bluuebunny/crossref_metadata_2025 huggingface dataset:
Satellite Data Reveal Concerns Regarding Mangrove Restoration Efforts in Southern China
Authors: Fan Chao , Hou Xiyong , Zhang Yuxin , Li Dong
Published: August 2023

Mangrove restoration projects are often evaluated based on the increase in mangrove forest (MF) area, but the reliability of this indicator as a measure of successful restoration is questionable. Considering both numerical and quality dimensions, this study assessed mangrove restoration efforts in the Leizhou Peninsula and Beibu Gulf (LP-BG) in China. The hypothesis was that due to the limited social capital investment in mangrove restoration, there exist hierarchical differences in the urgency of mangrove restoration. Time-series Landsat imagery from the Google Earth Engine platform was used to analyze the MF distribution from 2000 to 2020. A resilience indicator, incorporating resistance and adaptive capacity, was constructed to assess MF quality within identified mangrove boundaries. The results revealed an increase in MF area from 6655.87 ha in 2000 to 14,607.93 ha in 2020. However, the majority (79.6%) of MF patches exhibited low resilience (values < 3), with only a minority (51 patches) demonstrating high resilience. Interestingly, MFs within the mangrove reserve displayed higher resilience, but these areas did not exhibit a significant spatial expansion of MFs. These findings highlight the limitation of relying solely on the net growth in the MF area as an indicator of successful restoration. Instead, an ecologically optimal solution is recommended, focusing on expanding conservation boundaries to include remnant MFs outside protected areas, rather than creating new planting areas. This study provides an assessment framework to evaluate the efficiency of mangrove restoration efforts and offers insights for local decision makers to guide future restoration endeavors.
A Novel Heterogeneous Ensemble Framework Based on Machine Learning Models for Shallow Landslide Susceptibility Mapping
Authors: Tang Haozhe , Wang Changming , An Silong , Wang Qingyu , Jiang Chenglin
Published: August 2023

Landslides are devastating natural disasters that seriously threaten human life and property. Landslide susceptibility mapping (LSM) plays a key role in landslide hazard management. Machine learning (ML) models are widely used in LSM but suffer from limitations such as overfitting and unreliable accuracy. To improve the classification performance of a single machine learning (ML) model, this study selects logistic regression (LR), support vector machine (SVM), random forest (RF), and gradient boosting decision tree (GBDT), and proposes a novel heterogeneous ensemble framework based on Bayesian optimization (BO), namely, stratified weighted averaging (SWA), to test its applicability in a typical landslide area in Yanbian Prefecture, China. Firstly, a dataset consisting of 1531 historical landslides was collected from field investigations and historical records, and a spatial database containing 16 predisposing factors was established. The dataset was divided into a training set and a test set in a ratio of 7:3. The results showed that SWA effectively improved the Accuracy, AUC, and robustness of the model compared to a single ML model. The SWA achieved the best classification results (Accuracy = 91.39% and AUC = 0.967). To verify the generalization ability of SWA, we selected published landslide datasets from Yanshan country and Yongxin country in China for testing. SWA also performed well, with an AUC of 0.871 and 0.860, respectively. As indicated by shapely values (SVs), Normalized Difference Vegetation Index (NDVI) is the factor that has the greatest impact on landslide occurrence. The landslide susceptibility maps obtained from this study will provide an effective reference program for land use planning and disaster prevention and mitigation projects in Yanbian Prefecture, China.
Coastal Assessment of Sentinel-6 Altimetry Data during the Tandem Phase with Jason-3
Authors: Passaro Marcello , Schlembach Florian , Oelsmann Julius , Dettmering Denise , Seitz Florian
Published: August 2023

This study presents a comparative analysis of the coastal performances of Sentinel-6 and Jason-3 altimeters during their tandem phase, considering their different processing modes. We examine the measurements available in the standard geophysical data records (GDR) and also perform dedicated reprocessing using coastal retracking algorithms applied to the original waveforms. The performances are evaluated, taking into account the quality of retrievals (outlier analysis), their precision (along-track noise analysis), potential systematic biases, and accuracy (comparison against tide gauges). The official SAR altimetry product of Sentinel-6 demonstrates improved coastal monitoring capabilities compared to Jason-3, except for the remaining issues related to significant wave height, which have already been identified. These findings highlight the significance of dedicated coastal retracking algorithms for enhancing the capabilities of both traditional, pulse-limited altimeters and more recent developments utilizing SAR altimetry.
Estimating Uncertainties of Simulated MW Sounding Sensor Brightness Temperatures
Authors: Iacovazzi Siena , Liu Quanhua , Yang Hu , Fuentes James , Sun Ninghai
Published: August 2023

