bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Bathymetric Inversion Capability of Different Multispectral Remote Sensing Images in Seaports
Authors: Shen Wei , Wang Jiaqi , Chen Muyin , Hao Lihua , Wu Zhongqiang
Published: January 2023

In recent years, remote sensing has become an indispensable supplementary method for determining water depth in the seaports. At present, many scholars use multi-spectral satellite data to invert the water depth of the seaports, but how to select the appropriate satellite data in the seaports area is worth exploring. In this article, the differences in the retrieving ability between domestic and foreign multispectral images are compared, through building the random forest model and the band ratio model, which use different multispectral images to conduct retrieving water depth in Nanshan Port in conjunction with the WBMS multi-beam sounding system. The band ratio model and random forest model are chosen for water depth exploration, remote sensing images use GF-6, GF-2, Sentinel-2B, and Landsat 8 OLI data, which are all popular and easily accessible. The final experiment results from the constant adjustment of the model parameter show that the domestic series of GF-6 images performed the best in this experiment. The Root Mean Square Error (RMSE) and Mean Relative Error (MRE) of the random forest model are only 1.202 and 0.187, respectively. Simultaneously, it is discovered that the ‘Red Edge’ band of GF-6 is also very helpful in improving the accuracy of water depth inversion, which is rarely mentioned in previous studies. To some extent, the preceding studies demonstrate that it is possible to investigate water depth using common multispectral remote sensing images. In the case of some bathymetry inversion models or in some waters, the aforementioned study demonstrates that it is possible to examine the water depth using domestic remote sensing images that are superior to foreign multispectral images in terms of bathymetry inversion ability.
A Novel Multi-Objective Binary Chimp Optimization Algorithm for Optimal Feature Selection: Application of Deep-Learning-Based Approaches for SAR Image Classification
Authors: Sadeghi Fatemeh , Larijani Ata , Rostami Omid , Martín Diego , Hajirahimi Parisa
Published: January 2023

Removing redundant features and improving classifier performance necessitates the use of meta-heuristic and deep learning (DL) algorithms in feature selection and classification problems. With the maturity of DL tools, many data-driven polarimetric synthetic aperture radar (POLSAR) representation models have been suggested, most of which are based on deep convolutional neural networks (DCNNs). In this paper, we propose a hybrid approach of a new multi-objective binary chimp optimization algorithm (MOBChOA) and DCNN for optimal feature selection. We implemented the proposed method to classify POLSAR images from San Francisco, USA. To do so, we first performed the necessary preprocessing, including speckle reduction, radiometric calibration, and feature extraction. After that, we implemented the proposed MOBChOA for optimal feature selection. Finally, we trained the fully connected DCNN to classify the pixels into specific land-cover labels. We evaluated the performance of the proposed MOBChOA-DCNN in comparison with nine competitive methods. Our experimental results with the POLSAR image datasets show that the proposed architecture had a great performance for different important optimization parameters. The proposed MOBChOA-DCNN provided fewer features (27) and the highest overall accuracy. The overall accuracy values of MOBChOA-DCNN on the training and validation datasets were 96.89% and 96.13%, respectively, which were the best results. The overall accuracy of SVM was 89.30%, which was the worst result. The results of the proposed MOBChOA on two real-world benchmark problems were also better than the results with the other methods. Furthermore, it was shown that the MOBChOA-DCNN performed better than methods from previous studies.
Experimental Study of Deep Submersible Structure Defect Monitoring Based on Flexible Interdigital Transducer Surface Acoustic Wave Technology
Authors: Ding Zhongjun , Feng Zhiliang , Li Hongyu , Meng Dejian , Zhang Yi , Li Dewei
Published: January 2023

In view of the shortage of structural defect monitoring methods for deep submersibles, numerical simulation and experimental research on underwater SAW propagation based on interdigital transducers are carried out in this paper. PVDF interdigital transducer (PVDF-IDT) has shown considerable potential in the application of structural health monitoring because of its micro size, soft material characteristics, and the characteristics of long-term bonding on the surface of the tested structure. In order to realize the application of IDT on submersible or underwater structures, it is necessary to understand the influence of underwater environment on IDTs with different structures. The underwater attenuation of IDT with 2–5 mm wavelength and the underwater attenuation of Lamb (A0 mode) wave on a 4 mm thick titanium alloy plate is obtained through COMSOL software simulation. The experimental verification shows that the simulation results match with the actual situation, which proves that COMSOL software can accurately calculate the acoustic attenuation of surface waves at the solid–liquid interface. At the same time, the underwater attenuation of IDT with different structures is very different, providing important design parameters for the underwater interdigital transducer. In this paper, it is found that the Lamb wave has significant advantages over the Rayleigh wave in the health monitoring of underwater thin plate structures.
AI-Driven Validation of Digital Agriculture Models
Authors: Romero-Gainza Eduardo , Stewart Christopher
Published: January 2023

