Hasil untuk "Trade associations"

L. Tedersoo, M. Bahram, M. Zobel

The pervasive power of mycorrhizas Associations between plants and symbiotic fungi—mycorrhizas—are ubiquitous in plant communities. Tedersoo et al. review recent developments in mycorrhizal research, revealing the complex and pervasive nature of this largely invisible interaction. Complex networks of mycorrhizal hyphae connect the root systems of individual plants, regulating nutrient flow and competitive interactions between and within plant species, controlling seedling establishment, and ultimately influencing all aspects of plant community ecology and coexistence. Science, this issue p. eaba1223 BACKGROUND All vascular plants associate with fungi and bacteria—the microbiome. Root associations with mycorrhizal fungi benefit most plants by enhancing their nutrient access and stress tolerance. Mycorrhizal fungi also mediate plant interactions with other soil microbes, including pathogens and mycorrhizosphere mutualists that produce vitamins and protect against antagonists. Through these functions, mycorrhizal root symbionts influence the belowground traits of plants, regulate plant-plant interactions, and alter ecosystem processes. Extensive mycorrhizal networks physically connect conspecific and heterospecific plant individuals belowground, mediating nutrient transfer and transmission of phytochemical signals. Arbuscular mycorrhiza (AM), ectomycorrhiza (EcM), ericoid mycorrhiza (ErM), and orchid mycorrhiza (OM) have a distinct evolutionary history, anatomy, and ecology, thereby differently affecting plant protection, nutrient acquisition, and belowground C and nutrient cycling. ADVANCES Mycorrhizal fungi are commonly the key determinants of plant population and community dynamics, with several principal differences among mycorrhizal types. We synthesize current knowledge about mycorrhizal effects on plant-plant interactions and ecological specialization. We conclude that mycorrhizal associations per se and fungal diversity and mycorrhizal types directly or indirectly affect plant dispersal and competition that shape plant populations and communities, and regulate plant coexistence and diversity at a local scale. Among AM plants, which represent nearly 80% of plant species globally, mycorrhizal associations and belowground hyphal networks tend to intensify intraspecific competition and alleviate interspecific competition by promoting the performance of inferior competitors. In AM systems, fungal diversity enhances plant diversity and vice versa, by providing species-specific benefits and suppressing superior competitors. Compared with other mycorrhizal types, EcM fungi provide substantial protection against soil-borne pathogens by ensheathing feeder roots and acidifying soil. Pathogen suppression leads to positive plant-soil feedback that promotes seedling establishment near adult trees, which can result in monodominant plant communities with a low diversity of various organism groups. Orchids produce millions of dust seeds with high dispersal potential to encounter compatible OM fungal partners, which nourish plants, at least in the seedling stage. Species of Ericaceae achieve competitive advantage and large population densities by shedding allelopathic litter and establishing ErM root symbiosis with selected groups of ubiquitous humus saprotrophs that have evolved efficient enzymes to access nutrients in recalcitrant organic compounds in strongly acidic environments. OUTLOOK Increasing evidence suggests that mycorrhizal fungi drive plant population biology and community ecology by affecting dispersal and establishment and regulating plant coexistence. Plant-fungal mycorrhizal associations per se and interlinking hyphal networks synergistically determine the functional traits and hence autecology of host plants, which is best reflected in the specialized nutrition and dispersal of orchids. Habitat patches dominated by either positive plant-soil feedback near EcM plants or negative conspecific feedback near AM plants may generate distinct regeneration patches for different plant species. Furthermore, niche differentiation both within and among mycorrhizal types enhances coexistence by leveraging interspecific competition through different rooting depths, foraging strategies, and soil nutrient partitioning. We still lack critical information about the mechanistic basis of several processes, such as interplant nutrient transfer through mycelial networks and the principles of carbon-to-nutrient exchange and trading in the mycorrhizal interface, as well as kin recognition and promotion. Understanding these processes will enable us to improve predictions about the impacts of global change and pollution on vegetation and soil processes and to elaborate technologies to improve yields in agriculture and forestry. Scheme indicating how mycorrhizal types (circles) differ in their effects on plant population- and community-level processes (squares). Blue lines, positive effects; red lines, negative effects; green lines, overlap of plant taxa among mycorrhizal types; pink lines, overlap of fungal taxa among mycorrhizal types. Line breadth indicates relative effect strength. ILLUSTRATION: SIIRI JÜRIS Mycorrhizal fungi provide plants with a range of benefits, including mineral nutrients and protection from stress and pathogens. Here we synthesize current information about how the presence and type of mycorrhizal association affect plant communities. We argue that mycorrhizal fungi regulate seedling establishment and species coexistence through stabilizing and equalizing mechanisms such as soil nutrient partitioning, feedback to soil antagonists, differential mycorrhizal benefits, and nutrient trade. Mycorrhizal fungi have strong effects on plant population and community biology, with mycorrhizal type–specific effects on seed dispersal, seedling establishment, and soil niche differentiation, as well as interspecific and intraspecific competition and hence plant diversity.

