Hasil untuk "Balance of trade"

Zhiming Zhao, Zhao Liu, Yuanyuan Geng et al.

Abstract Background The hexapod external fixator (HEF) allows for precise three-dimensional reduction of tibial fractures, but its therapeutic efficacy is highly dependent on the accuracy of postoperative mounting parameters. Currently, X-ray and computed tomography (CT) are the primary imaging modalities, each with distinct trade-offs between accuracy and efficiency in clinical use. This study compares the accuracy of postoperative X-ray and CT in measuring mounting parameters for HEF in tibial fracture treatment and assesses the associated clinical outcomes. Methods This single-center retrospective cohort study included 71 patients with tibial fractures treated with HEFs at our institution between June 2021 and June 2023. The cohort consisted of 40 males and 31 females, aged 30 to 60 years. Patients were divided into two groups based on the imaging method used for postoperative measurement of the hexapod fixator’s mounting parameters: the X-ray group (n = 34, using 2D measurements from standard anteroposterior (AP) and lateral radiographs) and the CT group (n = 37, using CT scans and 3D reconstruction). Baseline characteristics—including age, sex, mechanism of injury, AO/OTA fracture classification, and Gustilo-Anderson classification—were comparable between groups (all P > 0.05). Primary outcomes were the number of electronic prescriptions, time to fracture reduction (from the first postoperative electronic correction prescription to radiographic confirmation of satisfactory reduction), and measurement operation time. Secondary outcomes included final radiological outcome, time to fracture union, and Johner-Wruhs score at final follow-up. Results All 71 patients were followed up for a mean of 24.5 months (range: 18–36 months). The number of electronic prescriptions was lower in the CT group (median [IQR]: 1 [1]-[1]) than in the X-ray group (2 [1-2]). Time to fracture reduction was shorter in the CT group (3.3 ± 0.6 days vs. 4.8 ± 0.8 days). Measurement operation time was shorter in the X-ray group (12.9 ± 2.1 min vs. 14.1 ± 1.5 min). All these between-group differences were statistically significant. In the CT group, 81.1% (30/37) achieved satisfactory reduction with a single prescription, significantly higher than the 55.9% (19/34) in the X-ray group (P < 0.05). No statistically significant group differences were seen in time to fracture union (X-ray: 26.1 ± 3.2 weeks, CT: 25.7 ± 2.3 weeks), final radiological outcomes (displacement and angulation on AP and lateral views), or Johner-Wruhs scores (excellent and good rate: 82.4% for X-ray, 89.2% for CT; P > 0.05). No severe vascular or nerve injuries occurred in either group. Clinical trial number Not applicable. Conclusion Both X-ray and CT can successfully guide hexapod fixator correction for tibial fractures. CT measurement was associated with greater efficiency in the correction process, requiring fewer adjustments and less time to achieve reduction. However, this did not lead to differences in final radiographic or functional outcomes. The decision to use CT should therefore balance its potential for streamlining the early correction phase against considerations of cost, radiation exposure, and local resources. For many routine cases, X-ray-based measurement remains a robust and effective standard approach.

Emanuele Coccia, Martino Bernasconi, Andrea Celli

We study the problem of contextual online bilateral trade. At each round, the learner faces a seller-buyer pair and must propose a trade price without observing their private valuations for the item being sold. The goal of the learner is to post prices to facilitate trades between the two parties. Before posting a price, the learner observes a $d$-dimensional context vector that influences the agent's valuations. Prior work in the contextual setting has focused on linear models. In this work, we tackle a general nonparametric setting in which the buyer's and seller's valuations behave according to arbitrary Lipschitz functions of the context. We design an algorithm that leverages contextual information through a hierarchical tree construction and guarantees regret $\widetilde{O}(T^{{(d-1)}/d})$. Remarkably, our algorithm operates under two stringent features of the setting: (1) one-bit feedback, where the learner only observes whether a trade occurred or not, and (2) strong budget balance, where the learner cannot subsidize or profit from the market participants. We further provide a matching lower bound in the full-feedback setting, demonstrating the tightness of our regret bound.

A. Arize, J. Malindretos, E. U. Igwe

Danilo Enrique Morales Ruiz, Deb Raj Aryal, Gilberto Villanueva-López et al.

