Search Results (408,702)

Background/Objectives: To assess the impact of the 2023 FIGO staging revision on stage distribution, survival outcomes, and prognostic performance in endometrial cancer compared to the 2009 system. Methods: This retrospective cohort study analyzed 2969 patients with FIGO 2009 stage I–III endometrial cancer diagnosed at Samsung Medical Center (1994–2023). Patients were reclassified per the 2023 FIGO system. Stage migration, progression-free survival (PFS), and overall survival (OS) were evaluated. Prognostic performance was compared using the Akaike information criterion (AIC), Bayesian information criterion (BIC), concordance index (C-index), and area under the receiver operating characteristic curve (AUC). Results: Stage migration occurred in 20.2% of patients, with 98.3% involving upstaging from FIGO 2009 stage I, largely due to the inclusion of aggressive histology, p53 abnormality, and substantial lymphovascular space invasion (LVSI). The proportion of stage I tumors decreased from 81.5% to 65.2%, while stage II increased to 21.9%, including 14.8% newly classified as stage IIC. Patients remaining in stage I showed favorable outcomes (5-year PFS: 95.3%, OS: 98.5%), whereas those upstaged—especially to stage IIC—had significantly worse outcomes (5-year PFS: 76.5%, OS: 83.1%). Tumors with p53 abnormalities had poorer survival (PFS: 70.8%, OS: 76.6%). The 2023 FIGO system outperformed the 2009 system in prognostic discrimination across all metrics. Conclusions: The FIGO 2023 staging revision improves prognostic accuracy in endometrial cancer by integrating histopathologic and molecular risk factors. These refinements enhance risk stratification and may support more individualized treatment strategies. Full article

The four-quadrant wind imaging interferometer achieves wind field measurement by acquiring interferograms of the target scene in four distinct phase states while maintaining identical radiation intensity. This unique operational principle endows the system with notable advantages, including low sensitivity to temporal variations of the light source and exceptional compactness in instrument design. This paper proposes a step-free, four-quadrant, stepped-phase coating technique, which is applicable to an all-solid-state wind imaging interferometer scheme while offering advantages such as high reflectivity and improved stepped-phase precision for quadrants of wind imaging interferometers. Beginning with the underlying principles, we provide a detailed analysis of the four-quadrant material selection and coating architecture. This is followed by computer-aided thin-film design and simulation for verification. Full article

Agrivoltaic technology holds great significance for promoting the collaborative development of new energy industries and modern agriculture. A systematic optimization design and preliminary electrical scheme for a 50 MW agrivoltaic power station in Shaanxi Province, China, were studied in this work. A combination of checkerboard and long-row layouts was adopted, considering the influence of the shading rate on agricultural production and photovoltaic power generation. The checkerboard pattern features the highest system efficiency, the smallest irradiance loss, and a slight lead in power generation, with a moderate shading rate, when compared to the other patterns. The expected energy gain from the bifacial modules’ rear side in this specific setup is 7.6%. These layouts ensure the power generation efficiency of the photovoltaic power station, while minimizing the shading impact of shading on crop growth, thereby achieving efficient comprehensive utilization of agricultural greenhouses and solar power generation. The primary electrical system was designed, including the main wiring design, main transformer selection, and type selection of major electrical equipment. The research results provide a practical reference for the large-scale application of agrivoltaic power stations, which is beneficial to promoting the high-quality development of modern agriculture. Full article

With the implementation of China’s “dual carbon” strategy, the installed capacity of new energy has grown rapidly. Wind power and photovoltaic power have accounted for more than 40%, but the integration of power electronic apparatus into the grid has resulted in the manifestation of a system with “low inertia and weak damping”, which can easily lead to transient overvoltage problems at transmitters when high-voltage direct-current (HVDC) latching faults occur. Although a variety of dynamic reactive power optimization strategies have been proposed in the existing research, most of them are aimed at single equipment, and multi-reactive power source collaborative control schemes are lacking. In this paper, we innovatively establish a transient voltage analysis model for a new energy transmitter, derive the expression of overvoltage amplitude, and propose a method for the construction of a multi-reactive source collaborative optimization model, which can effectively suppress transient overvoltage through capacity and initial output configuration. We provide a new idea for the safe operation of a significant percentage of new energy grids. The case analysis shows that the co-optimization method outlined in this paper is an effective solution to suppress the transient overvoltage triggered by AC faults and has wide application value. Full article

