China’s carbon flow: 2008–2012

As the world’s largest CO2 emitter, China’s CO2 emissions have become one of the most popular issues concerned by domestic and foreign researchers. Therefore, analysis of the current status of China’s carbon emissions is very important. After drawing a chart of China’s carbon flow in 2012, based on the IPCC carbon emission inventory method and China’s energy balance table, this paper gives a detailed description of the current status of China’s carbon flow and compares the changing characteristics of China’s carbon flow between 2008 and 2012. The results show that 75.12% of total CO2 emissions flow mainly into several sectors, such as ferrous sectors, and the chemical industry in the terminal sub-sectors. Although China’s thermoelectric efficiency increased dramatically during past four years, emissions from the heat and power production sector are still increasing due to China’s large demand for heat and power. In the ferrous metal and chemical industry sectors, CO2 emissions are mainly energy-related, while in the non-metallic mineral sector, CO2 emissions are mainly from process CO2 emissions. In different terminal sub-sectors, the main carriers of CO2 flow are different, thus, related CO2 reduction policies should also be targeted. In addition, some valuable suggestions are given in this paper

Design of super-efficient mixer based on induced charge electroosmotic

The super-efficient sample mixing induced by the induced-charge electrokinetic flow around conducting/Janus cylinder was numerically studied in a confined |U-shaped microchannel with suddenly applied DC weak electric filed. It’s found that there are four large circulations around the conducting cylinder and two smaller circulations around the Janus cylinder. The results show that samples can still be well mixed with high flux due to the induced electroosmosis. It is demonstrated that the local flow circulations provide effective means to enhance the flow mixing between different solutions. The dependence of the degree of mixing enhancement on the electric field is also predicted

Climate policy modeling: An online SCI-E and SSCI based literature review

This study utilizes the bibliometric method on climate policy modeling based on the online version of SCI-E from 1981 to 2013 and SSCI from 2002 to 2013, and summarizes several important research topics and methodologies in the field. Publications referring to climate policy modeling are assessed with respect to quantities, disciplines, most productive authors and institutes, and citations. Synthetic analysis of keyword frequency reveals six important research topics in climate policy modeling which are summarized and analyzed. The six topics include integrated assessment of climate policies, uncertainty in climate change, equity across time and space, endogeneity of technological change, greenhouse gases abatement mechanism, and enterprise risk in climate policy models. Additionally, twelve types of models employed in climate policy modeling are discussed. The most widely utilized climate policy models are optimization models, computable general equilibrium (CGE) models, and simulation models

FedRolex: Model-Heterogeneous Federated Learning with Rolling Sub-Model Extraction

Most cross-device federated learning (FL) studies focus on the model-homogeneous setting where the global server model and local client models are identical. However, such constraint not only excludes low-end clients who would otherwise make unique contributions to model training but also restrains clients from training large models due to on-device resource bottlenecks. In this work, we propose FedRolex, a partial training (PT)-based approach that enables model-heterogeneous FL and can train a global server model larger than the largest client model. At its core, FedRolex employs a rolling sub-model extraction scheme that allows different parts of the global server model to be evenly trained, which mitigates the client drift induced by the inconsistency between individual client models and server model architectures. We show that FedRolex outperforms state-of-the-art PT-based model-heterogeneous FL methods (e.g. Federated Dropout) and reduces the gap between model-heterogeneous and model-homogeneous FL, especially under the large-model large-dataset regime. In addition, we provide theoretical statistical analysis on its advantage over Federated Dropout and evaluate FedRolex on an emulated real-world device distribution to show that FedRolex can enhance the inclusiveness of FL and boost the performance of low-end devices that would otherwise not benefit from FL. Our code is available at: https://github.com/AIoT-MLSys-Lab/FedRolexComment: 20 pages, 7 Figures, Published in 36th Conference on Neural Information Processing And System

Temperature and GDP: A review of climate econometrics analysis

Climate econometric analysis of the relationship between temperature and gross domestic product (GDP) is increasingly being used to evaluate climate risks and understand economic impacts caused by climate change. We review the literature on growth and level effects (i.e., temperature rise respectively affects the growth and level of economic output), the setting of temperature variables’ forms and functional forms, and the inherent model specification of climate econometrics. Additionally, we introduce an approach for combining empirical findings with climate change integrated assessment models (IAMs) to improve damage modelling. Our findings show that estimates of damage through growth effects are generally much larger than those through level effects. Diverse impact mechanisms and adaptation effects can be revealed by changing the time resolution of temperature variables, introducing non-linearity into econometrics functions, and specifying temperature deviation. Combing the cross-sectional and panel model would enable us to examine the economic impacts at different future times

Research on a New Signature Scheme on Blockchain

With the rise of Bitcoin, blockchain which is the core technology of Bitcoin has received increasing attention. Privacy preserving and performance on blockchain are two research points in academia and business, but there are still some unresolved issues in both respects. An aggregate signature scheme is a digital signature that supports making signatures on many different messages generated by many different users. Using aggregate signature, the size of the signature could be shortened by compressing multiple signatures into a single signature. In this paper, a new signature scheme for transactions on blockchain based on the aggregate signature was proposed. It was worth noting that elliptic curve discrete logarithm problem and bilinear maps played major roles in our signature scheme. And the security properties of our signature scheme were proved. In our signature scheme, the amount will be hidden especially in the transactions which contain multiple inputs and outputs. Additionally, the size of the signature on transaction is constant regardless of the number of inputs and outputs that the transaction contains, which can improve the performance of signature. Finally, we gave an application scenario for our signature scheme which aims to achieve the transactions of big data on blockchain

Risk management of extreme events under climate change

Risk management is an effective way to mitigate the adverse consequences of extreme events, and plays an important role in climate change adaptation. On the basis of the literature, this paper presents a conceptual framework for managing the risk of extreme events under climate change, and accordingly summarizes the recent developments with a focus on several key topics. In terms of risk determinants, the impacts of climate variability on the frequency of extreme events are addressed, and the various meanings and measurements of specific vulnerability are compared. As for the process of risk management, the dynamic assessment approach regarding future climate condition is emphasized. Besides, in view of decision making the available means to enhance the effectiveness of adaptation and mitigation strategies are highlighted. Finally, uncertainty is discussed with respect to its sources and solution

Tracking Berry curvature effect in molecular dynamics by ultrafast magnetic x-ray scattering

The spin-dependent Berry force is a genuine effect of Berry curvature in molecular dynamics, which can dramatically result in spatial spin separation and change of reaction pathways. However, the way to probe the effect of Berry force remains challenging, because the time-reversal (TR) symmetry required for opposite Berry forces conflicts with TR symmetry breaking spin alignment needed to observe the effect, and the net effect could be transient for a molecular wave packet. We demonstrate that in molecular photodissociation, the dissociation rates can be different for molecules with opposite initial spin directions due to Berry force. We showcase that the spatially separated spin density, which is transiently induced by Berry force as the molecular wave packet passes through conical intersection, can be reconstructed from the circular dichroism (CD) of ultrafast non-resonant magnetic x-ray scattering using free electron lasers