The therapeutic effects of low-intensity pulsed ultrasound in musculoskeletal soft tissue injuries: Focusing on the molecular mechanism

Musculoskeletal soft tissue injuries are very common and usually occur during both sporting and everyday activities. The intervention of adjuvant therapies to promote tissue regeneration is of great importance to improving people’s quality of life and extending their productive lives. Though many studies have focused on the positive results and effectiveness of the LIPUS on soft tissue, the molecular mechanisms standing behind LIPUS effects are much less explored and reported, especially the intracellular signaling pathways. We incorporated all research on LIPUS in soft tissue diseases since 2005 and summarized studies that uncovered the intracellular molecular mechanism. This review will also provide the latest evidence-based research progress in this field and suggest research directions for future experiments

Transvaginal versus transabdominal specimen extraction surgery for right colon cancer: A propensity matching study

BackgroundThe transvaginal route for specimen extraction is considered ideal for colorectal surgery, but its safety is still questioned. There has been little research on transvaginal natural orifice specimen extraction surgery (NOSES) in the right hemicolectomy. As a result, we conducted a study comparing transvaginal NOSES to traditional transabdominal specimen extraction surgery.Patients and methodsData on female patients who underwent radical right hemicolectomy at the First Affiliated Hospital of Nanchang University between January 2015 and December 2020 were collected retrospectively. A total of 847 patients were compliant, with 51 undergoing the transvaginal specimen extraction surgery (NOSES) group and 796 undergoing the transabdominal specimen extraction surgery (TISES) group. A propensity score matching method (1:2) was used to balance the clinicopathological characteristics of the two groups.ResultsFinally, 138 patients were enrolled in our study, with 46 in the NOSES group and 92 in the TISES group. Compared to the TISES group, the NOSES group had less intraoperative blood loss (p = 0.036), shorter time to first flatus (p < 0.001), shorter time to first liquid diet (p < 0.001), lower postoperative white blood cell counts (p = 0.026), lower C-reactive protein levels (p = 0.027), and lower visual analog scale (VAS) scores (p < 0.001). Regarding the quality of life after surgery, the NOSES group had better role function (p < 0.01), emotional function (p < 0.001), and improved symptoms of postoperative pain (p < 0.001) and diarrhea (p = 0.024). The scar satisfaction was significantly higher in the NOSES group than in the TISES group. Overall survival and disease-free survival in two groups were similar.ConclusionThe short-term results of transvaginal NOSES were superior to conventional transabdominal specimen extraction surgery. At the same time, transvaginal NOSES could improve the abdominal wall appearance and quality of life. The long-term survival was similar in the two surgical approaches. Therefore, transvaginal NOSES is worthy of our implementation and promotion

Covariant entanglement wedge cross-section, balanced partial entanglement and gravitational anomalies

The balanced partial entanglement (BPE) was observed to give the reflected entropy and the entanglement wedge cross-section (EWCS) for various mixed states in different theories \cite{Wen:2021qgx,Camargo:2022mme}. It can be calculated in different purifications, and is conjectured to be independent from purifications. In this paper we calculate the BPE and the EWCS in generic covariant scenarios in two-dimensional (holographic) CFTs with and without gravitational anomalies, and find that they coincide with the reflected entropy. In covariant configurations we determine the partition for the purifying system with the help of the gravitational anomalies, and we extend our discussion to topological massive gravity (TMG). We give the first prescription to evaluate the entropy quantity associated to the EWCS beyond Einstein gravity, i.e. the correction to the EWCS from the Chern-Simons term in TMG. Apart from the gravity theory and geometry, further input from the mixed state should be taken into account.Comment: 37 pages, 8 figures; v2: references updated, a few typos fixed, more calculation details adde

Balanced partial entanglement and mixed state correlations

Recently in Ref. [1], one of the authors introduced the balanced partial entanglement (BPE), which has been proposed to be dual to the entanglement wedge cross-section (EWCS). In this paper, we explicitly demonstrate that the BPE could be considered as a proper measure of the total intrinsic correlation between two subsystems in a mixed state. The total correlation includes certain crossing correlations, which are minimized by particular balance conditions. By constructing a class of purifications from Euclidean path-integrals, we find that the balanced crossing correlations show universality and can be considered as the generalization of the Markov gap for the canonical purification. We also test the relation between the BPE and the EWCS in three-dimensional asymptotically flat holography. We find that the balanced crossing correlation vanishes for the field theory invariant under BMS3 symmetry (BMSFT) and dual to the Einstein gravity, indicating the possibility of a perfect Markov recovery. We further elucidate these crossing correlations as a signature of tripartite entanglement and explain their interpretation in both AdS and non-AdS holography

