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This year marks the 20th anniversary of the discovery of LaAlO3/SrTiO3 (LAO/STO) oxide heterointerfaces. Since their discovery, transition metal oxide (TMO) interfaces have emerged as a fascinating and fast‐growing area of research, offering a variety of unique and exotic physical properties which has provided a strong impetus for the rapid advances and actualization of oxide electronics. This review revisits the fundamental mechanisms accounting for the two‐dimensional (2D) conducting interfaces, and how new models proposed to better account for the unique interfacial effects. Recent breakthroughs in the theoretical and experimental domains of oxide interfaces are also discussed including the detection and investigation of 2D quasiparticle. Moving beyond the well‐known LAO/STO interface, this review delves into other systems where unconventional interfacial superconductivity, interfacial magnetism, and spin polarization are dealt with in greater detail. In terms of device applications, this review proceeds with a treatment on the recent developments in domains including field effect transistors and freestanding heterostructure membranes. By emphasizing the opportunities and challenges of integrating oxide interfaces with existing technologies, the review will end off with an outlook projecting the progress and the trajectory of this research domain in the years to come. [ABSTRACT FROM AUTHOR]

StarCraft is a popular real-time strategy game that has been widely used as a research platform for artificial intelligence. Micromanagement refers to the process of making each unit perform appropriate actions separately, depending on the current state in the the multi-agent system comprising all of the units, i.e., the fine-grained control of individual units for common benefit. Therefore, cooperation between different units is crucially important to improve the joint strategy. We have selected multi-agent deep reinforcement learning to tackle the problem of micromanagement. In this paper, we propose a method for learning cooperative strategies in StarCraft based on role-based montonic value function factorization (RoMIX). RoMIX learns roles based on the potential impact of each agent on the multi-agent task; it then represents the action value of a role in a mixed way based on monotonic value function factorization. The final value is calculated by accumulating the action value of all roles. The role-based learning improves the cooperation between agents on the team, allowing them to learn the joint strategy more quickly and efficiently. In addition, RoMIX can also reduce storage resources to a certain extent. Experiments show that RoMIX can not only solve easy tasks, but it can also learn better cooperation strategies for more complex and difficult tasks. [ABSTRACT FROM AUTHOR]

We performed a meta‐analysis to compare the effect of preoperative and postoperative radiotherapy on wound complications after resection of extremity soft tissue sarcoma (ESTS). A comprehensive computerised search of the PubMed, Cochrane Library, Web of Science, EMBASE, China National Knowledge Infrastructure (CNKI), VIP, and Wanfang databases was conducted from their inception to August 2023 to identify studies comparing the effect of preoperative and postoperative radiotherapy on wound complications after ESTS resection. Two investigators independently screened the literature, extracted the data, and assessed the quality of the articles. The meta‐analysis was performed using RevMan 5.4 software. Nine studies with 1271 patients were included, with 631 and 640 patients in the preoperative and postoperative radiotherapy groups, respectively. The results showed that the incidence of postoperative wound complications after ESTS resection was significantly higher with preoperative radiotherapy than with postoperative radiotherapy (27.26% vs. 12.03%, odds ratio [OR]: 2.88, 95% confidence interval [CI]: 2.12–3.91, p < 0.001). However, the rate of local recurrence of ESTS was significantly lower with preoperative radiotherapy than with postoperative radiotherapy (8.75% vs. 14.81%, OR: 0.57, 95% CI: 0.36–0.91, p = 0.02), and the 3‐year overall survival was significantly higher in the preoperative radiotherapy group than in the postoperative radiotherapy group (82.24% vs. 70.04%, OR: 1.97, 95% CI: 1.05–3.71, p = 0.03). This pooled analysis suggests that although preoperative radiotherapy increases the rate of wound complications in ESTS compared with postoperative radiotherapy, it significantly reduces the rate of local recurrence after ESTS resection and improves the overall survival of patients. Owing to the limitations in the number and quality of the included studies, additional prospective cohort studies or randomised controlled trials are required to confirm these findings. [ABSTRACT FROM AUTHOR]

