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Accurate discharge measurement in irrigation channels is critical for improving water use efficiency and optimizing water allocation. To investigate the controlling factors of sediment deposition and its influence on the stage–discharge relationship, controlled experiments were conducted in a rectangular glass flume. Sediment concentration (4–16 kg/m3), bed slope (0.0005–0.002), and discharge (15–45 L/s) were systematically varied, and longitudinal deposition thickness and corresponding water stages were measured. Results indicate that sediment concentration is the dominant factor controlling deposition thickness, exhibiting a downstream-decreasing influence, with pronounced differences upstream and convergence downstream. Bed slope and discharge mitigate deposition by enhancing near-bed hydraulics; upstream deposition thickness decreased by approximately 35% and 23% as slope increased from 0.0005 to 0.002 and discharge increased from 15 to 45 L/s, respectively, with the regulatory effect diminishing along the flow direction. Three-dimensional response analysis revealed a compound “concentration-dominated and hydraulically regulated” mechanism: under low-discharge, low-slope, and high-concentration conditions, the ratio of deposition thickness to measured water depth (hd/h) exceeded 15%, whereas it decreased below 5% under high-discharge, high-slope, and low-concentration conditions. Sediment deposition elevated the overall water stage by approximately 3–4% and caused systematic overestimation of stage-based discharge, with errors reaching 31.4% under low-discharge and high-concentration conditions and decreasing to 4.94% under high-discharge and steep-slope conditions. These findings provide quantitative evidence for discharge measurement and stage–discharge relationship calibration in sediment-laden open channels.

Flooding is now becoming one of the most frequent and widely distributed natural hazards, with significant losses to human lives and property around the world. Evacuation of pedestrians during flooding events is a crucial factor in flood risk management, in addition to saving people’s lives and increasing time for rescue. The key objective of this work is to propose a shortest evacuation path planning algorithm by considering the evacuable areas and human instability during floods. A shortest route optimization algorithm based on cellular automata is established while using diagonal distance calculation methods in heuristic search algorithms. The Morpeth flood event that occurred in 2008 in the UK is used as a case study, and a highly accurate and efficient 2D hydrodynamic model is adopted to discuss the flood characteristics in flood plains. Two flood hazard assessment approaches [i.e., empirical and mechanics-based and experimental calibrated (M&E)] are chosen to study human instability. A comprehensive analysis shows that extreme events are better identified with mechanics-based and experimental calibration methods than with an empirical method. The result of M&E is used as the initial condition for the Morpeth evacuation scenario. Evacuation path planning in Morpeth shows that this algorithm can realize shortest route planning with multiple starting points and ending points at the microscale. These findings are of significance for flood risk management and emergency evacuation research.

The far-reaching impacts of central Pacific El Niño events on global climate differ appreciably from those associated with eastern Pacific El Niño events. Central Pacific El Niño events may become more frequent in coming decades as atmospheric greenhouse gas concentrations rise, but the instrumental record of central Pacific sea-surface temperatures is too short to detect potential trends. Here we present an annually resolved reconstruction of NIÑO4 sea-surface temperature, located in the central equatorial Pacific, based on oxygen isotopic time series from Taiwan tree cellulose that span from 1190 AD to 2007 AD. Our reconstruction indicates that relatively warm Niño4 sea-surface temperature values over the late twentieth century are accompanied by higher levels of interannual variability than observed in other intervals of the 818-year-long reconstruction. Our results imply that anthropogenic greenhouse forcing may be driving an increase in central Pacific El Niño-Southern Oscillation variability and/or its hydrological impacts, consistent with recent modelling studies. El Niño events in the Central Pacific may be changing due to climate change, but long records to support this are lacking. Here, the authors present sea surface temperature reconstructions from tree cellulose for the last 800 years which suggest the variability of Central Pacific El Niño events has increased.

