Trading Strategies for All Stock Programs

 Market traders buy and sell volatile assets frequently, with a goal to maximize their total return. There is usually a commission for each purchase and sale. Two such assets are gold and bitcoin. In order to solve the existing issues of purchases between gold and bitcoin, given that we have 1,000 USD, what strategies should we take to maximize our profits? In this article, the authors established seven models to predict the value of gold and bitcoins and how you should buy them, as the trends of value fluctuate, our models must be accurate enough to avoid being influenced. Targeted at that, the content is divided into three parts. For part 1: The authors selected several indicators that feature how the stock runs. For instance, price of gold and profit of gold to build first two models, which are the risk of investment model and the judgment on bull-or-bear market model. Then we use these models to evaluate whether it is safe to invest. The models are as follows: bear-bull market judgment model, risk of investment evaluation model, prediction model, trade model. For part 2: Based on the data concerned, the authors established the time series model to predict the way the market fluctuates. Meanwhile, the result of this model can be applied in correcting the results of former two models so as to make it more accurate. For part 3: The authors combined models above to give the best trading strategy. In addition, we improved the models by adding more indicators to make it more precise. We hope that by applying our models and strategies, you can successfully maximize your profit

Primary localized histoplasmosis with lesions restricted to the mouth in a Chinese HIV-negative patient

SummaryHistoplasmosis is a deep mycosis caused by Histoplasma capsulatum, which is endemic in many areas of the world but is relatively rare in China. Although the majority of cases present as a mild to moderate flu-like disease requiring only supportive therapy, approximately 1% of patients experience more serious pulmonary and extrapulmonary disease, which can be life-threatening if diagnosis is delayed or the treatment is not initiated rapidly. Definitive diagnosis is usually made by a combination of culture, detection of the organism in tissues, measurement of antibodies, and detection of antigen. We present the case of a 51-year-old patient who presented with histoplasmosis only, with several ulcerated lesions in the oral cavity and without HIV infection, who did not show any detectable signs and symptoms of systemic disease or extra-oral manifestations. Histopathological analysis indicated a chronic inflammatory process with granulomas with yeast-like organisms. Isolation of H. capsulatum and molecular identification provided the definitive diagnosis. Treatment with oral itraconazole led to remission of the oral lesions. This is the first Chinese case report of localized histoplasmosis with lesions restricted to the mouth in an HIV-negative patient

LLM-Based Agent Society Investigation: Collaboration and Confrontation in Avalon Gameplay

This paper aims to investigate the open research problem of uncovering the social behaviors of LLM-based agents. To achieve this goal, we adopt Avalon, a representative communication game, as the environment and use system prompts to guide LLM agents to play the game. While previous studies have conducted preliminary investigations into gameplay with LLM agents, there lacks research on their social behaviors. In this paper, we present a novel framework designed to seamlessly adapt to Avalon gameplay. The core of our proposed framework is a multi-agent system that enables efficient communication and interaction among agents. We evaluate the performance of our framework based on metrics from two perspectives: winning the game and analyzing the social behaviors of LLM agents. Our results demonstrate the effectiveness of our framework in generating adaptive and intelligent agents and highlight the potential of LLM-based agents in addressing the challenges associated with dynamic social environment interaction. By analyzing the social behaviors of LLM agents from the aspects of both collaboration and confrontation, we provide insights into the research and applications of this domain