bluuebunny/crossref_metadata_2025 huggingface dataset:
Super-Resolution Technique of Multi-Radar Fusion 2D Imaging Based on ExCoV Algorithm in Low SNR
Authors: Song Dawei , Shang She , Ding Dazhi
Published: April 2023

Limited by the hardware, the bandwidth of the transmitted signal is not wide enough for super resolution; this is the same for cross resolution, which is limited by the observation angle. In this paper, we propose a technique for imaging fusion using 2D-imaging super-resolution by using multi-radar data from different observation locations, and the resultant effective band is proposed. First, a sparse 2D parametric model based on GTD theory is introduced to construct a dictionary by matching the scattering theory of the radar observation target. Then, the multi-radar fusion imaging framework is constructed. Meanwhile, the 2D model’s sparse parameters are obtained in low SNR using an expansion-compression variance-component algorithm. Finally, radar echo data is expanded to realize the fusion imaging process. The simulation results show that the image quality is improved after multi-radar fusion, which is better than that of the single radar echo, verifying the effectiveness of our method.
Shoreline Detection from PRISMA Hyperspectral Remotely-Sensed Images
Authors: Souto-Ceccon Paola , Simarro Gonzalo , Ciavola Paolo , Taramelli Andrea , Armaroli Clara
Published: April 2023

Coastal managers, policymakers, and scientists use shoreline accretion/erosion trends to determine the coastline’s historical evolution and generate models capable of predicting future changes. Different solutions have been developed to obtain shoreline positions from Earth observation data in recent years, the so-called Satellite-Derived Shorelines (SDS). Most of the methodologies available in the literature use multispectral optical satellite imagery. This paper proposes two new methods for shoreline mapping at the subpixel level based on PRISMA hyperspectral imagery. The first one analyses the spectral signatures along defined beach profiles. The second method uses techniques more commonly applied to multispectral image analysis, such as Spectral Unmixing algorithms and Spatial Attraction Models. The results obtained with both methodologies are validated on three Mediterranean microtidal beaches located in two different countries, Italy and Greece, using image-based ground truth shorelines manually photointerpreted and digitised. The obtained errors are around 6 and 7 m for the first and second methods, respectively. These results are comparable to the errors obtained from multispectral data. The paper also discusses the capability of the two methods to identify two different shoreline proxies.
Soil Organic Carbon Prediction Using Sentinel-2 Data and Environmental Variables in a Karst Trough Valley Area of Southwest China
Authors: Wang Ting , Zhou Wei , Xiao Jieyun , Li Haoran , Yao Li , Xie Lijuan , Wang Keming
Published: April 2023

Climate change is closely linked to changes in soil organic carbon (SOC) content, which affects the terrestrial carbon cycle. Consequently, it is essential for carbon accounting and sustainable soil management to predict SOC content accurately. Although there has been an extensive utilization of optical remote sensing data and environmental factors to predict SOC content, few studies have explored their applicability in karst areas. Therefore, it remains unclear how SOC content can be accurately simulated in these areas. In this study, 160 soil samples, 8 environmental covariates and 14 optical remote sensing variables were used to build SOC content prediction models. Three machine learning models, i.e., support vector machine (SVM), random forest (RF) and extreme gradient boosting (XGBoost), were applied for each of three land use classes, including the entire study area, as well as farmland and forest areas. The variables with the greatest influence were the optical remote sensing bands, derived indices, as well as precipitation and temperature for forest areas, and optical remote sensing band11 and Pop-density for farmland. The results from this study suggest that RF and XGBoost are superior to SVM in prediction accuracy. Additionally, the simulation accuracy of the RF model for the forest areas (R2 = 0.32, RMSE = 6.81, MAE = 5.63) and of the XGBoost model for farmland areas (R2 = 0.28, RMSE = 4.03, MAE = 3.27) was the greatest. The prediction model based on different land use types could obtain a higher simulation accuracy than that based on the whole study area. These findings provide new insights for the estimation of SOC content with high precision in karst areas.
An Innovative Approach for Effective Removal of Thin Clouds in Optical Images Using Convolutional Matting Model
Authors: Wu Renzhe , Liu Guoxiang , Lv Jichao , Fu Yin , Bao Xin , Shama Age , Cai Jialun , Sui Baikai , Wang Xiaowen , Zhang Rui
Published: April 2023

