Search Results (16,553)

Microwave imaging (MWI) is a non-invasive technique for visualizing the anomalies of biological tissues. The imaging process is accomplished by comparing the electrical parameters of healthy tissues and malignant tissues. This work introduces a microwave imaging system for tumor detection in breast tissue. The experiment is performed in a homogeneous background medium, where a high dielectric contrast material is used to mimic the tumor. The proposed imaging system is experimentally evaluated for multiple tumor locations and sizes using a horn antenna. Reflection coefficients obtained from the monostatic configuration of the horn antenna are used for image reconstruction. The evaluation metrics, such as localization error, absolute area error, DICE score, Intersection over Union (IoU), precision, accuracy, sensitivity and specificity, are computed from the reconstructed image. A modified version of the beamforming algorithm improves the quality of reconstructed images by providing a minimum accuracy of 96% for all test cases, with an evaluation time of less than 48 s. The proposed methodology shows promising results under a controlled environment and can be implemented for clinical applications after adequate biological studies. This methodology can be used to calibrate any antenna system or phantom, as it has high contrast in conductivity, leading to better imaging. The present study contributes to Sustainable Development Goal (SDG) 3 by ensuring healthy lives and promoting wellbeing for all ages. Full article

Precise characterization of the thermospheric neutral wind is essential for comprehending the dynamic interactions within the ionosphere-thermosphere system, as evidenced by the development of models like HWM and the need for localized data. However, numerical models often suffer from biases due to uncertainties in external forcing and the scarcity of direct wind observations. This study examines the influence of incorporating actual neutral wind profiles from the Michelson Interferometer for Global High-resolution Thermospheric Imaging (MIGHTI) on the Ionospheric Connection Explorer (ICON) satellite into the Thermosphere Ionosphere Electrodynamics General Circulation Model (TIE-GCM) via an ensemble-based data assimilation framework. To address the challenges of assimilating real observational data, a robust background check Quality Control (QC) scheme with dynamic thresholds based on ensemble spread was implemented. The assimilation performance was evaluated by comparing the analysis results against independent, unassimilated observations and a free-running model Control Run. The findings demonstrate a substantial improvement in the precision of the thermospheric wind field. This enhancement is reflected in a 45–50% reduction in Root Mean Square Error (RMSE) for both zonal and meridional components. For zonal winds, the system demonstrated effective bias removal and sustained forecast skill, indicating a strong model memory of the large-scale mean flow. In contrast, while the assimilation exceptionally corrected the meridional circulation by refining the spatial structures and reshaping cross-equatorial flows, the forecast skill for this component dissipated rapidly. This characteristic of “short memory” underscores the highly dynamic nature of thermospheric winds and emphasizes the need for high-frequency assimilation cycles. The system required a spin-up period of approximately 8 h to achieve statistical stability. These findings demonstrate that the assimilation of data from ICON/MIGHTI satellites not only diminishes numerical inaccuracies but also improves the representation of instantaneous thermospheric wind distributions. Providing a high-fidelity dataset is crucial for advancing the modeling and understanding of the complex interactions within the Earth’s ionosphere-thermosphere system. Full article

Background: In today’s dynamic healthcare environment, Changi General Hospital (CGH) has positioned staff wellbeing and engagement as fundamental priorities that underpin workforce sustainability and quality care delivery. Recognizing that allied health professionals (AHPs) face unique emotional demands and potential empathy fatigue, the CGH Allied Health Division (AHD) uses three strategic pillars: individual empowerment, leaders as key stewards and institutional support systems to address staff wellbeing and engagement. This paper will evaluate the outcomes of implementing the programs and identifying the barriers and enablers to achieving staff wellbeing and engagement. Methods: It adopts a mixed-methods approach using both quantitative survey data and qualitative feedback. Results: A total of 314 AHPs participated with a mean employment duration of 8.89 years. While 95% agreed that their work was meaningful and 76.8% reported happiness at work, 40.8% did not experience being recognized by the organization and approximately 30% did not find higher management responsive to their needs or transparent in their communication. Qualitative analysis revealed concerns about psychological safety of sharing one’s opinions and concerns, and a desire for better renumeration and career progression. Conclusions: AHPs reported happiness and meaningfulness in their clinical work. However, issues with organizational recognition, higher management responsiveness and transparency, as well as psychological safety were elicited. Working towards addressing fostering psychological safety and enhancing recognition and communication with management are important in order to develop and sustain a thriving healthcare workforce capable of high-quality patient care. Overall, the findings reinforced AHD direction of putting employee wellbeing and engagement as a strategic priority. Full article

