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Abstract Background Previous studies have shown that migraines are associated with brain structural changes. However, the causal relationships between these changes and migraine, as well as its subtypes, migraine with aura (MA) and migraine without aura (MO), remain largely unclear. Methods We utilized genome-wide association study (GWAS) summary statistics from European cohorts for 2,347 cortical structural magnetic resonance imaging (MRI) phenotypes, derived from both T1-weighted and diffusion tensor imaging scans (n = 36,663), with migraine and its subtypes (n = 147,970–375,752). Cortical phenotypes included both macrostructural (e.g., cortical thickness, surface area) and microstructural (e.g., fractional anisotropy, mean diffusivity) features. Genetic correlations were first assessed to identify significant associations, followed by bidirectional Mendelian randomization (MR) analyses to determine causal relationships between these brain phenotypes and migraine, as well as its subtypes (MA and MO). Sensitivity analyses were applied to ensure the robustness of the results. Results Genetic correlation analysis identified 510 significant associations between cortical structural phenotypes and migraine across 401 distinct traits. Forward MR analysis revealed nine significant causal effects of cortical structural changes on migraine risk. Specifically, increased cortical thickness and local gyrification index in specific cortical regions were associated with a decreased risk of overall migraine, MA, and MO, while intracellular volume fraction and orientation diffusion index in specific regions increased the risk of MA and MO. Reverse MR analysis demonstrated that MA causally increased mean diffusivity in the insular and frontal opercular cortex. Sensitivity analyses confirmed the robustness of these findings, with no evidence of horizontal pleiotropy or heterogeneity. Conclusion This study identifies causal relationships between cortical neuroimaging phenotypes and migraine, highlighting potential biomarkers for migraine diagnosis, treatment, and prevention.

This article presents a Robust Servo Linear Quadratic Regulator (RSLQR) method based on the Linear Extended State Observer (LESO), which solves the problem of optimal tracking control of electro-optical system under disturbance. For the problem that the accuracy of the electro-optical tracking system is reduced due to disturbance and modeling error, the LESO is adopted in this article to obtain and compensate the influence of internal and external disturbances in the controlled object model, so as to improve the disturbance suppression ability of the electro-optical tracking system. Considering the influence of weighting matrix in the RSLQR method on system's dynamic response performance, this article presents a selection criterion of weighting matrix in the RSLQR to meet the performance requirements of closed-loop system. Through simulation analysis and experimental verification, the design method proposed in this article has great reference value for the optimization of the dynamic response performance of the electro-optical tracking system and the improvement of the disturbance suppression ability.

Abstract Tropospheric ozone is an air pollutant and a greenhouse gas whose anthropogenic production is limited principally by the supply of nitrogen oxides (NOx) from combustion. Tropospheric ozone in the northern hemisphere has been rising despite the flattening of NOx emissions in recent decades. Here we propose that this sustained increase could result from the photolysis of nitrate particles (pNO3−) to regenerate NOx. Including pNO3− photolysis in the GEOS‐Chem atmospheric chemistry model improves the consistency with ozone observations. Our simulations show that pNO3− concentrations have increased since the 1960s because of rising ammonia and falling SO2 emissions, augmenting the increase in ozone in the northern extratropics by about 50% to better match the observed ozone trend. pNO3− will likely continue to increase through 2050, which would drive a continued increase in ozone even as NOx emissions decrease. More work is needed to better understand the mechanism and rates of pNO3− photolysis.

Selenium-enriched Lentinus edodes (SL) is a kind of edible fungi rich in organic selenium and nutrients. Monascus purpureus with high monacolin K (MK) production and Saccharomyces cerevisiae were selected as the fermentation strains. A single-factor experiment and response surface methodology were conducted to optimize the production conditions for MK with higher contents from selenium-enriched Lentinus edodes fermentation (SLF). Furthermore, we investigated the nutritional components, antioxidant capacities, and volatile organic compounds (VOCs) of SLF. The MK content in the fermentation was 2.42 mg/g under optimal fermentation conditions. The organic selenium content of SLF was 7.22 mg/kg, accounting for 98% of the total selenium content. Moreover, the contents of total sugars, proteins, amino acids, reducing sugars, crude fiber, fat, and ash in SLF were increased by 9%, 23%, 23%, 94%, 38%, 44%, and 25%, respectively. The antioxidant test results demonstrated that 1.0 mg/mL of SLF exhibited scavenging capacities of 40%, 70%, and 79% for DPPH, ABTS, and hydroxyl radicals, respectively. Using gas chromatography–ion mobility spectrometry technology, 34 unique VOCs were identified in SLF, with esters, alcohols, and ketones being the main components of its aroma. This study showed that fungal fermentation provides a theoretical reference for enhancing the nutritional value of SL.

