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Land use and cover change (LUCC) is an important issue affecting the global environment, climate change, and sustainable development. Detecting and predicting LUCC, a dynamic process, and its driving factors will help in formulating effective land use and planning policy suitable for local conditions, thus supporting local socioeconomic development and global environmental protection. In this study, taking Gansu Province as a case study example, we explored the LUCC pattern and its driving mechanism from 1980 to 2018, and predicted land use and cover in 2030 using the integrated LCM (Logistic-Cellular Automata-Markov chain) model and data from satellite remote sensing. The results suggest that the LUCC pattern was more reasonable in the second stage (2005 to 2018) compared with that in the first stage (1980 to 2005). This was because a large area of green lands was protected by ecological engineering in the second stage. From 1980 to 2018, in general, natural factors were the main force influencing changes in land use and cover in Gansu, while the effects of socioeconomic factors were not significant because of the slow development of economy. Landscape indices analysis indicated that predicted land use and cover in 2030 under the ecological protection scenario would be more favorable than under the historical trend scenario. Besides, results from the present study suggested that LUCC in arid and semiarid area could be well detected by the LCM model. This study would hopefully provide theoretical instructions for future land use planning and management, as well as a new methodology reference for LUCC analysis in arid and semiarid regions.

Oxidative Balance Scores (OBS) are utilized to assess an individual's antioxidant status, encompassing both dietary and lifestyle factors that contribute to oxidative balance. This study investigates the relationship between OBS and chronic kidney disease (CKD) prevalence among U.S. adults, utilizing data from the National Health and Nutrition Examination Survey (NHANES) 2007–2018. The study involved a cross-sectional analysis of 13,373 individuals from NHANES, focusing on adults aged 20 years or older. OBS was calculated using 20 components, including dietary and lifestyle factors. CKD was identified based on albumin-to-creatinine ratio and estimated glomerular filtration rate, with patients stratified into mild, moderate, and high-risk groups. Statistical analysis included logistic regression models and restricted cubic splines to explore the OBS-CKD relationship. Our findings indicate a statistically significant negative correlation between OBS and CKD prevalence, particularly in mild and moderate-risk groups. Higher OBS quartiles were associated with a decreased likelihood of CKD (OR 0.70; 95% CI 0.53–0.92; P = 0.013). Restricted cubic splines indicated a non-linear, inverse association between OBS and CKD odds for the overall population (P for nonlinearity = 0.017). For mild and moderate CKD risk groups, the relationships were less pronounced (P for nonlinearity = 0.053 and 0.184, respectively), suggesting variability in the OBS-CKD link across different risk levels. The study highlights the potential of elevated OBS as a primary prevention measure for CKD, particularly in individuals with mild to moderate risk. These findings underscore the importance of antioxidant status in CKD risk management and encourage further research into the role of dietary and lifestyle factors in CKD prevention.

Background Chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) is a common disorder impacting the genitourinary system of adult males, primarily driven by pathogenic mechanisms involving immune and inflammatory mediators, immune cells and molecules, oxidative stress, and apoptosis. Cepharanthine (CEP), a bisbenzylisoquinoline alkaloid, exhibits properties such as immunomodulatory, antioxidant, anti-inflammatory, and antitumor activities. Nevertheless, the effects of CEP on CP/CPPS and its underlying mechanisms remain insufficiently characterized. Methods Two experimental models were developed, one utilizing experimental autoimmune prostatitis (EAP) mouse models and the other employing LPS-induced RWPE-1 cells. The pivotal role of Nrf2 was investigated using Nrf2 knockout mice and the Nrf2 inhibitor ML385. Results Treatment with CEP reduced prostate inflammation scores, alleviated tactile sensitization of the pelvic region in EAP mice, improved pathological damage in prostate tissues, and inhibited the upregulation of systemic and localized pain and pro-inflammatory mediators in the prostate. Furthermore, CEP treatment was shown to inhibit oxidative stress, ameliorate mitochondrial dysfunction, and suppress apoptosis. In vitro studies indicate that CEP treatment stabilizes Nrf2 protein levels by binding to the Nrf2 protein and inhibiting its ubiquitination-mediated degradation. Consequently, CEP treatment activates the Nrf2 signaling pathway, facilitates its nuclear translocation, and upregulates the expression of downstream target proteins, such as HO-1 and NQO1. Concurrently, CEP suppresses the activation of the NF-κB pathway. Notably, the blockade of Nrf2 signaling negates the protective effects mediated by CEP. Conclusions CEP inhibits the ubiquitination-mediated degradation of Nrf2 and exhibits potential to activate the Nrf2 pathway while concurrently inhibiting the NF-κB pathway, thereby alleviating CP/CPPS.

Chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) is a common disorder impacting the genitourinary system of adult males, primarily driven by pathogenic mechanisms involving immune and inflammatory mediators, immune cells and molecules, oxidative stress, and apoptosis. Cepharanthine (CEP), a bisbenzylisoquinoline alkaloid, exhibits properties such as immunomodulatory, antioxidant, anti-inflammatory, and antitumor activities. Nevertheless, the effects of CEP on CP/CPPS and its underlying mechanisms remain insufficiently characterized. Two experimental models were developed, one utilizing experimental autoimmune prostatitis (EAP) mouse models and the other employing LPS-induced RWPE-1 cells. The pivotal role of Nrf2 was investigated using Nrf2 knockout mice and the Nrf2 inhibitor ML385. Treatment with CEP reduced prostate inflammation scores, alleviated tactile sensitization of the pelvic region in EAP mice, improved pathological damage in prostate tissues, and inhibited the upregulation of systemic and localized pain and pro-inflammatory mediators in the prostate. Furthermore, CEP treatment was shown to inhibit oxidative stress, ameliorate mitochondrial dysfunction, and suppress apoptosis. In vitro studies indicate that CEP treatment stabilizes Nrf2 protein levels by binding to the Nrf2 protein and inhibiting its ubiquitination-mediated degradation. Consequently, CEP treatment activates the Nrf2 signaling pathway, facilitates its nuclear translocation, and upregulates the expression of downstream target proteins, such as HO-1 and NQO1. Concurrently, CEP suppresses the activation of the NF-κB pathway. Notably, the blockade of Nrf2 signaling negates the protective effects mediated by CEP. CEP inhibits the ubiquitination-mediated degradation of Nrf2 and exhibits potential to activate the Nrf2 pathway while concurrently inhibiting the NF-κB pathway, thereby alleviating CP/CPPS.

Leaf stoichiometry of plants can respond to variation in environments such as elevation ranging from low to high and success in establishing itself in a given montane ecosystem. An evaluation of the leaf stoichiometry of Qinghai Spruce (Picea crassifolia Kom.) growing at different elevations (2400 m, 2600 m, 2800 m, 3000 m, and 3200 m) in eastern China’s Qilian Mountains, showed that leaf carbon (LC) and leaf phosphorus (LP) were similar among elevations, with ranges of 502.76–518.02 g·kg−1, and 1.00–1.43 g·kg−1, respectively. Leaf nitrogen (LN) varied with changes of elevation, with a maxima of 12.82 g·kg−1 at 2600 m and a minima of 10.74 g·kg−1 at 2800 m. The LC:LN under 2400 m and 2600 m was lower than that under other elevations, while LC:LP and LN:LP were not different among these elevations. Except for LN and LC:LN, P. crassifolia’s other leaf stoichiometries remained relatively stable across elevations, partly supporting the homeostasis hypothesis. Variations in leaf stoichiometry across elevations were mainly linked to mean annual precipitation, mean annual temperature, soil pH, and the soil organic C to soil total N ratio. P. crassifolia growth within the study area was more susceptible to P limitation.

