Analysis of Asperger Syndrome Using Genetic-Evolutionary Random Support Vector Machine Cluster

Asperger syndrome (AS) is subtype of autism spectrum disorder (ASD). Diagnosis and pathological analysis of AS through resting-state fMRI data is one of the hot topics in brain science. We employed a new model called the genetic-evolutionary random Support Vector Machine cluster (GE-RSVMC) to classify AS and normal people, and search for lesions. The model innovatively integrates the methods of the cluster and genetic evolution to improve the performance of the model. We randomly selected samples and sample features to construct GE-RSVMC, and then used the cluster to classify and extract lesions according to classification results. The model was validated by data of 157 participants (86 AS and 71 health controls) in ABIDE database. The classification accuracy of the model reached to 97.5% and we discovered the brain regions with significant differences, such as the Angular gyrus (ANG.R), Precuneus (PCUN.R), Caudate nucleus (CAU.R), Cuneus (CUN.R) and so on. Our method provides a new perspective for the diagnosis and treatment of AS, and a universal framework for other brain science research as the model has excellent generalization performance

Computational modeling of the cephalic arch with jugulocephalic vein variant predicts hemodynamic profiles in patients with brachiocephalic fistula

Background: The cephalic vein is often used in for arteriovenous fistula creation; however, the cephalic vein variation is common. This study will propose new theoretical explanations for a new discovered variation of cephalic vein draining into external jugular vein with “T-junction” shape by means of 3D computational hemodynamic modeling, which may provide reference for clinical practice. Methods: The precise measurements were conducted for the variant right cephalic vein draining into external jugular vein and for a normal right cephalic vein as a control. After processing the anatomical data, 3D geometrical model was reconstructed. Then, the influent field inside the variant jugulocephalic vein was mathematically modeled to get a detailed description of hemodynamic environment. Results: The anatomical parameters of the “T-junction” jugulocephalic vein variant were much more different from the normal right cephalic vein. The wall shear stress of variant cephalic vein at the corresponding position was higher and changed more rapidly than that of normal cephalic vein. The shear rate contour lines are disordered in several areas of the variant cephalic vein, indicating that the hemodynamic parameters in these areas are unstable. The hemodynamic characteristics at the confluence of the variant cephalic vein are more complex, with more areas where hemodynamic parameters are disrupted. Conclusions: The variation of cephalic arch in a “T-junction” with external jugular vein largely altered the fluid dynamics, especially in hemodialysis patients with brachiocephalic fistula in terms of the simulating flow in 3D computational model. This computational model provides hemodynamic profiles for stabilizing or modulating fluid dynamics in patients with jugulocephalic vein variant after brachiocephalic fistula

Complete remission of advanced pancreatic cancer induced by claudin18.2-targeted CAR-T cell therapy: a case report

Pancreatic cancer (PC) is one of the most malignant tumors in digestive system due to its highly invasive and metastatic properties. At present, conventional treatment strategies for PC show the limited clinical efficacy. Therefore, novel effective therapeutic strategies are urgently needed. Here, we report a case of complete remission of advanced PC induced by claudin18.2-targeted CAR-T cell therapy. The patient was a 72-year-old man who was diagnosed with pancreatic ductal adenocarcinoma 2 years ago, and he experienced tumor recurrence and multiple metastases after pancreaticoduodenectomy and multi-line chemotherapies, including liver, peritoneum, and cervical lymph node metastases. Then, the patient was referred to our department for further treatment of metastatic PC, and he was enrolled in a clinical trial of claudin18.2-targeted CAR-T cell therapy. After lymphodepleting chemotherapy, the patient received claudin18.2-targeted CAR-T cell infusion at a dose of 1.2 × 106 cells/kg on November 21, 2022. During CAR-T cell therapy, the patient experienced grade 2 cytokine release syndrome (CRS) and gastric mucosa injury, which were controlled by tocilizumab and conventional symptomatic and supportive treatment. The patient achieved a complete response (CR) 1 month after claudin18.2-targeted CAR-T cell therapy, and remained in clinical remission for 8 months. Unfortunately, the patient experienced claudin18.2-negative relapse in July, 2023. Despite antigen-negative relapse after claudin18.2-targeted CAR-T cell infusion, the patient achieved sustained remission for 8 months, which indicates that claudin18.2-targeted CAR-T cell therapy is an extremely effective therapeutic strategy for the treatment of advanced PC

China’s 10-year progress in DC gas-insulated equipment: From basic research to industry perspective

The construction of the future energy structure of China under the 2050 carbon-neutral vision requires compact direct current (DC) gas-insulation equipment as important nodes and solutions to support electric power transmission and distribution of long-distance and large-capacity. This paper reviews China's 10-year progress in DC gas-insulated equipment. Important progresses in basic research and industry perspective are presented, with related scientific issues and technical bottlenecks being discussed. The progress in DC gas-insulated equipment worldwide (Europe, Japan, America) is also reported briefly

