Ebola virus is a potent infectious disease virus that can cause Ebola haemorrhagic fever caused by human and primate. It has high mortality and easy infectivity to form a great obstacle to the steady development of human society. The profound understanding of the virus is particularly important harm. In this paper, a number of mathematical models are established to solve this problem. The software is used to analyze and predict the propagation of Ebola virus. The residual analysis is used to test the model. Finally, the effects of various control measures on controlling the epidemic are analyzed. In order to solve the problem, we will establish the infectious disease model to dynamically describe the spread of the virus in the 'virtual orangutan population'. Considering that the latent population is analyzed in this question, we will improve the model. Join the latent group (), and the migrants are divided into self-healing () and the dead (), to establish a suitable solution to this problem model. According to the relevant data given in the title, differential equations were established. For the second question, this question involves the one-way transmission of the virus across the species, so we can improve the model, on the basis of human contact with orangutans infected groups, the establishment of a one-way model to solve this problem. On the basis of the problem one, the differential equation is established, the model is predicted and tested. In the case of question 3, the number of human susceptible groups is much higher than that of the orangutan infection group by comparing the relevant data with the increase of the cure rate to 80% after the intervention of the outside experts. Therefore, the original data of human populations from experts can be ignored. Since then the virus spreads within a single species, the differential equation can be established according to the model in question 1 and the data values in the virtual human population are predicted. For question 4, the effect of the measures such as the strict enforcement of the various epidemic control measures and the improvement of the drug effect on the control of the epidemic are analyzed by comparing the above-mentioned models with the control measures.
Given the importance of Information Communication Technology (ICT) in stimulating stock market development, many researchers have investigated their influences on the developed markets and high-income economies. The aim of this study is to examine the impact of ICT diffusion on stock market development for a panel of 17 selected emerging countries over the period 1990–2020 and employed the system-generalized method of moments (S-GMM) to test its objective. Three stock market development indicators are also used, namely: stock market capitalization (SMC), stock market total value traded (SMTT), and stock market turnover (SMT). Three ICT indicators are also employed, namely: Fixed telephone subscriptions (FTS), Individuals using the Internet (IUI), and Mobile cellular subscriptions (MCS). Three financial development indicators (deposit money among bank assets (DMB), liquid liabilities (LLB), and private credit by deposit money bank (PCM)) were employed as control variables. In its findings, all selected ICT dynamics positively affect stock market development and its constituents. Secondly, no proof was confirmed in relation to the impact of fixed telephone and stock market development with its elements. Thirdly, evidence of a positive relationship is sparingly apparent in financial development and its components. Fourthly, compared with fixed telephone, internet users more positively and significantly affect stock market development indicators. Policy implications are discussed.
In recent years, incidents of school bullying have been on the rise, attracting increasing attention from society. School bullying refers to the repeated and sustained use of force or coercion by individual or group of students to oppress other students in terms of power or status, resulting in many physical and psychological problems for the victims. This paper introduces the definition, classification, role types, and the impact on victims, as well as interventions for school bullying. Studies have shown that school bullying can have negative psychological consequences for victims, such as anxiety and depression, making timely intervention extremely important. Intervention measures include educating the active perpetrators, victims, and bystanders. In particular, the "STAC" course is an effective way to educate bystanders. In summary, school bullying is a problem that requires timely intervention, and it requires joint efforts from schools, families, and society to solve.
The purpose of this study is to identify the effects of multidimensional (fuzzy) inequalities and marginal changes on the Gini coefficients of various factors. This allows a range of social policies to be specifically targeted to reduce broader inequalities, but these policies are focused primarily on health, education, housing, sanitation, energy and drinking water. It is necessary to target policy areas that are unequally distributed, such as those with access to unevenly distributed drinking water policies. The data are from the Household and Consumption Survey of 6695 households in 2003 and 9259 households in 2011. This paper uses Lerman and Yitzhaki’s method. The results revealed that the main contributors to inequalities over the two periods were health and education. These sources have a potentially significant effect on total inequality. Health increases overall inequalities, but sources such as housing, sanitation and energy reduce them. This article provides resources to disadvantaged and vulnerable target groups. Multiple inequalities are analyzed for different subgroups of households, such as place of residence and the gender of the head of household. Analyzing fuzzy poverty inequalities makes it possible to develop targeted measures to combat poverty and inequality. This study is the first to investigate the sources of Gini’s fuzzy inequality in Chad via data analysis techniques, and in general, it is one of the few studies in Saharan Africa to be interested in this subject. Some development policies in sub-Saharan Africa should therefore focus on different sources (negative effect), sources (positive effect) and the equalization effect.
The significance of remittances to the Vietnamese economy necessitates investigating how they affect the value of the Vietnamese currency and other macroeconomic factors. Macroeconomic articles struggle to discover their impact on economic development, but measured remittances by migrant workers have recently soared. There is no academic study that has examined this phenomenon in Vietnam. This study uses wavelet frameworks to analyze the lead-lag nexus between exchange rates, remittances, and economic growth in Vietnam in time-frequency domains from 1995 to 2020. Overall, we find that: (i) remittances enhance economic growth in the short and medium run; (ii) exchange rates boost remittances in the short and medium run; (iii) exchange rates promote GDP in all frequency and time domains. Moreover, the partial wavelet coherence and multiple wavelet coherence frameworks also offered evidence supporting the wavelet coherence approach. More importantly, the outcomes of wavelet-based Granger causality unveil that there is two-way causality between the selected indicators, which means that all the indicators can predict each other at different frequencies. Our empirical results provide meaningful information for market participants and policymakers.
The study aims to explore the extent to which Jordanian e-news sites rely on artificial intelligence applications in their news content. The researchers will use a media survey methodology, and the sample will consist of 45 editors-in-chief and editors from 10 Jordanian news sites, namely: Ammon, Khabrny, Joe24, Saraya, Amman Net, Jafra, Crown News, Petra, Kingdom, and Roya. The researcher will use an electronic questionnaire, which led to several findings, the most significant of which are: Many news and media sites have introduced artificial intelligence systems to enhance the services they provide to the public. A significant number of journalistic and electronic media websites have shown interest in data analysis tools for their media services. Electronic news sites are clearly striving to improve their capabilities in using artificial intelligence technologies to enhance the services they provide to the Jordanian audience. Additionally, most electronic media websites have expressed a willingness to develop a plan to improve cybersecurity systems to protect against hacking and intrusion attempts, safeguarding their data and the AI systems that operate continuously.AI systems in media organizations also aim to enhance the news experience for users by enriching media services with modern, communicative content.
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