bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on the Dynamic Monitoring Technology of Road Subgrades with Time-Lapse Full-Coverage 3D Ground Penetrating Radar (GPR)
Authors: Ling Jianyu , Qian Rongyi , Shang Ke , Guo Linyan , Zhao Yu , Liu Dongyi
Published: March 2022

Road safety is important for the rapid development of the economy and society. Thus, it is of great significance to monitor the dynamic changing processes of road diseases, such as cavities, to provide a basis for the daily maintenance of roads and prevent any possible car accidents. The ground penetrating radar (GPR) technology is widely used in road disease detection due to its advantages of nondestructiveness, rapidness, and high resolution. Traditionally, one-time 2D GPR detection cannot obtain the 3D spatial changes of subgrades. Thus, we developed a road subgrade monitoring method based on the time-lapse full-coverage (TLFC) 3D GPR technique by focusing on solving the key problems of time and spatial position mismatches in experimental data. Moreover, we used the time zero consistency correction, 3D data combination, and spatial position matching methods, as they greatly improve the 3D imaging quality of underground spaces. Finally, the time-lapse attribute analysis method was used in the TLFC 3D GPR data to obtain detailed characteristics and an overall rule of the dynamic subgrade change. Overall, this research proves that TLFC 3D GPR is an optimal choice for road subgrade monitoring.
Approach towards a Holistic Management of Research Data in Planetary Science—Use Case Study Based on Remote Sensing Data
Authors: Nass Andrea , Mühlbauer Martin , Heinen Torsten , Böck Mathias , Munteanu Robert , D’Amore Mario , Riedlinger Torsten , Roatsch Thomas , Strunz Günter , Helbert Jörn
Published: March 2022

In the planetary sciences, the volume of remote sensing data and derived research products has been continuously increasing over the last five decades. The amount and complexity of data require growing sophistication in data analysis, data management, and data provision targeted at a growing research community. In order to efficiently manage and facilitate the reuse of research data and to provide stable and long-term access, sustainable research data solutions are needed. We here present a prototype for structured storage, management, and visualisation of planetary research data and discuss the particular benefits, as well as challenges of such an information system for data management, for establishing data references by cross-linking information, and for improving the visibility of data products. The prototype is a co-development of two research institutes of the German Aerospace Center (DLR) and is based on two components: the Earth Observation Center (EOC) Geoservice, which constitutes an infrastructure providing data storage and management capabilities, as well as an interface compliant with collaborative and web-based data access services, and the Environmental and Crisis Information Systems (UKIS), a framework for the implementation of geoscientific web applications.
A Multi-Stage Vessel Tracklet Association Method for Compact High-Frequency Surface Wave Radar
Authors: Sun Weifeng , Pang Zhenzhen , Huang Weimin , Ma Peng , Ji Yonggang , Dai Yongshou , Li Xiaotong
Published: March 2022

A compact high-frequency surface wave radar, used for target detection, suffers from a low signal-to-noise ratio, low detection probability, a high false alarm rate, and low positioning accuracy; this is due to its low transmit power and the reduced aperture size of the receiving antenna array. When target tracking algorithms are applied to compact high-frequency surface wave radar data, track fragmentation often occurs and a long track may be broken into several track segments (a.k.a. tracklets), which degrade the tracking continuity for a maritime surveillance system. We present a multi-stage vessel tracklet association method, based on bidirectional prediction and optimal assignment, to associate the broken tracklets belonging to the same target, and connect them to form one continuous track in a multi-target tracking scenario. Firstly, two global motion parameters, i.e., the average heading and average speed, were, respectively, extracted from the newly initiated and terminated tracklets as features for a rough tracklet association, then k-means clustering was used to produce the preliminary tracklet pairs. Subsequently, the temporal and spatial constraints on the initiated and terminated tracklets were considered to refine the preliminary tracklet pairs, to obtain the candidate tracklet pairs. Finally, the tracklet association costs were calculated using Doppler velocity, range, and azimuth to determine the similarity between tracklets in the candidate tracklet pairs, and an association cost matrix was obtained. Then an optimal assignment method based on Jonker–Volgenant–Castanon algorithm was applied to the association matrix to achieve optimal tracklet matching by minimizing the total association costs. Tracklet association experiments with both simulated and field data were conducted; experimental results show that, compared with existing track segment association methods, the association accuracy of the proposed method is significantly improved with better tracking continuity.
A Bibliometric Review of the Use of Unmanned Aerial Vehicles in Precision Agriculture and Precision Viticulture for Sensing Applications
Authors: Singh Abhaya Pal , Yerudkar Amol , Mariani Valerio , Iannelli Luigi , Glielmo Luigi
Published: March 2022

