bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of Micro-Seismic Monitoring in Post-Fracturing Evaluation of Shale Gas: A Case Study of Well X from Puguang Area, China
Authors: Zhang Lufeng , Wang Haibo , Cai Jiujie , Zhang Shicheng
Published: June 2023

Multi-stage fracturing of horizontal wells is an indispensable technology to create complex fracture networks, which can unlock production potential and enable commercial productivity for shale gas with low porosity and permeability. Real-time monitoring of fracture networks is essential for adjusting key parameters, mitigating fracturing risks, and achieving optimal fracturing effects. Micro-seismic monitoring technology accurately captures and describes the development of fracture networks by detecting micro-seismic waves generated through rock ruptures, providing valuable insights into the evaluation of post-fracturing. In this study, we first introduced the basic parameters of well X that were obtained by laboratory experiments and logging interpretation, including porosity, gas-bearing properties, mineral composition, rock mechanics, and crustal stress. Then, the hydraulic fracturing scheme was designed on the basis of the geological engineering characteristics of well X. Finally, we conducted a comprehensive analysis of various factors that can affect hydraulic fracturing. This included an examination of the impact of pre-fluid temporary plugging and fracture complexity on the overall effectiveness of the operation. Based on the laboratory experiments and theoretical analysis, the following conclusions can be drawn: (1) fracture size is essentially formed when the fluid strength exceeds 35 m3/m; (2) both preflush with high viscosity and the amount of power sand exceeding 20 cubic meters are conducive to the propagation of fracture height; (3) temporary plugging balls facilitate the balanced propagation of multiple fracture clusters within a stage, whereas temporary plugging particles promote the formation of complex fractures; and (4) geological conditions are a prerequisite for creating a complex network of fractures, and only engineering techniques can facilitate the appropriate enhancement of fracture complexity. This study provides an essential method for the fracturing design of shale gas.
Ethical Decision-Making in Law Enforcement: A Scoping Review
Authors: Dempsey Ronald P. , Eskander Elizabeth E. , Dubljević Veljko
Published: June 2023

Decision-making in uncertain and stressful environments combined with the high-profile cases of police violence in the United States has generated substantial debates about policing and created challenges to maintaining public confidence and trust in law enforcement. However, despite the manifestations of reactions across the ideological spectrum, it is unclear what information is available in the literature about the convergence between ethical decision-making and policing. Therefore, an interdisciplinary scoping review was conducted to map the nature and extent of research evidence, identify existing gaps in knowledge, and discuss future implications for ethical decision-making in law enforcement. This review investigates the interaction between the job complexities of policing (psychological and normative factors) and aspects of ethical decision-making, synthesizing three distinct themes: (1) socio-moral dimensions impact the job complexities of police work, (2) lethal means and moral injury influence intuitive and rational decision-making, and (3) police wellness and interventions are critical to sustaining police readiness. Gaps in recruiting, training, and leadership and managerial practices can be broadly transformed to fundamentally emphasize officer wellness and a holistic approach to ethical practices, enabling police officers to uphold the rule of law, promote public safety, and protect the communities they serve.
Enhanced Radar Detection in the Presence of Specular Reflection Using a Single Transmitting Antenna and Three Receiving Antennas
Authors: Yang Yong , Wang Xue-Song
Published: June 2023

Radar target echoes undergo fading in the presence of specular reflection, which is adverse to radar detection. To address this problem, this paper proposes a radar detection method that uses a single transmitting antenna and three receiving antennas. The proposed method uses the maximum absolute value of the difference in the radar received signal power among the three receiving antennas as the test statistic. First, the target echo in the presence of specular reflection is analyzed. Then, selection of the required number of radar antennas and the heights at which they must be situated are discussed. Subsequently, analytical expressions of the radar detection probability and the false alarm probability are derived. Finally, simulation results are presented, which show that the proposed method improves radar detection performance in the presence of specular reflection.
Unsupervised Machine Learning for GNSS Reflectometry Inland Water Body Detection
Authors: Kossieris Stylianos , Asgarimehr Milad , Wickert Jens
Published: June 2023

