Search Results (4,819)

Upon the challenges of climate change and the demand for energy sustainability, nuclear power (NP) units not only provide clean electricity but are also equipped for cogeneration to achieve energy cascade utilization; this represents a key avenue for improving the overall efficiency and achieving the comprehensive utilization of nuclear energy. However, following the heating retrofitting stage, there exists a risk that the supply control valve of the unit may accidentally open completely during operation, which increases the risk of over-powering. Therefore, this study designs response schemes for second-generation large pressurized water reactor NP plants (NPPs) under the accidental full-open condition of the heat-supply control valve. Specifically, an integrated model encompassing the nuclear steam supply system, secondary circuit system, thermal energy supply system (TESS), and related control systems was constructed using the optimal estimation program and 3KeyMaster simulation platform. Subsequently, two response schemes were designed for the accidental full-open valve scenario under two operation modes—namely, the “Reactor Follows Turbine + TESS” and “Turbine Follows TESS” modes. Finally, on the basis of the established simulation platform, the scenario of accidental full opening of the heat-supply control valve was simulated and verified. Ultimately, the results indicate that the response scheme implemented under the “Turbine Follows TESS” mode is more effective in suppressing nuclear overpower when the heat supply control valve accidentally opens fully. Thus, overall, this study provides a feasible accident response strategy and critical technical reference for NPPs involving cogeneration and energy cascade utilization. Full article

Cadmium (Cd) is an environmental toxicant originating from both natural processes and human activities. Cd has been strongly associated with multiple diseases, including breast cancer (BC). Background/Objective: Environmental Cd exposure represents a significant contributor to BC onset and progression. Cd-induced breast carcinogenesis is driven by a constellation of molecular events, including DNA damage, oxidative stress (OS), and the dysregulation of key signaling pathways. These include the ERK/JNK/p38 MAPK cascade, the PI3K/AKT/mTOR axis, NF κB activation, and Wnt signaling, all of which collectively promote tumor initiation, survival, and metastasis. This review underscores the complex interplay between Cd exposure and its effects on cancer-triggering factors. Methods: The complexity of the mechanisms Cd-induced BC, underlying Cd-induced BC makes it challenging to treat, highlighting the need for novel therapeutic strategies that complement or enhance conventional chemotherapy. Therefore, this review was developed by reviewing the literature and presenting the different aspects of the challenge associated with Cd exposure and BC therapy. Results: Phytochemicals, especially phenolics, alkaloids, carotenoids, terpenoids, and related plant-derived compounds, have emerged as promising candidates for mitigating Cd-induced BC. Their antioxidants, anti-estrogenic, and anti-inflammatory properties position them as potential chemopreventive and therapeutic agents capable of counteracting Cd’s molecular toxicity. Conclusions: The review presents current evidence linking Cd exposure to BC development and highlights the protective potential of selected phytochemicals in preventing or attenuating Cd-induced BC. Understanding these interactions reinforces the importance of phytochemical-based interventions as a strategy to reduce Cd-related cancer risk and support breast health. Full article

Sepsis is a life-threatening syndrome caused by dysregulated host response to infection and remains a major global health challenge with high healthcare burden. Early recognition is critical for improving outcomes, yet current diagnostic tools and conventional biomarkers such as C-reactive protein and procalcitonin have important limitations related to kinetics, specificity, and cost. This review examines Monocyte Distribution Width (MDW), a novel hematologic parameter derived from routine complete blood count analysis, as an emerging biomarker for early sepsis detection and prognostic assessment. MDW reflects monocyte morphological heterogeneity associated with innate immune activation and rises early in the inflammatory cascade, often at the time of initial clinical presentation. Evidence from emergency department and intensive care unit studies demonstrates that MDW provides high sensitivity and negative predictive value for early sepsis screening and performs comparably to or better than established biomarkers, particularly when integrated with clinical scoring systems and other laboratory indices. Beyond diagnosis, elevated MDW correlates with disease severity, organ dysfunction, and adverse outcomes, suggesting prognostic utility. Although promising, current evidence is limited by heterogeneity and the need for standardized cut-off values and multicenter validation. Overall, MDW represents a rapid, cost-effective adjunct that may enhance multimodal sepsis assessment and clinical decision-making. Full article

