Efficiency Of Research Activities Research Articles

A GPT-4 Reticular Chemist for Guiding MOF Discovery.

We present a new framework integrating the AI model GPT-4 into the iterative process of reticular chemistry experimentation, leveraging a cooperative workflow of interaction between AI and a human researcher. This GPT-4 Reticular Chemist is an integrated system composed of three phases. Each of these utilizes GPT-4 in various capacities, wherein GPT-4 provides detailed instructions for chemical experimentation and the human provides feedback on the experimental outcomes, including both success and failures, for the in-context learning of AI in the next iteration. This iterative human-AI interaction enabled GPT-4 to learn from the outcomes, much like an experienced chemist, by a prompt-learning strategy. Importantly, the system is based on natural language for both development and operation, eliminating the need for coding skills, and thus, make it accessible to all chemists. Our collaboration with GPT-4 Reticular Chemist guided the discovery of an isoreticular series of MOFs, with each synthesis fine-tuned through iterative feedback and expert suggestions. This workflow presents a potential for broader applications in scientific research by harnessing the capability of large language models like GPT-4 to enhance the feasibility and efficiency of research activities.

A GPT‐4 Reticular Chemist for Guiding MOF Discovery**

AbstractWe present a new framework integrating the AI model GPT‐4 into the iterative process of reticular chemistry experimentation, leveraging a cooperative workflow of interaction between AI and a human researcher. This GPT‐4 Reticular Chemist is an integrated system composed of three phases. Each of these utilizes GPT‐4 in various capacities, wherein GPT‐4 provides detailed instructions for chemical experimentation and the human provides feedback on the experimental outcomes, including both success and failures, for the in‐context learning of AI in the next iteration. This iterative human‐AI interaction enabled GPT‐4 to learn from the outcomes, much like an experienced chemist, by a prompt‐learning strategy. Importantly, the system is based on natural language for both development and operation, eliminating the need for coding skills, and thus, make it accessible to all chemists. Our collaboration with GPT‐4 Reticular Chemist guided the discovery of an isoreticular series of MOFs, with each synthesis fine‐tuned through iterative feedback and expert suggestions. This workflow presents a potential for broader applications in scientific research by harnessing the capability of large language models like GPT‐4 to enhance the feasibility and efficiency of research activities.

Research and Innovation as Priority Directions for the Development of the System Higher Education in the Republic of Uzbekistan

This article is devoted to the analysis of the activities of higher educational institutions of the Republic of Uzbekistan in reliance upon such criteria as academic prestige, efficiency of research activities and the quality of human resources. In addition, the authors have analyzed the ranking of Uzbekistan in the Global Innovation Index (GII) for the period 2020-2022 within the framework of indicators of efficiency of research and development and the use of innovations in the higher education system.

Аналіз ресурсних та інвестиційно-інноваційних факторів розвитку галузевих структур

The article is aimed at solving the actual problem of studying the factors of internal and external environment of functioning of sectoral structures. The authors analyzed an aggregate of various indicators for assessing the factors of development of sectoral structures using methods of multivariate statistical analysis. The completeness of the theoretical description of objects and objectivity of conclusions during the study of the problem of factor analysis of functioning of the mechanism of management of sectoral structures has been achieved. The problem of analysis of resource and investment-innovation factors of development of sectoral structures using factor analysis is examined. It is proposed to quantify the efficiency of functioning of the mechanism of enterprise management to use indicators of assessment of resource and investment-innovation potentials, which should be considered as indicators of outputs of the production system, transformed and obtained as a result of the influence of the management mechanism. The analysis was carried out in two directions: resource and investment-innovation. A large number of indicators characterizing the state of the internal and external environment of enterprises were processed, and using the methods of factor analysis, they were replaced with a certain set of uncorrelated parameters, which allowed to reduce the dimension of the studied totality of data. The state of resource and investment-innovation potentials of enterprises was considered as a result of the influence of the management mechanism, taking into account industry affiliation, that is, separately for enterprises of mechanical engineering, light or food industries. As result of the analysis, the following general factors were formed for light industry enterprises: economic direction of capital use; efficiency of use of the labor and material resources; efficiency of use of the equity and borrowed capital; efficiency of use of the borrowed funds. For food industry enterprises, the following factors are formed: the economic direction of capital use; efficiency of the financial and production activities; the ability of the management mechanism to provide a stable amount of profit; efficiency of use of fixed assets. Within the terms of investment and innovation direction for mechanical engineering and light industry enterprises, the most important factor is that which can be interpreted as the efficiency of research activities, the less important factor – the direction of using own investments for innovation; of the smallest importance is the direction of using investment resources for the production of innovative products.