Background: Silvopastoral systems, agroforestry with grazing livestock, have a high capacity for carbon sequestration in tree biomass and enhance biological diversity in grasslands, contributing to counteract the negative effects of deforestation led by the expansion of open pasturelands. Objective: To assess tree structure, species diversity, and carbon storage in biomass components in three different silvopastoral systems (SPS): 1) scattered trees in pasture (STP), 2) live fences (LF), 3) forest plantations (FP), and compare them with pasture monoculture (PM). Methodology: Carbon stock in biomass, relative importance value of tree species, Shannon´s biodiversity, Pileou´s evenness, and Sorenson´s similarity indices were calculated in forty sampling plots, ten for each system in Tabasco, Mexico. Results: Biomass stock varied significantly (P<0.05) between SPS and PM. FP had the highest carbon stock in the biomass pool with an average of 73.5 MgCha-1, followed by STP (45.8), LF (20.8), and PM (9.1). STP system tended to be more diverse with a relatively even distribution of tree species, while tree density per hectare was greater in FP. Species composition and their relative value indices varied between SPS but there was a medium level of similarity between them. Furthermore, we determined an optimum basal area of 14.5 m2ha-1 to harmonize the trade-offs between carbon sequestration in woody biomass and forage production in grass (herbaceous) biomass in these SPS. Implications: These results are useful to farmers and policymakers in developing and incentivizing climate-smart livestock production systems in line with the Sustainable Development Goals (SDGs). Conclusion: SPS are biodiverse and accumulate more carbon in biomass than pasture monoculture. The STP was the most biodiverse, followed by LF and FP, while carbon storage was higher in FP followed by STP and LF. An optimal tree cover with 14.5 m2ha-1 basal area can balance the trade-off between carbon sequestration and forage productivity in SPS.

Victoria Pistikou, Anastasios Ketsetsidis, Soultana Anna Toumpalidou

This study aims to explore the relationship between macroeconomic factors and the decision to file an anti-dumping (AD) initiation, focusing on the post-WTO period from 1995 to 2022 for both reporting and targeted countries. We analyze the 20 most frequent users of the AD mechanism and the 20 most frequently targeted countries through econometric analysis to determine how gross domestic product (GDP) volume, GDP growth rate, and merchandise trade balance (MTB) influence the frequency of AD initiations. Our findings indicate that at least half of the sampled countries exhibit a significant correlation between AD filings and at least one of the macroeconomic variables examined. In many cases, GDP volume and MTB not only affect a country’s decision to initiate an AD investigation but also influence how often it becomes a target of such measures. Although the results are fragmented across different economies, they highlight the role of the macroeconomic environment in shaping the decision to resort to AD mechanisms. By adopting a dual perspective, considering both reporting and targeted countries, and incorporating MTB as a key variable, this research extends beyond previous studies to provide deeper insights into the macroeconomic determinants of AD measures. These findings suggest that macroeconomic conditions play a crucial role in shaping trade defense policies, highlighting the need for policymakers to consider broader economic trends when formulating AD regulations.

Han-Wen Chang, Hung-Che Lin, Ching-Ting Yang et al.

Adhesive interactions, mediated by specific molecular and structural mechanisms, are fundamental to host-pathogen and predator-prey relationships, driving evolutionary dynamics and ecological interactions. Here, we investigate the cellular and molecular basis of adhesion between the nematode Caenorhabditis elegans and its natural predator, the nematode-trapping fungus Arthrobotrys oligospora, which employs specialized adhesive nets to capture its prey. Using forward genetic screens, we identified C. elegans mutants that escape fungal traps and revealed the nuclear hormone receptor NHR-66 as a key regulator of fungal-nematode adhesion. Loss-of-function mutations in nhr-66 conferred resistance to fungal trapping through the downregulation of a large subset of cuticular collagen genes. Restoring collagen gene expression in nhr-66 mutants abolished the escape phenotype, highlighting the essential role of these structural proteins in fungal-nematode adhesion. Furthermore, sequence analysis of natural C. elegans populations revealed no obvious loss-of-function variants in nhr-66, suggesting selective pressures exist that balance adhesion-mediated predation risk with physiological robustness. We observed that loss of nhr-66 function resulted in a trade-off of increased hypersensitivity to hypoosmotic stress and cuticular fragility. These findings underscore the pivotal role of structural proteins in shaping ecological interactions and the evolutionary arms race between predator and prey.