This review focuses on the use of unmanned aerial vehicles (UAVs) in precision agriculture, and specifically, in precision viticulture (PV), and is intended to present a bibliometric analysis of their developments in the field. To this aim, a bibliometric analysis of research papers published in the last 15 years is presented based on the Scopus database. The analysis shows that the researchers from the United States, China, Italy and Spain lead the precision agriculture through UAV applications. In terms of employing UAVs in PV, researchers from Italy are fast extending their work followed by Spain and finally the United States. Additionally, the paper provides a comprehensive study on popular journals for academicians to submit their work, accessible funding organizations, popular nations, institutions, and authors conducting research on utilizing UAVs for precision agriculture. Finally, this study emphasizes the necessity of using UAVs in PV as well as future possibilities.
Interference Management with Reflective In-Band Full-Duplex NOMA for Secure 6G Wireless Communication Systems
Authors: Khan Rabia , Tsiga Nyasha , Asif Rameez
Published: March 2022

The electromagnetic spectrum is used as a medium for modern wireless communication. Most of the spectrum is being utilized by the existing communication system. For technological breakthroughs and fulfilling the demands of better utilization of such natural resources, a novel Reflective In-Band Full-Duplex (R-IBFD) cooperative communication scheme is proposed in this article that involves Full-Duplex (FD) and Non-Orthogonal Multiple Access (NOMA) technologies. The proposed R-IBFD provides efficient use of spectrum with better system parameters including Secrecy Outage Probability (SOP), throughput, data rate and secrecy capacity to fulfil the requirements of a smart city for 6th Generation (6thG or 6G). The proposed system targets the requirement of new algorithms that contribute towards better change and bring the technological revolution in the requirements of 6G. In this article, the proposed R-IBFD mainly contributes towards co-channel interference and security problem. The In-Band Full-Duplex mode devices face higher co-channel interference in between their own transmission and receiving antenna. R-IBFD minimizes the effect of such interference and assists in the security of a required wireless communication system. For a better understanding of the system contribution, the improvement of secrecy capacity and interference with R-IBFD is discussed with the help of SOP derivation, equations and simulation results. A machine learning genetic algorithm is one of the optimization tools which is being used to maximize the secrecy capacity.
DFT-Net: Deep Feature Transformation Based Network for Object Categorization and Part Segmentation in 3-Dimensional Point Clouds
Authors: Sheikh Mehak , Asghar Muhammad Adeel , Bibi Ruqia , Malik Muhammad Noman , Shorfuzzaman Mohammad , Mehmood Raja Majid , Kim Sun-Hee
Published: March 2022

Unlike 2-dimensional (2D) images, direct 3-dimensional (3D) point cloud processing using deep neural network architectures is challenging, mainly due to the lack of explicit neighbor relationships. Many researchers attempt to remedy this by performing an additional voxelization preprocessing step. However, this adds additional computational overhead and introduces quantization error issues, limiting an accurate estimate of the underlying structure of objects that appear in the scene. To this end, in this article, we propose a deep network that can directly consume raw unstructured point clouds to perform object classification and part segmentation. In particular, a Deep Feature Transformation Network (DFT-Net) has been proposed, consisting of a cascading combination of edge convolutions and a feature transformation layer that captures the local geometric features by preserving neighborhood relationships among the points. The proposed network builds a graph in which the edges are dynamically and independently calculated on each layer. To achieve object classification and part segmentation, we ensure point order invariance while conducting network training simultaneously—the evaluation of the proposed network has been carried out on two standard benchmark datasets for object classification and part segmentation. The results were comparable to or better than existing state-of-the-art methodologies. The overall score obtained using the proposed DFT-Net is significantly improved compared to the state-of-the-art methods with the ModelNet40 dataset for object categorization.
A Gaussian Process State Space Model Fusion Physical Model and Residual Analysis for Fatigue Evaluation
Authors: Yin Aijun , Zhou Junlin , Liang Tianyou
Published: March 2022

Residual stress is closely related to the evolution process of the component fatigue state, but it can be affected by various sources. Conventional fatigue evaluation either focuses on the physical process, which is limited by the complexity of the physical process and the environment, or on monitored data to form a data-driven model, which lacks a relation to the degenerate process and is more sensitive to the quality of the data. This paper proposes a fusion-driven fatigue evaluation model based on the Gaussian process state–space model, which considers the importance of physical processes and the residuals. Through state–space theory, the probabilistic space evaluation results of the Gaussian process and linear physical model are used as the hidden state evaluation results and hidden state change observation function, respectively, to construct a complete Gaussian process state–space framework. Then, through the solution of a particle filter, the importance of the residual is inferred and the fatigue evaluation model is established. Fatigue tests on titanium alloy components were conducted to verify the effectiveness of the fatigue evaluation model. The results indicated that the proposed models could correct evaluation results that were far away from the input data and improve the stability of the prediction.
MmWave Radar and Vision Fusion for Object Detection in Autonomous Driving: A Review
Authors: Wei Zhiqing , Zhang Fengkai , Chang Shuo , Liu Yangyang , Wu Huici , Feng Zhiyong
Published: March 2022

