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Water resources underpin human society and economic growth, yet freshwater is unevenly distributed, leaving arid regions severely water-stressed. The Beishan mining district in Inner Mongolia exemplifies this challenge: despite abundant minerals, it lacks surface water and depends almost entirely on groundwater. To improve exploration in such complex settings, we propose a Bayesian joint inversion that leverages the complementary sensitivities of Surface Nuclear Magnetic Resonance (SNMR) and Transient Electromagnetic (TEM) data within a probabilistic framework. Using a transdimensional Markov Chain Monte Carlo (MCMC) algorithm, the method adaptively balances data weighting and model complexity. Tests on synthetic and field datasets show that combining SNMR’s direct sensitivity to water content with TEM’s high-resolution resistivity imaging enhances aquifer detection across depths and enables quantitative uncertainty assessment. Applied in Beishan, the approach delineates promising aquifers, with results confirmed by drilling, offering a robust basis for groundwater exploration and sustainable management in arid regions.

The welding quality of industrial pipelines directly impacts structural safety. X-ray non-destructive testing (NDT), known for its non-invasive and efficient characteristics, is widely used for weld defect detection. However, challenges such as low contrast between defects and background, as well as large variations in defect scales, reduce the accuracy of existing object detection models. To address these, an optimized detection model based on You Only Look Once (YOLO) v5 is proposed. Firstly, the Efficient Multi-Scale Attention (EMA) attention mechanism is integrated into the first Cross Stage Partial (C3) module of the backbone to enhance the model’s receptive field and the initial feature extraction. Secondly, the Efficient Channel Attention (ECA) attention mechanism is embedded before the Spatial Pyramaid Pooling Fast (SPPF) layer to enhance the model’s ability to extract small targets and key features. Finally, the Complete Intersection over Union (CIoU) loss is replaced with Wise Intersection over Union (WIoU) to improve localization accuracy and multi-scale detection performance. The experimental results show that the optimized model achieves a precision of 94.1%, a recall of 89.2%, and an mAP@0.5 of 94.6%, representing improvements by 11.5%, 5.4%, and 6.9%, respectively, over the original YOLOv5. The optimized model also outperforms several mainstream object detection models in weld defect detection. In terms of mAP@0.5, the optimized YOLOv5 model shows improvements of 14.89%, 13.02%, 6.1%, 19.37%, 7.1%, 7.5%, and 10.7% compared with the Faster-RCNN, SSD, RT-DETR, YOLOv3, YOLOv8, YOLOv9, and YOLOv10 models, respectively. This optimized model significantly enhances X-ray weld defect detection accuracy, meeting industrial application requirements and offering another high-precision solution for weld defect detection.

Background The advancement of biomimetic drug delivery systems designed for biomedical applications has attracted considerable attention from researchers in recent years. A particularly noteworthy approach involves the use of various cell membranes, which can impart distinctive functionalities to the nanoparticles, including specific recognition of target cells, prolonged circulation within the bloodstream, and enhanced ability to evade the immune system, as surface coatings on nanoparticles. This innovative strategy has positioned cell membrane-coated nanoparticles (CMCNPs) as a promising framework for addressing a wide range of diseases more effectively. Methods In the current investigation, lipid nanoparticles were specifically engineered using glioblastoma cell membrane (GBMM) coatings, termed as LNPs/D@GBMM, to serve as targeted nanotheranostics against homologous malignant glioblastoma (GBM). The physicochemical properties of LNPs/D@GBMM were investigated in terms of particle size, morphology, drug loading (DL), drug release behavior and so on. Homologous cellular uptake was evaluated by confocal laser scanning microscopy (CLSM). Cell cytotoxicity was evaluated by MTT assay. Moreover, the bio-distribution of CMCNPs in vivo was investigated via the near-infrared (NIR) fluorescence imaging technique, and the anti-tumor effect in vivo was evaluated in xenografted nude mice. Results Compared to non-targeted lipid nanoparticles, LNPs/D@GBMM exhibited superior cytotoxic effects against homologous tumor cells. In addition, fluorescence imaging of targeted tumor cells treated with LNPs/D@GBMM indicated a marked increase in cell internalization, and improved fluorescence distribution in vivo. LNPs/D@GBMM finally produced an excellent tumor suppression effect on homologous tumors. Conclusion The robust platform established by CMCNPs leveraging the inherent characteristics of homologous tumor cell membranes, is expected to facilitate systemic delivery of therapeutic agents specifically aimed at treating tumors, thus advancing the efficacy of cancer therapy in clinical settings.

