Hasil untuk "Balance of trade"

M. Tinetti, C. Kumar

Joel Huber, Klaus Zwerina

J. McCombie, A. Thirlwall

Hananto Widodo, Intan Lovisonnya, Fradhana Putra Disantara et al.

Economic globalization has heightened tensions between national sovereignty and international trade obligations. This study compares constitutional review mechanisms in Indonesia, Thailand, and India, representing civil law and common law systems. Using normative legal methods with statute and comparative analysis, it finds that Indonesia applies ex post review of ratification laws, Thailand uses preventive ex ante review, and India employs substantive, precedent-based judicial review. Effectiveness varies: India achieves high substantive effectiveness through judicial activism, Thailand excels procedurally, and Indonesia remains limited to formal review. The study concludes that constitutional review effectiveness depends on institutional design, legal tradition, and the ability to balance constitutional supremacy with international commitments.

Zhanle Zhao, Son Dinh-Van, Yuen Kwan Mo et al.

Connected braking can reduce fatal collisions in connected and autonomous vehicles (CAVs) by using reliable, low-latency 5G New Radio (NR) links, especially NR Sidelink Vehicle-to-Everything (V2X). In rural areas, road side units are sparse and power-constrained, so energy efficiency must be considered alongside safety. This paper studies how three communication control factors including subcarrier spacing (SCS), modulation and coding scheme (MCS), and transmit power (<inline-formula> <tex-math notation="LaTeX">${\boldsymbol{P}}_{\text {t}}$ </tex-math></inline-formula>) should be configured to balance safety and energy consumption in rural scenarios in light and heavy traffic scenarios. Safety is quantified by the packet receive ratio (PRR) against the minimum communication distance <inline-formula> <tex-math notation="LaTeX">${\boldsymbol{D}}_{\text {comm}}$ </tex-math></inline-formula>, defined as the distance that the vehicle travels during the transmission of the safety message. Results show that, under heavy traffic, increasing <inline-formula> <tex-math notation="LaTeX">${\boldsymbol{P}}_{\text {t}}$ </tex-math></inline-formula> and selecting a low-rate MCS at SCS = 30 kHz sustains high PRR at <inline-formula> <tex-math notation="LaTeX">${\boldsymbol{D}}_{\text {comm}}$ </tex-math></inline-formula>, albeit with higher energy cost. In light traffic, maintaining lower <inline-formula> <tex-math notation="LaTeX">${\boldsymbol{P}}_{\text {t}}$ </tex-math></inline-formula> with low MCS levels achieves a favorable reliability-energy trade-off while preserving acceptable PRR at <inline-formula> <tex-math notation="LaTeX">${\boldsymbol{D}}_{\text {comm}}$ </tex-math></inline-formula>. These findings demonstrate the necessity of adaptive, energy-aware strategy to guarantee both safety and energy efficiency in rural V2X systems.

M. Nick, R. Cherkaoui, M. Paolone

Yuhang Wang, Mingguang Zhang, Jun Lu et al.

The high concentration of hazardous sources in chemical parks, which is prone to cause chain accidents, puts forward the demand for dynamic cooperative optimization of emergency resource scheduling. Aiming at the deficiencies of existing studies in the adaptability of dynamic multi-hazard scenarios and the quantification of resource allocation fairness, this paper constructs a three-objective mixed-integer planning model that integrates time efficiency, demand coverage and allocation fairness. Fairness is innovatively quantified as an independent optimization objective, and a standard deviation-based dynamic resource allocation balance index is proposed, which combines multi-warehouse collaborative supply and multi-resource coupling constraint mechanism to systematically solve the problem of trade-offs between timeliness, adequacy and fairness in emergency dispatching in chemical accidents. The improved NSGA-II algorithm is used to solve the Pareto front efficiently, and the search efficiency is improved by the elite reservation strategy and the congestion adaptive adjustment mechanism. In the case study, comparative experiments with the weighted method and the MOGWO algorithm demonstrate that NSGA-II performs superiorly in key metrics, exhibiting excellent convergence, diversity, and stability. Based on this, a case study is conducted using a chemical industrial park in China as an example, generating 41 sets of weights covering extreme preferences, two-objective balance, and three-objective balance. Decision-makers screen solutions based on loss tolerance thresholds and select the optimal solution using a composite score of comprehensive weighted losses. The study further reveals that improvements in demand satisfaction rates are often accompanied by significant increases in transportation time, while pursuing optimal fairness may weaken overall demand satisfaction levels. Sensitivity analysis confirms that resource demand is the key driver determining the number of feasible solutions, while fairness, as an independent optimization objective, holds irreplaceable importance in emergency scheduling decisions.

