Search Results (368)

To achieve energy transition, hydrogen and carboxylic acids have attracted much attention due to their cleanliness and renewability. Anaerobic fermentation technology is an effective combination of waste biomass resource utilization and renewable energy development. Therefore, the utilization of anaerobic fermentation technology is expected to achieve efficient co-production of hydrogen and carboxylic acids. However, this process is fundamentally affected by gas–liquid mass transfer kinetics, bubble behaviors, and system partial pressure. Moreover, the related studies are few and unfocused, and no systematic research has been developed yet. This review systematically summarizes and discusses the basic mathematical models used for gas–liquid mass transfer kinetics, the relationship between gas solubility and mass transfer, and the liquid-phase product composition. The review analyzes the roles of the headspace gas composition and partial pressure of the reaction system in regulating co-production. Additionally, we discuss strategies to optimize the metabolic pathways by modulating the gas composition and partial pressure. Finally, the feasibility of and prospects for the realization of hydrogen and carboxylic acid co-production in anaerobic fermentation systems are outlined. By exploring information related to gas mass transfer and system pressure, this review will surely provide an important reference for promoting cleaner production of sustainable energy. Full article

Unmanned aerial vehicles are increasingly used in civil Search and Rescue operations due to their rapid deployment and wide-area coverage capabilities. However, detecting missing persons from aerial imagery remains challenging due to small object sizes, cluttered backgrounds, and limited onboard computational resources, especially when managed by civil agencies. In this work, we present a comprehensive methodology for optimizing YOLO-based object detection models for real-time Search and Rescue scenarios. A two-stage transfer learning strategy was employed using VisDrone for general aerial object detection and Heridal for Search and Rescue-specific fine-tuning. We explored various architectural modifications, including enhanced feature fusion (FPN, BiFPN, PB-FPN), additional detection heads (P2), and modules such as CBAM, Transformers, and deconvolution, analyzing their impact on performance and computational efficiency. The best-performing configuration (YOLOv5s-PBfpn-Deconv) achieved a mAP@50 of 0.802 on the Heridal dataset while maintaining real-time inference on embedded hardware (Jetson Nano). Further tests at different flight altitudes and explainability analyses using EigenCAM confirmed the robustness and interpretability of the model in real-world conditions. The proposed solution offers a viable framework for deploying lightweight, interpretable AI systems for UAV-based Search and Rescue operations managed by civil protection authorities. Limitations and future directions include the integration of multimodal sensors and adaptation to broader environmental conditions. Full article

The “Baby Ubuntu” programme is a well-established, low-cost, community-based intervention to support caregivers of children with complex neurodisability, like cerebral palsy, in low- and middle-income country (LMIC) contexts. This process-focused paper describes our utilisation of the ADAPT guidance to adapt “Baby Ubuntu” for use in ethnically and linguistically diverse, and economically deprived urban boroughs in the United Kingdom (UK). The process was guided by an adaptation team, including parents with lived experience, who explored the rationale for the intervention from local perspectives and its fit for this UK community. Through qualitative interviews and co-creation strategies, the perspectives of caregivers and healthcare professionals substantially contributed to the “Encompass” programme theory, drafting the content, and planning the delivery. Ten modules were co-produced with various topics, based on the “Baby Ubuntu” modules, to be co-facilitated by a parent with lived experience and a healthcare professional. The programme is participatory, allowing caregivers to share information, problem solve, and form supportive peer networks. The “Encompass” programme is an example of a “decolonised healthcare innovation”, as it aims to transfer knowledge and solutions developed in low- and middle-income countries to a high-income context like the UK. Piloting of the new programme is underway. Full article

