bluuebunny/crossref_metadata_2025_split huggingface dataset:
Road preview method for active suspension based on reinforcement learning
Authors: Wang Guohong , Kou Farong , Liu Pengtao , Lv Wenhua , Xing Longlong 
Published: January 2025

Abstract
The pre-identification of impulse road surfaces, such as speed bumps, potholes, and manhole covers, can significantly enhance the performance of active suspension systems. However, existing current identification methods often fail to balance between low cost, high reliability, and precise speed. This study proposes an impulse road surface identification method based on a reinforcement learning (RL) network. First, a real dataset of impulse road surfaces was collected, with suspension dynamic responses serving as inputs and random road levels along with impulse road surface features as outputs. This data was used to develop a random forest extreme gradient boosting (RF-XGBoost) network to recognize road surface information from vehicle dynamics. Next, a semantic segmentation network was employed to segment road surfaces during intelligent vehicle travel, using road surface information identified by the random forest network as the reward function for RL. The RL policy was pre-trained using the actual collected data. To validate the effectiveness of the proposed control strategy, a simulation environment was constructed in Prescan, where speed bumps, potholes, and manhole covers of varying heights and sizes were randomly arranged. The RL-based road surface identification algorithm was implemented in Simulink, and a co-simulation was conducted with the CarSim vehicle model. The enhanced RF-XGBoost network effectively distinguishes between random and impulse road surfaces, achieving average recognition accuracies of 95.7% for random surfaces and 98.2% for impulse surfaces. During initial training iterations, the RL network exhibited lower accuracy; however, as training progressed, the accuracy for unfamiliar road surface features reached an average of 96.5%, and overall recognition accuracy improved by an average of 9%. The simulation results demonstrate that the proposed RL identification method effectively acquires information about the road ahead, shows robustness and generalization, and provides crucial disturbance data for subsequent active suspension control.
The regional ventilation distribution monitored by electrical impedance tomography during anesthesia induction with head-rotated mask ventilation
Authors: Xu Qing , Fang Yijiao , Pan Congxia , Gao Lingling , Zhu Yun , Zhang Jun , Zhao Zhanqi , Yang Li 
Published: January 2025

Abstract

Objective. Abnormal regional lung ventilation can lead to undesirable outcomes during the induction of anesthesia. Head rotated ventilation has proven to change the airflow of upper airway tract and be effective in increasing the tidal volume. This study aimed to investigate the influence of head rotated mask ventilation on regional ventilation distribution during the induction phase of anesthesia. Approach. Ninety patients undergoing anesthesia induction were randomly assigned to receive either neutral head (neutral-head group) or rotated right side head (rotated-head group) mask ventilation. Pressure-controlled mode was used in all mechanical ventilation. The regional lung ventilation was monitored by electrical impedance tomography. The primary outcome was the ratio of left/right lung ventilation distribution. The secondary outcomes were global inhomogeneity index (GI), center of ventilation (CoV, 100% = entirely dorsal), and the regional lung distribution differences between spontaneous and mask ventilation. Main results. Forty-two patients with neutral-head and 38 with rotated-head mask ventilation were analyzed finally. Compared with spontaneous ventilation, mask positive-pressure ventilation caused significant changes in the ratio of left/right lung ventilation distribution [0.85 (0.27) versus 0.94 (0.30); P = 0.022]. However, there were no differences in the ratio of left/right lung ventilation distribution between neutral and rotated head groups (P = 0.128). When compared with spontaneous ventilation, mask ventilation caused regional distributions of ventilation shifts towards ventral lung areas (CoV: 45.7 ± 5.0% versus 39.2 ± 4.8%; P < 0.001), and significant lung ventilation inhomogeneity (GI: 0.40 ± 0.07 versus 0.49 ± 0.14; P < 0.001). Compared with neutral-head mask ventilation, rotated-head mask ventilation was associated with higher expiratory tidal volume (TVe) (575.1 ± 148.6 ml versus 654.2 ± 204.0 ml; P = 0.049). Significance. Mask positive ventilation caused regional lung ventilation changes. When compared with neutral-head mask ventilation, rotated-head mask ventilation did not improve the regional ventilation towards to left lung. However, rotated-head mask ventilation was associated with higher TVe, and has the potential for better oxygenation.

