This paper aims to utilize bibliometric analysis to analyze research hotspots and styles in carbon neutrality study, and accesses the literary works through the Web of Science (WoS) core database and undertakes an in-depth examination of 909 publications linked to carbon neutrality throughout the world using Vosviewer and Bibliometrix software. In line with the conclusions, the sheer number of carbon neutrality journals has increased dramatically in the past few years. There are notable differences in carbon neutrality research across nations and regions. Asia plus the US would be the main drivers and frontrunners of carbon neutrality analysis, and developing countries have fairly small carbon neutrality analysis. Research has concentrated on carbon neutrality’s practical, technical, policy, and financial aspects, along with renewable energy sources, carbon transformation technologies, and carbon capture and storage technologies will also be study hotspots. The report also describes possibilities for the advancement of carbon neutrality research in the foreseeable future, including just how it could be additional incorporated with synthetic intelligence (AI) plus the Regional military medical services metaverse, and how to strike the difficulties and uncertainties experienced by the post-epidemic rebound. This research aids in understanding the present state for the field of carbon neutrality research and certainly will be used to guide future studies.The central oxygen product of hospitals is considered a high-risk unit, needing large security requirements to steadfastly keep up the integrity associated with the system during the COVID-19 pandemic. The linear thinking assumption of mainstream threat analysis techniques cannot adequately explain these modern systems, that are described as tight contacts and complex communications between technical, human being, and business aspects. Consequently, this study presents an innovative new and extensive strategy to oxygen tanks in hospitals through the COVID-19 pandemic. In this research, trapezoidal fuzzy figures were used to calculate failure rates. After deciding the probability of standard events (BEs), advanced events (IE), and top occasion (TE) with fuzzy logic and moving it into Bayesian Network (BN), deductive and inductive reasoning, and sensitiveness evaluation were done making use of RoV in GeNIe software. The outcomes of this case study showed that the IE of “Human mistake” had the best likelihood of fuzzy fault tree (FFT) plus the probability of oxygen leakage ended up being lower making use of FBN than FFT. Based on the results, BE16 (failure to utilize standard and updated instructions) and BE12 (defects into the assessment and testing system of container devices) had the highest posterior probability, while on the basis of the FFT results, BE4 (defects when you look at the additional coating system of this tank) and, BE3 (Corrosive environment (acidity condition)) had minimal likelihood selleck inhibitor . In accordance with the susceptibility analysis Osteoarticular infection , fundamental activities 10, 11, and 16 were the main into the oxygen leakage event with a really small difference, that has been practically in line with the outcomes of posterior FBN (FBNPO). Upgrading the current tips, correcting defects into the evaluation of all forms of container gauges, and assessment related equipment can greatly help the reliability of the tanks. Root cause analysis of those occasions provides options for prevention and crisis response in critical situations, such as the COVID-19 pandemic.Complex computer system rules are often used in engineering to generate outputs centered on inputs, which could make it difficult for developers to comprehend the partnership between inputs and outputs and to determine top feedback values. One answer to this problem is by using design of experiments (DOE) in combination with surrogate designs. Nonetheless, there is too little help with how to select the proper model for a given data set. This research compares two surrogate modelling techniques, polynomial regression (PR) and kriging-based models, and analyses vital problems in design optimisation, such as for example DOE selection, design sensitivity, and model adequacy. The analysis concludes that PR is much more efficient for model generation, while kriging-based models tend to be much better for evaluating max-min search results due to their capacity to predict a broader range of objective values. The quantity and area of design things can impact the performance for the model, in addition to mistake of kriging-based models is lower than that of PR. Furthermore, design sensitivity information is very important to enhancing surrogate model performance, and PR is way better suited to identifying the style variable with the greatest effect on reaction.
Categories