Advancements in technology and innovation for sustainable agriculture: Understanding and mitigating greenhouse gas emissions from agricultural soils.

In recent decades, Technology and Innovation (TI) have shown tremendous potential for improving agricultural productivity and environmental sustainability. However, the adoption and implementation of TI in the agricultural sector and its impact on the environment remain limited. To gain deeper insights into the significance of TI in enhancing agricultural productivity while maintaining environmental balance, this study investigates 21 agriculture-dependent Asian countries. Two machine learning techniques, LASSO (Least Absolute Shrinkage and Selection Operator) and Elastic-Net, are employed to analyze the data, which is categorized into three regional groups: ASEAN (Association of Southeast Asian Nations), SAARC (South Asian Association for Regional Cooperation), and GCC (Gulf Cooperation Council). The findings of this study highlight the heterogeneous nature of technology adoption and its environmental implications across the three country groups. ASEAN countries emerge as proactive adopters of relevant technologies, effectively enhancing agricultural production while simultaneously upholding environmental quality. Conversely, SAARC countries exhibit weaker technology adoption, leading to significant fluctuations in environmental quality, which in turn impact agricultural productivity. Notably, agricultural emissions of N2O (nitrous oxide) and CO2 (carbon dioxide) in SAARC countries show a positive association with agricultural production, while CH4 (methane) emissions have an adverse effect. In contrast, the study reveals a lack of evidence regarding technological adoption in agriculture among GCC countries. Surprisingly, higher agricultural productivity in these countries is correlated with increased N2O emissions. Moreover, the results indicate that deforestation and expansion of cropland contribute to increased agricultural production; however, this expansion is accompanied by higher emissions related to agricultural activities. This research represents a pioneering empirical analysis of the impact of TI and environmental emission gases on agricultural productivity in the three aforementioned country groups. It underscores the imperative of embracing relevant technologies to enhance agricultural output while concurrently ensuring environmental sustainability. The findings of this study provide valuable insights for policymakers and stakeholders in formulating strategies to promote sustainable agriculture and technological advancement in the context of diverse regional dynamics.

Graph-Regularized Non-Negative Tensor-Ring Decomposition for Multiway Representation Learning.

Tensor-ring (TR) decomposition is a powerful tool for exploiting the low-rank property of multiway data and has been demonstrated great potential in a variety of important applications. In this article, non-negative TR (NTR) decomposition and graph-regularized NTR (GNTR) decomposition are proposed. The former equips TR decomposition with the ability to learn the parts-based representation by imposing non-negativity on the core tensors, and the latter additionally introduces a graph regularization to the NTR model to capture manifold geometry information from tensor data. Both of the proposed models extend TR decomposition and can be served as powerful representation learning tools for non-negative multiway data. The optimization algorithms based on an accelerated proximal gradient are derived for NTR and GNTR. We also empirically justified that the proposed methods can provide more interpretable and physically meaningful representations. For example, they are able to extract parts-based components with meaningful color and line patterns from objects. Extensive experimental results demonstrated that the proposed methods have better performance than state-of-the-art tensor-based methods in clustering and classification tasks.

Dynamics between carbon emission, imported cultural goods, human capital, income, and energy consumption: renewed evidence from panel VAR approach.

Few studies have examined the link between the importation of cultural goods and carbon emission. With an emphasis on the driving forces of carbon emission, this paper constructs conventional panel vector autoregressive (PVAR) models to examine the dynamics between carbon emission, imported cultural goods, income, human capital, and energy consumption based on country-panel data of 158 countries or regions from 2004 to 2017. Through Granger causality tests, we find a unidirectional causality running from GDP per capita to energy consumption, from HDI to imported cultural goods, from imported cultural goods to carbon emission, and from imported cultural goods and energy consumption for Annex I countries. As for non-Annex-I countries, energy consumption is the Granger cause of GDP per capita, while HDI has a bidirectional causality with GDP per capita. Through impulse response functions, we find that energy consumption and GDP per capita have significantly positive impacts on carbon emission within the shorter period for non-Annex-I countries than for Annex-I countries. In the same pattern, imported cultural goods have significantly negative impacts on carbon emission. Our variance decomposition results showed that the largest variation in carbon emission can be explained by its own shock for both non-Annex-I countries and Annex-I countries, while the carbon emission of Annex-I countries showed a stronger path dependence than non-Annex-I countries.