Reflections on teaching and learning issues of integrated education in China based on UDL concept

Universal Design for Learning (UDL) has the potential to provide equal learning opportunities to various kinds of learners, which not only help address differential treatment in segregated education but also provide students with the same quality education. This study compares the current problems of integrated education in China in order to explore the necessity and countermeasures for the application of UDL in integrated education in China

RIS-Assisted Network Slicing Resource Optimization Algorithm for Coexistence of eMBB and URLLC

Enhanced mobile broadband (eMBB) and Ultra-Reliable and Low-Latency Communications (URLLC) are the two main services in the fifth-generation mobile network. URLLC services have stringent latency and reliability requirements, while eMBB services are designed to provide extremely high data rates for content delivery. The differentiated Quality of Service (QoS) requirements of the two services make their coexistence on the same bandwidth resources a challenging issue. To meet this challenge, we introduce reconfigurable intelligent surface (RIS) technology to assist in solving the resource allocation problem. The problem is formulated as two optimization problems. For the eMBB allocation problem, we jointly optimize the resource block allocation, power allocation, and RIS phase shift matrix and propose a two-stage alternating iterative algorithm to maximize the total traversal capacity of eMBB users. For the URLLC allocation problem, we maximize the URLLC packet reception rate and minimize the amount of eMBB rate loss while ensuring the quality of service for eMBB and URLLC. A heuristic URLLC allocation algorithm based on pre-configured RIS is proposed. Simulation results show that the proposed algorithm can meet the strict delay requirements of URLLC even when the URLLC packet reception rate is nearly 95.5%. Meanwhile, the total loss rate of eMBB service caused by the reuse of URLLC service is less than 6%. Thus, the applicability of the proposed solution to the coexistence problem is demonstrated

Research on Wear Resistance of AISI 9310 Steel with Micro-Laser Shock Peening

Improving the wear resistance of turbine engine drive components is crucial. This study presented a new Laser Shock Peening (LSP) technique: Micro-Laser Shock Peening (Micro-LSP) technology for surface modification and strengthening of AISI 9310 steel. The effects of different pulse energies (50 mJ, 150 mJ, 200 mJ) on surface morphology, mechanical properties, and wear behavior were investigated. The results showed that the Micro-LSP treatment reduced the wear rate by 56% to 74%. The dimpled structure induced during the strengthening process increased the surface roughness and reduced the contact area; moreover, the coefficient of friction (COF) was reduced. The treatment also had the effect of reducing the wear rate by collecting abrasive debris and changing some of the sliding wear into rolling wear. The reduced wear rate was a result of the combined effect of the dimpled structure and the hardened layer. In addition, a deeper hardened layer also slows down the onset of wear behavior. Micro-LSP technology offers completely new methods and possibilities for wear reduction

Engineered Microbial Cell Factories for Sustainable Production of L-Lactic Acid: A Critical Review

With the increasing demand for the biodegradable polymer material polylactic acid and its advantage of being metabolized by the human body, L-lactic acid (L-LA) is becoming increasingly attractive in environmental protection and food industry applications. However, the supply of L-LA is not satisfied, and the price is still high. Compared to enzymatic and chemical synthesis methods, L-LA production by microbial fermentation has the advantages of low cost, large yield, simple operation, and environmental protection. This review summarizes the advances in engineering microbial cell factories to produce L-LA. First, the synthetic pathways and microorganisms for L-LA production are outlined. Then, the metabolic engineering strategies for constructing cell factories to overproduce L-LA are summarized and fermentation modes for L-LA production are also given. Finally, the challenges and prospects of the microbial production of L-LA are discussed. This review provides theoretical guidance for researchers engaged in L-LA production

Moisture Prediction of Transformer Oil-Immersed Polymer Insulation by Applying a Support Vector Machine Combined with a Genetic Algorithm

The support vector machine (SVM) combined with the genetic algorithm (GA) has been utilized for the fault diagnosis of transformers since its high accuracy. In addition to the fault diagnosis, the condition assessment of transformer oil-immersed insulation conveys the crucial engineering significance as well. However, the approaches for getting GA-SVM used to the moisture prediction of oil-immersed insulation have been rarely reported. In view of this issue, this paper pioneers the application of GA-SVM and frequency domain spectroscopy (FDS) to realize the moisture prediction of transformer oil-immersed insulation. In the present work, a method of constructing a GA-SVM multi-classifier for moisture diagnosis based on the fitting analysis model is firstly reported. Then, the feasibility and reliability of the reported method are proved by employing the laboratory and field test experiments. The experimental results indicate that the reported prediction model might be serviced as a potential tool for the moisture prediction of transformer oil-immersed polymer insulation