Search Results (1,609)

Although technological innovations are often intended to improve quality and efficiency, they can exacerbate systemic challenges when not aligned with the principles of value-based care. As a result, healthcare systems in many countries face persistent inefficiencies stemming from the overuse, underuse, misuse, and waste associated with the adoption of health technology. This narrative review examines the dual impact of healthcare technology and evaluates how contract mechanisms can serve as strategic tools for promoting cost-effective, outcome-oriented integration. Drawing from healthcare management, and supply chain literature, this paper analyzes various payment and contract models, including performance-based, bundled, cost-sharing, and revenue-sharing agreements, through the lens of stakeholder alignment. It explores how these mechanisms influence provider behavior, patient access, and system sustainability. The study contends that well-designed contract mechanisms can align stakeholder incentives, reduce inefficiencies, and support the delivery of high-value care across diverse healthcare settings. We provide concrete examples to illustrate how various contract mechanisms impact the integration of health technologies in practice. Full article

pH is a critical parameter requiring precise monitoring across scientific, industrial, and biological domains. Fluorescent pH probes offer a powerful alternative to traditional methods (e.g., electrodes, indicators), overcoming limitations in miniaturization, long-term stability, and electromagnetic interference. By utilizing photophysical mechanisms—including intramolecular charge transfer (ICT), photoinduced electron transfer (PET), and fluorescence resonance energy transfer (FRET)—these probes enable high-sensitivity, reusable, and biocompatible sensing. This review systematically details recent advances, categorizing probes by operational pH range: strongly acidic (0–3), weakly acidic (3–7), strongly alkaline (>12), weakly alkaline (7–11), near-neutral (6–8), and wide-dynamic range. Innovations such as ratiometric detection, organelle-specific targeting (lysosomes, mitochondria), smartphone colorimetry, and dual-analyte response (e.g., pH + Al³⁺/CN⁻) are highlighted. Applications span real-time cellular imaging (HeLa cells, zebrafish, mice), food quality assessment, environmental monitoring, and industrial diagnostics (e.g., concrete pH). Persistent challenges include extreme-pH sensing (notably alkalinity), photobleaching, dye leakage, and environmental resilience. Future research should prioritize broadening functional pH ranges, enhancing probe stability, and developing wide-range sensing strategies to advance deployment in commercial and industrial online monitoring platforms. Full article

Infection control and bleeding management in deep wounds remain urgent and unmet clinical challenges that demand innovative, multifunctional, and sustainable solutions. Unlike previously reported sodium alginate and silk fibroin-based gel formulations, the present work introduces a dual-functional system combining antimicrobial and haemostatic activity in the form of conformable aerogel beads. This dual-functional formulation is designed to absorb exudate, promote clotting, and provide localized antimicrobial action, all essential for accelerating wound repair in high-risk scenarios within a single biocompatible system. Aerogel beads were obtained by supercritical drying of a silk fibroin–sodium alginate blend, resulting in highly porous, spherical structures measuring 3–4 mm in diameter. The formulations demonstrated efficient ciprofloxacin encapsulation (42.75–49.05%) and sustained drug release for up to 12 h. Fluid absorption reached up to four times their weight in simulated wound fluid and was accompanied by significantly enhanced blood clotting, outperforming a commercial haemostatic dressing. These findings highlight the potential of silk-based aerogel beads as a multifunctional wound healing platform that combines localized antimicrobial delivery, efficient fluid and exudate management, biodegradability, and superior haemostatic performance in a single formulation. This work also shows for the first time how the prilling encapsulation technique with supercritical drying is able to successfully produce silk fibroin and sodium alginate composite aerogel beads. Full article

Remote sensing images are often degraded by atmospheric haze, which not only reduces image quality but also complicates information extraction, particularly in high-level visual analysis tasks such as object detection and scene classification. State-space models (SSMs) have recently emerged as a powerful paradigm for vision tasks, showing great promise due to their computational efficiency and robust capacity to model global dependencies. However, most existing learning-based dehazing methods lack physical interpretability, leading to weak generalization. Furthermore, they typically rely on spatial features while neglecting crucial frequency domain information, resulting in incomplete feature representation. To address these challenges, we propose ScaleViM-PDD, a novel network that enhances an SSM backbone with two key innovations: a Multi-scale EfficientViM with Physical Decoupling (ScaleViM-P) module and a Dual-Domain Fusion (DD Fusion) module. The ScaleViM-P module synergistically integrates a Physical Decoupling block within a Multi-scale EfficientViM architecture. This design enables the network to mitigate haze interference in a physically grounded manner at each representational scale while simultaneously capturing global contextual information to adaptively handle complex haze distributions. To further address detail loss, the DD Fusion module replaces conventional skip connections by incorporating a novel Frequency Domain Module (FDM) alongside channel and position attention. This allows for a more effective fusion of spatial and frequency features, significantly improving the recovery of fine-grained details, including color and texture information. Extensive experiments on nine publicly available remote sensing datasets demonstrate that ScaleViM-PDD consistently surpasses state-of-the-art baselines in both qualitative and quantitative evaluations, highlighting its strong generalization ability. Full article