Trial Registration. This study was registered on Chinese Clinical Trial Registry on 6 August, 2024 (ChiCTR2400087858).
A novel dual-inertia driven piezoelectric actuator for flexible mounting applications
Authors: Shao Yan , Xu Minglong , Liu Kaiyuan , Meng Min 
Published: January 2025

Abstract
Stepping piezoelectric actuators are widely recognized for their high power density, fine resolution, and extensive travel range. However, their dependence on rigid supports limits their applicability in flexible mounting scenarios, such as cable traction systems, where insufficient reaction forces can result in in-place oscillation and subsequent functional failure. To address this challenge, this study has proposed a novel dual-inertia driven piezoelectric actuator specifically designed for flexible mounting applications. The actuator comprises two primary components with large inertia, an innovative rhombus-shaped clamping mechanism enabling precise clamping force adjustment, and a compact Hall sensor for accurate displacement monitoring. A multi-body dynamic model has been developed to analyze the interaction between inertial forces and frictional transitions, which are critical for achieving precise stepwise elongation or contraction in flexible setups. Experimental evaluations have demonstrated the actuator’s superior performance, achieving a maximum load capacity of 5.57 N, a clamping friction of 11.2 N, a free-load speed of 10.53 mm s−1, and a stepping resolution of 0.55 μm. These findings have established the proposed actuator as a significant advancement in piezoelectric technology, offering a robust and adaptable solution for high-precision actuation in flexible mounting applications.
Presetting-time complete synchronization of two Lorenz systems with applications into nonlinear PMSMs and Hindmarsh-Rose neuron models
Authors: Ma Ru-Ru , Huang Zhixiang , Ma Zhicai 
Published: January 2025

Abstract
This paper begins by examining the presetting-time synchronization (PtS) of two nonlinear Lorenz systems and subsequently applies these findings to synchronize the permanent magnet synchronous motors (PMSMs) and Hindmarsh-Rose neuron models. Unlike conventional finite-time synchronization (FtS) or fixed-time synchronization (FxS) methods, the upper bound estimation of convergence time (UBECT) in this study can be predefined as a constant, unaffected by initial conditions or control parameters. Furthermore, the control schemes developed here are free from chattering, as they avoid using traditional discontinuous signum and absolute value functions. Through classical Lyapunov stability analysis, sufficient conditions are derived to ensure PtS between nonlinear Lorenz systems, PMSMs, and Hindmarsh-Rose neuron models. Lastly, numerical simulations are conducted to confirm the accuracy and efficiency of the theoretical findings, with comparisons and perturbation analyses also included.
Finite Time Hybrid Synchronization of Heterogeneous Duplex Complex Networks via Time-varying Intermittent Control
Authors: Xie Cheng-jun , Lu Xiang-qing 
Published: January 2025

Abstract
This paper study the finite time internal synchronization and the external synchronization (hybrid synchronization) for duplex heterogeneous complex networks by time-varying intermittent control. There few study hybrid synchronization of heterogeneous duplex complex networks. Therefore, we research the finite time hybrid synchronization of heterogeneous duplex networks, which employs the time-varying intermittent control to drive the duplex heterogeneous complex networks to achieve hybrid synchronization in finite time. To be specific, the switch frequency of the controllers can be changed with time by devise Lyapunov function and boundary function, the internal synchronization and external synchronization are achieved simultaneously in finite time. Finally, numerical examples are presented to illustrate the validness of theoretical results.
A novel approach to visual image encryption: 2D hyperchaos, variable Josephus, and 3D diffusion
Authors: Hong Yan , Duan Xinyan , Su Jingming , Wang Zhaopan , Fang Shihui 
Published: January 2025