Inland water bodies, wetlands and their dynamics have a key role in a variety of scientific, economic, and social applications. They are significant in identifying climate change, water resource management, agricultural productivity, and the modeling of land–atmosphere exchange. Changes in the extent and position of water bodies are crucial to the ecosystems. Mapping water bodies at a global scale is a challenging task due to the global variety of terrains and water surface. However, the sensitivity of spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) to different land surface properties offers the potential to detect and monitor inland water bodies. The extensive dataset available in the Cyclone Global Navigation Satellite System (CYGNSS), launched in December 2016, is used in our investigation. Although the main mission of CYGNSS was to measure the ocean wind speed in hurricanes and tropical cyclones, we show its capability of detecting and mapping inland water bodies. Both bistatic radar cross section (BRCS) and signal-to-noise ratio (SNR) can be used to detect, identify, and map the changes in the position and extent of inland waterbodies. We exploit the potential of unsupervised machine learning algorithms, more specifically the clustering methods, K-Means, Agglomerative, and Density-based Spatial Clustering of Applications with Noise (DBSCAN), for the detection of inland waterbodies. The results are evaluated based on the Copernicus land cover classification gridded maps, at 300 m spatial resolution. The outcomes demonstrate that CYGNSS data can identify and monitor inland waterbodies and their tributaries at high temporal resolution. K-Means has the highest Accuracy (93.5%) compared to the DBSCAN (90.3%) and Agglomerative (91.6%) methods. However, the DBSCAN method has the highest Recall (83.1%) as compared to Agglomerative (82.7%) and K-Means (79.2%). The current study offers valuable insights and analysis for further investigations in the field of GNSS-R and machine learning.
Identification of Brush Species and Herbicide Effect Assessment in Southern Texas Using an Unoccupied Aerial System (UAS)
Authors: Shen Xiaoqing , Clayton Megan K. , Starek Michael J. , Chang Anjin , Jessup Russell W. , Foster Jamie L.
Published: June 2023

Cultivation and grazing since the mid-nineteenth century in Texas has caused dramatic changes in grassland vegetation. Among these changes is the encroachment of native and introduced brush species. The distribution and quantity of brush can affect livestock production and water holding capacity of soil. Still, at the same time, brush can improve carbon sequestration and enhance agritourism and real estate value. The accurate identification of brush species and their distribution over large land tracts are important in developing brush management plans which may include herbicide application decisions. Near-real-time imaging and analyses of brush using an Unoccupied Aerial System (UAS) is a powerful tool to achieve such tasks. The use of multispectral imagery collected by a UAS to estimate the efficacy of herbicide treatment on noxious brush has not been evaluated previously. There has been no previous comparison of band combinations and pixel- and object-based methods to determine the best methodology for discrimination and classification of noxious brush species with Random Forest (RF) classification. In this study, two rangelands in southern Texas with encroachment of huisache (Vachellia farnesianna [L.] Wight & Arn.) and honey mesquite (Prosopis glandulosa Torr. var. glandulosa) were studied. Two study sites were flown with an eBee X fixed-wing to collect UAS images with four bands (Green, Red, Red-Edge, and Near-infrared) and ground truth data points pre- and post-herbicide application to study the herbicide effect on brush. Post-herbicide data were collected one year after herbicide application. Pixel-based and object-based RF classifications were used to identify brush in orthomosaic images generated from UAS images. The classification had an overall accuracy in the range 83–96%, and object-based classification had better results than pixel-based classification since object-based classification had the highest overall accuracy in both sites at 96%. The UAS image was useful for assessing herbicide efficacy by calculating canopy change after herbicide treatment. Different effects of herbicides and application rates on brush defoliation were measured by comparing canopy change in herbicide treatment zones. UAS-derived multispectral imagery can be used to identify brush species in rangelands and aid in objectively assessing the herbicide effect on brush encroachment.
PCRMLP: A Two-Stage Network for Point Cloud Registration in Urban Scenes
Authors: Liu Jingyang , Xu Yucheng , Zhou Lu , Sun Lei
Published: June 2023

Point cloud registration plays a crucial role in 3D mapping and localization. Urban scene point clouds pose significant challenges for registration due to their large data volume, similar scenarios, and dynamic objects. Estimating the location by instances (bulidings, traffic lights, etc.) in urban scenes is a more humanized matter. In this paper, we propose PCRMLP (point cloud registration MLP), a novel model for urban scene point cloud registration that achieves comparable registration performance to prior learning-based methods. Compared to previous works that focused on extracting features and estimating correspondence, PCRMLP estimates transformation implicitly from concrete instances. The key innovation lies in the instance-level urban scene representation method, which leverages semantic segmentation and density-based spatial clustering of applications with noise (DBSCAN) to generate instance descriptors, enabling robust feature extraction, dynamic object filtering, and logical transformation estimation. Then, a lightweight network consisting of Multilayer Perceptrons (MLPs) is employed to obtain transformation in an encoder–decoder manner. Experimental validation on the KITTI dataset demonstrates that PCRMLP achieves satisfactory coarse transformation estimates from instance descriptors within a remarkable time of 0.0028 s. With the incorporation of an ICP refinement module, our proposed method outperforms prior learning-based approaches, yielding a rotation error of 2.01° and a translation error of 1.58 m. The experimental results highlight PCRMLP’s potential for coarse registration of urban scene point clouds, thereby paving the way for its application in instance-level semantic mapping and localization.
Energy-Efficient Data Transmission for Underwater Wireless Sensor Networks: A Novel Hierarchical Underwater Wireless Sensor Transmission Framework
Authors: Zhang Jiasen , Wang Xiaomei , Wang Bin , Sun Weikai , Du Haiyang , Zhao Yuanke
Published: June 2023

