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Acute farmland expansion and rapid urbanization in Central Asia have accelerated land use/land cover changes, which have substantial effects on ecosystem services. However, the spatiotemporal variations in ecosystem service values (ESVs) in Central Asia are not well understood. Here, based on land use products with 300-m resolution for the years 1995, 2005 and 2015 and transfer methodology, we predicted land use and land cover (LULC) for 2025 and 2035 using CA-Markov, assessed changes in ESVs in response to LULC dynamics, and explored the elasticity of the response of ESV to LULC changes. We found significant expansions of cropland (+22.10%) and urban areas (+322.40%) and shrinking of water bodies (−38.43%) and bare land (−9.42%) during 1995–2035. The combined value of ecosystem services of water bodies, cropland, and grassland accounted for over 90% of the total ESVs. Our study showed that cropland ecosystem services value increased by 93.45 billion US $ from 1995 to 2035, which was mainly caused by the expansion of cropland area. However, the area of water bodies decreased sharply during 1995–2035, causing a loss of 64.38 billion US$ . Biodiversity, food production and water regulation were major ecosystem service functions, accounting for 80.52% of the total ESVs. Our results demonstrated that effective land-use policies should be made to control farmland expansion and protect water bodies, grassland and forestland for more sustainable ecosystem services.

Landscape ecological risk assessment and ecological network construction are of great significance for optimizing territorial functions and reducing regional ecological risks. Based on the production-living-ecological space perspective, this study evaluated the spatiotemporal differentiation characteristics of landscape ecological risk and its driving mechanism in Southwest China and constructed a landscape ecological network. The results showed that the proportions of ecological space, production space and living space to the total space in 2020 were 74.35%, 24.55% and 1.10%, respectively. The industrial production space had the highest growth rate, increasing by 9.8 times from 2000 to 2020. During the study period, the average value of the ecological risk index ranged from 0.2 to 0.21 for the whole landscape. The geographical distribution of ecological risk zones showed significant differences, with risk zones showing a transition from high-risk and low-risk to medium-risk zones. A total of 105 ecological corridors and 156 ecological nodes have been constructed in the 2020 ecological network. The northeastern part of the study area needs better landscape connectivity and should be focused on ecological protection. Random Forest (RF) and Geodetector modeling showed that anthropogenic disturbance and land use levels have strong explanatory power for the evolution of ecological risk in the landscape. The interactions between anthropogenic disturbance, natural climate and regional economy are essential factors in the spatiotemporal differentiation of ecological risk. This study provides scientific references for ecological risk research and the promotion of high-quality development in Southwest China.

Cadmium (Cd) pollution is a serious threat to food safety and human health. Minimizing Cd uptake and enhancing Cd tolerance in plants are vital to improve crop yield and reduce hazardous effects to humans. In this study, we designed three Cd concentration stress treatments (Cd1: 0.20 mg·kg −1 , Cd2: 0.60 mg·kg −1 , and Cd3: 1.60 mg·kg −1 ) and two foliar silicon (Si) treatments (CK: no spraying of any material, and Si: foliar Si spraying) to conduct pot experiments on soil Cd stress. The results showed that spraying Si on the leaves reduced the Cd content in brown rice by 4.79–42.14%. Si application increased net photosynthetic rate (Pn) by 1.77–4.08%, stomatal conductance (Gs) by 5.27–23.43%, transpiration rate (Tr) by 2.99–20.50% and intercellular carbon dioxide (CO 2 ) concentration (Ci) by 6.55–8.84%. Foliar spraying of Si significantly increased the activities of superoxide dismutase (SOD) and peroxidase (POD) in rice leaves by 9.84–14.09% and 4.69–53.09%, respectively, and reduced the content of malondialdehyde (MDA) by 7.83–48.72%. In summary, foliar Si spraying protects the photosynthesis and antioxidant system of rice canopy leaves, and is an effective method to reduce the Cd content in brown rice.

