Hasil untuk "Balance of trade"

Tuychiyev Ikhtiyor, Rashidov Karim, Nurillaev Laziz et al.

Polyethylene (PE) is susceptible to photo-oxidative degradation under ultraviolet (UV) irradiation, exhibits limited thermal/oxidative stability, and faces stiffness-toughness trade-offs. This work examines TiO₂ and ZnO nanoparticles-employed as bare and surface-modified fillers with a PE-g-MA compatibilizer-to optimize the UV resistance, thermal stability, and mechanical performance of PE composites. Composites were produced by melt compounding and solution casting. Accelerated UV weathering was performed, and specimens were characterized by FTIR carbonyl index, UV-Vis, TGA/DSC/DMA, and SEM/TEM; differences were evaluated using ANOVA. Coated TiO2⁄ZnO at 1 − 3 wt% delivered the best balance, increasing oxidative-induction time, raising TGA onset temperature, and elevating crystallinity and storage modulus while preserving tensile strength after aging. Surface modification suppressed photocatalytic discoloration and embrittlement, whereas compatibilization improved interfacial stress transfer. The improvements arise from UV attenuation, heterogeneous nucleation, and strengthened polymer-filler interfaces. The findings demonstrate applicability to industrial packaging and outdoor parts; limitations include agglomeration and viscosity growth at higher loadings.

Togo Yamada, Pamella Apriliana, Prihardi Kahar et al.

3-Amino-4-hydroxybenzoic acid (3,4-AHBA) is a non-proteinogenic aromatic compound that functions as a key biosynthetic precursor for diverse secondary metabolites with pharmaceutical and industrial value. Microbial production of 3,4-AHBA offers a sustainable alternative to petroleum-based chemical synthesis; however, metabolic complexity and trade-offs between growth and product formation constrain rational strain design. Here, genome-scale metabolic (GSM) modeling and flux balance analysis (FBA) were integrated with targeted genetic engineering to elucidate and enhance 3,4-AHBA production in <i>Streptomyces thermoviolaceus</i>. A genome-scale metabolic model was constructed and expanded by incorporating the <i>nspH–nspI</i> gene operon, which encodes the 3,4-AHBA biosynthetic pathway. In silico FBA predicted substantial rewiring of central carbon metabolism, with carbon flux redirected from glycolysis and the tricarboxylic acid cycle toward aspartate-derived intermediates and 3,4-AHBA synthesis, accompanied by reduced biomass-associated flux. Guided by these predictions, an engineered strain (<i>St::NspHI</i>) was developed and experimentally evaluated. Consistent with model predictions, the engineered strain exhibited lower growth rates and glucose uptake than the wild type, reflecting a metabolic burden. Nevertheless, 3,4-AHBA production was achieved exclusively in the engineered strain. Comparison of simulated and experimental fluxes revealed overestimation by FBA, likely due to secondary metabolism and incomplete genome annotation. Overall, GSM-guided design enables optimization of precursor production.

Anna Lunghi, Mattia Piccinato, Matteo Castiglioni et al.

We study online bilateral trade, where a learner facilitates repeated exchanges between a buyer and a seller to maximize the Gain From Trade (GFT), i.e., the social welfare. In doing so, the learner must guarantee not to subsidize the market. This constraint is usually imposed per round through Weak Budget Balance (WBB). Despite that, Bernasconi et al. [2024] show that a Global Budget Balance (GBB) constraint on the profit -- enforced over the entire time horizon -- can improve the GFT by a multiplicative factor of two. While this might appear to be a marginal relaxation, this implies that all existing WBB-focused algorithms suffer linear regret when measured against the GBB optimum. In this work, we provide the first algorithm to achieve sublinear regret against the GBB benchmark in stochastic environments under one-bit feedback. In particular, we show that when the joint distribution of valuations has a bounded density, our algorithm achieves $\widetilde{\mathcal{O}}(T^{3/4})$ regret. Our result shows that there is no separation between the one-dimensional problem of learning the optimal WBB price and the two-dimensional problem of learning the optimal GBB distribution over pairs of prices.

Moshe Babaioff, Aviad Rubinstein, Xizhi Tan et al.

A central challenge in mechanism design is to develop truthful trade mechanisms that maximize the expected gains-from-trade (GFT) in two-sided markets with strategic agents. As achieving the full GFT is generally impossible, much of the literature has focused on constant-factor approximations. Existing results, however, are limited to the highly structured settings of bilateral trade and double auctions, in which every buyer can trade with every seller. We consider the significantly more general setting of two-sided matching markets with arbitrary downward-closed constraints on the family of allowed matchings. For this setting, we present a simple randomized truthful mechanism that guarantees a constant-factor approximation to the optimal expected GFT. This result also resolves an open problem posed by Cai, Goldner, Ma, and Zhao (2021).