The complexity of the underwater environment enables significant energy consumption of sensor nodes for communication with base stations in underwater wireless sensor networks (UWSNs), and the energy consumption of nodes in different water depths is unbalanced. How to improve the energy efficiency of sensor nodes and meanwhile balance the energy consumption of nodes in different water depths in UWSNs are thus urgent concerns. Therefore, in this paper, we first propose a novel hierarchical underwater wireless sensor transmission (HUWST) framework. We then propose a game-based, energy-efficient underwater communication mechanism in the presented HUWST. It improves the energy efficiency of the underwater sensors personalized according to the various water depth layers of sensor locations. In particular, we integrate the economic game theory in our mechanism to trade off variations in communication energy consumption due to sensors in different water depth layers. Mathematically, the optimal mechanism is formulated as a complex nonlinear integer programming (NIP) problem. A new energy-efficient distributed data transmission mode decision algorithm (E-DDTMD) based on the alternating direction method of multipliers (ADMM) is thus further proposed to tackle this sophisticated NIP problem. The systematic simulation results demonstrate the effectiveness of our mechanism in improving the energy efficiency of UWSNs. Moreover, our presented E-DDTMD algorithm achieves significantly superior performance to the baseline schemes.
Metaheuristic for Optimal Dynamic K-Coloring Application on Band Sharing for Automotive Radars
Authors: Roudiere Sylvain , Martinez Vincent , Maréchal Pierre , Delahaye Daniel
Published: June 2023

The number of vehicles equipped with radars on the road has been increasing for years and is expected to reach 50% of cars by 2030. This rapid rise in radars will likely increase the risk of harmful interference, especially since radar specifications from standardization bodies (e.g., ETSI) provide requirements in terms of maximum transmit power but do no mandate specific radar waveform parameters nor channel access scheme policies. Techniques for interference mitigation are thus becoming very important to ensure the long-term correct operation of radars and upper-layer ADAS systems that depend on them in this complex environment. In our previous work, we have shown that organizing the radar band into time-frequency resources that do not interfere with each other vastly reduces the amount of interference by facilitating band sharing. In this paper, a metaheuristic is presented to find the optimal resource sharing between radars, knowing their relative positions and thereby the line-of-sight and non-line-of-sight interference risks during a realistic scenario. The metaheuristic aims at optimally minimizing interference while minimizing the number of resource changes that radars have to make. It is a centralized approach where everything about the system is known (e.g., the past and future positions of the vehicles). This and the high computational load induce that this algorithm is not meant to be used in real-time. However, the metaheuristic approach can be extremely useful for finding near optimal solutions in simulations, allowing for the extraction of efficient patterns, or as data generation for machine learning.
High-Dynamic-Range Tone Mapping in Intelligent Automotive Systems
Authors: Shopovska Ivana , Stojkovic Ana , Aelterman Jan , Van Hamme David , Philips Wilfried
Published: June 2023

Intelligent driver assistance systems are becoming increasingly popular in modern passenger vehicles. A crucial component of intelligent vehicles is the ability to detect vulnerable road users (VRUs) for an early and safe response. However, standard imaging sensors perform poorly in conditions of strong illumination contrast, such as approaching a tunnel or at night, due to their dynamic range limitations. In this paper, we focus on the use of high-dynamic-range (HDR) imaging sensors in vehicle perception systems and the subsequent need for tone mapping of the acquired data into a standard 8-bit representation. To our knowledge, no previous studies have evaluated the impact of tone mapping on object detection performance. We investigate the potential for optimizing HDR tone mapping to achieve a natural image appearance while facilitating object detection of state-of-the-art detectors designed for standard dynamic range (SDR) images. Our proposed approach relies on a lightweight convolutional neural network (CNN) that tone maps HDR video frames into a standard 8-bit representation. We introduce a novel training approach called detection-informed tone mapping (DI-TM) and evaluate its performance with respect to its effectiveness and robustness in various scene conditions, as well as its performance relative to an existing state-of-the-art tone mapping method. The results show that the proposed DI-TM method achieves the best results in terms of detection performance metrics in challenging dynamic range conditions, while both methods perform well in typical, non-challenging conditions. In challenging conditions, our method improves the detection F2 score by 13%. Compared to SDR images, the increase in F2 score is 49%.
Identification of Control-Related Signal Path for Semi-Active Vehicle Suspension with Magnetorheological Dampers
Authors: Krauze Piotr
Published: June 2023

