bluuebunny/crossref_metadata_2025 huggingface dataset:
Gottschelia (Gottscheliaceae, Marchantiophyta) in Indochina
Authors: Bakalin Vadim A. , Vilnet Anna A. , Klimova Ksenia G. , Nguyen Van Sinh , Choi Seung Se
Published: August 2024

Gottschelia, collected for the first time in Indochina, inspired an attempt to review the genus phylogeny to identify a more precise position of Indochinese plants. The genetic distance between African and Asian populations of G. schizopleura sensu lato was confirmed. The two groups should be treated as different species. A new combination, G. microphylla comb. nov., has been proposed for Asian plants. Aside from molecular genetics, distinguishing this species from the presumable strictly African G. schizopleura is also possible by morphological characteristics, as well as by its distribution. At the same time, at least three groups are distinguished among Asian haplotypes of G. microphylla, each of which can be interpreted as a species or, at least, subspecies. A morphological description, intravital photographs of the general habitat, and details of the morphological structures are provided. The position of Gottschelia in the phylogenetic schema of Jungermanniales does not allow us to attribute it to any of the known families and forces us to describe a new family, Gottscheliaceae, which is phylogenetically somewhat related to the Chaetophyllopsidaceae re-evaluated here and very different from Gottscheliaceae morphologically.
Changes in the Chemical Composition of Polyethylene Terephthalate under UV Radiation in Various Environmental Conditions
Authors: Rostampour Sara , Cook Rachel , Jhang Song-Syun , Li Yuejin , Fan Chunlei , Sung Li-Piin
Published: August 2024

Polyethylene terephthalate has been widely used in the packaging industry. Degraded PET micro(nano)plastics could pose public health concerns following release into various environments. This study focuses on PET degradation under ultraviolet radiation using the NIST SPHERE facility at the National Institute of Standards and Technology in saturated humidity (i.e., ≥95% relative humidity) and dry conditions (i.e., ≤5% relative humidity) with varying temperatures (30 °C, 40 °C, and 50 °C) for up 20 days. ATR-FTIR was used to characterize the chemical composition change of degraded PET as a function of UV exposure time. The results showed that the cleavage of the ester bond at peak 1713 cm−1 and the formation of the carboxylic acid at peak 1685 cm−1 were significantly influenced by UV radiation. Furthermore, the formation of carboxylic acid was considerably higher at saturated humidity and 50 °C conditions compared with dry conditions. The ester bond cleavage was also more pronounced in saturated humidity conditions. The novelty of this study is to provide insights into the chemical degradation of PET under environmental conditions, including UV radiation, humidity, and temperature. The results can be used to develop strategies to reduce the environmental impact of plastic pollution.
Design and Evaluation of a Novel Passive Shoulder Exoskeleton Based on a Variable Stiffness Mechanism Torque Generator for Industrial Applications
Authors: Zhu Yu , Balser Felix , Shen Ming , Bai Shaoping
Published: August 2024

Work-related musculoskeletal disorders (WMSDs) are a common occupational health problem in industries, and they can lead to decreased productivity and a reduced quality of life for workers. Exoskeletons, as an emerging technology, have the potential to solve this challenge by assisting arm movements and reducing muscle effort during load lifting tasks. In this paper, a passive exoskeleton based on a variable stiffness mechanism (VSM) torque generator is proposed and evaluated. This exoskeleton can provide adjustable torque curves and accommodate three degrees of freedom (DOFs) while remaining compact and lightweight. The workspace analysis shows that the workspace of this exoskeleton is sufficient for most industrial manual handling tasks. The experimental results demonstrate that the exoskeleton effectively reduces muscle effort during overhead reaching and load-lifting tasks, highlighting its effectiveness for repetitive tasks in industrial settings.
Trends and Innovations in Surface Water Monitoring via Satellite Altimetry: A 34-Year Bibliometric Review
Authors: Huang Zhengkai , Sun Rumiao , Wang Haihong , Wu Xin
Published: August 2024

The development of satellite altimetry has significantly advanced the application of satellite Earth observation technologies in surface water monitoring, resulting in a substantial body of research. Although numerous reviews have summarized progress in this field, their analyses are often limited in scope and fail to provide a systematic, quantitative assessment of the current research prospects and trends. To address this gap, we utilize CiteSpace and VOSviewer bibliometric software to analyze 13,500 publications from the WOS database, spanning the years from 1988 to 2022. Our analysis focused on publication volume, authorship, collaboration networks, and content. We also compare data from Google Scholar and Scopus to validate the reliability of our dataset. Our findings indicate a steadily growing research potential in this field, as evidenced by trends in publication volume, authorship, journal influence, and disciplinary focus. Notably, the leading journals are primarily in the realm of remote sensing, while key disciplines include geology, remote sensing science, and oceanography. Keyword analysis revealed current research hotspots such as sea-level rise, snow depth, and machine learning applications. Among various water body types, research on glaciers ranks second only to ocean studies. Furthermore, research focus areas are shifting from large oceanic regions like the Pacific and Atlantic Oceans to significant inland water bodies, notably the Tibetan Plateau and the Amazon basin. This study combines qualitative and quantitative methods to analyze vast amounts of information in the field of surface water monitoring by satellite altimetry. The resulting visualizations provide researchers with clear insights into the development trends and patterns within this domain, offering valuable support for identifying future research priorities and directions.
A New Open-Source Software to Help Design Models for Automatic 3D Point Cloud Classification in Coastal Studies
Authors: Pellerin Le Bas Xavier , Froideval Laurent , Mouko Adan , Conessa Christophe , Benoit Laurent , Perez Laurent
Published: August 2024