Digital agriculture employs artificial intelligence (AI) to transform data collected in the field into actionable crop management. Effective digital agriculture models can detect problems early, reducing costs significantly. However, ineffective models can be counterproductive. Farmers often want to validate models by spot checking their fields before expending time and effort on recommended actions. However, in large fields, farmers can spot check too few areas, leading them to wrongly believe that ineffective models are effective. Model validation is especially difficult for models that use neural networks, an AI technology that normally assesses crops health accurately but makes inexplicable recommendations. We present a new approach that trains random forests, an AI modeling approach whose recommendations are easier to explain, to mimic neural network models. Then, using the random forest as an explainable white box, we can (1) gain knowledge about the neural network, (2) assess how well a test set represents possible inputs in a given field, (3) determine when and where a farmer should spot check their field for model validation, and (4) find input data that improve the test set. We tested our approach with data used to assess soybean defoliation. Using information from the four processes above, our approach can reduce spot checks by up to 94%.
A Novel A-ECMS Energy Management Strategy Based on Dragonfly Algorithm for Plug-in FCEVs
Authors: Li Shibo , Chu Liang , Hu Jincheng , Pu Shilin , Li Jihao , Hou Zhuoran , Sun Wen
Published: January 2023

The mechanical coupling of multiple powertrain components makes the energy management of 4-wheel-drive (4WD) plug-in fuel cell electric vehicles (PFCEVs) relatively complex. Optimizing energy management strategies (EMSs) for this complex system is essential, aiming at improving the vehicle economy and the adaptability of operating conditions. Accordingly, a novel adaptive equivalent consumption minimization strategy (A-ECMS) based on the dragonfly algorithm (DA) is proposed to achieve coordinated control of the powertrain components, front and rear motors, as well as the fuel cell system and the battery. To begin with, the equivalent consumption minimization strategy (ECMS) with extraordinary instantaneous optimization ability is used to distribute the vehicle demand power into the front and rear motor power, considering the different motor characteristics. Subsequently, under the proposed novel hierarchical energy management framework, the well-designed A-ECMS based on DA empowers PFCEVs with significant energy-saving advantages and adaptability to operating conditions, which are achieved by precise power distribution considering the operating characteristics of the fuel cell system and battery. These provide state-of-the-art energy-saving abilities for the multi-degree-of-freedom systems of PFCEVs. Lastly, a series of detailed evaluations are performed through simulations to validate the improved performance of A-ECMS. The corresponding results highlight the optimal control performance in the energy-saving performance of A-ECMS.
Tool-Wear-Estimation System in Milling Using Multi-View CNN Based on Reflected Infrared Images
Authors: Jang Woong-Ki , Kim Dong-Wook , Seo Young-Ho , Kim Byeong-Hee
Published: January 2023

A novel method for tool wear estimation in milling using infrared (IR) laser vision and a deep-learning algorithm is proposed and demonstrated. The measurement device employs an IR line laser to irradiate the tool focal point at angles of −7.5°, 0.0°, and +7.5° to the vertical plane, and three cameras are placed at 45° intervals around the tool to collect the reflected IR light at different locations. For the processing materials and methods, a dry processing method was applied to a 100 mm × 100 mm × 40 mm SDK-11 workpiece through end milling and downward cutting using a TH308 insert. This device uses the diffused light reflected off the surface of a rotating tool roughened by flank wear, and a polarization filter is considered. As the measured tool wear images exhibit a low dynamic range of exposure, high dynamic range (HDR) images are obtained using an exposure fusion method. Finally, tool wear is estimated from the images using a multi-view convolutional neural network. As shown in the results of the estimated tool wear, a mean absolute error (MAE) of prediction error calculated was to be 9.5~35.21 μm. The proposed method can improve machining efficiency by reducing the downtime for tool wear measurement and by increasing tool life utilization.
Reconstructing Roots: Emotional Drivers of Migration and Identity
Authors: Silver Alexis M.
Published: January 2023

This study examines how emotions propel migration from the United States to Mexico and subsequent migration within Mexico for young deported migrants and migrants compelled to return. Though often relegated to a second tier of importance after political or economic factors, emotions are central to the decisions that young migrants make about where to live and how to identify. I argue that emotions influence young immigrants in the U.S. to make life changing decisions to return to Mexico at moments of acute stress or uncertainty. Additionally, I argue that both compelled and deported return migrants carve out spaces of belonging and construct identities through emotional labor. Specifically, I find that young returnees draw on memories from the U.S., connections with other returnees, and imagined attachments to their ancestral cultures in Mexico as they adopt proud Mexican identities in surroundings that often mark them as outsiders on both sides of the border.
Photodegradation and Its Effect on Plant Litter Decomposition in Terrestrial Ecosystems: A Systematic Review
Authors: Hussain Mohammed Bakr , Al-Hadidi Sara H. , Erfanian Mohammad Bagher , Yahia Mohamed Nejib Daly , Mullungal Muhammed Nayeem , Alsafran Mohammed , Bai Yang , Alatalo Juha M.
Published: January 2023

