Adjustment Mechanism Research Articles

The Permeability of the “Cordon Sanitaire” against Eurosceptics in the European Parliament

Based on voting protocols and debate minutes for the Carbon border adjustment mechanism (CBAM) hearings in the European Parliament in 2022–2023 the cases where positions of MEPs from political groups “Identity and Democracy” and “European Conservatives and Reformists” coincided with those of parliamentarians from other parties (particularly opponents from “The Left” and “The Greens”) were analysed. These actions bypassing the “sanitary cordon” were explored together with the content of the CBAM, which made possible to identify the main motivations of MEPs’ voting. Such cases of solidary vote allowed to evaluate the strength of this barrier, the applicability of theories of two-dimensional nature of ideological space and the prospects of coordinated actions of selected parties after the European parliament elections 2024. These ad hoc coalitions were facilitated by the differences in attitudes to amendments. Among significant factors ensured Eurosceptic MEPs to express the same views were reluctanсe to transfer additional competences to the EU bodies and willingness to support the European industry. Supranationality and deindustrialisation are considered to be more imminent threats than climate change. The article explores a two-dimensional structure of ideological space of the given activity. Close relations between left-wing and right-wing parties could be explained by similarity of political views (i. e Euroscepticism in attributed not only to far-right politicians).

Extended state observer-based adaptive dynamic surface prescribed performance control for electro-hydraulic actuators with uncertainties.

For Electro-Hydraulic Actuators (EHA) with parametric uncertainties and mismatched and matched disturbances, most existing robust adaptive control strategies can achieve only uniformly ultimately bounded tracking errors. An Extended-State-Observer (ESO)based asymptotic control scheme is proposed by incorporating the prescribed performance control into the backstepping framework to ensure satisfied tracking performance and anti-disturbance ability of EHA systems. A novel ESO is designed to acquire an asymptotic estimation without prior bounds of the mismatched disturbance and its derivatives. Dynamic surface control with an adaptive adjustment mechanism is utilized to avoid the "complexity explosion" and guarantee the asymptotic stability of the closed-loop system. The efficacy of the proposed strategy is validated through simulation and experiments.

WTO Legality Analysis of the European Union's Carbon Border Adjustment Mechanism and China's Response

Now that the EU Carbon Border Adjustment Mechanism (CBAM) has entered into force and is entering a transition period, its compliance with WTO trade rules has been controversial. CBAM's differential treatment of goods from different origins based on their carbon content violates the GATT principle of non-discrimination and may result in WTO members being denied fair, just and equal treatment in international trade. CBAM is a tax on the carbon emissions of some specific imported goods, requiring high-carbon products imported into or exported from the EU to pay the corresponding amount of tax or refund the corresponding carbon emission quotas, thus affecting China's export trade. This study mainly utilizes literature research method and comparative research method. At the international level, analyze whether CBAM can meet the WTO legal requirements to construct international carbon tariff rules separately from the existing WTO rules, affecting the global environment and climate change issues. At the domestic level, the impact of CBAM on China's foreign trade is explored. China should adhere to multilateralism, strengthen international cooperation, continuously develop low-carbon technologies and improve the carbon trading market to cope with the impacts of CBAM. Thus, to the effect of safeguarding international interests and contributing to global development.

Quantitative evaluation study of lithium sustainable development policies in China based on the PMC index model

The sustainable development of lithium is essential for facilitating the low-carbon energy transition and ensuring sustainable economic growth. Understanding the effectiveness of China’s policies on lithium development is vital for advancing these goals. This study constructed a comprehensive policy evaluation system using content analysis and the PMC (Policy Modeling Consistency) index model. A total of 12 representative policies were analyzed, and their performance was visualized through PMC surface diagrams. The evaluation revealed that among the 12 policies, 2 were rated as “excellent,” 9 as “good,” 1 as “acceptable,” and none as “poor.” These results indicate that China’s policies for lithium’s sustainable development are generally well-designed and scientifically grounded. Despite their strengths, the policies exhibit areas for improvement, including low timeliness, insufficient long-term planning, and limited dynamic adjustment mechanisms. Regional policy coordination is also lacking, especially in non-major lithium-producing areas where policy quality tends to be lower. To address these issues, we recommend optimizing future policies by enhancing timeliness and flexibility, improving regional coordination, refining policy tools, and increasing public participation.

Adaptive Step RRT*-Based Method for Path Planning of Tea-Picking Robotic Arm.

