Adjustment Mechanism Research Articles

DBUP: Dynamic blockchain UTXO processing for storage efficiency optimization

In traditional blockchain systems, the Unsent Transaction Output (UTXO) dataset stores all generated UTXOs, which typically represent digital assets of the users. UTXOs can be used to track the output status of cryptocurrency transactions. However, with the development of blockchain networks, the UTXO dataset continuously increasing in scale. In the UTXO dataset, a large number of low-value UTXOs occupied huge storage space, making the blockchain dataset expanded. This impacts the running performance of the whole blockchain system. To address this issue, this paper proposes the Dynamic Blockchain UTXO Processing strategy (DBUP) for UTXO storage efficiency optimization. This strategy aims to rapidly consume the low-value UTXOs, effectively alleviating UTXO dataset expansion. Furthermore, Through improved simulated annealing (ISA) algorithm and a UTXO dynamic adjustment mechanism in DBUP, the strategy ensures that the transaction fee in the transaction process remain at a low level. The experimental evaluation indicates that our strategy can achieve the better performance against the Low Value First (LVF) and the First-In-First-Out (FIFO) strategies, enhancing the storage efficiency of blockchain systems.

Design and Testing of a 2-DOF Adaptive Profiling Header for Forage Harvesters

The existing forage harvester header cannot automatically adjust the height and inclination during operation, resulting in uneven stubble height of forage, which, in turn, affects the efficiency of harvesting and the quality of forage regeneration. To address this issue, this study conducted the design and experimentation of a 2-degrees-of-freedom (DOF) profiling header. Firstly, this study designed an adaptive profiling header with 2-DOF adjustment, which was realized by the height adjustment mechanism and the tilt angle adjustment mechanism. The relationship model between the profiling device and the attitude of the header was established so that the header can acquire ground undulation in real time through the angle sensor of the profiling device. In order to verify the rationality of the header design, a co-simulation model of ADAMS and MATLAB/Simulink was built, and the header attitude control system was designed based on the fuzzy PID algorithm. The co-simulation results show that the header height (H) is always kept around 150 mm during the forwarding process of the harvester, with a maximum error of 5.8 mm, and the average relative error (REH) and root mean square error (RMSEH) were 1.4% and 2.6 mm, respectively, and the maximum error of the tilt angle (γ) of the header is 0.53° and the RMSEγ is 0.22°, which indicates that the header profiling mechanism can accurately reflect the undulation of the terrain and the header attitude control system has good robustness. Finally, the test platform was built and tested in a grassland. The test results show that the average height of the header is 149.8 mm, the maximum error is 7.5 mm, and the REH and RMSEH are 3.4% and 5.3 mm, respectively. The average error of the header inclination is 0.34°, and the maximum error is 0.57°. The test results indicate that the header can realize the adaptive adjustment of height and inclination, and the control system has high precision, stability and reliability, meeting the demand of automatic regulation of header attitude of a forage harvester.

Measurement of the water vapor transmission rate at temperatures above 100 °C

ABSTRACT Water vapor transmission rate (WVTR) and water vapor permeability coefficient were measured at temperatures between 110 and 138°C using the modified cup method. The cup, placed in a Highly Accelerated Stress Test chamber, allowed water vapor to permeate the sample film attached to the cup. The WVTR was determined based on the increase in mass of the cup. To prevent sample damage during measurement, a cup with a pressure adjustment mechanism was utilized. Carrier-incorporated phosphorus pentoxide was used as the desiccant instead of anhydrous calcium chloride to ensure a consistent moisture absorption rate, especially at high temperatures. The water vapor permeability coefficients for the polycarbonate, polyimide, and adhesive films were distributed on an approximately straight line in the Arrhenius plot. Additionally, the Arrhenius plots for the polyethylene terephthalate and polyethylene naphthalate films captured the permeability bending point near the glass transition temperature. To accurately measure the high-temperatureWVTR, upper and lower limits were established for the weighing interval, cup mass gain, and WVTR measurement range.

