bluuebunny/crossref_metadata_2025 huggingface dataset:
Piezoelectric Properties of As-Spun Poly(vinylidene Fluoride)/Multi-Walled Carbon Nanotube/Zinc Oxide Nanoparticle (PVDF/MWCNT/ZnO) Nanofibrous Films
Authors: Xu Lei , Lv Jiao , Yu Shengrui
Published: September 2024

Conductive multi-walled carbon nanotubes (MWCNTs) as well as piezoelectric zinc oxide (ZnO) nanoparticles are frequently used as a single additive and dispersed in polyvinylidene fluoride (PVDF) solutions for the fabrication of piezoelectric composite films. In this study, MWCNT/ZnO binary dispersions are used as spinning liquids to fabricate composite nanofibrous films by electrospinning. Binary additives are conducive to increasing the crystallinity, piezoelectric voltage coefficient, and consequent piezoelectricity of as-spun films owing to the stretch-enhanced polarization of the electrospinning process under an applied electric field. PCZ–1.5 film (10 wt. % PVDF/0.1 wt. % MWCNTs/1.5 wt. % ZnO nanoparticles) contains the maximum β-phase content of 79.0% and the highest crystallinity of 87.9% in nanofibers. A sensor using a PCZ–1.5 film as a functional layer generates an open-circuit voltage of 10 V as it is subjected to impact loads with an amplitude of 6 mm at 10 Hz. The piezoelectric sensor reaches a power density of 0.33 μW/cm2 and a force sensitivity of 582 mV/N. In addition, the sensor is successfully applied to test irregular motions of a bending finger and stepping foot. The result indicates that electrospun PVDF/MWCNT/ZnO nanofibrous films are suitable for wearable devices.
Study on the Storage Stability and Rheological Property of Bio-Oil/Lignin Composite-Modified Asphalt
Authors: Guo Guixiu , Gao Junfeng , Jin Dongzhao , Wang Xuan , Bi Yanqiu , Guo Peng
Published: September 2024

The objective of this study is to investigate the storage stability and rheological property of bio-oil/lignin composite-modified asphalt. The composite-modified asphalt with different proportions of bio-oil was prepared and cured at 105 °C, 135 °C, and 165 °C for 24 h and 48 h. The storage stability of the composite-modified asphalt was evaluated based on the softening point difference, the storage stability index derived from rotational viscosity, the segregation rate based on temperature sweep, and the non-recoverable creep compliance measured through the Multiple Stress Creep Recovery test. The storage stability of bio-oil/lignin composite-modified asphalt was evaluated through testing and analysis of its infrared spectroscopy and scanning electron microscopy before and after thermal storage. The research results indicate that the maximum difference in softening point is 0.9 °C, and the calculated storage stability index is generally below 0.1. The maximum value of the segregation rate is 0.43, indicating excellent storage stability of the bio-oil/lignin composite-modified asphalt. According to the results from infrared spectroscopy, no chemical reactions occurred during the storage process of the composite-modified asphalt. The scanning electron microscope confirmed that the samples became more stable after 48 h of storage.
Lignin-Based Composite Film and Its Application for Agricultural Mulching
Authors: Huang Zujian , Zhang Yan , Zhang Chenwei , Yuan Fangting , Gao Hairong , Li Qiang
Published: September 2024

Agricultural mulching is an important input for modern agricultural production and plays an important role in guaranteeing food security worldwide. At present, polyethylene (PE) mulching is still commonly used in agricultural production in most countries around the world, which is non-biodegradable, and years of mulching have caused serious agricultural white pollution. Lignin is one of the three major components of plant cell walls, and it is also the main renewable natural aromatic compounds in nature. Lignin-based composite film materials are green, biodegradable, and show good prospects for development in the field of agricultural mulch. This paper introduces the types, structure, and application status of lignin, summarizes the preparation of lignin-based composite film materials and its latest research progress, focuses on the types, preparation methods, and application examples of lignin-based agricultural mulching, and looks forward to the future development prospects of lignin-based agricultural mulching.
Mechanochemical Upcycling of Waste Polypropylene into Warm-Mix Modifier for Asphalt Pavement Incorporating Recycled Concrete Aggregates
Authors: Hu Jingxuan , Jiang Xueliang , Chu Yaming , Xu Song , Xu Xiong
Published: September 2024

To solve the problems on resource utilization and environmental pollution of waste concrete and waste polypropylene (PP) plastics, the recycling of them into asphalt pavement is a feasible approach. Considering the high melting temperature of waste PP, this study adopted a thermal-and-mechanochemical method to convert waste PP into high-performance warm-mix asphalt modifiers (PPMs) through the hybrid use of dicumyl peroxide (DCP), maleic anhydride (MAH), and epoxidized soybean oil (ESO) for preparing an asphalt mixture (RCAAM) containing recycled concrete aggregate (RCA). For the prepared RCAAM containing PPMs, the mixing temperature was about 30 °C lower than that of the hot-mix RCAAM containing untreated PP. Further, the high-temperature property, low-temperature crack resistance, moisture-induced damage resistance, and fatigue resistance of the RCAAM were characterized. The results indicated that the maximum flexural strain of the RCAAM increased by 7.8~21.4% after using PPMs, while the sectional fractures of the asphalt binder were reduced after damaging at low temperature. The use of ESO in PPMs can promote the cohesion enhancement of the asphalt binder and also improve the high-temperature deformation resistance and fatigue performance of the RCAAM. Notably, the warm-mix epoxidized PPMA mixture worked better close to the hot-mix untreated PPMA mixture, even after the mixing temperature was reduced by 30 °C.
Efficient Removal of Mercury from Wastewater Solutions by a Nitrogen-Doped Hyper-Crosslinked Polyamine
Authors: Al Ghamdi Khalid , Ahmad Aqeel , Falca Gheorghe , Alrefaeia Meshal Nawaf , Al-Hamouz Othman Charles S.
Published: September 2024