Radiative transfer model (RTM) simulated microwave (MW) brightness temperatures (Tbs) are commonly used to monitor and evaluate space-based MW sensor-observed antenna temperature (Ta) data. Although these simulated Tbs are paramount to this data integrity maintenance activity, their uncertainties have not been quantified. This study develops and implements a method to estimate these simulated Tb uncertainties based on a statistical comparison of two Community RTM (CRTM)-simulated operational MW sounder Tb data sets, separately generated using the European Center for Medium Range Forecasts (ECMWF) Atmospheric Model High Resolution (HRES) and Global Navigation Satellite System (GNSS) Radio Occultation (RO) sounding inputs. The study shows the smallest single-sensor CRTM-simulated Tb uncertainties, computed from differences of ECMWF HRES and GNSS RO soundings-based simulated Tbs data sets, are on the order of 10−4 relative to a 300 K Tb for the two NOAA operational MW sounder channels with low- to mid-tropospheric peak weighting function sensitivity. Meanwhile, inter-sensor-simulated Tb differences, computed from the double difference of single-sensor-simulated Tb differences, lead to CRTM-simulated Tb uncertainties on the order for 10−4 for at least nine MW sounder channels with peak sensitivity from the low-troposphere to the low-stratosphere. These findings provide the basis of future work to assess the ability to identify and quantify suspected on-orbit MW sounder calibration anomalies using RTM-driven, on-orbit MW instrument monitoring techniques.
Learning Implicit Neural Representation for Satellite Object Mesh Reconstruction
Authors: Yang Xi , Cao Mengqing , Li Cong , Zhao Hua , Yang Dong
Published: August 2023

Constructing a surface representation from the sparse point cloud of a satellite is an important task for satellite on-orbit services such as satellite docking and maintenance. In related studies on surface reconstruction from point clouds, implicit neural representations have gained popularity in learning-based 3D object reconstruction. When aiming for a satellite with a more complicated geometry and larger intra-class variance, existing implicit approaches cannot perform well. To solve the above contradictions and make effective use of implicit neural representations, we built a NASA3D dataset containing point clouds, watertight meshes, occupancy values, and corresponding points by using the 3D models on NASA’s official website. On the basis of NASA3D, we propose a novel network called GONet for a more detailed reconstruction of satellite grids. By designing an explicit-related implicit neural representation of the Grid Occupancy Field (GOF) and introducing it into GONet, we compensate for the lack of explicit supervision in existing point cloud surface reconstruction approaches. The GOF, together with the occupancy field (OF), serves as the supervised information for neural network learning. Learning the GOF strengthens GONet’s attention to the critical points of the surface extraction algorithm Marching Cubes; thus, it helps improve the reconstructed surface’s accuracy. In addition, GONet uses the same encoder and decoder as ConvONet but designs a novel Adaptive Feature Aggregation (AFA) module to achieve an adaptive fusion of planar and volume features. The insertion of AFA allows for the obtained implicit features to incorporate more geometric and volumetric information. Both visualization and quantitative experimental results demonstrate that our GONet could handle 3D satellite reconstruction work and outperform existing state-of-the-art methods by a significant margin. With a watertight mesh, our GONet achieves 5.507 CD-L1, 0.8821 F-score, and 68.86% IoU, which is equal to gains of 1.377, 0.0466, and 3.59% over the previous methods using NASA3D, respectively.
Effective Removal of Hexavalent Chromium from Aqueous Solutions Using Quaternary Ammonium-Functionalized Magnetic Graphene Oxide Composites
Authors: Huang Yue , Huang Weibin , Chen Ying , Sun Jianteng , Liang Maofeng , Guo Yonggui , Liu Xiaping , Liu Mingqiang , Wei Yajing , Wei Junfu , Zhang Huan , Wang Huicai
Published: August 2023

Novel quaternary ammonium/magnetic graphene oxide composites (M-PAS-GO) that efficiently remove Cr(VI) ions were fabricated through the introduction of the (3-aminopropyl) triethoxysilane and Fe3O4 nanoparticles on the surface of GO, and then modified with n-butyl bromide. The fabricated M-PAS-GO was comprehensively characterized by SEM, TEM, EDX, XRD, Raman spectroscopy and FTIR, and the results manifest that the quaternary ammonium group was introduced onto the surface of GO. Under the reaction conditions of pH 3.20, temperature of 25 °C and M-PAS-GO dosage of 0.01 g/50 mL, 90% of 10 mg/L Cr(VI) ions were removed from the solution within 20 min. The kinetics study indicates that the adsorption process followed the pseudo-second-order model and was surface reaction-controlled. The thermodynamic parameters calculated from temperature-dependent adsorption isotherms suggest that the adsorption process was an exothermic and spontaneous process. The maximum adsorption capacities of Cr(VI) ions on M-PAS-GO composites calculated by the Langmuir model were 46.48 mg/g. Moreover, the reusability and stability of M-PAS-GO demonstrates its economic sustainability. This study suggests that M-PAS-GO is a potential candidate adsorbent for the separation of Cr(VI) from wastewater.
Green Synthesis of Zinc Oxide Nanoparticles Using Aqueous Extracts of Hibiscus cannabinus L.: Wastewater Purification and Antibacterial Activity
Authors: Yang Xitao , Cao Xuan , Chen Chenxiao , Liao Liping , Yuan Sitian , Huang Siqi
Published: August 2023