Clouds are the major source of clutter in optical remote sensing (RS) images. Approximately 60% of the Earth’s surface is covered by clouds, with the equatorial and Tibetan Plateau regions being the most affected. Although the implementation of techniques for cloud removal can significantly improve the efficiency of remote sensing imagery, its use is severely restricted due to the poor timeliness of time-series cloud removal techniques and the distortion-prone nature of single-frame cloud removal techniques. To thoroughly remove thin clouds from remote sensing imagery, we propose the Saliency Cloud Matting Convolutional Neural Network (SCM-CNN) from an image fusion perspective. This network can automatically balance multiple loss functions, extract the cloud opacity and cloud top reflectance intensity from cloudy remote sensing images, and recover ground surface information under thin cloud cover through inverse operations. The SCM-CNN was trained on simulated samples and validated on both simulated samples and Sentinel-2 images, achieving average peak signal-to-noise ratios (PSNRs) of 30.04 and 25.32, respectively. Comparative studies demonstrate that the SCM-CNN model is more effective in performing cloud removal on individual remote sensing images, is robust, and can recover ground surface information under thin cloud cover without compromising the original image. The method proposed in this article can be widely promoted in regions with year-round cloud cover, providing data support for geological hazard, vegetation, and frozen area studies, among others.
Performance Evaluation of Container Orchestration Tools in Edge Computing Environments
Authors: Čilić Ivan , Krivić Petar , Podnar Žarko Ivana , Kušek Mario
Published: April 2023

Edge computing is a viable approach to improve service delivery and performance parameters by extending the cloud with resources placed closer to a given service environment. Numerous research papers in the literature have already identified the key benefits of this architectural approach. However, most results are based on simulations performed in closed network environments. This paper aims to analyze the existing implementations of processing environments containing edge resources, taking into account the targeted quality of service (QoS) parameters and the utilized orchestration platforms. Based on this analysis, the most popular edge orchestration platforms are evaluated in terms of their workflow that allows the inclusion of remote devices in the processing environment and their ability to adapt the logic of the scheduling algorithms to improve the targeted QoS attributes. The experimental results compare the performance of the platforms and show the current state of their readiness for edge computing in real network and execution environments. These findings suggest that Kubernetes and its distributions have the potential to provide effective scheduling across the resources on the network’s edge. However, some challenges still have to be addressed to completely adapt these tools for such a dynamic and distributed execution environment as edge computing implies.
Dynamic Analysis of the Coracohumeral Ligament Using Ultra-Sonography in Shoulder Contracture
Authors: Kato Tatsuo , Inui Atsuyuki , Mifune Yutaka , Nishimoto Hanako , Yoshikawa Tomoya , Shinohara Issei , Furukawa Takahiro , Tanaka Shuya , Kusunose Masaya , Kuroda Ryosuke
Published: April 2023

The coracohumeral ligament (CHL) is related to the range of motion of the shoulder joint. The evaluation of the CHL using ultrasonography (US) has been reported on the elastic modulus and thickness of the CHL, but no dynamic evaluation method has been established. We aimed to quantify the movement of the CHL by applying Particle Image Velocimetry (PIV), a technique used in the field of fluid engineering, to cases of shoulder contracture using the US. The subjects were eight patients, with 16 shoulders. The coracoid process was identified from the body surface, and a long-axis US image of the CHL parallel to the subscapularis tendon was drawn. The shoulder joint was moved from 0 degrees of internal/external rotation to 60 degrees of internal rotation at a rhythm of one reciprocation every 2 s. The velocity of the CHL movement was quantified by the PIV method. The mean magnitude velocity of CHL was significantly faster on the healthy side. The maximum magnitude velocity was significantly faster on the healthy side. The results suggest that the PIV method is helpful as a dynamic evaluation method, and in patients with shoulder contracture, the CHL velocity was significantly decreased.
Information Security Threats and Working from Home Culture: Taxonomy, Risk Assessment and Solutions
Authors: Kotak Jaidip , Habler Edan , Brodt Oleg , Shabtai Asaf , Elovici Yuval
Published: April 2023

During the COVID-19 pandemic, most organizations were forced to implement a work-from-home policy, and in many cases, employees have not been expected to return to the office on a full-time basis. This sudden shift in the work culture was accompanied by an increase in the number of information security-related threats which organizations were unprepared for. The ability to effectively address these threats relies on a comprehensive threat analysis and risk assessment and the creation of relevant asset and threat taxonomies for the new work-from-home culture. In response to this need, we built the required taxonomies and performed a thorough analysis of the threats associated with this new work culture. In this paper, we present our taxonomies and the results of our analysis. We also examine the impact of each threat, indicate when it is expected to occur, describe the various prevention methods available commercially or proposed in academic research, and present specific use cases.
A Threshold Helium Leakage Detection Switch with Ultra Low Power Operation
Authors: Mohaidat Sulaiman , Alsaleem Fadi
Published: April 2023

