bluuebunny/crossref_metadata_2025_split huggingface dataset:
Utilization of Muria Strait Toponymy data in mitigation: Building resilience to disaster risk
Authors: Wahyudi Deny Yudo , Purnawan Jati Slamet Sujud , Wijaya Daya Negri , Azda Laili Vita Sabrina , Ananda Labuda Shofiya , Ikhrom Anisa Musyaroful 
Published: November 2024

Abstract
The North Coast of Java Island, including the area around Kendal to Rembang (formerly known as the Muria Strait region), is susceptible to sea water rise and land subsidence, which pose a significant risk to the lives of its inhabitants. Similarly, the districts of Demak, Kudus, Pati, Rembang, and Juwana are also vulnerable to these threats given that they were formed by alluvial deposits and are now densely populated. However, the community’s resilience to various changes in Muria Strait’s geosphere can be observed in the development of local knowledge, including toponymy. In the modern era, toponymic data can be used as instruments to support disaster mitigation and recovery efforts. The information content obtained after the toponymy study can be used as an instrument to increase public awareness and develop a targeted mitigation infrastructure. Given the community’s vulnerability to a range of disasters exacerbated by climate change, the objective of this research is to disseminate the findings of a toponym study of the Muria Strait, with a focus on the potential of these data to inform disaster-mitigation strategies. Toponymy data analysis was conducted using an ethnopedological approach in the context of archaeological and historical research. This approach was also necessary to analyse historical sources related to soil cover/land use (SLC) and changes in the geosphere of the Muria Strait over time.
Compression behavior of ex-situ PVC foam-filled tubes
Authors: Linul Emanoil , Vălean Cristina , Rusu Andreea-Iustina 
Published: November 2024

Abstract
The present work investigates the mechanical characteristics of tubes filled with Polyvinyl chloride (PVC) foam. The tubes used are made of aluminum and were filled ex-situ. Static compression tests were performed on both axially (AL) and laterally (LL) loaded tubes. Comparisons between foam-filled (FFT) and empty (ET) tubes are presented, highlighting the foam-tube interaction effect. The emphasis is on elastic, strength and strain properties, but energy absorption performances are not neglected. Discussions regarding the failure mechanisms of ETs and FFTs are also presented. It was obtained that, regardless of the loading direction, FFTs show clearly superior mechanical properties to ETs. At the same weight, the specimens tested axially support higher loads than those tested laterally. This aspect is due to deformation mechanisms that take place in the samples during the tests. It was noted that the compressive strength is more affected by the filling than by the compressive modulus. Under lateral loads, the ETs samples fail quasi-brittle through complete failure of the tube, while in the case of FFTs, a ductile fracture with stable deformation of the sample is obtained.
The possibility of recycling iron sludge in the steel industry
Authors: Bobora Adriana , Socalici Ana , Birtok Baneasa Corneliu , Sapta Doru 
Published: November 2024

Abstract
The steel industry strives to achieve quality steel with improved mechanical properties. In order to meet these market requirements, steel manufacturers need to streamline technological operations, increase process efficiency and productivity, and improve product quality control. Old iron and scrap metal used in the production of steel come from various sources and special attention should be paid to their quality, in particular, to the content of elements harmful to steel. The paper presents the results of the research undertaken on the use as raw material of the steel-making aggregates, in addition to the classic assortments of old iron of by-products obtained from the processing of iron slats in the form of briquettes. The influence of the quality of waste used was assessed by expanding the raw material base in the context of sustainable development, on steel blanks by investigating the effect on the chemical composition as well as the possibility of recovery of alloying element.
Study on the mechanical properties of Polyacrylic Acid/Chitosan double network hydrogels in dynamic water content
Authors: Gao Yang , La Huanjun , Min Haonan , Hou Zhenzhong 
Published: November 2024