In this study, both experiments and computational fluid dynamics simulations were performed to investigate the transport characteristics of transient high-temperature dust in a tee duct. The experimental results showed that there is a cavity downstream of the main duct. The simulation results showed that the second flow was generated downstream, and the high-temperature dust moved to the top of the main duct owing to thermal expansion and buoyancy. The temperature change in the particles depended on the site, and the temperature of the particles in the center was higher than that of the surrounding particles. The thermal expansion and buoyancy of high-temperature fluids affected the particle motion through the drag force. The deposition of particles was wing-like and was mainly present on both sides of the tee duct, which was five times the diameter of the main duct. This study provides theoretical guidance for the development of industrial ventilation systems. [ABSTRACT FROM AUTHOR]

Applying soil amendments such as biochar has been proposed as a means to improve soil properties and reduce greenhouse gas emission from agricultural soils. The objective of this study was to evaluate and compare the effects of biochar and straw application on rice yield, select soil properties, global warming potential (GWP), and greenhouse gas intensity (GHGI) over the 3-year period. The study treatments included control (CN), barley straw biochar (BC, 2,000 kg ha−1), barley straw (BS, 2,000 kg ha−1), and BC+BS (each 1,000 kg ha−1). During the rice-growing season, significant interactive effects of BC and BS treatment were observed in major soil properties. The average rice yields in BC, BS, and BC+BS treatments increased by 4.6%, 4.7%, and 18.7%, compared with CN treatment, respectively. Also, BC+BS treatment produced relatively stable yield during the 3-year study. Both BC and BS applications, either alone or in combination, lowered soil bulk density values compared to the CN treatment. Further, BC application produced a low total CH4 flux than other treatments. The total produced GWP over the 3 years occurred in the order: BS ≧ CN > BC+BS > BC treatment. These results clearly demonstrate the advantages of biochar and straw applications in improving rice yield and soil fertility while reducing GWP and GHGI. [ABSTRACT FROM AUTHOR]

Summary: Due to the limited fast dynamic response of the dual proportional‐integral (PI) control strategy in sensorless speed control, a novel composite control strategy is proposed for sensorless control of the full speed range of the surface‐mounted permanent magnet synchronous motor. This strategy combines dual closed‐loop model predictive control (MPC) with a sliding mode observer (SMO) and a constant current‐frequency ratio (I‐f). The I‐f control scheme is employed in the low‐speed range, while the SMO is utilized for motor speed and rotor position estimation in the medium and high‐speed ranges, enabling the dual‐loop MPC. Furthermore, a new smooth switching method is proposed for transitioning between the two control methods. In addition, the MPC outer loop parameters were thoroughly analyzed and optimized for better dynamic performance of sensorless control. The steady‐state performance of this control strategy is compared to PI control and improved the dynamic responsiveness of the system. Experiments have verified the feasibility of this strategy. Under the control of the MPC outer loop, the steady‐state speed fluctuation of the motor is within 10 r/min. Compared to PI control, the motor settling time was reduced by 17% and 60% during the start‐up phase and after a sudden speed change, respectively. [ABSTRACT FROM AUTHOR]

Aims: To analyse spatial and temporal changes in the global burden of diabetes mellitus (DM) attributable to dietary factors from 1990 to 2019. Materials and Methods: The burden of DM was analysed in terms of age‐standardized disability‐adjusted life‐year (DALY) rates and age‐standardized death rates (ASDRs), which were obtained from the Global Burden of Disease Study 2019, and their corresponding estimated annual percentage changes (EAPCs). Results: The ASDR exhibited a decreasing trend (EAPC = −0.02), while the age‐standardized DALY rate exhibited an increasing trend (EAPC = 0.65). Forty‐four percent of the burden of DM was attributable to dietary factors, with the three largest contributors being high intake of red meat, high intake of processed meat, and low intake of fruit. Residence in a region with a high sociodemographic index (SDI) was associated with a diet low in whole grains and high in red meat and processed meat, while residence in a low‐SDI region was associated with a diet low in whole grains and fruits, and high in red meat. Conclusions: The age‐standardized DALYs of DM attributable to dietary factors increased between 1990 and 2019 but differed among areas. The three largest dietary contributors to the burden of DM were high intake of red meat, high intake of processed meat, and low intake of fruit. [ABSTRACT FROM AUTHOR]