Skin cancer is one of the most prevalent forms of cancer worldwide, and early and accurate diagnosis critically impacts patient outcomes. Given the sensitive nature of medical data and its fragmented distribution across institutions (data silos), privacy-preserving collaborative learning is essential to enable knowledge-sharing without compromising patient confidentiality. While federated learning (FL) offers a promising solution, existing methods struggle with heterogeneous and missing modalities across institutions, which reduce the diagnostic accuracy. To address these challenges, we propose an effective and flexible Personalized Multimodal Federated Learning framework (PMM-FL), which enables efficient cross-client knowledge transfer while maintaining personalized performance under heterogeneous and incomplete modality conditions. Our study contains three key contributions: (1) A hierarchical aggregation strategy that decouples multi-module aggregation from local deployment via global modular-separated aggregation and local client fine-tuning. Unlike conventional FL (which synchronizes all parameters in each round), our method adopts a frequency-adaptive synchronization mechanism, updating parameters based on their stability and functional roles. (2) A multimodal fusion approach based on multitask learning, integrating learnable modality imputation and attention-based feature fusion to handle missing modalities. (3) A custom dataset combining multi-year International Skin Imaging Collaboration(ISIC) challenge data (2018–2024) to ensure comprehensive coverage of diverse skin cancer types. We evaluate PMM-FL through diverse experiment settings, demonstrating its effectiveness in heterogeneous and incomplete modality federated learning settings, achieving 92.32% diagnostic accuracy with only a 2% drop in accuracy under 30% modality missingness, with a 32.9% communication overhead decline compared with baseline FL methods. Full article

Ferrocene (Fc) is a redox-active organometallic scaffold whose unique electronic properties, stability, and modularity have enabled a broad range of catalytic and sensing applications. This review critically examines recent advances in Fc-based systems for hydrogen evolution and carbon dioxide (CO₂) conversion, encompassing electrochemical, photochemical, and thermochemical strategies. Fc serves diverse functions: it operates as a reversible redox mediator, an electron reservoir, a ligand framework, and a structural modulator. Each role contributes differently to enhancing catalytic performance, improving selectivity, or increasing operational stability. We highlight how Fc integration facilitates proton-coupled electron transfer in hydrogen evolution, supports selective CO₂ reduction in molecular and hybrid catalysts, and promotes efficient CO₂ fixation and capture within functionalised frameworks. Emerging applications in electrosynthetic organic transformations are also discussed. Together, these findings position Fc as a foundational motif for designing future electrocatalytic and carbon management platforms. Full article

Circularly polarized luminescence (CPL) materials have shown great application potential in the fields of three-dimensional displays, bioimaging, and information encryption and decryption. The chirality enhancement of CPL by a physical chiral environment, involving the delivery of structural asymmetry from helical architectures to luminescent molecules through electromagnetic field resonance, represents an innovative approach for constructing high-performance CPL materials. Liquid crystal polymers (LCPs), possessing helical superstructures, show great potential in constructing CPL systems. By modulating the chirality transfer from the helical structural environment of LCPs to luminescent sources via distinct strategies, the CPL properties of LCP-based composites are readily generated and tailored. This review summarizes the newest construction strategies of LCP-based CPL materials and provides a perspective on their emerging applications and future opportunities. This review can deepen our understanding of the fundamentals of chirality transfer and shed light on the development of functional chiral luminescent materials. Full article

Style transfer technology has seen substantial attention in image synthesis, notably in applications like oil painting, digital printing, and Chinese landscape painting. However, it is often difficult to generate migrated images that retain the essence of paper-cutting art and have strong visual appeal when trying to apply the unique style of Chinese paper-cutting art to style transfer. Therefore, this paper proposes a new method for Chinese paper-cutting style transformation based on the Transformer, aiming at realizing the efficient transformation of Chinese paper-cutting art styles. Specifically, the network consists of a frequency-domain mixture block and a multi-level feature contrastive learning module. The frequency-domain mixture block explores spatial and frequency-domain interaction information, integrates multiple attention windows along with frequency-domain features, preserves critical details, and enhances the effectiveness of style conversion. To further embody the symmetrical structures and hollowed hierarchical patterns intrinsic to Chinese paper-cutting, the multi-level feature contrastive learning module is designed based on a contrastive learning strategy. This module maximizes mutual information between multi-level transferred features and content features, improves the consistency of representations across different layers, and thus accentuates the unique symmetrical aesthetics and artistic expression of paper-cutting. Extensive experimental results demonstrate that the proposed method outperforms existing state-of-the-art approaches in both qualitative and quantitative evaluations. Additionally, we created a Chinese paper-cutting dataset that, although modest in size, represents an important initial step towards enriching existing resources. This dataset provides valuable training data and a reference benchmark for future research in this field. Full article