This paper presents a method for the identification of control-related signal paths dedicated to a semi-active suspension with MR (magnetorheological) dampers, which are installed in place of standard shock absorbers. The main challenge comes from the fact that the semi-active suspension needs to be simultaneously subjected to road-induced excitation and electric currents supplied to the suspension MR dampers, while a response signal needs to be decomposed into road-related and control-related components. During experiments, the front wheels of an all-terrain vehicle were subjected to sinusoidal vibration excitation at a frequency equal to 12 Hz using a dedicated diagnostic station and specialised mechanical exciters. The harmonic type of road-related excitation allowed for its straightforward filtering from identification signals. Additionally, front suspension MR dampers were controlled using a wideband random signal with a 25 Hz bandwidth, different realisations, and several configurations, which differed in the average values and deviations of control currents. The simultaneous control of the right and left suspension MR dampers made it necessary to decompose the vehicle vibration response, i.e., the front vehicle body acceleration signal, into components related to the forces generated by different MR dampers. Measurement signals used for identification were taken from numerous sensors available in the vehicle, e.g., accelerometers, suspension force and deflection sensors, and sensors of electric currents, which control the instantaneous damping parameters of MR dampers. The final identification was carried out for control-related models evaluated in the frequency domain and revealed several resonances of the vehicle response and their dependence on the configurations of control currents. In addition, the parameters of the vehicle model with MR dampers and the diagnostic station were estimated based on the identification results. The analysis of the simulation results of the implemented vehicle model carried out in the frequency domain showed the influence of the vehicle load on the absolute values and phase shifts of control-related signal paths. The potential future application of the identified models lies in the synthesis and implementation of adaptive suspension control algorithms such as FxLMS (filtered-x least mean square). Adaptive vehicle suspensions are especially preferred for their ability to quickly adapt to varying road conditions and vehicle parameters.
IRDC-Net: An Inception Network with a Residual Module and Dilated Convolution for Sign Language Recognition Based on Surface Electromyography
Authors: Wang Xiangrui , Tang Lu , Zheng Qibin , Yang Xilin , Lu Zhiyuan
Published: June 2023

Deaf and hearing-impaired people always face communication barriers. Non-invasive surface electromyography (sEMG) sensor-based sign language recognition (SLR) technology can help them to better integrate into social life. Since the traditional tandem convolutional neural network (CNN) structure used in most CNN-based studies inadequately captures the features of the input data, we propose a novel inception architecture with a residual module and dilated convolution (IRDC-net) to enlarge the receptive fields and enrich the feature maps, applying it to SLR tasks for the first time. This work first transformed the time domain signal into a time–frequency domain using discrete Fourier transformation. Second, an IRDC-net was constructed to recognize ten Chinese sign language signs. Third, the tandem CNN networks VGG-net and ResNet-18 were compared with our proposed parallel structure network, IRDC-net. Finally, the public dataset Ninapro DB1 was utilized to verify the generalization performance of the IRDC-net. The results showed that after transforming the time domain sEMG signal into the time–frequency domain, the classification accuracy (acc) increased from 84.29% to 91.70% when using the IRDC-net on our sign language dataset. Furthermore, for the time–frequency information of the public dataset Ninapro DB1, the classification accuracy reached 89.82%; this value is higher than that achieved in other recent studies. As such, our findings contribute to research into SLR tasks and to improving deaf and hearing-impaired people’s daily lives.
Recent Advances in Underwater Signal Processing
Authors: Zhang Xuebo , Sun Haixin
Published: June 2023

The ocean, covering 71% of the Earth’s surface, is integral to human life [...]
Low-Profile Dual-Band Reflector Antenna for High-Frequency Applications
Authors: Lu Senlin , Qu Shi-Wei
Published: June 2023

A high-gain low-profile reflector antenna with dual-band radiation ability is presented in this paper. The antenna achieves a relative 2 dB gain bandwidth of 10% around fl, and a relative 2 dB gain bandwidth of 20%, around fh, where fl and fh are the center operating frequencies of the frequency bands of 29.4~32.4 GHz and 142~174 GHz, respectively. To achieve the dual-band radiation ability, a composite dual-band feed with an fh/fl ratio of around 5 is proposed as the feed for the reflector antenna, which includes a higher-band circular waveguide and a lower-band coaxial horn. The metallic elliptical surface serves as the subreflector (SR) in the higher band, while the SR is the planar reflectarray in the lower band. Due to the design of the dual reflector, the dual-band reflector antenna features a low focal-to-diameter (F/D) ratio of approximately 0.2. According to the simulated results, the proposed reflector antenna achieves efficiencies of 59.0% and 42.9% at fl and fh, respectively. For verification purposes, a Ku/E-band scaled prototype is manufactured. The measured VSWRs, radiation patterns, and gains are in reasonable agreement with the simulated ones, proving the correctness of the proposed design method.
Safety Practices and Associated Factors among Healthcare Waste Handlers in Four Public Hospitals, Southwestern Ethiopia
Authors: Ketema Sisay , Melaku Abayneh , Demelash Habtamu , G/Mariam Meseret , Mekonen Seblework , Addis Taffere , Ambelu Argaw
Published: June 2023