Photodegradation is an important mechanism that affects carbon and nutrient cycling; a significant amount of data has been reported previously. The present review includes the effect of a wider spectrum of solar radiation (sun light, UV, and visible light) on plant litter decay in terrestrial ecosystems. Although the positive effect of photodegradation on decomposition is most common, a substantial number of studies reports contrasting results. Litter from 148 plant species, from 41 families, have been used in photodegradation studies, representing functional groups of trees (33%), graminoids (30%), shrubs (23%), forbs (11%), and peat (1%). Although the majority of studies focused on mass loss, a growing number focuses on nutrient release. Positive effects on mass loss are most common across different climate regions and laboratory studies, whereas “positive” influence and “no effect” on nitrogen and lignin release are equally common in temperate and sub-tropical environments. This may potentially be due to other decomposition processes which increase in relevance with increasing moisture and can facilitate microbial activity, leaching, and fractioning by soil fauna. In addition to climate region, initial litter quality influences photodegradation. Field-based and laboratory experiments frequently obtain contrasting results, suggesting that the mechanisms controlling the responses are unclear and might be dependent on several interactions, and/or the differences in experimental approaches (such as UV filters), or coverage by particles. Future research should focus on interactions between different factors, and on conducting experiments that test specific relationships such as the potential interaction between photodegradation, soil moisture, microbial communities, soil fauna, and their effects on litter decomposition (both mass loss and nutrient release). Furthermore, the topic would benefit from international studies applying the same experimental approach, as has successfully been conducted in other fields.
Trade Union Members’ Experiences and Attitudes towards Working from Home during the Pandemic
Authors: Debono Manwel , Garzia Christine
Published: January 2023

The pandemic increased working from home (WFH) across the world. The implications of such practice for both organisations and employees are not sufficiently clear. This study examines the work-related experiences and attitudes of trade union members WFH in Malta during the first two years of the pandemic and compares them to those of workers not WFH. Data was collected through a mixed-method approach comprising focus groups (11 participants), a survey (340 participants) and interviews (15 participants). The pandemic appears to have affected less the careers of participants WFH than those of their peers. Participants were generally satisfied with their preparedness and productivity when WFH and experienced better work-related attitudes than those not WFH. But since the pandemic started, significant minorities of participants WFH felt lower levels of happiness and higher stress levels and experienced a deterioration in their physical and/or mental health. Participants experienced differential access to WFH according to their demographics and managerial attitudes. This study recommends trade unions to promote blended work whenever possible, as this system was not only favoured by participants WFH but also appeared to carry considerable benefits for both workers and organisations.
Mathematical Modeling and A Novel Heuristic Method for Flexible Job-Shop Batch Scheduling Problem with Incompatible Jobs
Authors: Ji Bin , Zhang Shujing , Yu Samson S. , Zhang Binqiao
Published: January 2023

This paper investigates a novel flexible job-shop scheduling problem, where the machines have batch-processing capacity, but incompatible jobs cannot be processed in a batch (FJSPBI) simultaneously. This problem has wide applications in discrete manufacturing, especially in chemical and steel casting industries. For the first time, in this study, a 3-indexed mixed-integer linear programming (MILP) model is proposed, which can be efficiently and optimally solved by commercial solvers for small-scale problems. In addition, an improved large neighborhood search (LNS) algorithmic framework with an optimal insertion and tabu-based components (LNSIT) is proposed, which can achieve high-quality solutions for a large-scale FJSPBI in a reasonable time. A perturbation strategy and an optimal insertion strategy are then additionally embedded to improve the exploitation and exploration ability of the algorithm. The proposed model and algorithm are tested on numerous existing benchmark instances without the incompatibility characteristics, and on newly generated instances of the FJSPBI. The experimental results indicate the effectiveness of the proposed MILP model and the algorithm, including the proposed strategies, and the optimal insertion strategy can significantly reduce the computational burden of the LNS algorithm. The comparison results further verify that the proposed LNSIT can directly solve the specific flexible job-shop batch scheduling problem without incompatibility, with better results than existing methods, especially for large-scale instances. Additionally, the impacts of a wide range of characteristics, including batch capacity, incompatibility rate, instance scale, and machine processing rate, on the performance of the LNSIT and the scheduling results are analyzed and presented.
Evaluation of Elastic Filament Velocimetry (EFV) Sensor in Ventilation Systems: An Experimental Study
Authors: Keli Athanasia , Rahnama Samira , Hultmark Göran , Hultmark Marcus , Afshari Alireza
Published: January 2023