Carbonaceous aerosol plays an important role in climate, but its sources and atmospheric processes are least understood in the Tibetan Plateau (TP), a remote yet climatically sensitive region. This study presents the first seasonal cycle of radiocarbon and stable isotope 13C of organic and elemental carbon (OC and EC) in the atmosphere of the northeastern TP. Large seasonal variations of EC and OC concentrations were explained by non‐fossil sources. Regardless of the season, fossil contribution to OC was strongly correlated with inverse OC concentrations. This allowed the separating a constant background source and a source responsible for OC variability that was mostly of non‐fossil origin. The 13C signature of OC shows that OC was highly atmospherically processed and thus less volatile than OC found near sources or in urban areas. The 13C‐depleted secondary sources contributed strongly to more volatile OC, whereas the 13C‐enriched less volatile OC suggests the influence of atmospheric aging. Plain Language Summary The climate effects of carbonaceous aerosols (CAs) are highly uncertain and debated. The high‐altitude Tibetan Plateau (TP) is sensitive to climate change, however, sources and atmospheric processes of CAs in the TP are poorly known. This is particularly challenging for organic aerosols, due to the large number of species involved in their formation and transformation processes in the atmosphere. In recent years, dual‐carbon isotope characterization (i.e., radiocarbon 14C and the stable carbon isotope 13C) has become a promising tool to elucidate the sources and formation processes of organic aerosols. With this approach, we found that organic aerosols in the northeastern TP (Qinghai Lake) are highly atmospheric processed, and their seasonal variability is driven by a variable largely non‐fossil source. Findings from this study lead to a better understanding of the sources and formation mechanisms of organic aerosols in different seasons, and thus organic aerosols' effects on climate change. Key Points High seasonality of elemental carbon (EC) and organic carbon (OC) concentrations in the northeastern Tibetan Plateau (TP) was driven by non‐fossil sources In the monsoon season, low EC and OC concentrations reflected local sources, with most evident contributions from fossil sources OC in the northeastern TP was highly atmospherically processed and thus less volatile compared to OC near sources or in urban areas

Adversarial attacks expose the latent vulnerabilities within artificial intelligence systems, necessitating a reassessment and enhancement of model robustness to ensure the reliability and security of deep learning models against malicious attacks. We propose a fast method designed to efficiently find sample points close to the decision boundary. By computing the gradient information of each class in the input samples and comparing these gradient differences with the true class, we can identify the target class most sensitive to the decision boundary, thus generating adversarial examples. This technique is referred to as the “You Only Attack Once” (YOAO) algorithm. Compared to the DeepFool algorithm, this method requires only a single iteration to achieve effective attack results. The experimental results demonstrate that the proposed algorithm outperforms the original approach in various scenarios, especially in resource-constrained environments. Under a single iteration, it achieves a 70.6% higher success rate of the attacks compared to the DeepFool algorithm. Our proposed method shows promise for widespread application in both offensive and defensive strategies for diverse deep learning models. We investigated the relationship between classifier accuracy and adversarial attack success rate, comparing the algorithm with others. Our experiments validated that the proposed algorithm exhibits higher attack success rates and efficiency. Furthermore, we performed data visualization on the ImageNet dataset, demonstrating that the proposed algorithm focuses more on attacking important features. Finally, we discussed the existing issues with the algorithm and outlined future research directions. Our code will be made public upon acceptance of the paper.

Tree-ring samples from Chinese Pine (Pinus tabulaeformis Carr.) that were collected in the Taihe Mountains on the western Loess Plateau, China, were used to analyze the effects of climate and drought on radial growth and to reconstruct the mean April-June Standardized Precipitation Evapotranspiration Index (SPEI) during the period 1730-2012 AD. Precipitation positively affected tree growth primarily during wet seasons, while temperature negatively affected tree growth during dry seasons. Tree growth responded positively to SPEI at long time scales most likely because the trees were able to withstand water deficits but lacked a rapid response to drought. The 10-month scale SPEI was chosen for further drought reconstruction. A calibration model for the period 1951-2011 explained 51% of the variance in the modeled SPEI data. Our SPEI reconstruction revealed long-term patterns of drought variability and captured some significant drought events, including the severe drought of 1928-1930 and the clear drying trend since the 1950s which were widespread across northern China. The reconstruction was also consistent with two other reconstructions on the western Loess Plateau at both interannual and decadal scales. The reconstructed SPEI series showed synchronous variations with the drought/wetness indices and spatial correlation analyses indicated that this reconstruction could be representative of large-scale SPEI variability in northern China. Period analysis discovered 128-year, 25-year, 2.62-year, 2.36-year, and 2.04-year cycles in this reconstruction. The time-dependency of the growth response to drought should be considered in further studies of the community dynamics. The SPEI reconstruction improves the sparse network of long-term climate records for an enhanced understanding of climatic variability on the western Loess Plateau, China.

Tree-ring samples from Chinese Pine (Pinus tabulaeformis Carr.) collected at Mt. Shimen on the western Loess Plateau, China, were used to reconstruct the mean May-July temperature during AD 1630-2011. The regression model explained 48% of the adjusted variance in the instrumentally observed mean May-July temperature. The reconstruction revealed significant temperature variations at interannual to decadal scales. Cool periods observed in the reconstruction coincided with reduced solar activities. The reconstructed temperature matched well with two other tree-ring based temperature reconstructions conducted on the northern slope of the Qinling Mountains (on the southern margin of the Loess Plateau of China) for both annual and decadal scales. In addition, this study agreed well with several series derived from different proxies. This reconstruction improves upon the sparse network of high-resolution paleoclimatic records for the western Loess Plateau, China.