Occupational safety is a critical concern for disease prevention and control at healthcare facilities. Medical waste handlers, in particular, are those most exposed to occupational hazards among healthcare workers. Therefore, this cross-sectional study was conducted to evaluate safety practices and associated factors among healthcare waste handlers in four public hospitals, southwest Ethiopia from 15 March to 30 May 2022. The study included 203 healthcare waste handlers. The data were collected using an interviewer-administered questionnaire and observational checklists. The overall performance of occupational safety practices among healthcare waste handlers was 47.3% (95%CI; 40.3, 54.2). Waste handlers with an educational status of secondary and above (AOR 4.95; 95%CI 2.13, 11.50), good knowledge of infection prevention and safety practices (AOR 4.95; 95%CI 2.13, 11.50), training in infection prevention and safety practices (AOR 2.57; 95%CI 1.25, 5.29), and adequate access to safety materials (AOR 3.45; 95%CI 1.57, 7.60) had significantly better occupational safety practices than their counterparts. In general, medical waste handlers’ occupational safety practices were found to be inadequate. Waste handlers’ knowledge of safety measures and training, educational level, and availability of safety materials were predictors of safe occupational practices. Therefore, appropriate strategies and actions are needed to ensure the safe occupational practices of healthcare waste handlers.
Glitches in the Digitization of Asylum: How CBP One Turns Migrants’ Smartphones into Mobile Borders
Authors: Kocher Austin
Published: June 2023

As the emerging literature on migration studies has demonstrated, migrants who are seeking asylum around the world are increasingly finding that the process is mediated by a variety of new technologies. While the process of digitizing various aspects of migrant protection may promise improvements, new technologies also risk limiting access to asylum for migrants who are unable to overcome these new digital barriers to entry. This article explores the digitization of asylum by examining the context and consequences of the U.S. government’s deployment of a smartphone app called CBP One in early 2023 which suddenly became one of the main pathways for migrants to seek asylum along the U.S.–Mexico border. In doing so, this article makes two contributions to the literature on the digitization of asylum. First, the article shows how CBP One, which was not initially designed for asylum seekers, morphed into a tool that took center stage in border enforcement statecraft during a period of exceptional migration policies. Second, this article examines the range of what have been referred to as “glitches” with CBP One, to demonstrate how the app created new digital barriers to asylum. Rather than accepting glitches as mere accidents, this article argues that these glitches are the result of a political decision to force already vulnerable migrants to rely upon experimental technologies that hinder rather than facilitate their asylum-seeking process.
Microbial Degradation of Plant Residues Rapidly Causes Long-Lasting Hypoxia in Soil upon Irrigation and Affects Leaching of Nitrogen and Metals
Authors: Siedt Martin , Teggers Eva-Maria , Linnemann Volker , Schäffer Andreas , van Dongen Joost T.
Published: June 2023

With this study, we aim to relate the substrate quality of different organic materials derived from plant residues to the respiratory activity of soil microorganisms after amendment, the formation of oxygen gradients upon irrigation, and the leaching of macronutrients and metals in soil. Elemental analyses were performed to determine the chemical composition of wheat straw, green compost, and a biochar product, showing that carbon availability, C/N ratio, and metal contents varied markedly. Consequently, after application to well-aerated sandy loam soil at 1% w/w, only straw increased microbial activity substantially, and nitrate was depleted within one week. Upon intense irrigation of soil columns packed with differently amended soils, strong hypoxia formed only in straw–soil, where microbial oxygen demand for straw degradation was high. This was enhanced after the application of mineral fertilizers, and nitrate leaching was mitigated. With the decreasing redox potential in straw–soil, the leaching of Fe, Mn, Al, Ni, Co, and As was increased. However, nitrate from mineral fertilizer mitigated the reduction of redox potential and, thus, the leaching of these metals. Measuring oxygen at different depths revealed near anoxic conditions at −15 cm of straw–soil with NP-fertilizer applied within 12 h after the start of irrigation and remained for at least 60 h, while oxygen showed extensive fluctuations in the upper few centimeters. This study showed that organic soil amendments with high carbon availability induce microbial respiration to the extent that causes strong and long-lasting hypoxia upon irrigation, even in sandy soil, which leads to substantial effects on the mobility of nutrients and toxic metals. In contrast, organic soil amendments with low carbon availability did not cause such effects.
Research on Sustainable High-Quality Forestry Development in China—From Measurements, Dynamic Evolution, and Regional Differences
Authors: Jiang Yu , Zhang Shihao
Published: June 2023

