bluuebunny/crossref_metadata_2025_split huggingface dataset:
A new global hybrid map of annual herbaceous cropland at a 500 m resolution for the year 2019
Authors: Fritz Steffen , Lesiv Myroslava , See Linda , Schepaschenko Dmitry , Pérez Guzmán Katya , Laso Bayas Juan Carlos , Schepaschenko Maria , Georgieva Ivelina , Collivignarelli Francesco , Meroni Michele , Kerdiles Hervé , Rembold Felix , McCallum Ian 
Published: August 2024

Abstract
The global spatial extent of croplands is a crucial input to global and regional agricultural monitoring and modeling systems. Although many new remotely-sensed products are now appearing due to recent advances in the spatial and temporal resolution of satellite sensors, there are still issues with these products that are related to the definition of cropland used and the accuracies of these maps, particularly when examined spatially. To address the needs of the agricultural monitoring community, here we have created a hybrid map of global cropland extent at a 500 m resolution by fusing two of the latest high resolution remotely-sensed cropland products: the European Space Agency’s WorldCereal and the cropland layer from the University of Maryland. We aggregated the two products to a common resolution of 500 m to produce percentage cropland and compared them spatially, calculating two kinds of disagreement: density disagreement, where the two maps differ by more than 80%, and absence-presence of cropland disagreement, where one map indicates the presence of cropland while the other does not. Based on these disagreements, we selected continuous areas of disagreement, referred to in the paper as hotspots of disagreement, for manual correction by experts using the Geo-Wiki land cover application. The hybrid map was then validated using a stratified random sample based on the disagreement layer, where the sample was visually interpreted by a different set of experts using Geo-Wiki. The results show that the hybrid product improves upon the overall accuracy statistics in the areas where the underlying cropland layer from the University of Maryland was improved with the WorldCereal product, but more importantly, it represents an improved spatially explicit cropland mask for early warning and food security assessment purposes.
Contrasting East Asian climate extremes in 2020 and 2022 tied to zonal flow
Authors: He Chao , Collins Matthew , Zhou Tianjun , Jiang Xingwen , Wu Peili , Dunstone Nick 
Published: August 2024

Abstract
Subtropical East Asia (STEA) experienced a historic flood in the summer of 2020, and historic drought and heatwaves in the summer of 2022. Previous studies emphasized the role of western Pacific subtropical high (WPSH), but there is a paradox that the contrasting climate extremes over STEA in 2020 and 2022 are both associated with anomalously strong WPSH. Given that local vertical motion has a dominant control on precipitation variability, here we investigate the mechanism for the variability of vertical motion in STEA. In most extratropical regions of the Northern Hemisphere, ascent (descent) motion aligns with southerly (northerly) flow in the troposphere due to the northward tilting isentropic surfaces. However, isentropic surfaces tilt eastwards over STEA in the summer due to the existence of a strong warm center over the Tibetan Plateau (TP). Thus, the ascent motion over the STEA is insensitive to the strength of southerly flow related to the intensity of the WPSH but sensitive to the strength of westerly flow related to the meridional shift of subtropical jet. The notably strong WPSH in 2020 and 2022 increased water vapor transport into STEA but had little impact on atmospheric vertical motion. However, the East Asian subtropical jet displaced southwards (northwards) in the summer of 2020 (2022), leading to anomalous westerly (easterly) flows in the mid-upper troposphere from TP to STEA on the jet’s southern flank, prompting anomalous ascent (descent) motion in STEA that contributed to the flood (drought) conditions in 2020 (2022). Our results highlight the essential role of anomalous zonal flow in generating surface climate extremes over STEA in the summer because of its strong control of vertical motion.
Graph limit of the consensus model with self-delay
Authors: Haskovec Jan 
Published: August 2024