Методичні підходи до оцінки результативності та ефективності науково-дослідної діяльності: світова практика

The article discusses methodological approaches to assessing the effectiveness and efficiency of research activities used in world practice, in particular, such OECD standards as Oslo Manual, Frascati Manual, Using Patent Data as Science and Technology Indikators – Patent Manual, The Measurement of Human Resources Devoted to S&T – Canberra Manual and Guide for the Measurement and Interpretation of Balance of Payments Data, Hong Kong Principles etc. The assessment of the scientific sphere in international comparisons is given according to the following world rankings: The Global Innovation Index (GII, Global Innovation Index), the Global Competitiveness Index (GCІ, The Global Competitiveness Index) and the European Innovation Scoreboard (EIS, European Innovation Scoreboard). To compare world practice, the article presents the indicators used in Ukraine for grouping statistical data on scientific activity, which are covered by the State Statistics Service and the Ministry of Education and Science. The article emphasizes the importance of adopting the Concept of the State Program for the Development of Research Infrastructures in Ukraine until 2026, proposed by the Ministry of Education and Science. The adoption of such a Concept is extremely important, as its implementation will contribute to the effective and balanced development of research infrastructures and will ensure the functioning of the research infrastructure system at the appropriate level. Scientists will be provided with access to a competitive research infrastructure and motivated to engage in high-level scientific and scientific-technical activities. The effectiveness of the Concept implementation measures will be ensured by optimizing logistical, financial and labor costs aimed at improving the quality of Ukrainian research infrastructures.

The knowledge spillover effects of FDI on the productivity and efficiency of research activities in China

As China is moving toward an innovation-driven economy, this paper offers new insights for both policymakers and investors to optimize the effectiveness of investment performance. This paper studies China's provincial research activities with a focus on the spillover-induced productivity and efficiency change. The results show that spillovers as a result of inflow of foreign investment contribute positively to the performance of overall research activities, however, the productivity effects vary across regions. Our analysis also indicates that highly skewed distribution of FDI leads to a less improved innovation efficiency in FDI-rich provinces. Future innovation policy should adjust the investment profiles based on the preferential innovation output on one hand, and optimize the complementary policy for FDI on the other hand to reduce inefficiency and the potential negative effects of knowledge spillovers. Inter-provincial governmental cooperation is necessary to resolve the uneven distribution of FDI and improve the innovation efficiency in both FDI-poor and rich regions.

Innovation Goes Global

By taking a U.S.-national approach to innovative capabilities and comparing the present with the postwar period, W. B. Bonvillian (“Advanced manufacturing policies and paradigms for innovation,” Policy Forum, 6 December 2013, p. [1173][1]) ignores the truly transformational change that has occurred over the past several decades: the growth of the global science system. The critical knowledge needed to innovate into the next generation of production is increasingly distributed across the globe, and it is just as likely to be located in India or China as in Ohio. The Organization for Economic Co-Operation and Development reports that the growth in the number of triadic patents demonstrates the worldwide spread of innovative activities ([ 1 ][2]). U.S. researchers are actively tapping this global resource by collaborating with researchers from many other countries. The global network of international links (drawn from coauthorships on publications) has tripled in density over the past 20 years ([ 2 ][3]), with many new members joining the global network from developing countries, particularly China. Chinese addresses now appear more frequently than any other country in publications coauthored with U.S. researchers. Scientific globalization does not threaten an end to U.S. excellence in innovation; quite the opposite. The diffusion and rooting of scientific capacity to new places provides opportunity for greater efficiency in research activities, particularly by removing redundancy. Creative problem-solving can be enhanced by having new entrants grapple with technological challenges, as many U.S. companies are finding as they invest in foreign research. Culturally tied knowledge is often important to market access in foreign countries. These goods require a deliberate policy shift on the part of U.S. agencies from pushing knowledge creation to fomenting knowledge scanning and integration. Scanning the globe for the best new knowledge and ensuring local uptake is the more promising approach to closing the gaps in U.S. know-how than building a U.S.-only R&D effort, as Bonvillian suggests. 1. [↵][4] OECD, OECD Science, Technology and Industry Scoreboard 2013 (OECD Publishing, Paris, 2013). 2. [↵][5] 1. L. Leydesdorff, 2. C. Wagner , J. Informetrics 2, 317 (2008). [OpenUrl][6][CrossRef][7][Web of Science][8] [1]: /lookup/doi/10.1126/science.1242210 [2]: #ref-1 [3]: #ref-2 [4]: #xref-ref-1-1 View reference 1 in text [5]: #xref-ref-2-1 View reference 2 in text [6]: {openurl}?query=rft.jtitle%253DJ.%2BInformetrics%26rft.volume%253D2%26rft.spage%253D317%26rft_id%253Dinfo%253Adoi%252F10.1016%252Fj.joi.2008.07.003%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [7]: /lookup/external-ref?access_num=10.1016/j.joi.2008.07.003&link_type=DOI [8]: /lookup/external-ref?access_num=000260903700007&link_type=ISI