Zahoor Ahmed, Hoang Phong Le

M. Nasir, N. P. Canh, Thi Ngoc Lan Le

This paper is a pioneering endeavour to investigate the determinants of environmental degradation in Australia through a comprehensive framework of EKC and STIRPAT. Specifically, the impacts of multiple factors of socio-economic development including economic growth, trade openness, industrialization, energy consumption on CO2 emissions are analysed. Furthermore, the influences of financial development through different dimensions (financial efficiency, access and depth) in two subsectors (financial markets and institutions) and other proxies of financial development are focused over the period 1980-2014. Empirical results show short as well as long-run differences in the association among the variables. Short-term bidirectional causality prevails between economic growth, energy consumption, industrialization, and stock market development with carbon dioxide (CO2) emissions. However, there is no significant evidence found on EKC. This is due to the long-run positive impact of financial development, energy consumption, and trade openness on CO2 emissions. Interestingly, the industrialization process is found to does not affect CO2 emissions. Empirical findings provide insight into why the quality of the Australian environment is truncated with frequent and widespread bushfires and suggest policymakers to have selective and strict environmental-friendly strategies to fulfil a sustainable development goal.

Muntasir Murshed

Abstract This paper primarily aimed to assess the impacts of regional trade integration on the prospects of undergoing renewable energy transition in selected South Asian economies between 1992 and 2015. The overall results from the econometric analyses, controlling for the cross-sectional dependency and slope heterogeneity issues, highlight the importance of promoting intra-regional trade among the South Asian economies to boost the renewable energy consumption shares and renewable electricity output shares in the total final energy consumption and aggregate electricity output figures, respectively. Besides, the non-linearity of the nexuses between intra-regional trade shares and renewable energy consumption shares and between intra-regional trade shares and renewable electricity output shares are also ascertained. The threshold intra-regional trade shares concerning the renewable energy consumption and renewable electricity output shares are predicted at 20.53% and 17.50%, respectively. However, the predicted threholds are significantly higher than the current average intra-regional trade share in South Asia. Moreover, the panel causality analysis reveals unidirectional causal relationships stemming from intra-regional trade shares to renewable energy consumption and renewable electricity output shares. Besides, greater FDI inflows are found to reduce the overall use of renewable energy while higher levels of economic growth and CO2 emissions are found to catalyze renewable energy use in South Asia. Furthermore, the results also implicate a non-linear U-shaped association between positive crude oil price shocks and renewable energy consumption and renewable electricity output shares. Therefore, these findings impose critically important policy implications for liberalizing the intra-regional trade barriers, reducing dirty foreign direct investment inflows, expediting economic growth, reducing fossil fuel dependency and abating carbon dioxide emissions to facilitate renewable energy transition in South Asia.

Shanxiang Wei, Jiandong Wen, Hummera Saleem

This analysis investigates the impact of renewable energy consumption, green economic growth, green technology, green trade, and inward financial inflow on environmental quality in the world’s top green future economies from 1990–2018. The analysis applied the Cross-sectional-Augmented Auto Regressive Distributed Lag (CS-ARDL) method. For robustness check, the current study used Augmented Mean Group (AMG) and Common Correlated Effect Mean Group (CCEMG) methods to identify the relationship between variables in the long-run analysis. The statistical findings show that green trade and inbound FDI significantly improve the environment quality, confirming the hypothesis of a “pollution halo.” The results concluded that environmental quality is improving through trade liberalization in the short and long run. Green economic growth is stimulated through green energy (renewable energy use). These findings supported the theory of Core-macroeconomics. This analysis concluded that environmental quality is significantly improving through green technological innovation and growth. The bi-directional association between green growth and green technologies indicates that both promote a green and clean environment. The findings of this study significantly supported the theory of green competitiveness and the Porter hypothesis. The statistical results of green trade indicate that the reduction in CO2 emission enhances green economic growth. Thus, green trade is beneficial for these future green economies. The current analysis tries to establish helpful suggestions for policymakers on implementing practical policies addressing renewable energy sources, green growth projects, and green trade to improve environmental quality. Graphical Abstract Graphical illustration of D-H panel test.