The Adaptive Step RRT* (AS-RRT*) path planning algorithm for tea-picking robotic arms was proposed as a solution to the autonomy, safety, and efficiency problems inherent to tea-picking robots in tea plantations. The algorithm employs an accumulator-based sampling point selection strategy to enhance the efficiency of path planning and the quality of the resulting path. It combines fast connectivity and pruning optimization methods to identify collision-free paths in a shorter time and to reduce the computational burden. It also incorporates a dynamic step length adjustment mechanism following collision detection, ensuring that the robot arm can avoid obstacles in real time. Furthermore, the generated paths were optimized through the introduction of redundant node removal and curve smoothing techniques. In the robotic arm motion planning experiments, the depth vision sensor was employed to obtain three-dimensional information within the tea plantation as the data source. The experimental results demonstrate that the AS-RRT* algorithm reduces the path length by 14.18% and the path planning time is less than 1 s, indicating that the proposed method enhances the efficiency of path planning and obstacle avoidance performance of the tea-picking robot arm.

Development and Experiment of Adaptive Oolong Tea Harvesting Robot Based on Visual Localization

Aimed to improve the quality of picked tea leaves and the efficiency of tea harvesting, an adaptive oolong tea harvesting robot with an adjustment module of a cutting tool and a harvesting line localization algorithm is proposed. The robot includes a vision measurement module and an adjustment mechanism of a cutting tool, enabling it to assess the shape of tea bushes and adaptively adjust the cutter configuration. To address the challenges of complex tea bush structures and environmental noise, a Prior–Tukey RANSAC algorithm was proposed for accurate harvesting model fitting. Our algorithm leverages prior knowledge about tea bush stem characteristics, uses the Tukey loss function to enhance robustness to outliers, and incorporates workspace constraints to ensure that the cutting tool remains within feasible operational limits. To evaluate the performance of the robot, experiments were conducted in a tea garden in Wuyi Mountain, China. Under ideal conditions, our algorithm achieved an inlier ratio of 43.10% and an R2 value of 0.9787, significantly outperforming traditional RANSAC and other variants. Under challenging field conditions, the proposed algorithm demonstrated robustness, maintaining an inlier ratio of 47.50% and an R2 value of 0.9598. And the processing time of the algorithm met the real-time requirements for effective tea-picking operations. The field experiments also showed an improvement in intact tea rates, from 79.34% in the first harvest to 81.57% in the second harvest, with a consistent usable tea rate of around 85%. Additionally, the robot had a harvesting efficiency of 260.14 kg/h, which was superior to existing handheld and riding-type tea pickers. These results indicate that the robot effectively balances efficiency, accuracy, and robustness, providing a promising solution for high-quality tea harvesting in complex environments.

BLASTFURNACESINTHEAGEOFDECARBONIZATION: THESEARCHFOR COKE ALTERNATIVES

The aim of this work is to analyze the prospects of using hydrogen as an alternative to coke in blast furnaces in the context of decarbonizing the steel industry, particularly considering the introduction of the Carbon Border Adjustment Mechanism (CBAM). It is shown that the widespread notion of a complete replacement of coke with hydrogen needs clarification, as there are technological limitations and economic challenges. According to the analysis of global experience, the use of hydrogen in blast furnaces allows for a reduction of CO2 emissions by 10-70%, which is particularly relevant in the context of CBAM, but requires significant capital investments in the modernization of production and the creation of infrastructure for the production and transportation of hydrogen. It is shown that the efficiency of hydrogen use, and therefore its potential for reducing the cost of carbon quotas within the CBAM framework, depends on the technology of its production, the method of injection into the blast furnace, and the conditions of blast furnace smelting.

Second-Generation Flanking Policies: Addressing Extraterritorial and Non-Economic Costs of Trade Liberalization

AbstractFlanking policies – policies that aim to address potential negative effects of trade liberalization, and/or the concerns of domestic stakeholders regarding those negative effects, and that are either legally or factually linked to trade liberalization – have been a critical component of international trade policy since at least 1962. Over the years, however, flanking policies have changed. This Article argues that there is a heretofore unnoticed distinction between what I term first-generation flanking policies and second-generation flanking policies. Specifically, first-generation flanking policies target negative economic effects, or costs, of trade liberalization experienced within the enacting country. Trade adjustment assistance is the paradigmatic example. By contrast, second-generation flanking policies target non-economic costs that arise outside of the enacting country. Examples include the European Union's Carbon Border Adjustment Mechanism, Deforestation-free Products Regulation, and the United States' Uyghur Forced Labor Prevention Act. Because second-generation flanking policies directly target foreign activity, they often employ more trade-distorting policies – tariffs, imports bans, and associated administrative hurdles for imports – than first-generation flanking policies, which more often relied on domestic subsidies. Moreover, they reflect a significant reorientation of the limits of state authority in international trade law. Whereas authority to tax and regulate production in international economic law has historically been based primarily on a territorial link to productive activity, second-generation flanking policies target production but rely on a territorial nexus with consumption of goods and services.