Achieving the construction sector’s dual carbon objectives necessitates scaling green energy adoption in new residential buildings. The current literature critically overlooks four unresolved problems: oversimplified penalty mechanisms, ignoring escalating regulatory costs; static subsidies misaligned with market maturity evolution; systematic exclusion of innovation feedback from energy suppliers; and underexplored behavioral evolution of building owners. This study establishes a government–suppliers–owners evolutionary game framework with dynamically calibrated policies, simulated using MATLAB multi-scenario analysis. Novel findings demonstrate: (1) A dual-threshold penalty effect where excessive fines diminish policy returns due to regulatory costs, requiring dynamic calibration distinct from fixed-penalty approaches; (2) Market-maturity-phased subsidies increasing owner adoption probability by 30% through staged progression; (3) Energy suppliers’ cost-reducing innovations as pivotal feedback drivers resolving coordination failures, overlooked in prior tripartite models; (4) Owners’ adoption motivation shifts from short-term economic incentives to environmentally driven decisions under policy guidance. The framework resolves these gaps through integrated dynamic mechanisms, providing policymakers with evidence-based regulatory thresholds, energy suppliers with cost-reduction targets, and academia with replicable modeling tools. Full article

Maximizing the efficient utilization of critical apatite resources through flotation necessitates the exploration of effective and innovative collectors. This study investigates the potential of a fatty acid mixture (FAM) synthesized from saturated palmitic and stearic acids, monounsaturated oleic and palmitoleic acids, and polyunsaturated linoleic acid. The saponified collector FAM and the depressant sodium alginate (NaAl) achieved a direct flotation of apatite from calcite and quartz (97% apatite, 10% calcite, and 7% quartz). The flotation performance with the tested combination exhibited a highly effective enrichment of apatite, mainly from calcite, which aligns with the surface chemistry assessments. Adsorption tests and zeta potential measurements confirmed the micro-flotation results. They provided compelling evidence of a chemisorption interaction between Ca²⁺ sites on calcite and the carboxyl and hydroxyl groups of NaAl. FTIR analyses suggested a reaction between the apatite surface and the carboxyl groups of saturated and unsaturated acid groups in FAM, even those conditioned with NaAl before, facilitating the complex formation. Remarkably, the synergistic effect of the functional groups demonstrates dual functionality, serving as both a hydrophilic entity for calcite and a hydrophobic entity for apatite flotation. The universal mechanism unveils substantial potential for the extensive application of FAM within apatite flotation. Full article

The COVID-19 pandemic catalyzed the rapid adoption of remote patient monitoring (RPM) technologies such as telemedicine and wearable devices (WDs), significantly transforming healthcare delivery. Telemedicine made virtual consultations possible, reducing in-person visits and infection risks, particularly for the management of chronic diseases. Wearable devices enabled the real-time continuous monitoring of health that assisted in condition prediction and management, such as for COVID-19. This narrative review addresses these transformations by uniquely synthesizing findings from 13 diverse studies (sourced from PubMed and Google Scholar, 2020–2024) to analyze the parallel evolution of telemedicine and WDs as interconnected RPM components. It highlights the pandemic’s dual impact, as follows: accelerating RPM innovation and adoption while simultaneously unmasking systemic challenges such as inequities in access and a need for robust integration approaches; while telemedicine usage soared during the pandemic, consumption post-pandemic, as indicated by the reviewed studies, suggests continued barriers to adoption among older adults. Likewise, wearable devices demonstrated significant potential in early disease detection and long-term health management, with promising applications extending beyond COVID-19, including long COVID conditions. Addressing the identified challenges is crucial for healthcare providers and systems to fully embrace these technologies and this would improve efficiency and patient outcomes. Full article

