Firm Actions Toward Data Breach Incidents and Firm Equity Value: An Empirical Study

Managing information resources including protecting the privacy of customer data plays a critical role in most firms. Data breach incidents may be extremely costly for firms. In the face of a data breach event, some firms are reluctant to disclose information to the public. Firm may be concerned with the potential drop in the market value following the revelation of a data breach. This paper examines the impact of data breach incidents to the firm’s market value/equity value, and explores the possibility that certain firm behaviors may reduce the cost of the incidents. We use regression analysis to identify the factors that affect cumulative abnormal stock return (CAR). Our results indicate that when data breach happens, firms not only should notify customers or the public timely, but also try to control the amount of information disclosed. These findings should provide corporate executives with guidance on managing public disclosure of data breach incidents

Network Traffic Classification Based on External Attention by IP Packet Header

As the emerging services have increasingly strict requirements on quality of service (QoS), such as millisecond network service latency ect., network traffic classification technology is required to assist more advanced network management and monitoring capabilities. So far as we know, the delays of flow-granularity classification methods are difficult to meet the real-time requirements for too long packet-waiting time, whereas the present packet-granularity classification methods may have problems related to privacy protection due to using excessive user payloads. To solve the above problems, we proposed a network traffic classification method only by the IP packet header, which satisfies the requirements of both user's privacy protection and classification performances. We opted to remove the IP address from the header information of the network layer and utilized the remaining 12-byte IP packet header information as input for the model. Additionally, we examined the variations in header value distributions among different categories of network traffic samples. And, the external attention is also introduced to form the online classification framework, which performs well for its low time complexity and strong ability to enhance high-dimensional classification features. The experiments on three open-source datasets show that our average accuracy can reach upon 94.57%, and the classification time is shortened to meet the real-time requirements (0.35ms for a single packet).Comment: 12 pages, 5 figure

Towards a low-emission agrifood sector in the People’s Republic of China: A country profile

The global food system is responsible for 23 – 42% of total net anthropogenic emissions. The food systems of all countries need to be transformed to lower their emissions while producing sufficient, nutritious and healthy food. The Low-Emissions Food Systems (Mitigate+) Initiative aims to offer a comprehensive, evidence-based and holistic approach to reducing agrifood systems emissions. It explores possible pathways that reduce greenhouse gas emissions while enhancing food security and nutrition and livelihoods and preserving the environment. In this context, a set of country profiles are being developed opening avenues towards low-emission food systems. The present document focuses on China’s agrifood system. Net greenhouse gas emissions from China’s agrifood system reached 1.9 GtCO2eq in 2020, accounting for 14.2% of nationwide total greenhouse gas emissions. China pledged to cut its CO2 emissions by 65% between 2005 and 2030, to reach an emission peak before 2030 and achieve carbon neutrality before 2060. To feed its large population while reducing its carbon footprint, China must transition to a low-emission agricultural model. This report illustrates the progress made by China towards this goal and it discusses the remaining challenges. Three main categories of measures have been identified that are advancing low-emission agriculture in China: (i) adopt protective cultivation practices; (ii) enhance carbon sequestration in forest, rangeland and wetland ecosystems; and (iii) develop innovative low-emission technologies and practices. This document formulates seven specific policy recommendations to address current challenges and accelerate the needed transition towards low-emission agriculture in China

Microstructure and mechanical properties of wire and arc additive manufactured thin wall with low-temperature transformation

Low-temperature transformation (LTT) welding wire was initially developed to mitigate residual stress in the weld. It could also be used for internal stress optimization in Wire and Arc Additive Manufacturing (WAAM) process. In this study, a 26 layers LTT wall sample fabricated by using the WAAM technique was investigated. The microstructure of the LTT deposited wall includes elongated cellular martensite and reticular residual austenite. With the accumulation of deposition height, the prior austenite grain size increases, and the volume fraction of residual austenite and the density of dislocations in martensite decreases. According to the model of martensite transformation kinetics, the original austenite grain size is the main reason that affects the austenite fraction. In addition, the presence of a thermal cycle leads to the refinement of the martensitic microstructure and the increase in the boundary density, as well as the elimination of the sub-stable austenitic phase resulting in higher tensile properties in the middle samples than in the top ones. From the current work, it is clear that the unique thermal cycle treatment of WAAM is beneficial in improving the performance of LTT materials.</p

An Intensified Mode of Variability Modulating the Summer Heat Waves in Eastern Europe and Northern China

This study investigates the leading pattern of Eurasian summer heat waves (HWs) using observed and simulated data sets and reveals an intensified mode of variability that bridges the HWs in eastern Europe (EE) and northern China (NC). The concurrent variability of the HWs in EE and NC is primarily driven by an atmospheric circum-global teleconnection that induces anomalous anticyclones over the two regions. The observed upward trends in EE and NC HW days could be related to the warm sea surface temperatures around Greenland Island, which may weaken the Atlantic westerly jet stream and lead to amplified wave trains at the exit of the jet, resulting in strengthened anticyclones over EE and NC that favor the occurrences of HWs. The Geophysical Fluid Dynamics Laboratory high-resolution atmospheric model fails to simulate the EE and NC HWs, due probably to the model’s poor representation of the South Asian summer rainfall