This study addresses the problems of critical conduction mode (CRM) Boost-PFC circuit switch tubes(switch tubes are semiconductor devices like MOSFET that control electric current on/off states) with large opening voltages that lead to high opening loss and high dv/dt, which result in poor electromagnetic interference (EMI). This study also proposes an improved soft-switching constant on time (COT) control method that adaptively realizes ZVS at low instantaneous input voltage values and valley conduction at high instantaneous input voltage values. The EMI performance of the circuit was improved by reducing the switching voltage, switching loss, and the dv/dt of the switch tube. This study discusses the Boost-PFC circuit of the CRM mode, the principle and working process of the proposed control method, analyzes the impact of the proposed control method on the EMI characteristics of the circuit, and designs key parameters. Finally, the simulation and experimental results demonstrate the input and output characteristics, efficiency curves, and EMI curves of the prototype with a power of 20–40 W, an input of 176-277Vac, and an output constant voltage of 430Vdc, which verify the effectiveness of the proposed control method.

This study delved into the role of the PI3K/AKT signaling pathway and cuproptosis in steroid-induced osteonecrosis of the femoral head (SIONFH), assessing the therapeutic potential of the PI3K agonist 740Y-P. We analyzed femoral head specimens from SIONFH patients using DIA proteomics, identifying differentially expressed proteins linked to cuproptosis. In vitro, MC3T3-E1 cells treated with dexamethasone (DEX) exhibited hallmarks of cuproptosis, including downregulation of DLAT, PDHB, SLC25A3, and FDX1, increased copper ions, and reduced osteogenic potential, as shown by decreased ALP activity and RUNX2/BMP2 expression. The PI3K/AKT pathway’s modulation of FDX1 was key to cuproptosis regulation; activating it with 740Y-P restored FDX1 levels and partially recovered osteogenic capacity. An in vivo rat model of SIONFH treated with 740Y-P demonstrated improved bone parameters, reversed osteogenic suppression, and upregulated PI3K/AKT/FDX1 expression, validating the pathway’s role in cuproptosis and the agonist’s therapeutic potential for treating SIONFH and glucocorticoid-associated bone disorders.

Accurately counting the number of sorghum seedlings from images captured by unmanned aerial vehicles (UAV) is useful for identifying sorghum varieties with high seedling emergence rates in breeding programs. The traditional method is manual counting, which is time-consuming and laborious. Recently, UAV have been widely used for crop growth monitoring because of their low cost, and their ability to collect high-resolution images and other data non-destructively. However, estimating the number of sorghum seedlings is challenging because of the complexity of field environments. The aim of this study was to test three models for counting sorghum seedlings rapidly and automatically from red-green-blue (RGB) images captured at different flight altitudes by a UAV. The three models were a machine learning approach (Support Vector Machines, SVM) and two deep learning approaches (YOLOv5 and YOLOv8). The robustness of the models was verified using RGB images collected at different heights. The R 2 values of the model outputs for images captured at heights of 15 m, 30 m, and 45 m were, respectively, (SVM: 0.67, 0.57, 0.51), (YOLOv5: 0.76, 0.57, 0.56), and (YOLOv8: 0.93, 0.90, 0.71). Therefore, the YOLOv8 model was most accurate in estimating the number of sorghum seedlings. The results indicate that UAV images combined with an appropriate model can be effective for large-scale counting of sorghum seedlings. This method will be a useful tool for sorghum phenotyping.

A bidirectional DC–DC converter is required for an energy storage system. High efficiency and a high step-up and step-down conversion ratio are the development trends. In this research, a series of bidirectional high-gain Cuk circuits was derived by combining tapped inductors and bidirectional Cuk. After analyzing and comparing the characteristics of each circuit, a bidirectional high-gain Cuk circuit with a tapped-inductor (reverse coupling) was proposed. The proposed converter has a simple structure and a high voltage gain in both the step-down (Buck) and step-up (Boost) operation modes. The voltage stress of S 2 was low. The voltage stress of S 1 was high, however, and this is a disadvantage of the proposed converter. The proposed circuit’s characteristics were thoroughly examined, including the voltage gain characteristics and the design of the main parameters. We established a power loss model of the new topology, and the tapped-inductor turn ratio was optimized for high efficiency. Finally, a 400 W experimental implementation of the converter was shown to achieve efficiencies of 93.5% and 92.4% in the step-up and step-down modes, respectively. These findings verified the validity of the proposed circuit’s theoretical analysis.