This study introduces a new software, cLASpy_T, that helps design models for the automatic 3D point cloud classification of coastal environments. This software is based on machine learning algorithms from the scikit-learn library and can classify point clouds derived from LiDAR or photogrammetry. Input data can be imported via CSV or LAS files, providing a 3D point cloud, enhanced with geometric features or spectral information, such as colors from orthophotos or hyperspectral data. cLASpy_T lets the user run three supervised machine learning algorithms from the scikit-learn API to build automatic classification models: RandomForestClassifier, GradientBoostingClassifier and MLPClassifier. This work presents the general method for classification model design using cLASpy_T and the software’s complete workflow with an example of photogrammetry point cloud classification. Four photogrammetric models of a coastal dike were acquired on four different dates, in 2021. The aim is to classify each point according to whether it belongs to the ‘sand’ class of the beach, the ‘rock’ class of the riprap, or the ‘block’ class of the concrete blocks. This case study highlights the importance of adjusting algorithm parameters, selecting features, and the large number of tests necessary to design a classification model that can be generalized and used in production.
MGCET: MLP-mixer and Graph Convolutional Enhanced Transformer for Hyperspectral Image Classification
Authors: Al-qaness Mohammed A. A. , Wu Guoyong , AL-Alimi Dalal
Published: August 2024

The vision transformer (ViT) has demonstrated performance comparable to that of convolutional neural networks (CNN) in the hyperspectral image classification domain. This is achieved by transforming images into sequence data and mining global spectral-spatial information to establish remote dependencies. Nevertheless, both the ViT and CNNs have their own limitations. For instance, a CNN is constrained by the extent of its receptive field, which prevents it from fully exploiting global spatial-spectral features. Conversely, the ViT is prone to excessive distraction during the feature extraction process. To be able to overcome the problem of insufficient feature information extraction caused using by a single paradigm, this paper proposes an MLP-mixer and a graph convolutional enhanced transformer (MGCET), whose network consists of a spatial-spectral extraction block (SSEB), an MLP-mixer, and a graph convolutional enhanced transformer (GCET). First, spatial-spectral features are extracted using SSEB, and then local spatial-spectral features are fused with global spatial-spectral features by the MLP-mixer. Finally, graph convolution is embedded in multi-head self-attention (MHSA) to mine spatial relationships and similarity between pixels, which further improves the modeling capability of the model. Correlation experiments were conducted on four different HSI datasets. The MGEET algorithm achieved overall accuracies (OAs) of 95.45%, 97.57%, 98.05%, and 98.52% on these datasets.
Optimization of Fuzzy Control Parameters for Wind Farms and Battery Energy Storage Systems Based on an Enhanced Artificial Bee Colony Algorithm under Multi-Source Sensor Data
Authors: Liu Zejian , Yang Ping , Zhang Peng , Lin Xu , Wei Jiaxi , Li Ning
Published: August 2024

With the rapid development of sensors and other devices, precise control for the generation of new energy, especially in the context of highly stochastic wind power generation, has been strongly supported. However, large-scale wind farm grid connection can cause the power system to enter a low inertia state, leading to frequency instability. Battery energy storage systems (BESSs) have the advantages of a fast response speed and high flexibility, and can be applied to wind farm systems to improve the frequency fluctuation problem in the process of grid connection. To address the frequency fluctuation problem caused by the parameter error of the fuzzy membership function in the fuzzy control of a doubly fed induction generator (DFIG) and a BESS, this paper proposes an improved Artificial Bee Colony (ABC) algorithm based on multi-source sensor data for optimizing the fuzzy controller to improve the frequency control ability of BESSs and DFIGs. A Gaussian wandering mechanism was introduced to improve the ABC algorithm and enhance the convergence speed of the algorithm, and the improved ABC algorithm was optimized for the selection of fuzzy control affiliation function parameters to improve the frequency response performance. The effectiveness of the proposed control strategy was verified on the MATLAB/Simulink simulation platform. After optimization using the proposed control strategy, the oscillation amplitude was reduced by 0.15 Hz, the precision was increased by 40%, and the steady-state frequency deviation was reduced by 26%. The results show that the method proposed in this paper provides a great improvement in the frequency stability of coordinated systems of wind farms and BESSs.
Linear-Structured-Light Measurement System Based on Scheimpflug Camera Thick-Lens Imaging
Authors: Guo Dongyu , Cui Jiwen , Wu Yuhang
Published: August 2024