Clouds modulate the net radiative flux that interacts with both shortwave (SW) and longwave (LW) radiation, but the uncertainties regarding their effect in polar regions are especially high because ground observations are lacking and evaluation through satellites is made difficult by high surface reflectance. In this work, sky conditions for six different polar stations, two in the Arctic (Ny-Ålesund and Utqiagvik [formerly Barrow]) and four in Antarctica (Neumayer, Syowa, South Pole, and Dome C) will be presented, considering the decade between 2010 and 2020. Measurements of broadband SW and LW radiation components (both downwelling and upwelling) are collected within the frame of the Baseline Surface Radiation Network (BSRN). Sky conditions—categorized as clear sky, cloudy, or overcast—were determined using cloud fraction estimates obtained through the RADFLUX method, which integrates shortwave (SW) and longwave (LW) radiative fluxes. RADFLUX was applied with daily fitting for all BSRN stations, producing two cloud fraction values: one derived from shortwave downward (SWD) measurements and the other from longwave downward (LWD) measurements. The variation in cloud fraction used to classify conditions from clear sky to overcast appeared consistent and reasonable when compared to seasonal changes in shortwave downward (SWD) and diffuse radiation (DIF), as well as longwave downward (LWD) and longwave upward (LWU) fluxes. These classifications served as labels for a machine learning-based classification task. Three algorithms were evaluated: Random Forest, K-Nearest Neighbors (KNN), and XGBoost. Input features include downward LW radiation, solar zenith angle, surface air temperature ($T_a$), relative humidity, and the ratio of water vapor pressure to $T_a$. Among these models, XGBoost achieved the highest balanced accuracy, with the best scores of 0.78 at Ny-Ålesund (Arctic) and 0.78 at Syowa (Antarctica). The evaluation employed a leave-one-year-out approach to ensure robust temporal validation. Finally, the results from cross-station models highlighted the need for deeper investigation, particularly through clustering stations with similar environmental and climatic characteristics to improve generalization and transferability across locations. Additionally, the use of feature normalization strategies proved effective in reducing inter-station variability and promoting more stable model performance across diverse settings. Full article

The efficient simultaneous removal of NO_x and CO from sintering flue gas under low-temperature conditions (110–180 °C) in iron and steel enterprises remains a significant challenge in the field of environmental catalysis. In this study, we present an innovative strategy to enhance the performance of CuSmTi catalysts through silver modification, yielding a bifunctional system capable of oxygen structure regulation and demonstrating superior activity for the combined NH₃-SCR and CO oxidation reactions under low-temperature, oxygen-rich conditions. The modified AgCuSmTi catalyst achieves complete NO conversion at 150 °C, representing a 50 °C reduction compared to the unmodified CuSmTi catalyst (T_100% = 200 °C). Moreover, the catalyst exhibits over 90% N₂ selectivity across a broad temperature range of 150–300 °C, while achieving full CO oxidation at 175 °C. A series of characterization techniques, including XRD, Raman spectroscopy, N₂ adsorption, XPS, and O₂-TPD, were employed to elucidate the Ag-Cu interaction. These modifications effectively optimize the surface physical structure, modulate the distribution of acid sites, increase the proportion of Lewis acid sites, and enhance the activity of lattice oxygen species. As a result, they effectively promote the adsorption and activation of reactants, as well as electron transfer between active species, thereby significantly enhancing the low-temperature performance of the catalyst. Furthermore, in situ DRIFTS investigations reveal the reaction mechanisms involved in NH₃-SCR and CO oxidation over the Ag-modified CuSmTi catalyst. The NH₃-SCR process predominantly follows the L-H mechanism, with partial contribution from the E-R mechanism, whereas CO oxidation proceeds via the MvK mechanism. This work demonstrates that Ag modification is an effective approach for enhancing the low-temperature performance of CuSmTi-based catalysts, offering a promising technical solution for the simultaneous control of NO_x and CO emissions in industrial flue gases. Full article