Determination of airflow rates is an inevitable part of the energy-efficient control of ventilation systems. To achieve efficient control, the flowmeters used must be suitably accurate and create minimum disturbance to the airflow. In this study, we evaluate the quantitative performance characteristics of an innovative micro-electromechanical systems (MEMS) flowmeter, a so-called Elastic Filament Velocimetry (EFV), in ventilation ducts. Two versions of the EFV-sensor, i.e., an 11-nanoribbon and a 22-nanoribbon variety, were evaluated in laboratory studies. The results indicate that the 11-nanoribbon sensor is more suitable for air velocity measurements in ducts than the 22-nanoribbon sensor. The 11-nanoribbon sensor can measure air velocities from 0.3 m/s. The maximum variation of the sensor-output is 3% for velocities over 0.5 m/s. Calibration models have been developed for the 11-nanoribbon sensor. The error due to model calibration is lower than ±5% for velocities over 0.6 m/s. Moreover, laboratory studies were performed to investigate the airflow disturbance in a duct system due to the EFV sensor. The results were compared with the corresponding disturbance caused by two different types of self-averaging probes. At a bulk velocity of 3 m/s, the self-averaging probes introduced a greater pressure drop by at least 50% compared to the EFV-sensor.
Improving the Heat Transfer of Phase Change Composites for Thermal Energy Storage by Adding Copper: Preparation and Thermal Properties
Authors: Trigui Abdelwaheb , Abdelmouleh Makki
Published: January 2023

Phase change materials (PCMs), as an effective thermal energy storage technology, provide a viable approach to harness solar heat, a green energy source, and optimize energy consumption in buildings. However, the obstacle preventing widespread practical use of PCM is its poor performance in terms of heat transfer and shape stabilization. This article focuses on the application of the shape stabilization method. To improve the thermal conductivity of organic PCMs (hexadecane), copper microparticles are added to form phase change composites (PCC). This process allows an enhanced PCM (75 wt%) that distributes effective thermal storage capabilities while maintaining low cost. SEM, FTIR, ATG, infrared thermography (IRT), and DSC were used to characterize the composites’ micromorphology, chemical composition, thermal degradation stability, and thermal energy storage capabilities. DSC results showed that a proportion of 75 wt% phase change material with 15 wt% Cu had excellent thermal stability and high energy storage density per unit mass. In light of its high latent heat storage capacity of 201.32 J/g as well as its ability to prevent Hexadecane exudation, PCC ensures higher thermal conductivity and shape stability during phase transition than ordinary PCM. The incorporation of Cu to paraffin causes delay in PCM phase transformation, leading it to respond to rapid charging and discharging rates and, consequentially, to challenges in temperature control, as shown by IRT. The new PCCs had favorable thermal stability below 100 °C, which was advantageous for practical application for thermal energy storage and management, and notably for solar thermal energy storage.
Green Innovation, Self-Efficacy, Entrepreneurial Orientation and Economic Performance: Interactions among Saudi Small Enterprises
Authors: Alshebami Ali Saleh
Published: January 2023

The stiff competition in the market, and continuous pressures from various stakeholders such as customers, business owners, environmental authorities, and society, in general, to produce unique products and services, protect the environment, and obtain competitive advantage continue to challenge the sustainability of enterprises in the market, especially the small ones. Accordingly, to minimize the effect of these challenges and pressures, small enterprises can improve their performance by directing their practices and processes towards developing innovative products and services that can help obtain a competitive advantage, protect the environment and better market share. Accordingly, this study aimed to explore the necessary antecedents contributing to developing innovative green products and services among small enterprises in Saudi Arabia. The study targeted a sample of 284 small entrepreneurs across various regions of Saudi Arabia. The responses were collected with a convenience sample through an online questionnaire. The data were analyzed using partial least squares structural equation modelling (PLS-SEM). The findings revealed that both green entrepreneurial self-efficacy (GESE) and green entrepreneurial orientation (GEO) have a positive relationship with green innovation (GI). The findings also reported that GI mediates the relationship between GESE, GEO and economic performance (EP).
Sustainable Digital Marketing: Factors of Adoption of M-Technologies by Older Adults in the Chinese Market
Authors: Zhang Bohan , Ying Li , Khan Muhammad Asghar , Ali Madad , Barykin Sergey , Jahanzeb Agha
Published: January 2023

A rapidly graying population has coincided with the widespread use of information technology (IT) since the turn of the 20th century. As the elderly are less familiar with IT, paying attention to the acceptance of the rapidly evolving digital marketing ecosystem is essential. Engagement with consumers and M-technologies is one of the most significant aspects of the digital marketing environment. The technology acceptance model (TAM) and the theory of planned behavior (TPB) were used to develop the theoretical framework of this study. Using technological anxiety as a moderating variable, we tested the theoretical model linking perceived value, subjective norm, effort expectancy, performance expectancy, and self-efficacy to measure older adults’ attitudes and intentions toward M-technology. Sample sizes of 251 respondents were selected with 95% confidence. To analyze the relationships between the variables proposed, structural equation modeling (SEM) was implemented. The results revealed that perceived value positively affects performance expectancy, effort expectancy, self-efficacy, subjective norm, attitude, and intention to adopt M-technology. Furthermore, technology anxiety moderated the effect of intention toward M-technology. The results explain that technology anxiety dampens the positive impact of the attitude of older adults on their intention to adopt M-technology. Managers must address this issue while developing marketing strategies for elderly consumers.
Upcycling of FGD Gypsum into a Product to Reduce Interrill Erosion: A Study Assessing Methods of Soil Surface Application
Authors: Acuña-Guzman Salvador F. , Norton L. Darrell
Published: January 2023