Mercury, a highly toxic metal and pollutant, poses a significant risk to human health and the environment. This study describes the synthesis of a new nitrogen-doped heteroaromatic hyper-crosslinked polyamine (HCPA) via the polycondensation of 2,6-diaminopyrazine and tris(4-formylphenyl)amine for the efficient removal of mercury ions from aqueous solutions. The HCPA polymer was characterized by solid-state 13C-NMR and FT-IR spectroscopy. A powder X-ray diffraction and thermogravimetric analysis showed that the polymer was semicrystalline in nature and stable up to 500 °C. Adsorption isotherms indicated that mercury adsorption occurred via mono- and multilayer adsorption by HCPA, as depicted by the Langmuir, Freundlich, and Redlich–Peterson isotherm models, with a maximum adsorption capacity of qm = 333.3 mg/g. Adsorption kinetic models suggested that the adsorption process was fast and effective, reaching equilibrium within 20 min. Thermodynamics of the adsorption process revealed that it was endothermic and spontaneous in nature due to the positive ΔH0 of 48 kJ/mol and negative ΔG0 values of −4.5 kJ/mol at 293 K. Wastewater treatment revealed 98% removal of mercury indicating the selective nature of HCPA. Finally, HCPA exhibited excellent performance and regeneration up to three cycles, demonstrating its great potential as an adsorbent for environmental remediation applications.
Cross-Linking Reaction of Bio-Based Epoxy Systems: An Investigation into Cure Kinetics
Authors: Di Matteo Pietro , Iadarola Andrea , Ciardiello Raffaele , Paolino Davide Salvatore , Gazza Francesco , Lambertini Vito Guido , Brunella Valentina
Published: September 2024

The cure kinetics of various epoxy resin mixtures, comprising a bisphenol epoxy, two epoxy modifiers, and two hardening agents derived from cardanol technology, were investigated through differential scanning calorimetry (DSC). The development of these mixtures aimed to achieve epoxy materials with a substantial bio-content up to 50% for potential automotive applications, aligning with the 2019 European Regulation on climate neutrality and CO2 emission. The Friedman isoconversional method was employed to determine key kinetic parameters, such as activation energy and pre-exponential factor, providing insights into the cross-linking process and the Kamal–Sourour model was used to describe and predict the kinetics of the chemical reactions. This empirical approach was implemented to forecast the curing process for the specific oven curing cycle utilised. Additionally, tensile tests revealed promising results showcasing materials’ viability against conventional counterparts. Overall, this investigation offers a comprehensive understanding of the cure kinetics, mechanical behaviour, and thermal properties of the novel epoxy–novolac blends, contributing to the development of high-performance materials for sustainable automotive applications.
Magnetic Silver Nanoparticles Stabilized by Superhydrophilic Polymer Brushes with Exceptional Kinetics and Catalysis
Authors: Dolatkhah Asghar , Dewani Chandni , Kazem-Rostami Masoud , Wilson Lee D.
Published: September 2024

Stimuli-responsive catalysts with exceptional kinetics and complete recoverability for efficient recyclability are essential in, for example, converting pollutants and hazardous organic compounds into less harmful chemicals. Here, we used a novel approach to stabilize silver nanoparticles (NPs) through magneto/hydro-responsive anionic polymer brushes that consist of poly (acrylic acid) (PAA) moieties at the amine functional groups of chitosan. Two types of responsive catalyst systems with variable silver loading (wt.%) of high and low (PAAgCHI/Fe3O4/Ag (H, L)) were prepared. The catalytic activity was evaluated by monitoring the reduction of organic dye compounds, 4-nitrophenol and methyl orange in the presence of NaBH4. The high dispersity and hydrophilic nature of the catalyst provided exceptional kinetics for dye reduction that surpassed previously reported nanocatalysts for organic dye reduction. Dynamic light scattering (DLS) measurements were carried out to study the colloidal stability of the nanocatalysts. The hybrid materials not only showed enhanced colloidal stability due to electrostatic repulsion among adjacent polymer brushes but also offered more rapid kinetics when compared with as-prepared Ag nanoparticles (AgNPs), which results from super-hydrophilicity and easy accumulation/diffusion of dye species within polymer brushes. Such remarkable kinetics, biodegradability, biocompatibility, low cost and facile magnetic recoverability of the Ag nanocatalysts reported here contribute to their ranking among the top catalyst systems reported in the literature. It was observed that the apparent catalytic rate constant for the reduction of methyl orange dye was enhanced, PAAgCHI/Fe3O4/Ag (H) ca. 35-fold and PAAgCHI/Fe3O4/Ag (L) ca. 23-fold, when compared against the as prepared AgNPs. Finally, the regeneration and recyclability of the nanocatalyst systems were studied over 15 consecutive cycles. It was demonstrated that the nanomaterials display excellent recyclability without a notable loss in catalytic activity.
The Influence of Oil and Thermal Aging on the Sealing Characteristics of NBR Seals
Authors: Li Yiding , Wu Jian , Chen Zhihao , Zhang Ziqi , Su Benlong , Wang Youshan
Published: September 2024