MicroRNAs play crucial roles in plant responses to pathogen infections. The rice blast disease, caused by the fungus Magnaporthe oryzae, is the most important disease of rice (Oryza sativa). To explore the microRNA species that participate in rice immunity against the rice blast disease, we compared the expression of small RNAs between mock- and M. oryzae-treated rice. We found that infection by M. oryzae strain Guy11 specifically induced the expression of rice miR319 and, consequently, suppressed its target gene TEOSINTE BRANCHED/CYCLOIDEA/PROLIFERATING CELL FACTOR1 (OsTCP21), which encodes a transcription factor. Using transgenic rice that overexpresses miR319b (OE) or expresses OsTCP21-Res (which is resistant to miR319-mediated silencing), we found that OsTCP21 is a positive regulator of the rice defense response against the blast disease. When wild-type and miR319b-OE rice were infected by Guy11, multiple jasmonic acid (JA) synthetic and signaling components were suppressed, indicating that Guy11 suppresses JA signaling through inducing miR319. In particular, we found that LIPOXYGENASE2 (LOX2) and LOX5 were specifically suppressed by miR319 overexpression or by Guy11 infection. LOXs are the key enzymes of JA synthesis, which catalyze the conversion of 𝛼-linoleic acid to hydroperoxy-octadecadienoic acid. The application of 𝛼-linoleic acid rescued disease symptoms on the OsTCP21-Res rice but not wild-type rice, supporting our hypothesis that OsLOX2 and OsLOX5 are the key JA synthesis genes hijacked by Guy11 to subvert host immunity and facilitate pathogenicity. We propose that induced expression of OsLOX2/5 may improve resistance to the rice blast disease.

The application of basalt fibre reinforced concrete (BFRC) is crucial for reducing carbon emissions, enhancing structural performance, and extending service life. Electrical resistivity (ER), a non-destructive testing indicator, can be used to evaluate parameters such as compressive strength and chloride ion permeability of concrete. Therefore, this study examines BFRC-ER from three perspectives: the applicability of existing ER prediction models, hybrid machine learning modelling, and experimental validation. The findings indicate that the predicted values of the existing nine models have a poor correlation with actual values, limiting their practical application. The prairie dog–optimised XGBoost (PDO–XGBoost) model developed in this study exhibited closer alignment between predicted and actual values. It boasted smaller mean and standard deviation ( μ  = 0.0508 kΩ·cm, σ  = 3.409) of model error distribution, along with superior performance evaluation metrics (MAE = 2.165, MAPE = 0.243, RMSE = 3.410 MSE = 11.625, and R 2  = 0.984). Analysing the contribution of each input feature to BFRC-ER revealed that saturation, age, and water–binder ratio are the three significant influencing factors. Moreover, this study developed a graphical user interface (GUI) for BFRC-ER, enabling the visualisation of BFRC-ER predictions. Subsequently, BFRC with varying mix proportions was prepared, and BFRC-ER was tested using the two-electrode method. The comparison between actual values and GUI predictions showed errors below 7.5%, highlighting the accuracy of the predictions. This research achieves high-accuracy predictions of BFRC-ER, laying the foundation for optimising BFRC mix proportions and evaluating concrete performance.