Exceptio Inadimpleti Contractus: CBAMs as International Countermeasures

A growing number of states and international organizations, including the EU and the US, are envisaging carbon border adjustment mechanisms (CBAMs) as a means to implement their climate policies. From an economic perspective, CBAMs are instruments aiming to level crossborder trade between countries that implement uneven carbon pricing schemes. From a legal perspective, CBAMs are considered ‘general exceptions’ to free trade, whose lawfulness is debated in the context of the World Trade Organization (WTO). This article develops a systemic analysis of CBAMs, notably the EU CBAM, under general and particular international law, and argues that they could be framed under the specific exception of ‘countermeasures’ under treaty law, particularly the General Agreement on Tariffs and Trade (GATT), thus fundamentally establishing a presumption of legality.

Greening Development: Examining The Impact of European Union Economic Cooperation on Vietnam’s Environmental Sustainability

Abstract In recent years, economic cooperation between the European Union (EU) and Vietnam has played a crucial role in shaping Vietnam’s path toward sustainable development, particularly through trade agreements and environmental commitments. However, the environmental impact of this cooperation remains under debate. This paper investigates whether economic ties with the EU lead to greener development in Vietnam. Particular attention is paid to the EU-Vietnam Free Trade Agreement (EVFTA) and recent EU policies like the Carbon Border Adjustment Mechanism and fisheries control system. While the research suggests that EU cooperation has contributed to a greener trajectory for Vietnam’s development, challenges are also explored.

Multi-scale spatio-temporal transformer: A novel model reduction approach for day-ahead security-constrained unit commitment

Security-constrained unit commitment (SCUC) in large-scale power systems faces significant computational challenges, particularly with increasing renewable energy integration. This paper introduces a multi-scale spatio-temporal transformer (MSTT) model for efficient SCUC problem reduction through three key innovations: a multi-scale ST attention mechanism integrating both hierarchical temporal attention and electrical distance-based spatial attention to capture complex system dependencies, a physics-informed position encoding method incorporating power system domain knowledge including electrical distance, power flow sensitivity, and generator stability characteristics, and an adaptive reduction strategy with dynamic threshold adjustment mechanism that automatically balances computational efficiency and solution reliability based on system states and prediction confidence. Experimental results on IEEE test systems demonstrate that the MSTT model achieves up to 69.5 % computational time reduction while maintaining solution optimality (base-normalized cost (BNC) ≤ 0.05 %), significantly outperforming existing approaches.

An Intelligent Maneuver Decision-Making Approach for Air Combat Based on Deep Reinforcement Learning and Transformer Networks

The traditional maneuver decision-making approaches are highly dependent on accurate and complete situation information, and their decision-making quality becomes poor when opponent information is occasionally missing in complex electromagnetic environments. In order to solve this problem, an autonomous maneuver decision-making approach is developed based on deep reinforcement learning (DRL) architecture. Meanwhile, a Transformer network is integrated into the actor and critic networks, which can find the potential dependency relationships among the time series trajectory data. By using these relationships, the information loss is partially compensated, which leads to maneuvering decisions being more accurate. The issues of limited experience samples, low sampling efficiency, and poor stability in the agent training state appear when the Transformer network is introduced into DRL. To address these issues, the measures of designing an effective decision-making reward, a prioritized sampling method, and a dynamic learning rate adjustment mechanism are proposed. Numerous simulation results show that the proposed approach outperforms the traditional DRL algorithms, with a higher win rate in the case of opponent information loss.

Перспективи впровадження технології прямого відновлення заліза для декарбонізації металургійних підприємств

The metallurgical manufacturing is one of the most carbon-intensive sectors globally, accounting for over 7% of greenhouse gas emissions. The Ukrainian metallurgical industry, a strategic source of foreign revenue and an essential element of the country's economic stability, currently faces significant challenges due to the need to adapt to climate obligations outlined in the Paris Agreement, as well as the introduction of the Carbon Border Adjustment Mechanism (CBAM) in the European Union. This article provides a comprehensive analysis of the prospects for implementing direct reduced iron (DRI) technology in Ukrainian metallurgical enterprises as an effective pathway for steel decarbonization. A comparison is made between traditional methods grounded in blast furnaces and oxygen converters and the DRI technology with natural gas, coal, syngas, and hydrogen. The main advantages of implementing DRI are identified, along with the infrastructural, technological, and financial barriers that is necessary to be overcome for effective decarbonization of Ukraine’s metallurgical sector. Keywords: decarbonization, metallurgy, steel, direct recovery of iron, hydrogen, greenhouse gases, CBAM, Ukraine.