Soil conditioners have shown benefits in the reduction of soil erosion. A concomitant application of gypsum and polyacrylamide promotes aggregate stability and reduces the amount of runoff discharge and soil losses. Synthetic gypsum produced from flue gas desulfurization (FGD) at coalfired power plants has the potential to serve as a more sustainable source for the agricultural application of this soil conditioner. Upcycling of FGD gypsum into a pellet of a mixture of ground FGD gypsum and polyacrylamide (PAM) was compared to other types of soil surface application methods. Results confirm that surface application of PAM and FGD gypsum reduced soil erosion. Depending on the type of application method, addition of PAM and FGD gypsum presented different effects on the local hydrological processes and microtopography. Though PAM in solution acts as a physical net on the soil surface, the amount of water needed for its application makes it impractical for agricultural fields. Granular application of PAM and FGD gypsum, as well as pellets (upcycled product) has been shown to have a delayed effect in reducing soil erosion, as these methods required PAM particles to be activated. The upcycled product of FGD gypsum and PAM in the form of pellets demonstrates that the sudden expansion of the pellets due to PAM hydration results in the rapid release of the gypsum grains, providing a better treatment on the soil surface. Moreover, the increased surface area of PAM and gypsum due to the grinding is advantageous for a more rapid activation of the soil conditioners. The upcycled product of FGD gypsum and PAM is a practical application method that could be adapted by farmers to be used at field scale.
Twenty Years of Urban Reforestation: Overstory Development Structures Understory Plant Communities in Lexington, KY, USA
Authors: Sena Kenton L. , Hackworth Zachary J. , Maugans Julia , Lhotka John M.
Published: January 2023

Urban forests provide critical ecosystem services in an increasingly urbanized global landscape. The reforestation of undeveloped parcels and serially mowed grasslands can increase urban forest cover, but plant community development in planted urban forests is poorly understood. We conducted a study to elucidate the roles of time since tree planting, invasive species abundance, and other abiotic and biotic site-level factors in structuring understory plant communities within a 20-year chronosequence of planted urban forests in Lexington, KY, USA. We assessed the percent of groundcover of all understory species in fixed-radius plots on the site. Understory herbaceous plant communities demonstrated shifts from graminoid dominance to forb dominance over time, and plant communities in successively younger sites were increasingly dissimilar from that of the 20-year-old site. Invasive plant species were abundant, representing 21% of total groundcover across all surveyed plots, and became increasingly prevalent over time. Understory plant diversity was negatively associated with invasive species abundance. Overall, site factors, including time since planting, forest canopy closure, density of tree and shrub reproduction, and soil pH, accounted for much of the variability among understory communities. Understory plant communities across the chronosequence of planted sites demonstrated apparent structural shifts with overstory canopy development, but the increasing prevalence of invasive species and their negative impacts to plant diversity warrant future management to ensure the continuation of the desired successional trajectories.
Nonlinear Effects of Eco-Industrial Parks on Sulfur Dioxide and Carbon Dioxide Emissions—Estimation Based on Nonlinear DID
Authors: Xu Qunfang , Cao Kairui , Dai Jiaying , Zhu Yuanyuan , Dai Yue
Published: January 2023

Eco-industrial parks (EIPs) promote the coordination of economic development and environmental protection. This paper uses the nonlinear DID method, with the data of 288 cities spanning from 2003–2019, to study the nonlinear effects of EIPs on SO2 and CO2 emissions, aiming to portray the nonlinear and heterogeneous characteristics of EIP’s effects. Meanwhile, this paper examines the effects of EIPs more accurately and completely. The main results are as follows: 1. EIPs can significantly reduce CO2 and SO2 emissions, but there is significant heterogeneity between the effects. 2. The effect of EIPs on SO2 and CO2 emissions is nonlinear. In addition, it shows significant nonlinear characteristics as the change of foreign investment and population density in cities. Therefore, it is important to consider these nonlinear characteristics when establishing and evaluating EIPs. This paper accurately identifies the nonlinear effects of EIPs and provides some suggestions for the future development of EIPs.
The Impact of New Energy Vehicle Product Attributes on Consumer Purchase Intention in the Backdrop of Sustainable Development Goals
Authors: Wang Yueying , Tian Ying
Published: January 2023

