bluuebunny/crossref_metadata_2025 huggingface dataset:
A Fetal Health Classification Approach Based on Broad Learning System
Authors: Li Mingxuan , Lin Yifeng , Yang Yuer
Published: October 2024

Fetal health problems are still a serious issue nowadays, affecting mothers and their children. The rate of mortality caused by fetal health problems is notably high in some areas of the earth, especially in lower-income countries. At present, besides the conventional clinical assessment, the methods of fetal health classification are mainly traditional machine learning and deep learning, such as KNN, SVM, Logistic Regression, and Naive Bayes, with the problems of low precision or long training time. In this study, we apply the broad learning system (BLS) to fetal health classification. The data set is sourced from the UCI ML repository database, which is made available by the Biomedical Engineering Institute and the University of Porto’s Faculty of Medicine. With the training accuracy of 92%, training time of 0.52s, and testing accuracy of 90%, the experimental results that highly satisfactory on BLS in the experiment.
UAV Position Optimization for Servicing Ground Users Based on Deep Reinforcement Learning
Authors: Gao Feiyu , Wang Zichen , Liu Xuan , Liu Shumei
Published: October 2024

A Deep Q-Network (DQN) algorithm is proposed for optimization of UAVs, which can increase the communication rate of multiple users within a certain area. The UAV is able to automatically adjust its position in 3D by means of the DQN Agent’s design and training, and then get the best UAV placement location. Furthermore, the Double Deep Q-Network (Double DQN) has been researched. It has been proved that this method has higher efficiency and higher convergence rate compared with traditional DQN for locating optimal UAV position. In this paper, we perform a complex simulation of a random distribution of users in a simulated region. The experimental results indicate that UAV is able to locate the optimal position with maximum mean transfer rate, and reduce the distance from central point to customer centre, thus increasing the communication quality. This study not only verifies the effectiveness of deep reinforcement learning in dynamic positioning optimization, but also provides new insights for the optimization design of future intelligent communication systems.
Spatio-temporal Evolution of Total Nitrogen in Xixi River Based on Sentinel-2 Remote Sensing Images
Authors: Wei Chenyan , Fu Haiyan , Zheng Yuanmao
Published: October 2024

Remote sensing technology holds significant advantages in the analysis of aquatic ecological environments, including rapid processing speed, abundant information, extensive spatial coverage, and high reliability. Total nitrogen, as a key indicator for assessing the eutrophication state of water bodies, has important application value in evaluating aquatic ecological environments and water quality monitoring. By analyzing the spatiotemporal changes in the concentration of total nitrogen, the dynamic changes in water quality can be effectively reflected. This study selected the Xixi River in Tong’an District, Xiamen City, as the research subject, using six Sentinel-2 satellite remote sensing image data from 2018 to 2023 to construct an empirical regression model for remote sensing inversion of the total nitrogen concentration in the study area. The spatiotemporal evolution of the research results was analyzed, to achieve real-time monitoring and assessment of water quality. The study results indicate that from 2018 to 2023, the total nitrogen concentration in the Xixi River showed a cyclical fluctuation pattern of first increasing, then decreasing and increasing again. The concentration reached its lowest in 2021, at 2.415 mg/L, and the research findings can provide important support for the sustainable development of the river.
Improving the UNet with channel attention mechanism for Taihu Lake water body recognition
Authors: Nie Shiliang , Zhao Limin , Jiang Mingyong , Li Zhiliang , Liu Shumin , Li Jiaguo , Wan Wei , Sun Yuan
Published: October 2024

Accurate recognition of surface water bodies is important for disaster management and resource planning. To explore a higher-precision water body recognition method, propose an improved channel attention mechanism UNet (ECA-UNet) water body recognition model based on Sentinel-2A remote sensing images. Utilizing ECA-UNet, UNet, PSPnet, and DeeplabV3, as well as the traditional normalized water body index (NDWI), recognize the water body in the Taihu Lake area. Through comparative analysis, the following main conclusions are drawn: (1) The recognition accuracy of the deep learning network model is better than the traditional NDWI method, among which the ECA-UNet network model has the highest accuracy of 98.67%, and the lowest recognition accuracy of NDWI is 89.06%. (2) The ECA-UNet network model can effectively extract water body recognition targets, has a better recognition effect on local features of water bodies, and can improve the water body extraction effect. The above results show that the improved channel attention mechanism ECA-UNet has the highest accuracy in water body recognition in Taihu Lake, which provides a reference for subsequent research and applications in this field.
A land parcel segmentation method for remote-sensing images based on an improved U-Net network
Authors: Wang Zitang
Published: October 2024

Land parcel segmentation in remote-sensing images aims to achieve pixel-level content analysis of the images, extracting and classifying categories of interest within the remote-sensing data. It holds significant practical value in areas such as urban and rural planning, flood control, and disaster relief, attracting widespread attention in the industry. With the continuous development of remote-sensing technology, deep learning has demonstrated substantial potential in the analysis of remote-sensing images. In this study, leveraging deep learning techniques to address the challenge of land parcel segmentation in remote-sensing images, we employed the U-Net architecture and further enhanced it by incorporating channel and spatial attention mechanisms. This improvement aims to enhance the model’s ability to identify complex land parcel boundaries and structures, ultimately achieving more accurate land parcel segmentation.
Remote sensing extraction of aquaculture ponds in China’s coastal zone based on random forest
Authors: Zhang Peng , Gui Fukun , Feng Dejun , Zhang Guangyang
Published: October 2024