Godwin Olasehinde-Williams, Cihat Köksal

This paper explores the impact of geoeconomic fragmentation on the energy transition in the Global North, a region historically responsible for high greenhouse gas emissions yet crucial in addressing climate change. Recent policy shifts away from economic integration have raised concerns about the risks of geoeconomic fragmentation in climate policy discussions. Using panel quantile methods, the study analyzes how trade restrictions and other factors influence renewable energy consumption across 23 Global North countries from 1990 to 2020. The results show a dual effect: at lower to middle levels of renewable energy consumption, geoeconomic fragmentation positively influences energy transition. However, at higher levels, its impact turns negative, emphasizing the importance of economic integration and reduced trade barriers. These findings suggest that policies should be tailored to specific national conditions to balance geoeconomic shifts with sustainable energy goals. Ultimately, this research highlights the complex relationship between economic fragmentation and energy transition.

Yakai Wang, Yawen Huang, Wei Ren

Abstract Fertilizer use enhances crop yields but exacerbates nitrate leaching, threatening water quality in farming systems. This study optimizes nitrogen fertilization strategies by integrating numerical modeling and machine learning to balance corn yield and nitrate leaching in the US Midwest, 1979–2100. We evaluate the economic optimum nitrogen rate under climate‐smart agricultural practices like no‐tillage and cover crops. Findings show that the economic optimum nitrogen rate sustains yields but increases nitrate leaching, especially under future scenarios. In contrast, optimized strategies—such as a lower rate (−30%) than the economic optimum nitrogen rate combined with cover crops and no‐tillage—could reduce yield‐scaled nitrate leaching by over 60% from 2020 to 2100. The study underscores the synergistic benefits of integrated management in mitigating trade‐offs between productivity and environmental impacts. Further predictions offer adaptive strategies for achieving sustainable, high yields while minimizing nitrate leaching under various climate scenarios.

Asif Hameed, Guozhu Mao, Adnan Ahmed Sheikh et al.

The Paris Agreement mandated high-greenhouse-emitting countries implement carbon pricing to accelerate emission reduction to cope with environmental challenges posed by climate change. We emphasized a research analysis of the reciprocal feedback mechanism between micro- and macro-economic systems in response to the carbon tax in the economy, facilitating the adoption of renewable technology for social welfare. This research utilized a bi-model comprising the dynamic computable general equilibrium model and energy system optimization model for analysis. Results revealed empirical and positive evidence of carbon tax efficacy of three times emission reduction related to a less than one-time economic contraction, while significant environmental benefits positively influenced the individual welfare and technological advancement in Tianjin, China. The conclusion offers concrete long-term benefits of cleaner energy adoption, public health, and environmental sustainability to align with the Paris Agreement goals. The study suggests that policymakers implement a gradual carbon tax to maintain economic growth and fund carbon tax revenue to renewable energy technology, industrial efficiency upgradation, and social welfare programs to balance economic trade-offs.

Charlotte Sarsaba, Izon Garret Diano, Jamaica Daro et al.

Background: Trade contributes to a nation's economic development, and the exchange rate indicates a country's trade competitiveness. This study investigates the potential for a bidirectional causal relationship between exchange rate volatility and trade balance in the Philippines. Methods: The study uses the Granger Causality Test to determine and ascertain whether there is a two-way causative relationship between exchange rate volatility and the balance of trade in the Philippines using the time series analysis considering the period from 1990–2023. Results: The findings indicate that the balance of trade can influence and be a factor in the change and movement of exchange rate volatility due to factors such as the export-import of the country that reflects the demand and supply of currency, indicating that shifts in the trade balance can contribute to fluctuations in exchange rates. Exchange rate changes may be necessary to restore equilibrium in trade flows in response to shifts in the balance of trade, including improvements or deteriorations. Conclusion: The study, therefore, recommends utilizing trade-related tactics to improve the trade balance by enhancing exports while cutting down unproductive and unprocessed imports, attracting more foreign investments and more exportation for exchange rate stability.