Yu.I. Rubinskiy, A.A. Sindeev

The authors explore the views on progress held by French President Emmanuel Macron and former Chancellor Olaf Scholz. It is argued that modern, effective intellectual discourses, including those in the political sphere, are always oriented towards national interests. Analyzing these discourses separately and comparing them can provide additional information about the directions in which national policy is developing and the potential for success of these different approaches. The article consists of five parts. The first one formulates the scientific problem and highlights the various ways in which progress can be interpreted. It also describes the novelty of the article, its timeframe, and potential limitations of the research. The second part research focuses on an analysis of E. Macron’s priorities for both French national and European policy. It is highlighted that the concept of balance is particularly important in this context. The concept encompasses numerous relationships at the national, sub-national, and international levels. The president is convinced that his country can successfully establish these balanced relationships and then maintain them effectively. The third part of the article is focused on O. Scholz’s idea of a harmonious process of progressive transformation, the conditions for which include an open economy, free trade, and fair competition. The fourth part is dedicated to the method of comparison. The authors conclude that there are several contradictions between ideas of E. Macron and O. Scholz. They formulate hypotheses in the fifth part of the article. The seamless transformations desired by the political elites of both countries will not occur because French and German societies are ideologically disoriented in different ways. The hypotheses presented should be considered in the context of the authors’ previous research.

Mohamed Ismail, Esraa Kamal, Shimaa Saber

Supply chains face two kinds of uncertainty: random variation and indeterminacy caused by missing, delayed, or conflicting information. This paper models both by using a neutrosophic representation that attaches to every key quantity a triplet for support, indeterminacy, and refutation. Building on this, we define neutrosophic measure and probability for supply-chain events, and we embed them in linear and mixed-integer programs that remain feasible under worst-case demand. The framework provides clear operators for aggregating evidence, converting triplets to actionable intervals, and ranking alternatives with a risk-averse score. We evaluate the approach in three studies. First, supplier selection with an explicit reliability share shifts volume toward trustworthy sources while meeting capacity and reducing total cost. Second, demand forecasting translates ambiguous signals into effective intervals that, when added to a simple baseline, lower mean absolute percentage error and maintain full coverage of realized demand. Third, transportation planning uses a tunable share on a high-availability path to trade cost for improved plan availability. Across all cases, enforcing robust balance removes indeterminacy from service, while neutrosophic metrics quantify where uncertainty remains and what it costs. The method is transparent, easy to audit, and compatible with standard optimization tools, making it practical for resilient planning.

Kristie E. Cameron, Greyson Minjung Jeon, Emily Burden et al.

To ensure the optimal welfare of a species in captivity, housing and enclosure design must align with the ecology, physiology, and behavioral biology of the animal. For the guinea pig (Cavia porcellus), a popular pet and laboratory animal, it is important to consider the behaviors associated with being a prey animal, and how that is influenced by their environment. In this study, seven guinea pigs climbed a ramp of increasing heights with full and partial cover. Each session, the ramp’s height was increased by 3 cm, up to a maximum of 63 cm. Under full cover, the guinea pigs climbed faster, whereas under no cover, their climbing speed was slower as the ramp height increased, and not all guinea pigs reached the maximum height. There was also an order effect where climbing behavior in the partial cover condition affected movement in the subsequent cover condition. The study highlighted a potential effect of personality, and the elicitation of vigilant behavior associated with the level of cover on the ramp. This study indicated that it is important for guardians to provide for the behavioral needs of guinea pigs by considering the effect of cover type in the design of enclosures. This offers balance to the trade-off between the need for guinea pigs to visually assess their environment and explore and forage safely.

Qi Chen

This paper reveals a fundamental conflict at the heart of the online education partnership between platforms and their instructors. While intuition suggests that flexible dynamic pricing benefits all parties, our analysis uncovers a critical and counterintuitive trade-off: the platform’s profit-maximizing pricing strategy can systematically reduce the instructor’s earnings. We model this strategic interaction using a game-theoretic framework that incorporates both instructor-driven course quality and learners’ evolving psychological reference prices (their expectations of a fair price). By analyzing three scenarios (basic, static, and fully dynamic), we demonstrate how this conflict between platform optimization and instructor incentives arises. This central finding highlights a significant managerial challenge: platforms must balance short-term revenue gains from dynamic pricing against the long-term need to retain high-quality instructors. An extension of the model to include market uncertainty (stochastic effects) further demonstrates the robustness of this core finding. The results suggest that while platforms can leverage dynamic pricing even in volatile markets, they must simultaneously implement safeguards, such as fair revenue-sharing agreements, to protect instructor incentives and ensure a sustainable partnership.

Abdulrahman M. Alfaraidi, Nina Ni, Jordan Sosa et al.