Contact electrification (CE), or triboelectrification, is an electron transfer phenomenon occurring at the interface between dissimilar materials due to differences in polarity, holding significant research value in tribology. The microscopic mechanisms of CE remain unclear due to the complex coupling of multiple physical processes. Recently, with the rise of triboelectric nanogenerator (TENG) technology, solid–liquid contact electrification has demonstrated vast application potential, sparking considerable interest in its underlying mechanisms. Emerging experimental evidence indicates that at water–polymer CE interfaces, the process involves not only traditional ion adsorption but also electron transfer. Halogen-containing functional groups in the solid material significantly enhance the CE effect. To elucidate the microscopic mechanism of water–polymer CE, this study employed first-principles density functional theory (DFT) calculations, simulating the interfacial electrification process using unit cell models of water contacting polymers. We systematically and quantitatively investigated the charge transfer characteristics at interfaces between water and three representative polymers with similar backbones but different halogen-functionalized (F, Cl) side chains: fluorinated ethylene propylene (FEP), polyvinyl chloride (PVC), and polytetrafluoroethylene (PTFE), focusing on evaluating halogen’s influence and mechanism on interfacial electron transfer. The results reveal that electron transfer is primarily governed by the energy levels of the polymer’s lowest unoccupied molecular orbital (LUMO) and highest occupied molecular orbital (HOMO). Halogen functional groups modulate the material’s electron-donating/accepting capabilities by altering these frontier orbital energy levels. Consequently, we propose that the critical strategy for polymer chemical modification resides in lowering the LUMO energy level of electron-accepting materials. This study provides a novel theoretical insight into the charge transfer mechanism at solid–liquid interfaces, offers guidance for designing high-performance TENG interfacial materials, and holds significant importance for both the fundamental theory and the development of advanced energy devices. Full article

The first ray plays a fundamental role in foot biomechanics, particularly in stabilizing the medial longitudinal arch and enabling efficient weight transfer during the mid-stance and propulsion phases of gait. When dorsiflexed—a condition known as metatarsus primus elevatus—especially in its flexible form, this structure disrupts load distribution, impairs propulsion, and contributes to various clinical symptoms. Despite its clinical importance, the biomechanical impact of orthotic elements placed beneath the first ray remains underexplored. This study aimed to quantify the variations in medio-lateral (Fx), antero-posterior (Fy), and vertical (Fz) force vectors generated during gait in response to different orthotic elements positioned under the first ray. A quasi-experimental, post-test design was conducted involving 22 participants (10 men and 12 women) diagnosed with flexible metatarsus primus elevatus. Each participant was evaluated using custom-made insoles incorporating various orthotic elements, while gait data were collected using a dynamometric platform during the mid-stance and propulsion phases. Significant gait-phase-dependent force alterations were observed. A cut-out (E) reduced medio-lateral forces during propulsion (p < 0.05), while a kinetic wedge (F) was correlated with late-stance stability (r = −0.526). The foot posture index (FPI)/body mass index (BMI) mediated the vertical forces. The effect sizes reached 0.45–0.42 for antero-posterior force modulation. Phase-targeted orthoses (a cut-out for propulsion, a kinetic wedge for late stance) and patient factors (FPI/BMI) appear to promote biomechanical efficacy in metatarsus primus elevatus, enabling personalized therapeutic strategies. Full article

With the rapid development of wearable electronics, traditional rigid thermal management materials face limitations in flexibility, conformability, and multi-physics adaptability. Low-dimensional carbon materials such as graphene and carbon nanotubes combine ultrahigh thermal conductivity with outstanding mechanical compliance, making them promising building blocks for flexible thermal regulation. This review summarizes recent advances in integrating these materials into textile architectures, mapping the evolution of this emerging field. Key topics include phonon-dominated heat transfer mechanisms, strategies for modulating interfacial thermal resistance, and dimensional effects across scales; beyond these intrinsic factors, hierarchical textile configurations further tailor macroscopic performance. We highlight how one-dimensional fiber bundles, two-dimensional woven fabrics, and three-dimensional porous networks construct multi-directional thermal pathways while enhancing porosity and stress tolerance. As for practical applications, the performance of carbon-based textiles in wearable systems, flexible electronic packaging, and thermal coatings is also critically assessed. Current obstacles—namely limited manufacturing scalability, interfacial mismatches, and thermal performance degradation under repeated deformation—are analyzed. To overcome these challenges, future studies should prioritize the co-design of structural and thermo-mechanical properties, the integration of multiple functionalities, and optimization guided by data-driven approaches. This review thus lays a solid foundation for advancing carbon-based smart textiles toward next-generation flexible thermal management technologies. Full article

