Infrastructure development, human development index, and CO2 emissions in China: A quantile regression approach

This study investigates the relationships between infrastructure development, human development index (HDI), and CO2 emissions in China. Infrastructure has played an essential role in achieving social and economic developmental goals in China, but environmental pollution has significantly increased in the country in the last two decades. Our analysis uses time series data from 1990 to 2021 and quantile regressions, and we find that infrastructure has positive and statistically significant relationships with HDI, CO2 emissions, and GDP in all quantiles. Recent infrastructure upgrades improve living standards and increase HDI but damage the environment, and infrastructure is the main source of CO2 emissions in the country. Therefore, the government should invest in sustainable infrastructure to mitigate CO2 emissions. The government may consider infrastructure options such as low carbon transportation, including railway infrastructure, urban metros, and light rail

IvyGPT: InteractiVe Chinese pathwaY language model in medical domain

General large language models (LLMs) such as ChatGPT have shown remarkable success. However, such LLMs have not been widely adopted for medical purposes, due to poor accuracy and inability to provide medical advice. We propose IvyGPT, an LLM based on LLaMA that is trained and fine-tuned with high-quality medical question-answer (QA) instances and Reinforcement Learning from Human Feedback (RLHF). After supervised fine-tuning, IvyGPT has good multi-turn conversation capabilities, but it cannot perform like a doctor in other aspects, such as comprehensive diagnosis. Through RLHF, IvyGPT can output richer diagnosis and treatment answers that are closer to human. In the training, we used QLoRA to train 33 billion parameters on a small number of NVIDIA A100 (80GB) GPUs. Experimental results show that IvyGPT has outperformed other medical GPT models.Comment: 5 pages, 3 figure

Multi-Level Text Clustering in Subject Knowledge Library and its Visualization

The large-scale and complex data generated in the teaching field of business administration poses challenges for decision-makers and managers of companies, and how to effectively extract and manage the useful information contained in these data has become a problem to be solved. Currently available methods of subject knowledge library clustering and visualization struggle to handle the complexity and multi-hierarchies of such subject data effectively or meet users’ requirements for advanced semantic understanding and retrieval. In view of these matters, this study aims to probe deeper into the problem of multi-level text clustering in the subject knowledge library and its visualization. Firstly, an innovative strategy-based subject semantic representation method for knowledge libraries was proposed to better interpret and represent the semantic information of subject data. Secondly, a subject clustering model of the knowledge library was constructed based on an improved hierarchical Dirichlet polynomial distribution, enabling efficient and accurate clustering of subject data. Lastly, visualization technology was employed to display the cluster results, allowing users to gain a clear understanding of the internal relationships and structure of the subject data. The research findings of this study could provide valuable new tools and methods for solving the problem of subject knowledge library management and utilization, analyzing the subject data, and supporting decision-making. As a result, they hold both theoretical and practical significance

Carbon flows from trade in harvested wood products using different accounting approaches

Carbon flow in forest products trade will affect the report of a country's carbon stock. This will have an impact on a country's contribution of carbon flows. Based on the analysis of China’s forest product trade, this paper uses the stock-change approach, the production approach and the atmospheric-flow approach to calculate the changes of China's forest products trade carbon flows. Different carbon flow measurement approaches have very different results. From the perspective of the contribution of forest products to carbon flow, the production approach of calculation for forest products trade carbon flow has the largest contribution to atmospheric carbon flows. However, the calculation results of the stock-change approach and the atmospheric-flow approach are just the opposite, that is, the calculation for forest products trade has a negative contribution to China's carbon sinks, and forest products trade has become a source of carbon emissions

Evaluation of the coordinated development of China’s Forest Resources-Economy-Environment System

Forests provide enormous ecological, economic, and social benefits, as such forest development should be oriented toward resource-economy-environment harmonization. This paper constructs a comprehensive evaluation index system and uses the coupled coordination degree model to measure the coordinated development level of China’s forest resources-economy-environment system. The results show that, across 2006‒2020, the level of coupled coordinated development of China’s forest resources-economy-environment composite system fluctuates in an upward trend, thus gradually developing from an initial imbalance to a high degree of coordination; the level of coordinated development of each subsystem of the forest resources, economy, and environment also shows an upward trend. The factors influencing the coordinated development of the forest resource-economy-environment system are, in order, the government’s financial capacity, market environment, scientific and technological innovation capacity, level of economic development, and strength of policy implementation. Therefore, this paper proposes some measures to improve the coordinated development

Production of Bacterial Cellulose in the Medium with Yeasts Pre-Fermented Coconut Water or with Addition of Selected Amino Acids

The uncontrolled natural pre-fermentation process of coconut water represents great hidden safety hazards, unstable production, and impact on the quality of nata de coco–the trade name of bacterial cellulose (BC) in food industry. In this study, BC production from Komagataeibacter nataicola Q2 was conducted in the media of coconut water (50%, v/v) pre-fermented by 11 coconut-sourced yeast strains in static. Results suggested that coconut water pre-fermented by different yeast strains had varied effects on the production of BC. Compared with the use of fresh coconut water, the use of coconut water pre-fermented by Saccharomyces cerevisiae SC7 increased the BC yield by 165%. Both natural pre-fermentation and SC7 pre-fermentation altered the concentrations of amino acids in fresh coconut water. The addition of selected amino acids aspartic acid, glutamic acid, serine, methionine, threonine, isoleucine, phenylalanine, and proline at different concentrations had varied effects on the production of BC. The yield of BC was the highest when adding 3.0% (w/v) methionine. Moreover, adding 3.0% methionine allowed the production of BC with larger loops of looser aggregated microfibers, increased the crystallinity of BC from 64.8% to 69.4%, but decreased the temperature of maximum weight loss rate, hardness, and adhesiveness from 223 °C, 8.68 kg, and 92.8 g.sec to 212 °C, 7.01 kg, and 58.5 g.sec, respectively, in the test condition