Explore the vast range of titles available.

Object detection in low-light environments is often hampered by unfavorable factors such as low brightness, low contrast, and noise, which lead to issues like missed detections and false positives. To address these challenges, this paper proposes a low-light object detection algorithm named Dark-YOLO, which dynamically extracts features. First, an adaptive image enhancement module is introduced to restore image information and enrich feature details. Second, the spatial feature pyramid module is improved by incorporating cross-overlapping average pooling and max pooling to extract salient features while retaining global and local information. Then, a dynamic feature extraction module is designed, which combines partial convolution with a parameter-free attention mechanism, allowing the model to flexibly capture critical and effective information from the image. Finally, a dimension reciprocal attention module is introduced to ensure the model can comprehensively consider various features within the image. Experimental results show that the proposed model achieves an mAP@50 of 71.3% and an mAP@50-95 of 44.2% on the real-world low-light dataset ExDark, demonstrating that Dark-YOLO effectively detects objects under low-light conditions. Furthermore, facial recognition in dark environments is a particularly challenging task. Dark-YOLO demonstrates outstanding performance on the DarkFace dataset, achieving an mAP@50 of 49.1% and an mAP@50-95 of 21.9%, further validating its effectiveness for face detection under complex low-light conditions.

To enhance the sustainable power regulation capability of hydroelectric unit regulation systems (HURS) under modern power system requirements, this paper proposes an optimal linear quadratic regulator (LQR)-based power control strategy optimized using an improved Salp Swarm Algorithm (ISSA). First, comprehensive mathematical models of the hydraulic, mechanical, and electrical subsystems of HURS are established, enabling a unified state-space representation suitable for LQR controller design. Then, the weighting matrices of the LQR controller are optimally tuned via ISSA using a hybrid objective function that jointly considers dynamic response performance and control effort, thereby contributing to improved energy efficiency and long-term operational sustainability. A large-scale hydropower unit operating under weakly stable conditions is selected as a case study. Simulation results demonstrate that, compared with conventional LQR tuning approaches, the proposed ISSA-LQR controller achieves faster power response, reduced overshoot, and enhanced robustness against operating condition variations. These improvements effectively reduce unnecessary control actions and mechanical stress, supporting the reliable and sustainable operation of hydroelectric units. Overall, the proposed method provides a practical and effective solution for improving power regulation performance in hydropower plants, thereby enhancing their capability to support renewable energy integration and contribute to the sustainable development of modern power systems.

Colorectal cancer (CRC) poses a threat to the health of people worldwide. Long noncoding RNAs (lncRNAs) have been reported to play a key role in regulating carcinogenesis, including CRC. In this study, the levels of lncRNA FOXP4-AS1 were analyzed in CRC specimens and cells via qRT-PCR. The impacts of FOXP4-AS1 on CRC cell metastasis were investigated. Then, the silver staining assay, western blot, RIP, Co-IP, and immunofluorescence were conducted to explore and validate the molecular mechanisms by which FOXP4-AS1 affects CRC progression. We discovered that FOXP4-AS1 expression was markedly elevated in CRC. Functionally, FOXP4-AS1 knockdown suppressed CRC cell migration, invasion, and EMT. Also, FOXP4-AS1 silencing weakened CRC tumor growth in vivo. Mechanistically, we identified that FOXP4-AS1 functioned as a scaffold to simultaneously bind USP7 and ZEB1, and regulated the ubiquitination and expression of ZEB1 by binding to USP7. Rescue experiments demonstrated that USP7 inhibitor P005091 abolished the promotion of cell metastasis by FOXP4-AS1 overexpression. Furthermore, ZEB1 overexpression reversed the impact of silencing FOXP4-AS1 on cell metastasis. Collectively, our work revealed the molecular mechanism and role of FOXP4-AS1-mediated USP7-ZEB1 axis in CRC.