With autonomous driving developing in a booming stage, accurate object detection in complex scenarios attract wide attention to ensure the safety of autonomous driving. Millimeter wave (mmWave) radar and vision fusion is a mainstream solution for accurate obstacle detection. This article presents a detailed survey on mmWave radar and vision fusion based obstacle detection methods. First, we introduce the tasks, evaluation criteria, and datasets of object detection for autonomous driving. The process of mmWave radar and vision fusion is then divided into three parts: sensor deployment, sensor calibration, and sensor fusion, which are reviewed comprehensively. Specifically, we classify the fusion methods into data level, decision level, and feature level fusion methods. In addition, we introduce three-dimensional(3D) object detection, the fusion of lidar and vision in autonomous driving and multimodal information fusion, which are promising for the future. Finally, we summarize this article.
gRDF: An Efficient Compressor with Reduced Structural Regularities That Utilizes gRePair
Authors: Sultana Tangina , Lee Young-Koo
Published: March 2022

The explosive volume of semantic data published in the Resource Description Framework (RDF) data model demands efficient management and compression with better compression ratio and runtime. Although extensive work has been carried out for compressing the RDF datasets, they do not perform well in all dimensions. However, these compressors rarely exploit the graph patterns and structural regularities of real-world datasets. Moreover, there are a variety of existing approaches that reduce the size of a graph by using a grammar-based graph compression algorithm. In this study, we introduce a novel approach named gRDF (graph repair for RDF) that uses gRePair, one of the most efficient grammar-based graph compression schemes, to compress the RDF dataset. In addition to that, we have improved the performance of HDT (header-dictionary-triple), an efficient approach for compressing the RDF datasets based on structural properties, by introducing modified HDT (M-HDT). It can detect the frequent graph pattern by employing the data-structure-oriented approach in a single pass from the dataset. In our proposed system, we use M-HDT for indexing the nodes and edge labels. Then, we employ gRePair algorithm for identifying the grammar from the RDF graph. Afterward, the system improves the performance of k2-trees by introducing a more efficient algorithm to create the trees and serialize the RDF datasets. Our experiments affirm that the proposed gRDF scheme can substantially achieve at approximately 26.12%, 13.68%, 6.81%, 2.38%, and 12.76% better compression ratio when compared with the most prominent state-of-the-art schemes such as HDT, HDT++, k2-trees, RDF-TR, and gRePair in the case of real-world datasets. Moreover, the processing efficiency of our proposed scheme also outperforms others.
Signal Detection for GSTFIM Systems with Carrier Frequency Offset
Authors: Wu Tingyong , Fan Shiwen , Di Chengliang , Ji Jinwei
Published: March 2022

Generalized space-time-frequency index modulation (GSTFIM) inherits the drawbacks of the conventional orthogonal frequency-division multiplex (OFDM), such as being sensitive to carrier frequency offset (CFO). For a robust design against this problem, in this contribution, a novel construction of a message passing (MP)-aided detector is developed for GSTFIM systems to combat the influence of CFO, while offering a flexible tradeoff between transmission performance and computational complexity. Through complexity analysis and simulation results, we demonstrate that, in the context of CFO, with a careful design, the developed MP detector is capable of approaching traditional GSTFIM with maximum likelihood (ML) detection, and of offering better performance at lower complexity compared to its minimum mean-square-error (MMSE)-aided counterpart.
Analysis of Electromagnetic Properties of New Graphene Partial Discharge Sensor Electrode Plate Material
Authors: Zhang Huiyuan , Wu Zhensheng
Published: March 2022

Advanced sensing and measurement technology is the key to realizing the transparent power grid and electric internet of things. Meanwhile, sensors, as an indispensable part of the smart grid, can monitor, collect, process, and transmit various types of data information of the power system in real-time. In this way, it is possible to further control the power system. Among them, partial discharge (PD) sensors are of great importance in the fields of online monitoring of insulation condition, intelligent equipment control, and power maintenance of power systems. Therefore, this paper intends to focus on advanced sensing materials and study new materials for the improvement for partial discharge sensors. As two-dimensional material, graphene is introduced. The electromagnetic properties of graphene partial discharge sensor electrode plate material are analyzed theoretically. By studying the influence of different chemical potential, relaxation time, temperature, and frequency, we obtain the changing curve of conductivity, dielectric constant, and refractive index. A linear regression model based on the least-squares method was developed for the three electromagnetic properties. Finally, the simulation and experiment verified that the graphene partial discharge sensor has better absorption of the partial discharge signal. This study can apply to the design of graphene partial discharge sensors.
Feature Extraction of the Brain’s Dynamic Complex Network Based on EEG and a Framework for Discrimination of Pediatric Epilepsy
Authors: Liang Zichao , Chen Siyang , Zhang Jinxin
Published: March 2022