Detecting helium leakage is important in many applications, such as in dry cask nuclear waste storage systems. This work develops a helium detection system based on the relative permittivity (dielectric constant) difference between air and helium. This difference changes the status of an electrostatic microelectromechanical system (MEMS) switch. The switch is a capacitive-based device and requires a very negligible amount of power. Exciting the switch’s electrical resonance enhances the MEMS switch sensitivity to detect low helium concentration. This work simulates two different MEMS switch configurations: a cantilever-based MEMS modeled as a single-degree-freedom model and a clamped-clamped beam MEMS molded using the COMSOL Multiphysics finite-element software. While both configurations demonstrate the switch’s simple operation concept, the clamped-clamped beam was selected for detailed parametric characterization due to its comprehensive modeling approach. The beam detects at least 5% helium concentration levels when excited at 3.8 MHz, near electrical resonance. The switch performance decreases at lower excitation frequencies or increases the circuit resistance. The MEMS sensor detection level was relatively immune to beam thickness and parasitic capacitance changes. However, higher parasitic capacitance increases the switch’s susceptibility to errors, fluctuations, and uncertainties.
Improving the Accuracy of TOF LiDAR Based on Balanced Detection Method
Authors: Li Jingjing , Bi Ying , Li Kun , Wu Lingyi , Cao Jie , Hao Qun
Published: April 2023

The ranging accuracy of pulsed time-of-flight (TOF) lidar is affected by walk error and jitter error. To solve the issue, the balanced detection method (BDM) based on fiber delay optic lines (FDOL) is proposed. The experiments are carried out to prove the performance improvement of BDM over the conventional single photodiode method (SPM). The experimental results show that BDM can suppress common mode noise and simultaneously shift the signal to high frequency, which reduces the jitter error by approximately 52.4% and maintains the walk error at less than 300 ps with a non-distorted waveform. The BDM can be further applied to silicon photomultipliers.
In-Wheel Motor Fault Diagnosis Using Affinity Propagation Minimum-Distance Discriminant Projection and Weibull-Kernel-Function-Based SVDD
Authors: Liu Bingchen , Xue Hongtao , Ding Dianyong , Sun Ning , Chen Peng
Published: April 2023

To effectively ensure the operational safety of an electric vehicle with in-wheel motor drive, a novel diagnosis method is proposed to monitor each in-wheel motor fault, the creativity of which lies in two aspects. One aspect is that affinity propagation (AP) is introduced into a minimum-distance discriminant projection (MDP) algorithm to propose a new dimension reduction algorithm, which is defined as APMDP. APMDP not only gathers the intra-class and inter-class information of high-dimensional data but also obtains information on the spatial structure. Another aspect is that multi-class support vector data description (SVDD) is improved using the Weibull kernel function, and its classification judgment rule is modified into a minimum distance from the intra-class cluster center. Finally, in-wheel motors with typical bearing faults are customized to collect vibration signals under four operating conditions, respectively, to verify the effectiveness of the proposed method. The results show that the APMDP’s performance is better than traditional dimension reduction methods, and the divisibility is improved by at least 8.35% over the LDA, MDP, and LPP. A multi-class SVDD classifier based on the Weibull kernel function has high classification accuracy and strong robustness, and the classification accuracies of the in-wheel motor faults in each condition are over 95%, which is higher than the polynomial and Gaussian kernel function.
Exposure to Multicultural Context Affects Neural Response to Out-Group Faces: A Functional Magnetic Resonance Imaging Study
Authors: Carollo Alessandro , Rigo Paola , Bizzego Andrea , Lee Albert , Setoh Peipei , Esposito Gianluca
Published: April 2023

Recent migration and globalization trends have led to the emergence of ethnically, religiously, and linguistically diverse countries. Understanding the unfolding of social dynamics in multicultural contexts becomes a matter of common interest to promote national harmony and social cohesion among groups. The current functional magnetic resonance imaging (fMRI) study aimed to (i) explore the neural signature of the in-group bias in the multicultural context; and (ii) assess the relationship between the brain activity and people’s system-justifying ideologies. A sample of 43 (22 females) Chinese Singaporeans (M = 23.36; SD = 1.41) was recruited. All participants completed the Right Wing Authoritarianism Scale and Social Dominance Orientation Scale to assess their system-justifying ideologies. Subsequently, four types of visual stimuli were presented in an fMRI task: Chinese (in-group), Indian (typical out-group), Arabic (non-typical out-group), and Caucasian (non-typical out-group) faces. The right middle occipital gyrus and the right postcentral gyrus showed enhanced activity when participants were exposed to in-group (Chinese) rather than out-group (Arabic, Indian, and Caucasian) faces. Regions having a role in mentalization, empathetic resonance, and social cognition showed enhanced activity to Chinese (in-group) rather than Indian (typical out-group) faces. Similarly, regions typically involved in socioemotional and reward-related processing showed increased activation when participants were shown Chinese (in-group) rather than Arabic (non-typical out-group) faces. The neural activations in the right postcentral gyrus for in-group rather than out-group faces and in the right caudate in response to Chinese rather than Arabic faces were in a significant positive correlation with participants’ Right Wing Authoritarianism scores (p < 0.05). Furthermore, the activity in the right middle occipital gyrus for Chinese rather than out-group faces was in a significant negative correlation with participants’ Social Dominance Orientation scores (p < 0.05). Results are discussed by considering the typical role played by the activated brain regions in socioemotional processes as well as the role of familiarity to out-group faces.
Implementing Dual Base Stations within an IoT Network for Sustaining the Fault Tolerance of an IoT Network through an Efficient Path Finding Algorithm
Authors: Sastry J. K. R. , Ch Bhupati , Budaraju Raja Rao
Published: April 2023

