LCA-based Carbon Footprint of a Typical Wind Farm in China

AbstractWind power resources are abundant in China, with the reserves and exploitable capacity ranking the first in the world. The carbon footprint is used to provide an expending scale accounting of carbon emission embodied in relative phases and sectors. In order to account the carbon footprint of wind farm, this paper introduces a method combining the Life Cycle Assessment and Input-Output analyses to calculate the overall carbon footprint in the construction, operating and dismantling phases of a typical wind farm in China on the basis of the latest acquirable input-output table of province level and province energy statistic. As a result, the total carbon footprint of the case wind farm is 14,490 tCO2 all over the 21 years lifetime. Due to a mass of steel and copper was consumed to manufacture the wind turbines, the ‘Smelting and Pressing of Metals’ sector discharged the largest amount of CO2among all economic sectors. Considering the character of wind farm, IO-LCA is an appropriate method to analyze the overall direct and indirect carbon emissions of wind farm

Wormhole Attack Detection Algorithms in Wireless Network Coding Systems

Network coding has been shown to be an effective approach to improve the wireless system performance. However, many security issues impede its wide deployment in practice. Besides the well-studied pollution attacks, there is another severe threat, that of wormhole attacks, which undermines the performance gain of network coding. Since the underlying characteristics of network coding systems are distinctly different from traditional wireless networks, the impact of wormhole attacks and countermeasures are generally unknown. In this thesis, we quantify wormholes' devastating harmful impact on network coding system performance through experiments. Firstly, we propose a centralized algorithm to detect wormholes and show its correctness rigorously. For the distributed wireless network, we propose DAWN, a Distributed detection Algorithm against Wormhole in wireless Network coding systems, by exploring the change of the flow directions of the innovative packets caused by wormholes. We rigorously prove that DAWN guarantees a good lower bound of successful detection rate. We perform analysis on the resistance of DAWN against collusion attacks. We find that the robustness depends on the node density in the network, and prove a necessary condition to achieve collusion-resistance. DAWN does not rely on any location information, global synchronization assumptions or special hardware/middleware. It is only based on the local information that can be obtained from regular network coding protocols, and thus the overhead of our algorithms is tolerable. Extensive experimental results have verified the effectiveness and the efficiency of DAWN.Computer Scienc

Multi-Agent Consensus Seeking via Large Language Models

Multi-agent systems driven by large language models (LLMs) have shown promising abilities for solving complex tasks in a collaborative manner. This work considers a fundamental problem in multi-agent collaboration: consensus seeking. When multiple agents work together, we are interested in how they can reach a consensus through inter-agent negotiation. To that end, this work studies a consensus-seeking task where the state of each agent is a numerical value and they negotiate with each other to reach a consensus value. It is revealed that when not explicitly directed on which strategy should be adopted, the LLM-driven agents primarily use the average strategy for consensus seeking although they may occasionally use some other strategies. Moreover, this work analyzes the impact of the agent number, agent personality, and network topology on the negotiation process. The findings reported in this work can potentially lay the foundations for understanding the behaviors of LLM-driven multi-agent systems for solving more complex tasks. Furthermore, LLM-driven consensus seeking is applied to a multi-robot aggregation task. This application demonstrates the potential of LLM-driven agents to achieve zero-shot autonomous planning for multi-robot collaboration tasks. Project website: westlakeintelligentrobotics.github.io/ConsensusLLM/

New Insights on Relieving Task-Recency Bias for Online Class Incremental Learning

To imitate the ability of keeping learning of human, continual learning which can learn from a never-ending data stream has attracted more interests recently. In all settings, the online class incremental learning (CIL), where incoming samples from data stream can be used only once, is more challenging and can be encountered more frequently in real world. Actually, the CIL faces a stability-plasticity dilemma, where the stability means the ability to preserve old knowledge while the plasticity denotes the ability to incorporate new knowledge. Although replay-based methods have shown exceptional promise, most of them concentrate on the strategy for updating and retrieving memory to keep stability at the expense of plasticity. To strike a preferable trade-off between stability and plasticity, we propose a Adaptive Focus Shifting algorithm (AFS), which dynamically adjusts focus to ambiguous samples and non-target logits in model learning. Through a deep analysis of the task-recency bias caused by class imbalance, we propose a revised focal loss to mainly keep stability. By utilizing a new weight function, the revised focal loss can pay more attention to current ambiguous samples, which can provide more information of the classification boundary. To promote plasticity, we introduce a virtual knowledge distillation. By designing a virtual teacher, it assigns more attention to non-target classes, which can surmount overconfidence and encourage model to focus on inter-class information. Extensive experiments on three popular datasets for CIL have shown the effectiveness of AFS. The code will be available at \url{https://github.com/czjghost/AFS}.Comment: 12 pages,15 figure

Transfer of spin to orbital angular momentum in the Bethe-Heitler process

According to the conservation of angular momentum, when a plane-wave polarized photon splits into a pair of electron-positron under the influence of the Coulomb field, the spin angular momentum (SAM) of the photon is converted into the angular momentum of the leptons. We investigate this process (the Bethe-Heitler process) by describing the final electron and positron with twisted states and find that the SAM of the incident photon is not only converted into SAM of the produced pair, but also into their orbital angular momentum (OAM), which has not been considered previously. The average OAM gained by the leptons surpasses the average SAM, while their orientations coincide. Both properties depend on the energy and open angle of the emitted leptons. The demonstrated spin-orbit transfer shown in the Bethe-Heitler process may exist in a large group of QED scattering processes

Fiber Evolution during Alkaline Treatment and Its Impact on Handsheet Properties

To understand the swelling effects of alkaline treatment on the morphological properties of fibers and physical properties of handsheets, bleached softwood kraft pulp was treated with NaOH at different concentrations. The results showed that the fiber swelling increased, but the shrinkage and elongation of the paper at a NaOH concentration of 6% or higher did not improve. Dissolution of amorphous material occurred during the treatment together with peeling reactions. The fiber length and shape factor decreased and the fines content increased with an increasing alkali concentration. The cellulose crystallinity decreased with an increasing NaOH concentration. This was confirmed by X-ray diffractometry, which also showed that some cellulose I was converted to cellulose II, especially at higher NaOH concentrations (\u3e 9%). The fiber curl and kink indices increased and the handsheet density decreased with an increasing NaOH concentration. However, the tensile index decreased more steeply than the density with an increasing NaOH concentration, possibly because of the lower number and strength of the interfiber bonds, increased kinks, and reduced fiber strength and length. The handsheet extensibility first increased and subsequently decreased as the NaOH concentration increased, which indicated that well-controlled NaOH treatment could be used to improve the extensibility of paper