Traffic emissions are a major source of ambient air pollution, and exposure to these emissions has been linked to numerous adverse health effects. Our study investigated the reduction of traffic emissions in downtown Tianjin, China, and assessed its health benefits. Based on the vehicle emission inventory, The Atmospheric Dispersion Modelling System (ADMS) was adopted for simulating the dispersion of traffic-related air pollutants including primary fine particulate matter (PM2.5), and carbon monoxide (CO). The Benefits Mapping and Analysis Program (BenMAP) was then used to quantify the benefits of emission reductions with respect to cardiovascular disease and respiratory disease. We found a downward trend in PM2.5 and CO concentrations from 2015 to 2019 (PM2.5: 17.8 to 10.5μg/m3, CO: 2.3 to 1.3mg/m3). Furthermore, in line with the reduction of average annual PM2.5 and CO attributable to traffic emissions during 2016–2019 compared with 2015, the accumulative deaths from the two diseases mentioned above in these years decreased by 156 and 961 respectively. Our study constructs an integrated framework combining emission inventories, air quality modeling, and population health benefits, which can be used for further health effects of related air quality improvement. [ABSTRACT FROM AUTHOR]

This study investigates the impact of different conductive buffer electrode layers on the electrical properties, fatigue behavior and phase transition of epitaxial KNN-based ferroelectric films. Two types of buffer electrode layers, p-type La0.67Ca0.33MnO3/La0.67Ba0.33MnO3 and n-type LaNiO3/Nb-SrTiO3, are selected for analysis. The results demonstrate that the electrical properties and fatigue behavior of the KNN-based films are significantly influenced by the buffer electrode layers. Specifically, the KNN-based films buffered with p-type electrodes exhibit superior ferroelectric/dielectric properties and fatigue resistance compared to those buffered with n-type electrodes. The ferroelectric hysteresis loops of p-type electrode buffered KNN-based films demonstrate higher saturation, larger twice remnant polarization (2Pr) and higher dielectric constant (ε) (2Pr = 58.5/46.9 μC cm−2 and ε = 1290/1003 for La0.67Ca0.33MnO3/La0.67Ba0.33MnO3-buffered KNNLT-M films) compared to the films grown on n-type electrodes (2Pr = 29.5/24.5 μC cm−2 and ε = 802/668 for LaNiO3/Nb-SrTiO3-buffered KNNLT-M films). Moreover, the KNN-based films grown on p-type buffer electrode layers exhibit high fatigue resistance, maintaining consistent ferroelectric hysteresis loops even after 108 bipolar switching cycles, while those on n-type buffer electrode layers experience dramatic fatigue after only 106 cycles. Temperature-dependent dielectric analysis reveals that all studied KNN-based films exhibit relaxor ferroelectric behavior, with the p-type electrode buffered films exhibiting higher phase transition temperatures than the n-type electrode buffered films. These findings demonstrate that the conductive type of the buffer electrode layer can effectively tune the performance of KNN-based films, indicating the high application potential in lead-free electronic device. [ABSTRACT FROM AUTHOR]

The theory of compressive sampling (CS) has revolutionized data compression technology by capitalizing on the inherent sparsity of a signal to enable signal recovery from significantly far fewer samples than what is required by the Nyquist–Shannon sampling theorem. Recent advancement in deep generative models, which can represent high-dimension data in a low-dimension latent space efficiently when trained with big data, has been used to further reduce the sample size for image data compressive sampling. However, compressive sampling for 1D time series data has not significantly benefited from this technological progress. In this study, we investigate the application of different architectures of deep neural networks suitable for time series data compression and propose an efficient method to solve the compressive sampling problem on one-dimensional (1D) structural health monitoring (SHM) data, based on block CS and the vector quantized–variational autoencoder model with a naïve multitask paradigm (VQ-VAE-M). The proposed method utilizes VQ-VAE-M to learn the data characteristics of the signal, replaces the "hard constraint" of sparsity to realize the compressive sampling signal reconstruction and thereby does not need to select the appropriate sparse basis for the signal. A comparative analysis against various CS methods and other deep neural network models was performed in both synthetic data and real-world data from two real bridges in China. The results have demonstrated the superiority of the proposed method, with achieving the smallest reconstruction error of 0.038, 0.034 and 0.021, and the highest reconstruction accuracy of 0.882, 0.892 and 0.936 for compression ratios of 4.0, 2.66, and 2.0, respectively. [ABSTRACT FROM AUTHOR]