BackgroundFew studies to date have analyzed the epidemiology of acute kidney injury (AKI) in children with cancer in developing countries. The aim of this study was to assess the incidence, risk profile and outcomes of AKI in Chinese children hospitalized with cancer.MethodsThis multi-center study analyzed Chinese children hospitalized with cancer in 2013–2015. Electronic hospital and laboratory databases were screened to select pediatric patients with malignancy who had at least two Scr results within any 7-day window during their first 30 days of hospitalization. AKI events were identified and staged according to Kidney Disease Improving Global Outcomes (KDIGO) criteria. The incidence of and risk factors for AKI were analyzed, as were mortality rate, incidence of kidney recovery, and length of hospital stay.ResultsOf the 9828 children with cancer, 1657 (16.9%) experienced AKI events, including 549 (5.6%) community-acquired (CA-AKI) and 1108 (11.3%) hospital-acquired AKI (HA-AKI) events. The three types of cancer with the highest incidence of AKI were urinary system cancer (25.8%), hepatic cancer (19.4%), and retroperitoneal malignancies (19.1%). The risk factor profiles of CA-AKI and HA-AKI events differed, with many HA-AKI events due to treatment with nephrotoxic agents. In-hospital death rates were 5.4% (90 of 1657) in children with and 0.9% (74 of 8171) in children without AKI events. AKI events were also associated with longer hospitalization and higher daily costs.ConclusionsAKI events are common among Chinese children hospitalized for cancer and are associated with adverse in-hospital outcomes.

Background Sepsis is the most common trigger for AKI and up to 40% of mild or moderate septic AKI would progress to more severe AKI, which is associated with significantly increased risk for death and later CKD/ESRD. Early identifying high risk patients for AKI progression is a major challenge in patients with septic AKI. Methods This is a prospective, multicenter cohort study which enrolled adult patients with sepsis and initially developed stage 1 or 2 AKI in the intensive care unit from January 2014 to March 2018. AKI was diagnosed and staged according to 2012 KDIGO-AKI guidelines. Renal cell arrest biomarkers (urinary TIMP2*IGFBP7, u[TIMP-2]*[IGFBP7]) and renal damage biomarkers (urinary KIM-1[uKIM-1] and urinary IL-18 [uIL-18]) were measured at time of AKI clinical diagnosis, and the performance of biomarkers for predicting septic AKI progression alone or in combination were evaluated. The primary outcome was AKI progression defined as worsening of AKI stage. The secondary outcome was AKI progression with subsequent death during hospitalization. Results Among 433 screened patients, 149 patients with sepsis and stage 1 or 2 AKI were included, in which 63 patients developed progressive AKI and 49 patients subsequently died during hospitalization. u[TIMP-2]*[IGFBP7], uKIM-1 and uIL-18 independently predicted the progression of septic AKI in which u[TIMP-2]*[IGFBP7] showed the greatest AUC (0.745; 95%CI, 0.667-0.823) as compared to uKIM-1 (AUC 0.719; 95%CI 0.638-0.800) and uIL-18 (AUC 0.619; 95%CI 0.525-0.731). Combination of u[TIMP-2]*[IGFBP7] with uKIM-1 improved the performance of predicting septic AKI progression with AUC of 0.752. u[TIMP-2]*[IGFBP7], alone or combined with uKIM-1/uIL-18, improved the risk reclassification over the clinical risk factor model alone both for the primary and secondary outcomes, as evidenced by significant category-free net reclassification index. Conclusions Combination of renal cell arrest and damage biomarkers enhanced the prediction of AKI progression in patients with sepsis and improved risk reclassification over the clinical risk factors.