Nitrile Butadiene Rubber (NBR) is widely used as a sealing material due to its excellent mechanical properties and good oil resistance. However, when using NBR material, the seal structure is unable to avoid the negative effects of rubber aging. Hence, the influence of oil and thermal aging on the characteristics of NBR seals was studied by coupling the mechanical behavioral changes with the tribological behavioral changes of NBR in oil and the thermal environment. For this paper, aging testing and compression testing of NBR were carried out. Additionally, friction testing between friction pairs under different aging times was carried out. The surface morphology of the NBR working surface under different aging conditions was also observed. Finally, coefficients of different test conditions were introduced into the finite element model of NBR seals. It can be seen from the results that the elastic modulus increased with the increase in aging time in the thermal oxidative aging testing. The elastic modulus after 7 days of thermal oxidative aging increased by 135.45% compared to the unaged case, and the elastic modulus after 7 days of oil aging increased by 15.03% compared to the unaged case. The compression set rate of NBR increased significantly with the increase in aging time and temperature. The coefficient of friction (COF) between friction pairs increased first and then decreased with the increase in aging time. The maximum contact pressure decreased by 2.43% between the shaft and sealing ring and decreased by 4.01% between the O-ring and groove. The proportion of the effective sealing area decreased by 3.05% between the shaft and sealing ring and decreased by 6.11% between the O-ring and groove. Furthermore, the sealing characteristics between the O-ring and groove were better than those between the shaft and sealing ring.
Pressure Source Model of the Production Process of Natural Gas from Unconventional Reservoirs
Authors: Yarnangoré Boubacar , Acosta-González Francisco Andrés
Published: September 2024

This work is focused on developing a computational model to predict the production rate and pressure evolution of natural gas from unconventional reservoirs, particularly shale gas deposits. The model is based on the principle of conservation of mechanical energy and was developed from the transient solution of Bernoulli’s equation. This solution was obtained by computing the pressure evolution in the well resulting from the combined action of extracting the free gas and of gasification from kerogen. The transient behavior of gas production by hydraulic fracturing was calculated by numerically integrating Bernoulli’s equation. The curves representing gas flow evolution were considered as a series of stepwise steady states under a constant gas flow rate, similar to the pressure–time curves. These time steps were connected by instantaneous drops in pressure or gas flow rates. On the other hand, the delayed release of the adsorbed and dissolved gas in the kerogen was accurately calculated by introducing a semi-empirical gas pressure source term into the gas well pressure equation. The effect of this source is to gradually increase the gas pressure in the reservoir, emulating the gas release mechanisms from the organic matter. Model validation was based on production data from the unconventional reservoirs Eagle Ford, U.S.A., and Burgos basin, México. The initial measured gas production rate was used to determine a global friction factor of the gas flowing out from soil cracks and ducts. Additionally, measured production rate data were used to determine the coefficients of the source term function. Pearson correlation coefficients of 0.97 and 0.96 were obtained for Eagle Ford and Burgos basins data, respectively. In contrast, the corresponding coefficients calculated from the traditional Arps’ model were 0.89 and 0.5, respectively. The present pressure source model (PSM) represents a new approach to characterize the process of gas production from unconventional reservoirs, proving to be accurate in forecasting both the gas flow rate and pressure evolution during gas production. The postulated pressure source term was shown to mimic the desorption and diffusion kinetics, which release free gas from the kerogen.
Bimetallic Fe, Co-Modified TiO2 Derived from NH2-MIL-125(Ti) as an Efficient Photocatalyst for N2 Fixation
Authors: Yang Huiying , Meng Xiangchao
Published: September 2024

The conversion of nitrogen (N2) and water (H2O) into NH3 by photocatalysis under ambient conditions has been considered an environmentally friendly strategy. However, developing effective catalysts for N2 fixation is still challenging. Herein, we report a bimetallic JH Fe, Co/TiO2 derived from NH2-MIL-125(Ti) by the fast Joule heating (FJH) method for visible–light–driven catalytic N2 fixation. It was found that the photocatalytic N2 reduction efficiency of bimetallic FC@TiO2-JH was improved, enabling an NH3 yield rate of 110.14 µmol g−1 h−1 without any sacrificial agents. Furthermore, the rate was higher than those of Fe@TiO2-JH and Co@TiO2-JH, suggesting that the synergistic effect between Fe and Co broke the electronic equilibrium and increased the center of its d-band, enhancing electronic feedback to the antibonding π* orbitals of N2 while weakening the bonding energy of N≡N. Meanwhile, the rate was about 2.75 times higher than that of FC@TiO2-TF, which was calcined in a tube furnace. It is assumed that FJH might lead to the formation of lattice defects, leading to localized charge deficiency, enhanced carrier separation, and transport. Thus, doping of Fe and Co synergistically interacted with the defects produced from FJH, facilitating the photocatalytic reduction process. As detected, it had a greater ability to separate hole–electron pairs and transferred electrons to adsorbed N2 at faster rates. Our work demonstrates a prospective strategy for designing bimetallic catalysts derived from NH2-MIL-125(Ti) for N2 fixation.
Scaling up the Natural Mode of Action of Macrophyte Allelochemicals and Their Effect on Toxic Cyanobacteria Using a Nitrogen-Limited Chemostat
Authors: Tazart Zakaria , Lazrak Khawla , El Bouaidi Widad , Redouane El Mahdi , Tebaa Lamiaa , Douma Mountasser , Mouhri Khadija , Loudiki Mohammed
Published: September 2024