Aquaculture ponds are one of the most important land use types in coastal areas of China. However, the rapid expansion of aquaculture ponds threatens coastal ecosystems, which is the problem the sustainable development goals seek to address. Studying changes at its scale is crucial to exploring its drivers and understanding its impacts, which is a focus of sustainable management of aquaculture. To scientifically manage the coastal aquaculture industry, it is necessary to understand its spatial size changes. Given the problems of low extraction efficiency and low accuracy in traditional remote sensing extraction methods for large-scale areas, this study aims to use long-term sequence remote sensing images and geographical information methods to evaluate the performance of aquaculture ponds in coastal areas of China during 2019-2023. This research is based on the Google Earth Engine platform and proposes a random forest classification method for aquaculture pond extraction, taking 20 km inland of China’s coastal zone as the research area, and extracting coastal aquaculture ponds for five years from 2019 to 2023. The results show: (1) The areas of coastal breeding ponds from 2019 to 2023 were 9, 425 km², 9, 526 km², 8, 992 km², 9, 092 km², and 8, 883 km² respectively. The breeding ponds have experienced a significant decrease; (2) Breeding ponds are mainly distributed in China’s coastal plains and bay areas, with the Bohai Rim, Yangtze River Delta, and Pearl River Delta being particularly concentrated. In terms of area changes, compared with 2019, the area of China’s coastal aquaculture ponds has decreased by 5.75%, and the aquaculture area has shrunk by approximately 542 km². This change process is dynamic, going through two stages of rapid expansion and gradual shrinkage; (3) Taking Hainan Province as an example, combined with the factors affecting the distribution and area size of coastal breeding ponds obtained by the correlation analysis method, the statistical analysis concluded that the discharge of ammonia nitrogen, phosphorus, and other water pollutants is closely related to the size of the breeding ponds. The positive correlation of aquaculture output and the negative correlation of fishery output value reflects the increasing intensification of aquaculture ponds to a certain extent. This method can be applied to identify and extract coastal ponds, which is beneficial to the formulation of scientific and reasonable coastal land planning and is of great significance in promoting the sustainable development of the coastal ecological environment.
Remote sensing image fusion method based on depth feature extraction
Authors: Xiao Yunlong , Guo Xinyi
Published: October 2024

Remote sensing image fusion involves combining data from various remote sensing sensors or merging multiple images acquired by the same sensor but in different spectral bands to create a superior quality composite image, high resolution, multi-band, and multi-temporal remote sensing image through certain algorithms and technologies. By utilizing fusion techniques, remote sensing images of varying bands, resolutions, and phases can be combined to enhance the accuracy of ground object information. This paper introduces a remote sensing image fusion method that leverages deep learning for depth feature extraction. Swin Transformer makes full use of the characteristics of the relationship between adjacent pixels, and adaptively extracts panchromatic image (PAN) and multispectral image (MS) features through two adaptive feature extraction channels. High-quality satellite data is employed to confirm the efficacy of the suggested approach, with the findings demonstrating strong performance in ERGAS, SCC, SSIM, and PSNR, and other evaluation indexes and has good spectral information fidelity and spatial information integration degree.
Time series cube data construction and land use attribute change study based on high-resolution imagery
Authors: Zhao Jianghong , Xu Ailin , Yu Haiquan , Zhao Jifu
Published: October 2024

In order to better understand the changes in land use attributes, comprehend the drivers of land use changes, assess their environmental and economic impacts, and provide a scientific basis and data support for land use planning, environmental protection, and agricultural production, this study is based on Qiu County’s high-resolution image data from 2020-2022 and makes use of the latest research results of hyperspectral remote sensing technology to analyze its changes in land use attributes by establishing the time of the high-resolution image sequence cube data and solving the characteristic variables through band operations to quickly and accurately calculate a variety of remote sensing indicators and analyze the changes in their land use attributes. The results of the study show that vegetation in Qiu County will change significantly between 2020 and 2022, mainly due to seasonal and land-use changes; Water bodies will change less but more consistently; And buildings will change less, mainly focusing on villages and industrial land.
Gross error detection method for high-precision data processing of beidou satellite navigation system
Authors: Zhang Jingfa , Li Jianye , Fu Yunjie , Hong Zhijia , Song Zhenkang
Published: October 2024

Gross error detection is indispensable in the Beidou high-precision positioning process. In this paper, the ratio difference of cycle slip detection using the constant relationship between the observation values of any two different frequency data in the tri-frequency data is proposed. The algorithm is susceptible to abnormal changes in observations. It can detect abnormal changes of more than 0.1 weeks of observations. When the three-frequency data and three frequencies jump at the same time, the MW combination must be combined. The resolution accuracy is 1.6 weeks. Any other single-frequency or the resolution accuracy of dual-frequency simultaneous hopping can reach 0.1 weeks. Example validations were performed and found to be better than the TurbiEdit algorithm for roughness detection.
Spatial-spectral attention state-space fusion network for tree carbon estimation using multi-source data
Authors: Fu Yawen , Hu Dong , Zhou Yuxin , Sun Zhixiong , Zhang Shuyu
Published: October 2024