A thick-lens, structured-light measurement model is introduced to overcome the oversights in traditional models, which often disregard the impact of lens thickness. This oversight can lead to inaccuracies in Scheimpflug camera calculations, causing systematic errors and diminished measurement precision. By geometrical optics, the model treats the camera as a thick lens, factoring in the locations of its principal points and the spatial shifts due to image plane tilting. The model deduces the positional relationship of the thick lens with a tilted optical axis and establishes a linear-structured-light measurement model. Simulations confirm that the model can precisely calculate the 3D coordinates of subjects from image light strip data, markedly reducing systematic errors across the measurement spectrum. Moreover, experimental results suggest that the refined sensor model offers enhanced accuracy and lower standard deviation.
Quantitative Prediction and Analysis of Rattle Index Using DNN on Sound Quality of Synthetic Sources with Gaussian Noise
Authors: Nam Jaehyeon , Kim Seokbeom , Ko Dongshin
Published: August 2024

This study researched the prediction of the BSR noise evaluation quantitative index, Loudness N10, for sound sources with noise using statistics and machine learning. A total of 1170 data points was obtained from 130 automotive seats measured at 9-point positions, with Gaussian noise integrated to construct synthetic sound data. Ten physical quantities related to sound quality and sound pressure were used and defined as dB and fluctuation strength, considering statistical characteristics and Loudness N10. BSR quantitative index prediction was performed using regression analysis with K-fold cross-validation, DNN in hold-out, and DNN in K-fold cross-validation. The DNN in the K-fold cross-validation model demonstrated relatively superior prediction accuracy, especially when the data quantity was relatively small. The results demonstrate that applying machine learning to BSR prediction allows for the prediction of quantitative indicators without complex formulas and that specific physical quantities can be easily estimated even with noise.
Optimization of Operational Parameters of Plant Protection UAV
Authors: Xing Wei , Cui Yukang , Wang Xinghao , Shen Jun
Published: August 2024

The operational parameters of plant protection unmanned aerial vehicles (UAVs) significantly impact spraying effectiveness, but the underlying mechanism remains unclear. This paper conducted a full factorial experiment with varying flight speeds, heights, and nozzle flow rates to collect parameter space data. Using the Kriging surrogate model, we characterized this parameter space and subsequently optimized the average deposition rate and coefficient of variation by employing a variable crossover (mutation) probability multi-objective genetic algorithm. In the obtained Pareto front, the average sedimentation rate is no less than 46%, with a maximum of 56.08%, and the CV coefficient is no more than 13.91%, with a minimum of only 8.42%. These optimized parameters enhance both the average deposition rate and spraying uniformity compared to experimental data. By employing these optimized parameters in practical applications, a balance between the maximum average deposition rate and minimum coefficient of variation can be achieved during UAV spraying, thereby reducing pesticide usage, promoting sustainable agriculture, and mitigating instances of missed spraying and re-spraying.
Phytochemical Profiling and Biological Activities of Two Helianthemum Species Growing in Greece
Authors: Panou Evgenia , Graikou Konstantia , Tsafantakis Nikolaos , Sakellarakis Fanourios-Nikolaos , Chinou Ioanna
Published: August 2024

Helianthemum nummularium (HN) and Helianthemum oelanticum subsp. incanum (HO) are plant species, among Cistaceae, that are highly distributed in the Mediterranean region. In the current study, extracts of the aerial parts from both species have been analyzed phytochemically. The non-polar extract analysis resulted in the identification of 15 compounds in each species, mainly terpene and fatty acid derivatives, through GC–MS. The methanolic extract analysis, conducted through UHPLC–MS/MS, led to the identification of 39 metabolites in HN and 29 in HO, respectively, the majority of which were phenolics. Among the identified compounds, several have also been isolated and structurally determined (from HN: rutin, linoleic acid, gallic acid, and isoquercetin, and from HO: quercetin-3-O-(2″-O-galloyl)-galactopyranoside, methyl gallate, catechin-3-O-glucopyranoside, and astragalin, while hyperoside, and cis- and trans-tiliroside have been determined in both species). Furthermore, the methanolic extracts of HN and HO displayed a high total phenolic content (177.2 mg GA/g extract and 150.6 mg GA/g extract, respectively) and considerable free-radical scavenging activity against the DPPH radical (94.6% and 94.0% DPPH inhibition, respectively). Antimicrobial testing showed stronger inhibition of HN against Gram (+) bacterial strains (MIC values 0.07–0.15 mg/mL), while both extracts exhibited low tyrosinase-inhibitory activity. Considering the lack of studies conducted on the chemistry and biological activities of the genus Helianthemum, the chemical characterization of extracts could contribute to new sources of bioactive metabolites to be explored and exploited for further potential applications such as food and/ or the cosmetic industry.
Brújula Intersexual: Working Strategies, the Emergence of the Mexican Intersex Community, and Its Relationship with the Intersex Movement
Authors: Alcántara Eva , Inter Laura , Flores Frida , Narváez-Pichardo Carlos
Published: August 2024