Abstract
Hydrogels have demonstrated significant potential in wound dressings, owing to their adjustable water content, excellent biocompatibility, and other advantages. An ideal wound dressing requires absorbing exudate while maintaining mechanical properties to prevent secondary damage to the wound under external pressure. In this study, Polyacrylic Acid (PAA)/Chitosan (CS) double network hydrogels were prepared via radical polymerization, and the swelling ratio, compressive modulus, and other parameters were experimentally measured. A hyperelastic finite element model of the hydrogel was then established, and its rationality was validated by experiments. Based on the model, the impacts of CS content and dynamic water content on the compressive properties of PAA/CS hydrogels were analyzed. Tetracycline hydrochloride was loaded into PAA/CS hydrogels, the drug release performance and adhesion experiments were carried out. The results indicated that, compared with the hydrogels with 2.5% and 5% CS content, the hydrogel with 1% CS content had the highest swelling ratio, which was 1774%. Meanwhile, its equilibrium water content could attain 94.6%. When the water content varied within the range from 45% to 75%, the compressive strength of the hydrogel with 5% CS content ranged from 0.33 MPa to 1.22 MPa, similar to that of skin tissue. Additionally, the prepared drug-loaded PAA/CS hydrogels exhibited a drug release pattern approximately following the Korsmeyer-Peppas model within 7 days. They also exhibited remarkable adhesion to porcine skin and different substrate surfaces. This study provides a basis for the clinical application of PAA/CS double network hydrogels as wound dressings in the repair of infected wounds.
Freeze-necking and volumetric change of clay during freezing by 3D x-ray computed tomography
Authors: Fan Wenhu , Wang Jiaqi , Zhang Tao , Zuo Xi , Xiao Zhi , He Pengfei , Shi Xin 
Published: November 2024

Abstract
In artificial freezing engineering, the freezing temperature is an important factor affecting soil frost heave deformation, and studying its impact is of great significance. The frost heave ratio of soil is a crucial factor for designing and predicting soil frost heave. However, it only considers vertical deformation while neglecting radial deformation. This paper introduces a simple unidirectional freezing apparatus specifically designed for three-dimensional x-ray computed tomography (CT) scanning, which allows for the investigation of internal structural changes in clay during freezing at four different freezing temperatures (i.e., −3 °C, −5 °C, −7 °C, and −9 °C). Freeze-necking of the soil was observed during freezing. An image processing method was proposed to segment the soil samples, and parameters such as length, equivalent diameter, and volume were measured to assess changes during freezing. The observed variations in necking depth and equivalent diameter indicate that freeze-necking is uniform. As the freezing temperature decreased, the necking depth reduced from 72.4 mm to 38.1 mm, and within this necking depth, the equivalent diameter decreased progressively from the bottom to the top. Moisture content increased near the cold end of the soil and decreased near the warm end, suggesting that freeze-necking is due to moisture migration within the soil. Considering freeze-necking, the volumetric frost heave ratio was defined to characterize soil frost heave deformation. This ratio also decreases as the freezing temperature decreases, and the values are smaller than those of the traditional frost heave ratio. The discrepancies become more pronounced at higher freezing temperatures, reaching up to 1.8% at −3 °C. The results indicate that lower freezing temperatures can reduce frost heave deformation, and freeze-necking requires greater attention in engineering at higher freezing temperature.
Comparing the performance of a femoral shaft fracture fixation using implants with biodegradable and non-biodegradable materials.
Authors: Taghipour Sina , Vakili-Tahami Farid , Chakherlou Tajbakhsh Navid 
Published: November 2024

