Hasil untuk "Balance of trade"

Xunbo Hou, Linan Yin, RuiBao Liu et al.

BackgroundThe optimal treatment strategy for advanced hepatocellular carcinoma (HCC) with portal vein tumor thrombosis (PVTT) remains undefined. Although combinations of locoregional therapies—such as transarterial chemoembolization (TACE) and hepatic arterial infusion chemotherapy (HAIC)—with systemic agents (tyrosine kinase inhibitors [TKIs] and PD-1 inhibitors) show promise, direct comparative evidence among different regimens remains limited.MethodsIn this single-center retrospective study, we included 347 patients with unresectable HCC and PVTT treated between January 2020 and December 2022. Patients were categorized into four groups based on initial therapy: TACE-HAIC-TP (n = 79), TACE-TP (n = 90), HAIC-TP (n = 98), and TACE alone (n = 80). The primary endpoints were overall survival (OS) and progression-free survival (PFS).ResultsAll combination regimens significantly improved OS and PFS compared with TACE alone (median OS: 11.4 months; median PFS: 5.8 months; all p < 0.001). The TACE-HAIC-TP group had the longest median OS (21.0 months) and PFS (15.3 months). However, after propensity score matching, no significant difference in survival outcomes was observed between the TACE-HAIC-TP and HAIC-TP groups. The HAIC-TP and TACE-TP regimens demonstrated comparable efficacy. Regarding safety, TACE-HAIC-TP was associated with the highest incidence of adverse events, including appetite loss, fatigue, nausea/vomiting, bleeding, and immune-related pneumonia. HAIC-TP carried a higher risk of gastrointestinal reactions and bleeding, whereas hand-foot syndrome was more frequent with TACE-TP.ConclusionIn patients with unresectable HCC and PVTT, combining TKIs and PD-1 inhibitors with locoregional therapy (TACE or HAIC) confers superior survival benefits over TACE monotherapy. The HAIC-TP regimen was associated with a more favorable balance of efficacy and tolerability compared with the more intensive TACE-HAIC-TP strategy, suggesting it may represent a promising therapeutic option pending prospective validation. Treatment selection should be individualized based on efficacy–safety trade-offs.

Mariia Voronenko

Background. Modern intelligent systems require efficient mechanisms for analysis, prediction, and decision-making. Bayesian networks allow for the efficient representation of causal relationships between variables. The quality and reliability of the constructed network directly correlate with the effectiveness of the final intelligent system. Materials and Methods. Structural training of a Bayesian network involves determining the structure of a directed acyclic graph in which variables are related to each other. The quality of the structure has a decisive impact on the ability of the model to accurately represent conditional probabilities and on the efficiency of the training algorithms and the reliability of the model. The main problem limiting the structural learning of Bayesian networks is the computational complexity of the model. This fundamental complexity means that for multidimensional problems, it is impossible to perform a complete search of all possible structures and find a global optimum. This forces reliance on heuristic search methods and approximation algorithms and creates a constant need to balance the quality of structure determination and computational resources. Results and Discussion. The formalized concept of adaptive selection of algorithms for structural learning is based on a systematic analysis of algorithm characteristics and data properties, which allows you to choose the most suitable algorithm for a particular case, optimize the trade-off between model quality and computational resources, and increase the generalizability of the model in practical scenarios. Conclusion. The proposed concept of adaptive selection of algorithms for structural learning is a timely contribution to the field of stochastic dependence modeling. It successfully translates the process of selecting the optimal algorithm from a routine, heuristic, brute force method to a systematic, multivariate analysis. Its full implementation has the potential to significantly increase the reliability, accuracy, and computational efficiency of building Bayesian models in complex analytical domains.

Zhigao Huang, Musheng Chen, Shiyan Zheng

Rotary Positional Embedding (RoPE) is a widely used technique in Transformers, influenced by the hyperparameter theta (θ). However, the impact of varying *fixed* theta values, especially the trade-off between performance and efficiency on tasks like character-level modeling, remains under-explored. This paper presents a systematic evaluation of RoPE with fixed theta values (ranging from 500 to 50,000) on a character-level GPT model across three datasets: Tiny Shakespeare, Enwik8, and Text8, compared against the standard θ = 10, 000 baseline. However, all non-default theta configurations incur significant computational overhead: inference speed is approximately halved across all datasets, suggesting implementation—specific bottlenecks rather than theta—dependent costs. This study quantifies a critical performance—efficiency trade-off when tuning fixed RoPE theta. Our findings emphasize the practical need to balance generalization gains with computational budgets during model development and deployment, contributing empirical insights into RoPE hyperparameter sensitivity and demonstrating that optimal theta selection is highly dataset-dependent. These insights suggest that future positional encoding designs could benefit from adaptive θ scheduling or dataset-specific θ optimization strategies to maximize both performance and computational efficiency.