Amid rapid industrialization and urbanization, global warming and the urban heat island effect are intensifying. There is an urgent need for rapid and accurate monitoring of carbon storage in urban vegetation to assess and mitigate these environmental issues. While methods exist for estimating above-ground carbon (AGC) stocks in individual trees using deep learning, fewer studies integrate multi-source remote sensing data with these techniques. This study introduces a network that leverages spatial-spectral attention and state-space models, called the spatial-spectral attention state-space fusion network (S4FNet). S4FNet utilizes UAV hyperspectral imaging (HSI) data, light detection and ranging (LiDAR) data, and RGB data to estimate AGC storage in individual trees. This study conducted experiments at two sites, the South and North areas of Shenzhen University’s Yuehai Campus, Shenzhen City, Guangdong Province, China, and compared S4FNet with eight traditional machine learning methods and a deep learning method. The experimental results demonstrate that S4FNet achieves the best performance across all metrics, confirming its excellent capability in predicting AGC stocks using multi-source remote sensing data.
Research on on-orbit relative radiometric calibration method based on solar diffuse reflector hyperspectral camera
Authors: Zhang Wenjie , Yuan Fuxiang , Shi Haiyang
Published: October 2024

In the original image data obtained by optical remote sensing satellite sensors, there is stripe noise caused by inconsistent probe response, which will seriously affect the application effect and accuracy of the image. The importance of relative radiometric calibration is that it can eliminate the stripe noise in the image, thus improving the quality and clarity of the image. In this paper, a relative radiometric calibration method based on the data of a solar diffuse reflector downloaded from the satellite is proposed. The relative radiation calibration coefficient is calculated by using the least square method by obtaining the calibration image of the on-board diffuse reflector covering all the detectors. To verify the method proposed in this paper, the on-board relative radiometric calibration experiment is carried out by using the on-orbit hyperspectral camera of a terrestrial ecological carbon monitoring satellite, and the calibration effect of the calibration coefficient on the original image is tested, and the relative radiometric calibration accuracy is quantitatively analyzed. The experimental results show that the calibration coefficient can effectively eliminate the band noise of the original hyperspectral image. From the quantitative evaluation, the signal-to-noise ratio index of the corrected hyperspectral image is greater than 200, and the generalized noise index is better than 3%, which achieves a good calibration effect and meets the requirements of high-quality remote sensing image application. It provides a reliable guarantee for quantitative remote sensing applications during the satellite’s on-orbit operation.
Research on hexagonal grid off-road path planning algorithm considering multiple factors
Authors: Kong Yunbo , Chang Ming , Zhang Zhixin , Liang Rui , Zhao Xi
Published: October 2024

This article proposes a hexagonal grid off-road path planning algorithm that takes into account multiple factors for the path planning problem of motor vehicles in complex off-road environments. This method first uses a hexagonal grid model to abstract and quantify the terrain factors that affect off-road vehicles. Then, the Analytic Hierarchy Process is used to determine the weight of each factor on the impact of off-road vehicle traffic. Finally, by comprehensively considering the elevation, slope, and surface coverage elements, as well as the search efficiency of the algorithm, the cost function and heuristic function of the A * algorithm are further designed and optimized. The experimental results show that the method proposed in this paper outperforms existing algorithms in terms of pathfinding results and search efficiency, thus verifying the effectiveness and feasibility of the algorithm proposed in this paper.
Wireless sensor fusion localization method for target vehicles in a collaborative environment of vehicle road trajectory information
Authors: Zhang Yusen , Qi Tianxing , Zhang Chao , Guo Tianhong , Wu Jiangong
Published: October 2024

Vehicle positioning technology is the foundation for achieving traffic management. Vehicle positioning errors are significant in complex environments, making it challenging to ensure positioning accuracy. To reduce positioning errors, this paper explores a wireless sensor fusion localization method for target vehicles in a collaborative environment of vehicle road trajectory information. Based on wireless sensor data, we achieve collaborative environmental perception of vehicle and road trajectory information and construct a target vehicle trajectory optimization model. Through a fuzzy neural network, data from different sensors are integrated to overcome the problem of limited positioning accuracy of a single sensor in a complex environment. The experimental results show that both the heading angle and rolling angle errors float between −0.1° and 0.1°, and the positioning error is less than 0.1 m, which proves that the method has high positioning accuracy and good application value.
Multi-reference source aircraft classification network based on unknown class prototype estimation
Authors: Guan Huihui , Wang Yuqing , Zhao Wei , Zhang Rufei , Li Nannan , Li Dongjin
Published: October 2024