Sajid Ali, Z. Yusop, Shivee Ranjanee Kaliappan et al.

Shu Jiang, M. Chishti, Husam Rjoub et al.

Dimitrios Emmanoulopoulos, Ollie Olby, Justin Lyon et al.

Large language models (LLMs) are increasingly deployed in agentic frameworks, in which prompts trigger complex tool-based analysis in pursuit of a goal. While these frameworks have shown promise across multiple domains including in finance, they typically lack a principled model-building step, relying instead on sentiment- or trend-based analysis. We address this gap by developing an agentic system that uses LLMs to iteratively discover stochastic differential equations for financial time series. These models generate risk metrics which inform daily trading decisions. We evaluate our system in both traditional backtests and using a market simulator, which introduces synthetic but causally plausible price paths and news events. We find that model-informed trading strategies outperform standard LLM-based agents, improving Sharpe ratios across multiple equities. Our results show that combining LLMs with agentic model discovery enhances market risk estimation and enables more profitable trading decisions.

Zifan Song, Kaitao Song, Guosheng Hu et al.

Recent advancements in large language models (LLMs) and agentic systems have shown exceptional decision-making capabilities, revealing significant potential for autonomic finance. Current financial trading agents predominantly simulate anthropomorphic roles that inadvertently introduce emotional biases and rely on peripheral information, while being constrained by the necessity for continuous inference during deployment. In this paper, we pioneer the harmonization of strategic depth in agents with the mechanical rationality essential for quantitative trading. Consequently, we present TiMi (Trade in Minutes), a rationality-driven multi-agent system that architecturally decouples strategy development from minute-level deployment. TiMi leverages specialized LLM capabilities of semantic analysis, code programming, and mathematical reasoning within a comprehensive policy-optimization-deployment chain. Specifically, we propose a two-tier analytical paradigm from macro patterns to micro customization, layered programming design for trading bot implementation, and closed-loop optimization driven by mathematical reflection. Extensive evaluations across 200+ trading pairs in stock and cryptocurrency markets empirically validate the efficacy of TiMi in stable profitability, action efficiency, and risk control under volatile market dynamics.

F. Ahmed, Shazia Kousar, Amber Pervaiz et al.

The objective of this study is to contribute to the existing debate of green economic growth by empirically investigating the role of cleaner energy production, green innovation, and green trade in green economic growth in the context of South Asian countries. For this purpose, the study collects the data of South Asian Economies for 2000–2018 from different sources such as world development indicators (WDI), International Energy Statistics (IES), and Organization for Economic Co-operation and Development (OECD) statistics. The study applied Pesaran’s (2007) second-generation unit root test to test the stationarity of the data. Wasteland’s (2007) test of cointegration was applied to examine the long-run association among modeled variables. The study confirmed the long-run association among modeled variables that turn to be stationary at the first differences. Moreover, the study applied fully modified least square (FMOLS) and dynamic least square (DOLS) to estimate the empirical results of the study. Results of the study show that the production of clean energy, green innovation, and green trade positively contributes to the green economic growth of South Asian Economies Graphical abstract Graphical abstract Graphical abstract

Rulia Akhtar, M. M. Masud, Nusrat Jafrin et al.

Jonathan Munguti, Mavindu Muthoka, Mercy Chepkirui et al.

This review paper provides an in-depth analysis of the current status, challenges, and strategies for improvement within the fish feed industry in East Africa, focusing on Kenya, Uganda, Tanzania, and Rwanda. Aquaculture production in these countries is experiencing steady growth, driven by increasing demand for fish and fish products for both nutritional and economic purposes. Despite the market facilitating the transition from extensive to semi-intensive and moderately intensive farming systems across the four countries, the sector’s progress is hampered by a lack of sustainable, locally produced, high-quality, and cost-effective fish feeds tailored to different developmental stages of fish. Despite the evident need, there is a notable scarcity of comprehensive reviews addressing the regional perspective of fish feed due to heightened cross-border trade driven by the soaring demand and increased installation of cages in Lake Victoria, as well as in inland dams and reservoirs. This paper addresses critical challenges, such as regional scarcity and limited access to quality feed ingredients, regulatory obstacles, insufficient quality control measures, infrastructure constraints, and a lack of awareness and understanding of feed management and formulation. To overcome these challenges, the paper recommends fostering collaboration to establish a robust regional fish feed supply chain, investing in research and development initiatives, advocating for policy reforms and regulatory support, and compliance with East African Community quality standards for fish feed. Moreover, there is an urgent need to enhance human resource capacity through training and extension services, promote public investment support, strengthen sector institutions and industry associations, conduct training and awareness programs for feed providers, and improve storage facilities to maintain feed quality. The paper provides policymakers with valuable insights to inform targeted interventions that will catalyze positive transformation within the fish feed industry in East Africa.