D. Leitner, A. Schnepf, J. Vanderborght

<p>Root water uptake strongly affects soil water balance and plant development. It can be described by mechanistic models of soil–root hydraulics based on soil water content, soil and root hydraulic properties, and the dynamic development of the root architecture. Recently, novel upscaling methods have emerged, which enable the application of detailed mechanistic models on a larger scale, particularly for land surface and crop models, by using mathematical upscaling.</p> <p>In this study, we explore the underlying assumptions and the mathematical fundamentals of different upscaling approaches. Our analysis rigorously investigates the errors introduced in each step during the transition from fine-scale mechanistic models, which considers the nonlinear perirhizal resistance around each root, to more macroscopic representations. Upscaling steps simplify the representation of the root architecture, the perirhizal geometry, and the soil spatial dimension and thus introduces errors compared to the full complex 3D simulations. In order to investigate the extent of these errors, we perform simulation case studies, spring barley as a representative non-row crop and maize as a representative row crop, using three different soils.</p> <p>We show that the error introduced by the upscaling steps strongly differs, depending on root architecture and soil type. Furthermore, we identify the individual steps and assumptions that lead to the most important losses in accuracy. An analysis of the trade-off between model complexity and accuracy provides valuable guidance for selecting the most suitable approach for specific applications.</p>

Gaetan de Rassenfosse

Intellectual property (IP) rules have the potential to shape cross-border trade far more than their legalistic origins might suggest. Drawing on three decades of evidence, this review shows that stronger IP rights simultaneously create market-power forces that raise prices and market-expansion forces that broaden demand, while dynamic incentives spur quality upgrading and new export varieties. Micro-data and quasi-natural experiments after TRIPS reveal that IP most often boosts trade along the extensive margin and redirects some activity toward licensing and foreign investment. Policy bundling and measurement gaps on the strength of IP rights still cloud causal inference. Future work must map intangible flows and enforcement quality to capture the digital, data-driven frontier of international commerce.

Yan Li, Carol Alexander, Michael Coulon et al.

This study investigates the inherently random structures of dry bulk shipping networks, often likened to a taxi service, and identifies the underlying trade dynamics that contribute to this randomness within individual cargo sub-networks. By analysing micro-level trade flow data from 2015 to 2023, we explore the evolution of dry commodity networks, including grain, coal, and iron ore, and suggest that the Giant Strongly Connected Components exhibit small-world phenomena, indicative of efficient bilateral trade. The significant heterogeneity of in-degree and out-degree within these sub-networks, primarily driven by importing ports, underscores the complexity of their dynamics. Our temporal analysis shows that while the Covid-19 pandemic profoundly impacted the coal network, the Ukraine conflict significantly altered the grain network, resulting in changes in community structures. Notably, grain sub-networks display periodic changes, suggesting distinct life cycles absent in coal and iron ore networks. These findings illustrate that the randomness in dry bulk shipping networks is a reflection of real-world trade dynamics, providing valuable insights for stakeholders in navigating and predicting network behaviours.

Élodie Brun, Ana Covarrubias

Abstract The article addresses the question of autonomy in Mexico’s and Brazil’s foreign policies in the context of increasing tensions between the United States and China. Although Mexico’s and Brazil’s relations with China —and to a lesser extent the United States— are very different in nature, both Latin American countries face the same challenge of finding a balance in relations with both great powers. The article analyzes Mexico’s and Brazil’s handling of a “triangular relationship” since 2018, illustrating the scope and limits of each country’s autonomy. In the case of Mexico, economic integration with the United States explains the place of China as both an opportunity and a threat; in the case of Brazil, although China is its major trade partner, domestic interests become as important as structural elements, and its government cannot disregard US concerns. In addition to the review of secondary literature, the article uses a series of interviews of Mexican and Brazilian diplomats.

Tianyi Shi, Ruixiao Wu, Chuantian Zhou et al.

At the current stage of autonomous driving, monitoring the behavior of safety stewards (drivers) is crucial to establishing liability in the event of an accident. However, there is currently no method for the quantitative assessment of safety steward behavior that is trusted by multiple stakeholders. In recent years, deep-learning-based methods can automatically detect abnormal behaviors with surveillance video, and blockchain as a decentralized and tamper-resistant distributed ledger technology is very suitable as a tool for providing evidence when determining liability. In this paper, a trusted supervision paradigm for autonomous driving (TSPAD) based on multimodal data authentication is proposed. Specifically, this paradigm consists of a deep learning model for driving abnormal behavior detection based on key frames adaptive selection and a blockchain system for multimodal data on-chaining and certificate storage. First, the deep-learning-based detection model enables the quantification of abnormal driving behavior and the selection of key frames. Second, the key frame selection and image compression coding balance the trade-off between the amount of information and efficiency in multiparty data sharing. Third, the blockchain-based data encryption sharing strategy ensures supervision and mutual trust among the regulatory authority, the logistic platform, and the enterprise in the driving process.