Abstract
Orthopedic injuries, such as femur shaft fractures, often require surgical intervention to promote healing and functional recovery. Metal plate implants are widely used due to their mechanical strength and biocompatibility. Biodegradable metal plate implants, including those made from magnesium, zinc, and iron alloys, offer distinct advantages over non-biodegradable materials like stainless steel, titanium, and cobalt alloys. Biodegradable implants gradually replace native bone tissue, reducing the need for additional surgeries and improving patient recovery. However, non-biodegradable implants remain popular due to their stability, corrosion resistance, and biocompatibility. This study focuses on designing an implant plate for treating transverse femoral shaft fractures during the walking cycle. The primary objective is to conduct a comprehensive finite element analysis (FEA) of a fractured femur’s stabilization using various biodegradable and non-biodegradable materials. The study assesses the efficacy of different implant materials, discusses implant design, and identifies the optimal materials for femoral stabilization. Results indicate that magnesium alloy is superior among biodegradable materials, while titanium alloy is preferred among non-biodegradable options. The findings suggest that magnesium alloy is the recommended material for bone implants due to its advantages over non-degradable alternatives.
A class alignment network based on self-attention for cross-subject EEG classification
Authors: Ma Sufan , Zhang Dongxiao , Wang Jiayi , Xie Jialiang 
Published: November 2024

Abstract
Due to the inherent variability in EEG signals across different individuals, domain adaptation and adversarial learning strategies are being progressively utilized to develop subject-specific classification models by leveraging data from other subjects. These approaches primarily focus on domain alignment and tend to overlook the critical task-specific class boundaries. This oversight can result in weak correlation between the extracted features and categories. To address these challenges, we propose a novel model that uses the known information from multiple subjects to bolster EEG classification for an individual subject through adversarial learning strategies. Our method begins by extracting both shallow and attention-driven deep features from EEG signals. Subsequently, we employ a class discriminator to encourage the same-class features from different domains to converge while ensuring that the different-class features diverge. This is achieved using our proposed discrimination loss function, which is designed to minimize the feature distance for samples of the same class across different domains while maximizing it for those from different classes. Additionally, our model incorporates two parallel classifiers that are harmonious yet distinct and jointly contribute to decision-making. Extensive testing on two publicly available EEG datasets has validated our model's efficacy and superiority.
Escalating threat of human-perceived heatwaves in Brazil
Authors: Ballarin André S , Oliveira Paulo Tarso S , Uchôa José Gescilam S M , Lima Carlos H R , Zaerpour Masoud , Godoy Mijael Rodrigo Vargas , Meira Neto Antônio A , Papalexiou Simon Michael , Wendland Edson 
Published: November 2024

Abstract
Heatwaves pose significant threats to socioeconomic and environmental systems, with their intensity and frequency expected to increase due to climate change. Despite their critical impacts, future heatwaves in Brazil remain underexplored, especially from a human-perceived perspective, which is crucial for assessing potential public health impacts. Here, we propose a method to assess heatwaves using the humidex (

H

)—a climate index that combines temperature and relative humidity to indicate human-perceived heat - alongside traditional temperature-based measures. Using bias-corrected simulations from 10 CMIP6 models under SSP2-4.5 and SSP5-8.5 scenarios, we quantified projected changes in heatwaves across Brazil. The results indicate that heatwaves will become more severe and prolonged, with greater changes under the SSP5-8.5 scenario by the end of the century, particularly in the North, Northeast, and Central regions. The magnitude of human-perceived heatwaves is expected to rise faster than temperature-based ones, underscoring the need for public health-focused assessments. CMIP6 models strongly agree on increased future heatwaves, potentially tripling population exposure in most Brazilian states, with the Southeast experiencing greater changes due to its larger population. These events are expected not only to affect more people but also to be more severe, exceeding over 60 days per year of serious danger (H > 45 °C) by the end of the century under SSP5-8.5. Record-shattering events in the historical period are projected to become the norm by mid-century, highlighting the accelerating nature of these extreme events. Our findings emphasize the importance of considering human-perceived heat in climate impact studies and public health planning to mitigate potential impacts. Significance Statement Despite the increasing threat of heatwaves, most studies focus on their climate properties, overlooking human-perceived aspects. This is especially true for Brazil, where heatwaves receive limited attention. This study introduces a novel approach, coupling heatwaves with a heat stress index (H) to evaluate them from a human-perceived perspective. Our results suggest more intense and prolonged heatwaves in the future, with record-breaking events becoming the norm by mid-century. Human-perceived heatwaves are projected to rise faster than climate-based ones, emphasizing the need for public health-focused assessments. These increases are expected to more than triple population exposure in most Brazilian states, with severe events (H > 45 °C) exceeding 60 days per year by the end of the century under the pessimistic scenario.
How could payments for U.S. climate-smart farming practices change the regional adoption of conservation practices?
Authors: Burnett J Wesley , Sichko Christopher , Gramig Benjamin M , Bowman Maria , O’Hara Jeffrey 
Published: November 2024