Gathering complete aircraft types for close-set tasks is challenging and costly in fine-grained aircraft classification, resulting in encountering unknown class aircraft images in real-world models. To address this problem, we propose a network called a multi-reference source fine-grained aircraft classification network (MRSN) to explicitly and implicitly distinguish known class boundaries and embed unknown classes into the sample space. Specifically, we propose an embedding module (UCPE) to synthesize an unknown class prototype to facilitate the modeling of unknown class data distribution. Besides, we introduce a concatenated multi-reference source module (CMS) that combines distance measurement and probability estimation to classify whether testing images are of unknown class or not. Our proposed MRSN innovatively extends the open-set learning paradigm to the fine-grained classification of geospatial objects rather than simple scene classification. Besides, it shows excellent performance in our constructed dataset, which demonstrates the effectiveness and progressiveness of our method.
Cloudformer-CycleGAN: an efficient cloud removal network integrating residual learning and channel spatial attention mechanism
Authors: Fang Yongli
Published: October 2024

Removing clouds from remote sensing images poses a significant challenge in image analysis. Despite the widespread application of deep learning methods in the field of cloud removal, their ability to extract and integrate contextual information still needs to be strengthened, which is crucial for describing complex terrain features in remote sensing images. Therefore, we propose a new cloud removal method, Cloudformer-CycleGAN. In this method, we replace the original CNN module in CycleGAN with a Residual Group (RG) module for significant enhancement. The introduction of the Residual Group (RG) module enables the network to focus more on local features in cloud regions, significantly reducing the problem of residual clouds during cloud removal. Experimental results show that the proposed model achieves improvements in multiple image evaluation metrics, demonstrating superior performance in the issue of cloud residue, with a significant reduction in cloud residue in the images.
Measurements of Low Optical Power with Cryostat-Based Predictable Quantum Efficient Detector at Liquid Nitrogen Temperature
Authors: Korpusenko Mikhail , Sildoja Meelis-Mait , Manoocheri Farshid , Ikonen Erkki
Published: October 2024

We have validated optical power measurements with a Predictable Quantum Efficient Detector (PQED) at liquid nitrogen temperature (77 K) at low optical power from 130 fW to 3.3 pW. Two laser wavelengths at 514 nm and 785 nm were used. The lowest measured optical power corresponds to a photon flux of 0.5·106 photons per second (785 nm). The PQED’s responsivity is linear within the relative measurement uncertainties of 8% at 0.5·106 ph/s and 1.4% at 10·106 ph/s (95% confidence level), which enables the calibration of other low photon flux detectors directly against a primary standard of optical power.
Characterization of hexagonal boron nitride quantum emitters for application in quantum radiometry
Authors: Sewidan L. , Georgieva H. , Tieben P. , Schell A. W. , López M. , Kück S.
Published: October 2024

We present the metrological characterization of single-photon emitters based on single point defects in hexagonal boron nitride (hBN) to be used in quantum radiometry. The characterization is performed in terms of their spectral characteristics, single-photon properties and stability of photon flux emission at room temperature. A statistical analysis of 563 emitters has been carried out showing that approximately one third of the photon emission can be attributed to single photon emitters. In addition, a relative calibration of two single-photon avalanche diode (SPAD) detectors using a selected hBN single-photon emitter is presented.
Hybrid trap detector sensitive at visible and telecom wavelengths
Authors: Vaigu Aigar , Kübarsepp Toomas , Rammo Matt , Ikonen Erkki
Published: October 2024

We have developed a transmission trap detector sensitive over a wide optical wavelength range. The developed device takes advantage of the smooth reflectance profile of silicon photodiodes. The detector is based on two 10 mm size photodiodes – a Si photodiode and an InGaAs photodiode. The constructed hybrid trap detector is sensitive at the wavelength range from 400 nm up to 1600 nm. The detector is designed to provide a tool for countermeasures against attacks to secure quantum communication.
Indoor Direct Comparison between High-Accuracy Pyrheliometer and Room Temperature Absolute Radiometer
Authors: Liu Wen-Chun , Yu Hsueh-Ling
Published: October 2024

This article proposes a practicable indoor method by directly comparing the pyrheliometer with the room temperature absolute radiometer (RTAR) to overcome the inconvenience of outdoor pyrheliometer calibration caused by the limitation of weather conditions. The RTAR serves as the primary standard for radiant power, irradiance, illuminance, and candela at the Center for Measurement Standards/ITRI. Given that the RTAR and pyrheliometer exhibit different sensitivity curves, the key to a successful comparison lies in designing an incident beam that enables both the RTAR and pyrheliometer to operate within their respective uniform sensitivity regions. While the indoor incident beam’s irradiance is considerably lower than solar radiation, the comparison results demonstrate a quite well measurement consistence between the RTAR and the pyrheliometer. As the indoor method is insusceptible to weather, the complex data acquisition procedures for the outdoor method can be simplified due to the stable incident beam indoors. Despite current documentary standards recommending outdoor calibration and comparison for pyrheliometer, the indoor method presented in this article can serve as a supplementary approach for assessing the accuracy of pyrheliometers during the intervals between two calibration or comparison events.
A peridynamic-based reconstruction and analysis method for short-fiber reinforced composites
Authors: Yao Zhiyang , Hu Yile
Published: October 2024