Balanced Partial Entanglement and Mixed State Correlations

Recently in Ref.\cite{Wen:2021qgx}, one of the authors introduced the balanced partial entanglement (BPE), which has been proposed to be dual to the entanglement wedge cross-section (EWCS). In this paper, we explicitly demonstrate that the BPE could be considered as a proper measure of the total intrinsic correlation between two subsystems in a mixed state. The total correlation includes certain crossing correlations which are minimized on some balance conditions. By constructing a class of purifications from Euclidean path-integrals, we find that the balanced crossing correlations show universality and can be considered as the generalization of the Markov gap for canonical purification. We also test the relation between the BPE and the EWCS in three-dimensional asymptotically flat holography. We find that the balanced crossing correlation vanishes for the field theory invariant under BMS$_3$ symmetry (BMSFT) and dual to the Einstein gravity, indicating the possibility of a perfect Markov recovery. We further elucidate these crossing correlations as a signature of tripartite entanglement and explain their interpretation in both AdS and non-AdS holography.Comment: 37 pages, 9 figure

A multi-agent reinforcement learning-based method for server energy efficiency optimization combining DVFS and dynamic fan control

With the rapid development of the digital economy and intelligent industry, the energy consumption of data centers (DCs) has increased significantly. Various optimization methods are proposed to improve the energy efficiency of servers in DCs. However, existing solutions usually adopt model-based heuristics and best practices to select operations, which are not universally applicable. Moreover, existing works primarily focus on the optimization methods for individual components, with a lack of work on the joint optimization of multiple components. Therefore, we propose a multi-agent reinforcement learning-based method, named MRDF, combining DVFS and dynamic fan control to achieve a trade-off between power consumption and performance while satisfying thermal constraints. MRDF is model-free and learns by continuously interacting with the real server without prior knowledge. To enhance the stability of MRDF in dynamic environments, we design a data-driven baseline comparison method to evaluate the actual contribution of a single agent to the global reward. In addition, an improved Q-learning is proposed to deal with the large state and action space of the multi-core server. We implement MRDF on a Huawei Taishan 200 server and verify the effectiveness by running benchmarks. Experimental results show that the proposed method improves energy efficiency by an average of 3.9% compared to the best baseline solution, while flexibly adapting to different thermal constraints

Effects of Low Pressure Injection on Fuel Atomization and Mixture Formation for Heavy Fuel Engines

The application of direct injection (DI) technology can effectively improve the atomization effect of heavy fuel to reduce the fuel loss of heavy fuel engines (HFE). The fuel spray characteristics directly affect the combustion performance of the engine. To investigate the atomization process and evaporation characteristics of heavy fuel in-cylinder for an air-assisted direct injection (AADI) engine, a simulation calculation model of AADI HFE was established with the use of a computational fluid dynamics tool. The air-assisted injector model and the one-dimensional performance calculation model were verified by test data. The influences of injection timing and injection pressure on the spray characteristics and mixture formation in the engine cylinder were discussed. The results show that the mixture concentration distribution is uniform after the injection timing is advanced, and the mass fraction of the fuel evaporation increases. The earlier injection timing can provide the fuel with sufficient time to evaporate, while the later injection timing will result in increasing the Sauter mean diameter (SMD) of the fuel droplets, and the unevaporated heavy fuel in the combustion chamber tends to become concentrated. With the increase in air injection pressure, the distribution of the mixed gas in the cylinder becomes uniform, and the SMD of the fuel droplets in the cylinder decreases. When the injection pressure is 0.65 MPa and 0.75 MPa, the difference between the SMD of the fuel droplets in-cylinder decreases, and a favorable fuel atomization effect can be maintained

Compressor Performance Prediction Based on the Interpolation Method and Support Vector Machine

Compressors are important components in various power systems in the field of energy and power. In practical applications, compressors often operate under non-design conditions. Therefore, accurate calculation on performance under various operating conditions is of great significance for the development and application of certain power systems equipped with compressors. To calculate and predict the performance of a compressor under all operating conditions through limited data, the interpolation method was combined with a support vector machine (SVM). Based on the known data points of compressor design conditions, the interpolation method was adopted to obtain training samples of the SVM. In the calculation process, preliminary screening was conducted on the kernel functions of the SVM. Two interpolation methods, including linear interpolation and cubic spline interpolation, were used to obtain sample data. In the subsequent training process of the SVM, the genetic algorithm (GA) was used to optimize its parameters. After training, the available data were compared with the predicted data of the SVM. The results show that the SVM uses the Gaussian kernel function to achieve the highest prediction accuracy. The prediction accuracy of the SVM trained with the data obtained from linear interpolation was higher than that of cubic spline interpolation. Compared with the back propagation neural network optimized by the genetic algorithm (GA-BPNN), the genetic algorithm optimization of extreme learning machine neural network (GA-ELMNN), and the genetic algorithm optimization of generalized regression neural network (GA-GRNN), the support vector machine optimized by the genetic algorithm (GA-SVM) has a better generalization, and GA-SVM is more accurate in predicting boundary data than the GA-BPNN. In addition, reducing the number of original data points still enables the GA-SVM to maintain a high level of predictive accuracy