Total factor productivity (TFP) is essential for disentangling the determinants of economic growth, productivity, and the standard of living. Understanding the variations in TFP, however, is greatly challenging because of the many assumptions that comprise the theoretical growth framework. In this paper, we aim to explore the determinants of TFP growth for countries at different stages of information and communication technology (ICT) development. To address the endogenous nature of the associated growth variables, we implement a three-stage-least (3SLS) square panel regression to improve the efficiency and asymptomatic accuracy of the estimators. We find that transmission channels, such as financial openness and trade globalization, have contributed substantially to growth in both advanced and developing countries. However, we also discover that greater financial openness can undermine a country’s TFP growth if the financial system is not sufficiently developed. When time horizons are decomposed into pre-ICT development and post-ICT development periods, a significant crowding-out effect is observed between ICT investment and financial openness in the pre-period, implying that the allocation of resources is critical for countries in the developing stage. Trade and finance policies that are adopted by advanced and developed countries might not be ideal for underdeveloped countries. Discretion in choosing adequate policies regarding financial integration and trade liberalization is advised for these emerging countries.
The main objective of this study was comparative advantages analysis at social price of Num-mango in the export channels. The examination of the domestic resource cost per shadow exchange rate (DRC/SER) ratio provides insights into the comparative advantage of the trading system in the Num-mango industry. A comprehensive study was conducted, with a total of 317 observations, with a specific emphasis on the significant individuals in Vinh Long, Vietnam. The comparative advantage of the Num-mango commerce system was inferred from a DRC/SER ratio below one, which may be attributed to the existence of two distinct export channels. The DRC/SER in export channel 1 exhibited values of 0.55, 0.67, and 0.53 over the three seasons. In season 1, export channel 2 had a score of 0.42, which then was 0.79 in season 2. The value of export channel 2 had a consistent upward trend during season 3, reaching its highest point of 0.3. It is recommended that regulators and governments provide export-focused incentives that prioritize the maximum comparative advantage. This study examines the concept of comparative advantage within export supply chains, specifically in relation to a diverse selection of tropical fruits and vegetables. Furthermore, it provides empirical evidence that supports the applicability and reliability of the Ricardian model.
Soil salinity is a major abiotic stress that drastically hinders plant growth and development, resulting in lower crop yields and productivity. As one of the most consumed vegetables worldwide, tomato (Solanum lycropersicum L.) plays a key role in the human diet. The current study aimed to explore the differential tolerance level of two tomato varieties (Rio Grande and Agata) to salt stress. To this end, various growth, physiological and biochemical attributes were assessed after two weeks of 100 mM NaCl treatment. Obtained findings indicated that, although the effects of salt stress included noticeable reductions in shoots’ and roots’ dry weights and relative growth rate as well as total leaf area, for the both cultivars, Rio Grande performed better compared to Agata variety. Furthermore, despite the exposure to salt stress, Rio Grande was able to maintain an adequate tissue hydration and a high leaf mass per area (LMA) through the accumulation of proline. However, relative water content, LMA and proline content were noticeably decreased for Agata cultivar. Likewise, total leaf chlorophyll, soluble proteins and total carbohydrates were significantly decreased; whereas, malondialdehyde was significantly accumulated in response to salt stress for the both cultivars. Moreover, such negative effects were remarkably more pronounced for Agata relative to Rio Grande cultivar. Overall, the current study provided evidence that, at the early growth stage, Rio Grande is more tolerant to salt stress than Agata variety. Therefore, Rio Grande variety may constitute a good candidate for inclusion in tomato breeding programs for salt-tolerance and is highly recommended for tomato growers, particularly in salt-affected fields.
This article presents a methodology to perform quality analysis on the cadastral map, based on the tools provided by open (public or free) license geographic information systems (GIS). The errors presented in the cadastral map have a direct impact on the information systems, which can lead to erroneous decisions and to an increase in the costs of maintenance and updating of spatial data. The methodology developed was used and tested by Costa Rica’s Cadastre and Registry Regularization Program; as a product of this program, a continuous cadastral map has been created for Costa Rica, on which cadastral and registry transactions will be processed within the National Registry of Costa Rica. The methodology allows detecting, locating and classifying errors in the cadastral map for easily correcting, so that this map correctly represents the reality of the properties that conform it.
Branched micro/nano Se was prepared by the redaction of L-Cys•HCl and H2SeO3 in hydrothermal method, as β-CD was used as soft template. The structures of products were characterized by SEM, TEM and XRD. Some important factors influencing the morphology of products were studied and discussed, including the amounts of soft template, the reaction temperature and the reaction time. The results showed that external causes had a potent effect on the morphology of micro/nano Se. The uniform branched micro/nano Se prepared under the optimal reaction condition was rhombohedral trigonal selenium t-Se0, but its crystallinity degree was low.
With society’s continuous development and progress, artificial intelligence (AI) technology is increasingly utilized in higher education, garnering increased attention. The current application of AI in higher education impacts teachers’ instructional methods and students’ learning processes. While acknowledging that AI advancements offers numerous advantages and contribute significantly to societal progress, excessive reliance on AI within education may give rise to various issues, students’ over-dependence on AI can have particularly severe consequences. Although many scholars have recently conducted research on artificial intelligence, there is insufficient analysis of the positive and negative effects on higher education. In this paper, researchers examine the existing literature on AI’s impact on higher education to explore the opportunities and challenges presented by this super technology for teaching and learning in higher educational institutions. To address our research questions, we conducted literature searches using two major databases—Scopus and Web of Science—and we selected articles using the PRISMA method. Findings indicate that AI plays a significant role in enhancing student efficiency in academic tasks and homework; However, when considering this issue from an ethical standpoint, it becomes apparent that excessive use of AI hinders the development of learners’ knowledge systems while also impairing their cognitive abilities due to an over-reliance on artificial technology. Therefore, our research provides essential guidance for stakeholders on the wise use of artificial intelligence technology.
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