The green preparation of metal oxide nanoparticles is an environmentally friendly method, which could reduce the use of toxic solvents and their impact on the environment. The purpose of this study is to investigate the green synthesis of zinc oxide (ZnO) nanoparticles using extracts of Hibiscus cannabinus leaves and to evaluate their potential applications in environmental remediation. In this work, ZnO nanoparticles were successfully prepared and thoroughly characterized using UV–vis, Fourier transform infrared analysis (FTIR), X-ray diffraction (XRD), transmission electron microscope (TEM) analysis, and scanning electron microscope (SEM) with energy dispersive x-ray analysis (EDAX). As a result, the synthesized ZnO nanoparticles showed a good adsorption capacity for Congo red (CR), and satisfactory antioxidant and antibacterial activities. They exhibited good adsorption and removal abilities for CR in aqueous solutions. With the conditions optimized, the adsorption kinetics and isotherms were fitted to the pseudo-second-order model and the Langmuir model. The ZnO nanoparticles could also effectively scavenge 2-2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2′-azino-di(3-ethylbenzthiazoline sulphonate) (ABTS) radicals, and appeared to inhibit the growth of Escherichia coli and Staphylococcus aureus bacteria. Based on the identified adsorption capacity, the green synthesized ZnO nanoparticles demonstrated their potential to be used in the removal of dyeing wastewater and in the further purification of water due to their antioxidant activity and antibacterial activity.
Tourist Experience Challenges: A Holistic Approach
Authors: Rusu Virginica , Rusu Cristian , Matus Nicolás , Botella Federico
Published: August 2023

Tourist experience (TX) has been covered by many studies. However, a consensus on the topic still needs to be reached in terms of its dimensions, factors, evaluation methods, and evaluation models. Moreover, the COVID-19 pandemic severely affected the tourism sector, and the post-pandemic era could bring about new challenges and opportunities, such as the growing awareness of the need for greener, more sustainable, and more balanced tourism. In this study, we consider TX a particular case of customer experience (CX) and an extension of the user experience (UX) concept. We conducted a systematic literature review addressing the concept of TX and reviewing articles published from 2012 to April 2023, indexed in two significant and relevant databases (Web of Sciences and Science Direct). We addressed research questions concerning (1) TX definition; (2) TX dimensions, attributes, and factors; (3) methods used to evaluate TX; and (4) the post-pandemic TX. We selected and thoroughly analyzed 167 articles. We analyze the TX concept, models, evaluation, and the post-pandemic context. We propose a holistic definition of TX and recommend ways to achieve its better analysis. Lessons learned during the COVID-19 pandemic may be helpful when dealing with future challenges and crises.
Evaluation of Community Emergency Management Capability Based on SWOT Analysis—A Case Study
Authors: Wang Kai , Feng Yuanyuan , Yang Hua , Deng Jun , Li Quanfang
Published: August 2023

(1) Background: the community is the most basic place to maintain residents’ lives, and therefore it is urgent to strengthen community resilience construction, which is directly related to the economic development, security and stability of urban communities. (2) Methods: this article combines the SWOT (Strengths, Weaknesses, Opportunities, Threats) qualitative analysis method and the AHP (Analytic hierarchy process) qualitative and quantitative analysis method to explore the current status of community emergency management in Xi’an City. A community emergency management evaluation model is constructed, which is based on six dimensions: infrastructure resilience, community organization resilience, risk hazard governance, emergency material security, emergency force construction, and emergency literacy. The evaluation index for community emergency management is established. Focusing on analyzing the strengths and weaknesses of communities in responding to sudden public health emergencies, opportunities and threats are identified. (3) Results: it was concluded that infrastructure resilience and emergency material support are community strengths, community organizational resilience is a community weakness, the emergency literacy dimension is a community opportunity, and risk and hazard management and emergency force construction are community threats. The results of the data research were further analyzed. (4) Conclusions: The final research results provide new theoretical support for community emergency management, while also providing theoretical and methodological references for emergency capacity evaluation in other fields.
Experimental Research and Transfer Matrix Method for Analysis of Transmission Loss in Multilayer Constructions with Devulcanized Waste Rubber
Authors: Vilniškis Tomas , Januševičius Tomas
Published: August 2023