After a decade of work, Brújula Intersexual has become a reference in Mexico and Latin America. However, the presence of the Latin American intersex movement in the specialised literature in English is restricted. We consider that conducting a self-reflexive review of Brújula Intersexual could contribute to understanding (1) the work strategies implemented by Brújula Intersexual; (2) the formation of the Spanish-speaking intersex community and movement in Mexico; and (3) the heterogeneous dynamics of the global intersex movement. We designed a qualitative–quantitative study involving discussion meetings with the Brújula Intersexual team, revision of the Brújula Intersexual archive, a scoping review, and a timeline. The results and discussion are focused on two axes: (1) Brújula Intersexual: structure and working strategies, in which two concepts are developed, namely, the intimate sphere and the atmosphere of trust; (2) The articulation of Brújula Intersexual within the intersex movement and its resonances in public policy. Researching Brújula Intersexual contributes to the collective memory and reveals important events that link the Spanish-speaking and global anglophone intersex movements. In particular, Brújula Intersexual was configured as a critical counter-device that manages intense flows of affection, allowing for the production of new subjectivation modes for people with intersex bodies.
An Influencing Factors Analysis of Road Traffic Accidents Based on the Analytic Hierarchy Process and the Minimum Discrimination Information Principle
Authors: Zeng Youzhi , Qiang Yongkang , Zhang Ning , Yang Xiaobao , Zhao Zhenjun , Wang Xiaoqiao
Published: August 2024

Safe traffic is an important part of sustainable transportation. Road traffic accidents lead to a large number of casualties and property losses every year. Current research mainly studies some types of traffic accidents and ignores other types of traffic accidents; therefore, taking various types of road traffic accidents as a whole, an overall study of their influencing factors is urgently needed. To improve road traffic safety, taking various types of road traffic accidents as a whole, this paper analyzes the influencing factors and finds out the causative factors of road traffic accidents. A new index system of road traffic accident influencing factors is constructed based on the existing literature and real traffic data, and their subjective weights and objective weights are obtained by the analytic hierarchy process based on the subjective data and the normalization of the actual traffic data for Yizheng City, Yangzhou, China from January 2020 to December 2020, where the subjective weights are the main weights, and comprehensive weights are obtained by the minimum discrimination information principle correcting the subjective weights with the objective weights. Finally, the global weights, their ranks, and their weight differences are obtained. The main findings are as follows: (1) compared with the real traffic data, experts generally overestimate the impact of road factors on traffic accidents and underestimate the impact of human factors on traffic accidents; (2) in the first-level, human factors and road factors are the causative factors; (3) in the second-level, “motor vehicle drivers’ misconduct”, “road condition”, and “road section” are the causative factors; and (4) in the third-level, “slippery road”, “rain and snow weather”, “intersection”, and “untimely braking” are the causative factors. The research results can provide some scientific basis for improving road traffic safety.
Research on Carbon Emissions and Influencing Factors of Residents’ Lives in Hebei Province
Authors: Zhang Cuiling , Yang Weihua , Wang Ruyan , Zheng Wen , Guo Liying
Published: August 2024

The standard of living has significantly risen along with ongoing economic progress, but CO2 emissions have also been rising. The reduction in CO2 resulting from the daily activities of residents has become a crucial priority for every province. A relevant study on the carbon emissions of Hebei Province residents was conducted for this publication, aiming to provide a theoretical basis for the sustainable development of Hebei Province. The first part of the article calculates the carbon emissions of Hebei Province people from 2005 to 2020 using the emission factor method and the Consumer Lifestyle Approach (CLA). Secondly, the Logarithmic Mean Divisia Index (LMDI) decomposition approach is used to assess the components that influence both direct and indirect carbon emissions. Finally, the scenario analysis approach is employed in conjunction with the LEAP model to establish baseline, low-carbon, and ultra-low-carbon scenarios to predict the trend of residents’ carbon emissions in Hebei Province from 2021 to 2040. The results show that the total carbon emissions of residents in Hebei Province from 2005 to 2020 rose, from 77.45 million tons to 153.35 million tons. Income level, energy consumption intensity, and population scale are factors that contribute to the increase in direct carbon emissions, while consumption tendency factors have a mitigating effect on direct carbon emissions. Economic level, consumption structure, and population scale factors are factors that contribute to the increase in indirect carbon emissions, while energy consumption intensity and energy structure factors have a mitigating effect on indirect carbon emissions. The prediction results show that under the baseline scenario, the cumulative residents’ carbon emissions in Hebei Province will not reach a zenith from 2021 to 2040. However, under the low-carbon situation, the carbon emissions of residents in Hebei Province will peak in 2029, with a peak of 174.69 million tons, whereas under the ultra-low-carbon scenario, it will peak in 2028, with a peak of 173.27 million tons.
Toward Sustainable Futures by Design Education
Authors: Stevens Nicholas Sebastian , Culén Alma Leora
Published: August 2024