Abstract
It is known that models of interacting agents with self-delay (reaction-type delay) do not admit, in general, the classical mean-field limit description in terms of a Fokker–Planck equation. In this paper we propose the graph limit of the nonlinear consensus model with self-delay as an alternative continuum description and study its mathematical properties. We establish the well-posedness of the resulting integro-differential equation in the Lebesgue Lp
space. We present a rigorous derivation of the graph limit from the discrete consensus system and derive a sufficient condition for reaching global asymptotic consensus. We also consider a linear variant of the model with a given interaction kernel, which can be interpreted as a dynamical system over a graphon. Here we derive an optimal (i.e. sufficient and necessary) condition for reaching global asymptotic consensus. Finally, we give a detailed explanation of how the presence of the self-delay term rules out a description of the mean-field limit in terms of a particle density governed by a Fokker–Planck-type equation. In particular, we show that the indistinguishability-of-particles property does not hold, which is one of the main ingredients for deriving the classical mean-field description.
Study on antibacterial characteristics and mechanism of synergistic modification of calcined gypsum from phosphogypsum by inorganic antibacterial materials
Authors: Fu Juan , Fang Shuang-Ming , Luo Jie , Peng Zhu , Li Zi-Ling , Cheng Jin-Ke 
Published: August 2024

Abstract
Mold on the phosphogypsum wallboard seriously hinders the resource utilization of phosphogypsum, and incorporating inorganic antibacterial materials can effectively inhibit mold growth. In this study, Escherichia coli and wallboard mold were used as experimental strains, and the antibacterial activity of antibacterial material-modified calcined gypsum from phosphogypsum (CPG) was determined using the inhibition zone method and mold surface growth area analysis. Characterization techniques such as XRF, XRD, and SEM were used to study the phase composition and microstructure of the samples, and an antibacterial model was constructed to explore the antibacterial mechanism. The results indicated that using E. coli as an indicator bacterium, ZnO-0.05TiO2-CPG exhibited the best bactericidal effect, while ZnO-CPG exhibited the best bacteriostatic effect. Against mold, ZnO contents of 2.5% or 5% demonstrated strong antibacterial properties, with compressive strengths of 10.1 MPa and 9.95 MPa, respectively, meeting the requirements of ≥3.50 MPa for compressive strength according to the ‘Lightweight Partition Plates for Building’ standard (GB/T 23451 2009). The superior antibacterial performance of ZnO compared to TiO2 is attributed to the slow release of Zn2+, which disrupts cell membranes and the generated reactive oxygen species inhibit cell growth.
Forming quality and static properties of self-piercing riveted joints of hot-rolled steel and aluminum alloy sheets
Authors: Jia Yinglian , He Shisong , Li Xiaoyang 
Published: August 2024

Abstract
The self-piercing riveting (SPR) Forming and tensile tests of hot-rolled steel sheet BR1200HS and aluminum alloy sheet AA 6082-T6 were simulated by Simufact Forming software. The test results show that the diameter of the rivet leg opening, which is the most important parameter affecting the mechanical properties of the joints, shows a first increase and a second decrease with the increase of rivet length, and the Max. tensile loads of the joints have the same variation law. The larger the diameter of the rivet leg opening, the greater the Max. tensile load of the joint, and the greater the effective plastic strain of the rivet of the joint. The rivet length of the joints in the five preferred SPR formation schemes obtained were all 6.5 mm, and only one scheme had a rivet hardness of H4, the rest were H5. The SPR experiment is used to verify the current finite element simulation data can get the final research conclusion. The finite element simulation (FEM) would greatly reduce the test times of the SPR test, save the test consumables and save the test cost.
Strength, microstructure and bonding mechanism of borosilicate glass-to-SA105 carbon steel seals
Authors: Liu Zheng , Cai Yangyang , Gong Keqian , Zhou Chao , Wang Chen , Zhao Yuna , Zhang Yong 
Published: August 2024