Actinidia chinensis Planch. is a fruit tree originating from China that is abundant in the wild. Actinidia eriantha Benth. is a type of A. chinensis that has emerged in recent years. The shape of A. eriantha is an elongated oval, and the skin is covered with dense, non-shedding milk-white hairs. The mature fruit has flesh that is bright green in colour, and the fruit has a strong flavour and a grass-like smell. It is appreciated for its rich nutrient content and unique flavour. Vitamin C, sugar, and organic acids are key factors in the quality and flavour composition of A. eriantha but have not yet been systematically analysed. Therefore, we sequenced the transcriptome of A. eriantha at three developmental stages and labelled them S1, S2, and S3, and comparisons of S1 vs. S2, S1 vs. S3, and S2 vs. S3 revealed 1218, 4019, and 3759 upregulated differentially expressed genes and 1823, 3415, and 2226 downregulated differentially expressed genes, respectively. Furthermore, the upregulated differentially expressed genes included 213 core genes, and Gene Ontology enrichment analysis showed that they were enriched in hormones, sugars, organic acids, and many organic metabolic pathways. The downregulated differentially expressed genes included 207 core genes, which were enriched in the light signalling pathway. We further constructed the metabolic pathways of sugars, organic acids, and vitamin C in A. eriantha and identified the genes involved in vitamin C, sugar, and organic acid synthesis in A. eriantha fruits at different stages. During fruit development, the vitamin C content decreased, the carbohydrate compound content increased, and the organic acid content decreased. The gene expression patterns were closely related to the accumulation patterns of vitamin C, sugars, and organic acids in A. eriantha. The above results lay the foundation for the accumulation of vitamin C, sugars, and organic acids in A. eriantha and for understanding flavour formation in A. eriantha.

Elevated CO2 concentration has been reported to decrease grain nutrient concentrations and thus worsen nutritional deficiency and hidden hunger. One nutritional aspect is mineral content, yet mineral bioavailability can be limited by the presence of phytic acid. Given that future climate scenarios predict elevated global temperature driven by elevated atmospheric CO2 concentrations, we used Temperature by Free‐Air CO2 Enrichment (T‐FACE) field experiments to investigate whether elevated temperature alters the effects of elevated CO2 on grain mineral concentrations, grain mineral yields, and their bioavailability in a range of wheat and rice genotypes. We found that the negative effects of elevated CO2 were compensated for by positive effects of elevated temperature. As a result, the combined elevated CO2 and elevated temperature increased concentrations of some minerals by up to ~15% in both rice and wheat relative to control conditions. Moreover, the combined elevated CO2 and elevated temperature did not significantly change total yields of some minerals despite lower grain yields. The combined CO2 and temperature elevation increased phytic acid concentration in rice by 18.1% but decreased it in wheat by 3.5%. The mineral bioavailability, estimated as the mole ratio of phytic acid to minerals in rice and wheat grains, was limited by the combined CO2 and temperature elevation in only a few cases. Our results indicate that under future climate conditions of elevated temperature and CO2, the nutritional quality of rice and wheat with respect to minerals may remain unchanged. The combined elevated CO2 and temperature increased concentrations of some minerals but resulted in lower grain yields, thereby did not significantly change the yields of some minerals. The combined CO2 and temperature elevation increased phytic acid concentrations but limited the mineral bioavailability. Our results indicate that elevated temperature cancelled out the effect of elevated CO2, thereby, to a large extent, safeguarding the nutritional quality of rice and wheat under climate change.