Design plays an integral role in shaping our everyday lives by providing and mediating the objects and relationships we surround ourselves with. As we find our lifestyles inherently unsustainable, design is therefore also implicated. If design is to fully address this issue and meaningfully contribute to future sustainable lifestyles, then it must undergo significant transformation. Part of this transformation must include design education. While many agree on the necessary transformation of design education, disagreements arise as to what this new education might entail and, significantly, how it might be implemented. This article explores how transformations happen in design education and to what extent such education should tackle significant societal issues, including sustainability, amid the increasing complexity and interdependence of modern-day challenges. It investigates practical issues around implementing such education, its challenges and opportunities, as well as how geographical location might help or hinder through aspects such as social or cultural tendencies, infrastructures or regulation and historical context. To this end, six in-depth interviews were conducted with educators at the forefront of this transformation in Scandinavia, most of whom have established courses and programs that address systemic problems and engage students in reflecting and designing to mitigate current challenges. The analysis of interviews utilised an emergent coding method. It led to four important findings that require attention when considering sustainable design education. The findings are (1) these transformations are often driven by impassioned and visionary individuals, (2) new variants of design must incorporate collaborations at all scales and in various formats, (3) increased responsibility arises from immersion in collaborative projects concerning long-term visions, values, and continuity in design beyond current practices and finally, (4) there are some unresolved tensions found in the balance of practical, reflective, and analytical skills needed. At a more abstract level, this paper positions design education as a significant force in transitioning to sustainable futures.
The Impact of Environmental, Social, and Governance Performance on the Total Factor Productivity of Textile Firms: A Meditating-Moderating Model
Authors: Zhang Yu , Chen Chiping , Zhang Xizheng
Published: August 2024

Today’s world is experiencing a great change that has not been seen in a hundred years, with a tense and complex world situation; under the influence of the Israeli–Palestinian conflict, trade friction between China and the U.S., and other events, enterprises need to choose good tactics to achieve strategic development. Environmental, Social, and Governance (ESG) is an indicator that measures the non-financial performance of an enterprise; this article takes listed companies in China’s textile industry from 2015 to 2022 as a research sample and utilizes a bi-directional fixed-effect model that controls for time and individuals to empirically analyze the relationship between ESG performance and corporate total factor productivity (TFP). The results show the following: (1) the better the corporate ESG performance, the higher the TFP; (2) the mechanism test results show that corporate ESG performance promotes TFP by improving green innovation capacity and enhancing corporate human capital, and green innovation and human capital play a partially mediating role; (3) the moderation test shows that agency costs play a weakening role in ESG performance, positively affecting corporate total factor productivity; (4) the heterogeneity analyses found that enterprises are more significantly affected by ESG among non-state-owned enterprises and in the central region. The results of the study provide empirical evidence to guide textile enterprises to actively fulfill ESG performance to enhance enterprise total factor productivity and achieve high quality and sustainable development.
Evaluation of Coastal Ecological Security Barrier Functions Based on Ecosystem Services: A Case Study of Fujian Province, China
Authors: Luo Fang , He Li , He Zhengwei , Zeng Wanting , Wang Yuanchao
Published: August 2024

Constructing coastal ecological security barriers is beneficial for preventing environmental degradation and enhancing resilience to natural disasters. This study examines the functionality of these barriers from an ecosystem service perspective, developing an Ecosystem Security Barrier Function (ESBF) index to analyze its spatiotemporal variations. From 2000 to 2020, habitat quality in the study area experienced a slight decline, while water supply capacity initially increased and then decreased. Water purification capacity hit its lowest point in 2015 before improving. The ESBF generally ranged from moderate to high levels, with higher values in the northwest and lower values in the southeast, showing strong spatial autocorrelations. Despite mild degradation in some areas, overall stability was maintained with frequent transitions between ESBF levels. Utilizing the Multiscale Geographically Weighted Regression (MGWR) model, we conducted a grid-scale analysis of the driving mechanisms behind ESBF. We found that precipitation, elevation, and the Normalized Difference Vegetation Index (NDVI) positively correlated with ESBF, whereas population density, land use, and nighttime lights negatively correlated. The relationship between temperature and ESBF showed a “north-positive, south-negative” pattern. The study recommends enhancing coastal wetland restoration, strengthening protective forest construction, and effectively controlling pollutant sources entering the sea to safeguard and improve the ecological security barrier function.
Towards Equitable Compensation: Unraveling China’s Regional Comprehensive Land Price System from Legal Connotation to Practical Implementation
Authors: Liao Xialin , Zhao Xin , Zhou Sina , Wang Ying
Published: August 2024