The IoT networks for implementing mission-critical applications need a layer to effect remote communication between the cluster heads and the microcontrollers. Remote communication is affected through base stations using cellular technologies. Using a single base station in this layer is risky as the fault tolerance level of the network will be zero when the base stations break down. Generally, the cluster heads are within the base station spectrum, making seamless integration possible. Implementing a dual base station to cater for a breakdown of the first base station creates huge remoteness as the cluster heads are not within the spectrum of the second base station. Furthermore, using the remote base station involves huge latency affecting the performance of the IoT network. In this paper, a relay-based network is presented with intelligence to fetch the shortest path for communicating to reduce latency and sustain the fault tolerance capability of the IoT network. The results demonstrate that the technique improved the fault tolerance of the IoT network by 14.23%.
Longitudinal Gait Analysis of a Transfemoral Amputee Patient: Single-Case Report from Socket-Type to Osseointegrated Prosthesis
Authors: Di Paolo Stefano , Barone Giuseppe , Alesi Domenico , Mirulla Agostino Igor , Gruppioni Emanuele , Zaffagnini Stefano , Bragonzoni Laura
Published: April 2023

The aim of the present case report was to provide a longitudinal functional assessment of a patient with transfemoral amputation from the preoperative status with socket-type prosthesis to one year after the osseointegration surgery. A 44 years-old male patient was scheduled for osseointegration surgery 17 years after transfemoral amputation. Gait analysis was performed through 15 wearable inertial sensors (MTw Awinda, Xsens) before surgery (patient wearing his standard socket-type prosthesis) and at 3-, 6-, and 12-month follow-ups after osseointegration. ANOVA in Statistical Parametric Mapping was used to assess the changes in amputee and sound limb hip and pelvis kinematics. The gait symmetry index progressively improved from the pre-op with socket-type (1.14) to the last follow-up (1.04). Step width after osseointegration surgery was half of the pre-op. Hip flexion-extension range significantly improved at follow-ups while frontal and transverse plane rotations decreased (p < 0.001). Pelvis anteversion, obliquity, and rotation also decreased over time (p < 0.001). Spatiotemporal and gait kinematics improved after osseointegration surgery. One year after surgery, symmetry indices were close to non-pathological gait and gait compensation was sensibly decreased. From a functional point of view, osseointegration surgery could be a valid solution in patients with transfemoral amputation facing issues with traditional socket-type prosthesis.
Smart Metering Cybersecurity—Requirements, Methodology, and Testing
Authors: Kohout David , Lieskovan Tomas , Mlynek Petr
Published: April 2023

This paper addresses the current challenges in cybersecurity of smart metering infrastructure, specifically in relation to the Czech Decree 359/2020 and the DLMS security suite (device language message specification). The authors present a novel testing methodology for verifying cybersecurity requirements, motivated by the need to comply with European directives and legal requirements of the Czech authority. The methodology encompasses testing cybersecurity parameters of smart meters and related infrastructure, as well as evaluating wireless communication technologies in the context of cybersecurity requirements. The article contributes by summarizing the cybersecurity requirements, creating a testing methodology, and evaluating a real smart meter, using the proposed approach. The authors conclude by presenting a methodology that can be replicated and tools that can be used to test smart meters and the related infrastructure. This paper aims to propose a more effective solution and takes a significant step towards improving the cybersecurity of smart metering technologies.
Synthesis of Isoreticular Metal Organic Framework-3 (IRMOF-3) Porous Nanostructure and Its Effect on Naphthalene Adsorption: Optimized by Response Surface Methodology
Authors: Kalashgrani Masoomeh , Babapoor Aziz , Mousavi Seyyed , Feizpoor Solmaz , Hashemi Seyyed , Binazadeh Mojtaba , Chiang Wei-Hung , Lai Chin
Published: April 2023

Naphthalene is a carcinogenic compound and its environmental release poses a major risk to human and aquatic health. Therefore, the application of nanomaterial technologies for naphthalene removal from wastewater has attracted significant attention. In this research, for the first time, the performance of IRMOF-3 for naphthalene removal from aqueous media is evaluated. IRMOF-3 with a specific surface area of 718.11 m2·g−1 has the ability to absorb naphthalene from synthetic wastewater to a high extent. The structures and morphology of IRMOF-3 were determined by FT-IR, XRD, SEM and BET analyses. Thirty adsorption experiments were conducted to obtain the best conditions for naphthalene removal. An optimum naphthalene removal efficiency of 80.96% was obtained at IRMOF-3 amounts of 0.1 g·L−1, a solution concentration of 15 mg·L−1, a contact time of 60 min and a pH = 11. The results indicate that the lower the concentration of naphthalene, the higher its dispersion at the surface of the porous nanostructure. Increasing naphthalene concentration results in its accumulation on porous nanostructures that clog cavities. In addition, high contact time provides ample opportunity for naphthalene to penetrate the cavities and pores which facilitates crystallization phenomena deep in the pores. Finally, the results of this study revealed that IRMOF-3 is one of the most effective adsorbents for naphthalene removal from wastewater.
The Career Adaptability and Support Structures of Pilots Losing Medical Certification
Authors: Kurukulaadithya Trevis , Nair Rajeev , Tariq Waqas , Wall Jeremy , Rodwell John
Published: April 2023