This study investigates the inhibitory and hormetic effects of Myriophyllum spicatum extract on Microcystis aeruginosa in a controlled, continuous culture environment. To address the global challenge posed by harmful algal blooms, we used a range of extract concentrations to delineate the growth response patterns. At very low concentrations (6.25 and 12.5 mg/L), the addition of M. spicatum extract shows no discernible reduction in M. aeruginosa cell density or growth rate; instead, a slight increase is observed during exposure, suggesting a hormetic effect. However, at higher concentrations (75 and 100 mg/L), there is a drastic reduction of more than 50% in cell density and growth rate at 75 mg/L, with complete inhibition at 100 mg/L, leading to pronounced oxidative stress, damage to antioxidant defense systems, and increased cell mortality. Increased levels of malondialdehyde, catalase, and superoxide dismutase activities indicate the involvement of these enzymes in combating oxidative stress. Furthermore, intracellular and extracellular microcystins were significantly decreased at higher extract concentrations (50, 75, and 100 mg/L) in a dose-dependent manner. Our results indicate a dose-dependent response and provide insight into the potential application of natural water treatment solutions. Implications for ecological management and future research directions are discussed.
Performance Assessment of One-Part Self-Compacted Geopolymer Concrete Containing Recycled Concrete Aggregate: A Critical Comparison Using Artificial Neural Network (ANN) and Linear Regression Models
Authors: Nikmehr Bahareh , Kafle Bidur , Al-Ameri Riyadh
Published: September 2024

Geopolymer concrete, a cement-free concrete with recycled concrete aggregate (RCA), offers an eco-friendly solution for reducing carbon emissions from cement production and reusing a significant amount of old concrete from construction and demolition waste. This research on self-compacted, ambient-cured, and low-carbon concrete demonstrates the superior performance of one-part geopolymer concrete made from recycled materials. It is achieved by optimally replacing treated RCA with a unique method that involves coating the recycled aggregates with a one-part geopolymer slurry composed of fly ash, micro fly ash, slag, and anhydrous sodium metasilicate. The research presented in this paper introduces predictive models to assist researchers in optimising concrete mix designs based on RCA rates and treatment methods, including the incorporation of coated recycled concrete aggregates and basalt fibres. This study addresses the knowledge gap regarding geopolymer concrete based on recycled aggregate, various RCA rates, and novel RCA treatments. The novelty of the paper also lies in presenting the effectiveness of Artificial Neural Network (ANN) models in accurately predicting the compressive strength, splitting tensile strength, and modulus of elasticity for self-compacting geopolymer concrete with various rates of RCA replacement. This addresses a knowledge gap in existing research on ANN models for the prediction of geopolymer concrete properties based on RCA rate and treatment. The ANN models developed in this research predict results that are more comparable to experimental outcomes, showcasing superior accuracy compared to linear regression models.
Adaptive Path Planning for Subsurface Plume Tracing with an Autonomous Underwater Vehicle
Authors: Wu Zhiliang , Wang Shuozi , Shao Xusong , Liu Fang , Bao Zefeng
Published: September 2024

Autonomous underwater vehicles (AUVs) have been increasingly applied in marine environmental monitoring. Their outstanding capability of performing tasks without human intervention makes them a popular tool for environmental data collection, especially in unknown and remote regions. This paper addresses the path planning problem when AUVs are used to perform plume source tracing in an unknown environment. The goal of path planning is to locate the plume source efficiently. The path planning approach is developed using the Double Deep Q-Network (DDQN) algorithm in the deep reinforcement learning (DRL) framework. The AUV gains knowledge by interacting with the environment, and the optimal direction is extracted from the mapping obtained by a deep neural network. The proposed approach was tested by numerical simulation and on a real ground vehicle. In the numerical simulation, several initial sampling strategies were compared on the basis of survey efficiency. The results show that direct learning based on the interaction with the environment could be an appropriate survey strategy for plume source tracing problems. The comparison with the canonical lawnmower path used in practice showed that path planning using DRL algorithms could be potentially promising for large-scale environment exploration.
The Loran-C Pseudorange Positioning and Timing Algorithm Based on the Vincenty Formula
Authors: Li Jingling , Wu Huabing
Published: September 2024