Florian Rupp, Alessandro Puddu, Christian Becker-Asano et al.

Achieving optimal balance in games is essential to their success, yet reliant on extensive manual work and playtesting. To facilitate this process, the Procedural Content Generation via Reinforcement Learning (PCGRL) framework has recently been effectively used to improve the balance of existing game levels. This approach, however, only assesses balance heuristically, neglecting actual human perception. For this reason, this work presents a survey to empirically evaluate the created content paired with human playtesting. Participants in four different scenarios are asked about their perception of changes made to the level both before and after balancing, and vice versa. Based on descriptive and statistical analysis, our findings indicate that the PCGRL-based balancing positively influences players' perceived balance for most scenarios, albeit with differences in aspects of the balancing between scenarios.

Sorin IONITESCU

The purpose of the study was to analyze the main indicators carried out in agriculture for assessing the contribution of agriculture to the economic development in Romania in the period 2013-2022 based on the data provided by National Institute of Statistics. The data were processed using fixed and structural indices, regression equations, determination coefficient, graphical illustrations and comparisons. The results highlighted that in the studied period, Romania's Gross Domestic Product (GDP) increased 2.21 times reaching Lei 1,409 Billion in 2022. Agriculture produced Lei 63.04 Billion GDP in 2022, and its contribution to Romania's GDP is 4.5%. Gross Value Added (GVA) increased 2.28 times in the economy accounting for Lei 1,282.3 Billion in 2022. Despite that GVA raised by 118.6% in agriculture, accounting for Lei 58.98 Billion in 2022, agriculture's contribution was only 4.6%. Gross Fixed Capital Formation (GFCF) raised in the economy by +131.55% accounting for Lei 377,2 Billion in 2022, but in agriculture it was very small, only Lei 2.65 Billion. Net Investment Rate (NIR) was 27.4% in 2022, but in agriculture only 4.5%. A decline by 8.7% in the number of employees was noticed in the economy, employment reaching 7,806 thousand persons in 2022, but in agriculture the reduction was 65.7% remaining only 878 thousand employees. Despite that both export and import value increased, the trade balance was a negative one, the deficit at the end of 2022 being EUR -34,101 Million. The agro-food export value raised by +126.32% and reached EUR 11,960 Million in 2022, which means that agriculture contributes by about 13% to Romania's exports, while the contribution to imports raised by +167.54%, accounting for EUR 13,248.6 Million. The deficit in the agro-food trade balance accounted for EUR -1,288.6 Million, Romania being a net importing country. Despite of its increased contribution to GDP and GVA, agriculture is facing a gap versus industry and services in GFCF and NIR. Without a better technical endowment and higher investment, agriculture cannot apply modern technologies to increase production and sustain internal market and export and to diminish imports.

Yingnan Cong, Yufei Hou, Jiaming Jiang et al.

As an integral part of economic trade, energy trade is crucial to international dynamics and national interests. In this study, an international energy trade network is constructed by abstracting countries as nodes and representing energy trade relations as edges. A variety of indicators are designed in terms of networks, nodes, bilaterals, and communities to analyze the temporal and spatial evolution of the global energy trade network from 2001 to 2020. The results indicate that network density and strength have been steadily increasing since the beginning of the 21st century. It is observed that the position of the United States as the core of the international energy market is being impacted by emerging developing countries, thus affecting the existing trade balance based on topological analysis. The weighted analysis of bilateral relations demonstrates that emerging countries such as China, Brazil, and Saudi Arabia are pursuing closer cooperation. The community analysis reveals that an increasing number of countries possess strong energy trade capabilities, resulting in a corresponding increase in energy trade volumes.

