Relationships between Environmental Factors and the Growth of Above-Ground Biomass in Boreal Forest

This study investigates the influence of shortwave radiation (albedo is calculated to characterize the absorption of shortwave radiation), temperature and relative humidity on biomass growth of two coniferous species in boreal forest. Stem circumferences are measured for calculating daily biomass growth rate and calculated growth rate is analysed by statistical method for revealing its possible correlations to environmental factors (shortwave radiation, temperature and relative humidity). Comparisons between biomass growth rate and environmental factors are also made for finding correlation. Temperature sets lower limit for biomass growth. Biomass growth rate is found dependent on the values of albedo, meaning absorption of shortwave radiation dominates growth. Relative humidity is found negatively dependent on temperature. However, there is no statistical dependence of growth rate found on temperature and relative humidity, although some extreme temperatures and relative humidity are noticed affecting growth rate through evaporation (temperature affects negatively and relative humidity affects positively). The model on the relationship between values of albedo and temperature in the process of glucose absorption is also revealed and albedo is regarded to dominate such a process. Connections among these environmental factors are found and the affecting mechanism is established finally. Besides, species-specific difference of response to shortwave radiation between Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies L.) is revealed

Reinforcement Learning in Computing and Network Convergence Orchestration

As computing power is becoming the core productivity of the digital economy era, the concept of Computing and Network Convergence (CNC), under which network and computing resources can be dynamically scheduled and allocated according to users' needs, has been proposed and attracted wide attention. Based on the tasks' properties, the network orchestration plane needs to flexibly deploy tasks to appropriate computing nodes and arrange paths to the computing nodes. This is a orchestration problem that involves resource scheduling and path arrangement. Since CNC is relatively new, in this paper, we review some researches and applications on CNC. Then, we design a CNC orchestration method using reinforcement learning (RL), which is the first attempt, that can flexibly allocate and schedule computing resources and network resources. Which aims at high profit and low latency. Meanwhile, we use multi-factors to determine the optimization objective so that the orchestration strategy is optimized in terms of total performance from different aspects, such as cost, profit, latency and system overload in our experiment. The experiments shows that the proposed RL-based method can achieve higher profit and lower latency than the greedy method, random selection and balanced-resource method. We demonstrate RL is suitable for CNC orchestration. This paper enlightens the RL application on CNC orchestration

AIGC Empowering Telecom Sector White Paper_chinese

In the global craze of GPT, people have deeply realized that AI, as a transformative technology and key force in economic and social development, will bring great leaps and breakthroughs to the global industry and profoundly influence the future world competition pattern. As the builder and operator of information and communication infrastructure, the telecom sector provides infrastructure support for the development of AI, and even takes the lead in the implementation of AI applications. How to enable the application of AIGC (GPT) and implement AIGC in the telecom sector are questions that telecom practitioners must ponder and answer. Through the study of GPT, a typical representative of AIGC, the authors have analyzed how GPT empowers the telecom sector in the form of scenarios, discussed the gap between the current GPT general model and telecom services, proposed for the first time a Telco Augmented Cognition capability system, provided answers to how to construct a telecom service GPT in the telecom sector, and carried out various practices. Our counterparts in the industry are expected to focus on collaborative innovation around telecom and AI, build an open and shared innovation ecosystem, promote the deep integration of AI and telecom sector, and accelerate the construction of next-generation information infrastructure, in an effort to facilitate the digital transformation of the economy and society

Vertical Federated Learning

Vertical Federated Learning (VFL) is a federated learning setting where multiple parties with different features about the same set of users jointly train machine learning models without exposing their raw data or model parameters. Motivated by the rapid growth in VFL research and real-world applications, we provide a comprehensive review of the concept and algorithms of VFL, as well as current advances and challenges in various aspects, including effectiveness, efficiency, and privacy. We provide an exhaustive categorization for VFL settings and privacy-preserving protocols and comprehensively analyze the privacy attacks and defense strategies for each protocol. In the end, we propose a unified framework, termed VFLow, which considers the VFL problem under communication, computation, privacy, and effectiveness constraints. Finally, we review the most recent advances in industrial applications, highlighting open challenges and future directions for VFL

6G Network Operation Support System

6G is the next-generation intelligent and integrated digital information infrastructure, characterized by ubiquitous interconnection, native intelligence, multi-dimensional perception, global coverage, green and low-carbon, native network security, etc. 6G will realize the transition from serving people and people-things communication to supporting the efficient connection of intelligent agents, and comprehensively leading the digital, intelligent and green transformation of the economy and the society. As the core support system for mobile communication network, 6G OSS needs to achieve high-level network automation, intelligence and digital twinning capabilities to achieve end-to-end autonomous network operation and maintenance, support the operation of typical 6G business scenarios and play a greater social responsibility in the fields of environment, society, and governance (ESG).This paper provides a detailed introduction to the overall vision, potential key technologies, and functional architecture of 6G OSS . It also presents an evolutionary roadmap and technological prospects for the OSS from 5G to 6G.Comment: 103 pages, 20 figures, 52 references (chinese version

Indirect aggression and parental attachment in early adolescence: Examining the role of perspective taking and empathetic concern

This study examined the unique and interactive roles of parental attachment and empathy in indirect aggression during early adolescence. A sample of 6301 early adolescents (49.2% boys and 50.8% girls) in urban China, aged from 11 to 14 years, completed self-administrated measures of parent-adolescent attachment, empathy, and indirect aggression. Results indicated that perspective taking was negatively associated with indirect aggression, and empathetic concern was not related to indirect aggression. Hierarchical regression analysis revealed that perspective taking moderated the association between empathetic concern and boys' indirect aggression. The findings highlighted that empathetic concern might not be a sufficient protective factor of indirect aggression for boys with low levels of perspective taking during early adolescence.The study was supported by the National Natural Science Foundation of China (30972496).Published versio