As the complex microstructure, predicting the effective elastic properties and damage mechanisms of Short-Fiber Reinforced Composites (SFRC) continues to pose a challenge. This study presents a new reconstruction and analysis method based on PeriDynamics (PD) for SFRC. The reconstruction of the surface profiles of short-fibers obtained from Micro-CT (Micro-Computed Tomography) scanning resulted in a PD computational model that accurately reflects the actual microstructure of SFRC. The results predicted the effective elastic modulus of SFRC while fiber volume fraction and distribution have impact. Micro-cracks emerge at stress concentration regions near the fiber-matrix-fiber interfaces between two adjacent fibers, and with increasing load, these cracks gradually propagate, interact, and merge with each other. Eventually, major cracks form, leading to material failure.
Study on the influence factors of the grain growth type of micro-nano silver powders prepared by liquid-phase reduction method
Authors: Ma Xiaoling , Wang Jianwei , He Huijun , Zhu Jie , Pan Xu , Ma Tianrun
Published: October 2024

The preparation was carried out by liquid-phase reduction method with AgNO3 as the oxidizing agent, ascorbic acid (C6H8O6) as the reducing agent, and polyvinyl pyrrolidone (PVPK30) as the dispersing agent. The effects of silver nitrate concentration, ascorbic acid concentration, PVPK30 concentration, solution PH value before and after the reaction, and the temperature of reaction on average particle size (D50), dispersity, and particle size uniformity of silver particles were investigated by orthogonal experiment L18 (36) with six factors and three levels. The spheroid-like silver particles with good dispersity of 400-600nm and the spheroid-like silver particles with suitable particle size uniformity of 80-100nm were successfully prepared by optimal experiments. The results of the orthogonal experiment show that the molar ratio of the reducing agent to the oxidizing agent plays a decisive role in the type of grain growth. The crystal nucleus will coagulate and grow at a higher molar ratio (⩾1.05). With the increase in molar ratio, the nucleation rate is higher, the grain growth rate is faster, and the size of silver particles is smaller.
Preparation and performance study of sludge biomass bamboo charcoal
Authors: Song Yanpeng , Zhu Jiayan , Bao Yuhang , Luo Tianwen
Published: October 2024

The purpose of this study is to explore a new low-cost and high-efficiency biochar adsorption material. The residual sludge as solid waste and fresh bamboo with fast growth and high yield were used as raw materials, modified by the KOH chemical activation method, and pyrolyzed in a tubular furnace with nitrogen atmosphere to obtain sludge biomass bamboo charcoal. In the performance test, the H2S gas adsorption experiment in a fixed bed reactor and the heavy metal adsorption experiment in soil were designed. Using different proportions of biochar, the preparation process of biochar was optimized by adjusting the raw material ratio and activation conditions. The results showed that when dealing with H2S gas, the appropriate amount of sludge can improve the adsorption effect, while the increase of bamboo component will reduce the adsorption rate. In the soil Cr(VI) restoration experiment, it was found that the best restoration effect was achieved after adding 10% biochar and applying it for 28 days, and the restoration rate reached 63.5%.
Highly efficient hydrogenation of levulinic acid into γ-valerolactone over modified bifunctional yolk-shell catalyst
Authors: Liu Mingya , Liu Yue
Published: October 2024

γ-valerolactone (GVL) is a widely used chemical raw material, which is mainly prepared by hydrogenation of levulinic acid (LA). The steps of hydrogenation and molecular lactone cyclization in the reaction make it require multi-active site catalysis. In this study, the Pd@mSiO2-CeAl catalyst was successfully prepared by doping Ce and Al to modify the Pd-based yolk-shell catalyst. It was used to catalyze LA to prepare GVL. In circumstances of mild response, 100% LA conversion and 97.5% GVL selectivity were obtained. The characterization results showed that the synergistic effect of the double acid sites (Brønsted and Lewis acid sites) and the hydrogenation sites is the key to high catalytic performance. Besides, the encapsulation strategy of the silica shell provides a stable catalytic environment for the catalyst and maintains high activity after 5 cycles.
Catalytic synthesis of DHHB using solid acids
Authors: Sun Zhendong , Wu Jinbo , Feng Baicheng
Published: October 2024

DHHB (Diethylamino hydroxybenzoyl hexyl benzoate) is a widely regarded UV absorber with a high degree of safety, excellent efficiency and good solubility characteristics. In the conventional method of DHHB synthesis, H2SO4 is not effective as a catalyst. To address this drawback, we synthesized solid acid (sulfonic acid group-modified ion exchange resin) catalysts to replace H2SO4 by suspension polymerization modification and optimized the process. The experimental results showed that the yield of DHHB could reach 85% at 110 °C for 10 h, and the conversion of DHHB could be maintained above 90% after 10 cycles of the catalyst. SEM, FT-IR characterization and analysis of the solid acid catalysts before and after use revealed that the catalysts did not show any significant changes. The use of solid acid not only improves the yield of DHHB and reduces the energy consumption in the experimental process, but also the solid acid is simple to recover, recycled and has less waste acid. This experiment successfully explored a green and economic synthesis method for synthesizing DHHB.
Effect of evaporation temperature on evaporative residue properties of waterborne polyurethane modified emulsified asphalt
Authors: Mu Minghao , Liu Xinqiang , Bi Haisong , Wang Zheng , Qian Chengduo , Liu Yifan , Liu Xiufen , Li Xue
Published: October 2024