D. L. Arévalo-Martínez, D. L. Arévalo-Martínez, D. L. Arévalo-Martínez et al.

<p>For millennia, humans have gravitated towards coastlines for their resource potential and as geopolitical centres for global trade. A basic requirement ensuring water security for coastal communities relies on a delicate balance between the supply and demand of potable water. The interaction between freshwater and saltwater in coastal settings is, therefore, complicated by both natural and human-driven environmental changes at the land–sea interface. In particular, ongoing sea-level rise, warming and deoxygenation might exacerbate such perturbations. In this context, an improved understanding of the nature and variability of groundwater fluxes across the land–sea continuum is timely yet remains out of reach. The flow of terrestrial groundwater across the coastal transition zone and the extent of freshened groundwater below the present-day seafloor are receiving increased attention in marine and coastal sciences because they likely represent a significant yet highly uncertain component of (bio)geochemical budgets and because of<span id="page648"/> the emerging interest in the potential use of offshore freshened groundwater as a resource. At the same time, “reverse” groundwater flux from offshore to onshore is of prevalent socio-economic interest, as terrestrial groundwater resources are continuously pressured by over-pumping and seawater intrusion in many coastal regions worldwide. An accurate assessment of the land–ocean connectivity through groundwater and its potential responses to future anthropogenic activities and climate change will require a multidisciplinary approach combining the expertise of geophysicists, hydrogeologists, (bio)geochemists and modellers. Such joint activities will lay the scientific basis for better understanding the role of groundwater in societally relevant issues such as climate change, pollution and the environmental status of the coastal oceans within the framework of the United Nations Sustainable Development Goals. Here, we present our perspectives on future research directions to better understand land–ocean connectivity through groundwater, including the spatial distributions of the essential hydrogeological parameters, highlighting technical and scientific developments and briefly discussing the societal relevance of that connectivity in rapidly changing coastal oceans.</p>

Kosuke Tatsumura, Ryo Hidaka, Jun Nakayama et al.

Financial portfolio construction problems are often formulated as quadratic and discrete (combinatorial) optimization that belong to the nondeterministic polynomial time (NP)-hard class in computational complexity theory. Ising machines are hardware devices that work in quantum-mechanical/quantum-inspired principles for quickly solving NP-hard optimization problems, which potentially enable making trading decisions based on NP-hard optimization in the time constraints for high-speed trading strategies. Here we report a real-time stock trading system that determines long(buying)/short(selling) positions through NP-hard portfolio optimization for improving the Sharpe ratio using an embedded Ising machine based on a quantum-inspired algorithm called simulated bifurcation. The Ising machine selects a balanced (delta-neutral) group of stocks from an $N$-stock universe according to an objective function involving maximizing instantaneous expected returns defined as deviations from volume-weighted average prices and minimizing the summation of statistical correlation factors (for diversification). It has been demonstrated in the Tokyo Stock Exchange that the trading strategy based on NP-hard portfolio optimization for $N$=128 is executable with the FPGA (field-programmable gate array)-based trading system with a response latency of 164 $μ$s.

Tongyang Xu, Fan Liu, Christos Masouros et al.

The integration of sensing and communication (ISAC) functionalities have recently gained significant research interest as a hardware-, power-, spectrum- and cost- efficient solution. This experimental work implements a dual-functional sensing and communication framework where a single radiation waveform, either omnidirectional or directional, can realize both sensing and communication functions. We design an orthogonal frequency division multiplexing (OFDM) based multi-user multiple input multiple output (MIMO) software-defined radio (SDR) testbed to validate the dual-functional model. We carry out over-the-air experiments to investigate the optimal trade-off factor to balance the performance for both functions. On the communication side, we obtain bit error rate (BER) results from the testbed to show the communication performance using the dual-functional waveform. On the sensing performance, we measure the output beampatterns of our transmission to examine their similarity to simulation based beampatterns. We also implement a sensing experiment to realize activity detection functions. Our experiment reveals that the dual-functional approach can achieve comparable BER performance with pure communication-based solutions while achieving fine sensing beampatterns and realistic sensing functionality simultaneously.

Sean A. P. Clouston, Minos Kritikos, Chuan Huang et al.

Abstract Prior research has demonstrated high levels of cognitive and physical functional impairments in World Trade Center (WTC) responders. A follow-up neuroimaging study identified changes to white matter connectivity within the cerebellum in responders with cognitive impairment (CI). In the first study to examine cerebellar cortical thickness in WTC responders with CI, we fielded a structural magnetic resonance imaging protocol. WTC responders (N = 99) participated in a structural magnetic resonance imaging (MRI) study, of whom 48 had CI. Participants with CI did not differ demographically or by intracranial volume when compared to cognitively unimpaired participants. MRIs were processed using the CERES imaging pipeline; bilateral cortical thickness in 12 cerebellar lobules was reported. Analyses were completed comparing mean cerebellar cortical thickness across groups. Lobules were examined to determine the location and functional correlates of reduced cerebellar cortical thickness. Multivariable-adjusted analyses accounted for the false discovery rate. Mean cerebellar cortical thickness was reduced by 0.17 mm in responders with CI. Decrements in cerebellar cortical thickness were symmetric and located in the Cerebellar Crus (I and II), and in Lobules IV, VI, VIIb, VIIIa, VIIIb, and IX. Cerebellar cortical thickness was associated with episodic memory, response speed, and tandem balance. WTC responders with CI had evidence of reduced cerebellar cortical thickness that was present across lobules in a pattern unique to this cohort.