The regulation of occupations such as aviation pilots can result in their facing the shock of losing their medical certification and thus, their license to work. What are the issues that these former pilots face upon losing their medical certification? The key issues may take the form of protean career characteristics and mechanisms such as identity, adaptability, and agency, which may help the individuals match to a new occupational environment. The method of convergent interviewing is used to inductively acquire the key common issues that arise when pilots lose their medical certification in Australia. The results indicate that the clarity and strength of the pilots’ sense of occupational identity may amplify the impact of the shock when that career is denied to them. The findings highlight the importance of adaptability, although the reliance on adaptability varies depending on the pathway chosen to respond to the shock. Those in situations with less adaptability, agency, or support may be most in need of career and mental health counseling. Support and adaptability may be particularly important for those facing career shocks in occupations with substantial investments in their career identity.
Secondary Traumatic Stress in Portuguese Social Workers
Authors: Carvalho Maria Irene , Cunha Sofia Mendes , Teles Helena , Ribeirinho Carla
Published: April 2023

This article analyses the level of secondary traumatic stress in Portuguese social workers. Social workers practice their profession in conditions that generate stress and trauma on a daily basis; this is triggered by clients’ anxiety, threats to the integrity of the professionals, and situations that have a negative impact on professional practice. This study was conducted in organisations registered under the Social Charter, which coordinates institutions of social policies operationalised in Portugal. A Secondary Traumatic Stress (STS) index was used to obtain data regarding practitioners’ practice for the characterisation and identification of situations of trauma experienced by clients, and their impact on social workers. Questionnaires were sent to the organisations via email, and in return 872 were answered by social workers. The results reveal a score of 2.65 on the Secondary Traumatic Stress Scale, and this appears more apparent in the Arousal dimension, followed by Avoidance and lastly Intrusion. Furthermore, it is evident that the conditions of professional practice and the sector in which professionals work generate STS because they significantly expose social workers to the traumas of the most vulnerable clients. The professionals recognise these incidences, which feasibly denotes that there is a possibility to avoid and act against STS by stimulating professionals’ internal resilience and psychological capital, increasing professionals’ access to professional supervision and improving working conditions in the organisations where they practice.
Smart Material Handling Solutions for City Logistics Systems
Authors: Tadić Snežana , Krstić Mladen , Dabić-Miletić Svetlana , Božić Mladen
Published: April 2023

Globalization, the growth of the world population, urbanization and the growth of the volume of the flow of goods have generated numerous problems in city logistics (CL). The opportunity to solve them is found in various fields by defining and implementing initiatives, concepts, measures, modern technologies and scenarios. The efficiency of the solution largely depends on the efficiency of logistics centers, which is one of the key subsystems of CL. The requirements for the reliable delivery of goods to customers in urban areas are conditioned by the efficiency their order fulfillment in logistics centers. Therefore, optimizing material handling (MH) time and costs aimed at reducing delivery errors, minimizing damage to goods and increasing customer service efficiency is directly conditioned by the automation of MH in logistics centers. Accordingly, this paper aims to rank and select smart MH solutions in logistics centers where deliveries are prepared for the supply of the city area. This paper proposes four smart solutions for a real company, and fourteen criteria are selected for the evaluation. A new hybrid Multi-Criteria Decision-Making model that combines the Fuzzy Analytic Hierarchy Process method, used to determine the criteria weights, and the Fuzzy COmprehensive distance-Based RAnking (FCOBRA) method, used to rank the alternatives, is proposed. The application of the model shows that the best alternative is the implementation of an autonomous forklift, which can greatly automate logistics activities and reduce the rate of delivery errors. The main contributions of this research are the definition of smart solutions, a framework for their evaluation and a new model for their ranking.
Understanding the COVID-19 Pandemic’s Impact on E-Learner Satisfaction at the Tertiary Level
Authors: Islam Mohammed Rafiqul , Sarker Rimon , Sultana Rebaka , Faisal-E-Alam Md. , Castanho Rui Alexandre , Meyer Daniel
Published: April 2023