Influence of overlap rate and ultrasonic compaction on mechanical performance for additive manufacturing of continuous carbon fiber reinforced polylactic acid composites

The additive manufacturing (AM) technology of continuous fiber reinforced thermoplastic composites (CFRTPCs) is gaining attention in the composites industry due to its excellent mechanical performance, potential designability and light-weight structures. Process parameters of AM have a significant impact on mechanical performance and forming accuracy. There is still a Lack of clear design basis for hatch spacing as structural parameter. This study focused on the effect of overlap rate on AM performance of continuous carbon fiber (CCF)/polylactic acid (PLA) composites through the mechanical test, surface morphology, defects characterization and failure analysis, and investigated the adaptability of ultrasonic compaction post-treatment to overlap rate settings. The results indicated that proper overlap state between filaments was beneficial for mechanical properties. The optimal interlaminar shear strength (ILSS) increased to 22.72 MPa by 56 % and tensile strength improved by 17.5 % to 721.65 MPa at various overlap rates. Surface roughness remained stable at approximately 33 μm. Ultrasonic compaction achieved a maximum ILSS up to 24.84 MPa with improvement of 10.26 %, and tensile strength reached to 736.76 MPa with 2.09 % improvement, showing excellent adaptability to overlap rate design. Research findings will improve understanding of digital adjustment mechanisms for printing parameters and provide design guidance for high-performance AM technology of CFRTPCs.

Carbon Border Adjustment Mechanism – a step towards Europe à la française?

Carbon Border Adjustment Mechanism (CBAM) presented by the European Commission (EC) as a part of the ‘Fit for 55’ package was a turning point in almost twenty years of the French eff orts to implement this instrument. In this article I present the concept of CBAM. I also pose questions why France was so fervent proponent of introducing it into EU law and why it finally succeeded. In order to find the answer to these questions I recall the main assumptions of the French European policy. Then, I explain how policy of continuity was rewarded in times of important political changes. I also argue that multidimensional character of CBAM gives enough opportunity for France to shape not only EU climate pol-icy but other EU policies as well. I conclude that CBAM fits perfectly to the French interests. It allows all successive presidents of the Fifth Republic to adapt it to the current needs and include it in their narratives on EU affairs.

Fertility in High-Income Countries: Trends, Patterns, Determinants, and Consequences

High-income countries have generally experienced falling fertility in recent decades. In most of these countries, the total fertility rate is now below the level that implies a stable population in the long run. This has led to concerns among economists, policymakers, and the wider public about the economic consequences of low fertility and population decline. In this contribution, we aim to (a) describe the main determinants of low fertility in high-income countries, (b) assess its potential economic consequences, (c) discuss adjustment mechanisms for individuals and economies, (d) propose a simple economic framework to analyze the long-run economic impacts of low fertility, and (e) draw lessons for economic policymakers to react appropriately. While the economic challenges of low fertility are substantial, a thoughtful and consistent policy response can mitigate most of the adverse consequences.

Automated Grading Model with Adjusted Level of Lenience for Short Answer Questions using Natural Language Processing

Automated grading of short answer questions is a challenging task that involves understanding and evaluating free-text responses. This research presents an innovative model that combines the capabilities of the language model all-mpnet-base-v2 with a machine learning-based lenience adjustment mechanism to enhance the accuracy and fairness of automated grading systems. The proposed model utilizes all-mpnet-base-v2 for natural language understanding and feature extraction from student responses. To address the variability in acceptable answers and provide a fair grading system, a machine learning-based model is integrated to adjust the level of lenience dynamically. This dual approach ensures that the grading system can handle a wide range of responses while maintaining consistency and reliability. The experimental results demonstrate that the combination of all-mpnet-base-v2 with the lenience adjustment model significantly improves grading accuracy compared to traditional methods. This model represents a significant advancement in the field of educational technology, offering a robust solution for automated grading systems that can adapt to diverse educational contexts and requirements.