Background Wilson disease (WD) is an autosomal recessive disorder caused by homozygous or compound heterozygous mutations in ATP7B . Clinical manifestations primarily involve liver and nervous system lesions, with rarely observed hematologic manifestations. Case presentation In the present case, a patient with WD presented with thrombocytopenia, giant platelets, and Döhle-like cytoplasmic inclusions in the leukocytes. Initially, the May–Hegglin anomaly was considered; however, whole-exome sequencing did not reveal any mutation in the MYH9 gene but a heterozygous mutation was found in (C.2804 C > T, p.T935M) in the ATP7B gene. After two years, the patient developed tremors in his hands, lower limb stiffness, and foreign body sensation in the eyes. Additionally, Kayser–Fleischer rings in the corneal limbus were detected by slit-lamp examination. Copper metabolism test indicated a slight decrease in serum ceruloplasmin. Transmission electron microscopy revealed that the inclusion bodies of leukocytes were swollen mitochondria. Mass spectrometry analysis showed that the copper levels were almost 20-fold higher in the leukocytes of the patient than in those of the control group. Based on the Leipzig scoring system, a diagnosis of WD was confirmed. Zinc sulfate treatment ameliorated the patient’s symptoms and enhanced platelet, serum ceruloplasmin, and albumin levels. Conclusions In conclusion, this case represents the first documented instance of WD presenting as thrombocytopenia, giant platelets, and Döhle-like cytoplasmic inclusions in the leukocytes. Excessive cellular copper accumulation likely underlies these findings; however, understanding precise mechanisms warrants further investigation.

In response to the International Maritime Organization’s emission reduction targets, ship power systems are transitioning toward microgrid architectures with high renewable energy penetration. In islanded mode, the lack of main grid support and the low inertia of power electronic interfaces pose significant frequency stability challenges. Virtual Synchronous Generator (VSG) technology offers an effective solution, but conventional VSG control exhibits two inherent limitations: steady-state frequency deviation under load variations due to its primary regulation nature, and poor dynamic response characterized by large overshoot and prolonged settling time. This paper proposes an enhanced VSG control strategy integrating two key innovations: (i) a communication-free secondary frequency regulation loop that eliminates steady-state error, and (ii) an adaptive control scheme for virtual inertia and damping coefficients that dynamically responds to frequency deviations and their rate of change. The adaptive mechanism reduces overshoot by 57% (from 0.14 Hz to 0.06 Hz) and shortens settling time by 40% (from 0.38 s to 0.23 s) compared to non-adaptive secondary regulation, as demonstrated through MATLAB/Simulink simulations and 6 kW experimental prototype validation. The proposed strategy ensures both steady-state accuracy and enhanced transient performance, providing a reliable solution for improving power quality in islanded shipboard microgrids and contributing to maritime decarbonization goals.

Background Acute kidney injury (AKI), a critical complication of childhood idiopathic nephrotic syndrome (INS), markedly increases the risk of chronic kidney disease (CKD) and mortality. This study developed an interpretable machine learning (ML) model for early AKI prediction in pediatric INS to enable proactive interventions and mitigate adverse outcomes. Methods A total of 3,390 patients and 356 hospitalized pediatric patients with INS were included in the derivation and external cohorts, respectively, from four hospitals across China. Logistic regression, Random Forest, K-nearest neighbors, Naïve Bayes, and Support Vector machines were integrated into a stacking ensemble model and optimized for class imbalance using SMOTE-Tomek. Model performance was assessed using the area under the curve (AUC), area under the precision-recall curve, sensitivity, specificity, and balanced accuracy. SHapley Additive Explanations (SHAP) analysis elucidated the importance of features, and a Random Forest model was developed to predict CKD progression in patients with AKI. Results Of the 3,390 patients with INS, 12.9% developed AKI. The stacking model outperformed the individual algorithms, achieving an AUC of 0.888 internally and 0.822 externally, which could be well explained by the SHAP algorithm. It was then deployed as a web-based calculator for real-time risk assessment. Key predictors included exposure to nephrotoxic antibiotics, exposure to cyclophosphamide, respiratory tract infection, urine pH, and admission times. In the AKI cohort, alanine transaminase, aspartate transaminase, and serum phosphate levels were primarily associated with the development of CKD. Conclusions This study presents an interpretable ML model for early AKI prediction in pediatric Chinese patients with INS, which could serve as a practical, efficient, and economical tool for preventing AKI by identifying modifiable risk factors to reduce AKI incidence and mitigate CKD progression.