Following the new development philosophy, this research elaborates the connotation of sustainable high-quality forestry development and constructs an evaluation index system based on the connotation. The entropy-based TOPSIS method was used to measure the forestry development level from 2005 to 2021 in China. On this basis, the kernel density estimation, spatial association analysis, Markov chain, and Gini index were used to analyze the evolution characteristics in time and space and regional differences in China’s forestry development from multiple angles and levels. The results show that, first, although the overall sustainable high-quality development level of China’s forestry tends to rise, and the level ranking of each province is relatively stable, the development level varies greatly from province to province; second, the development level in the central, eastern, and western regions shows an upward trend, and in the northeast region, it rose first and then fell, presenting a decreasing step distribution of from the eastern, central, northeast, to western regions; third, the regional differences are the main reasons for the development difference in China’s forestry, with the largest difference in the east, followed by the west, central, and northeast regions; fourth, sustainable high-quality forestry development in various provinces has a great effect in terms of spatial agglomeration, and the spatial lag has a significant impact on the transfer of sustainable high-quality forestry development; however, there are still some difficulties in achieving progress in its development.
Bituminous Coal Sorption Characteristics and Its Modeling of the Main Coal Seam Gas Component in the Huaibei Coalfield, China
Authors: Wu Gang , Ye Zhiwei , Zhang Lei , Tang Jun
Published: June 2023

Knowledge of the gas sorption and permeability characteristics of a coal provides an essential basis for the evaluation of coalbed methane reserves and their recoverability. Thus, the gas excess sorption capacities of the main gas component of coal seam gas (CSG) in bituminous coal samples derived from the Xutuan Coal Mine in the Huaibei Coalfield, in the Anhui Province of China, were measured using a volumetric method. The results showed that under the same equilibrium pressure, the order of excess sorption capacity was CO2 > CH4 > N2. Furthermore, the sorption capacity ratios of coal from the Xutuan Mine for CO2, CH4, and N2 were approximately 6.0:2.3:1. It was also demonstrated that the sorption capacity during depressurization was always larger than that of the adsorption process, which is indicative of desorption hysteresis. The behaviors of three adsorption models, Langmuir, BET, and D-R, all of which include two parameters, are considered in this paper. The different gas sorption measurement data were fitted by the three models. For the bituminous coal samples, the fits of the D-R equation of all three different gases are higher than 0.99, the fits of the Langmuir equation are higher than 0.985, while the fits of the BET equation for CH4 and N2 absorption are higher than 0.95. However, the fits of the BET equation for CO2 absorption are only about 0.5. Coal sorption has an apparent influence on coal permeability; the permeability of the same coal sample to N2, CH4, and CO2 gases was tested and analyzed. The result shows that the permeability of CO2 was found to be lower than that of other coal seam gas constituents, CH4 and N2, due to their different adsorption abilities.
Early Warning Evaluation and Warning Trend Analysis of the Resource and Environment Carrying Capacity in Altay Prefecture, Xinjiang
Authors: Lan Shengxin , Wang Xiaona , Li Meifang , Fu Xiaohua , Xu Mei , Zhu Jian , Wang Ping , Mao Yu , Dong Zuoji , Li Jiahui , Cao Lanfang , Liu Zhiming
Published: June 2023

Ecologically fragile areas in China account for more than half of its land area. Performing early warning assessments and trend analyses of resource and environment carrying capacity in ecologically fragile areas can lay a scientific foundation for ecological conservation in the areas. Based on the connotation of resource and environment carrying capacity, an early warning index system of resource and environment carrying capacity in Altay prefecture was constructed from the three aspects natural resource carrying capacity, eco-environment carrying capacity, and economic and social support capacity. The grey relational projection method model was used to analyze the current alarm situation of the resource and environment carrying capacity in Altay prefecture from 2011 to 2020, and then the back propagation (BP) neural network and a mathematical statistics software were used to predict the evolution of the alarm situation of the resource and environment carrying capacity in Altay prefecture from 2021 to 2025. The results demonstrated that (1) the natural resource carrying capacity subsystem was the main system of the development of the resource and environment carrying capacity in Altay prefecture, and its impact on the resource and environment carrying capacity in Altay prefecture was greater than the eco-environment carrying capacity and economic and social support capacity; (2) the resource and environmental carrying capacity of Altay prefecture showed a slight upward trend from 2011 to 2020, although the range was constrained and the level of warning remained “moderate warning”. A spatial pattern of “weak in the middle, strong in the two poles” was exhibited by the warning scenario about the carrying capacity of each county and city. Except for the warning of Habahe County and Qinghe County, where the warning was slightly worse than that in 2020, the warning of resource and environment carrying capacity in Altay prefecture and other counties and cities would show a trend of fluctuation and decline from 2021 to 2025. However, the degree of alarm did not change substantially and remained at the level of “moderate warning”; (3) the main factors restricting the mitigation of the warning of resource and environment carrying capacity in Altay prefecture included a low soil fertility index, a small total reservoir capacity, low per capita mineral resource reserves, a low water resource development and utilization rate, a low comprehensive utilization rate of industrial solid waste, and a low land output rate.
Too Much of a Good Thing? The Impact of Serial M&A on Innovation Performance
Authors: Zhang Xiaoxu , Song Yu , Liu Hongyu
Published: June 2023