The safe and stable operation of critical substation equipment is paramount to the power system, and its intelligent inspection relies on highly efficient and accurate object detection technology. However, the demanding requirements for both accuracy and efficiency in complex environments pose significant challenges for lightweight models. To address this, this paper proposes SD-FINE, a lightweight object detection technique specifically designed for detecting critical substation equipment. Specifically, we introduce a novel Fine-grained Distribution Refinement (FDR) approach, which fundamentally transforms the bounding box regression process in DETR from predicting coordinates to iteratively optimizing edge probability distributions. Central to the new FDR is an adaptive weight function learning mechanism that learns weights for these distributions. This mechanism is designed to enhance the model’s perception capability regarding equipment location information within complex substation environments. Additionally, this paper develops a new Efficient Hybrid Encoder that provides adaptive scale weighting for feature information at different scales during cross-scale feature fusion, enabling more flexible and efficient lightweight feature extraction. Experimental validation on a critical substation equipment detection dataset demonstrates that SD-FINE achieves an accuracy of 93.1% while maintaining model lightness. It outperforms mainstream object detection networks across various metrics, providing an efficient and reliable detection solution for intelligent substation inspection. Full article

Agroforestry landscape has undergone changes, namely land abandonment, which when combined with negative attitudes towards fire, is associated with the eradication of agroforestry leftovers and acts towards the proliferation of fires, threatening sustainability concerns. Agroforestry leftovers recovery presents high potential to act on this problem; however, the logistical costs associated with the recovery chain make it unfeasible. The lack of coordination/transparency between stakeholders is one of the main explanations for these costs. This study develops a digital tool to enhance the residual biomass supply chain for energy recovery and fire risk mitigation. In addition to this concept, this work also proposes conceptual models and a prototype, two essential contributions to software development. Methodologically, this study consulted 10 experts to validate a concept previously presented in the literature, supplemented with UML modeling and prototyping with Figma^®. The main results point to the creation of a disruptive concept that will allow access to information/transparency about agroforestry services, with the goal that this will improve the functioning of the RBSC, resulting in a reduction in fire risk and, consequently, improvements in sustainability concerns associated with this hazard. Full article

The photonic spin Hall effect (PSHE) has emerged as a powerful metrological approach for precision measurements. Dynamic manipulation of PSHE through external stimuli could substantially expand its applications. In this work, we present a simple and active modulation scheme for PSHE in a surface plasmon resonance (SPR) structure by exploiting electric-field-tunable refractive indices of electro-optic materials. By applying an electric field, the enhancement of PSHE spin shifts is observed, and the dual-field control can further amplify these spin shifts through synergistic effects in this SPR structure. Notably, various operation modes of external electric field enable the real-time switching between two high-performance sensing functionalities (refractive index detection and angle measurement). Therefore, our designed PSHE sensor based on SPR structure with a simple structure of only three layers not only makes up for the complex structure in multi-functional sensors, but more importantly, this platform establishes a new paradigm for dynamic PSHE manipulation while paving the way for advanced multi-functional optical sensing technology. Full article

Soft robot motion performance has long been a core focus in scientific research. This study investigates the motion capabilities of soft robots constructed using poly(N-isopropylacrylamide) (PNIPAM) hydrogels, with key innovations in material design and functional enhancement. By optimizing the hydrogel formulation and incorporating molybdenum disulfide (MoS₂) to endow it with photothermal response properties, the material achieves muscle-like controllable contraction and expansion deformation—a critical breakthrough in mimicking biological motion mechanics. Building on this material advancement, the research team developed a series of soft robotic prototypes to systematically explore the hydrogel’s motion characteristics. A flytrap-inspired soft robot demonstrates rapid opening–closing movements, replicating the swift responsiveness of natural carnivorous plants. For terrestrial locomotion, a hexapod crawling robot utilizes the photo-induced stretch-recovery mechanism of both horizontally configured and pre-bent feet to achieve stable directional propulsion. Most notably, a magnetically driven rolling robot integrates magnetic units to realize versatile multimodal movement: it achieves a stable rolling speed of 1.8 cm/s across flat surfaces and can surmount obstacles up to 1.5 times its own body size. This work not only validates the strong potential of PNIPAM hydrogel-based soft robots in executing complex motion tasks but also provides valuable new insights for the development of multimodal soft robotic systems, paving the way for future innovations in adaptive and bio-inspired robotics. Full article