C. R. Sharpe, G. D. Ruxton

ABSTRACT Ballistic seed dispersal (ballochory) involves the autonomous explosive release of seeds from adult plants. The unconventional mechanics of this strategy have understandably drawn considerable scientific attention. The explosive release of seeds is achieved by a variety of physical mechanisms but broadly involves the rapid coiling or shattering of seed pods to transfer kinetic energy to seeds, facilitated largely by either the evaporation or absorption of water in seed pod tissues. There has been a bias toward researching physiological and physical aspects of ballistic plants, with the evolutionary ecology being comparatively neglected. Although ballochory is represented in 23 plant families, it has never become common. This fact should invite curiosity regarding the selective pressures that encourage its evolution. Previous research has been unable to correlate ballochory with plant traits such as morphology, generation time or habitat preferences, and so we take an alternative approach in considering the evolutionary advantages that can provide insight on the shared set of circumstances that favour the evolution of this strategy. We review the known selective advantages that ballistic dispersal can confer to plants and promote a hypothesis that ballochory may be particularly selected for in instances of concentrated predation pressure on parental canopies. For plants in static and patchy landscapes, such a strategy could balance a trade‐off between escaping concentrated natural enemies while maximising the probability of transport to suitable habitat. We account for its rarity by considering the major opportunity cost that may only be justified when other seed dispersal mechanisms are limited. Moving forward, we suggest experimental manipulations to test this hypothesis and promote a research agenda in the field of ballistic seed dispersal that illuminates its intriguing evolution.

Qiong Zhao, Chen Pan, Zengkai Zhang et al.

Abstract Inter-regional input-output (IRIO) tables are essential for socioeconomic and environmental analysis. This paper compiled a continuous time series of Chinese IRIO tables with a detailed regional and sectoral classification, covering a longer period from 1987 to 2017 than existing Chinese IRIO tables. Additionally, we integrated the China provincial CO2 emission inventory data (1987–2017) to analyze trends and identify the main driving factors behind regional economic linkages and carbon emissions changes. Specifically, we adjusted the initial values of the international and interprovincial imports and exports using customs data. Subsequently, we employed the minimum cross-entropy model to balance the adjusted input-output tables (IOTs) from both row and column perspectives. Following this, we estimated the interprovincial trade flow for each sector using the gravity model. Then, we balanced these estimates with the minimum cross-entropy model to form the multi-regional input-output (MRIO) table. Finally, we constructed the IRIO table based on the proportion assumption. The compiled IRIO tables, integrated with carbon emission data, have significant applications in regional economic analysis, policy evaluation, and environmental studies.

Fabian Obster, Monica I. Ciolacu, Andreas Humpe

This paper investigates the empirical relationship between predictive performance, often called predictive power, and interpretability of various Machine Learning algorithms, focusing on bicycle traffic data from four cities. As Machine Learning algorithms become increasingly embedded in decision-making processes, particularly for traffic management and other high-level commitment applications, concerns regarding the transparency and trustworthiness of complex ‘black-box’ models have grown. Theoretical assertions often propose a trade-off between model complexity (predictive performance) and transparency (interpretability); however, empirical evidence supporting this claim is limited and inconsistent. To address this gap, we introduce a novel interpretability scoring system - a Machine Learning Interpretability Rank-based scale - that combines objective measures such as the number of model parameters with subjective interpretability rankings across different model types. This comprehensive methodology includes stratified sampling, model tuning, and a two-step ranking system to operationalize this trade-off. Results reveal a significant negative correlation between interpretability and predictive performance for intrinsically interpretable models, reinforcing the notion of a trade-off. However, this relationship does not hold for black-box models, suggesting that for these algorithms, predictive performance can be prioritized over interpretability. This study contributes to the ongoing discourse on explainable AI, providing practical insights and tools to help researchers and practitioners achieve a balance between model complexity and transparency. We recommend to prioritise more interpretable models when predictive performance is comparable. Our scale provides a transparent and efficient framework for implementing this heuristic and improving parameter optimization. Further research should extend this analysis to unstructured data, explore different interpretability methods, and develop new metrics for evaluating the trade-off across diverse contexts.