In recent years, waterborne polyurethane (WPU) modified emulsified asphalt has attracted much attention. The conventional property of WPU-modified emulsified asphalt (WPU-MEA) is usually measured by using the evaporative residue obtained at high temperatures. In this work, WPU-MEA was prepared and the influence of evaporative temperature on the conventional performances (softening point, penetration, ductility) of the residue of WPU-MEA was investigated. Fourier Transform Infrared Spectroscopy (FTIR) and Fluorescence microscope (FM) were used to analyze the chemical structure and morphology of the evaporative residues. It was found that the evaporation dehydration temperature has a significant influence on the property of the evaporation residue of WPU-MEA. The evaporative residue performance of WPU modified asphalt was better at an evaporation temperature of 110°C, and the three conventional properties were significantly improved. Upon increasing the evaporation temperature, the conventional properties of WPU-MEA continue to decrease. As the evaporation temperature is 190°C, the conventional property of the residue is close to that of unmodified emulsified asphalt. Considering the performance index of WPU-MEA, the optimal evaporation temperature should be determined in the characterization of residue performance. This study has a guiding significance for the development of polyurethane-modified asphalt materials.
Modification of chemical vapor-phase deposition and coking resistance over HZSM-5 catalysts for toluene disproportionation
Authors: Liu Tao , Liu Jian , Liang Jingjing , Han Songtao
Published: October 2024

To achieve higher catalytic activity of toluene disproportionation and improve the p-xylene selectivity and stability of coking resistance on HZSM-5 catalysts, tetrabutyl titanate, ethyl orthosilicate and diethyl phosphite were used for chemical gas-phase deposition modification on HZSM-5 catalysts. The properties of acid sites on catalysts were characterized by infrared spectroscopy (IR) and temperature-programmed desorption of pyridine (TPD), respectively. The experimental results showed that the type of acid sites and density of weaker acid sites over HZSM-5 zeolites deposited by oxides containing Ti, Si and P in chemical vapor coating did not change while the density of stronger acid sites decreased, in which acid intensity on HZSM-5 zeolite deposited by oxides containing P enhanced obviously. Using HZSM-5 zeolites modified as catalysts of toluene disproportionation, HZSM-5 catalysts deposited by oxides containing Si and P can greatly improve both catalytic activity and coking resistance on catalysts.
Influence of oil base and gelling agent on the performance of oil gels
Authors: Song Xiaoxu , Wang Yao , Sun Mengyu , Zhao Wenying , Zhu Qingshu
Published: October 2024

Oil gels, as a novel delivery system, have broad prospects in carrying nutrients and active substances. It has been found that the properties of oil gels are closely related to the types of oil bases and gelling agents used. In this study, soybean oil, sesame oil, and coconut oil were used as oil bases, while ethyl cellulose (EC), monoglycerides (MG), herbal extracts (HE), and hydroxypropyl methylcellulose-xanthan gum (HPMC-XG) were used as gelling agents to prepare different oil gels. The performance of the oil gels was evaluated based on appearance, microstructure, viscosity, oil-holding capacity, and drug-loading capability.
Comparative study on stress corrosion resistance of 7150/7055/7A56 aluminum alloys
Authors: Wang Qingsong , Ran Hongwei , Li Yanan
Published: October 2024

The effect of the alloying degree of 7xxx aluminum alloys on stress-corrosion resistance and microstructure was explored. The relationship between the microstructure characteristics and stress-corrosion performance of the three 7xxx aluminum alloys was analyzed. The results show that with an increase in alloying degree, the quantity of precipitated phases along grain boundaries notably increases, and the connectivity between precipitated phases is significantly enhanced, leading to an increased tendency for alloy dissolution. Anodic dissolution causes intergranular corrosion, making grain boundaries serve as channels for rapid crack propagation under tensile stress, thereby increasing the alloy’s stress-corrosion susceptibility. The stress-corrosion sensitivities of the three alloys are as follows: 7150 < 7055 < 7A56.
Anharmonic effect in combustion of high-carbon alcohol fuel 2-hexanol dissociation reaction
Authors: Wang Li , Xia Wenwen , Zhang Wenhan , Wang Yao , Yao Li
Published: October 2024

Quantum chemical calculations were applied to study the anharmonic effect and reaction mechanism of the 2-hexanol dissociation reaction. The thermodynamic quantity (C
o
p, S
o, Δf
H
o) for the title reaction were studied of 15 species in the temperature scope of 298 K − 4000 K. The kinetic quantity (k(T)) was studied for 8 reaction pathways within a temperature region of 1000 K − 4000 K. The results show that the H2O elimination pathway dominates at low temperatures, whereas the simple bond dissociation pathway plays a more important role at higher temperatures. The anharmonic and harmonic rate constants increase with rising temperature, the anharmonic effect of the 2-hexanol dissociation reaction system cannot be neglected. Finally, the principle of least squares was employed to present the thermodynamic coefficients a
1-a
7 and the kinetic coefficients A, n, E of the 2-Hexanol dissociation reaction mechanism.
A visible transparent infrared microwave compatible stealth metasurface with low infrared emissivity
Authors: Zhang Jihao , Zhu Huanzheng , Ghosh Pintu , Li Qiang
Published: October 2024