To improve the positioning accuracy of the Loran system and meet the requirements of Loran/BDS integrated positioning and timing, it is necessary to enhance the traditional Loran hyperbolic positioning method, making its pseudorange calculation consistent with the BDS positioning and timing solution. The existing pseudorange algorithm based on the Andoyer-Lambert formula has issues such as strict initial value selection range and susceptibility to singularities during calculations. This study proposes a new Loran pseudorange calculation method based on the Vincenty distance formula and conducts a simulation analysis of it. The results show that, in the absence of noise interference, the positioning and timing errors of this pseudorange algorithm are close to zero, demonstrating high accuracy. When subjected to random noise with a standard deviation of less than 100 ns, the latitude and longitude errors are both less than 10 m, and the timing error is less than 10−4 ns, meeting the requirements of Loran positioning and timing. Compared to the pseudorange algorithm based on the Andoyer-Lambert formula, the one based on the Vincenty formula has comparable positioning longitude accuracy but superior timing accuracy. Moreover, the latter offers a wider range of initial value selection and can avoid more singularity issues during calculations.
Detection and Retrieval of Supercooled Water in Stratocumulus Clouds over Northeastern China Using Millimeter-Wave Radar and Microwave Radiometer
Authors: Hu Hao , Yin Yan , Yang Jing , Bao Xinghua , Zhang Bo , Gao Wei
Published: September 2024

Supercooled water in mixed-phase clouds plays a significant role in precipitation formation, atmospheric radiation, weather modification, and aircraft flight safety. Identifying supercooled water in mixed-phase clouds is a crucial-frontier scientific issue in atmospheric detection research. In this study, we propose a new algorithm for identifying supercooled water based on the multi-spectral peak characteristics in cloud radar power spectra, combined with radar reflectivity factor and mean Doppler velocity. Using microwave radiometer data, we conducted retrieval analyses on two stratocumulus cases in the spring over the northeastern Daxing’anling region, China. The retrieval results show that the supercooled water in the spring stratocumulus clouds over the region is widespread, with liquid water content (LWC) ranging around 0.1 ± 0.05 g/m3, and particle sizes not exceeding 10 μm. The influence of updrafts on supercooled water is evident, with both showing good consistency in spatiotemporal variation trends. Comparing the liquid water path (LWP) variations retrieved from cloud radar and microwave radiometer, both showed good consistency in variation trends and high LWC areas, indicating the reliability of the identification algorithm developed in this study.
Estimating Leaf Area Index in Apple Orchard by UAV Multispectral Images with Spectral and Texture Information
Authors: Yu Junru , Zhang Yu , Song Zhenghua , Jiang Danyao , Guo Yiming , Liu Yanfu , Chang Qingrui
Published: September 2024

The Leaf Area Index (LAI) strongly influences vegetation evapotranspiration and photosynthesis rates. Timely and accurately estimating the LAI is crucial for monitoring vegetation growth. The unmanned aerial vehicle (UAV) multispectral digital camera platform has been proven to be an effective tool for this purpose. Currently, most remote sensing estimations of LAIs focus on cereal crops, with limited research on economic crops such as apples. In this study, a method for estimating the LAI of an apple orchard by extracting spectral and texture information from UAV multispectral images was proposed. Specifically, field measurements were conducted to collect LAI data for 108 sample points during the final flowering (FF), fruit setting (FS), and fruit expansion (FE) stages of apple growth in 2023. Concurrently, UAV multispectral images were obtained to extract spectral and texture information (Gabor transform). The Support Vector Regression Recursive Feature Elimination (SVR-REF) was employed to select optimal features as inputs for constructing models to estimate the LAI. Finally, the optimal model was used for LAI mapping. The results indicate that integrating spectral and texture information effectively enhances the accuracy of LAI estimation, with the relative prediction deviation (RPD) for all models being greater than 2. The Categorical Boosting (CatBoost) model established for FF exhibits the highest accuracy, with a validation set R2, root mean square error (RMSE), and RPD of 0.867, 0.203, and 2.482, respectively. UAV multispectral imagery proves to be valuable in estimating apple orchard LAIs, offering real-time monitoring of apple growth and providing a scientific basis for orchard management.
Tracking Forest Disturbance in Northeast China’s Cold-Temperate Forests Using a Temporal Sequence of Landsat Data
Authors: Wang Yueting , Jia Xiang , Zhang Xiaoli , Lei Lingting , Chai Guoqi , Yao Zongqi , Qiu Shike , Du Jun , Wang Jingxu , Wang Zheng , Wang Ran
Published: September 2024