The opportunistic pathogen Pseudomonas aeruginosa poses a serious threat to immunocompromised patients. Monosodium glutamate (MSG), a widely used flavor enhancer, has been reported to possess anti-inflammatory and antioxidant properties. However, its therapeutic potential and mechanism against Pseudomonas aeruginosa (P. aeruginosa) infection have remained unexplored. This study systematically elucidated the protective effects and molecular mechanisms of MSG against P. aeruginosa-induced acute lung injury (ALI). In a murine pneumonia model, MSG administration effectively alleviated lung pathological damage, edema, and inflammatory responses. Mechanistically, MSG exerted protection through a multifaceted strategy, including direct suppression of bacterial virulence via binding to PopB of T3SS inhibition of the TLR4/MyD88/MAPK-driven inflammatory cascade and pro-inflammatory cytokine production, enhancement of endogenous antioxidant defense (SOD, CAT), and reshaping of pulmonary macrophages from the M1 to M2 phenotype. Notably, the anti-virulence effect of MSG, achieved by binding to PopB (K_D = 3.52 × 10⁻⁶ M), presented a distinct advantage over traditional antimicrobials by potentially mitigating resistance development. Collectively, these findings indicated that MSG can alleviate ALI caused by P. aeruginosa infection. Full article

Osteoporosis (OP) is a metabolic bone disease characterized by reduced bone mass and impaired bone microarchitecture, significantly impacting patients’ quality of life. Stigmasterol (STG), a natural plant sterol, has been reported to possess multiple biological activities. However, its effects on OP bone formation and underlying molecular mechanisms remain unclear. The effects of STG on OP bone formation and potential mechanisms were investigated through in vivo and in vitro experiments combined with network pharmacology analysis. An OP model was established in ovariectomized (OVX) rats, and the bone-protective effects of STG were evaluated via micro-CT analysis and histological staining. In vitro experiments, MC3T3-E1 pre-osteoblasts were used to assess STG’s influence on osteogenic differentiation through Western blot analysis and ALP/ARS staining. Network pharmacology methods were used to predict potential targets and signaling pathways for STG in OP treatment, followed by mechanism validation. STG significantly improved bone microarchitecture in OVX rats, increased key osteogenic marker expression, and promoted MC3T3-E1 osteogenic differentiation in a dose-dependent manner. Network pharmacology analysis predicted 278 potential targets for STG in treating OP, with pathway enrichment analysis indicating significant involvement of the JAK/STAT pathway. Mechanistic studies revealed that STG promotes osteogenic differentiation by activating the JAK2/STAT3 signaling cascade. As an osteogenic promoter, STG effectively alleviates bone loss and enhances osteoblast differentiation by activating the JAK2/STAT3 signaling pathway. Full article

Epilepsy is a progressive network disorder in which recurrent seizures drive maladaptive neurodevelopmental remodeling, cognitive decline, and pharmacoresistance, particularly in developmental epileptic encephalopathies. Cannabidiol (CBD) has emerged as an evidence-based adjunctive therapy for selected childhood-onset epilepsies; however, its broader clinical utility remains limited by heterogeneous responsiveness, restricted indications, and an incomplete understanding of developmental stage–specific efficacy and safety. Here, we synthesize molecular, preclinical and clinical evidence supporting the pleiotropic antiseizure and neuroprotective actions of CBD, including modulation of endocannabinoid-related G protein–coupled receptors, adenosine signaling, transient receptor potential channels, GABAergic maturation, and neuroinflammatory cascades. We highlight critical neurodevelopmental windows during which timely CBD intervention may exert disease-modifying effects by preventing pathological consolidation of hyperexcitable networks. Furthermore, we position human brain organoids as transformative translational platforms that recapitulate early human cortical development and epileptic network dynamics, enabling functional stratification of CBD-responsive phenotypes, developmental safety profiling, and precision therapeutic discovery within human-relevant neural circuits. Collectively, organoid-guided frameworks provide a mechanistic foundation for personalized, developmentally informed CBD therapy and advance precision medicine strategies aimed at modifying epileptogenic trajectories rather than solely suppressing seizures. Full article