Achieving synergies between government-led and market-based policy instruments is critical to advancing Energy–Environmental Productivity and Sustainable Urban Development. This study investigates the effects of China’s dual-pilot energy policies (New Energy Demonstration Cities (NEDCs) and Energy Consumption Permit Trading (ECPT)) on urban environmental productivity (UEP) across 279 prefecture-level cities from 2006 to 2023. Utilizing a Non-Radial Directional Distance Function (NDDF) approach, combined with Difference-in-Differences (DID) estimation and spatial econometric models, the analysis reveals that these synergistic policies significantly enhance both comprehensive and net measures of UEP. Mechanism analysis highlights the roles of industrial restructuring, technological innovation, and energy transition in driving these improvements, while heterogeneity analysis indicates varying effects across different city types. Spatial spillover analysis further demonstrates that policy impacts extend beyond targeted cities, contributing to broader regional gains in UEP. These findings offer important insights for the design of integrated energy and environmental policies and support progress toward key Sustainable Development Goals (SDG 7, SDG 11, and SDG 12). Full article

Mycoplasma bovis is an important pathogen that is associated with respiratory diseases, mastitis, and arthritis in cattle, leading to significant economic losses in the global cattle industry. Most notably in this study, we pioneer the discovery that its secreted effector ENO1 (α-enolase) directly targets host cytoskeletal proteins for metabolic–immune regulation. Using an innovative GST pull-down/mass spectrometry approach, we made the seminal discovery of β-actin (ACTB) as the primary host target of ENO1—the first reported bacterial effector–cytoskeleton interaction mediating metabolic reprogramming. ENO1–ACTB binding depends on a hydrogen bond network involving ACTB’s 117Glu and 372Arg residues. This interaction triggers (1) glycolytic activation via Glut1 upregulation, establishing Warburg effect characteristics (lactic acid accumulation/ATP inhibition), and (2) ROS-mediated activation of dual inflammatory axes (HIF-1α/IL-1β and IL-6/TNF-α). This work establishes three groundbreaking concepts: (1) the first evidence of a pathogen effector hijacking host ACTB for metabolic manipulation, (2) a novel ‘glycolysis–ACTB–ROS-inflammation’ axis, and (3) the first demonstration of bacterial proteins coordinating a Warburg effect with cytokine storms. These findings provide new targets for anti-infection therapies against Mycoplasma bovis. Full article

In the digital era, understanding the intention to use generative AI is critical, as it enhances productivity, transforms workflows, and enables humans to focus on higher-value tasks. Drawing upon the unified theory of acceptance and use of technology (UTAUT) and the technology threat avoidance theory (TTAT), this research integrates perceived AI literacy into the AI acceptance–avoidance framework as a central variable. This study gathered 583 valid survey responses from China and validated its model using a dual-phase, combined method that integrates structural equation modeling and artificial neural networks. Research findings indicate that the model explains 51.6% of the variance in generative AI usage intention. Except for social influence, all variables within the extended framework significantly impact the usage intention, with perceived AI literacy being the strongest predictor (β = 0.33, p < 0.001). Additionally, perceived AI literacy mitigates the adverse effect of perceived threats on the intention to use AI. Practical implications suggest that enterprises adopt a tiered strategy, as follows: maximize perceived benefits by integrating AI skills into reward systems and providing task-automation training; minimize perceived costs through dedicated technical support and transparent risk mitigation plans; and cultivate AI literacy via progressive learning paths, advancing from data analysis to innovation. Full article

This study presents a comparative analysis of the annual performances of stationary and dual-axis sun-tracked photovoltaic–thermal (PVT) systems. The experimental research was conducted at a demonstration site in Oświęcim, Poland, where both systems were evaluated in terms of electricity and heat production. The test installation consisted of thirty stationary PVT modules and five dual-axis sun-tracking systems, each equipped with six PV modules. An innovative cooling system was developed for the PVT modules, consisting of a surface-mounted heat sink installed on the rear side of each panel. The system includes embedded tubes through which a cooling fluid circulates, enabling efficient heat recovery. The results indicated that the stationary PVT system outperformed a conventional fixed PV installation, whose expected output was estimated using PVGIS data. Specifically, the stationary PVT system generated 26.1 kWh/m² more electricity annually, representing a 14.8% increase. The sun-tracked PVT modules yielded even higher gains, producing 42% more electricity than the stationary system, with particularly notable improvements during the autumn and winter seasons. After accounting for the electricity consumed by the tracking mechanisms, the sun-tracked PVT system still delivered a 34% higher net electricity output. Moreover, it enhanced the thermal energy output by 85%. The findings contribute to the ongoing development of high-performance PVT systems and provide valuable insights for their optimal deployment in various climatic conditions, supporting the broader integration of renewable energy technologies in building energy systems. Full article