Purpose: We previously reported that the systemic administration of preprogrammed mouse hematopoietic bone marrow-derived progenitor cells (HSPCs) improved visual function and restored a functional retinal pigment epithelial (RPE) layer. Here, we investigated the potential impact of donor vs. host age on systemic cellular therapy in a murine model of retinal degeneration. Methods: HSPCs from young (8 weeks) and old (15 months) mice were programmed ex vivo with a lentiviral vector expressing the RPE65 gene (LV-RPE65) and systemically administering into young or old SOD2 KD mice. Visual loss and pathological changes were evaluated by electroretinogram (ERG), optical coherence tomography (OCT), histology, and immunohistochemistry. Results: Old donor HSPCs administered to old manganese superoxide dismutase (SOD2) knockdown (KD) recipient mice offered the least benefit. This was exemplified by the reduced recruitment and incorporation of LV-RPE65 HSPC into the RPE layer, as well as decreased improvement in visual function, retinal thinning, and limited reduction in oxidative damage and microglial activation. LV-RPE65 HSPC from young mice incorporated into the RPE layer of old SOD2 KD mice, though to a lesser extent than young cells administered to young hosts, offered some level of protection. By contrast, LV-RPE65 HSPCs from old mice, located to the subretinal space of young host mice, reduced visual loss, although some retinal pathology was observed. Conclusions: The administration of LV-RPE65 HSPC from old donors to old SOD2 KD mice offered the least improvement. Translational Relevance: Our findings highlight how both donor and recipient age impact the success of HSPC-based retinal therapy and using cells from aged donors for AMD treatment may have some limitations. Full article

As the core component of aircraft systems, aeroengines require accurate Remaining Useful Life (RUL) prediction to ensure flight safety, which serves as a key part of Prognostics and Health Management (PHM). Traditional RUL prediction methods primarily fall into two main categories: physics-based and data-driven approaches. Physics-based methods mainly rely on extensive prior knowledge, limiting their scalability, while data-driven methods (including statistical analysis and machine learning) struggle with handling high-dimensional data and suboptimal modeling of multi-scale temporal dependencies. To address these challenges and enhance prediction accuracy and robustness, we propose a novel hybrid deep learning framework (CLSTM-TCN) integrating 2D Convolutional Neural Network (2D-CNN), Long Short-Term Memory (LSTM) network, and Temporal Convolutional Network (TCN) modules. The CLSTM-TCN framework follows a progressive feature refinement logic: 2D-CNN first extracts short-term local features and inter-feature interactions from input data; the LSTM network then models long-term temporal dependencies in time series to strengthen global temporal dynamics representation; and TCN ultimately captures multi-scale temporal features via dilated convolutions, overcoming the limitations of the LSTM network in long-range dependency modeling while enabling parallel computing. Validated on the NASA C-MAPSS data set (focusing on FD001), the CLSTM-TCN model achieves a root mean square error (RMSE) of 13.35 and a score function (score) of 219. Compared to the CNN-LSTM, CNN-TCN, and LSTM-TCN models, it reduces the RMSE by 27.94%, 30.79%, and 30.88%, respectively, and significantly outperforms the traditional single-model methods (e.g., standalone CNN or LSTM network). Notably, the model maintains stability across diverse operational conditions, with RMSE fluctuations capped within 15% for all test cases. Ablation studies confirm the synergistic effect of each module: removing 2D-CNN, LSTM, or TCN leads to an increase in the RMSE and score. This framework effectively handles high-dimensional data and multi-scale temporal dependencies, providing an accurate and robust solution for aeroengine RUL prediction. While current performance is validated under single operating conditions, ongoing efforts to optimize hyperparameter tuning, enhance adaptability to complex operating scenarios, and integrate uncertainty analysis will further strengthen its practical value in aircraft health management. Full article