Most of the current complex network studies about epilepsy used the electroencephalogram (EEG) to directly construct the static complex network for analysis and discarded the dynamic characteristics. This study constructed the dynamic complex network on EEG from pediatric epilepsy and pediatric control when they were asleep by the sliding window method. Dynamic features were extracted and incorporated into various machine learning classifiers to explore their classification performances. We compared these performances between the static and dynamic complex network. In the univariate analysis, the initially insignificant topological characteristics in the static complex network can be transformed to be significant in the dynamic complex network. Under most connectivity calculation methods between leads, the accuracy of using dynamic complex network features for discrimination was higher than that of static complex network features. Particularly in the imaginary part of the coherency function (iCOH) method under the full-frequency band, the discrimination accuracies of most machine learning classifiers were higher than 95%, and the discrimination accuracies in the higher-frequency band (beta-frequency band) and the full-frequency band were higher than that of the lower-frequency bands. Our proposed method and framework could efficiently summarize more time-varying features in the EEG and improve the accuracies of the discrimination of the machine learning classifiers more than using static complex network features.
Experimental Research on Vibration-Damping Effect of Combined Shear Hinge Prefabricated Steel Spring Floating Slab Track
Authors: Zeng Zhiping , Huang Xudong , Li Zhuang , Wang Weidong , Shi Zixiao , Yuan Yu , Shuaibu Abdulmumin Ahmed
Published: March 2022

Objective: The cast-in-place steel spring floating slab track (SSFST) is difficult to maintain and repair, while the mechanical strength of the end of the traditional prefabricated SSFST is poor. In order to overcome the above shortcomings, a shear-hinge-combined prefabricated SSFST was developed, and an indoor test was carried out to analyze its vibration-damping effect. Methods: A combined shear hinge SSFST connection model with two length sizes was established. The dynamic response amplitude and frequency response characteristics of the foundation (ground) under different isolator installations and fatigue loads were studied, and the vibration-damping performance of two sizes of combined shear hinge SSFST was evaluated. Results: The vibration-damping effect of the steel spring vibration isolator mainly acts in the middle and low-frequency bands of 16–400 Hz, and the vibration near 10 Hz will be aggravated after the vibration isolator is installed. The vibration index and variation law of the two sizes of SSFST are similar, and the vibration response of 4.8 m SSFST is slightly less than 3.6 m SSFST. There is almost no change in each index when the load is 5 million times, and there is a certain range of change when the load is 10 million times, but the overall change is small. Conclusions: The combined shear hinge prefabricated SSFST can have an excellent isolation effect on vibration and can still maintain good vibration-damping ability within 10 million fatigue loads (about 5 years); 4.8 m SSFST should be laid in straight sections with higher train speeds, while 3.6 m SSFST should be applied in curved sections to ensure smooth lines.
Effects of Altitude, Plant Communities, and Canopies on the Thermal Comfort, Negative Air Ions, and Airborne Particles of Mountain Forests in Summer
Authors: Wang Rui , Chen Qi , Wang Dexiang
Published: March 2022

Forest bathing is considered an economical, feasible, and sustainable way to solve human sub-health problems caused by urban environmental degradation and to promote physical and mental health. Mountain forests are ideal for providing forest baths because of their large area and ecological environment. The regulatory mechanism of a mountain forest plant community in a microenvironment conducive to forest bathing is the theoretical basis for promoting physical and mental health through forest bathing in mountain forests. Based on field investigations and measurements, differences in the daily universal thermal climate index (UTCI), negative air ion (NAI), and airborne particulate matter (PM2.5 and PM10) levels in nine elevation gradients, six plant community types, and six plant community canopy parameter gradients were quantitatively analyzed. In addition, the correlations between these variables and various canopy parameters were further established. The results showed the following: (1) Altitude had a significant influence on the daily UTCI, NAI, PM2.5, and PM10 levels in the summer. The daily UTCI, NAI, PM2.5, and PM10 levels gradually decreased with the increase in altitude. For every 100 m increase in altitude, the daily UTCI decreased by 0.62 °C, the daily NAI concentration decreased by 108 ions/cm3, and the daily PM2.5 and PM10 concentrations decreased by 0.60 and 3.45 µg/m3, respectively. (2) There were significant differences in the daily UTCI, NAI, PM2.5, and PM10 levels among different plant communities in the summer. Among the six plant communities, the Quercus variabilis forest (QVF) had the lowest daily UTCI and the best thermal comfort evaluation. The QVF and Pinus tabuliformis forest (PTF) had a higher daily NAI concentration and lower daily PM2.5 and PM10 concentrations. (3) The characteristics of the plant community canopy, canopy density (CD), canopy porosity (CP), leaf area index (LAI), and sky view factor (SVF), had significant effects on the daily UTCI and NAI concentration, but had no significant effects on the daily PM2.5 and PM10 concentrations in the summer. The plant community with higher CD and LAI, but lower CP and SVF, showed a higher daily UTCI and a higher daily NAI concentration. In conclusion, the QVF and PTF plant communities with higher CD and LAI but lower CP and SVF at lower elevations are more suitable for forest bathing in the summer in mountainous forests at lower altitudes. The results of this study provide an economical, feasible, and sustainable guide for the location of forest bathing activities and urban greening planning to promote people’s physical and mental health.
Modeling and Evaluating Beneficial Matches between Excess Renewable Power Generation and Non-Electric Heat Loads in Remote Alaska Microgrids
Authors: Bolt Grace , Wilber Michelle , Huang Daisy , Sambor Daniel J. , Aggarwal Srijan , Whitney Erin
Published: March 2022