Large Vision Language Models (LVLMs) have shown promise in remote sensing applications, yet struggle with “uncommon” objects that lack sufficient public labeled data. This paper presents Enhanced-RSCLIP, a novel dual-prompt architecture that combines text prompting with exemplar-image processing for cattle herd detection in satellite imagery. Our approach introduces a key innovation where an exemplar-image preprocessing module using crop-based or attention-based algorithms extracts focused object features which are fed as a dual stream to a contrastive learning framework that fuses textual descriptions with visual exemplar embeddings. We evaluated our method on a custom dataset of 260 satellite images across UK and Nigerian regions. Enhanced-RSCLIP with crop-based exemplar processing achieved 72% accuracy in cattle detection and 56.2% overall accuracy on cross-domain transfer tasks, significantly outperforming text-only CLIP (31% overall accuracy). The dual-prompt architecture enables effective few-shot learning and cross-regional transfer from data-rich (UK) to data-sparse (Nigeria) environments, demonstrating a 41% improvement over baseline approaches for uncommon object detection in satellite imagery. Full article

This study investigates the synergistic modification of cement–soil using waste brick powder (WBP) and polyvinyl alcohol (PVA) fibers to address the growing demand for sustainable construction materials and recycling of demolition waste. An orthogonal experimental design was employed with 5% WBP (by mass) and PVA fiber content (0–1%), evaluating mechanical properties based on unconfined compressive strength (UCS) and splitting tensile strength (STS) and microstructure via scanning electron microscopy (SEM) across 3–28 days of curing. The results demonstrate that 0.75% PVA optimizes performance, enhancing UCS by 28.3% (6.87 MPa) and STS by 34.6% (0.93 MPa) at 28 days compared to unmodified cement–soil. SEM analysis revealed that PVA fibers bridged microcracks, suppressing propagation, while WBP triggered pozzolanic reactions to densify the matrix. This dual mechanism concurrently improves mechanical durability and valorizes construction waste, offering a pathway to reduce reliance on virgin materials. This study establishes empirically validated mix ratios for eco-efficient cement–soil composites, advancing scalable solutions for low-carbon geotechnical applications. By aligning material innovation with circular economy principles, this work directly supports global de-carbonization targets in the construction sector. Full article

Advances in plaque imaging have transformed cardiovascular diagnostics through detailed characterization of atherosclerotic plaques beyond traditional stenosis assessment. This review outlines the clinical applications of varying modalities, including dual-layer spectral CT, photon-counting CT, dual-energy CT, and CT-derived fractional flow reserve (CT-FFR). These technologies offer improved spatial resolution, tissue differentiation, and functional assessment of coronary lesions. Additionally, artificial intelligence has emerged as a powerful tool to automate plaque detection, quantify burden, and refine risk prediction. Collectively, these innovations provide a more comprehensive approach to coronary artery disease evaluation and support personalized management strategies. Full article

As a crucial reactive oxygen species, hydrogen peroxide (H₂O₂) serves as both a physiological regulator and a pathological indicator in human systems. Its urinary concentration has emerged as a valuable biomarker for assessing metabolic disorders and renal function. While conventional colorimetric determination methods predominantly employ enzymatic or nanozyme catalysts, we present an innovative non-catalytic approach utilizing the redox-responsive properties of organic neutral radicals. Specifically, we designed and synthesized a novel radical TTM-DMODPA based on the tris (2,4,6-trichlorophenyl) methyl (TTM) scaffold, which exhibits remarkable optical tunability and oxidative sensitivity. This system enables dual-mode H₂O₂ quantification: (1) UV-vis spectrophotometry (linear range: 2.5–250 μmol/L, LOD: 1.275 μmol/L) and (2) smartphone-based visual analysis (linear range: 2.5–250 μmol/L, LOD: 3.633 μmol/L), the latter being particularly suitable for point-of-care testing. Validation studies using urine samples demonstrated excellent recovery rates (96–104%), confirming the method’s reliability for real-sample applications. Our work establishes a portable, instrument-free platform for urinary H₂O₂ determination, with significant potential in clinical diagnostics and environmental monitoring. Full article