This article proposes a visible transparent infrared microwave-compatible stealth metasurface with low infrared emissivity, aiming to integrate visible transparency, low infrared radiation, and broadband microwave absorption. The entire structure consists of a dual layer of infrared shielding layer (IRSL) and microwave absorption layer (MAL). Among them, IRSL adopts a frequency selective surface (FSS) structure with high-duty cycle dielectric-metal-dielectric (DMD) to obtain low infrared emissivity and high microwave transmittance. MAL combines the equivalent circuit method (ECM) and particle swarm optimization algorithm (PSO) to design a circular ring metasurface for broadband microwave absorption. To achieve better absorption performance, a transition layer (TL) is introduced to improve impedance matching between IRSL and MAL. Meanwhile, the use of transparent materials throughout the entire structure has the characteristic of visible transparency. In summary, this article proposes a multiband compatible stealth metasurface design method that can meet the stealth requirements of modern battlefields.
A short-term wind power forecasting model based on CUR
Authors: Wu Shuang , Lei Hengxin , Ming Lim Tong , Yiqi Tew , Thein Lai Wong
Published: October 2024

Wind power forecasting plays a crucial role in the contemporary renewable energy system. During the process of forecasting wind power, the establishment of LSTM models requires a lot of time and effort, and the interpretability of prediction results is poor, making it difficult to understand and verify the results. To accomplish interpretable and precise wind power predictions, this paper introduces a wind power prediction algorithm model leveraging CUR matrix decomposition. The CUR matrix decomposition method first obtains the original matrix A (wind power data matrix). The statistical influence scores of rows and columns in A are calculated, and several columns and rows with higher scores are selected to form a low dimensional matrix C and R. Matrix C contains the main characteristic factors that affect wind power, while matrix R contains time series features. Then, the matrix U is approximated by A, C, and R to transform the preference feature extraction problem in high-dimensional space into a matrix analysis problem in low-dimensional space, making it more interpretable and accurate. The efficacy of the wind power forecasting approach utilizing CUR matrix decomposition is assessed and confirmed on openly accessible datasets. The results indicate that the CUR matrix decomposition method has good prediction accuracy and interpretability.
Multilayer decoupling control of photovoltaic integrated heat pump based on expected value
Authors: Han Nali , Xu Juan
Published: October 2024

In this paper, a multilayer decoupling control method for photovoltaic heat pumps based on expected values is proposed, which aims to achieve the optimal operation of the photovoltaic heat pump system and photovoltaic heat pump system. This method predicts the output energy of photovoltaic photovoltaic system and realizes multilayer decoupling control based on the load demand of the heat pump system. In order to adapt to the change in environment, the adaptive fuzzy PID compound control method is adopted to optimize the control strategy. Experimental results show that this method can effectively improve the system efficiency, reduce energy consumption, and demonstrate good adaptability and stability.
Assessement of the physico-chemical quality of Groundwater in the Zagora area, Morocco
Authors: Abdelmonaim Maliki , Moustaine Radouane El , Abdelkader Chahlaoui , Mourad Darbali , Abderrazzaq Boudellah , Mhamed Khaffou , Youssef Ouballouk , Aziz Taouraout
Published: October 2024

The Zagora region heavily relies on groundwater as a crucial water resource for a range of human activities. Mining activities can have significant impacts on groundwater quality in the areas surrounding mining sites. The primary objective of this study is to analyze and evaluate the effects of pollution on the quality of groundwater in the Zagora area, with a particular focus on mapping and identifying its sources. It is based on the use of Geographic Information Systems (GIS) and the spatial variation of the physico-chemical parameters of the studied water sources. Assessing the physico-chemical quality of groundwater in Zagora, involves evaluating several parameters that can affect its quality. These parameters include temperature (T°C), pH, electrical conductivity (EC), dissolved oxygen (O2), chlorides (Cl−), sulfates (SO4
2−), nitrates (NO3
−), nitrites (NO2
−), ammonium (NH4
+), and orthophosphates (PO4
3−). The results of the physico-chemical analysis have shown that, the electrical conductivity ranged from 501.59 to 3173.92 μs/cm, while sulfate concentrations ranged from 91.87 to 363.02 mg/L. The spatial distribution of the results indicates that the water samples were collected from different locations, and there are variations in the levels of parameters analyzed. Some of the parameters, such as electrical conductivity, and sulfate, have higher levels in some locations compared to others, indicating potential sources of pollution or natural variability in the water composition. The GIS analysis also revealed that the areas with poor water quality were clustered around specific locations, indicating potential sources of contamination. Therefore, further investigation and monitoring of the water sources may be necessary to ensure safe and healthy water consumption.
Spatio-temporal variability of precipitation from 1980 to 2021 within the Oum Er Rbia hydraulic basin (Morocco)
Authors: Hamid Meriem , Nafia Khouldia , Aguerd Jalal , Ghachi Mohamed El
Published: October 2024