Surya Murthy, Mustafa O. Karabag, Ufuk Topcu

Autonomous agents interact with other autonomous agents and humans of unknown preferences to share resources in their environment. We explore sequential trading for resource allocation in a setting where two greedily rational agents sequentially trade resources from a finite set of categories. Each agent has a utility function that depends on the amount of resources it possesses in each category. The offering agent makes trade offers to improve its utility without knowing the responding agent's utility function, and the responding agent only accepts offers that improve its utility. To facilitate cooperation between an autonomous agent and another autonomous agent or a human, we present an algorithm for the offering agent to estimate the responding agent's gradient (preferences) and make offers based on previous acceptance or rejection responses. The algorithm's goal is to reach a Pareto-optimal resource allocation state while ensuring that the utilities of both agents improve after every accepted trade. The algorithm estimates the responding agent's gradient by leveraging the rejected offers and the greedy rationality assumption, to prune the space of potential gradients. We show that, after the algorithm makes a finite number of rejected offers, the algorithm either finds a mutually beneficial trade or certifies that the current state is epsilon-weakly Pareto optimal. We compare the proposed algorithm against various baselines in continuous and discrete trading scenarios and show that it improves the societal benefit with fewer offers. Additionally, we validate these findings in a user study with human participants, where the algorithm achieves high performance in scenarios with high resource conflict due to aligned agent goals.

Hayat Khan, Liu Weili, Itbar Khan et al.

Studies regarding environmental degradation and its association with different factors have got considerable attention recently in the prevalent literature but with assorted outcomes which have been a guide to the ongoing debate on environmental studies. Energy from renewable sources has been considered beneficial for environmental quality while it is still below the anticipated level especially in developing economies. Openness to trade is important to enhance economic growth while it has been overawed to worsen the quality of environment due to deprived policies especially in developing countries. Subsequently, the present research investigates trade openness, renewable energy consumption, and foreign direct investment in carbon emission in the world developing and developed countries by employing static, dynamic and long run estimators. Trade openness has been found to have a decreasing effect on carbon emission in developed countries while degrading the quality of environment in developing countries while renewable energy consumption enhances environmental quality in both samples. The impact of tourism on carbon emission varies in different samples where FDI increases emission in developed countries while having a negative effect of carbon emission in developing countries. The long run estimators also evidence the existence of long run association among variables. The outcomes of this study have considerable policy implication regarding trade openness policy formulation to upsurge environmental quality especially in developing countries. The study has further suggestions regarding tourism and promoting the use of renewable energy sources by avoiding the use of former’s energy to enhance environmental quality.

E. Bontempi, M. Coccia, S. Vergalli et al.

The main goal of this study is to analyze the relation between commercial trade and pandemic severity in society, in order to support new hypotheses which can explain transmission dynamics of COVID-19, as well as promote policy responses to cope with future epidemics similar to COVID-19. This study considers the role of trade in the dynamics of pandemic diffusion, within and between countries, which has not been investigated yet in this emerging field of research. We focus on three large countries in Europe: Italy, France, and Spain. The analysis is performed at regional level (involving in total 52 European regions). Results suggest that the association between trade and pandemic severity seems to be supported by empirical evidence, making it possible to introduce new hypotheses for explaining transmission dynamics of COVID-19 within and between countries. In particular, international trade data is supposed to be used as a comprehensive indicator accounting for population density, economic dynamism, and human mobility. The statistical analyses, also in a multivariate context, strongly support this hypothesis and suggest that crisis management has to focus in the very first place on infections occurring outside the national boundaries, in order to cope with pandemic threat of new waves of COVID-19 and future similar epidemics/pandemics.

Benjamin Johnson, Steven Co, Tianze Sun et al.

