With the wide application of the Internet and smart systems, data centers (DCs) have become a hot spot of global concern. The energy saving for data centers is at the core of the related works. The thermal performance of a data center directly affects its total energy consumption, as cooling consumption accounts for nearly 50% of total energy consumption. Superior power distribution is a reliable method to improve the thermal performance of DCs. Therefore, analyzing the effects of different power distribution on thermal performance is a challenge for DCs. This paper analyzes the thermal performance numerically and experimentally in DCs with different power distribution. First, it uses Fluent simulate the temperature distribution and flow field distribution in the room, taking the cloud computing room as the research object. Then, it summarizes a formula based on the computing power distribution in a certain range by the numerical and experimental analysis. Finally, it calculates an optimal cooling power by analyzing the cooling power distribution. The results shows that it reduces the maximum temperature difference between the highest temperature of the cabinet from 5-7k to within 1.2k. In addition, the cooling energy consumption is reduced by more than 5%.

The purpose of this study is to predict the frequency of mortality from urban traffic injuries for the most vulnerable road users before, during and after the confinement caused by COVID-19 in Santiago de Cali, Colombia. Descriptive statistical methods were applied to the frequency of traffic crash frequency to identify vulnerable road users. Spatial georeferencing was carried out to analyze the distribution of road crashes in the three moments, before, during, and after confinement, subsequently, the behavior of the most vulnerable road users at those three moments was predicted within the framework of the probabilistic random walk. The statistical results showed that the most vulnerable road user was the cyclist, followed by motorcyclist, motorcycle passenger, and pedestrian. Spatial georeferencing between the years 2019 and 2020 showed a change in the behavior of the crash density, while in 2021 a trend like the distribution of 2019 was observed. The predictions of the daily crash frequencies of these road users in the three moments were very close to the reported crash frequency. The predictions were strengthened by considering a descriptive analysis of a range of values that may indicate the possibility of underreporting in cases registered in the city’s official agency. These results provide new elements for policy makers to develop and implement preventive measures, allocate emergency resources, analyze the establishment of policies, plans and strategies aimed at the prevention and control of crashes due to traffic injuries in the face of extraordinary situations such as the COVID-19 pandemic or other similar events.

This paper proposes a floating-interest-rate infrastructure bond, where the interest of a government bond is paid to investors during the period of construction and the early period of operation. Unlike the usual government bond, which provides a fixed interest rate, the proposed floating-interest-rate infrastructure bond pays a floating interest, the rate of which depends on spillover tax revenues. Effective infrastructure projects have a positive effect on the economic growth of a region, known as the spillover effect. When user charges and the return from spillover tax revenues are below the fixed rate of the government bond, the interest rate will equal to the fixed rate of the government bond. In this case, investors in the infrastructure will receive interest on the government bond at the minimum rate. As the spillover effect of the infrastructure increases, the rate of return for infrastructure investment will become greater than the fixed rate of the government bond. The success of the floating-interest-rate infrastructure bond depends on the spillover effect and on transparency and accountability. Policy recommendations are provided in this paper on how to increase the spillover effect and improve transparency and accountability. 

Due to the lack of clear regulation of management accounting at the state level in Russia, the authors conducted a study based on an analysis of information sources, an expert survey on their reliability, and a case method, which resulted in a reporting form compiled for the production process of an agro-industrial enterprise (grain products) as part of inter-organizational company cooperation. The developed management reporting system (composed of eight consecutive stages: standard reports, specialized reports, itemized query reports, notification reports, statistical reports, prognostic reports, modeling results reports, and process optimization reports), on one hand, allows solving a set of tasks to increase the competitiveness of Russian agro-industrial enterprises within the framework of inter-organizational management accounting. On the other hand, the introduction of ESG principles into the management reporting system (calculation of the environmental (E) index, which assesses the company’s impact on the natural ecosystem and covers emissions and efficient use of natural resources in the agricultural production process) increases the level of control and minimizes the risks of an unfair approach of individual partners to environmental issues.

This study aims to investigate the phenomenon of non-disclosure of personal information among male individuals, employing the Communication Privacy Management Theory as a guiding framework. The objectives of the study encompass identifying the specific types of personal information male students refrain from disclosing, examining the underlying reasons for their non-disclosure practices, and assessing the impact of non-disclosure on their interpersonal relationships. Qualitative research methods, primarily in-depth interviews, were employed to gather insights, with six male students from Sultan Idris Education University (UPSI) participating in the interviews. The findings reveal that male students at UPSI do engage in non-disclosure of personal information, albeit to a certain extent. Specifically, the findings discovered four types of personal information—secrets, traumas, dark history, and family matters—that these students commonly choose not to disclose. Notably, there are four categories of personal information they tend to withhold, namely secrets, traumas, dark history, and family matters. The reluctance to disclose stems from factors such as insecure attachment, a reluctance to worry about their parents, and strained relationships with their family members. Furthermore, the study highlights that non-disclosure of personal information has both negative and positive repercussions on the participants’ relationships with others. Moreover, the study underscores that non-disclosure of personal information can have both negative and positive effects on the participants’ relationships, shedding light on the complexities of navigating personal privacy choices in the university and job-seeking context. The study contributes valuable insights into the challenges of employability dilemmas faced by male university students concerning the management of personal information.