Fusarium ear rot (FER), caused by Fusarium verticillioides, is a devastating disease that substantially reduces maize yield and compromises kernel quality. To investigate the genetic and molecular basis of resistance, an F₂ population derived from a cross between the resistant inbred line 3IBZ2 and the susceptible inbred line KW5G321 was analysed. By integrating bulked segregant analysis sequencing (BSA-Seq) with RNA sequencing (RNA-Seq), a major quantitative trait locus (QTL), designated qFER4, was identified on chromosome 4. Genetic analysis further demonstrated that qFER4 confers resistance through partial dominance. Transcriptome profiling of the resistant line revealed 7684 and 7906 differentially expressed genes (DEGs) at 36 and 72 h post inoculation (hpi), respectively. These DEGs were significantly enriched in defence-related biological processes and pathways, including phenylpropanoid biosynthesis, jasmonic acid signalling, MAPK cascades, and plant-pathogen interactions. By combining QTL mapping with transcriptome analyses, four candidate genes within the qFER4 interval were screened. Sequence analysis identified extensive structural variations in the promoter and coding regions of Zm00001d053393, including a premature stop codon predicted to lead to a gain-of-function mutation. In contrast, the other three genes exhibited only minor promoter polymorphisms with identical coding sequences between the parental lines. Overall, this study identifies a novel major-effect QTL and candidate gene associated with FER resistance, providing a foundation for gene function and a valuable genetic resource for breeding FER-resistant maize varieties. Full article

This paper introduces a novel cascaded softsign function-based PID (CSoft-PID) controller designed for precise pressure regulation in highly nonlinear shell-and-tube steam condenser systems. For the first time in the literature, the classical PID control structure is enhanced through a cascaded nonlinear transformation using the softsign function, which dynamically adjusts the controller input according to the magnitude of the error. This architecture allows for high sensitivity near the setpoint while gracefully limiting excessive control efforts during larger deviations, thereby improving stability and transient performance. To optimally tune the six parameters of the proposed controller, a new hybrid optimization algorithm, termed hGASO-PS, is proposed. This method synergistically integrates an adaptive gbest-guided atom search optimization (ASO) strategy with the precision of the pattern search (PS) technique, ensuring both effective global exploration and fine-tuned local exploitation. The controller parameters are optimized by minimizing the integral of time-weighted absolute error (ITAE), subject to a step change in the condenser pressure setpoint. Extensive simulations and statistical evaluations demonstrate the superiority of the proposed approach. The hGASO-PS-based CSoft-PID controller achieved the lowest ITAE value of 2.1608, with an average of 2.2746 across 30 runs. It also demonstrated the fastest settling time (12.51 s) and the lowest overshoot (1.98%) among all tested controllers. Comparisons with recent PI, FOPID, and cascaded PI-PDN controllers confirm the consistent outperformance of the proposed method in both transient response and control precision, making it a promising candidate for industrial condenser applications. Full article

Background: Systemic inflammation is a key driver of heart failure (HF) progression across all ejection fraction (EF) phenotypes, with diet emerging as a modifiable factor influencing cardiac metabolism and inflammatory signaling. This narrative review integrates current evidence on the inflammatory mechanisms underlying HF, their links with common comorbidities and emerging anti-inflammatory therapeutic strategies, with a particular focus on the role of nutrition in supporting healthy cardiac metabolism. Methods: We searched MEDLINE/PubMed, EMBASE, Web of Science, the Cochrane Library, Scopus and reference lists of relevant publications using terms related to systemic inflammation, dietary patterns and HF prioritizing high-impact studies on nutrition–inflammation–HF interactions published from 2000 onward. Results: Major HF comorbidities sustain chronic, low-grade inflammation through elevated cytokine activity. Dietary patterns—especially those with high Dietary Inflammatory Index (DII)—substantially shape inflammatory milieu. The Mediterranean diet appears to have a favorable inflammatory profile with reduction in circulating pro-inflammatory biomarkers, especially C-reactive protein (CRP) and interleukin-6 (IL-6). Established therapies for HF with reduced ejection fraction and vagus nerve stimulation elicit anti-inflammatory efficacy through cytokine suppression. Sodium glucose cotransporter-2 (SGLT2) inhibitors demonstrate positive metabolic effects and anti-inflammatory actions through decrease in IL-6 and tumor necrosis factor-α (TNF-α). Interleukin-1 blockade has produced heterogeneous clinical outcomes, while definitive findings examining the role of IL-6 inhibitors in inflammation suppression and possible benefit on cardiac outcomes are anticipated. Preliminary data show the potential synergistic effects of dietary patterns/nutrients and pharmacological agents combination on improvement of endothelial function and attenuation of the fibrotic process, although there is a need for further research in large-scale trials. Conclusions: Systemic inflammation demonstrates a key role in HF initiation and progression, and the effect of diet on inflammatory pathways is central. Dietary patterns targeting inflammation-related mechanisms (inflammasome, gut dysbiosis) can lead to attenuation of systemic inflammatory response and restoration of cardiac metabolic flexibility. A deeper mechanistic discernment of cardiac inflammatory cascades, together with identification of HF subpopulations with excessive inflammatory activity, may facilitate the design of targeted randomized controlled trials (RCTs) aiming for novel personalized, inflammation-targeted HF therapies with potential clinical benefit. Full article