Abstract
The bonding strengths, microscopic characteristics and fracture properties of borosilicate glass-to-SA105 carbon steel seals were investigated, and two different glass-to-metal bonding mechanisms were compared. First, a mechanical interlocking mechanism was found via precipitates formed from chemical reactions at the interface of the seal bonded to unoxidized SA105 carbon steel. Second, a transitional layer mechanism was proven by the dissolution of metal oxides, which was on the surface of preoxidized SA105 carbon steel, into the glass. The bonding strength results showed that both mechanisms effectively contributed to the joining of dissimilar phases, but the effect of the latter mechanism was more prominent than that of the former mechanism. Various microstructures and chemical compositions of the surface oxide scales were obtained by applying different preoxidation conditions to SA105 carbon steel. Additionally, different sealing interfaces were reported through this process. The width of the interfacial transitional layer ranged from 0.5 μm to 1.5 μm, and the strength of the seal was closely related to this width. The sealing of SA105 carbon steel that was preoxidized at 800 °C for 30 min with a moderate width of the transitional layer had an optimal shear strength of 25.4 MPa. However, a wide transitional layer composed of the remaining oxide scales deteriorated the strength of the seal. In addition, fracture analysis of the seals after the shear test was conducted, and the intrinsic correlations between the macroscopic shear strength and microscopic bonding mechanism were established. The present work should provide a reference for the characterization of bonding strength in joining dissimilar materials.
Study on microstructure and mechanical properties of 5052 aluminum alloy MIG welded joint for high-speed train
Authors: Liu Shuang , Liu Zhanqi , Wang Haijiang , Liang Jianhui , Zhu Xiaoou 
Published: August 2024

Abstract
In this paper, the MIG welding process is utilized to weld a 3 mm thick 5052 aluminum alloy plate by using ER5356 welding wire as filler. The effects of different welding speeds on the microstructure and mechanical properties of the weld are systematically studied utilizing a metallographic microscope, x-ray diffractometer, scanning electron microscope, room temperature tensile, and microhardness. It was found that there were pore defects in the samples at lower or higher welding speeds, and there was no penetration at the maximum welding speed. When the welding speed is 650 mm min−1, the weld is well-formed, the surface is flat without pores, the fish scale is evenly distributed, and the weld shows good penetration. The intermetallic compounds of all the welds are mainly composed of α(Al), Mg2Si, Al3Fe, and Al3Mg2. The mechanical properties of the samples show that the hardness of the weld reaches the maximum value of 56.7HV at this welding speed, and the tensile strength and elongation are 210 MPa and 14.3%, respectively. The fracture is located at the junction of the base metal and the heat-affected zone, and the fracture type showed typical ductile fracture.
Novel polybenzoxazine-based arylidene moiety modified cellulose acetate for enhanced antifouling properties
Authors: Klfout Hafsah , Asiri Abdullah M , Alamry Khalid A , Hussein Mahmoud A 
Published: August 2024

Abstract
Marine fouling is a widespread problem in the maritime industry, causing significant damage to equipment and vessels. Polybenzoxazine (PBz) is a resin that is both remarkable and captivating, and it has a wide range of sophisticated uses. Due to their distinctive characteristics, benzoxazines have sparked the interest of scholars globally. However, most benzoxazine resin production and processing depend on petroleum resources, particularly those based on bisphenol A. This study aimed to create new benzoxazine monomers using bio-based raw materials, primarily motivated by the environmental ramifications. The main goal of this study is to synthesize a benzoxazine molecule, specifically (2E,6E)-2,6-bis(3-(2-hydroxyethyl)-3,4-dihydro-2H-benzo[e][1,3]oxazin-6-yl)methylene) cyclohexane-1-one, abbreviated as (CHPE), by employing an arylidene base. Later, the chemical was used as a modifier for the cellulose acetate (CA) matrix to create film samples. The primary objective is to evaluate the effectiveness of these film samples in preventing fouling. The CHPE molecule was produced using a bis(arylidene) cyclohexanone diol and analyzed using Fourier transform infrared (FTIR) and Nuclear magnetic resonance (NMR) spectroscopic techniques, respectively. The films were fabricated by blending various weight proportions. The composition of the (CHPE-CA) films was determined by FTIR analysis, while their morphology was examined using scanning electron microscopy (SEM). The thermal stability of the films was studied using Thermal Gravimetric Analysis (TGA). This study investigated the antifouling properties of polymer sheet compositions containing varying amounts of CA at two different processing temperatures, 180 °C and 200 °C and without curing. The results demonstrated the potential of incorporating CA into the polymer matrix to enhance antifouling performance. Among the polymer compositions tested, the 20% CA composition exhibited the highest percentage reduction in fouling at both processing temperatures, suggesting that a small amount of CA can contribute to effective antifouling properties.
Technical note: MR image-based synthesis CT for CyberKnife robotic stereotactic radiosurgery
Authors: Jiao Shengxiu , Zhao Xiaoqian , Zhou Peng , Geng Mingying 
Published: August 2024