Wastewater reclamation has gradually become an important way to cope with the global water crisis. Ultrafiltration plays an imperative part as a safeguard for the aim but is often limited by membrane fouling. Effluent organic matter (EfOM) has been known to be a major foulant during ultrafiltration. Hence, the primary aim of this study was to investigate the effects of pre-ozonation on the membrane fouling caused by EfOM in secondary wastewater effluents. In addition, the physicochemical property changes of EfOM during pre-ozonation and the subsequent influence on membrane fouling were systemically investigated. The combined fouling model and the morphology of fouled membrane were adopted to scrutinize the fouling alleviation mechanism by pre-ozonation. It was found that membrane fouling by EfOM was dominated by hydraulically reversible fouling. In addition, an obvious fouling reduction was achieved by pre-ozonation with 1.0 mg O3/mg DOC. The resistance results showed that the normalized hydraulically reversible resistance was reduced by ~60%. The water quality analysis indicated that ozone degraded high molecular weight organics such as microbial metabolites and aromatic protein and medium molecular weight organics (humic acid-like) into smaller fractions and formed a looser fouling layer on the membrane surface. Furthermore, pre-ozonation made the cake layer foul towards pore blocking, thereby reducing fouling. In addition, there was a little degradation in the pollutant removal performance with pre-ozonation. The DOC removal rate decreased by more than 18%, while UV254 decreased by more than 20%.

Whether the phosphorus removal chemical in wastewater treatment plants (WWTPs) can be accurately dosed not only affects the compliance of the effluent total phosphorus but also has a huge impact on sludge production and energy consumption during the wastewater treatment process. For the effluent from the secondary sedimentation tank of a wastewater treatment plant in southern China, based on experimental screening of the optimal pH value, chemical types and concentrations of chemicals, coagulation time, etc., a dynamic dosage prediction feedforward model for chemical phosphorus removal agents in the effluent from the secondary sedimentation tank of the WWTPs was developed to predict the most economical dosage of the chemicals. Meanwhile, combined with the adaptive fuzzy neural network P feedback control algorithm, dynamic real-time control of chemical dosing was achieved. Through micro-control design, a software model for signal collection and feedback in a specific phosphorus removal scenario was formed, and an automatic control system for chemical dosing was ultimately developed for a WWTP in a city in southern China. After stable operation for two months, the system achieved a 100% compliance rate for effluent total phosphorus (TP) concentration and a 67% improvement in effluent stability, helping the wastewater treatment plant achieve stable and precise control of the phosphorus removal process in the secondary sedimentation tank effluent, which is conducive to further promoting its implementation of low-carbon pathways.

Global mega-bay systems are experiencing intensive estuarine engineering (e.g. dredging and reclamation), yet the compound effects and underlying mechanisms driving flood risk amplification remain insufficiently quantified. This study investigates flood risk changes in the Bay-Inlet-Channel system of China's Greater Bay Area (ranked as the world's fourth largest mega-bay) through extreme value analysis of 1965-2017 water level records using generalized extreme value (GEV) theory and max-stable process modelling. Our results demonstrate spatially heterogeneity in flood risk trends, with differential extreme water level rise changes: 0.22 cm/yr at the bay mouth, 0.65 cm/yr in the inner bay, and 0.56 cm/yr in the upper tidal reach (Shiziyang), coinciding with a risk escalation from Category II (strong) to Category I (extreme). Hydrodynamic analysis reveals that deposition-induced tidal range attenuation at the bay mouth partially moderates flood risk acceleration, whereas synergistic effects of erosional dredging and convergent reclamation amplify both tidal and surge dynamics, consequently exacerbating flood risk in the inner bay, with the tidal reach exhibiting intermediate trends due to energy dissipation through Humen Inlet. Numerical simulations quantify maximum impacts on extreme high water levels, with 9.61% rising associated with slower-propagating waves from reclamation and 3.33% decreased with faster-propagating waves induced by dredging. Projections under SSP5-8.5 sea-level rise scenarios indicate that extreme high water levels will surpass optimized 300-yr return levels defense standards by 2080 (outer bay), 2090 (inner bay), and 2100 (tidal reach). These findings provide critical insights into global flood risk management in engineered mega-bay systems and advance methodological frameworks for extreme water level assessment.