Many Alaska communities rely on heating oil for heat and diesel fuel for electricity. For remote communities, fuel must be barged or flown in, leading to high costs. While renewable energy resources may be available, the variability of wind and solar energy limits the amount that can be used coincidentally without adequate storage. This study developed a decision-making method to evaluate beneficial matches between excess renewable generation and non-electric dispatchable loads, specifically heat loads such as space heating, water heating and treatment, and clothes drying in three partner communities. Hybrid Optimization Model for Multiple Electric Renewables (HOMER) Pro was used to model potential excess renewable generation based on current generation infrastructure, renewable resource data, and community load. The method then used these excess generation profiles to quantify how closely they align with modeled or actual heat loads, which have inherent thermal storage capacity. Of 236 possible combinations of solar and wind capacity investigated in the three communities, the best matches were seen between excess electricity from high-penetration wind generation and heat loads for clothes drying and space heating. The worst matches from this study were from low penetrations of solar (25% of peak load) with all heat loads.
Eco-Efficiency Analysis of Integrated Waste Management Strategies Based on Gasification and Mechanical Biological Treatment
Authors: Abdeljaber Abdulrahman , Zannerni Rawan , Masoud Wedad , Abdallah Mohamed , Rocha-Meneses Lisandra
Published: March 2022

Integrated solid waste management (ISWM) strategies are developed towards promoting sustainable approaches for handling waste. Recently, gasification and mechanical biological treatment (MBT) technologies were recognized as effective processes for treating municipal solid waste. This study investigates the feasibility of integrating gasification and MBT technologies in multiple ISWM strategies, compared to incineration- and anaerobic digestion (AD)-based strategies. A comprehensive techno-economic and environmental assessment was carried out to evaluate the performance of the examined ISWM strategies. The evaluation was based on the energy generation potential, carbon footprint, and life cycle costing (LCC). An eco-efficiency analysis was conducted to quantify the environmental costs by incorporating the carbon footprint and LCC results. The proposed strategies were applied for the city of Abu Dhabi, United Arab Emirates, based on local bylaws and guidelines. The analysis revealed that the gasification-based strategy had the highest energy production of 47.0 million MWh, followed by the incineration- (34.2 million MWh), AD- (17.2 million MWh), and MBT-based (14.9 million MWh) strategies. Results of the environmental analysis indicated that the MBT- and AD-based strategies contributed the least to global warming with greenhouse gas emissions of 4442 and 4539 GgCO2-eq, respectively, compared to the gasification- (9922 GgCO2-eq) and incineration-based (15,700 GgCO2-eq) strategies. Furthermore, over a 25-year assessment period, the LCC findings demonstrated that the gasification- and MBT-based strategies were the most financially feasible with a positive net present value (NPV) of USD 364 and USD 284 million, respectively. The eco-efficiency analysis indicated that the MBT and gasification strategies are the most sustainable among the examined strategies. The sustainability of the assessed systems was improved by implementing policy and legal reforms, including incentive programs, less stringent bylaws on digestate, and encouraging source separation of wastes. Overall, this research emphasized the potential environmental and financial benefits of incorporating MBT and gasification technologies into ISWM strategies.
Exploring the Spatial Correlation Network Structure of Green Innovation Efficiency in the Yangtze River Delta, China
Authors: Wang Keliang , Bian Yajing , Cheng Yunhe
Published: March 2022

Green innovation is crucial to high-quality economic development and has become an important engine for green transformation development in the Yangtze River Delta region. In this study, we used the super epsilon-based measure (super-EBM) to measure the green innovation efficiency of 26 cities in the Yangtze River Delta region of China from 2003 to 2018. Secondly, on the basis of a modified gravity model, we determined the spatial correlation of the Yangtze River Delta region’s green innovation efficiency and built a relation matrix. Finally, using the Moran index, centrality analysis, and a block model, we investigated its spatial characteristics and empirically analyzed its influencing factors by applying the quadratic assignment procedure. The results show that (1) in spatial terms, the Yangtze River Delta’s green innovation efficiency is extremely unbalanced, and the spatial network association density is low, only 0.218; (2) in terms of block analysis, the green innovation efficiency of the Yangtze River Delta region’s cities can be divided into four blocks, with distinct blocks holding distinct responsibilities; and (3) in terms of influencing factors, geographic distance; the expansion of the difference in energy consumption and the environment pollution index; and narrowing the gap in economic development, the industrial structure, and green coverage will push forward the formation of spatial correlation at a significance level of 10%. Our findings expand the research on traditional innovation efficiency and provide theoretical guidance for formulating regional green innovation coordinated development policy. It is necessary to strengthen urban green innovation cooperation in the Yangtze River Delta and promote regional integrated development. Different policies should be adopted for cities with different spatial correlation patterns. From the perspective of block analysis, it is necessary to balance the acceptance relationship and spillover relationship between cities. In addition, to improve the spatial correlation of green innovation efficiency in the Yangtze River Delta, the allocation of green innovation resources in the Yangtze River Delta should be optimized.
Natural Treatment Systems and Importance of Social Cost Benefit Analysis in Developing Countries: A Critical Review
Authors: De Indranil , Hasan Rooba , Iqbal Mubashshir
Published: March 2022

