetrating a steel plate essentially holds, thereby verifying the correctness of the dimensional analysis. Full article

Academic motivation and achievement are central to student success in applied STEM, engineering, and technical and vocational education and training (TVET); however, despite extensive research, the evidence remains fragmented across theoretical traditions, educational levels, and disciplinary settings. This structured narrative review synthesizes research on the factors shaping academic motivation, achievement, and career readiness in these contexts. A literature search was conducted in Web of Science, Scopus, ScienceDirect, PubMed, and PsycINFO for studies published between 2010 and 2025. A total of 58 studies met the inclusion criteria from an initial pool of 2184 records. Guided by self-determination theory, achievement goal theory, social cognitive career theory, and expectancy–value theory, this review identifies self-efficacy, perceived competence, task value, intrinsic/extrinsic motivation, goal orientation, metacognitive skills, teacher and peer support, curriculum relevance, and industry-aligned learning opportunities as key factors associated with student engagement, achievement, and career-related development. The synthesis shows that these factors operate through an integrated motivational core linking motivational regulation, self-belief, task value, and goal orientation. The findings suggest that student success is shaped by the interaction between individual beliefs, social support, instructional conditions, and perceived links between learning and future professional pathways. Practical implications are discussed for designing student-centered, career-relevant, and motivation-supportive learning environments in engineering and TVET. Full article

In protected areas, fragmentation and artificial light at night are usually present alongside changes in land type, from natural to agricultural or urban. We explored the intensity of edge effects on light trap responses of nocturnal insects at the margin of the floodplain forest in the Donau-Auen National Park in Central Europe, Austria. Specifically, we examined the abundance and biomass of nocturnal insects and characterized the community composition and diversity of moths with respect to the local habitat. In this study, 58 species were observed, with 21 unique records on the forest edge and nine in the interior. Traps in the forest interior harbored significantly higher nocturnal insect biomass. However, moth assemblages were more diverse at edge sites due to many singletons, attributed to individuals attracted from areas with open vegetation. Nine species (15.5% of total) were recorded later than expected given their summer flight periods, potentially reflecting the effects of ongoing climate change associated with warmer autumns. Overall, we observed higher moth species diversity at the forest edge, and insect biomass and moth abundance were higher within the forest. These findings underscore the urgent need to incorporate local anthropogenic landscape and climate change as synergically evolutionary drivers in future population and community-focused research. Full article

The implementation of an artificial intelligence (AI)-based system for monitoring, forecasting, and learner performance support has been intensified by the rapid expansion of online education systems. Existing online educational platforms completely rely on learning analytics and machine learning to customize content delivery. On the other hand, these platforms fundamentally focus on behavioral and cognitive indicators, whereas the integration of affective computing into learning analytics and adaptive decision-making processes is lacking. During the learning process, emotions like engagement, boredom, and confusion play a vital role. Nonetheless, the integration of adaptive online learning systems is still fragmented and underdeveloped. The latest progress in affective computing and multimodal sensing technologies allow for the inference of the affective state of learners in real-time, which creates a range of potential opportunities to create emotionally sensitive learning spaces. Despite technological innovations, the existing studies do not have a conceptual framework that is unified, design-oriented, and clearly incorporates affective computing with AI-based learning analytics to inform real-time pedagogical adaptation. To address this gap, this study introduces a design-oriented conceptual framework for AI-based online education systems that incorporate real-time affective computing. This conceptual framework combines the theoretical foundation of learning analytics, affective computing, and adaptive learning systems. The suggested framework offers a clear and scalable basis of online learning environments that are affective-aware by offering a clear framework of development, assessment, and consequent empirical validation. Full article

Digitalization is transforming urban mobility and logistics, changing behaviors and the way demand is anticipated and managed. This paper frames both research and practice in this area. Through a systematic review of reviews in Scopus and Web of Science, following PRISMA 2020, a corpus of 21 documents was compiled. The analysis organizes findings into five interrelated dimensions: technology; operation and service design; society, user, and equity; institution, regulation, and governance; and economics and scalability. These are interpreted through two cross-cutting axes: behavioral change among users and operators, and the anticipation and management of demand supported by big data and predictive models. By integrating urban mobility and logistics, usually analyzed separately, this study compares barriers and enablers. The two axes help identify gaps: limited coverage of medium-sized cities, low-density environments, and developing countries; fragmented treatment of user diversity; weak integration between mobility and logistics data; and the lag between the sophistication of predictive models and the institutional capacity to incorporate them into planning. This paper proposes an integrative framework for analyzing the digitalization of urban mobility and logistics as part of a single urban transition. Full article