RMB₆-TMB₂ (RM = rare earth elements, TM = transition metal elements) composites retain superior field emission properties of RMB₆ while addressing its inherent mechanical limitations by constructing a eutectic structure with TMB₂. Herein, an in situ route for synthesizing RMB₆-TMB₂ composite nanopowders with homogeneous phase distribution using reduction reactions was proposed. The LaB₆-ZrB₂ composite nanopowders were synthesized in situ for the first time using sodium borohydride (NaBH₄) as both a reducing agent and boron source, with lanthanum oxide (La₂O₃) and zirconium dioxide (ZrO₂) serving as metal sources. The effects of the synthesis temperature on phase compositions and microstructure of the composites were systematically investigated. The LaB₆-ZrB₂ system with a eutectic weight ratio exhibited an accelerated reaction rate, achieving a complete reaction at 1000 °C, 300 °C lower than that of single-phase ZrB₂ synthesis. The composite phases were uniformly distributed even at nanoscale. The composite powder displayed an average particle size of ~170 nm when synthesized at 1300 °C. With the benefit of the in situ synthesis method, LaB₆-TiB₂, CeB₆-ZrB₂, and CeB₆-TiB₂ composite powders were successfully synthesized. This process effectively addresses phase separation and contamination issues typically associated with traditional mixing methods, providing a scalable precursor for high-performance RMB₆-TMB₂ composites. Full article

The addition of organic carbon sources in biofloc technology (BFT) systems promotes microbial community development, enhancing water quality, nutrient recycling, and supplemental feeding through microbial biomass. These characteristics make BFT a viable strategy for the cultivation of promising aquaculture species, such as Mugil cephalus. This study evaluated the effects of three carbon sources—unrefined cane sugar (locally known as chancaca), refined sucrose, and beet molasses—on water quality and growth performance of M. cephalus juveniles reared in a BFT system. Juvenile mullets (4.33 ± 2.09 g) were cultured for 45 days at a stocking density of 0.03 ± 0.01 kg·m⁻³, with biofloc pre-matured in ex situ tanks. Most water quality parameters showed no significant differences among treatments (p > 0.05), except for nitrite concentrations, which were significantly higher in the sucrose group (p < 0.05). The highest growth performance was observed in the sucrose treatment, with a weight gain (WG) of 4.26 ± 0.51 g, an average daily weight gain (AWG) of 0.09 ± 0.01 g, and a thermal growth coefficient (GF3) of 1.27 ± 0.15 at a constant temperature of 24 °C. Bromatological analysis of bioflocs revealed significantly higher crude protein (CP: 9.8%) and energy content (Kcal·100 g⁻¹: 3.44 ± 0.2) in the sucrose treatment compared to chancaca (CP: 5.1%). These findings confirm that M. cephalus can be effectively cultured in BFT systems using simple carbon sources. Refined sucrose, due to its high solubility and nutritional contribution to biofloc formation, is recommended for improving growth performance and system efficiency in M. cephalus production. Full article

In the evolving discourse of affective urbanism, emotions are increasingly recognized as fundamental, systemic drivers shaping the social, perceptual, and symbolic dimensions of urban space. Meanwhile, advances in visual technologies and media aesthetics have transformed contemporary cities into visually saturated environments, where visual cues actively influence how urban space is perceived, navigated, and emotionally experienced. While prior research has addressed affective belonging and spatial identity, these studies often treat emotion and visual design as separate influences rather than examining their interdependent, systemic roles. To address this gap, this study develops an emotion-driven systemic model to analyze how visual design activates affective pathways that contribute to the sustainable construction of place branding. Drawing on survey data from 134 residents in Wuxi, China, we employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine the interrelations among emotionally durable visual design, urban emotion, and place branding. The results reveal that visual attachment design (VAD) significantly strengthens place branding through emotional mediation, while visual behavior design (VBD) directly enhances sustainable branding by fostering participatory engagement even without emotional mediation. In contrast, visual function design (VFD) demonstrates limited impact, underscoring its insufficiency as a stand-alone strategy. These findings underscore the value of modeling emotionally durable visual communication as a system that links emotion, behavior, and identity in citizen-centered place branding. Full article