This paper investigates whether participation in Zambia’s social cash transfer programme (SCTP) improves household dietary diversity among ultra-poor rural households. While cash transfers are widely implemented across sub-Saharan Africa as social protection measures, empirical evidence regarding their impact on nutritional status remains mixed. This study focuses on dietary diversity, a proxy for nutrition quality, and uses data from the 2015 Rural Agricultural Livelihood Survey (RALS). The analysis employs propensity score matching to control for demographic differences between recipient and non-recipient households, followed by a regression analysis to examine the association between SCTP participation and dietary diversity scores. The findings reveal no statistically significant association between receiving social cash transfers and higher household dietary diversity. In contrast, positive predictors of dietary diversity included household remittances, own production of animal-source foods, and maize sales. Notably, households that relied on foraging exhibited significantly lower dietary diversity, suggesting foraging may be a coping strategy among food-insecure households. These results imply that while the SCTP may enhance household income stability, it does not necessarily translate into improved diet quality. This study contributes to the ongoing policy debate on the effectiveness of cash-based interventions in improving nutrition outcomes. It highlights the need to complement cash transfers with interventions that support food production and access, particularly in rural settings where market and infrastructure limitations persist. Full article

High-quality spectral filters with versatile tuning mechanisms are essential for applications in photonic integrated circuits, including sensing, laser stabilization, and spectral signal processing. We report the implementation of thermo-optic (TO) and electro-optic (EO) spectral tuning in silicon nitride Mach–Zehnder interferometers (MZIs) and micro-ring resonators (MRRs) by functionalizing the devices with a PMMA:JRD1 polymer cladding and integrating titanium tracks as heaters and electrodes. The fabricated MZIs and MRRs exhibit narrow linewidths of 25–30 pm and achieved TO tuning efficiencies of 1.7 and 13 pm/mW and EO tuning efficiencies of 0.33 and 1.6 pm/V, respectively. Closed-loop regulation using TO and EO effects enables stable half-fringe locking under environmental perturbations. This simple, broadly compatible hybrid platform demonstrates a practical approach to dual-mode spectral tuning and modulation in integrated photonic filters, providing a flexible route toward compact, reconfigurable, and environmentally robust photonic circuits. Full article

Green-synthesized nanomaterials have emerged as promising candidates for environmentally sustainable remediation; however, experimental evidence describing their synthesis routes, physicochemical properties, remediation performance, and sustainability-relevant attributes remains fragmented, inconsistently reported, and difficult to integrate across studies. This work addresses this challenge by proposing an ontology-based semantic framework for the interoperable integration of green-synthesized nanomaterials, contaminants, and remediation processes, incorporating explicit provenance metadata and structured sustainability descriptors. The ontology was developed using the Linked Open Terms (LOT) methodology and implemented in OWL 2 DL, with selective alignment to established vocabularies including eNanoMapper, ChEBI, ENVO, and PROV-O. Adsorption and photocatalysis were instantiated as representative remediation mechanisms to evaluate the framework’s capacity to accommodate structurally distinct processes. Logical reasoning and SHACL-based validation were applied to assess semantic consistency, provenance traceability, and data completeness. The results demonstrate that the proposed ontology effectively integrates heterogeneous experimental data within a unified, FAIR-compliant semantic framework, supports conservative and provenance-aware inference, and enables comparative analysis across mechanistically diverse remediation systems without structural modification. This ontology-based approach provides a robust foundation for sustainability-aware knowledge integration in environmental nanotechnology and establishes the basis for future extensions involving data quality assessment and explainable AI-driven analysis. Full article