Extreme storm tide levels, arising from nonlinear cross−scale interactions among surge, astronomical tide, and fluvial flood, threaten estuarine stability and cause major economic losses. The Bay-Inlet-Channel (BIC) system, pivotal to the Greater Bay Area, was severely impacted by Typhoon Hato, which produced record−breaking winds and severe inundation. To quantify the morphological-hydrodynamic resilience of the BIC system against the highest storm tide level (HSTL), the Delft3D model was employed to reproduce characteristics of Hato. Simulation results indicate that HSTL exhibited a sharp gradient along the Bay, with a relative increase of 63.84%, and a more moderate one in the Channel (37.00%), associated with the Channel’s higher resilience ( R G  = 0.87). Under a hypothetical “Triple Coincidence” scenario involving a stronger flood discharge, the robustness of the BIC system decreased, with a more pronounced decline for the Channel (Δ R G = −0.23) than for the Bay. Contribution analysis identified surge as the dominant driver of HSTL during Hato (52–75%), followed by astronomical tide (25–51%), nonlinear interactions (−7–6%), and flood (<2%). Surge dominance diminished under “Triple Coincidence” as nonlinear interactions intensified. Momentum and energy analyses showed that lateral HSTL differences were primarily governed by direct wind stress, while longitudinal variations were modulated by morphological heterogeneity. Stronger floods amplified HSTL unevenly, mainly through enhanced nonlinear convection. These discoveries advanced the understanding of the morphological-hydrodynamic resilience and its mechanism regulating HSTL in estuarine systems, providing insights for storm tide risk management.

( ) commonly induces refractory infection due to its multidrug-resistant nature. To date, there have been no reports on the application of phage treatment for infection. This study was conducted to explore the feasibility of phage application in treating refractory infection by collaborating with a 59-year-old male patient with a pulmonary infection of multidrug-resistant Our experiments included three domains: ) selection of the appropriate phage, ) verification of the efficacy and safety of the selected phage, ) confirmation of phage-bacteria interactions. Our results showed that phage Spe5P4 is appropriate for infection. Treatment with phage Spe5P4 showed good efficacy, manifested as amelioration of symptoms, hydrothorax examinations, and chest computed tomography findings. Phage treatment did not worsen hepatic and renal function, immunity-related indices, or indices of routine blood examination. It did not induce or deteriorate drug resistance of the involved antibiotics. Importantly, no adverse events were reported during the treatment or follow-up periods. Thus, phage treatment showed satisfactory safety. Finally, we found that phage treatment did not increase the bacterial load, cytotoxicity, virulence, or phage resistance of indicating satisfactory phage-bacteria interactions between Spe5P4 and , which are useful for the future application of phage Spe5P4 against This work provides evidence and a working basis for further application of phage Spe5P4 in treating refractory infections. We also provided a methodological basis for investigating clinical application of phage treatment against multidrug-resistant bacterial infections in the future.

Xinjiang, a region of China with arid and semi-arid areas, has abundant solar incidence with 166.5×104 km2 and diverse underlying surface. The meager number of surface radiation observatories cannot meet the need for efficient exploration of solar energy. In this study we classified Xinjiang into three regions: southern Xinjiang, northern Xinjiang and Tu-Ha region and applied satellite data to provide the surface solar radiation's temporal distribution for 10 typical cities. The study is focused on seasonal, annual and variations of all sky downward shortwave radiation flux at surface based on 24-year satellite dataset GEWEX-SRB from the WCRP/GEWEX (World Climate Research Program/Global Energy and Water Cycle Experiment) from 1984 to 2007. The results are as follows. In general, the monthly average solar radiation flux for the cities in the Tu-Ha region was the largest followed by the south Xinjiang and northern Xinjiang. The solar radiation in the most northern cities were less than 150.0 W/m2 in winter, the minimum is 138.7 W/m2, while the other cities were greater than 150.0 W/m2. The maximum of monthly solar flux for the Tu-Ha region, southern and northern Xinjiang was 400.0 W/m2.

In this paper, we aim to identify the significant variables that contribute to the injury severity level of the person in the car when an accident happens and build a statistical model for predicting the maximum injury severity level as well as estimating the potential economic cost in a car accident based on those variables. The General Estimates System data, which is a representative sample of police-reported motor vehicle crashes of all types collected by the National Highway Transportation Safety Administration, from the years 2012 to 2013 is the main data source. Some other data sources such as the car safety rating from the United State Department of Transformation and the state-specific cost of crash deaths fact sheets are also used in the predictive model building process. An interactive system programmed in HyperText Markup Language, Cascading Style Sheets and JavaScript is developed based on the results of predictive modeling. The system is hosted on a website at http://gessmu.azurewebsites.net for public access. The system allows users to input variables that are significant contributors in car accidents and obtain the predicted maximum injury severity level and potential economic cost of a car accident.