Kyle Erwin, Andries Engelbrecht

Portfolio optimization is a multi-objective optimization problem (MOOP) with risk and profit, or some form of the two, as competing objectives. Single-objective portfolio optimization requires a trade-off coefficient to be specified in order to balance the two objectives. Erwin and Engelbrecht proposed a set-based approach to single-objective portfolio optimization, namely, set-based particle swarm optimization (SBPSO). SBPSO selects a sub-set of assets that form a search space for a secondary optimization task to optimize the asset weights. The authors found that SBPSO was able to identify good solutions to portfolio optimization problems and noted the benefits of redefining the portfolio optimization problem as a set-based problem. This paper proposes the first multi-objective optimization (MOO) approach to SBPSO, and its performance is investigated for multi-objective portfolio optimization. Alongside this investigation, the performance of multi-guide particle swarm optimization (MGPSO) for multi-objective portfolio optimization is evaluated and the performance of SBPSO for portfolio optimization is compared against multi-objective algorithms. It is shown that SBPSO is as competitive as multi-objective algorithms, albeit with multiple runs. The proposed multi-objective SBPSO, i.e., multi-guide set-based particle swarm optimization (MGSBPSO), performs similarly to other multi-objective algorithms while obtaining a more diverse set of optimal solutions.

Elena M. Savicheva, Ammar M. Brebdane, Igor V. Ryzhov

The Middle East in general and the Persian Gulf sub-region in particular are becoming increasingly strategic for China. The sub-region is not only rich in natural resources, primarily energy, and to a large extent provides them to the dynamically developing Chinese economy, but also opens up access to main global maritime and land routes, as well as African and European markets. The study focuses on Chinas interaction with the Gulf Cooperation Council (GCC) countries in the field of energy, trade, and investment in the context of growing economic interdependence that elevates Beijings relations with the Arab countries of the sub-region to the level of strategic partnership. Thus, Chinas relations with this group of states go beyond purely economic interests and affect the strategic interests of Beijing, such as active promotion of the large-scale Belt and Road Initiative, which implies the intensification of Chinas policy in the Middle East. The methodological basis of the study is an interdisciplinary approach. The authors adhere to the neorealism, particularly the theory of the balance of power and regional security complexes, the principle according to which the foreign policy of a state is heavily dictated by the logic of the international system and the distribution of power among states. The power transit theory allows us to understand better the current role of China becoming a superpower in world politics. The research also applies such methods of historical science as chronological, genetic, systemic-structural, and comparative methods. The collection and processing of a significant layer of statistical data makes it possible to highlight the emergence of new powerful political actors in the Middle East.

Helenice Furtado Santos, Márcio Lopes da Silva, Naisy Silva Soares et al.

ABSTRACT This article aims to analyze Brazil’s global competitiveness in the exportation of forest products from 2008 to 2018. Data on importation and exportation were obtained from the Food and Agriculture Organization of the United Nations - FAO, while Revealed Comparative Advantage (RCA), Contribution to Trade Balance (CTB), and Terms of Trade (TOT) were the indicators used to measure international trade. The main results show that Brazil has a positive trade balance for forest products, mainly for wood pulp exports. Brazil’s RCA for forest products was classified as moderate to strong. As for the forest product groups, it was strong for wood pulp, weak to moderate for wood panels, weak for paper and paperboard, weak to nonexpressive for timber, and non-expressive for industrial roundwood and wood fuel. Based on Brazil’s CTB, all the forest product groups have a comparative advantage, except wood fuel. Brazil’s TOT was strong for wood panels, timber, industrial roundwood, wood pulp, in order from most to least expressive. In conclusion, Brazilian exports have comparative advantages and are competitive in the international market.

Xiaolin Yang, Tammo S. Steenhuis, Kyle Frankel Davis et al.