This review article attempts to analyse the social issues that impact the performance of natural treatment systems (NTSs). An NTS is a decentralised wastewater treatment system found to be appropriate in developing countries due to its affordability and lower technicity. However, if socio-economic and institutional issues of community are ignored then NTSs may turn out to be unsuitable for developing countries. The article also takes a critical view on the extant literature which ignores the social cost of NTSs. The social cost of NTSs may be high as a decentralised system requires the engagement of various governmental agencies, research institutes and the community. The cost of engagement may make NTSs a socio-economically unattractive proposition. The article discusses the variables to be considered for the social cost-benefit analysis. It also discusses the implications of social cost-benefit analysis for appreciating the incentives and net benefits for collective actions at the community level. Social cost-benefit analysis can help overcome the initial difficulty of high financial cost and usher sustainability.
Students’ Attitude and Perception towards Sustainability: The Case of Universiti Sains Malaysia
Authors: Syed Azhar Sharifah Nurlaili Farhana , Mohammed Akib Noor Adelyna , Sibly Suzyrman , Mohd Saidatulakmal
Published: March 2022

Sustainability awareness is a vital component in ensuring sustainability initiatives as a global effort for the benefit of future generations, particularly in countries with emerging economies, such as Malaysia. In higher education institutions (HEIs), students play an important role in manifesting the sustainability agenda to the campus community, as well as the rest of the globe. However, there is a scarcity of data on Malaysian students’ attitudes and perceptions towards sustainability. The purpose of this research is to establish a baseline for determining the level of positive attitude and perception among USM undergraduate students in regards to sustainability. A survey using a self-administered questionnaire via Google Forms was conducted with 513 undergraduate students between June 2020 and March 2021. The findings revealed that the students’ level of positive attitude and perceptions of sustainability on campus ranged from moderate to high. The study also observed a strong, positive correlation between students’ attitude and perception. The present study illustrated that “Attitudes Towards Sustainability on Campus” helps to explain 45% of the variance in respondents scores on “Perception of the USM Current Sustainability Program”. It could be summarized that USM students were able to relate sustainability issues to current situations and assumed a positive attitude towards the implementation of sustainability programs at USM. It is intended that the research findings will contribute background information that will reflect the strategies of higher education institutions on sustainability.
Does Innovation Climate Help to Effectiveness of Green Finance Product R&D Team? The Mediating Role of Knowledge Sharing and Moderating Effect of Knowledge Heterogeneity
Authors: Ding Xue , Li Wei , Huang Dujuan , Qin Xinghong
Published: March 2022

Green finance innovation has received emerging attention from the finance industry in recent years; however, few studies have explored the internal mechanisms that link innovation climate to a green finance R&D team’s effectiveness. Using data from 65 teams that belong to green finance industries, collected via the questionnaire survey, we explore how innovation climate positively affects knowledge sharing, and both innovation climate and knowledge sharing can improve the effectiveness of the green finance R&D team. We also find that knowledge sharing mediates the relationship between innovation climate and a green finance R&D team’s effectiveness and that knowledge heterogeneity moderates the relationship between knowledge sharing and team effectiveness. Based on these findings, this study contributes to providing useful recommendations for professional managers and policymakers to effectively promote the development of the green finance industry.
Analysis of Start-Up Digital Mental Health Platforms for Enterprise: Opportunities for Enhancing Communication between Managers and Employees
Authors: Truong Hang , McLachlan Craig Steven
Published: March 2022

The COVID-19 pandemic has resulted in employees being exposed to transformational stressors from within and outside the organization. This has created an opportunity for employee mental health solutions. Indeed, there has been a rapid growth in start-ups offering clinical mental health services via a digital health platform. These platforms servicing enterprise employee mental health needs have not been evaluated with respect to their ability to enhance management communication. Hence, the aims of the present study are to explore communication and service attributes across a sample of five operational leading commercial start-up platforms for mental service delivery to employees. We have observed that all platform models focused on providing on-demand mental health consultation services. Existing platforms fail to adequately support management communication for mental health solutions across 80% of platforms reviewed. We recommend that industry start-ups should understand the need for management engagement with digital mental health platforms. Digital mental health platform solutions in the workplace are ideally supported by valuing leadership communication. A culture around mental health will create sustainability in digital mental health solutions for an organization.
Influence of Tropical Cyclones on Outdoor Wind Environment in High-Rise Residential Areas in Zhejiang Province, China
Authors: Zhang Hua , Xiong Minghui , Chen Bing , Wang Yanfeng
Published: March 2022