Abstract
With the development of the Internet, image encryption technology has become critical for network security. Traditional methods often suffer from issues such as insufficient chaos, low randomness in key generation, and poor encryption efficiency. To enhance performance, this paper proposes a new encryption algorithm designed to optimize parallel processing and adapt to images of varying sizes and colors. The method begins by using SHA-384 to extract the hash value of the plaintext image, which is then processed to determine the chaotic system’s initial value and block size. The image is padded and divided into blocks for further processing. A novel two-dimensional infinite collapses hyperchaotic map (2D-ICHM) is employed to generate the intra-block scrambling sequence, while n improved variable Joseph traversal sequence is used for inter-block scrambling. After removing the padding, 3D forward and backward shift diffusions, controlled by the 2D-ICHM sequences, are applied to the scrambled image, producing the ciphertext. Simulation results demonstrate that the proposed algorithm outperforms others in terms of entropy, anti-noise resilience, correlation coefficient, robustness, and encryption efficiency.
Impact of trapping on tritium self-sufficiency and tritium inventories in fusion power plant fuel cycles
Authors: Meschini Samuele , Delaporte-Mathurin Rémi , Tynan George R. , Ferry Sara E. 
Published: January 2025

Abstract
The dynamic analysis of fusion power plant (FPP) fuel cycles highlights the challenge of achieving tritium self-sufficiency in future FPPs. While state-of-the-art fuel cycle models offer valuable insights into the necessary design parameters for attaining tritium self-sufficiency, none of these models currently consider the impact of tritium trapping within fuel cycle components. However, detailed analysis of individual components reveals that substantial amounts of tritium can be trapped within the first wall, divertors, and breeding blanket systems, suggesting that tritium trapping may significantly influence the FPP ability to achieve self-sufficiency. The compounded effects of additional tritium traps generated by irradiation effects and component replacements further exacerbate this challenge. The novelty of this work is the integration of an explicit, physics-based model for tritium trapping, evolution of damage-induced traps, and component replacements into a dynamic, system-level model of a fuel cycle. The results show an increase of a factor

10
3

−

10
4

of tritium inventory in the first wall and vacuum vessel of an ARC-class FPP when accounting for the aforementioned phenomena. This, coupled with the replacement of components subject to significant tritium trapping, slows down fuel cycle dynamics, resulting in an extended tritium doubling time (50% increase), higher start-up inventory (30% increase), and higher required tritium breeding ratio (2%–5%) compared to a scenario without tritium trapping.
Evaluation and optimization of physical, mechanical, and biological characteristics of 3D printed Whitlockite/calcium silicate composite scaffold for bone tissue regeneration using response surface methodology
Authors: Thangavel Mahendran , Elsen S Renold 
Published: January 2025

Abstract
Calcium phosphate-based bioscaffolds are used for bone tissue regeneration because of their physical and chemical resemblance to human bone. Calcium, phosphate, sodium, potassium, magnesium, and silicon are important components of human bone. The successful biomimicking of human bone characteristics involves incorporating all the human bone elements into the scaffold material. In this work, Mg-Whitlockite (WH) and Calcium Silicate (CS) were selected as matrix and reinforcement respectively, because of their desirable elemental composition and regenerative properties. The magnesium in WH increases mineralization in bone, and the silicon ions in CS support vascularization. The Mg-WH was synthesized using the wet chemical method, and powder characterization tests were performed. Response surface methodology (RSM) is used to design the experiments with a combination of material compositions, infill ratios (IFs), and sintering temperatures (STs). The WH/CS bioceramic composite is 3D printed in three different compositions: 100/0, 75/25, and 50/50 wt%, with IFs of 50%, 75%, and 100%. The physical and mechanical characterization study of printed samples is conducted and the result is optimized using RSM. ANOVA (Analysis of Variance) is used to establish the relationship between input parameters and responses. The optimized input parameters were the WH/CS composition of 50/50 wt%, IF of 50%, and ST of 1150 °C, which bring out the best possible combination of physical and mechanical characteristics. The RSM optimized response was a density of 2.27 g cm−3, porosity of 36.74%, wettability of 45.79%, shrinkage of 25.13%, compressive strength of 12 MPa, and compressive modulus of 208.49 MPa with 92% desirability. The biological characterization studies were conducted for the scaffold samples prepared with optimized input parameters. The biological studies confirmed the capabilities of the WH/CS composite scaffolds in bone regenerative applications.
Climate change risk trap: low-carbon spatial restructuring and disaster risk in petroleum-based economies
Authors: Rözer Viktor , Mehryar Sara , Alsahli Mohammad M M 
Published: January 2025