Based on the sample of serial M&A of Chinese listed companies from 2010–2019, this paper intends to investigate the impact of serial M&A on innovation performance and the impact of financing constraints and digital inclusive finance (DIF). The empirical results show that an inverted U-shaped relationship exists between serial M&A and innovation performance that first goes up and then goes down. The results of mechanism analysis show that financing constraints play a mediating role in the inverted U-shaped relationship between serial M&A and innovation performance, while DIF plays a moderating role in the mediating effect of serial M&A on innovation performance through the financing constraint. The heterogeneity analysis finds that the inverted U-shaped relationship between serial M&A and innovation performance is more significant in firms with non-state ownership property, a higher business environment index, and medium and large-scale firm size. The research results not only help to promote the in-depth analysis of the impact of serial M&A on innovation performance, but also help to provide targeted theoretical reference and practical guidance for corporate management decision making.
Experimental and Theoretical Study for a Displacement-Controlled Design Method of Embedded Cantilever Retaining Walls (Piles)
Authors: Fan Xiaozhen , Xu Changjie , Liang Luju
Published: June 2023

Displacement control is critical to the design of retaining walls, especially in urban areas, to avoid any potential damage to adjacent structures during excavations. In this study, model tests are first conducted to investigate the stress and deformation mechanisms of an embedded cantilevered retaining (ECR) wall during excavations. The development of the wall top displacement and the active and passive earth pressures acting on the ECR walls during excavations are studied. Upon the experimental observations, a displacement-dependent earth pressure coefficient is proposed to derive an analytical solution to predict both the active and passive earth pressure acting on the ECR wall (pile), where the displacement value and displacement mode of the ECR wall (pile) are taken into account. Comparisons between the model predictions and test results are carried out. A good agreement is observed, which shows the validity of the proposed solution. Based on the proposed solution, a displacement-controlled method for the design of ECR walls (piles) that takes into account the location of the rotation point is proposed. Parametric studies are conducted to demonstrate the impact of deformation control and excavation depth on the design parameters of ECR walls (piles).
Research on the Regional Cooperation Innovation Network of Universities in the Guangdong–Hong Kong–Macao Great Bay Area
Authors: Wang Yan , Liu Zhihua
Published: June 2023

As typical innovation organizations, the structure and efficiency of cooperation among universities’ innovation behaviors are important influencing factors for regional innovation sustainable development. In 2019, the Chinese government promulgated the “Outline of the Development Plan of The Guangdong, Hong Kong and Macao Great Bay Area”, which directly promotes a sustainable cooperation network of universities in the Great Bay Area. This study used UCINET to visualize the cooperation network of universities in Guangdong, Hong Kong, and Macao based on the cooperation data generated by 35 universities in the Guangdong–Hong Kong–Macao Great Bay Area, jointly establishing 37 professional alliances that developed 888 cooperation ties from 2017 to 2022. The results show that the current cooperative network density of universities in the Great Bay Area is high (density = 0.746), but the cohesion trend is not significant (network centralization = 26.92%); a clear circle structure has been formed. The network exhibits a narrow shape at both ends and widens in the middle; the higher the hierarchical position of universities in the region, the more likely they are to enter the core cooperation network and establish more cooperation relationships. Universities in the marginal circles find it especially difficult to initiate cooperative relationships due to their disadvantageous position in terms of limited resources and a lack of administrative intervention. The current cooperation situation still has room for expansion.
Cite Space-Based Bibliometric Analysis of Green Marketing
Authors: Liu Li , Cui Hailang , Nie Yuankun
Published: June 2023

“Lucid waters and lush mountains are invaluable assets”. Green marketing and sustainable development have become crucial topics in economic and social development. During 2019–2023, there are nearly 952 publications on green marketing-related topics in the Web of Science core database, and a large number of scholars researched green marketing, but there is still a lack of comprehensive and systematic studies on the current status of green marketing research and hot trends. The main purpose of this study is to summarize and sort out the current status of green marketing research by reviewing the literature related to green marketing (enterprises vs. consumers). Meanwhile, using Cite Space 6.2 R2 software, the core literature of green marketing in the past five years was screened, the data were visualized and analyzed, and a knowledge map of the cooperative authors, institutions, countries, and keywords was drawn in an attempt to discover the research hotspots and major development trends of green marketing. The results show that the publications and citation frequency of green marketing-related literature showed an increasing trend from 2019 to 2023, and the highest citation frequency was reached in 2022. Green marketing literature appears more frequently in the USA, China, and England and has a higher influence. Green management, firm performance, green innovation, green strategy, green capability, sustainable development, green business, green market orientation, green supply chain management, green exploitation, green responsibility, ecosystem, green commitment, green perceptions, green competitive advantage, and corporate social responsibility reflect the hot topics and important themes of green marketing research. This study innovatively combines a green marketing literature review and bibliometric analysis, comprehensively and systematically discusses the current status of green marketing research and hot trends based on both textual and data perspectives, and puts forward the “individual-environment-economy-society” virtuous ecological cycle of green marketing from a macro perspective.
A Comprehensive Review on Power-Quality Issues, Optimization Techniques, and Control Strategies of Microgrid Based on Renewable Energy Sources
Authors: Hernández-Mayoral Emmanuel , Madrigal-Martínez Manuel , Mina-Antonio Jesús D. , Iracheta-Cortez Reynaldo , Enríquez-Santiago Jesús A. , Rodríguez-Rivera Omar , Martínez-Reyes Gregorio , Mendoza-Santos Edwin
Published: June 2023