Regarding the microgrid with large-scale electric vehicle (EV) energy storage systems working at the vehicle-to-grid (V2G) mode, uncertain factors (e.g., the number of EVs feeding the microgrid shifts frequently) make the system unfixed, leading to the fact that it is difficult to precisely determine the real-time droop coefficients of the system, thereby degrading the performance of the traditional inverter control strategies that rely on the droop coefficients. To solve the problem, this paper proposes an errorless-control-targeted double control loop (DCL) technique based on robust MPC to control the microgrid with EV energy storage systems without using droop coefficients. Firstly, the structure of the DCL method is developed, with each component in the structure detailed. Compared to the traditional control strategies, the novel one regards the frequency, voltage, and currents as the control objectives instead of active/inactive power. It deserves to be mentioned that the frequency and voltage are regulated by proportional-integral controllers, while the currents are regulated by the finite control set model predictive control (FCS-MPC) method. Secondly, the impacts of system parameter uncertainties on the prediction accuracy of the FCS-MPC controller are analyzed clearly, illustrating that it is necessary to develop effective techniques to enhance the robustness of the controller. Thirdly, sliding mode observers (SMO) based on a novel hyperbolic function are constructed to detect the real-time disturbances, which can be used to generate voltage compensations by using automatic disturbance regulators. Then, the voltage compensations are adopted to establish a modified predicting plant model (PPM) used for the FCS-MPC controller. By using the proposed SMO-based disturbance detection and compensation techniques, the MPC controller gains a strong robustness against parameter uncertainties. Finally, a simulation is conducted on a microgrid system to verify the effectiveness of the proposed techniques, and the obtained results are compared with the traditional virtual synchronous machine (VSG) strategy relying on droop coefficients.

Recently, virtual synchronous generators (VSGS) are a hot topic in the area of microgrid control. However, the traditional fixed-parameter-based VSG control methods have an obvious disadvantage. Namely, if the damping value is set to be small, the amplitude of frequency deviations under external power disturbances is large, meaning that the frequency suppression capacity is insufficient, but if the damping value is large, the dynamics of the system will be greatly sacrificed. To solve the problem, taking the dynamic characteristics and the maximum allowable frequency deviation (MAFD) into account, in this paper an improved fuzzy adaptive damping-based VSG control strategy is proposed to simultaneously attenuate the microgrid frequency fluctuations and guarantee the system dynamics. Firstly, in order to address the necessity of using an adaptive damping-based VSG, the structure of a fixed-parameter VSG method that incorporates the f-p/Q-V droop controllers is introduced, based on which a small signal model is established to discuss the impacts of the virtual damping on the frequency response characteristics concerning the different penetration levels of power disturbances. Then, considering the dynamics and MAFD, a fuzzy adaptive controller is constructed relying on the well-designed membership functions, control rules and output scaling factors. The main feature of the improved fuzzy controller is that two alternative output scaling factors are employed to allow the system to be overdamped when the frequency deviation is large and undamped when the frequency deviation is small, balancing the frequency response dynamics and stability characteristics. To verify the effectiveness of the proposed fuzzy adaptive damping-based VSG technique, a computer simulation is conducted on a microgrid system in MATLAB/Simulink, and the obtained results are compared with the conventional droop control and fixed-parameter based VSGs. By using the proposed fuzzy adaptive damping-based VSG control method, the peak frequency deviations under the large power disturbances would become at least 8% lower compared to the traditional droop control and fixed-parameter VSG control, and meanwhile, the frequency response speed is fast when the disturbance stands at a low position. Consequently, it is valuable to promote the proposed techniques in engineering.

For networked control systems, the bandwidth resource is always limited; thus besides control performance, the efficient resource utilization is also crucial. In this paper, a novel event-triggered control and resource scheduling codesign approach is proposed to stabilize the uncertain dynamic systems which are subject to time-varying network introduced delays. A discrete switched system with uncertain parameters is employed to model the event-triggered control system with time-varying network-induced delays. Based on the model, a control law, scheduling strategy, and event-triggered condition codesign approach is investigated. A set of linear matrix inequalities are used to tackle the codesign problem. As the solution to the problem, a control law is obtained to guarantee stability or certain performance properties; an event-triggered condition and a scheduling strategy are also obtained to efficiently utilize the limited resources. That is, the event-triggered condition makes the network accession be triggered when it is necessary. The scheduling strategy guarantees the control loop suffering the worst control performance can get the authority to access the network. The proposed approach is evaluated through simulated experiments, with respect to the networked control of inverted pendulums. The results show that the proposed event-triggered control and scheduling approach can achieve better control performances with lower average resource consumption in comparison with the time-based control strategy.