Tomato sprayed monocalcium phosphate had production-phytoremediation dual function with high soil Cd extraction and safer fruit production

In order to make use of the large biomass of tomato plant to fulfill the purpose of remediating-while-producing, two commercial tomato varieties, ‘Baiguoqiangfeng’ (BG) and ‘Ouguan’ (OG) were grown in Cd contaminated acidic soil to compare their performance on Cd phytoextraction, and monocalcium phosphate (Ca) was foliar applied to reduce their fruit Cd concentration. The results showed that the BG was a more Cd tolerant variety, comparing with OG, it suffered lighter tissue peroxidation and photosynthesis obstacle, owning weaker amino acid metabolism, secondary metabolism and stress signal transduction under Cd stress. The Ca application reduced its ABA level but increased the GSH, IAA, ZR and GA3 level, and enhanced its lysine degradation, tyrosine metabolism, alanine, asparagine and glutamate metabolism, plant hormone signal transduction and phenylpropanoid biosynthesis under Cd stress. With these metabolic regulations, the Ca application promoted its leaf biomass accumulation, guaranteeing the total Cd extraction amount (0.88 mg pot−1 as 0.20 mg kg −1), and reduced the fruit Cd partition, decreasing the fruit Cd concentration by 71.4% with higher yield. Meanwhile, the OG had lower Cd phytoextraction capacity than the BG, and Ca spray enhanced its cell energy generation, flavonoids biosynthesis and photosynthetic carbon fixation, but had no effect on fruit Cd concentration. The two tomato varieties had different responses to Ca application under Cd stress in their hormone signaling, energy metabolism, secondary metabolism and amino acids metabolism, which furtherly differed their Cd phytoextraction capacity and production safety. Therefore, the monocalcium phosphate spray combined ‘Baiguoqiangfeng’ tomato realized the dual function of production-phytoremediation, and the mechanism of plant Cd sensitivity adjustment through phenylpropanoid biosynthesis and amino acids metabolism deserved further study.

Carbon governance or trade gaming: China's approach to addressing the EU's carbon border adjustment mechanism

The EU's Carbon Border Adjustment Mechanism (CBAM) poses a significant challenge for developing countries, especially China, a key player in the global market and a major carbon emitter. We use the GTAP-E model to evaluate CBAM's impact on China's economy and carbon reduction efforts, and propose two response strategies: carbon governance approaches and international trade gaming. Our findings show that CBAM may lead to a slight decrease of 0.003% in China's GDP and a 0.004% reduction in carbon emissions. It also generates ripple effects across the supply chain, notably affecting energy-intensive upstream industries. We find that the combination of carbon pricing and trade agreements is more effective than trade protection measures in minimizing economic losses from CBAM. This is achieved through mechanisms such as sharing carbon reduction costs and promoting decarbonization on both the supply and demand sides. Furthermore, improving carbon governance can enhance the green competitiveness of Chinese products. Going forward, China should maintain trade agreements with developing countries and enhance its carbon pricing mechanism to better align with global climate governance. Our study offers valuable policy insights for developing countries as they navigate the challenges posed by CBAM.

The effect of alimony on married women's labor supply and fertility: Evidence from state‐level reforms

AbstractReforms that reduce spousal support after divorce are generally thought to reduce the bargaining power of alimony recipients as well as their incentives to participate in the traditional model of household specialization. Using the U.S. Time Use Survey and exploiting a series of recent reforms in several U.S. states that reduced the rights of eligible spouses, we find that wives surprised by the reforms reacted by increasing their labor supply, but the adjustment mechanism varied by educational group. While college educated wives' labor supply increased at the expense of time spent on housework and childcare, wives with less than a college degree sacrificed personal care and leisure time. Effects for men are generally smaller and not statistically significant. We also find a reduction in the rate of new births following the reforms, with the effect being much more pronounced in the case of women with a university education, suggesting that part of the difference in time use may be attributable to differences in preferences and the cost of children by educational levels. Since children are a marital public good, our results imply a decrease in marriage‐specific investment. The estimated effects are robust to various sensitivity tests and are greater in couples with a high‐income differential and therefore more exposed to changes in alimony laws.