The selective regulation of gene expression at the RNA level represents a rapidly evolving field offering substantial clinical potential. This review examines the molecular mechanisms of intracellular enzymatic systems that utilize single-stranded nucleic acids to downregulate specific RNA targets. The analysis encompasses antisense oligonucleotides and synthetic mimics of small interfering RNA (siRNA), microRNA (miRNA), transfer RNA-derived small RNA (tsRNA), and PIWI-interacting RNA (piRNA), elucidating their intricate interactions with crucial cellular machinery, specifically RNase H1, RNase P, AGO, and PIWI proteins, mediating their biological effects. The functional and structural characteristics of these endonucleases are examined in relation to their mechanisms of action and resultant therapeutic outcomes. This comprehensive analysis illuminates the interactions between single-stranded nucleic acids and their endonuclease partners, covering antisense inhibition pathways as well as RNA interference processes. This field of research has important implications for advancing targeted RNA modulation strategies across various disease contexts. Full article

The dual-active-bridge (DAB) converter has emerged as a promising topology for renewable energy applications and microgrid systems due to its high power density and bidirectional energy-transfer capability. Enhancing the overall efficiency and reliability of DAB converters requires the simultaneous realization of zero-voltage switching (ZVS) across all switches and the minimization of current stress over wide load and voltage ranges—two objectives that are often in conflict. Conventional modulation strategies with limited degrees of freedom fail to meet these dual goals effectively. To address this challenge, this paper introduces an enhanced integrated optimization strategy based on triple phase shift (EIOS-TPS). This approach formulates the power transmission requirement as an equality constraint and incorporates ZVS and mode boundary conditions as inequalities, resulting in a comprehensive optimization framework. Optimal phase-shift parameters are obtained using the Karush–Kuhn–Tucker (KKT) conditions. To mitigate zero-current switching (ZCS) under a light load and achieve full-range ZVS with reduced current stress, a modulation factor λ is introduced, enabling a globally optimized control trajectory. An experimental 1176 W prototype is developed to validate the proposed method, which achieves full-range ZVS while maintaining low current stress. In the low-power region, it improves efficiency by up to 2.2% in buck mode and 2.0% in boost mode compared with traditional control strategies, reaching a peak efficiency of 96.5%. Full article

Enhancing solar photovoltaic (PV) power generation is fundamental to achieving energy sustainability goals. However, elevated module temperatures can diminish photoelectric conversion efficiency and output power, impacting the safe and efficient operation of PV modules. Therefore, understanding module temperature distribution is crucial for predicting power generation performance and optimizing cleaning schedules in PV power plants. To investigate the combined effects of multiple factors on the temperature distribution and output power of dusty PV modules, a heat transfer model was developed. Validation against experimental data and comparisons with the NOCT model demonstrated the validity and advantages of the proposed model in accurately predicting PV module behavior. This validated model was then employed to simulate and analyze the influence of various parameters on the temperature of dusty modules and to evaluate the module output power, providing insights into sustainable PV energy generation. Results indicate that the attenuation of PV glass transmittance due to dust accumulation constitutes the primary determinant of the lower temperature observed in dusty modules compared to clean modules. This highlights a significant factor impacting long-term performance and resource utilization efficiency. Dusty module temperature exhibits a positive correlation with irradiance and ambient temperature, while displaying a negative correlation with wind speed and dust accumulation. Notably, alignment of wind direction and module orientation enhances module heat dissipation, representing a passive cooling strategy that promotes efficient and sustainable operation. At an ambient temperature of 25 °C and a wind speed of 3 m/s, the dusty module exhibits a temperature reduction of approximately 11.0% compared to the clean module. Furthermore, increasing the irradiance from 200 W/m² to 800 W/m² results in an increase in output power attenuation from 51.4 W to 192.6 W (approximately 30.4% attenuation rate) for a PV module with a dust accumulation of 25 g/m². This underscores the imperative for effective dust mitigation strategies to ensure long-term viability, economic sustainability, and optimized energy yields from solar energy investments. Full article