This study addresses critical safety and productivity challenges faced by tower crane operators due to limited visibility during lifting operations. An intelligent crane-mounted visual system was implemented to enhance operator visibility, reduce communication faults, and improve overall crane performance in high-rise construction. The study followed a five-stage methodology: a literature review of visual and sensor technologies for collision prevention, site visits to identify visibility challenges, a comparative analysis of cranes with and without the vision system, and an impact assessment on safety and quality. The crane-mounted video system significantly improved efficiency, safety, and work quality, reducing cycle time, defined as the duration from hook pickup to placement, by 25%, with this reduction statistically significant at p < 0.001 using a two-paired t-test. Fewer near-miss incidents and lower idle times for workers and operators were observed, even when a less experienced operator operated the system. A cost–benefit assessment indicates that crane vision systems can generate annual economic benefits exceeding 240,000 NIS through accident prevention and time savings, based on the project context. This study’s contribution lies in providing a comprehensive, real-world evaluation of retrofitting older cranes with advanced vision technologies, demonstrating measurable impacts on safety, productivity, and economic outcomes. Full article

Background: Cardiac rehabilitation (CR) is a key component of secondary prevention after acute coronary events, coronary and valve interventions, and device implantation, yet participation and long-term adherence remain suboptimal. Digital technologies offer the potential to extend CR beyond the centre-based model and to support more flexible, patient-centred care. Methods: This narrative “review on a systematic backbone” synthesizes original clinical studies published between 2005 and 2025 that evaluated the use of digital technologies as an integral part of CR in adults after myocardial infarction, revascularization, valve procedures or implantation of cardiac devices. Interventions were grouped into four categories: mobile health (mHealth) and tele-rehabilitation, virtual reality (VR) and exergaming, virtual education platforms, and other multi-component digital CR solutions. Only original studies with clinical, functional, or patient-reported outcomes were included. Results: Twenty-one studies on the categories mentioned above met the eligibility criteria. mHealth-enabled home-based or hybrid CR programs consistently achieved improvements in functional capacity and physical activity that were broadly comparable to centre-based CR, with generally high adherence. VR and exergaming interventions were feasible and safe, produced at least similar functional gains, and showed more consistent benefits as far as anxiety levels and engagement levels. Virtual education platforms delivered knowledge and produced behaviour change similar to traditional education and, in some studies, supported better control of blood pressure and lipids. Comprehensive digital CR platforms improved risk-factor profiles and quality of life to a degree comparable with face-to-face CR. Conclusions: Digital technologies can credibly support core objectives of CR in high-risk patients and expand access, but must be implemented as a complement to, rather than a replacement for, multidisciplinary, patient-centred rehabilitation. Full article

Optimizing nanofiber morphology is essential for promoting osteoblast elongation and supporting bone regeneration. This study aimed to develop a machine-learning framework capable of predicting optimal scaffold architectures directly from scanning electron microscopy (SEM) images and chemical composition. A four-module pipeline was implemented, combining tile-based SEM preprocessing, Cellpose-based cell morphology extraction with edge correction, ensemble machine-learning models, and an end-to-end convolutional neural network (CNN). Cellular quality was quantified using an elongation-weighted metric to emphasize morphological maturity over cell number. The analysis revealed consistent structure–function relationships across samples, with Sample_5 achieving the highest quality score at the 72 h time point. Ensemble models reached an R² of 0.400, while the end-to-end CNN achieved an R² of 0.750, indicating that raw SEM texture provides additional predictive information beyond handcrafted features. Feature-importance analysis identified nonlinear MgO effects and synergistic interactions between MgO and gold nanoparticles as key determinants of cell morphology. These findings demonstrate that the integrated workflow can reliably identify morphology–chemistry combinations favorable for osteoblast performance and provide a foundation for data-driven scaffold optimization. The approach supports rational design of nanofibrous biomaterials and may facilitate future development of intelligent scaffolds for bone regeneration applications. Full article