Abstract
The economic risks from climate change can be separated into two categories: physical risks from increased frequency and magnitude of extreme weather and climate events, and transition risks due to rapid decarbonisation leading to stranded assets and shifts in production and the labour market. On the global level, the two risks are widely recognized as trade-offs by the academic and policy literature: rapid decarbonisation increases transition risks while reducing physical risks, and vice versa for a delayed reduction of greenhouse gas emissions. In contrast, little is known about the interaction between the two risks on smaller geographical scales. This paper investigates the interactions between physical and transition risks on the sub-national level for petroleum-based economies. Their strong dependency on the export of fossil fuels requires a more far-reaching economic restructuring to meet both local and global emission targets than most other economies, exposing them to high transition risks. At the same time, the profound economic changes resulting from a low-carbon transition lead to a spatial redistribution of assets and labour, when brown assets and jobs get stranded and new green assets and jobs are created elsewhere. Building on the literature on spatial economic restructuring and climate disaster risk, we show that, unlike the common conceptualisation as a trade-off, physical and transition risk can increase simultaneously on the sub-national level. We call this dynamic the climate change risk trap. The paper provides an empirical illustration of this trap using the example of flash flood risk in Kuwait, a wealthy petroleum-based economy in the Gulf region. It shows how decisions on urban planning and low-carbon economic restructuring have increased flash flood risk. The analysis highlights the importance of considering climate disaster risk and environmental impact assessments in low-carbon transition planning to avoid falling into the climate change risk trap.
Have crops already reached peak suitability: assessing global climatic suitability decreases for crop cultivation
Authors: Mombo Vhiny-Guilley , Duvallet Mathilde , Schaeffer Michiel , Baarsch Florent 
Published: January 2025

Abstract
Crop yield and the availability of arable land are impacted by climate change, leading to effects on global patterns of production and trading. To gain more precise insights in how future climate change might lead to redistributing productive crop areas, we developed a new method to assess climatic crop suitability, which combines temperature and precipitation suitability through water balance calculations. We applied the method to evaluate the effects of climate change under two climatic scenarios (SSP2-4.5 and SSP5-8.5), using an ensemble of five general circulation models, for nine crops (Arabica coffee, cassava, common beans, common wheat, maize, plantain, rice, sorghum and sugarcane) for four periods of time: past (1995–2014), present day (2015–2034), medium term (2040–2059), long term (2080–2099). We observed that the fraction of area with optimal suitability might be on a downward trajectory for coffee, cassava, beans, wheat and plantain, and could be halved by the end of the century. The tropics and sub-tropics are negatively affected for all crops, while mid-latitudes see large decreases in suitability for beans, wheat and maize. Global patterns show that suitability decreases at local levels (in about 30% of the global area for bean and wheat) are not compensated by increases in suitability elsewhere (in about 19% of the area for bean and wheat). As relocation and expansion of production areas are constrained by available arable land, other strategies might be considered to improve suitability, such as irrigation, which would increase the area of optimal suitability from 5%–25% to 40%–50% of total arable land for the nine crops. Drainage could improve the optimal suitability area fivefold for maize and sorghum, while shading increases suitability for coffee (by up to 20% in both cases). The increased risk of food supply shortages led by climatic suitability loss may trigger increased deforestation if adaptation measures are not implemented.
Advancements and opportunities to improve bottom–up estimates of global wetland methane emissions
Authors: Zhu Qing , Jacob Daniel J , Yuan Kunxiaojia , Li Fa , Runkle Benjamin R K , Chen Min , Bloom A Anthony , Poulter Benjamin , East James D , Riley William J , McNicol Gavin , Worden John , Frankenberg Christian , Halabisky Meghan 
Published: January 2025