According to circular economy principles, the recycling and reuse of tyre rubber waste are among the most advanced and ecological waste disposal technologies. Each year, about 19 million tons of tyres are produced, and this number increases every year. One of the most innovative ways to recycle rubber waste is devulcanization. There are many methods of rubber devulcanization, but the most popular is chemical devulcanization. Also, pre-process treatment is important before devulcanization. In this article, devulcanized rubber granules were used for the preparation of rubber samples. Two of the samples were obtained via the grinding method and one via chemical devulcanization. In total, 15 different rubber samples were produced for experimental measurements. Multilayer constructions, with two solid layers of plasterboard on both sides (GKB (a standard gypsum board) and GKFI (an enhanced-strength and surface-hardness gypsum board)) and the porous acoustic material of the rubber sample inside, were produced. Measurements were made in an impedance tube and compared with the results of a transfer matrix method (TMM) analysis. The same trends of resonant frequencies were determined. According to the results, the resonant frequencies depended on the thickness of the material, since transmission loss (TL) values depended on the mass of the construction. According to the test results of transmission loss, constructions with 50 mm thick rubber samples had results that were, on average, 3 dB better than those of structures with 25 mm thick samples and 5 dB better than those of structures with 12 mm thick rubber samples. In addition, it was found that higher-density plasterboards (GKFI) increased the overall transmission loss value of the structure by 5 dB. The same trends were determined using the TMM method. The test results showed that multilayered constructions with devulcanized waste rubber had high transmission loss results and could be used for sound-insulating structures.
A Global Analysis of Climate Change and the Impacts on Oyster Diseases
Authors: Okon Ekemini Moses , Birikorang Harriet Nketiah , Munir Mohammad Bodrul , Kari Zulhisyam Abdul , Téllez-Isaías Guillermo , Khalifa Norhan E. , Abdelnour Sameh A. , Eissa Moaheda E. H. , Al-Farga Ammar , Dighiesh Hagar Sedeek , Eissa El-Sayed Hemdan
Published: August 2023

Recently, global demand for seafood such oysters is increasing as consumers seek healthy and nutritive alternatives to a diet dominated by animal protein. This trend is attributed to the growing interest in sustainable seafood strategies and a surge in customer demand. Despite oysters being one of the most promising seafoods, the oyster industry faces various challenges, such as increased infectious diseases promoted by climate change, pollution, and environmental burdens. Hence, the industry’s current challenges must be addressed to ensure long-term viability. One of the current challenges in the production industry (in response to climate change) is mortality or poor product quality from microbial infection. This review reveals that climate change fosters pathogen development, significantly impacting disease spread, host susceptibility, and the survival rates of oysters. Rising temperatures, driven by climate, create favourable conditions for bacteria and viruses to multiply and spread quickly, making oysters more susceptible to diseases and ultimately adversely affecting the oyster industry. Climate-induced changes in oyster-associated microbes and pathogens, coupled with disruptions in biochemical pathways and physiological functions, can lead to increased disease outbreaks and reduced survival in the industry, impacting production and profitability. These adverse effects could result in decreased oyster supply, potentially affecting seafood markets and prices, and necessitate additional investments in disease management strategies. This review identifies and highlights how aquatic pathogens promoted by climate change will affect the oyster industry on a global scale. This review also presents an in-depth global assessment of climate change’s impacts on oysters relative to their disease exposure and pathogen spread and identifies possible future directions.
The Mediating Impact of Goal–Role Clarity on the Relationship between Feedback–Seeking Behavior and Goal Orientations with Job Satisfaction Intrinsic Cognitions and Person–Organization Fit
Authors: Manolache Madalina , Epuran Gheorghe
Published: August 2023

This study aims to offer a design for the cognitive calibration of employees’ work behaviors. The study focuses on fostering sustainable behavioral patterns in the workplace by arguing that, to sustain the cognitive maintenance of workplace behaviors, the nexus between self-efficacy behaviors, ability beliefs, job–role clarity, and employees’ perceived alignment should be considered during human resource (HR) processes and events, such as feedback conversations and performance reviews. The tool used to collect our data was a questionnaire administered both in paper format and digitally through an online platform compliant with European data protection regulations, to 210 professionals from two IT companies in northeastern Romania (n = 116 for the first sample and n = 94 for the second sample). The series of questions included Likert scales addressing frequency, (dis)agreement, and clarity. The model was tested using SPSS v.27 and SMART-PLS v.4 software, and the study used partial least squares structural equation modeling to examine the proposed hypotheses. Findings for Study 1 indicated that role clarity partially mediated the relationship between feedback–seeking and job cognitions whilst fully mediating the effect on person–organization fit. Results from Study 2 indicated that role clarity partially mediated the relationship between goal orientations and job cognitions and fully mediated the effect on person–organization fit. Therefore, it is possible to aid employees’ in storing their employment narratives in coherent cognitive schemas while elevating their assessment of work values’ alignment and meaningfulness. On this basis, effective tools and methodologies should be made available to employees, at the individual and team level, to help them understand the cognitive processing endorsing workplace behavioral patterns, compatibility, and causality for them to sustainably transform their workplace behavior.
Evaluation of the Level of Farmland Infrastructure Based on High-Resolution Images of UAV
Authors: Pan Jingrui , Chang Chunyan , Wang Zhuoran , Zhao Gengxing , Li Yinshuai , Zhang Shuwei , Chen Yue
Published: August 2023