Abstract The use of redox-active organic molecules for aqueous electrochemical carbon dioxide capture is limited by their tendency to undergo reversible oxidation by oxygen. Here we show that a naphthoquinone derivative, when reduced in the presence of tetraalkylammonium countercations, displays enhanced stability toward oxygen while maintaining carbon dioxide binding ability. By combining structural modification with control of non-covalent interactions, we mitigate a previously observed trade-off between carbon dioxide capture performance and resistance to aerobic oxidation. In situ spectrophotometry and comparative voltammetry indicate that ion pairing stabilizes the reduced quinone both by shifting its redox potential and by promoting carbon dioxide adduct formation. Among the cations tested, tetraethylammonium provides the most favorable balance, supporting efficient capture and release cycle with 87 % Coulombic efficiency and an energy cost of 157 kilojoules per mole of carbon dioxide from a gas mixture containing carbon dioxide, oxygen, and nitrogen. These findings illustrate how molecular design combined with electrolyte engineering can improve the durability of aqueous quinone-based electrochemical carbon capture systems and may inform the development of more robust and energy-efficient approaches for sustainable carbon management.

Tianyue Bao, Jiaxin Zhao, Yanchang Liu et al.

With the growing prevalence of drone technology across various sectors, efficient and safe path planning has emerged as a critical research priority. Traditional Aquila Optimizers, while effective, face limitations such as uneven population initialization, a tendency to get trapped in local optima, and slow convergence rates. This study presents a multi-strategy fusion of the improved Aquila Optimizer, aiming to enhance its performance by integrating diverse optimization techniques, particularly in the context of path planning. Key enhancements include the integration of Bernoulli chaotic mapping to improve initial population diversity, a spiral stepping strategy to boost search precision and diversity, and a “stealing” mechanism from the Dung Beetle Optimization algorithm to enhance global search capabilities and convergence. Additionally, a nonlinear balance factor is employed to dynamically manage the exploration–exploitation trade-off, thereby increasing the optimization of speed and accuracy. The effectiveness of the mixed multi-strategy improved Aquila Optimizer is validated through simulations on benchmark test functions, CEC2017 complex functions, and path planning scenarios. Comparative analysis with seven other optimization algorithms reveals that the proposed method significantly improves both convergence speed and optimization accuracy. These findings highlight the potential of mixed multi-strategy improved Aquila Optimizer in advancing drone path planning performance, offering enhanced safety and efficiency.

Ismiyatun Ismiyatun, Ita Puji Lestari

The Indo-Pacific region, as the fastest-growing and economically significant area in the world, is increasingly becoming a focal point of geopolitical tensions, particularly with the emergence of the AUKUS alliance. The introduction of nuclear-powered submarines by Australia under AUKUS presents a profound threat to the stability and security of the Indo-Pacific, challenging existing treaties like the Southeast Asia Nuclear Weapon Free Zone (SEANWFZ) and potentially igniting an arms race. Understanding these dynamics is critical for shaping policies that can mitigate the risks of escalating military conflicts and ensure regional stability. The primary objective of this study is to critically analyze the security implications of the AUKUS alliance on the Indo-Pacific region, with a particular focus on how the introduction of nuclear-powered submarines by Australia could undermine regional treaties and provoke an arms race. This study employs a qualitative research approach, specifically using the method of a literature review. The data sources for this study consist of secondary data, including academic journal articles, books, governmental and non-governmental reports, and policy briefs. Data collection was conducted by systematically searching for relevant literature using keywords such as "AUKUS," "Indo-Pacific security," "military alliances," and "geopolitical threats." The literature was then reviewed and categorized based on its thematic relevance to the study. For data analysis, a thematic analysis method was used to identify and interpret patterns within the literature. The research results show: the impact of defense spending in the Indo-Pacific can be influenced by changes in regional dynamics caused by the AUKUS agreement. Countries can change their defense budgets based on their assessment of security threats in the region and changes in the balance of power. Countries can provide funding to enhance their cybersecurity capabilities, which could include investing in cyber defense measures to protect critical military infrastructure and networks. Investments in capital and technology and equipment are part of defense expenditure. CAUCUS can enhance economic cooperation and integration between participating countries and open new opportunities for trade, investment, and technology transfer in the Indo-Pacific region. This could impact the economic landscape resulting from defense partnerships.

Haitham Khaled, Emad Alkhazraji

Traditional heterogeneous networks (HetNets) are constrained by their hardware design and configuration. These HetNets have a limited ability to adapt to variations in network dynamics. Software-defined radio technology has the potential to address this adaptability issue. In this paper, we introduce a software-defined radio (SDR)-based long-term evolution licensed assisted access (LTE-LAA) architecture for next-generation communication networks. We show that with proper design and tuning of the proposed architecture, high-level adaptability in HetNets becomes feasible with a higher throughput and lower power consumption. Firstly, maximizing the throughput and minimizing power consumption are formulated as a constrained optimization problem. Then, the obtained solution, alongside a heuristic solution, is compared against the solutions to existing approaches, showing our proposed strategy is drastically superior in terms of both power efficiency and system throughput. This study is then concluded by employing artificial intelligence techniques in multi-objective optimization, namely random forest regression, particle swarm, and genetic algorithms, to balance out the trade-offs between maximizing the throughput and power efficiency and minimizing energy consumption. These investigations demonstrate the potential of employing the proposed LTE-LAA architecture in addressing the requirements of next-generation HetNets in terms of power, throughput, and green scalability.