Drosophila spermatogenesis involves the renewal of germline stem cells, meiosis of spermatocytes, and morphological transformation of spermatids into mature sperm. We previously demonstrated that Ocnus (ocn) plays an essential role in spermatogenesis. The ValRS-m (Valyl-tRNA synthetase, mitochondrial) gene was down-regulated in ocn RNAi testes. Here, we found that ValRS-m-knockdown induced complete sterility in male flies. The depletion of ValRS-m blocked mitochondrial behavior and ATP synthesis, thus inhibiting the transition from spermatogonia to spermatocytes, and eventually, inducing the accumulation of spermatogonia during spermatogenesis. To understand the intrinsic reason for this, we further conducted transcriptome-sequencing analysis for control and ValRS-m-knockdown testes. The differentially expressed genes (DEGs) between these two groups were selected with a fold change of ≥2 or ≤1/2. Compared with the control group, 4725 genes were down-regulated (dDEGs) and 2985 genes were up-regulated (uDEGs) in the ValRS-m RNAi group. The dDEGs were mainly concentrated in the glycolytic pathway and pyruvate metabolic pathway, and the uDEGs were primarily related to ribosomal biogenesis. A total of 28 DEGs associated with mitochondria and 6 meiosis-related genes were verified to be suppressed when ValRS-m was deficient. Overall, these results suggest that ValRS-m plays a wide and vital role in mitochondrial behavior and spermatogonia differentiation in Drosophila.

The rapid advancement of unmanned aerial vehicle (UAV) technologies has led to an increasing demand for UAV operations in low-altitude, high-density, and complex airspace such as mountains or urban areas. In order to handle complex scenarios and ensure flight safety for UAVs with different flight missions beyond visual line of sight in such environments, a fusion framework of onboard autonomous flight trajectory management and decision-making system using global strategical path planning and local tactical trajectory optimization combination is proposed in this paper. The global strategical path planning is implemented by an enhanced A* algorithm under the multi-constraint of UAV positioning uncertainty and obstacle density to improve the safety and cost-effectiveness. The local tactical trajectory optimization is realized using quadratic programming to ensure smoothness, kinematic feasibility, and obstacle avoidance of the planned trajectory in dynamic environments. Receding-horizon control is used to ensure the flight path and trajectory planning efficiently and seamlessly. To assess the performance of the system, a terrain database and a navigation system are employed for environment and navigation performance simulation. The experimental results confirm that the fusion approach can realize better safety and cost-effectiveness through path planning with kino-dynamic feasible trajectory optimization.

Radiant cooling floors combined with ventilation systems have been widely applied in large space buildings. However, there has been a lack of research on system control strategies for their adaptation to weather changes. This study aimed to find control strategies for radiant cooling floors combined with displacement ventilation systems used in large space buildings in order to achieve energy conservation and environmental improvement. Supply air temperature and cooling surface temperature were determined to be the control variables. It was found that cooling capacity of the combined system and the comfort index, PMV (predicted mean vote), were linear in relation to the supply air temperature and cooling surface temperature. The linear equations regarding cooling capacity and PMV were established separately using environment data, and then the optimal region was determined. A case study on Terminal 3 of Xi’an Xianyang International Airport was conducted. The thermal environment was investigated through on-site measurements, questionnaires, and numerical simulations with CFD (computational fluid dynamics). It was found that supply air temperature and cooling surface temperature had a significant impact on PMV, and less impact on the cooling capacity. Therefore, it was determined that the supply air temperature should be altered first when the indoor temperature exceeds the upper limit, and then the cooling surface temperature should be changed if the indoor environment continues to overheat with the supply air temperature set to 18 °C. Thus, the supply air temperature was kept at 18 °C, and the floor surface temperature was set to be 22 °C on a high-temperature day. The average PMV was 0.87, and the cooling capacity of the combined system was 200 W/(m2·K), according to the CFD simulation. In addition, the surface heat transfer coefficient of the cooling floor was found to be 10.26 W/(m2·K). This research provides important references for the design and operational management of radiant cooling floors in large space buildings.