E-learning has recently gained considerable interest among stakeholders, including educators, students, and policymakers. During the pandemic, organized online learning is critical to an effective e-learning system because it helps both teaching and learning. Thus, the current study intends to explore the factors contributing to e-learners’ satisfaction during the COVID-19 pandemic. A questionnaire survey was conducted to gather data from 650 university students selected through convenience sampling. The data were analyzed using the Statistical Package for the Social Sciences (SPSS). The factors essential to boosting e-learner satisfaction were identified using confirmatory factor analysis (CFA). Frequency distribution and percentages were used to identify the demographic characteristics of respondents, and a reliability test was conducted to test the internal consistency of the data. This study employed structural equation modeling (SEM) to trace the relationship between the six independent variables and e-learner satisfaction. Regression results revealed that psychological factors, educational materials and design, access to technological devices, instructor attributes, and perceptions and expectations significantly influence e-learner satisfaction. However, students’ engagement had no significant influence on the same. Because, most respondents had a clear preference for physical learning. The findings of this study will help educationists and policymakers take necessary steps in enhancing learners’ satisfaction and improving their academic performance.
An Investigation of the Key Attributes of Korean Wellness Tourism Customers Based on Online Reviews
Authors: Riswanto Aura Lydia , Kim Hak-Seon
Published: April 2023

With its fast-growing trend, wellness tourism is transforming the client base and service and product offerings, and it is attracting new suppliers. The purpose of understanding the customer experience as portrayed in online reviews is to sustainably maintain customer loyalty and satisfaction. The objective of this research is to identify the critical attributes and their structural relationships to Korean wellness tourism. The study analyzed 24,060 Google-based customer reviews on 11 wellness tourism destinations in South Korea. Following the calculation of word frequencies in a matrix, UCINET 6.0 was utilized to analyze the centrality of the network and perform a CONCOR analysis. Based on the findings of the CONCOR analysis, the review data were sorted into four distinct categories. Following the quantitative analysis led to the identification of six variables that were grouped together through exploratory factor analysis.: wellness, tangible, value, F&B, purpose, and service. Whereas value, F&B, and service negatively affected the satisfaction of guests, the study also revealed that wellness, tangible, and purpose all had positive impacts and contributed to increased trust among wellness tourism customers. In terms of managerial implication, the results will enable wellness tourism destination managers to focus more on improving the factors of value, food, and service.
Environmentally Friendly Materialism: How It Is Generated and How Luxury Apparel Addresses Environmental Problems
Authors: Furukawa Hiroyasu , Lee Kyung-Tae
Published: April 2023

The increasing number of consumers possessing a global mindset has led to the emergence of environmentally friendly materialist consumers who find pleasure in owning environmentally friendly brands and products. We examine why and how such consumers emerge by studying consumers of luxury apparel products, which actively promote environmentally conscious values on a global scale. Structural equation modeling and mediation analysis were conducted on consumers in China and Japan—two countries with high consumption of this product category and a contrasting awareness of environmental consciousness. Our findings revealed that the higher the global mindset of consumers, environmentally friendly materialism is enhanced by internal motives in countries with high environmental consciousness and by external motives in countries with low environmental consciousness. Our results have implications for mechanisms on how the conditions for the emergence of environmentally friendly materialism differ from country to country and marketing measures that respond to these differences.
Triple Bottom Line, Sustainability, and Economic Development: What Binds Them Together? A Bibliometric Approach
Authors: Nogueira Elisabete , Gomes Sofia , Lopes João M.
Published: April 2023

The importance given to sustainable development paved the way for the development of the triple bottom line (TBL) concept. TBL is vital for the assessment of nations’ economic development (ED) beyond traditional economic measures. Despite this relevance, few studies still seek to deepen our understanding of the interaction between TLB and ED. Thus, this bibliometric study aimed to analyse the relationship between TBL, sustainability, and ED, adding business strategy concepts such as competitiveness, decision making, planning, and performance. We intended to reinforce the extension of TBL’s dominant rhetoric to sustainable ED. The results revealed the relationship between TBL and ED and allowed the identification of four clusters, from which a theoretical–conceptual model of the theory and application of TBL to achieve ED was formulated. This model can be adopted for the consolidation of ED through the TBL framework and as a tool to support business strategy related to obtaining competitive advantage; decision making; planning; and stimulating economic, social, and environmental performance.
Synthesis, Stability and Microstructure of a One-Step Mixed Geopolymer Backfill Paste Derived from Diverse Waste Slags
Authors: Zhao Xianhui , Wang Haoyu , Gao Han , Liang Luhui , Yang Jing
Published: April 2023