Abstract
Recent U.S. policies have promoted climate-smart farming practices. However, little is known about the costs of practice adoption or the regional allocation of support. The primary objective of this study is to identify cost-effective agricultural practices for climate mitigation and determine where practices might be targeted regionally. This study uses average regional abatement cost curves for six mitigation practices to analyze how conservation funding could incentivize adoption. Using a social benefit threshold of $51 per metric ton, we estimate that for all practices studied, except cover crops, there are regions where the average cost of reduction is less than the social benefit threshold, meaning that greenhouse gas could be cost-effectively mitigated or sequestered at regional levels given more adoption of these practices. For the purposes of conservation targeting, we outline the regions where the adoption of these practices is potentially the most cost-effective.
Land use change and its impact on ecosystem service value in Xinjiang
Authors: Hao Yifeng , Zhou Xindong , Shiyao Liu , Tao Wanghai 
Published: November 2024

Abstract
Xinjiang is an important hub connecting China and Eurasia and has an important strategic position in economy, energy, and ecological security. However, due to the fragile ecological environment in Xinjiang, there are substantial challenges in coordinating the relationship between social and economic development and ecological environment construction. To elucidate the relationship between land use changes induced by human activities and the valuation of ecosystem services, this study utilized the value equivalent method to evaluate the ecosystem service value in Xinjiang from 2000 to 2020 while analyzing its spatiotemporal response characteristics related to land use. The results showed that from 2000 to 2020, the value of ecosystem services in Xinjiang showed an upward trend, reaching 182.24 yuan/hm2 in 2020, and the total value of the whole region was 302.584 billion yuan. The value of ecological services in Xinjiang is mainly low-grade (about 50%), and high-grade only accounts for 1.03%~2.19%. There was a significant increase in land use in forested areas and water bodies, while the conversion trend from effective grassland to other land types was relatively limited. Specifically, 4.47% of bare ground and 3.76% of meadows transformed water bodies. Additionally, 2.69% of grassland experienced conversion into woodland. The land use intensity was generally low (more than 85% of the low-grade grades), and 83.71% of the land use intensity increased during the study period. The water area was the main controlling factor of the service value of the state system, with a contribution rate of 78.83%, followed by grassland (11.29%) and woodlands (9.30%), and 54.39% of the land use changes increased the value of ecosystem services.
The state and future of extreme heat studies in Southeast Asian megacities: risk, impacts and adaptation strategies in a warming world
Authors: Macagba Sharon Feliza Ann P , Delina Laurence L 
Published: November 2024