A modified Extended State Kalman Filter (ESKF)-based Model Predictive Control (MPC) algorithm is introduced to tailor the enhanced disturbance suppression in electro-optical tracking systems. Traditional control techniques, although robust, often struggle in scenarios with concurrent internal, external disturbances, and sensor noise. The proposed algorithm effectively overcomes these limitations by precisely estimating system states and actively mitigating disturbances, thus significantly boosting noise and perturbation control resilience. The primary contributions of this study include the integration of ESKF for accurate system state and disturbance estimation in noisy environments, the embedding of an ESKF estimation-compensation loop to simulate an improved disturbance-free system, and a simplified modeling approach for the controlled device. This designed structure minimizes the reliance on extensive system identification, easing the predictive control model-based constraints. Moreover, the approach incorporates total disturbance estimation into the optimization problem, safeguarding against actuator damage and ensuring high tracking accuracy. Through rigorous simulations and experiments, the ESKF-based MPC has demonstrated enhanced model error tolerance and superior disturbance suppression capabilities. Comparative analyses under varying model parameters and external disturbances highlight its exceptional trajectory tracking performance, even in the presence of model uncertainties and external noise.

A multi-channel phase-compensated active disturbance rejection control (MPADRC) incorporating an improved backstepping strategy is proposed in this paper to handle the phase lag in the extended state observer (ESO) and the residual uncertainty in the system. Firstly, a multi-channel phase-compensated ESO (MPESO) is constructed by adding phase-advanced networks to all output channels of the ESO, which allows disturbances and system states to be compensated and feedback in a more timely manner, respectively. Then, to estimate and offset the residual uncertainty in the system, an improved backstepping control method is employed and a Lyapunov function is designed to verify the convergence of the error between the estimated and actual values of the residual uncertainty. After that, the improved backstepping control is combined with MPADRC, and comparisons with the conventional linear active disturbance rejection control (LADRC) are conducted for a range of cases. Finally, on an inertial stabilization platform in the electro-optical tracking system (ETS), simulation and experimental results verified the effectiveness of the proposed method.

To address the problems of a low tracking accuracy and slow error convergence in high-order single-input, single-output electro-optical tracking systems, a backstepping control method based on a Softsign linear–nonlinear tracking differentiator is proposed. First, a linear–nonlinear tracking differentiator is designed in conjunction with the Softsign excitation function, using its output as an approximate replacement for the conventional differentiation process. Then, this is combined with backstepping control to eliminate the “explosion of complexity” problem in conventional backstepping procedures due to repeated derivation of virtual control quantities. This reduces the workload of parameter tuning, takes into account the rapidity and stability of signal convergence, and improves the trajectory tracking performance. This method can ensure the boundedness of the system signal. The effectiveness and superiority of this control method are verified through simulations and experiments.

The Chinese education system has been a subject of global interest, known for its emphasis on rigorous assessment practices and the ongoing pursuit of educational reform. The study delves into the landscape of educational reform and student evaluation practices within the Chinese education system, using the Singaporean Excellent School Model as a prism for evaluation. With a focus on nine quality criteria from the Singaporean model, the research aims to understand and enhance student evaluation processes in China. Assessing the impact of these practices on the overall education standard, the study gathers perspectives from educational leaders, teachers, students, and administrators regarding the role of leadership in fostering educational reform. Through a qualitative research approach, involving semi-structured interviews with 16 individuals in China's educational sphere, the study reveals a nuanced picture of evaluation processes. Traditional assessment methods, particularly standardized testing, persist, but formative assessment is gaining ground. Policymakers primarily drive education reform, emphasizing creativity and critical thinking, aligning with aspects of the Singaporean model. Leadership in the reform process manifests as distributed and visionary. This research significantly contributes to the discourse on education in China, offering a comprehensive understanding of assessment techniques, reform dynamics, leadership roles, and stakeholder perspectives. Building on prior research, it provides fresh insights into the diverse landscape of education reform in China, with implications for policymakers, educators, and stakeholders shaping the direction of Chinese education. [ABSTRACT FROM AUTHOR]