Research on blind source separation of operation sounds of metro power transformer through an Adaptive Threshold REPET algorithm

PurposeThe safe operation of the metro power transformer directly relates to the safety and efficiency of the entire metro system. Through voiceprint technology, the sounds emitted by the transformer can be monitored in real-time, thereby achieving real-time monitoring of the transformer’s operational status. However, the environment surrounding power transformers is filled with various interfering sounds that intertwine with both the normal operational voiceprints and faulty voiceprints of the transformer, severely impacting the accuracy and reliability of voiceprint identification. Therefore, effective preprocessing steps are required to identify and separate the sound signals of transformer operation, which is a prerequisite for subsequent analysis.Design/methodology/approachThis paper proposes an Adaptive Threshold Repeating Pattern Extraction Technique (REPET) algorithm to separate and denoise the transformer operation sound signals. By analyzing the Short-Time Fourier Transform (STFT) amplitude spectrum, the algorithm identifies and utilizes the repeating periodic structures within the signal to automatically adjust the threshold, effectively distinguishing and extracting stable background signals from transient foreground events. The REPET algorithm first calculates the autocorrelation matrix of the signal to determine the repeating period, then constructs a repeating segment model. Through comparison with the amplitude spectrum of the original signal, repeating patterns are extracted and a soft time-frequency mask is generated.FindingsAfter adaptive thresholding processing, the target signal is separated. Experiments conducted on mixed sounds to separate background sounds from foreground sounds using this algorithm and comparing the results with those obtained using the FastICA algorithm demonstrate that the Adaptive Threshold REPET method achieves good separation effects.Originality/valueA REPET method with adaptive threshold is proposed, which adopts the dynamic threshold adjustment mechanism, adaptively calculates the threshold for blind source separation and improves the adaptability and robustness of the algorithm to the statistical characteristics of the signal. It also lays the foundation for transformer fault detection based on acoustic fingerprinting.

Safe path planning of mobile robot based on improved particle swarm optimization

Path planning is a fundamental aspect of mobile robot navigation, playing a crucial role in enabling robots to autonomously navigate while avoiding obstacles. Nevertheless, traditional path planning algorithms face navigation challenges, including obstacle avoidance and the potential for getting stuck in local minima or deadlocks along the path. To tackle these challenges, the study proposes an enhanced path planning method based on control barrier function (CBF). This approach introduces a safety velocity adjustment mechanism based on CBF and combines it with the particle swarm optimization (PSO), adjusting the safe speed in global planning and addressing the issue of local minima. Experimental simulations are conducted to validate the flexibility and global optimization performance of the proposed path planning method across various obstacle scenarios.

Strategic priority-based course allocation

We introduce the conditional acceptance mechanism for solving the course allocation problem under priorities. This mechanism implements the set of stable allocations in both Nash equilibrium and undominated Nash equilibrium when preferences and priorities are substitutable. We model a post-allocation adjustment mechanism using a repeated version of the conditional acceptance mechanism that mitigates the inefficiencies caused by deviating from equilibrium. Both mechanisms are straightforward to implement, simplify the elicitation of students’ preferences, and share features with currently employed course allocation mechanisms.

The anti-gender movement and the populist radical right in Italy: a symbiotic relationship

The political landscape of Italy experienced a seismic shift in the September 2022 elections, marking a watershed moment. Giorgia Meloni, the leader of the populist radical right party (PRRP) Brothers of Italy, was elected as Italy’s head of government. This event highlighted a significant development in the country’s gender politics, reflecting the ascent of PRRPs across Europe, marked by their reactionary politics, emphasis on traditional values and staunch opposition to gender equality. This study focuses on the dynamics between PRRPs (Brothers of Italy and the League) and the anti-gender movement in Italy. Through a qualitative content analysis of the primary sources of political parties and movements, the research explores their symbiotic relationship, the linkage and adjustment mechanisms employed by both actors, and the political outcomes of their interactions, offering insights into the mobilization of anti-gender actors and their alliance with PRRPs. It contributes to understanding how the organized opposition to gender equality is mainstreamed within political spheres, especially in contexts where right-wing populists hold power.