BACKGROUND AND AIMS The volatile and 24/7 nature of the cryptocurrency market allows traders to engage in speculative trading patterns closely resembling gambling. Its potential for harm and financial loss warrant investigation from a public health perspective. Therefore, we summarized the emerging literature on cryptocurrency trading and its link to problematic gambling and other mental health outcomes such as depression and anxiety. We also examined demographic or psychological factors associated with cryptocurrency trading. METHODS We searched PubMed, Scopus, and Embase for published, original studies investigating associations with cryptocurrency trading behavior. We also conducted supplementary searches using Google Scholar. RESULTS Eight papers were included after eligibility screening. Our scoping review revealed associations between problem gambling symptoms and cryptocurrency trading engagement and intensity. Furthermore, we found cryptocurrency traders share similar demographic and personality characteristics with share-traders and problem gamblers. Studies on cryptocurrency trading and mental health produced mixed results. DISCUSSIONS AND CONCLUSIONS Our scoping review indicates a likely relationship between problem gambling and cryptocurrency trading. Findings also suggest overlap with high-risk stock traders, with similarities in gambling behaviors, demographics, and personality traits. These findings justify further research into problem cryptocurrency trading behaviors and their potential for harm, especially concerning mental health. To assess what behaviors are problematic, future research should also look to explore differences between long-term investors and short-term traders of cryptocurrency.

A. Rehman, Hengyun Ma, Munir Ahmad et al.

A. Rehman, Hengyun Ma, Munir Ahmad et al.

R. Radmehr, E. B. Ali, Samira Shayanmehr et al.

Achieving economic development is one of the most important economic goals of every country. Identifying the determinants of economic growth, is a useful tool for adopting appropriate economic policies. This study, therefore, empirically examines the impact of trade openness, foreign direct investment, and financial development on economic growth, across 62 countries over the period 1995–2016. These countries are divided into two groups: low-income and high-income countries. We employ the pooled mean group (PMG), mean group (MG), and dynamic fixed effect (DFE) estimation techniques on the cross-country panel data. The findings show a positive long run association between trade openness, foreign direct investment (FDI), financial development, labor, government expenditure, and economic growth in low-income countries, with a positive and negative short run effect from capital and government expenditures, respectively. For high-income countries, a positive long run association between trade openness, FDI, capital, and economic growth exist. The short run estimates indicate a positive effect on trade openness and capital as well as a negative effect on government expenditure. Our study shows that the adoption of policies that improves access to skilled labor and international trade, affect the attainment of a sustainable economic development.

M. L. Gorbunova, I. D. Komarov, T. E. Maslova

Regionalization and participation at the integration associations represent a typical way of national economic development. To be inside an integration process allows member states to address better their socio-economic problems and political coordination. The stability and resilience of integration associations are critical to their success. In this optic the integration associations may be subjects convergence and divergence. These phenomena may be envisaged in the income inequality of the participating countries.Aim. To study the features and prospects of the socio-economic convergence within the EEU member states, the EEU strategic contour and within the main trends of integration processes in Eurasia.Task. The tasks are following. The first one is to study the sustainability of the EEU and within its strategic contours formed by agreements on free trade zones through the convergent and divergent trends assessment. The second task is to conduct a comparative analysis of Eurasian integration to the European Union and ASEAN development.Methods. Assess the level and dynamics of income inequality among the EEU states and samples of states with which the EEU has agreements on free trade zones, which are the CIS, Serbia, Vietnam, Iran and Singapore, as well as states with which such agreements are planned to be concluded in the near future. This list of the EEU’s prospect partners includes Egypt, Israel and India, based on the Gini index, using the European Union and ASEAN as reference parameters. Use calculations to interpret the processes of convergence and divergence of various types of integration processes.Results. The estimates showed, in general, a significant interpretive potential of the interstate Gini index. The study particular results demonstrated that the EEU has a level of convergence comparable to the level of the EU before the accession of a large array of states in 2004. The level of convergence of the CIS, estimated using the Gini index, is comparable to the current level of the European Union. It was also revealed that both in the EU and in the CIS, the reduction in inequality over the selected analysis interval does not have a clear prospect. Calculations also showed the convergence of states within the EEU and its strategic contours to be sensitive to external shocks, while the convergence of ASEAN states is more directed.Conclusions. The approach used by the authors to assess the convergence of integration processes based on the calculation of the interstate Gini index explains with sufficient completeness the reasons for the successful development of the EEU and its sustainability. At the same time, the use of the interstate Gini index for the analysis of convergence and divergence of integration processes made it possible to conclude that the integration models of the states of the Global North and the Global South are diverse.