Zhaobin Li, Waifan Tang, Shulun Mak et al.

Background: Leachate-induced clogging in landfill drainage systems significantly impairs operational efficiency while posing substantial environmental risks. The complex interactions among leachate components (e.g., organic matter, heavy metals, and inorganic salts), microbial communities, and inorganic precipitates lead to clogging that reduces hydraulic conductivity. Traditional control methods often fail to address these underlying processes, necessitating a deeper understanding of clogging mechanisms and effective mitigation strategies. Significance: This study provides an in-depth analysis combining a review of existing literature and experimental insights into the role of microbial communities in clogging formation and the effectiveness of aged refuse layers as a mitigation measure.To provide a comprehensive assessment, a life cycle assessment (LCA) framework is employed to analyze the environmental impacts of various clogging control methods.This study contributes to theoretical advancements by integrating a comprehensive review of LCA frameworks in the context of landfill management, addressing a gap in current literature. The integration also provides a nuanced analysis of the environmental trade-offs and their implications for sustainable landfill practices.By integrating LCA, this research offers a dual perspective that addresses both technical challenges and environmental trade-offs, contributing to more sustainable landfill management practices. Results: Laboratory experiments demonstrated that microbial activity significantly promoted calcium carbonate precipitation, leading to reduced hydraulic conductivity in landfill drainage systems. Partially saturated aged refuse layers reduced clogging potential by up to 40% by stabilizing leachate chemistry and inhibiting biofilm formation. However, life cycle assessment (LCA) results indicate that while aged refuse layers mitigate clogging, they also increase the global warming potential (GWP) by 10% compared to conventional methods, highlighting the need to balance technical efficacy with environmental sustainability. Conclusion: This study provides critical insights into microbial contributions to landfill leachate-induced clogging and emphasizes the importance of incorporating environmental considerations into landfill management. Although aged refuse layers are effective in reducing clogging, their environmental trade-offs should be carefully evaluated. Future research should explore alternative materials and configurations to optimize both clogging control and environmental performance, promoting more sustainable landfill drainage management strategies.

Saul Ngarava, Alois Aldridge Mugadza

The use of renewable energy is an important way to achieve sustainable agricultural and economic development. However, there are differences in access to renewable energy between the Global North and Global South. This study utilised an autoregressive distributed lag-error correction model and the data spanning from 1991 to 2021 to comparatively analyse the dynamic relationship among renewable energy consumption, the value of agricultural production, gross domestic product (GDP), economic diversification index, urban population, the total water extraction for agricultural withdrawal, and trade balance in the Netherlands and South Africa. In the short run, renewable energy consumption was increased by the value of agricultural production but decreased by GDP in South Africa. In the long run, renewable energy consumption and GDP increased the value of agricultural production, while the value of agricultural production also increased GDP in South Africa. However, in the Netherlands, there was no short- and long-run relationship between renewable energy consumption and agricultural and economic development. The results revealed that there was a short- and long-run relationship in South Africa. Moreover, in the Netherlands, the adjustment speed was –1.46 for renewable energy consumption with an error correction of 0.68 a (8.22 months). In South Africa, the adjustment speed was –1.28 for renewable energy consumption with an error correction of 0.78 a (9.38 months). Therefore, compared to South Africa, renewable energy consumption in the Netherlands takes less time to return to balance after a shock. These findings signify different trajectories on sectoral and economic transition initiatives spurred using renewable energy between the Netherlands and South Africa. Policy relating to initiatives such as “agro-energy communities” in Global South countries such as South Africa should be emphasised to promote the use of renewable energy in the agricultural sector.

Katya M. Papais, Daniil Lisus, David J. Yoon et al.