Abstract
The purpose of this study is to investigate whether deep learning-based sCT images enable accurate dose calculation in CK robotic stereotactic radiosurgery. A U-net convolutional neural network was trained using 2446 MR-CT pairs and used it to translate 551 MR images to sCT images for testing. The sCT of CK patient was encapsulated into a quality assurance (QA) validation phantom for dose verification. The CT value difference between CT and sCT was evaluated using mean absolute error (MAE) and the statistical significance of dose differences between CT and sCT was tested using the Wilcoxon signed rank test. For all CK patients, the MAE value of the whole brain region did not exceed 25 HU. The percentage dose difference between CT and sCT was less than ±0.4% on GTV (D2(Gy), −0.29%, D95(Gy), −0.09%), PTV (D2(Gy), −0.25%, D95(Gy), −0.10%), and brainstem (max dose(Gy), 0.31%). The percentage dose difference between CT and sCT for most regions of interest (ROIs) was no more than ±0.04%. This study extended MR-based sCT prediction to CK robotic stereotactic radiosurgery, expanding the application scenarios of MR-only radiation therapy. The results demonstrated the remarkable accuracy of dose calculation on sCT for patients treated with CK robotic stereotactic radiosurgery.
Anatomy-constrained synthesis for spleen segmentation improvement in unpaired mouse micro-CT scans with 3D CycleGAN
Authors: Jiang Lu , Xu Di , Sheng Ke 
Published: August 2024

Abstract

Objective. Auto-segmentation in mouse micro-CT enhances the efficiency and consistency of preclinical experiments but often struggles with low-native-contrast and morphologically complex organs, such as the spleen, resulting in poor segmentation performance. While CT contrast agents can improve organ conspicuity, their use complicates experimental protocols and reduces feasibility. We developed a 3D Cycle Generative Adversarial Network (CycleGAN) incorporating anatomy-constrained U-Net models to leverage contrast-enhanced CT (CECT) insights to improve unenhanced native CT (NACT) segmentation. Approach. We employed a standard CycleGAN with an anatomical loss function to synthesize virtual CECT images from unpaired NACT scans at two different resolutions. Prior to training, two U-Nets were trained to automatically segment six major organs in NACT and CECT datasets, respectively. These pretrained 3D U-Nets were integrated during the CycleGAN training, segmenting synthetic images, and comparing them against ground truth annotations. The compound loss within the CycleGAN maintained anatomical fidelity. Full image processing was achieved for low-resolution datasets, while high-resolution datasets employed a patch-based method due to GPU memory constraints. Automated segmentation was applied to original NACT and synthetic CECT scans to evaluate CycleGAN performance using the Dice Similarity Coefficient (DSC) and the 95th percentile Hausdorff Distance (HD95p). Main results. High-resolution scans showed improved auto-segmentation, with an average DSC increase from 0.728 to 0.773 and a reduced HD95p from 1.19 mm to 0.94 mm. Low-resolution scans benefited more from synthetic contrast, showing a DSC increase from 0.586 to 0.682 and an HD95p reduction from 3.46 mm to 1.24 mm. Significance. Implementing CycleGAN to synthesize CECT scans substantially improved the visibility of the mouse spleen, leading to more precise auto-segmentation. This approach shows the potential in preclinical imaging studies where contrast agent use is impractical.
Seismocardiography and echocardiography: the correlation in the systolic complex
Authors: Kolind Christoffer Mejling , Tange Alberte Bjerre , Sten Sandra Toft , Sonne Maria Mathilde Sauer , Agam Ahmad , Søgaard Peter , Schmidt Samuel 
Published: August 2024