Tropical cyclones can cause tremendous harm to coastal areas. This research aims to explore the influence of tropical cyclones on outdoor wind environments in high-rise residential areas in the southeast coastal provinces of China, using Zhejiang Province as an example. It investigated four cities located in Zhejiang Province, including Taizhou and Wenzhou representing coastal cities, and Huzhou and Jiaxing representing inland cities, and collected data from 209 high-rise residential areas. Of these 209 samples, 131 high-rise residential areas with three typical spatial layouts (i.e., rows-style, free-style, and courtyard-style) have been selected for further studies. Numerical simulation was conducted to analyze the outdoor wind environment of these three types of high-rise residential areas, where the height of buildings was set as 26 floors (75 m), during tropical cyclones. Based on a comparison of the wind velocity at the horizontal planes of 1.5 m high and 10 m high, it was found that the spatial layouts of high-rise residential areas could mitigate the negative impact of tropical cyclones on the outdoor wind environment. Specifically, in the coastal cities, the courtyard-style layout led to a relatively small proportion of high wind speed areas (e.g., wind velocity above 14.4 m/s) in the high-rise residential areas; and in the inland cities, the free-style layout led to a relatively small proportion of high wind speed area in the high-rise residential area. In turn, to better cope with the tropical cyclones, it was suggested that the courtyard-style layout should be recommended for high-rise residential areas located in the coastal cities and the free-style layout should be recommended for high-rise residential areas located in the inland cities in coastal provinces.
Quantitative Assessment of Architectural Lighting Designs
Authors: Skarżyński Krzysztof , Żagan Wojciech
Published: March 2022

There has recently been a great interest in the outdoor lighting that is energy-efficient and does not intensify a light pollution phenomenon. In architectural lighting, these demands are difficult to implement and rarely analyzed. However, it is possible to introduce and use certain parameters based on the utilization factor for the quantitative assessment of floodlighting design in terms of both light pollution and energy efficiency. This paper presents the definitions of new parameters and the results of their calculations for several typical architectural objects. Different lighting concepts were created for each object together with appropriate computer simulations. The research shows a high potential for usefulness of new parameters in the design process. The floodlighting utilization factor is characterized by relatively low values of around 35%. In addition, obtaining the recommended lighting power density value below 2.2 W/m2 does not sufficiently determine the correctness of the design implementation considering the natural environment. This determines a great potential for opportunities to improve the implemented designs and provides a basis for redefining the currently used approach in architectural lighting. In order to create high-quality, sustainable solutions, all quantitative parameters should be analyzed simultaneously in addition to the esthetic visual effect issue.
Well-Being and Entrepreneurship Intention: An Empirical Study of New Perspectives
Authors: Contreras-Barraza Nicolás , Acuña-Duran Eduardo , Oyanedel Juan Carlos , Salazar-Sepúlveda Guido , Vega-Muñoz Alejandro , Ariza-Montes Antonio
Published: March 2022

The research aims to examine the relationships between the constructs of entrepreneurial intention according to the theory of planned behavior (TPB) model and subjective well-being (SW). The model used considers the works proposed by Liñán and Chen and Oyanedel, Vargas, and Paez, and a questionnaire was applied to 1043 people in an urban population of the three main regions of Chile using multivariate statistical methods for its analysis (structural equation models). The proposed hypotheses are that subjective well-being towards entrepreneurship has a direct and positive effect on entrepreneurial intention (H1), personal attitude towards entrepreneurship has a direct and positive effect on entrepreneurial intention (H2), perceived behavioral control towards entrepreneurship has a direct and positive effect on entrepreneurial intention (H3), and subjective norm towards entrepreneurship has a direct and positive effect on entrepreneurial intention (H4). The results indicate that subjective well-being on entrepreneurial intention shows indirect effects mediated by subjective norm, contributing to the theoretical development concerning well-being incidence on entrepreneurial behavior, providing theoretical elements that can serve as a basis for further strengthening the understanding of the relationships between personal well-being, economic growth, and the harmonious relationship with the environment.
Compliance with Building Energy Code for the Residential Sector in Egyptian Hot-Arid Climate: Potential Impact, Difficulties, and Further Improvements
Authors: GamalEldine Mennaallah , Corvacho Helena
Published: March 2022