Most autonomous vehicles rely on accurate and efficient localization, which is achieved by comparing live sensor data to a preexisting map, to navigate their environment. Balancing the accuracy of localization with computational efficiency remains a significant challenge, as high-accuracy methods often come with higher computational costs. In this paper, we present two ways of improving lidar localization efficiency and study their impact on performance. First, we integrate a lightweight Doppler-based odometry method into a topometric localization pipeline and compare its performance against an iterative closest point (ICP)-based method. We highlight the trade-offs between these approaches: the Doppler estimator offers faster, lightweight updates, while ICP provides higher accuracy at the cost of increased computational load. Second, by controlling the frequency of localization updates and leveraging odometry estimates between them, we demonstrate that accurate localization can be maintained while optimizing for computational efficiency using either odometry method. Our experimental results show that localizing every 10 lidar frames strikes a favourable balance, achieving a localization accuracy below 0.05 meters in translation and below 0.1 degrees in orientation while reducing computational effort by over 30% in an ICP-based pipeline. We quantify the trade-off of accuracy to computational effort using over 100 kilometers of real-world driving data in different on-road environments.

Spyros Galanis

No trade theorems examine conditions under which agents cannot agree to disagree on the value of a security which pays according to some state of nature, thus preventing any mutual agreement to trade. A large literature has examined conditions which imply no trade, such as relaxing the common prior and common knowledge assumptions, as well as allowing for agents who are boundedly rational or ambiguity averse. We contribute to this literature by examining conditions on the private information of agents that reveals, or verifies, the true value of the security. We argue that these conditions can offer insights in three different settings: insider trading, the connection of low liquidity in markets with no trade, and trading using public blockchains and oracles.

Hanyu Li, Xiaotie Deng

Classic no-trade theorems attribute trade to heterogeneous beliefs. We re-examine this conclusion for AI agents, asking if trade can arise from computational limitations, under common beliefs. We model agents' bounded computational rationality within an unfolding game framework, where computational power determines the complexity of its strategy. Our central finding inverts the classic paradigm: a stable no-trade outcome (Nash equilibrium) is reached only when "almost rational" agents have slightly different computational power. Paradoxically, when agents possess identical power, they may fail to converge to equilibrium, resulting in persistent strategic adjustments that constitute a form of trade. This instability is exacerbated if agents can strategically under-utilize their computational resources, which eliminates any chance of equilibrium in Matching Pennies scenarios. Our results suggest that the inherent computational limitations of AI agents can lead to situations where equilibrium is not reached, creating a more lively and unpredictable trade environment than traditional models would predict.

Yongheng Hu

In this paper, we design two chapters to discuss trade dynamics with heterogeneous fluctuations, contributing new insights to macroeconomic issues related to international trade. In the first chapter, we model general exchange rate fluctuations through stochastic processes and analyze the impact of heterogeneous price shocks on export competitiveness. We find that monetary policy and innovation both show positive effects on export trade, while monetary policy stabilizes exchange rate fluctuations to comprehensively boost provincial export competitiveness, innovation reduces its reliance on exchange rate mechanisms. The optimal policy according to exchange rate fluctuations aims to solve the wealth distribution of exporters, and it suggests that optimal policy should promote dynamic transitions in trade patterns rather than maintain existing comparative advantages in heterogeneous trade structures. In the second chapter, we model labor market fluctuations and the ability to utilize production factors through stochastic processes, and we analyze the impact of heterogeneous aggregate production shocks on general international trade. We find that labor market fluctuations only benefit international trade under the cooperation policy. Moreover, for both sanction and cooperation policy scenarios, positive shocks (i.e., shocks where average wage growth in the labor market exceeds unemployment) strengthen their impact on import trade while weakening their impact on export trade, and vice versa. Regarding the theories proposed in these two chapters, we prove them through empirical analyses using the provincial data of China.

Ruiyu Zhou, Hengrui Chen, Hong Chen

Improving the spatial-temporal balance between the supply and demand of urban transportation and alleviating traffic congestion are important ways to build sustainable cities. The travel reservation strategy (TRS) is more flexible and refined than traditional traffic demand management methods. This study aims to determine the optimal reservation volume (ORV) for urban roads and verify the effectiveness of the TRS. First, we employed the sustained flow index to estimate the ORV from the degree of trade-off between the road breakdown probability and capacity. Then, a bilevel programming model based on ORV constraints was established to analyse the effectiveness of the TRS. The results indicated that the ORV range is 0.79–0.89 times the road capacity. The TRS can achieve the best steady benefit when the demand for reservation travel reaches at least 40%. Selecting the most congested critical roads in the network to implement TRS is more effective than on a large area. The driver default behavior will increase the V/C ratios and travel costs of all roads in the network. It has been proven that the reservation transportation mode will promote the spatial-temporal balance between supply and demand to alleviate traffic congestion.