The Regional Comprehensive Land Price System (RCLPS) in China serves as the compensation standard for land expropriation, as established by the new Land Management Law in 2019. Its primary objectives include safeguarding the legitimate rights and interests of expropriated landowners and promoting social fairness and justice—critical components for achieving Sustainable Development Goal 10. Despite its significance, the existing literature lacks a comprehensive exploration of the RCLPS’s legal connotation and implementation challenges. This study first analyzes the research background and legal connotation of China’s RCLPS. It provides a comprehensive compensation standard for land expropriation, aiming to ensure consistent compensation levels within the same “expropriated districts”. Then, an empirical study examines the practical implementation of the RCLPS in Wuhan City, China. Through a comparative analysis of the 2020 Regional Comprehensive Land Price (RCLP) and state-owned land transfer fees in Wuhan, several deficiencies in the city’s RCLPS are identified. First, the distribution of land value-added benefits lacks reasonableness. Second, the district-level delineation of “expropriated districts” inadequately captures variations in land value. From a sustainable development perspective, specific countermeasures can be proposed, including re-evaluating the allocation of land value-added benefits and incorporating them into the RCLP assessment. Additionally, enhancing the precision in delineating “expropriated districts” within the administrative region is necessary. This study provides valuable guidance for achieving equitable compensation in land expropriation and improving the RCLPS.
An Electric Vehicle Adoption Model for Nigeria—A Fuzzy MCDA Policy Analysis Tool with Implications for Developing Nations
Authors: Osedeme Janose , Barron Robert , Salmon Christian , Ekong Joseph
Published: August 2024

The dominant source of the vehicle fleet in developing nations is the used vehicle market in developed nations. As the automotive fleet in developed nations electrifies, so will the used vehicle market. In many cases, developing nations’ electric infrastructure is inadequate to support significant vehicle electrification. Therefore, there is an immediate need for developing nations to plan and prepare for vehicle electrification before scarcity of fossil fueled vehicles constitutes a national emergency. This research presents the Developing Nations Electric Vehicle Adoption Model (DN-EVAM), a decision support tool designed to help decision makers in developing nations address this challenge. We then use DN-EVAM to analyze the vehicle adoption landscape of Nigeria. First, we survey subject matter experts in Nigeria to identify antecedent and moderating variables relevant to Nigeria. Then we implement DN-EVAM to model the Nigerian vehicle electrification landscape. Finally, we conduct a scenario-based analysis to identify those antecedent and moderating variables most important to vehicle electrification in Nigeria. We find that for Nigerian policy makers, adoption incentives and infrastructure investments are the most critical areas of focus in the near term while investments in technology development are generally not the most attractive option.
An Analysis of the Use of Autonomous Vehicles in the Shared Mobility Market: Opportunities and Challenges
Authors: Tu Lin , Xu Min
Published: August 2024

The rapid growth of the sharing economy has propelled shared mobility to the forefront of the public’s attention. Continuous advancements in autonomous driving technology also bring new opportunities and challenges to the shared mobility industry. This study comprehensively analyzes the impact of using land-based autonomous vehicles (AVs) to provide shared mobility services, utilizing SWOT analysis (Strengths, Weaknesses, Opportunities, and Threats), PESTLE analysis (Political, Economic, Social, Technological, Legal, and Environmental), and Porter’s Five Forces (the bargaining power of suppliers, the bargaining power of buyers, threats of new entrants, substitutes, and rivalry). The findings reveal that AVs can provide improved shared mobility services by increasing transportation safety, reducing emissions, reducing costs, enhancing traffic efficiency, and increasing customer satisfaction as well as the profitability of shared mobility services. However, challenges such as technological and policy uncertainties, safety concerns, high initial costs, inadequate public communication infrastructure, and the absence of standardized regulations can hinder the widespread adoption of AVs. The benefits are also restricted by the low market penetration rate of AVs. To promote AVs in the shared mobility market, this study also provides implications for AV stakeholders tailored to the evolving shared mobility market dynamics.
New Quality Productivity and Industrial Structure in China: The Moderating Effect of Environmental Regulation
Authors: Shao Changhua , Dong Han , Gao Yuan
Published: August 2024