The evaluation of the level of farmland infrastructure is a necessary objective condition for the use of arable land and agricultural development. In order to investigate the evaluation index system and method of farmland infrastructure level, this article uses the Kenli District of the Yellow River Delta as the research region. In the study region, six typical observation sample areas are chosen. Each area receives high-resolution UAV photos, which are then used to extract information about the farmland infrastructure of the field. A farming infrastructure evaluation index system was built, consisting of 10 indexes for four aspects, including farmland roads, field plots, ditches, and forest belts, using the 100 m by 100 m grid method to divide the evaluation units. The comprehensive index technique was used to calculate the farmland infrastructure score of each unit and identify the degree of excellent, good, and poor farmland infrastructure. The weight of each indication was decided by the hierarchical analysis method. There were 20 excellent grades, 77 good grades, and 29 poor grades among the 126 evaluation units in the study area, with excellent and good grades accounting for 79.13% and area proportions of 14.29%, 64.84%, and 20.87%, respectively. Among the six sample areas, sample areas E and F had the highest percentages of excellent grades, sample area A had 82.62% of the good grades, and all sample areas except A and C had a percentage of poor grades that was higher than 20%. Regularity of the fields, average size of the fields, and the agricultural plot’s slope are the dominant indexes of farmland infrastructure in each observation sample area, and the indexes of the ratio of the perimeter of roads to the perimeter of fields, density of ditches, and the ratio of area of agricultural forest networks to area of fields need to be optimized and improved. The spatial distribution of each grade differs significantly. The evaluation results are consistent with the real situation in the study region and have positive reference meaning for the development and management of farming infrastructure, according to the study’s proposed evaluation system and methodology.
Groundwater Hydrogeochemistry Impacted by Industrial Activities in Ain Sukhna Industrial Area, North-Western Part of the Gulf of Suez, Egypt
Authors: Al-Awah Hezam , Redwan Mostafa , Rizk Shaymaa
Published: August 2023

Economic development and human life depend on groundwater resources in arid regions around the world. To define water quality in the Northwest Gulf of Suez, its elements, geogenic and anthropogenic sources, and suitability for various purposes, ten groundwater samples were collected and analyzed from wells tapping Quaternary and Tertiary aquifers. Average ion distribution was in the following order: Na+ > Mg2+ > Ca2+ > K+ and Cl− > SO42− > HCO3−. Two water types with hydrochemical Ca-Mg-Cl-SO4 facies accounted for 30% of samples due to reverse ion exchange, while Na-K-Cl-SO4 accounted for 70% of samples due to evaporation. Cd (0–0.042 mg/L) and Pb (0–0.222 mg/L) from industrial applications in the study area exceeded the acceptable values in drinking water (>0.003 and 0.01 mg/L, respectively). Heavy metals and ionic value enrichment are due to weathering, precipitation/evaporation, ion exchange, and anthropogenic activities. Most ions in groundwater are higher than the acceptable limits prescribed for drinking water at all sites. Most groundwater in the investigated area is inappropriate for irrigation based on total salinity and MH index. High-salinity-tolerant plants and vegetables can be utilized according to the USSLS diagram. All groundwater samples have improper effects of incrustation and corrosion. Proper management actions are recommended to ameliorate the groundwater quality.
Strata Movement of Overburden-Separation Grouting Working Face and Its Influence on Gas Emission during Mining
Authors: Cao Junwen , Liu Ting , Shi Yu , Lin Baiquan , Shen Jiahao , Xu Youping , Gong Xiangming , Liu Yanchi
Published: August 2023

Due to its excellent effect of surface subsidence reduction, the overburden-separation grouting (OSG) technology has been widely applied to green mining. However, OSG changes the mine pressure, and the resultant gas emission in the stope remains unclear. Therefore, with the 22301 working face of Tunlan Coal Mine as an example, the overburden deformation and stress distribution in the absence and presence of OSG were studied through numerical simulation and on-site tests. Furthermore, the gas emission law in the stope was contrastingly analyzed. The following results were obtained. With the rise of grouting pressure (GP), the subsidence of strata above the separation layer decreases while that below the separation layer increases; the heave displacement of floor strata below the coal seam gradually decreases. OSG significantly changes the geometric shape and range of the overburden stress relief zone. As the GP rises, the gas enrichment area moves downward continuously and shrinks spatially. Horizontally, the ranges of the stress relief zone and the free space in the goaf shrink, while the range and compaction degree of the compaction area gradually grow. After OSG, the total amount of gas emission in the working face falls by 52.2%.
Finding Patterns of Construction Systems in Low-Income Housing for Thermal and Energy Performance Evaluation through Cluster Analysis
Authors: Schaefer Aline , Scolaro Taylana Piccinini , Ghisi Enedir
Published: August 2023