Nondestructive monitoring and diagnosis of plant N status is necessary for precision N management. The present study was conducted to determine if canopy reflectance could be used to evaluate leaf N status in rice (Oryza sativa L.). Ground-based canopy spectral reflectance and N concentration and accumulation in leaves were measured over the entire rice growing season under various treatments of N fertilization, irrigation, and plant population. Analyses were made on the relationships of seasonal canopy spectral reflectance, ratio indices, and normalized difference indices to leaf N concentration and N accumulation in rice under different N treatments. The results showed that at each sampling date, leaf N concentration was negatively related to the reflectance at the green band (560 nm) while positively related to ratio index, with the best correlation at jointing. However, the relationships between leaf N accumulation and reflectance at green band and ratio index were consistent across the whole growth period. The ratio of near infrared (NIR) to green (R810/R560) was especially linearly related to total leaf N accumulation, independent of N level and growth stage. Tests of the linear regression model with different field experiment data sets involving different plant densities, N fertilization, and irrigation treatments exhibited good agreement between the predicted and observed values, with an estimation accuracy of 96.69%, root mean square error of 0.7072, and relative error of -0.0052. These results indicate that the ratio index of NIR to green (R810/R560) should be useful for nondestructive monitoring of N status in rice plants.

This experiment was conducted to investigate the effects of increased atmospheric temperature and CO2 concentration during crop growth on the chemical composition and in vitro rumen fermentation characteristics of wheat straw. The field experiment was carried out from November 2012 to June 2013 at Changshu （31°32′93″N, 120°41′88″E） agro-ecological experimental station. A total of three treatments were set. The concentration of CO2 was increased to 500 pmol/mol in the first treatment （CO2 group）. The temperature was increased by 2℃ in the second treatment （TEM group） and the concentration of CO2 and temperature were both increased in the third treatment （CO2 ＋ TEM group）. The mean temperature and concentration of CO2 in control group were 10.5 ℃ and 413μmol/mol. At harvesting, the wheat straws were collected and analyzed for chemical composition and in vitro digestibility. Results showed that dry matter was significantly increased in all three treatments. Ether extracts and neutral detergent fiber were significantly increased in TEM and CO2 ＋ TEM groups. Crude protein was significantly decreased in CO2＋TEM group. In vitro digestibility analysis of wheat straw revealed that gas production was significantly decreased in CO2 and CO2 ＋ TEM groups. Methane production was significantly decreased in TEM and CO2 ＋ TEM groups. Ammonia nitrogen and microbial crude protein were significantly decreased in all three treatments. Total volatile fatty acids were significantly decreased in CO2 and CO2 ＋ TEM groups. In conclusion, the chemical composition of the wheat straw was affected by temperature and CO2 and the in vitro digestibility of wheat straw was reduced, especially in the combined treatment of temperature and CO2.

The subset sum problem is a combinatorial optimization problem, and its complexity belongs to the nondeterministic polynomial time complete (NP-Complete) class. This problem is widely used in encryption, planning or scheduling, and integer partitions. An accurate search algorithm with polynomial time complexity has not been found, which makes it challenging to be solved on classical computers. To effectively solve this problem, we translate it into the quantum Ising model and solve it with a variational quantum optimization method based on conditional values at risk. The proposed model needs only n qubits to encode 2 n dimensional search space, which can effectively save the encoding quantum resources. The model inherits the advantages of variational quantum algorithms and can obtain good performance at shallow circuit depths while being robust to noise, and it is convenient to be deployed in the Noisy Intermediate Scale Quantum era. We investigate the effects of the scalability, the variational ansatz type, the variational depth, and noise on the model. Moreover, we also discuss the performance of the model under different conditional values at risk. Through computer simulation, the scale can reach more than nine qubits. By selecting the noise type, we construct simulators with different QVs and study the performance of the model with them. In addition, we deploy the model on a superconducting quantum computer of the Origin Quantum Technology Company and successfully solve the subset sum problem. This model provides a new perspective for solving the subset sum problem.