Building energy codes are considered to be an effective policy tool for energy reduction worldwide. However, their application and effectiveness are still limited in developing countries. In Egypt, the residential sector is promising for energy savings, as most of the existing residential buildings are aged with low thermal performance and non-conformance with energy codes. This study aims to raise the awareness of promoting the Egyptian residential energy codes among construction parties, especially end-users, by quantifying the environmental impacts, in terms of energy savings and thermal comfort enhancement. Moreover, it attempts achieving a nearly zero energy building by integrating several energy-efficient measures with renewable energy sources. Thus, in this study, a typical residential building in Cairo was chosen for simulation. The simulation results revealed that applying energy code instructions for building envelope, lighting enhancement and increases in cooling set-points, from 24 °C to 25 °C, saved 37.85% of annual electrical energy and resulted in a cooling reduction of 50.53%. Furthermore, the photovoltaic system incorporation succeeded in transforming the building into a nearly zero energy building. Concerning thermal comfort, the application of passive energy-efficient measures significantly influences indoor thermal comfort, with a 30% reduction in discomfort hours during the cooling season, which represents the main concern in hot climate regions.
Reckoning with Reality: Reflections on a Place-Based Social Innovation Lab
Authors: Geobey Sean
Published: March 2022

This is a reflection upon a social innovation lab process used to establish and build an ongoing culture of sustainability (COS) within a new multi-tenant commercial office building. It seeks to answer two key questions: (1) what are the design tensions that emerge when constructing co-design processes meant to encourage social innovation in a complex system while working from inside that complex system; (2) in building commons governance structures in a complex system, what are realistic expectations for the voluntary participation when multiple organizations with different core mandates are involved? This paper’s primary results come from reflecting upon the COS development coming from the social innovation lab process and adaptations process needed for it to work within a place-based context. The COS intervention itself is still in process and was disrupted by COVID-19, so these findings are still preliminary. Participatory co-design research often involves a great deal of complexity and tacit knowledge, so the key finding here is the surfacing of four core sources of tension that arise when developing a co-design process for the management of a commons: the allocation of costs for co-ordinating collective action, balancing a homogeneous platform for action with heterogeneous participants, physical building infrastructure and social co-design approaches, and between-tenant organization leadership and co-design approaches. This paper’s key contribution is in clarifying core challenges that participatory process designers face when developing and implementing co-design processes.
Does Internet Use Aggravate Public Distrust of Doctors? Evidence from China
Authors: Meng Lingpeng , Yu Xiang , Han Chuanfeng , Liu Pihui
Published: March 2022

The internet has exacerbated the spillover of medical information, and changes in the quantity, quality, and scope of information supply also affect public trust in doctors, which is of great significance to the construction of a harmonious physician–patient relationship. The objective of this study is to explore the relationship between internet use and residents’ trust in doctors using data from the China Family Panel Studies for 2018. The empirical investigation utilizes an endogenous switching regression model (ESR) to overcome the endogeneity bias. Our results indicate that internet use is negatively associated with residents’ trust in doctors (β = 0.07, p < 0.05). Specifically, the patient trust of internet users is nearly 7 percent less than that of non-internet users. Nevertheless, residents with higher dependence on traditional media such as television, newspapers, magazines and radio as an information channel show stronger patient trust. Finally, the results of the subsample analysis indicate a need to focus on older and less-educated residents, who are more vulnerable and more likely to be affected.
Non-Thermal Fixed Points in Bose Gas Experiments
Authors: Madeira Lucas , Bagnato Vanderlei S.
Published: March 2022

One of the most challenging tasks in physics has been understanding the route an out-of-equilibrium system takes to its thermalized state. This problem can be particularly overwhelming when one considers a many-body quantum system. However, several recent theoretical and experimental studies have indicated that some far-from-equilibrium systems display universal dynamics when close to a so-called non-thermal fixed point (NTFP), following a rescaling of both space and time. This opens up the possibility of a general framework for studying and categorizing out-of-equilibrium phenomena into well-defined universality classes. This paper reviews the recent advances in observing NTFPs in experiments involving Bose gases. We provide a brief introduction to the theory behind this universal scaling, focusing on experimental observations of NTFPs. We present the benefits of NTFP universality classes by analogy with renormalization group theory in equilibrium critical phenomena.
Mining Critical Metals from Seawater by Subnanostructured Membranes: Is It Viable?
Authors: Buonomenna Maria Giovanna
Published: March 2022

The continuous demand for energy-critical elements such as lithium, cobalt, uranium and so on will soon exceed their availability increasing further their significance of geopolitical resources. Seawater is a relevant, not conventional source of critical metals. Synthetic membranes with subnanometer pores are the core of processes such as desalination for separating solutes from water. These membrane processes have achieved remarkable success at industrial level. However, state-of-the-art desalination membranes cannot selectively separate a single metal ion from a mixture of ions. In this review the challenges of membranes with subnanometer pores to selectivity discriminate among different metal ions are briefly discussed. The key points of the molecular-level mechanism that contribute to energy barrier for ions transport through subnanometer pores are highlighted to provide guidelines for the design of single-metal ion selective membranes.