Research of Proxy Cache Algorithm in Multi-media Education System

Multi-media education system is more and more widely used in all levels of education. In order to decrease cost of multi-media system and keep efficiency with increasing multi-media materials, proxy cache algorithm has been widely studied. Based on analysis of existing research of proxy cache results, an improved proxy coaching strategy of prefix cache and postfix merging is proposed. The strategy can dynamically adjust prefix cache size with the object access change. A more effective method of steaming merging has been proposed with multicast used in postfix portion. The results show that the improved strategy can effectively utilize proxy cache resource, shorten time delay and save band width

Optimal Transport-Guided Conditional Score-Based Diffusion Models

Conditional score-based diffusion model (SBDM) is for conditional generation of target data with paired data as condition, and has achieved great success in image translation. However, it requires the paired data as condition, and there would be insufficient paired data provided in real-world applications. To tackle the applications with partially paired or even unpaired dataset, we propose a novel Optimal Transport-guided Conditional Score-based diffusion model (OTCS) in this paper. We build the coupling relationship for the unpaired or partially paired dataset based on $L_2$-regularized unsupervised or semi-supervised optimal transport, respectively. Based on the coupling relationship, we develop the objective for training the conditional score-based model for unpaired or partially paired settings, which is based on a reformulation and generalization of the conditional SBDM for paired setting. With the estimated coupling relationship, we effectively train the conditional score-based model by designing a ``resampling-by-compatibility'' strategy to choose the sampled data with high compatibility as guidance. Extensive experiments on unpaired super-resolution and semi-paired image-to-image translation demonstrated the effectiveness of the proposed OTCS model. From the viewpoint of optimal transport, OTCS provides an approach to transport data across distributions, which is a challenge for OT on large-scale datasets. We theoretically prove that OTCS realizes the data transport in OT with a theoretical bound. Code is available at \url{https://github.com/XJTU-XGU/OTCS}.Comment: Accepted in NeurIPS 202

The Dynamic Effects of Perceptions of Dread Risk and Unknown Risk on SNS Sharing Behavior During Emerging Infectious Disease Events: Do Crisis Stages Matter?

In response to the increasing prevalence of emerging infectious disease (EID) threats, individuals are turning to social media platforms to share relevant information in ever greater numbers. In this study, we examine whether risk perceptions related to user-generated content have dynamic impacts on social networking site (SNS) sharing behavior in different crisis stages. To answer this question, we applied psychometric analysis to evaluate how dread risk and unknown risk can characterize EID threats. Drawing broadly on the literature of risk perceptions, self-perception theory, and crisis stages, we relied on microblogs collected from Sina Weibo, utilizing the vector autoregression model to analyze dynamic relationships. We found that perceptions of dread risk have a dominant and immediate impact on SNS sharing behavior in the buildup, breakout, and termination stages of EID events. Perceptions of unknown risk have a dominant and persistent impact on sharing behavior in the abatement stage. The joint effect of these two types of risk perception reveal an antagonism impact on SNS sharing behavior, and perceptions of dread- and unknown risk have interaction effects from the buildup to termination stages of EID events. To check robustness, we analyzed keywords related to perceptions of dread- and unknown risk. The results of this study support the empirical application of Slovic’s risk perception framework for understanding the characteristics of EID threats and provide a picture of how perceptions of dread- and unknown risk exert differential time-varying effects on SNS sharing behavior during EID events. We also discuss theoretical and practical implications for the crisis management of EID threats. This study is among the first that uses user-generated content in social media to investigate dynamic risk perceptions and their relationship to SNS sharing behavior, which may help provide a basis for timely and efficient risk communication

Towards Revealing the Mystery behind Chain of Thought: a Theoretical Perspective

Recent studies have discovered that Chain-of-Thought prompting (CoT) can dramatically improve the performance of Large Language Models (LLMs), particularly when dealing with complex tasks involving mathematics or reasoning. Despite the enormous empirical success, the underlying mechanisms behind CoT and how it unlocks the potential of LLMs remain elusive. In this paper, we take a first step towards theoretically answering these questions. Specifically, we examine the capacity of LLMs with CoT in solving fundamental mathematical and decision-making problems. We start by giving an impossibility result showing that any bounded-depth Transformer cannot directly output correct answers for basic arithmetic/equation tasks unless the model size grows super-polynomially with respect to the input length. In contrast, we then prove by construction that autoregressive Transformers of a constant size suffice to solve both tasks by generating CoT derivations using a commonly-used math language format. Moreover, we show LLMs with CoT are capable of solving a general class of decision-making problems known as Dynamic Programming, thus justifying its power in tackling complex real-world tasks. Finally, extensive experiments on four tasks show that, while Transformers always fail to predict the answers directly, they can consistently learn to generate correct solutions step-by-step given sufficient CoT demonstrations.Comment: 33 page