The impact of health information echo chambers on older adults avoidance behavior: the mediating role of information fatigue and the moderating role of trait mindfulness.

In the digital media era, the prevalence of algorithm-driven content push has intensified the health information echo chambers phenomenon, characterized by excessive homogenization and overload of information. This phenomenon may negatively impact the older adults, a "digitally vulnerable" group, by limiting their access to diverse health information and potentially inducing health information avoidance behaviors. However, the psychological mechanisms within this impact process remain unclear, and this study aims to explore them. Additionally, current study introduces trait mindfulness as a potential intervention tool in reducing health information avoidance behavior among the older adults. This study constructs an impact model based on the Stress-Coping Theory and the Stress-Strain-Outcome (SSO) framework. It identifies health information similarity, relevance, and overload as characteristics of the echo chamber, constituting the Stress part; information fatigue as the Strain; and health information avoidance as the Outcome, with trait mindfulness serving as a moderating factor between Strain and Outcome. A cross-sectional survey of 236 older adults individuals aged 60 and above was conducted, and the collected data were analyzed using SmartPLS and SPSS. The study found that health information similarity and overload significantly increased health information fatigue among the older adults, thereby promoting avoidance behavior, but no significant correlation was found between relevance and fatigue. While there was no significant correlation between trait mindfulness and health information fatigue, it effectively moderated the avoidance behavior induced by fatigue. Current study reveals the impact of the health information echo chamber phenomenon on health information avoidance behavior among the older adults and the moderating role of trait mindfulness. It emphasizes the importance of breaking the health information echo chamber and promoting diverse information dissemination to improve the health information behavior of the older adults. Furthermore, the moderating role of trait mindfulness demonstrates positive intervention potential, providing the older adults with a psychological adjustment mechanism to accept and process health information with a more open attitude, thereby reducing unproductive avoidance behavior.

Carbon Border Adjustment Mechanism (CBAM): Geographical and commodity scope in Polish imports

The Carbon Border Adjustment Mechanism (CBAM) is a new instrument of the EU’s European Green Deal policy. It is intended to contribute to the reduction of greenhouse gas emissions in the world. The CBAM provides for a levy (tax) to be imposed on energy-intensive imports which heavily pollute the environment. The aim of the study was to provide a quantitative assessment of the commodity and geographical coverage of the CBAM in Polish imports. Several indicators were calculated to assess the possible negative impact of CBAM. These indicators can be interpreted as rough measures of the effects of the tax. They were compared with similar indicators calculated by other authors for the whole EU. This paper is a continuation of earlier studies of other researchers who analyzed CBAM coverage and possible implications, while adopting assumptions other than those finally included in the CBAM Regulation. The key findings and main conclusions are as follows: Negative effects of the CBAM will be concentrated on several product groups: steel products, chemicals, polymers, and aluminum. These products accounted for as much as 96% of Poland’s external import subject to the levy. The scale of the final effects of the tax will depend mainly on the level of ETS allowance prices and the intensity of adjustments made by domestic companies and foreign partners. The study ends with two conclusions: First, manufacturers have several years to prepare a strategy to limit the negative effects of the levy (it will be charged as of 2026), but they should start the adjustments as soon as possible. Second, the carbon footprint of a product (as low as possible) is becoming an increasingly important factor in the manufacturers’ international competitiveness. The method of descriptive analysis as well as statistical methods were used.