Abstract
Wetlands are the single largest natural source of atmospheric methane (CH4), contributing approximately 30% of total surface CH4 emissions, and they have been identified as the largest source of uncertainty in the global CH4 budget based on the most recent Global Carbon Project CH4 report. High uncertainties in the bottom–up estimates of wetland CH4 emissions pose significant challenges for accurately understanding their spatiotemporal variations, and for the scientific community to monitor wetland CH4 emissions from space. In fact, there are large disagreements between bottom–up estimates versus top–down estimates inferred from inversion of atmospheric CH4 concentrations. To address these critical gaps, we review recent development, validation, and applications of bottom–up estimates of global wetland CH4 emissions, as well as how they are used in top–down inversions. These bottom–up estimates, using (1) empirical biogeochemical modeling (e.g. WetCHARTs: 125–208 TgCH4 yr−1); (2) process-based biogeochemical modeling (e.g. WETCHIMP: 190 ± 39 TgCH4 yr−1); and (3) data-driven machine learning approach (e.g. UpCH4: 146 ± 43 TgCH4 yr−1). Bottom–up estimates are subject to significant uncertainties (∼80 Tg CH4 yr−1), and the ranges of different estimates do not overlap, further amplifying the overall uncertainty when combining multiple data products. These substantial uncertainties highlight gaps in our understanding of wetland CH4 biogeochemistry and wetland inundation dynamics. Major tropical and arctic wetland complexes are regional hotspots of CH4 emissions. However, the scarcity of satellite data over the tropics and northern high latitudes offer limited information for top–down inversions to improve bottom–up estimates. Recent advances in surface measurements of CH4 fluxes (e.g. FLUXNET-CH4) across a wide range of ecosystems including bogs, fens, marshes, and forest swamps provide an unprecedented opportunity to improve existing bottom–up estimates of wetland CH4 estimates. We suggest that continuous long-term surface measurements at representative wetlands, high fidelity wetland mapping, combined with an appropriate modeling framework, will be needed to significantly improve global estimates of wetland CH4 emissions. There is also a pressing unmet need for fine-resolution and high-precision satellite CH4 observations directed at wetlands.
Improved bounds on quantum uncommon information
Authors: Lee Yonghae , Bae Joonwoo , Yamasaki Hayata , Lee Soojoon 
Published: January 2025

Abstract
In classical information theory, channel capacity quantifies the maximum number of messages that can be reliably transmitted using shared information. An equivalent concept, termed uncommon information, represents the number of messages required to be exchanged to completely share all information in common. However, this equivalence does not extend to quantum information theory. Specifically, quantum uncommon information (QUI) is operationally defined as the minimal amount of entanglement required for the quantum communication task of quantum state exchange (QSE), where two parties exchange quantum states to share all quantum messages in common. Currently, an analytical closed-form expression for the QUI remains undetermined. In this work, by investigating underlying characterization of the QUI, we derive improved bounds on it. To obtain these bounds, we develop a subspace exchange strategy that leverages a common subspace of two parties to identify the unnecessary qubits for exchange. We also consider a referee-assisted exchange, wherein a referee aids two parties in efficiently performing the QSE. Our bounds provide more precise estimations for the QUI. Furthermore, we demonstrate that the subspace technique is a versatile tool for characterizing uncommon information not only in the bipartite scenario but also in various multi-partite ones.
Coupled modelling and analysis of lubrication-wear evolution of textured piston/cylinder pair in high-pressure common rail pumps
Authors: Zhan Menghao , Huang Dan , Yan Kanghao , Zhou Guangde 
Published: January 2025

Abstract
Surface texturing is an important approach to enhance fluid lubrication performance and reduce friction and wear. Research on the surface texturing of the piston/cylinder pair considering various characteristics such as multi-physical fields and the evolution of friction and wear is still insufficient. The novelty of this work aims to establish a coupled numerical simulation model considering the coupling effect of multiple physical fields, wear of the cylinder bore and surface texture, and determine the effective surface texture parameters to improve the friction performance of the mechanical components of high-pressure common rail pump. The influence of surface texture on friction and wear characteristics and the evolution of lubrication-wear under different geometric cases were in-depth investigated, and the action mechanism of surface texture on lubrication and wear was revealed. Through numerical analysis, optimal parameters were identified that significantly reduce the friction coefficient and wear amount, offering practical insights for mitigating friction and wear in mechanical systems.