In the backdrop of the ‘dual carbon goal’, which aims to promote sustainable development of China, adoption of new energy vehicles (NEVs) is an important measure to help improve the environment, so it is of great significance to investigate the purchase intention of NEVs. Previous studies have established that subsidies and various product attributes could affect consumers’ purchase intention toward NEVs. As government subsidies have been on the decline in recent years, product attributes of NEVs need to be given more attention. However, there have been limited studies that quantitatively analyze the impact of product attributes of NEVs on purchase intention. Therefore, to fill this gap and help further expand the NEV market, this study investigated consumers’ adoption of NEVs empirically from the perception of product attributes. A questionnaire survey and structural equation model (SEM) were used for data collection and analysis. The results indicate that (1) both the functional and symbolic attributes of NEVs had a significant positive impact on consumers’ purchase intention; (2) both the functional and symbolic attributes of NEVs had a significant positive impact on consumers’ purchase intention through consumers’ perceived value; and (3) citizens’ environmental awareness positively moderated the relationship between products attributes and purchase intention. According to the results, to meet consumers’ needs of daily driving and self-image expression, new energy vehicle enterprises need to focus on improving the products in both functional and symbolic aspects by using various marketing strategies.
A Bibliometric Analysis of Forest Gap Research during 1980–2021
Authors: Xie Jiaqi , Zhang Guangqi , Li Yuling , Yan Xiyu , Zang Lipeng , Liu Qingfu , Chen Danmei , Sui Mingzhen , He Yuejun
Published: January 2023

(1) Background: Forest gaps play an important role in promoting forest regeneration and facilitating the forest growth cycle. Since the 1980s, forest gaps have been widely studied by forestry scientists. The purpose of this study was to review the global literature from 1980 to 2021, based on the scientific database Web of Science Core Collection, and to summarize the research hotspots and the trends of the forest gaps. (2) Method: A bibliometric analysis was performed using the visual analytic software CiteSpace to quantify the description of annual publications, collaboration analysis of authors, institutions and countries, co-citation analysis of cited journals, cited authors, and cited references. The keyword co-occurrence, burst, and time zone were also analyzed by the software. (3) Results: The results show that the volume of annual publications is increasing. Dr. Harald Bugmann is the author with the most published works. The most active institution is the American Forest Service. The United States, Canada, and China are the three most productive countries. “Ecology” is the most cited journal. The results indicate that the hotspot in the forest gap research has shifted, and the effects of forest environmental changes caused by forest gaps under climate change have received more attention from scientists. In the future, more attention may be paid to the role of forest gaps on near-natural forest management patterns, the effect of forest gaps on forest sustainable development, and the way to study forest gaps using lidar technology. (4) Conclusion: Our results can help to understand emerging trends in forest gap research to inform forest ecology and management.
Novel Features and Neighborhood Complexity Measures for Multiclass Classification of Hybrid Data
Authors: Camacho-Urriolagoitia Francisco J. , Villuendas-Rey Yenny , Yáñez-Márquez Cornelio , Lytras Miltiadis
Published: January 2023

The present capabilities for collecting and storing all kinds of data exceed the collective ability to analyze, summarize, and extract knowledge from this data. Knowledge management aims to automatically organize a systematic process of learning. Most meta-learning strategies are based on determining data characteristics, usually by computing data complexity measures. Such measures describe data characteristics related to size, shape, density, and other factors. However, most of the data complexity measures in the literature assume the classification problem is binary (just two decision classes), and that the data is numeric and has no missing values. The main contribution of this paper is that we extend four data complexity measures to overcome these drawbacks for characterizing multiclass, hybrid, and incomplete supervised data. We change the formulation of Feature-based measures by maintaining the essence of the original measures, and we use a maximum similarity graph-based approach for designing Neighborhood measures. We also use ordering weighting average operators to avoid biases in the proposed measures. We included the proposed measures in the EPIC software for computational availability, and we computed the measures for publicly available multiclass hybrid and incomplete datasets. In addition, the performance of the proposed measures was analyzed, and we can confirm that they solve some of the biases of previous ones and are capable of natively handling mixed, incomplete, and multiclass data without any preprocessing needed.
The Paradigm of Circular Economy and an Effective Electronic Waste Management
Authors: Ali Saidia , Shirazi Farid
Published: January 2023

Zero waste management is a holistic concept that recognizes waste both as a resource and a measure of the inefficiency of our modern society. While the traditional waste management system considers waste an ‘end-of-life’ product consumption, zero waste challenges this notion by recognizing that waste transforms resources in the intermediate stage of the resource consumption process. In this context, the most critical aspect of creating a zero-waste city is shifting from a linear economic model to a circular economy. According to a recent study, only 9 percent of the global economy is circular (reused or recycled into products). The other 91 percent follows a linear model of making and taking waste. This study investigates the role of effective e-waste management as a crucial part of a circular economy. Accordingly, this study offers insights into the role of the circular economy by presenting a successful implementation of the circular economy.
Research on the Siting of Rural Public Cultural Space Based on the Path-Clustering Algorithm: A Case Study of Yumin Township, Yushu City, Jilin Province, China
Authors: Liu Deli , Wang Keqi
Published: January 2023