Cold-temperate forests (CTFs) are not only an important source of wood but also provide significant carbon storage in China. However, under the increasing pressure of human activities and climate change, CTFs are experiencing severe disturbances, such as logging, fires, and pest infestations, leading to evident degradation trends. Though these disturbances impact both regional and global carbon budgets and their assessments, the disturbance patterns in CTFs in northern China remain poorly understood. In this paper, the Genhe forest area, which is a typical CTF region located in the Inner Mongolia Autonomous Region, Northeast China (with an area of about 2.001 × 104 km2), was selected as the study area. Based on Landsat historical archived data on the Google Earth Engine (GEE) platform, we used the continuous change detection and classification (CCDC) algorithm and considered seasonal features to detect forest disturbances over nearly 30 years. First, we created six inter-annual time series seasonal vegetation index datasets to map forest coverage using the maximum between-class variance algorithm (OTSU). Second, we used the CCDC algorithm to extract disturbance information. Finally, by using the ECMWF climate reanalysis dataset, MODIS C6, the snow phenology dataset, and forestry department records, we evaluated how disturbances relate to climate and human activities. The results showed that the disturbance map generated using summer (June–August) imagery and the enhanced vegetation index (EVI) had the highest overall accuracy (88%). Forests have been disturbed to the extent of 12.65% (2137.31 km2) over the last 30 years, and the disturbed area generally showed a trend toward reduction, especially after commercial logging activities were banned in 2015. However, there was an unusual increase in the number of disturbed areas in 2002 and 2003 due to large fires. The monitoring of potential widespread forest disturbance due to extreme drought and fire events in the context of climate change should be strengthened in the future, and preventive and salvage measures should be taken in a timely manner. Our results demonstrate that CTF disturbance can be robustly mapped by using the CCDC algorithm based on Landsat time series seasonal imagery in areas with complex meteorological conditions and spatial heterogeneity, which is essential for understanding forest change processes.
Aboveground Biomass Mapping in SemiArid Forests by Integrating Airborne LiDAR with Sentinel-1 and Sentinel-2 Time-Series Data
Authors: Zhang Linjing , Yin Xinran , Wang Yaru , Chen Jing
Published: September 2024

Aboveground biomass (AGB) is a vital indicator for studying carbon sinks in forest ecosystems. Semiarid forests harbor substantial carbon storage but received little attention due to the high spatial–temporal heterogeneity that complicates the modeling of AGB in this environment. This study assessed the performance of different data sources (annual monthly time-series radar was Sentinel-1 [S1]; annual monthly time series optical was Sentinel-2 [S2]; and single-temporal airborne light detection and ranging [LiDAR]) and seven prediction approaches to map AGB in the semiarid forests on the border between Gansu and Qinghai Provinces in China. Five experiments were conducted using different data configurations from synthetic aperture radar backscatter, multispectral reflectance, LiDAR point cloud, and their derivatives (polarimetric combination indices, texture information, vegetation indices, biophysical features, and tree height- and canopy-related indices). The results showed that S2 acquired better prediction (coefficient of determination [R2]: 0.62–0.75; root mean square error [RMSE]: 30.08–38.83 Mg/ha) than S1 (R2: 0.24–0.45; RMSE: 47.36–56.51 Mg/ha). However, their integration further improved the results (R2: 0.65–0.78; RMSE: 28.68–35.92 Mg/ha). The addition of single-temporal LiDAR highlighted its structural importance in semiarid forests. The best mapping accuracy was achieved by XGBoost, with the metrics from the S2 and S1 time series and the LiDAR-based canopy height information being combined (R2: 0.87; RMSE: 21.63 Mg/ha; relative RMSE: 14.45%). Images obtained during the dry season were effective for AGB prediction. Tree-based models generally outperformed other models in semiarid forests. Sequential variable importance analysis indicated that the most important S1 metric to estimate AGB was the polarimetric combination indices sum, and the S2 metrics were associated with red-edge spectral regions. Meanwhile, the most important LiDAR metrics were related to height percentiles. Our methodology advocates for an economical, extensive, and precise AGB retrieval tailored for semiarid forests.
Enhancing Integrated Sensing and Communication (ISAC) Performance for a Searching–Deciding Alternation Radar-Comm System with Multi-Dimension Point Cloud Data
Authors: Chen Leyan , Liu Kai , Gao Qiang , Wang Xiangfen , Zhang Zhibo
Published: September 2024

In developing modern intelligent transportation systems, integrated sensing and communication (ISAC) technology has become an efficient and promising method for vehicle road services. To enhance traffic safety and efficiency through real-time interaction between vehicles and roads, this paper proposes a searching–deciding scheme for an alternation radar-communication (radar-comm) system. Firstly, its communication performance is derived for a given detection probability. Then, we process the echo data from real-world millimeter-wave (mmWave) radar into four-dimensional (4D) point cloud datasets and thus separate different hybrid modes of single-vehicle and vehicle fleets into three types of scenes. Based on these datasets, an efficient labeling method is proposed to assist accurate vehicle target detection. Finally, a novel vehicle detection scheme is proposed to classify various scenes and accurately detect vehicle targets based on deep learning methods. Extensive experiments on collected real-world datasets demonstrate that compared to benchmarks, the proposed scheme obtains substantial radar performance and achieves competitive communication performance.
Fast Semantic Segmentation of Ultra-High-Resolution Remote Sensing Images via Score Map and Fast Transformer-Based Fusion
Authors: Sun Yihao , Wang Mingrui , Huang Xiaoyi , Xin Chengshu , Sun Yinan
Published: September 2024