The aim of this work is to assess the spatio-temporal variability of the mean annual rainfall during the last four decades within the Oum Er Rbia hydraulic basin. The used database in this study consists with a series of rainfall data at different time scale. These data were subjected to statistical and cartographic analysis. The obtained results show that, during the period of 1980-2021, interannual variability marked the evolution of annual rainfall averages. Furthermore, this variability is characterized by alternating sequences of dry and wet seasons. From the hydrological year of 2015, a general decreasing trend of rainfall has clearly marked and observed. Rainfall patterns in the Oum Er Rbia basin are also characterized by spatial variability. Interannual averages vary considerably from one catchment to another. The upstream part of the basin receives the most amount of rainfall. By contrast, the middle of the basin is the driest. The recent drop in precipitation has had a negative impact on the basin’s territory, most notably on water resources and agriculture.
Fratricide and Redemption
Authors: Jones Corredera Edward
Published: October 2024

This chapter studies the question of state succession and war debts in relation to the construction and dissolution of Gran Colombia. From the moment of its foundation, this new composite nation was faced with the threat of bankruptcy. Debates on debt shaped Gran Colombia’s constitutional approaches to the relationship between international law, slavery, colonial debts, and the protection of private property. The chapter then sheds light on how debts were distributed as Gran Colombia splintered into three different states: New Granada, Venezuela, and Ecuador. Mid-century officials turned to international law to facilitate a resolution of this discussion. By the end of the century, Colombia’s experience with confederalism and the law of nations contributed to broader regional debates about Pan-American public law.
Sacred Debt and Just War
Authors: Jones Corredera Edward
Published: October 2024

This chapter sheds light on the connections between early and mid-nineteenth-century debates on debts and the development of ideas of intervention and international law in early twentieth-century Latin America. Alberdi argued that his constitutional system for Argentina could be scaled up to a system of international relations for Latin America. Alberdi’s views on statehood and political economy, and Calvo’s views on international law, influenced one of the most prominent Latin American legal thinkers, Luis María Drago, and his reflections on interventionism. Drago sought to resolve the incongruities and tensions in the legal thought of the two men. The underlying question that nineteenth-century Latin American officials turned to international law to answer was whether, in light of the geopolitical realities of their age, a moral economy could be found in, or beyond, international law.
A Pediatric Case of Multiple Pilomatricomas: Assessing the Risk of Genetic Disorders
Authors: Nakaso Soma , Ishii Nobuaki , Akimoto Masataka , Ogawa Rei
Published: October 2024

Pilomatricomas are benign tumors from hair matrix cells, often associated with genetic disorders such as myotonic dystrophy. We report a case of multiple pilomatricomas in a 12-year-old boy, suggesting they may indicate underlying hereditary diseases, requiring careful post-surgical follow-up and examination.
How ‘nudge’ happened: the political economy of nudging in the UK
Authors: Mills Stuart , Whittle Richard
Published: October 2024

The UK Behavioural Insights Team transformed nudging and behavioural economics from nascent ideas to key policy tools for the UK Coalition Government. This article argues that political economic circumstances significantly contributed to the success of this ‘nudge’ programme. The Global Financial Crisis (GFC) created a ‘contest of authority’ over dominant policy approaches. By framing the crisis as a crisis of rationality, behavioural perspectives gained political support. The GFC also saw that the UK Government (from 2010) adopt a programme of fiscal austerity. Nudging complemented this programme by suggesting effective policy could be made cheaply. Using various accounts of nudging in the UK from those involved in its development, we demonstrate the role of the country’s political economy in the behavioural turn. We conclude by reflecting on the role of behavioural insights today, given a political–economic landscape much changed since 2010.
The power of sample size calculations
Authors: Jansen Marieke S , Groenwold Rolf H H , Dekkers Olaf M
Published: October 2024

Researchers frequently come across sample size calculations in the scientific literature they read, in projects undertaken by their peers, and likely within their own work. However, despite its ubiquity, calculating a sample size is often perceived as a hurdle and not fully understood. This paper provides a brief overview of sample size estimation to guide readers, researchers, and reviewers through its fundamentals.
Economic geography’s contribution to understanding the circular economy
Authors: Bourdin Sébastien , Torre André
Published: October 2024

This article explores the role of evolutionary economic geography in enhancing understanding and implementation of the circular economy (CE). By incorporating spatial and territorial dimensions into CE research, this study emphasizes the significant influence of geographical factors on achieving economic and environmental objectives. The research highlights the importance of localizing CE practices and emphasizes the contributions of proximity theory and territorial governance in promoting collaborative networks that are crucial for CE success. Furthermore, the article introduces the concept of Territorial Circular Ecosystems, which provides a framework for analyzing regional variations and the interplay between local actors, resources, and institutional support in the deployment of the CE. The findings offer fresh insights for policymakers and researchers, advocating for place-based policies to address CE challenges and optimize sustainability strategies.