The advent of industrialization has produced an enormous amount of industrial waste slag, which drastically pollutes environmental resources. This study examines the production, stability, and microstructure of a novel backfill geopolymer paste derived from multiple industrial waste slags, including silica-alumina precursors (low-calcium composition) and waste slags (high-calcium composition), as well as two additives. The characteristics of self-hardening were discovered. The effects of low-calcium fly ash, granulated blast furnace slag, red mud, and lime powder on fluidity and compressive strength were then evaluated. To assess the stability, the resistances to drying shrinkage, permeability, and chemical attack by an optimized geopolymer backfill paste were investigated. Furthermore, SEM-EDS, XRD, FTIR, and TG-DSC tests were employed to reveal the microstructures, products, and thermal stability. The results show that the backfill paste hardens well and has no impact on alkalinity dissolution for adjacent soils and water. The optimum sample, P1, had a water-binder ratio of 0.70, resulting in 201 mm fluidity and 2.1 MPa 28-d compressive strength. In terms of drying shrinkage, permeability, and Na2SO4 and NaCl solution attack, sample P1 outperformed the conventional Ordinary Portland cement paste (OPC) for 90 days. The paste P1 containing about 46.0 wt% waste slags meets the fresh and hardened property requirements for goaf backfill, and the chemical binding of P1 is acquired from the mixture of (N,C)-A-S-H, C-S-H, and C-A-S-H gel products. These findings lay the groundwork for the scientific application of a wide range of waste slags in backfill engineering.
Exploring the Direct and Spillover Effects of Aging on Green Total Factor Productivity in China: A Spatial Econometric Approach
Authors: Jiang Lei , Chen Xingyu , Jiang Yang , Zhang Bo
Published: April 2023

China is a rapidly aging nation. Therefore, it is a matter of urgency to address the challenges of aging in China and to coordinate the relationships between population aging, environmental issues, and socio-economic development. However, few empirical studies have thus far analyzed the impact of aging on green total factor productivity (GTFP) in China. Hence, this study employs a global Malmquist–Luenberger index method (GMLI) to calculate the GTFP scores of 30 Chinese provinces from 2002 to 2018. We apply spatiotemporal analysis methods to identify the variations of population aging and GTFP scores and then build a spatial econometric model to examine the impact of population aging on GTFP. Our study findings are as follows. (1) Whereas at the beginning of the 21st century, provinces with deep aging were mostly situated in the east, the population aging issue in China is now spreading across the entire country. (2) From a dynamic perspective, the overall GTFP growth rate in China during the sample period depicts a U-shaped structure with time. (3) Results of the spatial Durbin model show that the impact of population aging in a given region on GTFP is negative, but the spatial spillover effect of aging in neighboring regions on GTFP in a given region is positive, resulting in the loss of younger local labor forces in some provinces due to low birth rates and migration to neighboring regions. Finally, to cope with a growing aging population and to possibly eliminate the negative impacts of population aging on high-quality sustainable development, the government should promote the establishment of the old-age security system; increased investment in R & D and wide use of advanced technology should also be urgently encouraged.
The Role of Surface Functional Groups of Iron Oxide, Organic Matter, and Clay Mineral Complexes in Sediments on the Adsorption of Copper Ions
Authors: Sun Xiao-Long , Wang Yuan , Xiong Hao-Qin , Wu Fan , Lv Tian-Xin , Fang Yi-Chuan , Xiang Hong
Published: April 2023

Heavy metal pollution is a global problem affecting the environment and human health. Sediment is the source sink of heavy metals in water. Under certain circumstances, the migration of heavy metals will cause water pollution. Therefore, it is of great significance to study sediment composition and composite complexes in the migration and transformation of heavy metals. To understand the adsorption mechanisms of composite complexes and improve the theoretical understanding of adsorption in multi-component complex systems, this study explored the characteristics and rules of Cu adsorption to organic–inorganic, inorganic minerals, and iron-oxide–clay complexes in the estuary sediments of the Dianchi Lake. The Langmuir and Freundlich isotherm models were used for Cu adsorption experiments on three complexes to study their adsorption kinetics. X-ray diffraction and Fourier transform infrared spectroscopy characterized the samples before and after adsorption. The relationship between adsorption capacity and sediment composition was analyzed through redundant analyses. The results showed that the Freundlich isothermal model was better than the Langmuir model in describing the adsorption behavior of the adsorbents. The contribution of iron and aluminum oxides to Cu adsorption was more than that of organic matter. The organic–inorganic complexes functional groups involved in copper adsorption are the most, which resulting in a higher adsorption capacity. The organic matter removal (organic degradation in sediment) will reduce the polar functional groups and reduce silicide activity, leading to heavy metal desorption and re-entry into the water body.
Mechanical Properties of Metallocene Linear Low-Density Polyethylene Mulch Films Correlate with Ultraviolet Irradiation and Film Thickness
Authors: Guo Kai , Cao Mingzhu , Gu Fengwei , Wu Feng , Yang Hongguang , Xu Hongbo , Hu Zhichao
Published: April 2023

Mulching technology has created a major problem of agricultural plastic pollution. This is because the mulch is severely degraded by UV (ultraviolet) irradiation and the mechanical properties deteriorate, which makes mechanical recycling or manual recycling difficult. This study was conducted on m-LLDPE (metallocene linear low-density polyethylene) mulch films. The difference in mechanical properties of specimens in the TD (transverse direction) and PD (parallel direction) was investigated, and the changes in the mechanical properties after UV irradiation were compared. Finally, an initial mulch mechanical property evaluation model was developed to adapt to different recovery machines and crop agronomic requirements. The results suggest that the mechanical properties of m-LLDPE mulch films were strongly influenced by the film thickness, and also showed directional differences in tensile and tear properties. After UV irradiation, the mechanical properties of the specimens were enhanced after a short period of time, but the overall trend was a non-linear decay which gradually slowed down with time.
Urban Open Therapy Gardens in EU Cities Mission: Izmir Union Park Proposal
Authors: Alakavuk Ebru , Cinar Umdu Duygu
Published: April 2023