During the last decade, artificial intelligence (AI) has enabled key technological innovations within the modern dementia and frailty healthcare and prevention landscape. This has boosted the impact of technology in the clinical setting, enabling earlier diagnosis with improved specificity and sensitivity, leading to accurate and time-efficient support that has driven the development of preventative interventions minimizing the risk and rate of progression. Background/Objectives: The rapid ageing of the European population places a substantial strain on the current healthcare system and imposes several challenges. COMFORTage is the joint effort of medical experts (i.e., neurologists, psychiatrists, neuropsychologists, nurses, and memory clinics), social scientists and humanists, technical experts (i.e., data scientists, AI experts, and robotic experts), digital innovation hubs (DIHs), and living labs (LLs) to establish a pan-European framework for community-based, integrated, and people-centric prevention, monitoring, and progression-managing solutions for dementia and frailty. Its main goal is to introduce an integrated and digitally enabled framework that will facilitate the provision of personalized and integrated care prevention and intervention strategies on dementia and frailty, by piloting novel technologies and producing quantified evidence on the impact to individuals’ wellbeing and quality of life. Methods: A robust and comprehensive design approach adopted through this framework provides the guidelines, tools, and methodologies necessary to empower stakeholders by enhancing their health and digital literacy. The integration of the initial information from 13 pilots across 8 European countries demonstrates the scalability and adaptability of this approach across diverse healthcare systems. Through a systematic analysis, it aims to streamline healthcare processes, reduce health inequalities in modern communities, and foster healthy and active ageing by leveraging evidence-based insights and real-world implementations across multiple regions. Results: Emerging technologies are integrated with societal and clinical innovations, as well as with advanced and evidence-based care models, toward the introduction of a comprehensive global coordination framework that: (a) improves individuals’ adherence to risk mitigation and prevention strategies; (b) delivers targeted and personalized recommendations; (c) supports societal, lifestyle, and behavioral changes; (d) empowers individuals toward their health and digital literacy; and (e) fosters inclusiveness and promotes equality of access to health and care services. Conclusions: The proposed framework is designed to enable earlier diagnosis and improved prognosis coupled with personalized prevention interventions. It capitalizes on the integration of technical, clinical, and social innovations and is deployed in 13 real-world pilots to empirically assess its potential impact, ensuring robust validation across diverse healthcare settings. Full article

Background and Clinical Significance: Acquired angioedema (AAE) is a rare and potentially life-threatening condition characterized by acquired deficiency of C1-inhibitor (C1-INH) resulting in hyperactivation of the classical complement pathway. AAE occurs in association with malignancies or autoimmune diseases. Infectious triggers are rarely encountered, and the underlying mechanisms have yet to be completely clarified. Case Presentation: This case involves a previously healthy 19-year-old male who was admitted with Mycoplasma pneumonia and oral ulcers, subsequently developing unilateral facial angioedema. Laboratory studies demonstrated reduced C4, decreased levels and activity of C1-INH, and reduced C1q, all consistent with acquired C1-INH deficiency. These findings were attributed to the presence of cold agglutinins, which are frequently observed in Mycoplasma pneumoniae infections. Following treatment with icatibant, a bradykinin B2 receptor antagonist, the patient’s angioedema resolved rapidly. An exhaustive workup found no evidence of underlying systemic disorders, and the patient did not experience any angioedema attacks following resolution of the infection. Conclusions: The presence of cold agglutinins, commonly associated with Mycoplasma infections, can precipitate a decline in C1-INH levels, resulting in complement pathway dysregulation. This disruption leads to an excess of bradykinin, followed by increased vascular permeability and localized edema. Full article