Safe consensus control of cooperative-competitive multi-agent systems via differential privacy

summary:This paper investigates a safe consensus problem for cooperative-competitive multi-agent systems using a differential privacy (DP) approach. Considering that the agents simultaneously interact cooperatively and competitively, we propose a novel DP bipartite consensus algorithm, which guarantees that the DP strategy only works on competitive pairs of agents. We then prove that the proposed algorithm can achieve the mean square bipartite consensus and $(p,r)$-accuracy. Furthermore, a differential privacy analysis is conducted, which shows that the performance of privacy protection is positively correlated with the number of neighbors. Thus, a practical method is established for the agents to select their own privacy levels. Finally, the simulation results are presented to demonstrate the validity of the proposed safe consensus algorithm

Summary of ChatGPT/GPT-4 Research and Perspective Towards the Future of Large Language Models

This paper presents a comprehensive survey of ChatGPT and GPT-4, state-of-the-art large language models (LLM) from the GPT series, and their prospective applications across diverse domains. Indeed, key innovations such as large-scale pre-training that captures knowledge across the entire world wide web, instruction fine-tuning and Reinforcement Learning from Human Feedback (RLHF) have played significant roles in enhancing LLMs' adaptability and performance. We performed an in-depth analysis of 194 relevant papers on arXiv, encompassing trend analysis, word cloud representation, and distribution analysis across various application domains. The findings reveal a significant and increasing interest in ChatGPT/GPT-4 research, predominantly centered on direct natural language processing applications, while also demonstrating considerable potential in areas ranging from education and history to mathematics, medicine, and physics. This study endeavors to furnish insights into ChatGPT's capabilities, potential implications, ethical concerns, and offer direction for future advancements in this field.Comment: 35 pages, 3 figure

Case report: Targeted sequencing facilitates the diagnosis and management of rare multifocal pure ground-glass opacities with intrapulmonary metastasis

IntroductionTreatments for multiple ground-glass opacities (GGOs) for which the detection rate is increasing are still controversial. Next-generation sequencing (NGS) may provide additional key evidence for differential diagnosis or optimal therapeutic schedules.Case presentationWe first reported a rare case in which more than 100 bilateral pulmonary GGOs (91.7% of the GGOs were pure GGOs) were diagnosed as both multiple primary lung cancer and intrapulmonary metastasis. We performed NGS with an 808-gene panel to assess both somatic and germline alterations in tissues and plasma. The patient (male) underwent three successive surgeries and received osimertinib adjuvant therapy due to signs of metastasis and multiple EGFR-mutated tumors. The patient had multiple pure GGOs, and eight tumors of four pathological subtypes were evaluated for the clonal relationship. Metastasis, including pure GGOs and atypical adenomatous hyperplasia, was found between two pairs of tumors. Circulating tumor DNA (ctDNA) monitoring of disease status may impact clinical decision-making.ConclusionsSurgery combined with targeted therapies remains a reasonable alternative strategy for treating patients with multifocal GGOs, and NGS is valuable for facilitating diagnostic workup and adjuvant therapy with targeted drugs through tissue and disease monitoring via ctDNA

A Study of the Impact of Peer Review on Academic English Writing among English Majors

Peer review is a hot topic in the research of writing teaching for English majors. At present, there is still great controversy in the academic community about its feasibility and effect. To fully sort out the impact of peer feedback on different contents in English writing, grasp its advantages and disadvantages in teaching, and put forward some implementable suggestions to improve teaching and make peer feedback better serve the teaching, this study used semi-structured interviews as the main method and questionnaires as the supplemented survey to survey eight students majoring in English in a university of foreign languages in Northeast China. The study founds that peer review mainly includes mutual evaluation of nine parts, such as vocabulary, grammar, punctuation, sentence coherence, and article structure, and mainly focuses on the surface content of language, such as vocabulary, grammar, punctuation, etc. In addition, the study found that despite some shortcomings, peer feedback is still a promising way to 2nd language writing feedback, which can enhance students’ critical thinking skills and many other abilities. Research shows that we should actively incorporate peer feedback in college English writing classes to fully exploit its teaching potential in English writing

Reliability Analysis of Gasifier Lock Bucket Valve System Based on DBN Method

In order to solve the problem of zero-failure data and dynamic failure in gasification system, a dynamic Bayesian network (DBN) combined with Monte Carlo simulations is proposed to analyze the reliability of the gasifier lock bucket valve system. On the basis of studying the structure of the gasifier lock bucket valve system, the reliability model of the system is built based on DBN, and the structure learning is realized. The Monte Carlo simulation is used for the timed ending test in Bayesian estimation, which effectively solves the problem of zero-failure data and realizes the parameter learning. Through the Metropolis-Hastings (M-Hs) algorithm, the prior distribution of dynamic node is randomly sampled to obtain the target distribution, which makes the reliability predictive inference for DBN of the gasifier lock bucket valve system faster and more accurate. The obtained reliability prediction is a curve varying with time. The results show that the valve frequent switch node of DBN of the gasifier lock bucket valve system is identified as the weak link by the powerful reverse inference for DBN, which needs to be paid more attention to. This method can effectively improve the maintenance level of the gasifier lock bucket valve system and can effectively reduce the possibility of accidents

Study on Price Bubbles of China’s Agricultural Commodity against the Background of Big Data

Agriculture provides a basis for social and economic development. It is therefore crucial for society and the economy to stabilize agricultural prices. Recent large increases and decreases in Chinese agricultural commodity prices have increased production risks, heightened fluctuations in the domestic agricultural supply, and impacted the stability of the global agricultural market. Meanwhile, big data technology has advanced quickly and now serves as a foundation for the investigation of time series bubbles. Identifying agricultural price bubbles is important for determining agricultural production decisions and policies that control agricultural prices. Using weekly agricultural price data from 2009 to 2021, this paper identifies agricultural price bubbles, pinpoints their time points, and examines their causes. According to our research, prices for corn, hog, green onions, pork, and ginger all have bubbles, but garlic do not. The quantity, length, time distribution, and type of bubbles differ significantly among corn, ginger, green onion, hog, and pork. The main causes for ginger and green onion price bubbles are speculation and natural disasters. Price bubbles for hog and pork are influenced by animal disease and rising costs. Conflicts between supply and demand and changes in price policy cause corn price bubbles to form. This paper advises that the government adopt various regulatory actions to stabilize agricultural prices depending on the characteristics and causes of the various types of agricultural price bubbles, it should also improve the early warning system and response mechanism for agricultural price bubbles and focus on how policies and market processes work together

Management and outcomes of pregnancy with or without lupus nephritis: a systematic review and meta-analysis.

Although it is well established that systemic lupus erythematosus (SLE) negatively affects pregnancy outcomes, there is insufficient evidence on the effect of lupus nephritis (LN) on antenatal management and pregnancy outcomes. We performed a systematic review and meta-analysis to determine the association of LN with management and pregnancy outcomes in SLE patients.info:eu-repo/semantics/publishe