Nick S. Fradgley, Keith A. Gardner, Matt Kerton et al.

Societal Impact Statement Increasing crop productivity is often proposed as a key goal for meeting the food security demands of a growing global population. However, achieving high crop yields alone without meeting end‐use quality requirements is counter to this objective and can lead to negative environmental and sustainability issues. High yielding feed wheat crops in the United Kingdom are a typical example of this. The historical context of UK agricultural industrialisation, developments in plant breeding and wheat end‐use processing are examined. We then outline how employing innovations in plant breeding methods offer the potential to redress the balance between wheat quantity and quality. Summary Bread wheat (Triticum aestivum L.) has historically been an important crop for many human civilisations. Today, variability in wheat supply and trade has a large influence on global economies and food security. The United Kingdom is an example of an industrialised country that achieves high wheat yields through intensive cropping systems and a favourable climate. However, only a minority of the wheat grain produced is of suitable end‐use quality for modern bread baking methods and most wheat produced is fed to livestock. A large agricultural land area and input use dedicated to producing grain for animal rather than human food has wide‐ranging negative impacts for environmental sustainability and domestic food production. Here we present an historical perspective of agricultural and economic changes that have resulted in UK production primarily focussing on wheat quantity over quality. Agricultural intensification, liberalisation of free trade in agricultural commodities, innovations in the milling and baking sector, developments in scientific understanding of genetics and plant breeding, and geopolitical changes have all played a role. We propose that wheat breeding plays a crucial role in influencing these issues and although wheat breeders in the United Kingdom have historically applied the most‐up‐to‐date scientific advances, recent advances in genomics tools and quantitative genetics present a unique opportunity for breeders to redress the balance between quantity and quality.

Xiaopeng Wang, Chengyi Tu, Shuhao Chen et al.

As the global population and the per capita demand for resource intensive diets continues to grow, the corresponding increase in food demand challenges the global food system, enhancing its reliance on trade. Most previous research typically constructed either unweighted networks or weighted solely by tonnage to represent food trade, and focused on bilateral trade relationships between pairs of countries. This study investigates the properties of global food trade constructed in terms of total food calories associated with all the main food products exchanged along each trade link (edge of the food trade network). Utilizing data from the Food and Agriculture Organization between 1986 and 2022, we construct a directed, weighted network of net caloric flows between countries. This approach highlights the importance of considering nutritional value in discussions of food security and trade policies, offering a more holistic view of global food trade dynamics. Our analysis reveals significant heterogeneity in trade patterns, with certain countries emerging as major exporters or importers of food calories. Moreover, we employ network measures, including network connectivity, network heterogeneity, network modularity, and node correlation similarity, to elucidate the structural dynamics of global net food calorie trade networks that are relevant to the stability and resilience of the global food system. Our work provides a more nuanced understanding of global food trade dynamics, emphasizing the need for comprehensive strategies to enhance the resilience and sustainability of food trade networks.

Solenne Gaucher, Martino Bernasconi, Matteo Castiglioni et al.

Bilateral trade models the problem of facilitating trades between a seller and a buyer having private valuations for the item being sold. In the online version of the problem, the learner faces a new seller and buyer at each time step, and has to post a price for each of the two parties without any knowledge of their valuations. We consider a scenario where, at each time step, before posting prices the learner observes a context vector containing information about the features of the item for sale. The valuations of both the seller and the buyer follow an unknown linear function of the context. In this setting, the learner could leverage previous transactions in an attempt to estimate private valuations. We characterize the regret regimes of different settings, taking as a baseline the best context-dependent prices in hindsight. First, in the setting in which the learner has two-bit feedback and strong budget balance constraints, we propose an algorithm with $O(\log T)$ regret. Then, we study the same set-up with noisy valuations, providing a tight $\widetilde O(T^{\frac23})$ regret upper bound. Finally, we show that loosening budget balance constraints allows the learner to operate under more restrictive feedback. Specifically, we show how to address the one-bit, global budget balance setting through a reduction from the two-bit, strong budget balance setup. This established a fundamental trade-off between the quality of the feedback and the strictness of the budget constraints.