Different effects of carbon pricing and border adjustment in Germany and Spain

This study examines the effects of carbon pricing in Germany, Spain, and the broader European context using the dynamic, three-region environmental multisector general equilibrium model, EMuSe. Our findings indicate that unilateral carbon pricing in Germany or Spain leads to a sustained negative output. The marginal increase in production costs outweighs modest reductions in emissions. However, when Europe collectively adopts carbon pricing, the long-term output effects become positive, although there are more significant transition costs due to close trade relations within Europe. We find evidence of carbon leakage, which is marginally mitigated by a border adjustment mechanism. However, this mechanism mainly protects domestic carbon-intensive sectors and produces inconsistent country outcomes; Germany gains, while Spain loses. Notably, Spain’s energy sector emerges as a long-term beneficiary due to its relatively lower emission intensity. The findings highlight the strategic importance for Europe to engage global partners in carbon pricing as it reduces the economic downturn phase and increases long-term gains.

Carbon border adjustment mechanism, carbon pricing, and within-sector shifts: A partial equilibrium approach to Vietnam's steel sector

Carbon pricing has recently gained further momentum from the European Union (EU)'s plan for the Carbon Border Adjustment Mechanism (CBAM). The CBAM aims to align the greenhouse gas (GHG) emission costs in imported products with those within the EU. CBAM will affect foreign producers in targeted sectors, incentivizing them to employ low-emission technology, and encouraging trading partners to implement carbon pricing akin to the EU's. Our study assesses the potential impact of the CBAM and Vietnam's carbon pricing on the country's steel sector, using a multi-technology, multi-trade-partner partial equilibrium model. The results suggest that the CBAM could significantly reduce Vietnam's steel exports to the EU while it is not sufficient to significantly shift production from high-emission to low-emission steel production. However, CBAM may nudge Vietnam's carbon pricing, which can drive a substantial transition from high-emission to low-emission production and accelerate the transition to clean energy, depending on the level of carbon price. Our study results provide important insights for energy and climate policy discussions in relation to carbon border adjustment mechanisms and carbon pricing.

Challenges and Controversies to the European CBAM from a Legal Perspective

The Carbon Border Adjustment Mechanism (CBAM), proposed by the European Union to combat carbon leakage, presents a complex landscape of opportunities and challenges in the realm of global climate governance. This paper explores the problems and controversies surrounding CBAM, including potential WTO incompatibility, violations of UNFCCC principles, and complexities in carbon accounting. It also examines the potential impact of CBAM on developing countries and offers a range of suggested solutions. These solutions encompass designing domestic carbon markets in alignment with the European model, implementing policy and regulatory reforms, fostering China-European bilateral relations, and emphasizing international cooperation and adherence to established legal frameworks. Additionally, at the enterprise level, strategies to invest in green technologies, establish comprehensive carbon accounting systems, and adapt to the evolving low-carbon economy are proposed. By addressing these challenges and embracing these strategies, nations and businesses can contribute to a more sustainable and equitable global climate governance framework.

Research on the Optimal Trajectory Planning Method for the Dual-Attitude Adjustment Mechanism Based on an Improved Multi-Objective Salp Swarm Algorithm

In this study, an optimization method for the motion trajectory of attitude actuators was investigated in order to improve assembly efficiency in the automatic docking process of large components. The self-developed dual-attitude adjustment mechanism (2-PPPR) is used as the research object, and the structure is symmetrical. Based on the modified Denavit–Hartenberg (MDH) parameter description method, a kinematic model of the attitude mechanism is established, and its end trajectory is parametrically expressed using a five-order B-spline curve. Based on the constraints of the dynamics and kinematics of the dual-posture mechanism, the total posturing time, the degree of urgency of each joint, and the degree of difficulty of the mechanism’s posturing are selected as the optimization objectives. The Lévy flight and Cauchy variation algorithms are introduced into the salp swarm algorithm (SSA) to solve the parameters of the multi-objective trajectory optimization model. By combining the evaluation method of the multi-objective average optimal solution, the optimal trajectory of the dual-tuning mechanism and the motion trajectory of each joint are obtained. The simulation and experiment results show that the trajectory planning method proposed in this paper is effective and feasible and can ensure that the large-part dual-posture mechanism can complete the automatic docking task smoothly and efficiently.