Abstract Earth's water resources are critical for supporting livelihoods and food security but are being increasingly overexploited to support global agriculture. Diversifying cropping systems could potentially resolve unsustainable water use but trade‐offs with other aspects of sustainability and food security have not yet been assessed. We performed a detailed analysis of 31 different field crop rotations conducted during 1990–2019 in the North China Plain, to assess the potential impact of crop diversification on actual evapotranspiration (ETa), changes in regional groundwater table, grain yield, economic output, and water use efficiency (WUE) and to identify configurations that can achieve co‐benefits across multiple dimensions. We found that a combination of lowering the cropping index (i.e., harvest frequency), incorporating fallow periods, and introducing higher‐value crops into the currently dominant winter wheat–summer maize double cropping system can reduce growing season ETa by as much as 31%, mitigate groundwater decline by 19% or more, and increased economic output and economic WUE by more than 11% and 3%, respectively. We also found that multiple diversified wheat‐maize–based rotations—all with rotation lengths greater than 2 years—achieve co‐benefits across all evaluated dimensions. This study provides new empirical evidence of the opportunities for diversified crop rotations to balance the multiple objectives of food production, sustainable groundwater use, and farmer profitability. Extending this solution to other water‐stressed agricultural regions could be an effective strategy in achieving more sustainable food production system globally.

S. Star, H. Becker, Geof Bowker et al.

Oliinyk Oksana, Ksendzuk Valentyna, Sergiienko Larysa et al.

The article substantiates the need to carry out a research of the factors affecting the change in the exchange rate of EUR/UAH due to the fact that the devaluation of the Ukrainian hryvnia in the last few years destabilizes the economic environment of entrepreneurship development. Thus, this work analyzes the determinants of the exchange rate in Ukraine, and the investigated correlation between the dependence of the EUR / UAH exchange rate on a set of factors confirmed the tight correlation between the change in money supply and government debt and the rise / fall in the EUR / UAH national currency. Instead, other factors (GDP, budget deficit, export operations, the positive balance of payments, inflation, public debt) have statistically insignificant correlation to the studied indicator and are not included in the regression model. It is suggested to harmonize monetary policy that has the greatest influence on the formation of the exchange rate, as well as to analyze the connection this policy with the foreign trade policy of the country, which will enable to stabilize the exchange rate as well as to ensure the formation of suitable conditions for the economic development of foreign economic entities.

Taein Kong, Byung Je Kwak, Jonghyun Kim et al.

Recently, multi-pass caliber rolling has been shown to be effective for Mg alloys. This study investigated the effect of subsequent annealing on the mechanical properties of a caliber-rolled AZ31 Mg alloy to modulate the strength-ductility relationship. This annealing gave rise to different trends in mechanical properties depending on the temperature regime. Low-temperature annealing (T ≤ 473 K) exhibited a typical trade-off relationship, where an increase in annealing temperature resulted in increased ductility but decreased strength and hardness. Such a heat treatment did not degrade the high strength-ductility balance of the caliber-rolled alloy, suggesting that the mechanical properties could be tailored for different potential applications. In contrast, high-temperature annealing (T > 473 K) caused a simultaneous deterioration in strength, hardness, and ductility with increasing annealing temperature. These differences are discussed in terms of the varying microstructural features under the different investigated annealing regimes. Keywords: AZ31 Mg alloy, Caliber rolling, Annealing, Grain growth, Mechanical improvement, Twinning

Wei-Bin ZHANG

This paper builds an economic growth model with endogenous wealth and human capital accumulation. It analyzes interactions between domestic economic structure, foreign goods, foreign tourism, and imported energy. Education, foreign goods, foreign tourism, and imported energy are integrated into small-open growth models with wealth accumulation in a comprehensive framework. The economic structure is a synthesis of Uzawa’s two-sector growth model and Uzawa-Lucas’ two-sector growth model. The economy is composed of one capital goods sector, services sector, and education sector. The capital goods sector, service sector and households need energies, which foreign economies supply. The capital goods sector, services sector, and households use up the land. The general equilibrium model determines consumption, production, saving, education and resource distribution under given rate of interest and prices of imported energy and goods fixed in international markets. We build the model and simulates its behavior. We conduct comparative dynamic analysis to demonstrate how different exogenous changes change transitory processes and long-run structures of economic growth.

