Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Large language models have demonstrated remarkable performance across various natural language processing tasks; however, their efficacy in more challenging and domain-specific tasks remains less explored. This paper introduces the GAOKAO-Benchmark (GAOKAO-Bench), an intuitive benchmark that employs questions from the Chinese Gaokao examination as test samples for evaluating large language models.In order to align the evaluation results with humans as much as possible, we designed a method based on zero-shot prompts to analyze the accuracy and scoring rate of the model by dividing the questions into subjective and objective types. We evaluated the ChatGPT model on GAOKAO-Benchmark performance.Our findings reveal that the ChatGPT model excels in tackling objective questions, while also shedding light on its shortcomings and areas for improvement. To further scrutinize the model's responses, we incorporate human evaluations.In conclusion, this research contributes a robust evaluation benchmark for future large-scale language models and offers valuable insights into the limitations of such models

ViTAR: Vision Transformer with Any Resolution

This paper tackles a significant challenge faced by Vision Transformers (ViTs): their constrained scalability across different image resolutions. Typically, ViTs experience a performance decline when processing resolutions different from those seen during training. Our work introduces two key innovations to address this issue. Firstly, we propose a novel module for dynamic resolution adjustment, designed with a single Transformer block, specifically to achieve highly efficient incremental token integration. Secondly, we introduce fuzzy positional encoding in the Vision Transformer to provide consistent positional awareness across multiple resolutions, thereby preventing overfitting to any single training resolution. Our resulting model, ViTAR (Vision Transformer with Any Resolution), demonstrates impressive adaptability, achieving 83.3\% top-1 accuracy at a 1120x1120 resolution and 80.4\% accuracy at a 4032x4032 resolution, all while reducing computational costs. ViTAR also shows strong performance in downstream tasks such as instance and semantic segmentation and can easily combined with self-supervised learning techniques like Masked AutoEncoder. Our work provides a cost-effective solution for enhancing the resolution scalability of ViTs, paving the way for more versatile and efficient high-resolution image processing

Detecting Thalamic Abnormalities in Autism Using Cylinder Conformal Mapping

Abstract. A number of studies have documented that autism has a neurobiological basis, but the anatomical extent of these neurobiological abnormalities is largely unknown. In this paper, we applied advanced computational techniques to extract 3D surface models of the thalamus and subsequently analyze highly localized shape variations in a homogeneous group of autism children. In particular, a new conformal parameterization for high genus surfaces is applied in our shape analysis work, which maps the surfaces onto a cylinder domain. Surface matching among different individual meshes is achieved by re-triangulating each mesh according to the template. Children with autism and their controls are compared, and statistical significant abnormalities in thalamus of autism are detected

Research on Secure Localization Model Based on Trust Valuation in Wireless Sensor Networks

Secure localization has become very important in wireless sensor networks. However, the conventional secure localization algorithms used in wireless sensor networks cannot deal with internal attacks and cannot identify malicious nodes. In this paper, a localization based on trust valuation, which can overcome a various attack types, such as spoofing attacks and Sybil attacks, is presented. The trust valuation is obtained via selection of the property set, which includes estimated distance, localization performance, position information of beacon nodes, and transmission time, and discussion of the threshold in the property set. In addition, the robustness of the proposed model is verified by analysis of attack intensity, localization error, and trust relationship for three typical scenes. The experimental results have shown that the proposed model is superior to the traditional secure localization models in terms of malicious nodes identification and performance improvement

Study of andrographolide bioactivity against Pseudomonas aeruginosa based on computational methodology and biochemical analysis

Andrographolide is one of the main biologically active molecules isolated from Andrographis paniculata (A. paniculata), which is a traditional Chinese herb used extensively throughout Eastern Asia, India, and China. Pseudomonas aeruginosa, often known as P. aeruginosa, is a common clinical opportunistic pathogen with remarkable adaptability to harsh settings and resistance to antibiotics. P. aeruginosa possesses a wide array of virulence traits, one of which is biofilm formation, which contributes to its pathogenicity. One of the main modulators of the P. aeruginosa-controlled intramembrane proteolysis pathway is AlgW, a membrane-bound periplasmic serine protease. In this work, we have used a set of density functional theory (DFT) calculations to understand the variety of chemical parameters in detail between andrographolide and levofloxacin, which show strong bactericidal activity against P. aeruginosa. Additionally, the stability and interaction of andrographolide and levofloxacin with the protein AlgW have been investigated by molecular docking and molecular dynamics (MD) simulations . Moreover, the growth and inhibition of biofilm production by P. aeruginosa experiments were also investigated, providing insight that andrographolide could be a potential natural product to inhibit P. aeruginosa

Age over sex: evaluating gut microbiota differences in healthy Chinese populations