Muscadine Grape (\u3ci\u3eVitis rotundifolia\u3c/i\u3e) and Wine Phytochemicals Prevented Obesity-Associated Metabolic Complications in C57BL/6J Mice

The objective of this study was to determine the effects of muscadine grape or wine (cv. Noble) phytochemicals on obesity and associated metabolic complications. Muscadine grape or wine phytochemicals were extracted using Amberlite FPX66 resin. Male C57BL/6J mice were given a low-fat diet (LF, 10% kcal fat), high-fat diet (HF, 60% kcal fat), HF + 0.4% muscadine grape phytochemicals (HF+MGP), or HF + 0.4% muscadine wine phytochemicals (HF+MWP) for 15 weeks. At 7 weeks, mice fed HF+MGP had significantly decreased body weights by 12% compared to HF controls. Dietary MGP or MWP supplementation reduced plasma content of free fatty acids, triglycerides, and cholesterol in obese mice. Inflammation was alleviated, and activity of glutathione peroxidase was enhanced. Consumption of MGP or MWP improved insulin sensitivity and glucose control in mice. Thus, consumption of muscadine grape and wine phytochemicals in the diet may help to prevent obesity-related metabolic complications

A Comparative Analysis of Genistein and Daidzein in Affecting Lipid Metabolism in Rat Liver

Effects of soy isoflavones, genistein and daidzein, on the hepatic gene expression profile and indices for lipid metabolism were compared in rats. In the first experiment (Expt. 1), animals were fed diets containing 2 g/kg of either genistein or daidzein, or a control diet free of isoflavone for 14 days. In the second experiment (Expt. 2), rats were fed diets containing 1 or 2 g/kg of genistein, or an isoflavone-free diet for 16 days. Genistein at a dietary level of 2 g/kg reduced serum triacylglycerol concentrations in both experiments, and serum concentrations of cholesterol in Expt. 2. However, daidzein at 2 g/kg did not decrease serum lipid concentrations in Expt. 1. A DNA microarray analysis in Expt. 1 showed that genistein was stronger than daidzein in affecting gene expression in liver, targeting many genes involved in lipid and carbohydrate metabolism. Detailed analyses indicated that alterations in the expression of genes related to lipogenesis are primarily responsible for the serum lipid-lowering effect of genistein. This notion was supported by analyses of the activity of enzymes involved in lipogenesis in Expt. 2

Clinical profile of Parkinson's disease in the Gumei community of Minhang district, Shanghai

OBJECTIVE: We examined the demographic and clinical profiles of Parkinson's disease in Shanghai, China, to assist in disease management and provide comparative data on Parkinson's disease prevalence, phenotype, and progression among different regions and ethnic groups. METHODS: A door-to-door survey and follow-up clinical examinations identified 180 community-dwelling Han-Chinese Parkinson's disease patients (104 males, 76 females). RESULTS: The average age at onset was 65.16±9.60 years. The most common initial symptom was tremor (112 patients, 62.22%), followed by rigidity (38, 21.11%), bradykinesia (28, 15.56%) and tremor plus rigidity (2, 1.11%). Tremor as the initial symptom usually began in a single limb (83.04% of patients). The average duration from onset to mild Parkinson's disease (Hoehn-Yahr phase 1-2) was 52.74±45.64 months. Progression from mild to moderate/severe Parkinson's disease (phase≥3) was significantly slower (87.07±58.72 months;

Accurate Determination of Aldehydes, Ketones and Furans in Non-grape Wines by Headspace-Solid-Phase Microextraction Combined with High-Resolution Gas Chromatography-Orbitrap Mass Spectrometry

In this study, headspace-solid-phase microextraction extraction combined with gas chromatography-orbitrap-mass spectrometry (HS-SPME-GC-Orbitrap-MS) was used to establish a method for the simultaneous determination of five aldehydes and ketones and four furans in fruit wines. The method was validated on model wine, goji berry wine, blueberry wine and hawthorn wine. The limits of detection (LODs) for all target compounds ranged from 0.004 to 6.300 μg/L, and the limits of quantification (LOQs) were between 0.01 and 21.00 μg/L. The recoveries of all analytes in spiked wine samples were between 81% and 120% and the relative standard deviations (RSDs) for precision were equal to or less than 19.08%. This method is accurate and can meet the requirements for the quantification of aldehydes, ketones and furans in fruit wines