Fidel J. Tavárez

Reseña de: Alimento, Antonella & Stapelbroek, Koen (eds.), The Politics of Commercial Treaties in the Eighteenth Century: Balance of Power, Balance of Trade, Palgrave, Macmillan, 2017, 472 pp., ISBN: 978-3-319-53574-6

Tatyana Tsygankova, Roman Ponomarenko

As a result of organization and summarization of key concepts of evolution of the marketing tools of global companies, the authors determined the role of the marketing assets in the system of modern marketing management (as a dialectically higher stage of development of the analyzed tools, which will allow overcoming the antagonistic contradiction of “P- and C-vectors” of their development). The article identified the optimal set of key elements of the system of marketing assets, which are the brand, customer loyalty, reputation, network cooperation, marketing strategy, internal marketing, marketing information system and marketing innovation. Due to correlation and regression analysis of the impact of each system elements on performance of global companies, the model of the "marketing asset octagon" was built as an integrative management tool. Also, as a result of construction of the said model, the authors identified the most profitable marketing assets, return on investment and development of competencies in the field of efficient management will bring the highest profit to the company. On the basis of summarizing the regional and branch features of managing the disparate elements of the marketing assets of global companies, the key regional and sectoral priorities of formation, development and improvement of existing concepts of the international marketing management were identified, particularly in terms of building an author’s integrative octagon model.

Khuram Shafi, Liu Hua, Javed Altaf Satti et al.

Exchange rates always affect the prices of the imports and export of products and services in which countries are trading with other parts of the world. Therefore, exchange rate calculation is one of the essential issues for making appropriate policies. This research investigates the determinants of trade, i.e. import, export, industrial growth, consumption level and oil prices fluctuation, which bring changes in exchange rate and their influence eventually on balance of payments. Data of defined variables was collected on yearly basis for China and USA for thirty one years. By applying cointegration, it is estimated that there existed a long run relationship in both countries. USA and China had significant and correct signs on the short run dynamic and some of the factors did not. Exchange rate did not granger cause balance of payment and balance of payment did not granger cause exchange rate. In conclusion, we found that determinants of balance of trade could affect the exchange rates, also, these rates had considerable effect (positive or negative) on balance of payments. In this twofold study, we found relationship of exchange rate with selected determinants of trade, and also examined their bilateral effect, and then made contrast of both countries.

ARISTIŢA ROTILĂ

It is known that within trade relations providers often credit customers for the value of goods or services which are the subject of conducted commercial transactions, this aspect being materialized in the issuance and acceptance of a trade effect. From the time of acceptance until maturity / settlement, trade effects should be reflected separately in the accounts and, to the extent that were not settled until the end of exercise, their value must be presented in the financial statements. Based on analysis of the Romanian accounting regulations, also taking into consideration the opinions expressed in specific literature concerning accounting reflection of trade effects, in this article we try to point out some aspects which, in our opinion, require clarification. We also want to point out some contradictions / inconsistencies regarding the reporting of information on the trade effects, specifically between the text of accounting regulations concerning the definition of accounting structures „cash and bank accounts” and “short term investments” and their contents when presented as positions in the balance sheet structure. In relation to the issues raised we try to prove the effects on the indicators concerning financial position and to make some suggestions that would have effects on Romanian accounting regulations, namely the improvement of financial reporting performed by the economic operators.

Oded Berger-Tal, Jonathan Nathan, Ehud Meron et al.

The trade-off between the need to obtain new knowledge and the need to use that knowledge to improve performance is one of the most basic trade-offs in nature, and optimal performance usually requires some balance between exploratory and exploitative behaviors. Researchers in many disciplines have been searching for the optimal solution to this dilemma. Here we present a novel model in which the exploration strategy itself is dynamic and varies with time in order to optimize a definite goal, such as the acquisition of energy, money, or prestige. Our model produced four very distinct phases: Knowledge establishment, Knowledge accumulation, Knowledge maintenance, and Knowledge exploitation, giving rise to a multidisciplinary framework that applies equally to humans, animals, and organizations. The framework can be used to explain a multitude of phenomena in various disciplines, such as the movement of animals in novel landscapes, the most efficient resource allocation for a start-up company, or the effects of old age on knowledge acquisition in humans.