Adjustment of segmental rotations to achieve both racket speed and accuracy at various impact heights during a two-handed backhand stroke

ABSTRACT This study investigated the influence of impact height and competitive level on racket speed and stroke accuracy by analysing segmental angular kinematics under a random ball condition. High- (HQ, n = 7) and low-quality (LQ, n = 7) groups were determined by k-means clustering of the ratio of ball landing in the target (accuracy) and racket speed decrease. HQ showed higher accuracy (48.3% vs. 32.4%), less speed decrease at lower impact heights (−4.4% vs. −10.3%) and better competitive level ranking [median (1st–3rd quartiles); 4 (2–7)] than LQ [10 (8–13)]. HQ produced greater racket speed (24.4 vs. 21.6 m/s), especially with a notable horizontal velocity (23.8 vs. 20.8 m/s) of the racket at lower impact height, which was attributed to the central role of greater angular velocity of pelvis and thorax in the hitting direction. Both groups showed similar adjustment mechanisms that due to the decrease in angular velocity of pelvis, players increased the relative rotation angle between pelvis and thorax to maintain angular velocity of thorax when transitioning from low to high impact heights. Our findings suggest that players should emphasise the coordination between pelvic and thoracic rotations according to impact heights to maintain racket speed while controlling ball landing position.

Minimum cost consensus model with variable cost for multi-criteria large-scale group decision-making considering the tolerance of decision-makers

The objective of multicriteria large-scale group decision-making (LSGDM) is to obtain a decision result that gains acceptance from the majority of decision-makers (DMs). The consensus reaching process (CRP) plays a crucial role in guiding DMs to continuously adjust their opinions through feedback adjustment mechanisms to form a widely accepted decision result. In practical decision-making, adjusting opinions incurs costs and involves limited resources. Simultaneously, DMs have tolerance for modifying their opinions. To this end, this paper proposes a minimum cost consensus model (MCCM) with variable cost to reach consensus efficiently within limited resources and DMs’ tolerance. Firstly, a method to measure the combined similarity among DMs is proposed. Then, an extended local fitness maximization (ELFM) algorithm suitable for multicriteria LSGDM problems is proposed for clustering. Furthermore, an objective method of determining the unit adjustment costs for DMs in the MCCM is provided. For the CRP that considers the tolerance of DMs, this paper introduces the MCCM with variable cost to obtain the adjustment opinions of DMs. During the selection process, we utilize the stochastic multicriteria acceptability analysis (SMAA) method to evaluate alternatives and selection. Finally, the feasibility of the proposed method is verified through an illustrative example, and its advantages are emphasized through comparative analysis.

M&A contractual innovation in SME sector: the effect of valuation adjustment mechanism clause on SME growth

Identifying and effectively managing growth models for small and medium enterprises (SMEs) poses a significant challenge for entrepreneurs. Prior research has indicated that the dominant model is an acquisition-led growth strategy. Our paper introduces a novel acquisition growth model for SMEs in China, which incorporates the use of valuation adjustment mechanism (VAM) clauses in M&A contracts. We thoroughly analyze the financial implications of this innovative model on SME growth, the specific SME profiles that favor this approach, and the prevalent types of VAM clauses adopted by these SMEs. All hypotheses were rigorously tested using primary data from Chinese public SME companies. The results reveal a positive financial impact of VAM clauses in M&A contracts on SME growth. It was found that SMEs with lower equity concentration or smaller holdings are more likely to adopt the VAM Clauses Model, and the inclusion of equity payments as compensation in the VAM clause is highly common in practice. These findings hold significant implications for both theoretical research on SMEs and the practical strategies of entrepreneurs.