For ultra-high-resolution (UHR) image semantic segmentation, striking a balance between computational efficiency and storage space is a crucial research direction. This paper proposes a Feature Fusion Network (EFFNet) to improve UHR image semantic segmentation performance. EFFNet designs a score map that can be embedded into the network for training purposes, enabling the selection of the most valuable features to reduce storage consumption, accelerate speed, and enhance accuracy. In the fusion stage, we improve upon previous redundant multiple feature fusion methods by utilizing a transformer structure for one-time fusion. Additionally, our combination of the transformer structure and multibranch structure allows it to be employed for feature fusion, significantly improving accuracy while ensuring calculations remain within an acceptable range. We evaluated EFFNet on the ISPRS two-dimensional semantic labeling Vaihingen and Potsdam datasets, demonstrating that its architecture offers an exceptionally effective solution with outstanding semantic segmentation precision and optimized inference speed. EFFNet substantially enhances critical performance metrics such as Intersection over Union (IoU), overall accuracy, and F1-score, highlighting its superiority as an architectural innovation in ultra-high-resolution remote sensing image semantic segmentation.
Advancing Skarn Iron Ore Detection through Multispectral Image Fusion and 3D Convolutional Neural Networks (3D-CNNs)
Authors: Abubakar Jabir , Zhang Zhaochong , Cheng Zhiguo , Yao Fojun , Bio Sidi D. Bouko Abdoul-Aziz
Published: September 2024

This study explores novel techniques to improve the detection accuracy of skarn iron deposits using advanced image-processing methodologies. Leveraging the capabilities of ASTER image, band ratio (BR) images, and principal component analysis (PCA) alongside the power of 3D convolutional neural networks (3D-CNNs), the research aims to enhance the precision and efficiency of ore detection in complex geological environments. The proposed method employs a specific 3D-CNN architecture accepting input as a 7 × 7 × C image patch, where C represents the combined number of selected ASTER image bands, principal component (PC) bands, and computed BR images. To evaluate the accuracy of the proposed method, five distinct image band combinations, including the proposed band combination, were tested and evaluated based on the overall accuracy (OA), average accuracy (AA), and kappa coefficient. The results demonstrated that while the incorporation of BR images alongside ASTER bands initially seemed promising, it introduced significant confusion in certain classifications, leading to unexpected misclassification rates. Surprisingly, utilizing solely ASTER bands as input parameters yielded higher accuracy rates (OA = 93.13%, AA = 91.96%, kappa = 90.91%) compared with scenarios involving the integration with band ratios (OA = 87.02%, AA = 79.15, kappa = 82.60%) or the integration of BR images to PC bands (OA = 87.78%, AA = 82.39%, kappa = 83.81%). However, the amalgamation of ASTER bands with selected PC bands showed slight improvements in accuracy (OA = 94.65%, AA = 92.93%, kappa = 93.45%), although challenges in accurately classifying certain features persisted. Ultimately, the proposed combination of ASTER bands, PC bands, and BR images (proposed band combination) presented the most visually appealing and statistically accurate results (OA = 96.95%, AA = 94.87%, kappa = 95.93%), effectively addressing misclassifications observed in the other combinations. These findings underscore the synergistic contributions of each of the ASTER bands, PC bands, and BR images, with the ASTER bands proving pivotal for optimal skarn classification, the PC bands enhancing intrusions classification accuracy, and the BR images strengthening wall rock classification accuracy. In conclusion, the proposed combination of input image bands emerges as a robust and comprehensive methodology, demonstrating unparalleled accuracy in the remote sensing detection of skarn iron minerals.
From Radar Sensor to Floating Car Data: Evaluating Speed Distribution Heterogeneity on Rural Road Segments Using Non-Parametric Similarity Measures
Authors: Cantisani Giuseppe , Del Serrone Giulia , Mauro Raffaele , Peluso Paolo , Pompigna Andrea
Published: September 2024

Rural roads, often characterized by winding paths and nearby settlements, feature frequent curvature changes, junctions, and closely spaced private accesses that lead to significant speed variations. These variations are typically represented by average speed or v85 profiles. This paper examines complete speed distributions along rural two-lane roads using Floating Car Data (FCD). The Wasserstein distance, a non-parametric similarity measure, is employed to compare speed distributions recorded by a radar Control Unit (CU) and a selected FCD sample. Initially, FCD speeds were validated against CU speeds. Subsequently, differences in speed distributions between the CU location and specific sections identified by sharp curves, intersections, or accesses have been assessed. The Wasserstein Distance is proposed as the most effective synthetic indicator of speed distribution variability along roadways, attributed to its metric properties. This measure offers a more concise and immediate assessment compared to an extensive array of statistical metrics, such as mean, median, mode, variance, percentiles, v85, interquartile range, kurtosis, and symmetry, as well as qualitative assessments derived from box plot trends.
Heat Attainment and Retention in Surfers with and without a Land-Based Warm-Up and Accompanying Passive Heat Retention
Authors: Cook Christian J. , Serpell Benjamin G. , Hanna Lauren J. , Fox Aaron , Fourie Phillip J.
Published: September 2024