Energy consumption in buildings depends on many factors, including envelope materials. This paper aims to propose a method based on cluster analysis for finding reference models based on actual construction systems of low-income housing. Such reference models can be used in future thermal and energy performance studies. Data on the envelope composition of a sample of 106 dwellings were obtained through a field survey in Florianópolis, southern Brazil. Cluster analyses were performed to group similar materials and construction systems together, and therefore, a reference model was obtained for each cluster. Computer simulations and hypothesis tests were performed to verify whether the reference models represented the sample. Three reference models were obtained from the cluster analysis. Cluster 1 comprised houses with ceramic-brick walls, concrete floor, and concrete slabs. Cluster 2 comprised houses with ceramic-brick walls, concrete floor, ceramic tiles, and wooden ceilings. Cluster 3 comprised houses with wooden walls, wooden floor, cement tiles, and wooden ceilings. Cluster 1 performed better than the other clusters in the cold season (mean degree-hour was 1299 for cooling and 1361 for heating in the reference model). Cluster 2 performed better the other clusters over the hot season (mean degree-hour was 1014 for cooling and 1451 for heating). Cluster 3 showed the worst performance (mean degree-hour was 3793 for cooling and 2988 for heating). Thus, the hypothesis tests have shown that the three reference models differ from each other and can represent their clusters properly. Cluster analysis was a practical and objective method for obtaining reference models.
An Econometric Analysis of Weather Effects on Roadway Crash Severity in Bangladesh: Evidence from the Dhaka Metropolitan Area
Authors: Islam Nazmul , Iqra Sanjida Afroz , Huq Armana Sabiha , Tasnim Aniqa
Published: August 2023

This study identifies how weather-related factors affect crash severity and the number of fatalities from roadway crashes. We use pooled cross-section data for weather-related variables from the National Aeronautics and Space Administration (NASA) and crash data from the Dhaka Metropolitan Police (DMP). The novelty of our paper compared to existing research is the use of weather-related factors as regressors in a multinomial logit model. We use crash severity as the dependent variable. The results show that a unit increase in the specific humidity is associated with a change in the odds of fatal crashes by a factor of 0.2195, keeping other contributory factors constant. This research also shows that an increase in temperature is associated with an increase in the odds of a fatal accident. Moreover, it is observed that a one-unit increase in precipitation results in a 1.1151-unit increase in the odds of the risk of fatal crashes compared to that of non-fatal crashes. After a detailed inspection, wind speed was discovered to be an insignificant weather parameter with regard to accident severity. Furthermore, the number of fatalities is displayed graphically in a time series to thoroughly examine the fatality trend’s relationship with the monthly averaged weather variables. It is expected that the findings of this research will provide policy makers with insights into the weather-related causes of crash severity and assist in the execution of necessary measures to decrease unexpected and avoidable losses on Bangladesh’s roads.
Optimizing a Green and Sustainable Off-Grid Energy-System Design: A Real Case
Authors: Ghadirinejad Nickyar , Ottermo Fredric , Nowzari Raheleh , Alsaadi Naif , Ghadiri Nejad Mazyar
Published: August 2023

In recent years, unquestionable warnings like the negative effects of CO2 emissions, the necessity of utilizing sustainable energy sources, and the rising demand for municipal electrification have been issued. Therefore, users are encouraged to provide off-grid and sustainable energy systems for their own homes and businesses, especially if they are located rurally and far from grids. Hence, this study aims to design an off-grid hybrid energy system, in order to minimize both the baseline cost of energy and the net current expenditure in the desired system. To construct such a system, wind generators (WG), photovoltaic arrays (PV), battery banks, and bi-directional converters are considered in the real case of a supermarket with a 20-year lifespan in Malmö, Sweden. Some significant assumptions, such as the usage of renewable energy resources only, electricity production close to the business location, and a maximum allowance of 0.1% unmet are incorporated. To optimize the considered problem, a particle swarm optimization (PSO) approach as developed to provide the load requirements and establish the number of WGs, PVs, and other equipment. Moreover, to verify the obtained results, the developed system was simulated using HOMER Pro software, and the results are compared and discussed. The results indicated that the designed hybrid energy system is able to perform completely off-grid, while satisfying 99.9% of the yearly electricity demand. The best results obtained by the proposed PSO offered 160, 5, and 350 PVs, WGs, and batteries, respectively, while the best solution found by the simulation method was the use of 384 PVs, 5 WGs, and 189 batteries for the considered off-grid system. This study contributes to decentralized local electrification by utilizing renewable energy sources that have the potential to revolutionize green energy solutions.
The Role of Personality in the Adoption of Pro-Environmental Behaviors through the Lens of the Value-Belief-Norm Theory
Authors: Hidalgo-Crespo J. , Velastegui-Montoya Andrés , Amaya-Rivas J. L. , Soto M. , Riel Andreas
Published: August 2023

The present study investigated citizens’ self-reported pro-environmental behaviors by adopting a survey and bootstrapping via structural equation modeling for five different personality traits. Adopting one traditional psycho-social theory, this study investigates how motivations, values, intentions, norms, and behaviors are connected by using different constructs from the value-belief-norm theory extended with external influences and three different pro-environmental behaviors, namely, waste preventer, green consumer, and avoider, and how the connections change between different personality traits from the Big Five personality test, namely, openness, extroversion, neuroticism, agreeableness, and consciousness. According to this study, personal conscience may inspire environmentally beneficial behaviors like green purchasing and waste reduction when appealing to the emotions of the general public. As a result, strengthening the population’s subjective norms requires interventions that concentrate on communication tactics to raise knowledge of penalties and obligations for communal advantages.
The Impact of Establishment of Nature Reserves on the Urban–Rural Income Gap: Evidence from County-Level Analysis in China
Authors: Cheng Bo , Xue Wenhao , Zheng Yi , Yang Zhe , Tian Yulu
Published: August 2023