Microgrids (MGs) are systems that cleanly, efficiently, and economically integrate Renewable Energy Sources (RESs) and Energy Storage Systems (ESSs) to the electrical grid. They are capable of reducing transmission losses and improving the use of electricity and heat. However, RESs presents intermittent behavior derived from the stochastic nature of the renewable resources available on site. This can cause power-quality issues throughout the electrical grid, which can be solved by different optimization techniques and/or control strategies applied to power converters. This paper offers a detailed review of the literature regarding three important aspects: (i) Power-quality issues generated in MGs both in islanded mode and grid-connected mode; (ii) Optimization techniques used in the MGs to achieve the optimal operating conditions of the Energy Management System (EMS); and (iii) Control strategies implemented in the MGs to guarantee stability, mitigation of power-quality issues, power balance, and synchronization with the grid. It is worth mentioning that in this paper, we emphasize hybrid MGs (HMGs) since they combine the benefits of AC–MGs and DC–MGs while increasing system reliability. As the utility grid moves toward an optimal design of MG structures, this paper will serve as a foundation for future research, comparative analysis, and further development of novel techniques regarding HMGs.
Teacher Professional Development, Character Education, and Well-Being: Multicomponent Intervention Based on Positive Psychology
Authors: García-Álvarez Diego , Soler María José , Cobo-Rendón Rubia , Hernández-Lalinde Juan
Published: June 2023

The COVID-19 educational crisis has generated both psychosocial risks and growth opportunities for teaching staff; these are challenges to be addressed from the perspective of sustainable development in SDG 3 Health and Well-being and SDG 4 Quality Education. During the pandemic, a character education training experience was carried out for principals and teacher coordinators, with the dual purpose of developing professional competencies for the application of positive psychology in educational centers and strengthening teacher well-being: specifically, dedication and enthusiasm in conjunction with personal resources such as self-efficacy and resilience. The multicomponent intervention based on positive psychology applied to education was carried out with a sample of 32 teaching coordinators and school principals (mean age 45.9 years; 93.75% female staff and 71.8% between 16 and 21 years of experience) from different departments in Uruguay. The results suggest that the intervention was effective, detecting higher scores in the post-test in self-efficacy (F = 18.17, p < 0.001, η2 = 0.40), resilience (F = 13.41, p = 0.001, η2 = 0.33), dedication and enthusiasm (F = 8.09, p = 0.008, η2 = 0.23), and teacher training (F = 8.36, p = 0.007, η2 = 0.24). It is concluded that the training program can provide an opportunity for improving teacher health and well-being, as well funcitoning as a device for promoting teacher professional development.
Analysis of Spatial and Temporal Variation and Influencing Factors of Rural Land Dependence from the Perspective of Human-Land Relationship
Authors: Guo Liuna , Guo Lina , Li Jiaming , Zhao Yanxia , Jiang Guanghui
Published: June 2023

Face the issues of rural youth outflow, increase of aging population, and rural decline, this research explored the spatiotemporal evolution characteristics and influencing factors of the rural human-land relationship using the quantification index of rural land dependence. The research defines the concept of rural land dependence and constructs an evaluation index system for rural land dependence. By using the entropy weight method, the research quantitatively measures the high and low levels of rural land dependence in 30 provincial administrative units in China from 2006 to 2020. Besides, the GIS spatial analysis and geodetector are used to explore and analyze the spatial-temporal pattern and influencing factors of China’s land dependence. The results show that: (1) Temporal evolution: Since 2006, the level of rural land dependence in China has shown a decreasing trend, with economic dependence > population dependence > spatial dependence in terms of partial dependence differences. (2) Spatial pattern: During the study period, there are regional differences in the spatial distribution of rural land dependence in China, with a “high in the southwest and low in the eastern coastal areas” characteristic. The distribution of high-dependence areas has changed from being concentrated to being dispersed, while the distribution of low-dependence areas has changed from being dispersed to being concentrated. (3) Influencing factors analysis: From 2006 to 2018, the number of large agricultural employees is the main influencing factor of land dependence. With the decrease of population dependence and the increase of spatial dependence indexes, as well as the influence of the social environment, the area of rural areas and the total area of the region became the main influencing factor of land dependence from 2018 to 2020. The results can provide scientific basis for deepening the research on rural land use efficiency, and also provide decision support for promoting rural sustainable development and achieving common prosperity.