Deep reinforcement learning-based local path planning in dynamic environments for mobile robot

Path planning for robots in dynamic environments is a challenging task, as it requires balancing obstacle avoidance, trajectory smoothness, and path length during real-time planning.This paper proposes an algorithm called Adaptive Soft Actor–Critic (ASAC), which combines the Soft Actor–Critic (SAC) algorithm, tile coding, and the Dynamic Window Approach (DWA) to enhance path planning capabilities. ASAC leverages SAC with an automatic entropy adjustment mechanism to balance exploration and exploitation, integrates tile coding for improved feature representation, and utilizes DWA to define the action space through parameters such as target heading, obstacle distance, and velocity In this framework, the action space is defined by DWA’s three weighting parameters: target heading deviation, distance to the nearest obstacle, and velocity. To facilitate the learning process, a non-sparse reward function is designed, incorporating factors such as Time-to-Collision (TTC), heading, and velocity. To validate the effectiveness of the algorithm, experiments were conducted in four different environments, and the algorithm was evaluated based on metrics such as trajectory deviation, smoothness, and time to reach the end point. The results demonstrate that ASAC outperforms existing algorithms in terms of trajectory smoothness, arrival time, and overall adaptability across various scenarios, effectively enabling path planning in dynamic environments.

Three-point adaptive preview steady-state compensation driver model based on articulated heavy vehicle

This article proposes a three-point adaptive preview steady-state compensation driver model based on articulated heavy vehicles (AHVs). Although AHVs have extremely high road transportation efficiency, they have poor driving stability and high accident risk during high-speed transportation due to their large weight, high center of mass and multi-body characteristics. However, there are few studies on intelligent driving control of AHVs. In order to improve the active safety performance of AHVs, a three-point adaptive preview driver model is designed in this article. Based on the driver model, a sliding mode steady-state compensation controller is added. The three-point adaptive preview driver is different from other driver models. Its characteristic is that the preview distance can be automatically adjusted according to the vehicle speed and road curvature. A driver model with three-point preview weighted deviation, preview time, current vehicle speed and vehicle state as input and front wheel angle as output is established. Considering the trailer state, the front wheel angle is compensated and corrected by sliding mode steady-state compensation controller. The simulation results show that the model can reasonably judge the relationship between the target path and the vehicle position, adapt to the dynamic adjustment mechanism of the preview distance, and has good tracking accuracy. The front wheel compensation angle provided by the sliding mode controller under high speed and extreme conditions can ensure that the AHVs can track the target trajectory while maintaining driving stability.

Research on the Value Creation Mechanism of Green-Driven Products in the Internet+ Era

In order to improve the value of green-driven products, this paper studies the value creation mechanism of green-driven products in the Internet+ era. Under the framework of the classic Cournot output game, based on the bounded rationality assumption of the participants, this paper constructs a novel Cournot duopoly investment game model, and analyzes the dynamic adjustment mechanism of the participants' investment. The decision variable of participating enterprises is to select the optimal investment amount, and each production enterprise makes investment decisions in the next period according to the observed marginal profit of the current period to maximize the profit. Through calculation and analysis, it can be known that three boundary equilibriums and one interior point equilibrium of the discrete dynamic model system are obtained in this paper. The experimental analysis shows that the value creation mechanism of green-driven products proposed in this paper can effectively promote the value of green-driven products.

A Three-Party Dynamic Pricing Mechanism for Customized Data Products Based on the Stackelberg Game and Bargaining Model

In the era of big data, breaking down data silos to enable efficient data transactions has become essential, with the fairness and transparency of pricing mechanisms being paramount. This study addresses these challenges by introducing a novel tripartite pricing model for customized data products that integrates the Stackelberg and bargaining game frameworks. By designing distinct utility functions for buyers, sellers, and the platform, the model effectively aligns the varying objectives of each participant. A dynamic adjustment mechanism further enhances this model by adaptively recalibrating the guidance price and pricing range based on real-time updates to buyer budgets and seller offers, thus ensuring fairness and responsiveness throughout the negotiation process. Experimental simulations comprising 100 transaction rounds across diverse buyer–seller profiles validate the model’s effectiveness, achieving a transaction success rate of 92.70% with an average of 6.86 bargaining rounds. These findings underscore the model’s capacity to optimize transaction outcomes, promote pricing equity, and enhance bargaining efficiency. The proposed model has broad applications in sectors such as finance, healthcare, and e-commerce, where precise data pricing mechanisms are essential to maximize transactional value.