Cultural revitalization is the foundation of rural revitalization. Rural public cultural spaces are important places for rural residents to participate in cultural activities and important carriers for the occurrence, inheritance and development of rural culture. In this study, we propose a siting analysis method for public cultural spaces based on a path-clustering algorithm. Then, Yumin Township in Jilin Province is used as a case study to test the method. Within the township area, public cultural spaces are divided into three types based on the difference in service scope: “single-village decentralized”, “single-village concentration” and “multi-village concentration”. This paper focuses on the analysis of the siting of the “multi-village concentration” type of public cultural spaces using a path-clustering algorithm. First, the path-clustering algorithm is written, and then its parameters, initial clustering centers and number of clusters are analyzed for their effect on the clustering results. Two parameters, within-cluster sum of path distance (WCSPD) and maximum value of the path distance within-cluster (MPDWC), are proposed to evaluate the results of the algorithm. Then, taking Yumin Township of Jilin Province as an example, the villages in the township are clustered with travel distance as the main influencing factor. It is ensured that the shortest path distance from the central village in each cluster to other villages is no greater than the set travel distance. Finally, the public cultural space is constructed in the central village to serve all villages in the cluster. This siting analysis method can output a variety of results that can be used as a reference for decision making in rural public cultural space planning.
Visitors’ Perception Regarding Floating Treatment Wetlands in an Urban Green Space: Functionality and Emotional Values
Authors: Falfán Ina , Lascurain-Rangel Maite , Sánchez-Galván Gloria , Olguín Eugenia J. , Hernández-Huerta Arturo , Covarrubias-Báez Melissa
Published: January 2023

Floating treatment wetlands (FTW) are artificial structures used for water quality improvement through the hydroponic growth of certain macrophytes and their rhizospheric bacteria, with the capacity for pollutant removal. Through the application of face-to-face questionnaires, our study aimed to analyze visitors’ perception of the structure, functionality, and benefits of FTW installed in two ponds of one green space in Xalapa, Veracruz, Mexico, and the emotional experience that these FTW could incite in those same visitors. Visitors identified the plant component of FTW as the most noticeable one, perceived filtering/cleaning water as their principal function, and reported positive and negative emotions in the same proportion. The visitors’ perceptions of FTW varied according to their age, school level, and occupation. Positive and negative perceptions regarding FTW were linked to their maintenance and that of the ponds. Visitors’ awareness of FTW composition and function was associated with the presence of informative signs. The understanding of perception about the FTW can be integrated into management programs for the successful and participative improvement and cleaning of water bodies in urban settings. Along with people’s participation, the municipality of the city must improve the maintenance of these important water bodies given its positive repercussions on visitors’ perception.
A Multi-Analytical Approach for the Characterisation of Pigments from an Egyptian Sarcophagus Cover of the Late Dynastic Period: A Case Study
Authors: Lombardi Chiara Andrea , Comite Valeria , Fermo Paola , Bergomi Andrea , Trombino Luca , Guglielmi Vittoria
Published: January 2023

This work is concerned with a multi-analytical identification of the colour palette utilised in the decoration of the cover of an Egyptian sarcophagus dated to the Late Dynastic Period and belonging to a private collection. In this study, six different points were analysed with a portable Raman spectrometer; then, in these same points, six micro-fragments were taken from the sarcophagus for laboratory analysis performed by scanning electron microscopy coupled with energy dispersive X-ray spectroscopy (SEM-EDXS), attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) and visible induced luminescence imaging (VIL). Raman spectra collected in situ showed the characteristic bands of calcite, red ochre and black carbon. SEM-EDXS analyses highlighted the presence of a copper-based pigment in the light blue, blue and black fragments; then, the ATR-FTIR spectrum of the light blue sample only displayed the peculiar bands of Egyptian blue. The latter result was confirmed by VIL analysis, which successfully identified the same pigment in blue-black fragments as well, leading to the possible authentication of the finding. Moreover, the presence of calcite, red ochre, green earth and some organic material was assessed by FTIR spectroscopy, confirming some of the results of in situ Raman analyses. Regarding organic materials, whose investigation is still ongoing, some hypotheses were made on the basis of their FTIR spectra.
Litter Reduction during Beach Closure in the Context of the COVID-19 Pandemic: Quantifying the Impact of Users on Beach Litter Generation
Authors: Souza Filho José R. , Chagas Antônio A. S. , Silva Iracema R. , Guimarães Junia K. , Sakanaka Tania E. , Fernandino Gerson
Published: January 2023

This study aimed to quantify marine litter before and during the COVID pandemic found on urban touristic beaches closed to beachgoer access in northeastern Brazil. Litter identification and quantification was conducted during April, June, and August 2019, when 3583 items were sampled, and replicated during the same months in 2020, when access to the beaches studied was prohibited and a significant reduction in the amount of litter was found, 1812 items (49% decrease). Transects were used to monitor and classify litter according to its source, namely: autochthonous (litter that was locally discarded) and allochthonous (litter from other sites and sources). All beaches were classified as “very clean” and presented a smaller amount of litter during the beach closure period. The highest total marine litter reduction between the periods studied was 83%, while autochthonous litter in particular showed the most significant reduction, 88%. The comparison between the quantity and type of litter found in both periods showed greater specific anthropic pressure from beach users.
MSW Management to Zero Waste: Challenges and Perspectives in Belarus
Authors: Harbiankova Alena , Kalinowski Sławomir
Published: January 2023