While China has seen an economic boom in recent decades, ecological issues are becoming increasingly challenging, with biodiversity seriously threatened. Establishing nature reserves (NRs) is deemed a feasible measure to ease ecological pressure, but few studies have evaluated the impact of the establishment of NRs on the urban–rural income gap. Therefore, based on the county-level panel data from 2010 to 2018, this study analyzed in depth the effects of the establishment of NRs on the urban–rural income gap in China. The results suggested that establishing NRs is beneficial to bridging the income gap between urban and rural areas, especially in the western and the northeastern regions. In contrast to other levels (provincial level, city level, and county level), the establishment of national-level NRs demonstrated a more prominent effect on narrowing the urban–rural income gap. It is thus proposed to improve corresponding laws to strengthen the protection of NRs, especially for those located in the western and northeastern regions, where the increase in eco-economic compensation and development of tourism brands for the ecological tourism industry are of necessity. Taken together, this study provides evidence that the establishment of NRs alleviates the urban–rural income gap in China.
Comparative Study of Different Perovskite Active Layers for Attaining Higher Efficiency Solar Cells: Numerical Simulation Approach
Authors: Bhattarai Sagar , Mohammed Mustafa K. A. , Madan Jaya , Pandey Rahul , Abdelkader Hima , Farhat Lamia Ben , Amami Mongi , Hossain M. Khalid
Published: August 2023

The simulated device structures of ITO/ZnO/Perovskite absorber layers (PAL)/Spiro-OMeTAD/Au with distinct absorbers were modeled and investigated using solar cell capacitance simulator (SCAPS-1D) simulating software (version 3.8). The primary objective is to enhance the thermal stability of the solar device. As the absorber thickness and temperature impact PV performance parameters, thus main aim of this work is to determine the optimum thickness of PAL as well as the temperature affectability on the PV performance of the cells. It was also observed that the maximum PV parameters (among the cells under consideration), viz. 29% PCE, are achieved with the formamidinium tin iodide (FASnI3) at the thickness of 600 nm. Similarly, the temperature of 300 K shows a much-improved efficiency offering nearly 29%. Further, the external quantum efficiency (EQE) and J-V also confirm the determent of the more stable, lead-free, FASnI3-based device, which can provide an effective way to develop highly efficient, low-cost solar cell devices.
Can Service Trade Effectively Promote Carbon Emission Reduction?—Evidence from China
Authors: Liang Hongze , Hao Xiaoli
Published: August 2023

Carbon emissions have become a global issue of increasing concern due to their detrimental impact on the environment. Efforts to combat rising emissions have been taken globally. Despite China’s commitment to globalization, policymakers have faced challenges in adequately addressing this pressing issue. This paper aims to fill this gap by exploring a specific aspect of international trade, namely service trade. We theoretically analyzed the impact of service trade on carbon emissions and then empirically examined the impact using panel data from 2009 to 2019 of 30 provincial regions in China. Specifically, a non-linear model was used to capture the direct effect, particularly the potential non-linear relationship; a mediating effect model was applied to investigate the indirect effects; and a panel quantile model was adopted to examine the heterogeneity of the impact across different levels of carbon emissions. The research revealed: (1) The impact of service trade on carbon emissions exhibits a non-linear characteristic with a significant inverted U-shaped relationship being evident, indicating that the development of service trade can ultimately contribute to carbon reduction; (2) service trade can directly impact carbon emissions through its scale effect, while mechanism analysis showed that service trade can indirectly affect carbon emissions through its technological and structural effects, with carbon emission reduction also relying on these mechanisms; (3) There is significant heterogeneity in the impact of service trade on carbon emissions across geographic regions and at different levels of carbon emissions in China.
Impact of Green Finance on Carbon Emissions Based on a Two-Stage LMDI Decomposition Method
Authors: Lin Zirong , Wang Hui , Li Wei , Chen Min
Published: August 2023

As the “double carbon” goal gains traction worldwide, achieving a balance between economic growth and environmental sustainability has become a focal point for researchers. Green finance, as a specialized financial service, offers a new approach to sustainable development. This study analyzed carbon emission sources in 25 Chinese provinces between 2007 and 2020, dividing them into energy structure, economic development, energy efficiency, and industrial structure, using a two-stage LMDI method. It then examines the linear and non-linear relationships between green finance and carbon emissions using spatial measurement methods. The findings indicate that green finance is an effective way to reduce carbon emissions, primarily through its impact on energy structure, energy efficiency, and industrial structure. There are significant non-linear relationships between green finance and the factors affecting carbon emissions, with spatial effects playing a significant role in carbon emissions influenced by energy structure, economic development, energy efficiency, and industrial structure.
An Experimental Study on the Component Analysis and Variation in Concentration of Tire and Road Wear Particles Collected from the Roadside
Authors: Kang Taewoo , Kim Hyeokjung
Published: August 2023