Age and gender have been recognized as two pivotal covariates affecting the composition of the gut microbiota. However, their mediated variations in microbiota seem to be inconsistent across different countries and races. In this study, 613 individuals, whom we referred to as the “healthy” population, were selected from 1,018 volunteers through rigorous selection using 16S rRNA sequencing. Three enterotypes were identified, namely, Escherichia–Shigella, mixture (Bacteroides and Faecalibacterium), and Prevotella. Moreover, 11 covariates that explain the differences in microbiota were determined, with age being the predominant factor. Furthermore, age-related differences in alpha diversity, beta diversity, and core genera were observed in our cohort. Remarkably, after adjusting for 10 covariates other than age, abundant genera that differed between age groups were demonstrated. In contrast, minimal differences in alpha diversity, beta diversity, and differentially abundant genera were observed between male and female individuals. Furthermore, we also demonstrated the age trajectories of several well-known beneficial genera, lipopolysaccharide (LPS)-producing genera, and short-chain fatty acids (SCFAs)-producing genera. Overall, our study further elucidated the effects mediated by age and gender on microbiota differences, which are of significant importance for a comprehensive understanding of the gut microbiome spectrum in healthy individuals

The comparison of manual and mechanical anastomosis after total pharyngolaryngoesophagectomy

BackgroundTotal pharyngolaryngoesophagectomy (TPLE) is considered as a curative treatment for hypopharynx cancer and cervical esophageal carcinomas (HPCECs). Traditional pharyngo-gastric anastomosis is usually performed manually, and postoperative complications are common. The aim of this study was to introduce a new technique for mechanical anastomosis and to evaluate perioperative outcomes and prognosis.MethodsFrom May 1995 to Nov 2021, a series of 75 consecutive patients who received TPLE for a pathological diagnosis of HPCECs at Sun Yat-sen Memorial Hospital were evaluated. Mechanical anastomosis was performed in 28 cases and manual anastomosis was performed in 47 cases. The data from these patients were retrospectively analyzed.ResultsThe mean age was 57.6 years, and 20% of the patients were female. The rate of anastomotic fistula and wound infection in the mechanical group were significantly lower than that in the manual group. The operation time, intraoperative blood loss and postoperative hospital stays were significantly higher in the manual group than that in the mechanical group. The R0 resection rate and the tumor characteristics were not significantly different between groups. There was no significant difference in overall survival and disease-free survival between the two groups.ConclusionThe mechanical anastomosis technology adopted by this study was shown to be a safer and more effective procedure with similar survival comparable to that of manual anastomosis for the HPCECs patients

Effects of esketamine on postoperative rebound pain in patients undergoing unilateral total knee arthroplasty: a single-center, randomized, double-blind, placebo-controlled trial protocol

IntroductionRebound pain, transient and acute postoperative pain after the disappearance of regional block anesthesia, has been a concern in recent years. Insufficient preemptive analgesia and hyperalgesia induced by regional block are the main mechanisms. At present, the evidence for the treatment of rebound pain is limited. The esketamine, as an antagonist of the N-methyl-D-aspartate receptor, has been proven to prevent hyperalgesia. Therefore, this trial aims to evaluate the impact of esketamine on postoperative rebound pain in patients undergoing total knee arthroplasty.Methods/designThis study is a single-center, prospective, double-blind, randomized, placebo-controlled trial. Participants who plan to undergo total knee arthroplasty will be randomly assigned to the esketamine group (N = 178) and placebo group (N = 178) in a ratio of 1:1. This trial aims to evaluate the impact of esketamine on postoperative rebound pain in patients undergoing total knee arthroplasty. The primary outcome of this trial is the incidence of rebound pain within 12 h after the operation in the esketamine group and the placebo group. The secondary outcome will be to compare (1) the incidence of rebound pain 24 h after the operation; (2) the time to enter the pain cycle for the first time within 24 h after the procedure; (3) the first time of rebound pain occurred within 24 h after surgery; (4) the modified rebound pain score; (5) NRS score under rest and exercise at different time points; (6) the cumulative opioid consumption at different time points; (7) patient’s prognosis and knee joint function evaluation; (8) blood glucose and cortisol concentration; (9) patient’s satisfaction score; (10) adverse reactions and adverse events.DiscussionThe effect of ketamine on preventing postoperative rebound pain is contradictory and uncertain. The affinity of esketamine to the N-methyl-D-aspartate receptor is about four times higher than levo-ketamine, the analgesic effect is 3 times higher than levo-ketamine, and there are fewer adverse mental reactions. To our knowledge, there is no randomized controlled trial to verify the impact of esketamine on postoperative rebound pain in patients undergoing total knee arthroplasty. Therefore, this trial is expected to fill an important gap in relevant fields and provide novel evidence for individualized pain management.Clinical Trial Registrationhttp://www.chictr.org.cn, identifier ChiCTR2300069044