One of the biggest problems of societies living in modern world cities is the stress brought by a fast lifestyle. Stress affects individuals psychologically, physically, and socially. With the increase in the factors that cause stress, the need for places that individuals can use as therapy areas has also increased. Especially in this period when the 2030 100 EU (European Union) Cities Mission is determined, it is very important to design urban green spaces where the environmental and social criteria of sustainability are met, as places where society can breathe and where the society gets away from stress. In this study, based on the experiential quality criteria in outdoor therapy gardens, and the results of the evaluations made by experts and users, suggestions are made to improve the conditions of Birlik Park, located in the Gaziemir district of Izmir, one of the cities selected for the 100 EU Cities Mission, and to use it as an open space therapy garden.
Cooler and Healthier: Increasing Tree Stewardship and Reducing Heat-Health Risk Using Community-Based Urban Forestry
Authors: de Guzman Edith B. , Wohldmann Erica L. , Eisenman David P.
Published: April 2023

Heat exposure poses health risks that disproportionately burden disadvantaged communities. Trees protect against heat, but significant barriers exist to growing robust urban forests. In drier climates, complex logistics of watering during a multi-year establishment period pose a challenge because street trees are typically unirrigated and funding for maintenance is generally unavailable. This study tested the impacts of varying theory-guided community engagement approaches on beliefs, attitudes, knowledge, and behaviors related to foster street tree stewardship and individual-level heat mitigation actions in 116 households in Los Angeles County, USA. We tested a control intervention against experimental messaging focused on either public health or environmental health, and also segmented participants by the degree of prior household engagement with a local tree planting group. Outcomes measured were soil moisture, tree health, and survey responses indicating benefits and barriers related to tree stewardship. Results indicate that intervention messages had limited effect on these outcomes, and that level of engagement by the tree planting group was a stronger predictor of tree stewardship. We also found that tree stewardship correlated positively to heat protection measures, suggesting that environmental engagement may be an effective portal to reducing heat risk.
Middle Class Vulnerability in China: Measurement and Determinants
Authors: Chen Xuan , Li Guoping
Published: April 2023

The middle class has become an important force in enhancing social cohesion and alleviating the polarisation between the rich and the poor. However, the extent of vulnerability in the middle class is not yet known, especially in developing countries, where a large proportion of middle-income households are still vulnerable and severely vulnerable. This study provides important insights into the middle class and the extent of their vulnerability in developing countries. Specifically, this study utilizes the Vulnerability as Expected Poverty (VEP) methodology to measure the vulnerability of middle-income class in China and analyses the relative importance of different determinants based on data from the China Family Tracking Survey (CFPS) in 2018. The main finding is that in China, only 34.5% of the population belongs to the middle-income class, with 62.3% of the middle-income population still exhibiting vulnerability. Notably, at the top of the pyramid within middle-income class, nearly half of the population is at risk for slipping into the low-income class in the future (44.3%). In addition, rural areas are particularly vulnerable (70.5%). We also found that education and household properties are decisive factors in reducing the vulnerability of the middle-income class, especially the latter, which remains a key impact on reducing household vulnerability. In addition, we further estimate heterogeneity in terms of income and household size, and the results remain robust, with a greater mitigating effect of education and household properties as household income and size increase.
Decomposition and Scenario Analysis of Factors Influencing Carbon Emissions: A Case Study of Jiangsu Province, China
Authors: Cheng An , Han Xinru , Jiang Guogang
Published: April 2023

It is crucial for China to take the characteristics and development stage of every province in the region into account in order to achieve the “dual carbon” development goal. Using data collected from 2000 to 2019, this study identifies the factors that influence carbon emissions using the logarithmic mean Divisia index (LMDI) method and establishes a revised stochastic impacts by regression on population, affluence, and technology (STIRPAT) model to investigate the effects of four key factors on carbon emissions in Jiangsu province: population size, economic output, energy intensity, and energy structure. The following conclusions were drawn: (1) energy intensity contributes to a slowed rate of carbon emission production in Jiangsu, whereas population size, economic output, and energy structure contribute to a pulling effect; (2) under different scenarios, Jiangsu’s carbon dioxide emissions peak at different times and reach different values; and (3) two low-carbon scenarios are more in line with the current development situation and future policy orientation of Jiangsu Province and are therefore better choices. Our policy recommendations are as follows: (1) the development of economic and social activities should be coordinated and greenhouse gas emissions should be reduced; (2) the province’s energy structure should be transformed and upgraded by taking advantage of the “dual carbon” development model; and (3) regionally-differentiated carbon emission reduction policies should be developed.