Tire and road wear particles (TRWPs) are generated unintentionally while driving vehicles. The generated TRWPs move to various environments by environmental and mechanical action, and they are present in fresh water, river, and ocean and may cause problems to the environment and human health. In Korea, the number of registered cars is increasing year by year, so the problem of TRWPs will become serious. In this study, we study the concentrations of TRWPs generated from the roadsides by temperature difference, in order to reduce the generation of TRWPs. Dust samples were collected from roadsides during summer and winter to measure the amount of TRWPs generated on roadsides according to seasonal temperature changes. Dust particles of 75–150 µm size, which corresponds to the TRWP size, were separated from the dust samples using sieves. Additionally, only TRWPs were separated using a solution of dibromomethane and Trans-1,2-dichloroethylene. TRWPs accounted for <2% in the dust collected from roadsides, and their amount increased by approximately 7.6–24.2% in summer more than in winter. Thermogravimetric analysis results confirmed that the tire components and road components and minerals accounted for 30% and 70% in TRWPs regardless of the season, respectively.
Exploring BoP Generations through Business Model Innovation Lens: A Review and Framing
Authors: Voros Fregolente Mariana , Carvalho Marly M.
Published: August 2023

The evolution of base/bottom of the pyramid (BoP) literature from BoP 1.0 to 3.0 prompted the need for fresh theoretical perspectives to address complex and persistent social issues. This article investigates BoP through the lens of business model innovation, using a literature review along with bibliometric, network, and content analyses, to map the intellectual and conceptual structure and understand the key variables relating to BoP business models. The research encompasses 161 articles extracted from the Web of Science and Scopus databases. Documents were screened manually and with the assistance of VOS Viewer 1.6.18, Biblioshiny 4.0, IBM SPSS 20, UCINET6, and NVivo12, using abductive and deductive coding techniques. The findings reveal a prevailing focus on the exploratory phase among the articles, with a predominant utilization of qualitative research methods, particularly centered on case studies. Interviews and public data sources constitute the primary sources for supporting empirical evidence. Notably, the majority of these cases pertain to emerging economies situated across Asia, Africa, and Latin America, with India emerging as the most frequently cited country in the literature. Sectors, such as energy, healthcare, agrifood, finance, and telecommunications are studied, emphasizing themes of innovation, entrepreneurship, and corporate social responsibility (CSR). Emerging themes include social entrepreneurship, frugal innovation, and inclusive business models. The research panorama encompasses a categorization of BoP enterprises based on their origin (top-down or bottom-up), their typology (commercial, assistance, or collaboration), and their interactions with BoP communities (either as customers or entrepreneurs). From an innovation standpoint, certain concepts emerged, notably frugal innovation and bricolage, accompanied by the incorporation of ecosystem theory and sustainability perspectives. The research also outlines a BoP business model framework, providing insights into key components favored by entrepreneurs in this realm.
The New Geography of Manufacturing in China: The Internet and Manufacturing Agglomeration
Authors: Sun Yanlin , Ma Shaoxiong , Feng Hao
Published: August 2023

The Internet has profoundly affected the spatial structure of cities, but few relevant studies have investigated it from the perspective of manufacturing agglomeration. Using panel data of prefecture-level cities in China covering the period 2003–2019, this paper studies how the Internet affects manufacturing agglomeration. The results show that there is a U-shaped relationship between the Internet and manufacturing agglomeration, and the underlying channel can be the enhancement of market potential. Human capital can enhance the role of the Internet in promoting manufacturing agglomeration. The findings can contribute to a better understanding of the relationship between the Internet and urban spatial structure in developing countries.
Examining the Roles of Training, Fit Testing, and Safety Climate on User Confidence in Respiratory Protection: A Case Example with Reusable Respirators in Health Delivery Settings
Authors: Edirisooriya Mihili , Haas Emily J.
Published: August 2023

A lack of confidence in the efficacy of respiratory protection can contribute to uncertainty among workers and cast doubt on workplace safety. To date, no research has been conducted to study and understand the introduction of elastomeric half-mask respirators (EHMRs)—without exhalation valves (EVs) or with exhalation valve filters (EVFs), both representing new designs that address source control—in the workplace. To study this issue, researchers collaborated with partners at 32 health delivery settings that received EHMRs from the Strategic National Stockpile during the COVID-19 pandemic. EHMR users (n = 882) completed an online survey between October 2021 and September 2022. Analyses demonstrated that employees were statistically significantly more confident in the efficacy of EHMRs with no EV/with an EVF (including the efficacy in protecting the user from COVID-19) if they had been fit tested and received training. Respondents were also statistically significantly more confident in the efficacy of their EHMR if they had a more positive perception of their organization’s safety climate. The results provide insights for tailored fit testing and training procedures as manufacturers continue to improve respirator models to enhance worker comfort and use. Results also show that, even during a public health emergency, the role of safety climate cannot be ignored as an organizational factor to support worker knowledge, attitudes, and participation in health and safety behaviors specific to respirator use.