نشریه سیاست نامه علم و فناوری
سال سیزدهم شماره 1 (پیاپی 42، بهار 1402)

Payment technology or paytech is one of the largest sub-sectors of fintech and focuses on the movement of money within the country. the transition from traditional services to innovative services has many advantages, but in terms of establishing international relations, protecting users, and also the environment in which the startup business operates, the challenges exist. The purpose of this study is to know the typology of paytech transition path Based on what has happened so far in the field of payment. The research paradigm is interpretive and the research method is qualitative and based on narrative-research and the analytical framework of multilevel perspective is used. data has been collected from Central Bank Regulations and reports published in fintech media from the beginning of 1389 to the end of 1399. During this period, 829 reports were reviewed, of which 130 were related to the discussion, and by studying them, the actors and their relationship with each other and their behavior in the face of changes in regulations, laws, and the provision of new services were examined and the coexistence or competitiveness of the relationship, as well as the level of development of innivation and its competitiveness with the regime were analyzed. results show that the transition path is technological substitution and due to the gradual changes, it follows the pattern of Fit and Conform.

In the present study, a systemic approach while examining the innovation ecosystem in the field of radiation application and using the data theory method, while analyzing the challenges of developing an innovation ecosystem in the field of radiation application, solutions appropriate to key challenges and appropriate policy recommendations and implications for Country is provided. Findings from the research show that the key elements of innovation ecosystem development in the field of application of radiation in the country include the presence of influential actors in charge of the application, rearrangement of the internal structure of the Atomic Energy Organization, brand reconstruction and development of innovation ecosystem-centered roadmap It is nuclear and this is the basis for the conceptual model of developing the domestic share in the country's oil and gas industry.

The national system of industrial property is an important part of the infrastructure of innovation, and the reform and improvement of this system is a practical step towards enhancing the national capacity for innovation. An effective industrial property system provides the infrastructure that facilitates technology transfer and helps attract foreign direct investment. However, in many developing countries, setting up an industrial property system does not meet their development needs. In Iran, this system has a long history, but the impact of their development is unknown. The purpose of this study is to develop a model for evaluating the successful implementation of industrial property policy. This research is of qualitative type and its method is data foundation theory and the required data are obtained from semi-structured owners. For this purpose, 13 experts, professors and experts with sufficient knowledge and practical experience were interviewed and a semi-structured method based on Atlas ta software was used to collect the required research data. To validate the results of the interviews with experts, 90 property policy implementers were surveyed, and through data analysis, the researcher discovered, identified, and classified the facts and results. In this study, the researcher analyzed the data and information obtained from the questionnaire after extraction and classification using SmartPLS2 and SPSS26 software. The result is a valid tool for evaluating the implementation of industrial property policies in the country

Machine learning is a set of algorithms that make it possible for a computer to learn statistical patterns in existing data without explicit programming. Machine learning has many applications in financial services such as fraud detection, automated portfolio management, estimating transaction risk levels, and more. But since most of these methods require large amounts of data, performing these calculations on classical computers requires a large amount of computational time and resources. Because of their parallel processing power, quantum computers can solve certain computational problems much faster than their classical counterpart algorithms. Therefore, it is possible to increase the quantum speed in machine learning algorithms. This article examines the impact of quantum machine learning on financial science. Specifically, the present study has tried to identify those computational problems in the field of financial sciences that the use of quantum machine learning method is superior to the best classical algorithms. The feasibility of physical realization of these methods in the short term has also been investigated.

Today, the scientific community and science and technology policy makers have more than ever realized the need to create and apply environmental scenarios in climate change policies and put it on the agenda. Although these scenarios are not predictive of the future, they provide decision makers with a good understanding of the events and possible paths ahead. In this study, we have evaluated the production process of these scenarios by examining valid scenarios in the field of climate, such as the IPCC and other studies. The new generation of these scenarios with the approach of parallel compilation of emmision scenarios known as "RCP" and "SSP" scenarios. These scenarios, by reducing the time lag and greater correlation between researchers in various fields, have led to the widespread and optimal use of these scenarios by international researchers and policy makers in national and regional research. In the following, after stating the process of preparing these scenarios, we have presented five major narratives of the SSP scenarios and expressed the main features of each route and made comparisons about the four indicators.

Covid_19 pandemic is the most important issue that the world is facing with which directly effects human and even animal health. In addition to its irreparable effects on human health, this disease has had many economic social and environmental effects on the world and has alleviate the quality of human life. This essay proposes five main solutions for the world after Covid_19. Authors first recommend economic redistribution by advising to avoid a development model concentrated on cumulative economic growth then the importance of regenerative agriculture, protection of environment, reduction of consumption as well as unnecessary travel and forgiveness of debts at the international level as the key solutions for the world post covid-19 to deal with current risks. After reviewing each solution, we suggestions for further research are presented.