Vegetation changes and land surface feedbacks drive shifts in local temperatures over Central Asia

Vegetation changes play a vital role in modifying local temperatures although, until now, the climate feedback effects of vegetation changes are still poorly known and large uncertainties exist, especially over Central Asia. In this study, using remote sensing and re-analysis of existing data, we evaluated the impact of vegetation changes on local temperatures. Our results indicate that vegetation changes have a significant unidirectional causality relationship with regard to local temperature changes. We found that vegetation greening over Central Asia as a whole induced a cooling effect on the local temperatures. We also found that evapotranspiration (ET) exhibits greater sensitivity to the increases of the Normalized Difference Vegetation Index (NDVI) as compared to albedo in arid/semi-arid/semi-humid regions, potentially leading to a cooling effect. However, in humid regions, albedo warming completely surpasses ET cooling, causing a pronounced warming. Our findings suggest that using appropriate strategies to protect vulnerable dryland ecosystems from degradation, should lead to future benefits related to greening ecosystems and mitigation for rising temperatures

The effectiveness of China’s regional carbon market pilots in reducing firm emissions

China has implemented an emission trading system (ETS) to reduce its ever-increasing greenhouse gas emissions while maintaining rapid economic growth. With low carbon prices and infrequent allowance trading, whether China’s ETS is an effective approach for climate mitigation has entered the center of the policy and research debate. Utilizing China’s regional ETS pilots as a quasi-natural experiment, we provide a comprehensive assessment of the effects of ETS on firm carbon emissions and economic outcomes by means of a matched difference-in-differences (DID) approach. The empirical analysis is based on a unique panel dataset of firm tax records in the manufacturing and public utility sectors during 2009 to 2015. We show unambiguous evidence that the regional ETS pilots are effective in reducing firm emissions, leading to a 16.7% reduction in total emissions and a 9.7% reduction in emission intensity. Regulated firms achieve emission abatement through conserving energy consumption and switching to low-carbon fuels. The economic consequences of the ETS are mixed. On one hand, the ETS has a negative impact on employment and capital input; on the other hand, the ETS incentivizes regulated firms to improve productivity. In the aggregate, the ETS does not exhibit statistically significant effects on output and export. We also find that the ETS displays notable heterogeneity across pilots. Mass-based allowance allocation rules, higher carbon prices, and active allowance trading contribute to more pronounced effects in emission abatement

Bias Assessment and Mitigation in LLM-based Code Generation

Utilizing state-of-the-art Large Language Models (LLMs), automatic code generation models play a pivotal role in enhancing the productivity and efficiency of software development coding procedures. As the adoption of LLMs becomes more widespread in software coding ecosystems, a pressing issue has emerged: does the generated code contain social biases, such as those related to age, gender, and race? This issue concerns the integrity, fairness, and ethical foundation of software applications that depend on the code generated by these models, yet is under-explored in the literature. This paper presents a novel bias assessment framework that is specifically designed for code generation tasks. Based on this framework, we conduct an extensive evaluation on the bias of nine state-of-the-art LLM-based code generation models. Our findings reveal that first, 31.45\% to 79.93\% code functions generated by our evaluated code generation models are biased, and 9.68\% to 37.37\% code functions' functionality are affected by the bias, which means biases not only exist in code generation models but in some cases, directly affect the functionality of the generated code, posing risks of unintended and possibly harmful software behaviors. To mitigate bias from code generation models, we propose three mitigation strategies, which can decrease the biased code ratio to a very low level of 0.4\% to 4.57\%

Light Auditor: Power Measurement Can Tell Private Data Leakage Through IoT Covert Channels