Water is a critical resource underpinning natural, societal and economic development, and its importance will grow bigger in the next decades. Interfacial solar evaporators are a promising and cost-effective technology for the generation of freshwater from saline and polluted waters. Yet, although these devices effectively reject salts and non-volatile pollutants, the presence of volatile organic compounds in the water source may lead to low water quality of the distillate. This review addresses the introduction of photocatalytic materials in solar evaporator devices to improve water quality, highlighting in particular possible synergies and incompatibilities between the materials promoting these functionalities. The interactions of the photocatalyst with photothermal materials are described, along with an overview of the materials most commonly selected for both functionalities. A positive interaction clearly emerges, with the photothermal materials not only accelerating evaporation but also generally stimulating the photocatalytic degradation of VOCs. Limits to the implementation of such a combination are described, including those due to electrolyte content and salt accumulation, reaction rate and mass transfer. Finally, recommendations regarding testing conditions and future studies are presented. Full article

Building information modeling (BIM)-based interior design automation remains constrained by a semantic mismatch: engineering constraints are explicit and categorical, whereas aesthetic style is implicit, contextual, and difficult to formalize. As a result, existing systems often overfit local visual similarity or rely on rigid rules, producing recommendations that drift stylistically at the scene level or conflict with professional design logic. This paper proposes KsDesign, a neuro-symbolic framework for interpretable, retrieval-based BIM scene completion that unifies visual style perception with explicit design knowledge. Offline, KsDesign mines category-level co-occurrence and compatibility patterns from curated designer-quality interiors and encodes them as a weighted Furniture-Matching Knowledge Graph (FMKG). Online, it learns style representations exclusively from BIM-derived 2D renderings/projections of 3D family models and BIM scenes, and applies a knowledge-guided attention mechanism to weight contextual furniture cues, synthesizing a global scene-style representation for candidate ranking and retrieval. In a Top-3 (K = 3) evaluation on 10 BIM test scenes with a 20-expert consensus ground truth, KsDesign consistently outperforms single-modal baselines, achieving 86.7% precision in complex scenes and improving average precision by 23.5% (up to 40%), with a 15.5% average recall increase. These results suggest that global semantic constraints can serve as a logical regularizer, mitigating the local biases of purely visual matching and yielding configurations that are both aesthetically coherent and logically valid. We further implement in-authoring explainability within Revit, exposing KG-derived influence weights and evidence paths to support rationale inspection and immediate family insertion. Finally, the knowledge priors and traceable intermediate representations provide a robust substrate for integration with LLM-driven conversational design agents, enabling constraint-aware, verifiable generation and interactive iteration. Full article

Background: Mechanical circulatory support (MCS) has revolutionized advanced heart failure and cardiogenic shock management, yet randomized controlled trials have failed to demonstrate consistent mortality benefits with temporary devices, and outcomes remain highly variable across institutions. Methods: This narrative review examines contemporary MCS devices, analyzing their hemodynamic principles, clinical outcomes, complications, and selection strategies. The published literature addressing MCS clinical applications and outcomes was reviewed, with reference lists examined to identify additional sources. Results: Temporary MCS devices demonstrate a persistent hemodynamic-survival paradox where improved hemodynamics fail to translate into mortality benefits in randomized trials. This disconnect reflects delayed intervention after irreversible organ damage, device complications offsetting hemodynamic gains, heterogeneous patient selection without phenotyping, timing challenges, and inadequate statistical power. Landmark trials provide definitive evidence against routine early VA-ECMO use, showing no survival advantage while significantly increasing complications. Optimal device selection requires integrating hemodynamic phenotyping with shock stage to match devices to pathophysiology, while biventricular failure presents the greatest challenge with substantially lower survival. For durable devices, third-generation systems demonstrate superior outcomes with dramatically reduced pump thrombosis and improved survival. Critically, multidisciplinary shock teams employing standardized protocols significantly reduce mortality beyond what devices alone achieve, with structured programs showing substantially improved survival compared to trials using similar devices without organized care systems. Conclusions: Mechanical circulatory support has transformed heart failure management, but optimal outcomes require integrating devices within structured care delivery systems. Success depends on comprehensive hemodynamic assessment, multidisciplinary team activation, protocolized device selection, standardized escalation and weaning strategies, and regionalized networks. The future lies in shifting focus from device innovation to implementation science, establishing quality metrics, developing precision medicine approaches, and conducting trials in phenotype-selected populations with protocolized care. This systems-of-care paradigm offers the most promising path toward translating technological advances into sustained mortality reduction. Full article