Multiple myeloma (MM) is a genetically complicated plasma cell malignancy characterized by malignant plasma cell proliferation and monoclonal immunoglobulin synthesis. As a disease that remains incurable, enhancing prognostic accuracy is of paramount importance. Tumor-derived exosomes (TDEs) play key roles in modulating the tumor microenvironment, angiogenesis and immune system. Exosomes are involved in multiple processes contributing to cancer progression, including in MM. However, the connection between myeloma and exosome-related genes (ERGs) has not been explored. Therefore, we aim to establish a more accurate model to evaluate the prognosis of MM patients based on the exosome-related genes. This study established an ERG-based prognostic model for MM and investigated its association with the immune microenvironment. Using transcriptomic data from GSE136337 (training set) and GSE24080 (validation set), we identified six prognostic ERGs (BIRC5, LDHA, MRPS30, MRPL15, RPL26L1, and S1PR2) through Cox and LASSO regression analyses, constructing a risk-scoring model. The model demonstrated robust predictive performance for 3-year survival (AUC = 0.74 in training set; AUC = 0.69 in both validation sets). A nomogram integrating age, ISS stage, and risk score significantly improved prognostic accuracy (3-year survival AUC = 0.77). Functional enrichment analysis revealed that high-risk patients exhibited activation of oncogenic pathways, including cell cycle regulation and DNA replication ( P  < 0.01). Immune profiling identified an immunosuppressive microenvironment in the high-risk group, characterized by reduced CD8 + T cell infiltration ( P  = 0.004) and elevated TIDE scores ( P  = 0.012), indicating increased resistance to immunotherapy. TCGA database validation and in vitro experiments confirmed the critical role of these ERGs in tumor microenvironment remodeling. To our knowledge, this represents the first ERG-based prognostic system for MM, providing a biologically insightful and clinically applicable tool for personalized treatment strategies.

Background Iron overload, which is common in patients with haematological disorders, is known to have a suppressive effect on haematogenesis. However, the mechanism for this effect is still unclear. The antioxidant curcumin has been reported to protect against iron overload-induced bone marrow damage through an as-yet-unknown mechanism. Methods We established iron overload cell and mouse models. Mitochondrial reactive oxygen species (mROS) levels, autophagy levels and the SIRT3/SOD2 pathway were examined in the models and in the bone marrow of patients with iron overload. Results Iron overload was shown to depress haematogenesis and induce mitochondrion-derived superoxide anion-dependent autophagic cell death. Iron loading decreased SIRT3 protein expression, promoted an increase in SOD2, and led to the elevation of mROS. Overexpression of SIRT3 reversed these effects. Curcumin treatment ameliorated peripheral blood cells generation, enhanced SIRT3 activity, decreased SOD2 acetylation, inhibited mROS production, and suppressed iron loading-induced autophagy. Conclusions Our results suggest that curcumin exerts a protective effect on bone marrow by reducing mROS-stimulated autophagic cell death in a manner dependent on the SIRT3/SOD2 pathway.

In recent years, heavy rainfall events have occurred frequently in the Qinba region. Forecasting and predicting heavy rainfall in the Qinba region is difficult due to the unique underlying terrain and complicated mechanisms involved. One significant weather system that might bring significant rainfall to the region is the southwest vortex (SWV); however, its different positions, intensities, and interaction with other weather systems might result in precipitation with different intensities and distributions. In this study, ERA-5 reanalysis data, FY-4A satellite data, and conventional observation data were used to examine heavy rainstorms that occurred in the Qinba region in the periods of 3–4 September 2021 (referred to as Stage I) and 4–5 September 2021 (referred to as Stage II), while the SWV was in effect. During Stage I, the northwest vortex (NWV) and SWV generated a mesoscale shear line and mesoscale convective complex (MCC) in the Qinba region. This led to a considerable area of heavy rainfall, with a maximum hourly precipitation of 129 mm and heavy precipitation at 15 stations. During Stage II, a mesoscale convective system (MCS) influenced by the SWV was initiated by a low-level jet, resulting in a localized heavy downpour with a maximum hourly precipitation of 72 mm. Significant topography-forced uplift was found in both Stages I and II in the high-altitude Qinba region. Furthermore, the rainfall was stronger during Stage I due to the secondary circulation that developed in the middle and lower levels. These findings will improve our capability to predict rainstorms and prevent disasters in the Qinba region.