To mitigate the compliance deviation risk induced by wind power output fluctuations, this paper proposes a two-stage joint bidding model for cascaded hydropower–wind systems within the electricity spot market framework from a price-taker perspective, explicitly accounting for the decision maker’s risk preferences. To capture the impacts of hydropower vibration zones on joint bidding decisions, the feasible output range of hydropower units is divided into multiple safe operating sub-intervals, and vibration zone avoidance is modeled using binary decision variables; meanwhile, penalty terms are incorporated into the objective function to suppress vibration zone crossing behaviors. From a risk-aware decision-making perspective, Conditional Value-at-Risk (CVaR) is adopted to quantify the downside tail risk of bidding revenues, and a risk factor is introduced to flexibly adjust the decision maker’s risk attitude. Finally, a case study based on a cascaded hydropower system and an associated wind farm in Southwest China is conducted to demonstrate the effectiveness of the proposed joint bidding strategy and to examine the impacts of risk preferences and vibration zone considerations on joint bidding outcomes. Full article

Sea ice segmentation based on Synthetic Aperture Radar (SAR) images has become an important technical means for polar climate change monitoring and navigation safety guarantee. However, the existing methods have limitations in the utilization of SAR polarization information and the modeling of local diversity details of sea ice, which leads to insufficient segmentation, especially in complex ice-water boundary regions. To address these issues, this paper proposes a novel Polarization-Fused Edge-Enhanced UNet (PFEE-UNet) designed specifically for sea ice segmentation from high-resolution SAR images. Specifically, we design the Cross-Polarization Channel Interaction (CPCI) module, which employs a dual interaction strategy of hierarchical inter-group cascading and symmetric cross-fusion. This approach effectively leverages the complementary features of the HH and HV polarization channels, significantly enhancing the distinction between sea ice and open water. Additionally, we present the Dense–Sparse Diversity Enhancement (DSDE) module, which combines a spatial-channel joint attention mechanism to strengthen the model’s ability to capture spatial relationships within complex ice–water structures, effectively alleviating misclassifications caused by abrupt local texture changes. Finally, we design the Selective Edge Fusion (SEF) module, which dynamically selects and integrates multi-level edge features, improving the continuity of sea ice boundaries and preserving its morphological integrity. The experimental results show that the proposed PFEE-UNet model outperforms mainstream segmentation methods on the AI4Arctic/ASIP sea ice dataset, achieving an average Intersection over Union (IoU) of 84.48%, which surpasses existing methods such as HRNet (82.52%) and DeepLabv3+ (82.40%). Additionally, PFEE-UNet was applied for end-to-end ice–water segmentation on real-world Sentinel-1 SAR scenes, demonstrating its effectiveness and robustness for practical sea ice monitoring. Full article

The increasing penetration of wind energy is a key enabler of the global transition toward low-carbon and sustainable power systems. However, ensuring high efficiency, power quality, and operational reliability under variable wind and grid conditions remains a critical challenge for doubly fed induction generator (DFIG)-based wind energy conversion systems. Conventional direct power control (DPC) strategies based on proportional–integral (PI) regulators are simple and widely implemented, yet their performance degrades in the presence of nonlinear system dynamics, parameter uncertainties, and rapid wind speed fluctuations—factors that directly affect energy yield, component lifetime, and grid stability. To enhance the sustainability and resilience of wind power generation, this study proposes a cascaded neural network-based control architecture for DFIG-driven systems. The outer neural control loop regulates active and reactive power references to optimize energy capture and support grid requirements, while the inner neural loop ensures fast and precise tracking by generating appropriate control signals for the rotor-side converter. Leveraging their adaptive learning capability, the neural controllers effectively model nonlinear dynamics and compensate for uncertainties in real time. Compared with the conventional DPC-PI scheme, the proposed approach achieves improved dynamic response, reduced power and electromagnetic torque ripples, enhanced disturbance rejection, and greater robustness under varying wind and grid conditions. These improvements contribute to sustainable energy production by increasing conversion efficiency, reducing mechanical stress, minimizing maintenance requirements, and extending turbine service life. Furthermore, improved reactive power control enhances grid integration and supports stable operation in renewable-dominated power systems. Simulation results validate the superior performance of the cascaded intelligent control strategy. The findings demonstrate that advanced adaptive control techniques can play a significant role in strengthening the reliability, efficiency, and long-term sustainability of wind energy systems, thereby supporting global decarbonization goals and the broader transition to sustainable energy infrastructures. Future work will focus on real-time implementation, stability assessment, and experimental validation to facilitate practical deployment. Full article