The Special Education Center at National Taiwan Normal University implemented the PSMIGP (Problem-Solving and Multiple Intelligences for Gifted Preschoolers) program, designed to cultivate problem-solving abilities and multiple intelligences in gifted preschool children. The program included four cohorts with a total of 73 participants identified through multidimensional assessments in academic and artistic domains. Twenty years later, when participants were aged 23–27, their educational experiences and talent development were examined using a mixed-methods design through questionnaires and semi-structured interviews. Quantitative data were analyzed with SPSS and qualitative interviews were coded using NVivo 15; the data were validated through participant feedback and peer review. The results showed that nearly all the participants attended top universities in Taiwan or abroad, with a higher proportion than that in the general population receiving gifted education services. The consistent satisfaction reflected the influence of motivation, curriculum quality, supportive teachers, and access to diverse learning opportunities. Talent development resulted from dynamic, multilevel interactions—social, personal, cultural, and task-related—rather than innate ability alone. Full article

Sustainable business management in the food sector entails the systematic integration of social, environmental, and economic considerations into organizational decision-making, which has direct implications for food safety assurance systems. This study sought to evaluate how the maturity of an organization’s safety culture influences employees’ pro-quality and food-safety-related behaviors. A complementary objective was to examine employees’ understanding of pro-quality awareness in the context of the principles, goals, and operational procedures associated with sustainable management. The research was carried out in three food industry enterprises located in the Greater Poland region. The methodological framework consisted of internal audits assessing compliance with food safety and quality management standards, combined with a structured questionnaire survey. A total of 169 employees from various operational and administrative departments participated. The results indicate that employees’ professional qualifications and organizational roles significantly affect their awareness of how individual actions contribute to food safety and product quality outcomes. Moreover, the implementation of a sustainable, systems-oriented management approach supported a more comprehensive understanding of food production processes where employees recognize their impacts on public health, the socio-economic environment, natural ecosystems, and future generations. At the same time, this approach underscores the interdependence between employee well-being, organizational performance, and consumer protection. Full article

Background: The precise segmentation and classification of dermoscopic images remain prominent obstacles in automated skin cancer evaluation due, in part, to variability in lesions, low-contrast borders, and additional artifacts in the background. There have been recent developments in foundation models, with a particular emphasis on the Segment Anything Model (SAM)—these models exhibit strong generalization potential but require domain-specific adaptation to function effectively in medical imaging. The advent of new architectures, particularly Vision Transformers (ViTs), expands the means of implementing robust lesion identification; however, their strengths are limited without spatial priors. Methods: The proposed study lays out an integrated foundation-model-based framework that utilizes SAM-Adapter-fine-tuning for lesion segmentation and a ViT-based classifier that incorporates lesion-specific cropping derived from segmentation and cross-attention fusion. The SAM encoder is kept frozen while lightweight adapters are fine-tuned only, to introduce skin surface-specific capacity. Segmentation priors are incorporated during the classification stage through fusion with patch-embeddings from the images, creating lesion-centric reasoning. The entire pipeline is trained using a joint multi-task approach using data from the ISIC 2018, HAM10000, and PH2 datasets. Results: From extensive experimentation, the proposed method outperforms the state-of-the-art segmentation and classification across the dataset. On the ISIC 2018 dataset, it achieves a Dice score of 94.27% for segmentation and an accuracy of 95.88% for classification performance. On PH2, a Dice score of 95.62% is achieved, and for HAM10000, an accuracy of 96.37% is achieved. Several ablation analyses confirm that both the SAM-Adapters and lesion-specific cropping and cross-attention fusion contribute substantially to performance. Paired t-tests are used to confirm statistical significance for all the previously stated measures where improvements over strong baselines indicate a $p<0.01$ for most comparisons and with large effect sizes. Conclusions: The results indicate that the combination of prior segmentation from foundation models, plus transformer-based classification, consistently and reliably improves the quality of lesion boundaries and diagnosis accuracy. Thus, the proposed SAM-ViT framework demonstrates a robust, generalizable, and lesion-centric automated dermoscopic analysis, and represents a promising initial step towards clinically deployable skin cancer decision-support system. Next steps will include model compression, improved pseudo-mask refinement and evaluation on real-world multi-center clinical cohorts. Full article