Scott Régifère MOUANDAT

The objective of this paper is to show whether external debt management in Gabon is effective. Our study period is from 1989 to 2019 and we use error correction modeling. The significance and positive sign of the recall force shows that short-term imbalances do not correct in the long run, implying that debt management is inefficient as exchange rate fluctuations create changes in the shares of debt denominated in U.S. dollars, Japanese yen, and special drawing rights in both the short and long run. It is difficult for the debt manager to balance his portfolio. The originality of the article is to show that the management of the debt, in particular the external debt, is difficult to be seen inefficient by taking the example of a small economy opened on the outside. It is then a question of rethinking public policies and especially of carrying out structural reforms in the economy in order to minimize the consequences of a high external debt. In this context, the literature recommends either dollarizing all of its debt or allowing the development of a domestic bond market to protect against (or at least minimize) the effects of exchange rate fluctuations on external debt. While we find the latter proposal relevant, we believe that the former is not. Furthermore, we would add that Gabon should implement reforms to boost its industrial sector in order to improve its integration into international trade. The goal is to counter (even partially) the effects of currency fluctuations through export gains.

S. Solon-Biet, K. Walters, U. Simanainen et al.

A. M. Khan, S. Amin, Adib Ahmed

This study has explored the nexus among foreign exchange reserve, remittance, exchange rate, and trade balance in Bangladesh for the period of 1986 to 2019. By employing the Autoregressive Distributed Lag (ARDL) bound test approach, a long-run equilibrium relationship among the variables has been found. The study has shown a statistically significant positive impact of remittance inflow and trade balance on foreign exchange reserves in the long run. If remittance inflow increases by 1 percent, then the foreign exchange reserve would increase by 0.43 percent, and if trade openness rises by 1 percent, then the foreign exchange reserve would rise by 1.22 percent. Granger causality test has revealed the presence of unidirectional causality from the remittance inflow to foreign exchange reserve and remittance inflow to exchange rate. Bidirectional causality has observed between trade openness and exchange rate; however, no causal relationship exists between reserve and trade openness. Based on the findings, this study has endorsed several policy directions that Bangladesh can take to excel in the 21st century and cope with post-pandemic challenges. Contribution/Originality: This study is one of the very few studies which have investigated the foreign reserve dynamics in the context of Bangladesh and the first one to explore the nexus among foreign reserve, remittance, and trade openness by employing the ARDL approach.

Liang Cui, Ye Xu, Ling Xu et al.

Selecting an appropriate wind farm location must be specific to a particular administrative region, which involves restrictions balance and trade-offs. Multi-criteria decision making (MCDM) and GIS are widely used in wind energy planning, but have failed to achieve the selection of an optimal location and make it difficult to establish a set of independent factors. Fuzzy measurement is an effective method to evaluate intermediate synthesis and calculates the factor weight through fuzzy integrals. In this paper, optimal wind farm location is analyzed through coupling Grid GIS technique with λ fuzzy measure. Dalian City is selected as the study area for proving the feasibility of the proposed method. Typography, meteorological, transmission facilities, biological passage, and infrastructure are taken into the index system. All the indexes are specialized into victor grid cells which are taken as the base wind farm location alternative unit. The results indicate that the Grid GIS based λ fuzzy measure and Choquet fuzzy integral method could effectively deal with the special optimization problem and reflect optimal wind farm locations.

Jesús Bobadilla, Raúl Lara Cabrera, Ángel González Prieto et al.

The lack of bias management in Recommender Systems leads to minority groups receiving unfair recommendations. Moreover, the trade-off between equity and precision makes it difficult to obtain recommendations that meet both criteria. Here we propose a Deep Learning based Collaborative Filtering algorithm that provides recommendations with an optimum balance between fairness and accuracy. Furthermore, in the recommendation stage, this balance does not require an initial knowledge of the users’ demographic information. The proposed architecture incorporates four abstraction levels: raw ratings and demographic information, minority indexes, accurate predictions, and fair recommendations. Last two levels use the classical Probabilistic Matrix Factorization (PMF) model to obtain users and items hidden factors, and a Multi-Layer Network (MLN) to combine those factors with a ‘fairness’ (ß) parameter. Several experiments have been conducted using two types of minority sets: gender and age. Experimental results show that it is possible to make fair recommendations without losing a significant proportion of accuracy.