Processed meat products represent a major challenge for proteomic species identification due to extensive thermal treatment and protein structural changes. In this study, species-specific peptides in pork, chicken, and bovine meat products were identified using a directed fragmentation-assisted de novo sequencing workflow that combines 4-formylbenzene-1,3-disulfonic acid (FBDA) peptide derivatization, dual-polarity data-independent mass spectrometry (DIA-MS), and Protein Acrobat de novo sequencing software. Comparative analysis of non-fractionated and strong cation exchange (SCX)-fractionated pork luncheon samples improved peptide and protein identification after fractionation, with 312 peptides and 115 protein groups detected exclusively in fractionated samples. Species-specific peptides were predominantly assigned to conserved muscle-related proteins, including myosin, troponin, and tropomyosin, while sequence variability enabled reliable species discrimination despite protein conservation across species. To evaluate applicability for food fraud detection, mixed meat samples containing 10% chicken in pork or bovine matrices were analyzed, reflecting potential economically motivated adulteration through substitution with lower-cost meat components. Several chicken-specific peptides remained detectable in both mixtures, demonstrating robustness of the FBDA-assisted peptide sequencing combined with SCX fractionation and DIA-MS for detection of adulteration in complex processed food matrices. These findings establish a mass spectrometry-driven orthogonal method to ELISA testing for fast, reliable and accurate metaproteome analysis of highly processed food. Full article

Implicit bias, automatic attitudes or stereotypes outside conscious awareness, may influence clinicians’ communication, diagnosis, and treatment decisions, contributing to inequities in care. We conducted a scoping review to map measurement strategies used to assess implicit bias among health professionals and students in healthcare and training settings. Using Joanna Briggs Institute guidance and PRISMA-ScR, we searched PubMed, Embase, BVS, Google Scholar, and institutional repositories for studies to November 2025; two reviewers independently screened and charted data (protocol was developed a priori but submitted internal in organization, and then uploaded in OSF. Of 1864 records, 93 studies from 28 countries were included. We identified 57 bias domains, most often race/ethnicity, weight, and sexual orientation. Across studies, 42 unique instruments were reported; the Implicit Association Test was most common, while psychometric validation and administration details were frequently limited, constraining comparability and interpretation. Evidence gap mapping showed concentration in academic and hospital settings, with fewer studies in primary care or community contexts and limited attention to age, disability, and intersectionality-related biases. The evidence base is growing but fragmented; future work should prioritize standardized administration and reporting, stronger validation, and tools that better capture automatic responding across diverse identities and care settings to support education and equity-oriented interventions. Full article

The increasing global demand for dietary protein has intensified the search for functional and sustainable plant-based ingredients. Chickpea flour is a promising candidate owing to its high nutritional quality and rich bioactive content. This study evaluated the use of microfluidization as a non-thermal strategy to enhance the physicochemical and functional properties of chickpea flour. Microfluidization induced particle fragmentation and led to protein denaturation, producing more irregular and porous surface morphologies. These structural modifications increased surface hydrophobicity, enhancing emulsifying and foaming capacities. Enhanced surface hydrophobicity also led to marked improvements in oil-holding capacity (up to 210% increase over control, after microfluidization at 200 MPa for three passes), likely due to stronger interactions with non-polar solvents. In parallel, microfluidization facilitated greater protein-water interactions, resulting in a 210% increase in protein solubility and 40% improvement in water-holding capacity after microfluidization at 200 MPa for one pass, compared to control. Increased surface area additionally contributed to higher in vitro protein digestibility (about 45% higher than control for all microfluidized samples) and the formation of a stronger network. Overall, these results demonstrate that microfluidization is an effective approach for improving the functional performance of whole chickpea flour, supporting its potential application in plant-based food systems. Full article

Organizations are under constant strain to substitute the traditional ETL pipelines and monolithic warehouses for the dynamic cloud-native modular architectures. Despite rapid adoption, the Modern Data Stack (MDS) literature remains fragmented: lakehouse, mesh, and fabric paradigms are studied in isolation, and no prior review has linked component-level decisions to organizational maturity. This systematic review addresses that gap. Following PRISMA 2020 guidelines across six databases, 650 records were screened and 141 studies were retained for thematic synthesis (the corpus was peer-reviewed, with a small number of primary-source technical preprints screening was performed primarily by one reviewer; a 10% double-screened sample yielded Cohen’s κ = 0.81). Six functional layers (ingestion, storage, transformation, orchestration, analytics, and observability/governance) and four dominant architectural patterns (cloud warehouse, lakehouse, data mesh, and data fabric) were identified. Components were evaluated against five criteria—scalability, cost efficiency, vendor neutrality, learning curve, and business impact—across three organizational archetypes (startup, SME, and enterprise). A three-phase maturity model (Foundation, Extension, Consolidation), a five-stage iterative implementation cycle, and a RACI governance matrix constitute the resulting strategic framework. Governance emerged as simultaneously the least-adopted layer in the corpus and the most consequential for long-run adoption success. The framework is propositional; empirical validation through an expert Delphi study, multi-case longitudinal analysis, and an AHP-based practitioner survey are planned as future work. Full article