Building extraction is a core task in the semantic segmentation of satellite remote sensing imagery. Conventional pixel-level segmentation methods often prioritize texture over geometric structure, resulting in suboptimal performance in complex scenes affected by illumination variations, shadows, and scale changes. In this article, an innovative object-level building extraction approach is introduced to better capture the geometric structure of buildings, which incorporates superpixel segmentation to represent images as a set of adjacent regions. The proposed model consists of a cascade multi-scale fusion module (CMSFM) that progressively integrates contextual information across different receptive fields, along with a boundary-assisted loss function designed to enhance edge delineation and improve object-level accuracy. The experimental results on the WHU building dataset and the Massachusetts Buildings Dataset show that the proposed method notably outperforms other representative semantic segmentation approaches, such as FCN, UNet, DeepLab V3, and SETR. On the WHU dataset, MRLNet achieves the largest MIoU of 90.14% and the highest F1 score of 92.47%. On the Massachusetts Buildings Dataset, MRLNet attains the best MIoU of 83.14% and the highest F1 score of 90.46%. In addition, our building extraction model achieves a substantial performance improvement after the addition of the CMSFM module and the boundary-assisted loss function, demonstrating the effectiveness of these two enhancements used in our proposed model. It is expected that this research can provide a promising tool for the accurate extraction of buildings using satellite remote sensing images, which is indispensable in urban planning, disaster assessment, and other fields. Full article

To address the state-of-charge (SOC) imbalance and the limited convergence speed of conventional SOC balancing strategies in cascaded power conversion systems (PCSs) under practical grid-connected conditions, this paper investigates the control of cascaded H-bridge energy storage converters under multiple operating scenarios. The three-phase cascaded H-bridge topology is first reviewed, followed by the development of a hierarchical control framework for the cascaded PCSs. The corresponding overall control block diagram is then presented. Based on this, a unified power equalization control strategy based on the third harmonic injection is proposed, which ensures the effectiveness of power control, SOC equalization control, and fault-tolerant control by increasing the injection range, and it guarantees the normal operation of the cascaded PCSs. Considering the phase relationship of the PCS output voltage after the third harmonic injection, the maximum zero-sequence voltage injection range is found, and the constraints of zero-sequence voltage injection are derived. A MATLAB/Simulink simulation model and a real-time hardware-in-the-loop (HIL) platform based on the MT6016 are established to validate the effectiveness and practical feasibility of the proposed control strategy. Full article

Gas turbine engines operate in extremely harsh environments, subjecting turbines to high aerodynamic and thermal loads. In this context, non-axisymmetric endwalls have emerged as an effective strategy for reducing aerodynamic losses and mitigating heat transfer on the endwall surfaces, leading to their widespread adoption in turbine designs. This study presents an optimization of the endwall shape for a turbine guide vane from a real engine, employing the multi-island genetic algorithm. The optimization objectives are the endwall surface heat transfer coefficient and the total pressure loss coefficient at the blade outlet. The findings indicate that the modified endwall disrupts the horseshoe vortex structure at the blade leading edge, adversely influencing the formation and development of passage vortices within the cascade. Notably, this modification results in a significant reduction in aerodynamic losses and a decrease in the heat transfer coefficient on the endwall surface. Specifically, the total pressure loss coefficient at the outlet is reduced by 1.96%, while the endwall surface heat transfer coefficient decreases by 3.05%. These results underscore the considerable effectiveness of the optimized endwall design in enhancing turbine performance. Full article