The use of artificial intelligence (AI) in the detection and diagnosis of plant diseases has gained significant interest in modern agriculture. The appeal of AI arises from its ability to rapidly and precisely analyze extensive and complex information, allowing farmers and agricultural experts to quickly identify plant diseases. The use of artificial intelligence (AI) in the detection and diagnosis of plant diseases has gained significant attention in the world of agriculture and agronomy. By harnessing the power of AI to identify and diagnose plant diseases, it is expected that farmers and agricultural experts will have improved capabilities to tackle the challenges posed by these diseases. This will lead to increased effectiveness and efficiency, ultimately resulting in higher agricultural productivity and reduced losses caused by plant diseases. The use of artificial intelligence (AI) in the detection and diagnosis of plant diseases has resulted in significant benefits in the field of agriculture. By using AI technology, farmers and agricultural professionals can quickly and accurately identify illnesses affecting their crops. This allows for the prompt adoption of appropriate preventative and corrective actions, therefore reducing losses caused by plant diseases.

Autism is often referred to as autism spectrum disorder that constitutes a diverse group of conditions related to brain development (which is a neurodevelopmental disorder). Autism spectrum disorder patients often have difficulty communicating and interacting socially, and are characterized by restricted and repetitive patterns of behavior and interests that have been shown to be the same in cultures of countries around the world. However, the interpretation of symptoms and recognition in terms of policies and laws in countries are not the same. Accordingly, some countries recognize autism spectrum disorder as one of the types of disability and some countries do not, including Vietnam. Currently, Vietnam's Law on Persons with Disabilities 2010 does not recognize the term "autism" in the Law. At the same time, there is a lack of legal issues related to the "autism spectrum" from the time of diagnosis such as policies on practical support appropriate to each individual's needs and interests so that they can develop and be integrated in the medical field, education and enjoyment of other benefits such as persons with disabilities. This is an overlooked term that leads to the community having a misperception of "autism" when they are not aware that autism is a disease or a disability, what causes autism and why, etc. The article points out the current situation of adjustment by policies and laws on autistic people in Vietnam. On that basis, the article focuses on analyzing the contents that need to reform those policies and laws to ensure human rights of autistic people and their families.

The study aims to explore the role of artificial intelligence in enhancing the efficiency of public relations practitioners in Jordanian telecommunication companies. This study belongs to the category of descriptive research and adopted a survey methodology. The study surveyed (86) individuals representing the community of public relations practitioners and customer service personnel in the Jordanian telecommunication companies Zain and Orange.The study findings revealed that less experienced public relations personnel in Zain and Orange, with less than five years of experience, exhibit greater acceptance and enthusiasm for using artificial intelligence applications compared to their more experienced counterparts. The study also indicated that most public relations practitioners in Zain and Orange perceive artificial intelligence applications to have a moderate to significant contribution to achieving public relations functions and enhancing their work, reflecting technological advancement and the need to adapt to rapid changes in the business environment. Moreover, the study also discussed the limits, including that artificial intelligence can analyze large amounts of data related to the market and the audience, which provides further research and study.

Consumer satisfaction can be defined as the user’s response to a service or experience compared to the user’s expectations and perceived practical benefits. After reviewing consumer satisfaction models, it can be argued that there is no single model of consumer satisfaction assessment that is suitable for every service and every region of the world, as the causes and outcomes of satisfaction often vary. The research is original in its methodology: at the beginning, a theoretical research model is presented, then hypotheses are formulated, and correlation, factorial, regression analyses were made, which results confirmed hypotheses. The crop insurance system consists of relations between the state institution regulates insurance activities, farmers, insurers and insurance intermediaries. The aim of this article is to identify the factors that determine consumer satisfaction with crop insurance and to assess their impact. The empirical study found that consumer satisfaction is determined by the factors of recognizable value, functional (process) and technical (result) quality, consumer expectations, and image. The most important factors that determine consumer satisfaction of crop insurance are recognizable value, functional quality, and consumer expectations. Consumer satisfaction can be assessed by the cost paid and the quality received, the quality expected, and the consumers’ evaluation of the services. It was found that the socio-demographic elements of consumers do not have a decisive influence on the factors that determine service satisfaction and consumer satisfaction. It is also established that socio-demographic elements of consumers (farmer experience and insurance experience) have direct statistically significant but weak links with consumer satisfaction.

In the current context of China’s vigorous development of its high-speed rail (HSR) network to accelerate the realization of connectivity, which is the aim of the “Belt and Road” initiative, it is crucial to study how the specific opening of HSR enhances enterprise human capital investment efficiency. Using a multiple-time-point difference-in-differences (DID) regression model, we empirically study data from listed Chinese companies. An HSR opening can promote the efficiency of an enterprise’s human capital investment. We further explore the relationship between HSR and a company’s human capital investment, by considering the moderating effects of firm property rights and foreign shareholding. Our findings indicate that these factors can enhance the impact of HSR on the efficiency of firms’ investments in human capital. Finally, to ensure the reliability of our experimental findings, we employed a combination of propensity score matching and the DID methodology. The findings of this study offer empirical evidence that can inform enterprise management strategies and provide valuable insights for policymakers seeking to promote economic growth.