Surfing is a growing, high-participation recreational and competitive activity. It is relatively unique, being performed on, in, and through water with a range of temperatures. In other sports, warm-up and heat retention have proved useful at augmenting performance and ameliorating injury risk. Little work has been carried out examining this in surfing. The purpose of this work was to measure thermal profiles in surfers with and without warm-up and passive heat retention, and secondarily to assess any potential influence on free surfing. A repeated measures pre- and post- design was adopted whereby participants surfed in an artificial wave pool following an active warm-up combined with passive heat retention (experimental condition) and after no warm-up (control). Core body temperature was measured both occasions. Our results showed increases in core body temperature were greater for the experimental condition versus control (p = 0.006), and a time effect exists (p < 0.001)—in particular, a warm-up effect in the water itself was shown in both groups, possibly due to further activity (e.g., paddling) and wetsuit properties. Finally, performance trended to being superior following warm-up. We conclude that body warmth in surfers may be facilitated by an active warm-up and passive heat retention. In free surfing, this is associated with a trend towards better performance; it may also reduce injury risk.
Use of Indices Applied to Remote Sensing for Establishing Winter–Spring Cropping Areas in the Republic of Kazakhstan
Authors: Arystanov Asset , Karabkina Natalya , Sagin Janay , Nurguzhin Marat , King Rebecca , Bekseitova Roza
Published: September 2024

Farmers in Kazakhstan face unreliable water resources. This includes water scarcity in the summer, high fluctuations in precipitation levels, and an increase in extreme weather events such as snow, rain, floods, and droughts. Wheat production is regulated and subsidized by the Kazakh government to strengthen food security. The proper monitoring of crop production is vital to government agencies, as well as insurance and banking structures. These organizations offer subsidies through different levels support. Some farmers already use farmland soil monitoring combined with adaptive combinations of different crops. These include winter–spring plowing crop programs. Winter wheat crops are generally more adaptive and may survive summer droughts. Kazakhstan is a large country with large plots of farmland, which are complicated to monitor. Therefore, it would be reasonable to adapt more efficient technologies and methodologies, such as remote sensing. This research work presents a method for identifying winter wheat crops in the foothills of South Kazakhstan by employing multi-temporal Sentinel-2 data. Here, the researchers adapted and applied a Plowed Land Index, derived from the Brightness Index. The methodology encompasses satellite data processing, the computation of Plowed Land Index values for the swift recognition of plowed fields and the demarcation of winter wheat crop sowing regions, along with a comparative analysis of the acquired data with ground surveys.
Accurate Measurement of Tower Grounding Resistance for Single-Tower and Multi-Tower Parallel Scenarios Based on the Clamp Meter Method: For the Sustainable Operation of Towers
Authors: Zhang Yixuan , Wang Zoujun , Feng Kaiwen , Zhang Yirui , Tian Zhitong , Zheng Zhihui , Lu Hailiang
Published: September 2024

Transmission tower grounding safety is a critical element that significantly impacts the reliability and sustainability of power grids. Tower grounding resistance is a significant grounding characteristic parameter. In order to accurately measure the grounding resistance of towers using the clamp meter method in both single-tower and multi-tower parallel scenarios, this paper establishes theoretical calculation models for measuring tower grounding resistance using the clamp meter method. Considering the interaction between the artificial grounding device and the tower foundation, this paper models and simulates transmission towers and lightning shield wires, analyzing the influencing factors on the grounding resistance measurement results using the clamp meter method in both single- and multi-tower parallel scenarios. The results show that for single towers, the clamp meter measurement results increase with decreasing foundation root spacing and increasing length of the artificial device’s extension lines, but the changes are relatively small. In multi-tower grounding scenarios, due to the shunting effect of the parallel branches formed by the towers and lightning shield wires, the value is smaller than in single-tower grounding scenarios. Changing the number of parallel towers and the type of lightning shield wire produces little effect on the measurement results. However, changes in soil resistivity have the most significant impact. Therefore, correction formulas for the impact of soil resistivity on clamp meter measurements are proposed and then verified by applying them to field tests.
Does the Innovative City Pilot Policy Promote Urban Energy Use Efficiency? Evidence from China
Authors: Xiao Deheng , Sun Tengfei , Huang Kaixiang
Published: September 2024

The innovative city pilot policy (ICPP) is a key policy practice in China’s innovation-driven economic strategy, yet its influence on urban energy use efficiency (UEUE) has yet to be assessed. This study used balanced panel data from Chinese cities from the period of 2006 to 2022 to investigate the impact of innovative cities on urban energy consumption efficiency. The double-difference method, which treats creative cities as quasi-natural experiments, was applied to identify the impact mechanism of these cities. Additionally, this study looked at heterogeneity from several angles and assessed the effects of the policy on the environment. Following thorough testing to guarantee the reliability of the findings of this study—such as changing variables, ruling out further policy interferences, and running placebo tests—it can be concluded that the pilot program significantly improves urban energy consumption. The mechanism analysis performed in this study shows that, via talent concentration, utilizing technology, and optimizing the industrial structure, the creative city pilot policies increase energy consumption efficiency. Additionally, a heterogeneity analysis shows that eastern cities and cities with a high degree of digital finance benefit most from the legislation in terms of energy consumption efficiency. The application of creative city pilot programs has a more noticeable effect on increasing the energy consumption efficiency in eastern cities, as well as in cities with a high degree of digital infrastructure and digital finance, according to the heterogeneity analysis. Furthermore, an environmental consequence test shows that, by encouraging the growth of UEUE, the development of innovative cities can successfully help to reduce carbon emissions.