Despite many conveniences of using IoT devices, they have suffered from various attacks due to their weak security. Besides well-known botnet attacks, IoT devices are vulnerable to recent covert-channel attacks. However, no study to date has considered these IoT covert-channel attacks. Among these attacks, researchers have demonstrated exfiltrating users\u27 private data by exploiting the smart bulb\u27s capability of infrared emission. In this paper, we propose a power-auditing-based system that defends the data exfiltration attack on the smart bulb as a case study. We first implement this infrared-based attack in a lab environment. With a newly-collected power consumption dataset, we pre-process the data and transform them into two-dimensional images through Continous Wavelet Transformation (CWT). Next, we design a two-dimensional convolutional neural network (2D-CNN) model to identify the CWT images generated by malicious behavior. Our experiment results show that the proposed design is efficient in identifying infrared-based anomalies: 1) With much fewer parameters than transfer-learning classifiers, it achieves an accuracy of 88% in identifying the attacks, including unseen patterns. The results are similarly accurate as the sophisticated transfer-learning CNNs, such as AlexNet and GoogLeNet; 2) We validate that our system can classify the CWT images in real time

Extension of summer (June–August) temperature records for northern Inner Mongolia (1715–2008), China using tree rings

This paper presents a spatially and temporally improved reconstruction of mean summer (June–August) temperature derived from tree-ring width data of Dahurian larch (Larix gmelinii Rupr.) from the northern Great Xing'an Mountains, Northeast China. Three new chronologies were added to the original 2011 reconstruction, and the reconstruction extended back to AD 1715. The reconstruction was generated using a simple linear regression method, verified by independent meteorological data, and accounts for 47.0% of the actual temperature variance during the common period (1957–2008). The reconstruction captures decadal and century-scale regional temperature variability, such as cold decades (1940s, 1930s, 1790s, 1950s and 1850s), warm decades (2000s, 1870s, 1750s, 1980s and 1840s), a cold half-century (ca. 1750–1799), and a warm half-century (ca. 1900–1949). It also reveals slightly higher frequency of cold years (20.4%) than warm years (18.0%), and a recent warming trend. Compared to the original 2011 reconstruction, this reconstruction has lower inter-annual temperature variability, high explained variance and high representativeness of regional climate. The reconstruction also correlates with the East Asian Monsoon and the Pacific Ocean signals, and indicates the feasibility of using tree rings from high latitude Northeast China to reconstruct summer temperature in permafrost forest environments

Feasibility Investigation for Online Elemental Monitoring of Iron and Steel Manufacturing Processes using Laser-Induced Breakdown Spectroscopy

The metallurgical industries are very important for social development. In order to improve the metallurgical techniques and quality of products, the real-time analysis and monitoring of iron and steel manufacturing processes are very significant. Laser-induced breakdown spectroscopy (LIBS) has been studied and applied for the contents measurement of iron and steel. In this paper, the remote open-path LIBS measurement was studied under different sample temperature, lens to target distance (LTD), sample angle conditions to clarify its online measurement features. The 3D profile measurement system of parallel laser beam fringes projection was also developed to measure the sample profile at different sample temperature. The measurement results demonstrated the robustness of remote open-path LIBS system and 3D profile measurement system. However, the correction is necessary to enhance the detection ability of LIBS online measurement. In order to improve the precision and accuracy of real-time elemental measurement, an innovative co-axial laser beam measurement system combining LIBS and 3D profile techniques is proposed to automatically adjust the focus unit and measure the sample components. The further study of this promising method will be developed for online application of iron and steel manufacturing processes

PATS: Patch Area Transportation with Subdivision for Local Feature Matching

Local feature matching aims at establishing sparse correspondences between a pair of images. Recently, detectorfree methods present generally better performance but are not satisfactory in image pairs with large scale differences. In this paper, we propose Patch Area Transportation with Subdivision (PATS) to tackle this issue. Instead of building an expensive image pyramid, we start by splitting the original image pair into equal-sized patches and gradually resizing and subdividing them into smaller patches with the same scale. However, estimating scale differences between these patches is non-trivial since the scale differences are determined by both relative camera poses and scene structures, and thus spatially varying over image pairs. Moreover, it is hard to obtain the ground truth for real scenes. To this end, we propose patch area transportation, which enables learning scale differences in a self-supervised manner. In contrast to bipartite graph matching, which only handles one-to-one matching, our patch area transportation can deal with many-to-many relationships. PATS improves both matching accuracy and coverage, and shows superior performance in downstream tasks, such as relative pose estimation, visual localization, and optical flow estimation. The source code will be released to benefit the community.Comment: Project page: https://zju3dv.github.io/pat