Abstract
Southeast Asian cities are increasingly affected by heat-related phenomena and various climate-related disasters; however, research on urban heat in this region remains limited compared to other areas. This paper employs bibliometric and thematic analyses to investigate studies on extreme heat in mega-urban areas of Southeast Asia, focusing on the risks and impacts faced by vulnerable populations and their adaptation and mitigation strategies. The bibliometric analysis visualises the research landscape, identifying key clusters and highlighting prevalent themes and gaps. It reveals a predominant emphasis on characterising extreme heat and analysing urban temperature variations through satellite and meteorological data, underscoring a significant lack of research on the socio-economic factors affecting at-risk communities. The thematic analysis further examines how existing studies address these socio-economic vulnerabilities and evaluates the adaptation strategies employed, particularly concerning land use changes driven by population growth. Our findings indicate that, while studies address urban heat in Southeast Asia, their quantity is relatively small compared to the extensive research focused on other regions. Strategies to mitigate the effects of extreme heat on mental and social well-being emphasise the importance of green infrastructure and public spaces. There is also a pressing need to enhance urban planning and design to ensure adaptation measures include at-risk, lower-income communities. Understanding the complexities of the risks and impacts of extreme heat on urban populations is crucial for developing effective, context-specific adaptation strategies that prioritise the needs of vulnerable populations and promote equitable, sustainable urban development.
Friction stir processed magnesium matrix surface composites: a comprehensive review
Authors: Kang Amardeep Singh , Singh Ravinder Pal , Singla Shivali , Kumar Abhinav 
Published: November 2024

Abstract
Nowadays modern materials are tailored using different manufacturing techniques. Usually, material surface is modified by even distribution of reinforcement particles/ fibres up to a certain depth. The developed surface metal matrix composites (MMCs) exhibit superior metallurgical, mechanical and electrochemical properties in contrast to base materials. These surface MMCs have potential applications in biomedical, automotive, aerospace and power industries. Many techniques have been used to develop these surface MMCs, however, the friction stir processing (FSP) has gained wide popularity. This review paper summarizes the effects of different FSP parameters on the metallurgical, mechanical and electrochemical properties of developed surface composites. Furthermore, the effects of secondary phase particles on the Magnesium-matrix surface composites are also comprehensively discussed.
SSDSNet: a dual-stream state-space network for efficient image denoising with long-range dependency modeling
Authors: Chen Ling , Xia Xun 
Published: November 2024

Abstract
In recent years, advancements in deep learning architectures such as Convolutional Neural Networks (CNNs) and Transformers have significantly enhanced the field of image denoising. Nevertheless, current denoising techniques often encounter challenges stemming from inherent local inductive biases or the quadratic computational demands of their designs. Recently, Selective Structured State Space Models, particularly exemplified by Mamba, have demonstrated substantial promise in capturing long-range dependencies with linear computational complexity. Despite their potential, these models have not been extensively explored for low-level computer vision applications. In this paper, we present the Dual-Stream State-Space Module (DSSM), a simple yet powerful model tailored for image denoising tasks. The DSSM integrates convolutional operations with the Mamba model, thereby enhancing the ability to extract both local features and global contextual information. This dual-stream framework effectively utilizes the structured nature of local image patches while adeptly modeling long-range interactions, resulting in feature representations optimized for denoising. Comprehensive experiments validate the efficacy of our approach. Notably, on the SIDD dataset, our model matches the performance of leading state-of-the-art methods, maintaining a global receptive field with comparable computational efficiency.
Calibrating Bayesian generative machine learning for Bayesiamplification
Authors: Bieringer S , Diefenbacher S , Kasieczka G , Trabs M 
Published: November 2024

Abstract
Recently, combinations of generative and Bayesian deep learning have been introduced in particle physics for both fast detector simulation and inference tasks. These neural networks aim to quantify the uncertainty on the generated distribution originating from limited training statistics. The interpretation of a distribution-wide uncertainty however remains ill-defined. We show a clear scheme for quantifying the calibration of Bayesian generative machine learning models. For a Continuous Normalizing Flow applied to a low-dimensional toy example, we evaluate the calibration of Bayesian uncertainties from either a mean-field Gaussian weight posterior, or Monte Carlo sampling network weights, to gauge their behaviour on unsteady distribution edges. Well calibrated uncertainties can then be used to roughly estimate the number of uncorrelated truth samples that are equivalent to the generated sample and clearly indicate data amplification for smooth features of the distribution.