François Bachoc, Nicolò Cesa-Bianchi, Tommaso Cesari et al.

In online bilateral trade, a platform posts prices to incoming pairs of buyers and sellers that have private valuations for a certain good. If the price is lower than the buyers' valuation and higher than the sellers' valuation, then a trade takes place. Previous work focused on the platform perspective, with the goal of setting prices maximizing the gain from trade (the sum of sellers' and buyers' utilities). Gain from trade is, however, potentially unfair to traders, as they may receive highly uneven shares of the total utility. In this work we enforce fairness by rewarding the platform with the fair gain from trade, defined as the minimum between sellers' and buyers' utilities. After showing that any no-regret learning algorithm designed to maximize the sum of the utilities may fail badly with fair gain from trade, we present our main contribution: a complete characterization of the regret regimes for fair gain from trade when, after each interaction, the platform only learns whether each trader accepted the current price. Specifically, we prove the following regret bounds: $Θ(\ln T)$ in the deterministic setting, $Ω(T)$ in the stochastic setting, and $\tildeΘ(T^{2/3})$ in the stochastic setting when sellers' and buyers' valuations are independent of each other. We conclude by providing tight regret bounds when, after each interaction, the platform is allowed to observe the true traders' valuations.

Viktor Stojkoski, Philipp Koch, Eva Coll et al.

Despite global efforts to harmonize international trade statistics, our understanding of digital trade and its implications remains limited. Here, we introduce a method to estimate bilateral exports and imports for dozens of sectors starting from the corporate revenue data of large digital firms. This method allows us to provide estimates for digitally ordered and delivered trade involving digital goods (e.g. video games), productized services (e.g. digital advertising), and digital intermediation fees (e.g. hotel rental), which together we call digital products. We use these estimates to study five key aspects of digital trade. We find that, compared to trade in physical goods, digital product exports are more spatially concentrated, have been growing faster, and can offset trade balance estimates, like the United States trade deficit on physical goods. We also find that countries that have decoupled economic growth from greenhouse gas emissions tend to have larger digital exports and that digital products exports contribute positively to the complexity of economies. This method, dataset, and findings provide a new lens to understand the impact of international trade in digital products.

Mikrajuddin Abdullah

I propose a new terminology, international trade strength, which is defined as the ratio of a country's total international trade to its GDP. This parameter represents a country's ability to generate international trade by utilizing its GDP. This figure is equivalent to GDP per capita, which represents a country's ability to use its population to generate GDP. Trade strength varies by country. The intriguing question is, what distribution function does the trade strength fulfill? In this paper, a theoretical foundation for predicting the distribution of trade strength and the rate of change of trade strength were developed. These two quantities were found to satisfy the Pareto distribution function. The equations were confirmed using data from the World Integrated Trade Solution (WITS) and the World Bank by comparing the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) to five types of distribution functions (exponential, lognormal, gamma, Pareto, and Weibull). I also discovered that the fitting Pareto power parameter is fairly close to the theoretical parameter. In addition, a formula for forecasting a country's total international trade in the following years was also developed.

Ioannis N. Kallianiotis

Abstract The objective of this paper is to test empirically the effect of a devaluation of a currency on the trade account of the country, the J-curve effect, by using the trade between the U.S. and six countries (Euro-zone, Canada, United Kingdom, Switzerland, Japan, and Australia). A devaluation (depreciation) of the U.S. dollar is increasing the spot exchange rate ($/FC) and increases the price of imports and reduces the price of exports. Then, imports are falling and exports are increasing and the trade account is improved in the long-run. In the short-run, the trade account is deteriorated because imports are pre-arranged and continue to increase with the higher spot rate. This J-curve hypothesis is tested by using a regression and a VAR model, where the volatility of the real exchange rate (TOT) is specified with a GARCH-M process. The empirical results mostly are supporting the J-curve effect. JEL classification numbers: E4, F31, F32, F47, G14, G15. Keywords: Demand for Money and Exchange Rate, Foreign Exchange, Current Account Adjustment, Forecasting and Simulation, Information and Market Efficiency, International Financial Markets.