Relationship between economic liberalization and intellectual property protection with regional innovation in China. A case study of Chinese provinces.

International openness can affect regional innovation through more export opportunities, enhanced import competition and the spillover effects of foreign direct investment. Many studies have been conducted based on different countries for capturing the determinants of regional innovation, but very little literature is available with contradictory findings for the case of China. Based on 19 years' panel data of 31 Chinese provinces, this paper analyzes the impact of international openness on regional innovation measured by the number of patent grants. The positive effects of overall trade and a higher proportion of exports and imports to GDP are significant and robust across different model specifications, indicating that an increase in international openness can promote regional innovating activities in China. The causal relationship of all the variables depicted by path analysis matches the results of the system GMM model. Higher intellectual property protection provides each region with the opportunity to obtain economic benefits from innovation and then make a higher investment in R&D activities. Besides, the lag effect of regional innovation capability can also explain a large part of local innovating activities. In our subsample regressions, the positive effect of trade openness on innovation is majorly manifested in developed areas like eastern provinces.

The impact of economic complexity on embodied carbon emission in trade: new empirical evidence from cross-country panel data.

Establishing a fair platform for allocating carbon emission responsibility worldwide determines the sustainability and efficiency of the world's climate policy and framework. In the context of global environmental load displacement and CO2 transfer, this paper endeavors to examine the relationship between economic complexity and embodied carbon emissions based on cross-country panel data. Our study utilizes the generalized method of moments (GMM) approach to estimate our dynamic models covering 34 OECD countries and 24 non-OECD countries from 1995 to 2015. The empirical results show a heterogeneous impact of economic complexity on embodied carbon emissions in exports (EEE) and imports (EEI). Besides, the scale effect, composition effect, and technology effect are also significant drivers of embodied carbon emissions. The improvement of economic complexity can decrease the marginal effects of export scale and export structure on foreign EEE (but not domestic EEE) significantly, while the marginal positive impacts of technology on EEE can be further enhanced by economic complexity growth. Moreover, there is no strong evidence to prove the significant indirect impacts of economic complexity on foreign carbon emission embodied in imports, while economic complexity has significantly positive indirect impacts on domestic carbon emission embodied in imports only through import scale. In the subsample regressions, we found asymmetric impacts of economic complexity between high-income countries and low- and middle-income countries.

Attitudes of the patients and their families towards cancellation of anesthesia and surgery in hypertensive patients.

BACKGROUND: Pre-operative hypertension which is a common cause for cancellation of scheduled surgery is not merely a medical consideration. Understanding the patients' and their families' attitudes towards this issue may help develop an efficient system of qualitative management and promote the utilization of medical resources in a hospital. METHODS: Questionnaire of the study regarding the attitudes towards pre-operative hypertension and cancellation of scheduled surgery was answered through interviews by the patients and families admitted in a rural hospital in early 2003. RESULTS: A total of 189 people were interviewed. Over 42% of interviewees said that cancellation of scheduled surgery in hypertensive patients was acceptable. Nearly 43% felt that such a cancellation did not cause any loss to patient. However, less than 12% of respondents could accept the occurrence of a post-operative cardiovascular complication as a reasonable event even though most of them acknowledged that a hypertensive patient was not a good risk for surgery. If any loss or complication occurred, more than half of them thought that it was the surgeon's fault. CONCLUSIONS: Most patients and families in this rural area accept case cancellation rather than tempt the suffering of a post-operative cardiovascular complication. Developing a standard guideline for postponement of anesthesia and surgery in hypertensive patients may help reduce the variability in practising and management, with resultant increase of operating suite efficiency.