Abstract

Aim. This study aimed to investigate the correlation between seismocardiographic and echocardiographic systolic variables and whether a decrease in preload could be detected by the seismocardiography (SCG). Methods. This study included a total of 34 subjects. SCG and electrocardiography were recorded simultaneously followed by echocardiography (echo) in both supine and 30◦ head-up tilted position. The SCG signals was segmented into individual heartbeats and systolic fiducial points were defined using a detection algorithm. Statistical analysis included correlation coefficient calculations and paired sample tests. Results. SCG was able to measure a decrease in preload by almost all of the examined systolic SCG variables. It was possible to correlate certain echo variables to SCG time intervals, amplitudes, and peak to peak intervals. Also, changes between supineand tilted position of some SCG variables were possible to correlate to changes in echo variables. LVET, IVCT, S’, strain, SR, SV, and LVEF were significantly correlated to relevant SCG variables. Conclusion. This study showed a moderate correlation, between systolic echo and systolic SCG variables. Additionally, systolic SCG variables were able to detect a decrease in preload.
GAN-ACNN: a design decision-making algorithm based on EEG signals from different brain regions
Authors: Yang Bokai , Xue Huang , Ye Ziming , Yang Jingmin 
Published: August 2024

Abstract
Decision-making is an integral part of an individual’s life. Due to the small amount of data in the art design decision dataset, we increase the amount of data using data augmentation. However, different brain regions have distinct effects on the accuracy of art design decisions, so we divide the brain into four areas and investigate the influence of each on the results. We collect electroencephalogram (EEG) data from 16 subjects, apply a band-pass filter to filter it, and then feed it into a generative adversarial network (GAN) for data augmentation. The augmented EEG data is input to a convolutional neural network with a self-attention mechanism (ACNN). The experimental results show that the degree of influence of different brain regions is: right frontal lobe > right parietal-temporal-occipital lobe > left frontal lobe > left parietal-temporal-occipital lobe. In view of this, we find the six optimal channels for art design decisions, and their prediction results are better than those of all channels. In addition, our GAN-ACNN model achieves an average accuracy of 93.51%, which is an effective method. Finally, we also classify the DEAP dataset to evaluate the robustness of the model.
Faster-YOLOv5: real-time deep learning for sea cucumber defect recognition and classification
Authors: Meng Huang , Wei Honglei 
Published: August 2024

Abstract
To tackle the challenges of precise recognition and classification of sea cucumbers in food processing, including issues like external lighting conditions, hardware limitations, and slow inference speeds, we propose a lightweight Faster-YOLOv5 network for the recognition and classification of common sea cucumber defects. Firstly, we utilize the GhostNetV2 network fused with the Mixed Local Channel Attention (MLCA) mechanism as the backbone, enhancing model feature representation and lightweight characteristics to ensure efficient operation in resource-limited environments. Additionally, by introducing an Auxiliary Head (Aux head), we bolster training stability and efficiency, guiding the model to focus on intermediate feature learning, thereby improving generalization and accuracy in detecting various target categories. Lastly, the MPDIoU loss function is employed to optimize the intersection over union between predicted and ground truth bounding boxes, aiming to reduce false detection rates and accelerate model training convergence. The experimental results demonstrate that the network achieves a precision of 96.83% and an mAP@0.5 of 95.12% in sea cucumber recognition, with an inference speed of 82.71 frames per second. This method balances accuracy and inference speed, offering a viable solution for similar problems.
A generalizable approach to imbalanced classification of residential electric space heat
Authors: Lee Christopher S , Zhao Zhizhen , Stillwell Ashlynn S 
Published: August 2024

Abstract
Changes in climate and energy technologies motivate a greater understanding of residential electricity usage and its relation to weather conditions. The recent proliferation of smart electricity meters promises an influx of new datasets spanning diverse cities, geographies, and climates worldwide. However, although analytics for smart meters is a rapidly expanding field of research, issues such as generalizability to new data and robustness to data quality remain underexplored in the literature. We characterize residential electricity consumption patterns from a large, uncurated testbed of smart electricity meter data, revealing challenges in adapting existing methodologies to datasets with different scopes and locations. We propose a novel feature—the proportion of electricity used below a temperature threshold—summarizing a household’s demand-temperature profile that is productive for identifying electric primary space heating in a smart meter data set of Chicago single-family residences. Weighted logistic regression using the proportion of electricity consumed below a selected low temperature mitigates difficulties of the dataset such as skew and class imbalance. Although the limitations of the dataset restrict some approaches, this experiment suggests advantages of the feature that can be adapted to study other datasets beyond the identification of space heating. Such data-driven approaches can be valuable for knowledge distillation from abundant, uncurated smart electricity meter data.