A decision support system for public research organizations participating in national research assessment exercises

AbstractWe are witnessing a rapid trend toward the adoption of exercises for evaluation of national research systems, generally based on peer review. They respond to two main needs: stimulating higher efficiency in research activities by public laboratories, and realizing better allocative efficiency in government funding of such institutions. However, the peer review approach is typified by several limitations that raise doubts for the achievement of the ultimate objectives. In particular, subjectivity of judgment, which occurs during the step of selecting research outputs to be submitted for the evaluations, risks heavily distorting both the final ratings of the organizations evaluated and the ultimate funding they receive. These distortions become ever more relevant if the evaluation is limited to small samples of the scientific production of the research institutions. The objective of the current study is to propose a quantitative methodology based on bibliometric data that would provide a reliable support for the process of selecting the best products of a laboratory, and thus limit distortions. Benefits are twofold: single research institutions can maximize the probability of receiving a fair evaluation coherent with the real quality of their research. At the same time, broader adoptions of this approach could also provide strong advantages at the macroeconomic level, since it guarantees financial allocations based on the real value of the institutions under evaluation. In this study the proposed methodology was applied to the hard science sectors of the Italian university research system for the period 2004–2006.

Toward a new economics of science

Science policy issues have recently joined technology issues in being acknowledged to have strategic importance for national ‘competitiveness’ and ‘economic security’. The economics literature addressed specifically to science and its interdependences with technological progress has been quite narrowly focused and has lacked an overarching conceptual framework to guide empirical studies and public policy discussions in this area. The emerging ‘new economics of science’, described by this paper, offers a way to remedy these deficiencies. It makes use of insights from the theory of games of incomplete information to synthesize the classic approach of Arrow and Nelson in examining the implications of the characteristics of information for allocative efficiency in research activities, on the one hand, with the functionalist analysis of institutional structures, reward systems and behavioral norms of ‘open science’ communities-associated with the sociology of science in the tradition of Merton-on the other. An analysis is presented of the gross features of the institutions and norms distinguishing open science from other modes of organizing scientific research, which shows that the collegiate reputation-based reward system functions rather well in satisfying the requirement of social efficiency in increasing the stock of reliable knowledge. At a more fine-grain level of examination, however, the detailed workings of the system based on the pursuit of priority are found to cause numerous inefficiencies in the allocation of basic and applied science resources, both within given fields and programs and across time. Another major conclusion, arrived at in the context of examining policy measures and institutional reforms proposed to promote knowledge transfers between university-based open science and commercial R&D, is that there are no economic forces that operate automatically to maintain dynamic efficiency in the interactions of these two (organizational) spheres. Ill-considered institutional experiments, which destroy their distinctive features if undertaken on a sufficient scale, may turn out to be very costly in terms of long-term economic performance.

Factor Prices and Technical Change in Agricultural Development: The United States and Japan, 1880-1960

The purpose of this paper is to explore the hypothesis that a common basis for rapid growth in agricultural output and productivity lies in a remarkable adaptation of agricultural technology to the sharply contrasting factor proportions in the two countries. It is hypothesized that an important aspect of this adaptation was the ability to generate a continuous sequence of induced innovations in agricultural technology biased towards saving the limiting factors. In Japan these innovations were primarily biological and chemical. In the United States they were primarily mechanical.