To explore the connotation and development level of China’s new quality productivity, this paper constructs an index system based on innovation, greenness, and productivity. This system is used to describe the development level of China’s new quality productivity. Using relevant data from 30 provincial administrative regions in China from 2011 to 2021, the entropy weight-TOPSIS method was employed to measure the index system. The development level of new quality productivity in China and its four major economic regions was analyzed through the three dimensions of the index system. Additionally, this paper examines the impact of new quality productivity on China’s industrial restructuring and integrates environmental regulation to elucidate the interaction mechanisms among these factors. An econometric regression model is further constructed to verify the effect of new quality productivity on industrial structural change and to examine the moderating role of environmental regulation. The results of this study show that there is a regional imbalance in the level of development of new quality production in China, with the level of development of new quality productivity in the eastern region being significantly higher than that in the central, western, and northeastern regions. However, on the whole, the new quality productivity of the four major regions has been in a state of continuous improvement during the period under investigation, and the spatial gap has been constantly decreasing. The benchmark regression coefficients, sys-GMM regression coefficients, and diff-GMM regression coefficients for new quality productivity and industrial rationalization are −0.6228, −0.1121, and −0.0439, respectively, and they are negatively correlated. The regression coefficients of the sys-GMM and diff-GMM of the interaction terms of environmental regulation and new quality productivity are −0.0051 and −0.0045, and there is a negative moderating effect of environmental regulation between new quality productivity and industrial structure rationalization. The benchmark regression coefficient, the sys-GMM regression coefficient, and the diff-GMM regression coefficient of new quality productivity and industrial upgrading are 2.5179, 0.7525, and 0.3572, respectively, and there is a positive correlation between the two. The regression coefficients of sys-GMM and diff-GMM for the interaction terms of environmental regulation and new quality productivity are 0.0380 and −0.0167, and there is a positive moderating effect of environmental regulation between new quality productivity and industrial structure upgrading.
The Effect of Digitization on Economic Sustainable Growth in Shandong Province of China
Authors: Xu Ran , Kim Yeong-Gil , Liang Chenglei
Published: August 2024

In recent years, the digital economy has emerged as a widely debated economic topic, with China experiencing rapid development in this sector. As a pioneering region and microcosm of China’s economy, studying the impact of Shandong’s digitization level on economic development holds significant academic and practical importance. Based on the annual panel data for the 17 cities of Shandong Province from 2001 to 2019, a digitization index (DI) is generated through the entropy weight method (EWM). Then, the effects of DI on GDP and total factor productivity (TFP) are empirically analyzed through various regression models, including fixed effect and spatial regression techniques. Results indicate that: (1) DI has a direct effect on TFP and an indirect effect on GDP; (2) regional differences are significant but minimal, with most concentrated effects being relatively large in recent periods; (3) negative spatial spillovers in both GDP and TFP are caused by negative spillovers in DI. It is recommended that local governments carefully consider the negative spillover effects of digital development when formulating digitization policies. While concentrating resources on advancing digitization in high-priority cities, equal emphasis should be placed on promoting the dissemination of digital products and services to surrounding areas. This approach is crucial for mitigating the risk of regional economic disparities caused by the potential siphoning effect of digital development.
Study on Landslide Susceptibility Based on Multi-Model Coupling: A Case Study of Sichuan Province, China
Authors: Zhang Jinming , Qian Jianxi , Lu Yuefeng , Li Xueyuan , Song Zhenqi
Published: August 2024

Landslides are among the most prevalent geological hazards and are characterized by their high frequency, significant destructive potential, and considerable incident rate. Annually, these events lead to substantial casualties and property losses. Thus, conducting landslide susceptibility assessments in the regions vulnerable to such hazards has become crucial. In recent years, the coupling of traditional statistical methods with machine learning techniques has shown significant advantages in assessing landslide risk. This study focused on Sichuan Province, China, a region characterized by its vast area and diverse climatic and geological conditions. We selected 13 influencing factors for the analysis: elevation, slope, aspect, plan curve, profile curve, valley depth, precipitation, the stream power index (SPI), the topographic wetness index (TWI), the topographic position index (TPI), surface roughness, fractional vegetation cover (FVC), and slope height. This study incorporated the certainty factor method (CF), the information value method (IV), and their coupling with the decision tree C5.0 model (DT) and a logistic regression model (LR) as follows: IV-LR, IV-DT, CF-LR, and CF-DT. The results, validated by an ROC curve analysis, demonstrate that the evaluation accuracy of all six models exceeded 0.750 (AUC > 0.750). The IV-LR model exhibited the highest accuracy, with an AUC of 0.848. When comparing the accuracy among the models, it is evident that the coupling models outperformed the individual statistical models. Based on the results of the six models, a landslide susceptibility map was generated, categorized into five levels. High and very high landslide risk zones are mainly concentrated in the eastern and southeastern regions, covering nearly half of Sichuan Province. Medium-risk areas form linear distributions from northeast to southwest, occupying a smaller proportion of the area. Extremely low- and low-risk zones are predominantly located in the western and northwestern regions. The density of the landslide points increases with higher risk levels across the regions. This further validates the suitability of this research methodology for landslide susceptibility studies on a large scale. Consequently, this methodology can provide crucial insights for landslide prevention and mitigation efforts in this region.
Research on Optimal Greenness Decision and Coordination of Interests in Green Supply Chain of Livestock Products
Authors: Zhang Jianjun , Wang Min
Published: August 2024

Animal husbandry is an important industry related to the national economy and people’s livelihood, and its coordinated development can continuously enhance the quality, efficiency, and competitiveness of the livestock industry, and better meet the people’s diversified consumption demand for livestock and poultry products. In this paper, considering the government’s green subsidy to the leading enterprises in the green supply chain of livestock products, the article uses the stackelberg game method to establish the decision-making models of the green supply chain of livestock products led by the co-operatives and the slaughtering and processing enterprises, respectively, and measures the optimal greenness of the livestock products. Different from the previous optimal decision-making and coordination of interests in the case of only considering economic benefits, this paper combines economic and ecological benefits to construct a coordination mechanism of interests in the green supply chain of livestock products in line with the concept of ecological priority and green development. The conclusions showed that: (1) Under the background of considering economic and ecological benefits, the influence of greenness sensitivity factor, freshness sensitivity factor, and government subsidy factor on the decision-making of green supply chain of livestock products is not affected by the operation mode and decision-making scenario, with the increase in the three factors, the greenness, freshness, and total benefits of the green supply chain of livestock products. (2) The greenness, freshness, and total benefits of green supply chain of livestock products are higher in the operation mode led by slaughtering and processing enterprises, which is more favorable to the development of green supply chain of livestock products from the perspective of supply chain development. (3) Compared with decentralized decision-making mode, both benefit-sharing and cost-sharing contracts increase the greenness and freshness of livestock products, significantly reduce the retail price of livestock products, which improves the benefits of the co-operatives, slaughtering and processing enterprises, 3PL (third-party logistics) service providers, and retailers as well as the entire green supply chain of livestock products. Based on the research findings, this article proposes relevant management insights to better promote the coordination of interests in the green supply chain of livestock products.
Urbanization and Cultural Industry Correlation: An Empirical Analysis from China
Authors: Zhang Wen , Zhang Rong , Zou Yuntao
Published: August 2024

The cultural industry has been recognized as an indispensable component of sustainable economic development. Urbanization often represents a country’s level of economic development. While China is advancing its new urbanization strategy, it is also vigorously promoting cultural revitalization plans. This study employs a global Data Envelopment Analysis (DEA) model and Tobit regression analysis to examine the correlation between China’s cultural industry and urbanization. The results indicate that although the overall economic efficiency of China’s cultural industry is continuously improving, the returns to scale in many provinces are declining. Changes brought about by new urbanization, such as increases in per capita GDP, per capita income, and enterprise scale, have significant positive impacts on the cultural industry. However, the rising urban population ratio has a significant negative impact on the cultural industry. This study suggests that the current new urbanization in China faces issues of oversimplification and excessive advancement. It recommends adjusting relevant policies to allow sufficient time and space for the cultural industry to absorb the benefits brought by urbanization. Given China’s specific national conditions, the conclusions of this study may not necessarily apply to other regions. However, the global DEA-Tobit combination method used in this study aligns more closely with reality and achieves a higher degree of fit, thus possessing a certain level of universality.
Climate-Adaptive Nature-Based Regenerative Urban Green Streetscapes: Design Exploration from the City of Matera
Authors: Macaione Ina , Raffa Alessandro , Andaloro Bianca
Published: August 2024

Over the past two decades, global cities have been addressing climate challenges by transforming their gray infrastructural spaces through climate-adaptive and nature-based regeneration processes. These efforts also aim to tackle local ecological, social, and economic disparities. Despite the prevailing focus on technical and performance-based approaches, research on climate-adaptive, nature-based regeneration of streetscapes remains limited and has yet to significantly influence design-driven approaches to urban regeneration. This paper seeks to address these gaps by emphasizing the importance of spatial dimensions in overcoming current theoretical and operational limitations. It introduces a research experience that aims to leverage the potential of design to promote climate-adaptive, nature-based green regeneration of streetscapes and to integrate this approach into mainstream practices through a “research-by-design” methodology. To achieve this, an operational framework has been developed and is presented here, offering both conceptual and practical insights for creating climate-adaptive, nature-based streetscapes. Following the proposed methodology, two pilot design cases are introduced and discussed, both located in the Italian city of Matera: Piccianello and La Martella. This iterative process aims to establish a framework for sustainable, long-term urban resilience, making cities greener, more adaptive, and more equitable.