Municipal solid waste management is one of the key challenges of environmental, economic and social importance. It is a global problem regardless of economic development level and political orientation, and also applies to a country such as Belarus. There is a lack of studies considering the local aspects of waste management in Belarus, therefore the research is actual. The study aims to formulate the recommendations on the conceptual modelling of the MSW management system in Belarus. The research methods are based on the complex systems approach. The study provides a review of the actual concepts on MSW management, including its general principles, hierarchy and methods, analysis of the current state of MSW management system in Belarus, and recommendations on modeling the MSW management system covering the local and regional aspects in Belarus. The suggestions on formulating the MSW management system involve organizational, economic, technical and informational bases as well as considering the local and regional specifics. The results indicate the following: (1) the current MSW management system in Belarus does not move the country towards a circular economy, requiring an update of the existing waste management strategy; (2) sustainable waste management demands an integrated approach in order to support waste recycling into a manufacturing resource within circular economy; (3) two main approaches to solve the problem of waste management in rural communities have been identified— an economic approach implies the minimization of waste generation while a technological approach comprises the development of mini-solutions for waste recycling at the places of waste generation. The research results contribute to the increased interest in the issue of MSW management in Belarus, and can be a useful tool for improving the planning strategies considering the local and regional context.
On-Demand Tunnel Lighting System Utilizing Daylight: A Case Study
Authors: Shi Lingna , Tu Yun , Wang Xiaoyu , He Shiyong , Bhusal Pramod , Hou Zeyu , Zhang Chaoyu
Published: January 2023

Owing to the special tubular structural characteristics of highway tunnels, drivers typically experience a significant change in visual luminance when entering tunnels, which seriously impacts driving safety. This paper proposes a lighting scheme based on optical fiber technology to introduce natural light into the tunnel portal section. First, an on-demand lighting scheme based on the use of daylight is designed by developing an optical fiber lighting system, lighting demand algorithm, and an on-demand lighting control scheme. Furthermore, the scheme is applied to a physical tunnel, and the safety and energy-saving potential of the scheme are analyzed based on the obtained data. The results indicate that the average luminance and luminance uniformity in the tunnel portal section appear to improve with the application of the proposed scheme; the luminance uniformity is particularly increased by 0.18. The correlative color temperature (CCT) of the environment inside the cave changes in real time with the CCT value of the phase pair outside the cave. Compared with the explicit use of electrical lighting, the lighting energy consumption during daytime can be reduced by 34.7% with the application of the proposed scheme, and the highest reduction of 79.8% can be achieved at 13:00.
Effects of Counter Tillage and Slope Gradient on Nutrient Losses on Sloping Farmland
Authors: Lu Shuning , Yao Chong , Wu Faqi
Published: January 2023

Counter tillage is a typical cultivation practice on the Loess Plateau, which can influence the soil erosion process by intercepting runoff and increasing infiltration. However, few studies have investigated the mechanisms of nutrient losses associated with counter tillage. This study was conducted to reveal the effects of counter tillage and slope gradient on the soil nutrient loss mechanism on sloping farmland. In this study, the rainfall simulation was conducted with a rainfall intensity of 90 mm·h−1 and with five slope gradients (5.24%, 8.75%, 17.63%, 26.79%, 36.40%). The runoff plots involved the counter tillage (CT) and traditional plow (CK), in order to investigate the characteristics of soil erosion and available phosphorus (AP), ammonium nitrogen (NH4+-N) and nitrate nitrogen (NO3−-N) losses. The soil erosion characteristics included the time until runoff generation, RR (runoff rate), and SR (sediment rate); the nutrient loss characteristics included nutrient loss concentrations, nutrient loss and nutrient loss rate in runoff or sediment. The results indicated that the RR and SR with a slope gradient of 5.24~26.79% on CT decreased by 11.77~94.92% and 20.69~99.27%, respectively, compared with that of CK. As the slope gradient increased (36.40%), a break in the ridge occurred and the reduction in the RR and SR was weakened; this was likely to be close to that of the CK. Nutrient losses differed significantly between different slope gradients and tillage practices. Nutrient losses increased with an increasing slope gradient. The nutrient losses of AP, NH4+-N, and NO3−-N in runoff, with the slope gradient of 36.40%, increased 75.75%, 76.34%, 75.63%; meanwhile, in sediment, it increased 32.93, 30.70, 32.18 times, compared with the slope gradient of 5.24% on CT. The CT with the slope gradient of 5.24~26.79% had a good effect in controlling nutrient losses; however, for the slope gradient of 36.40%, the effects of CT in controlling nutrient losses decreased. The nutrient loss rate and RR or SR satisfied a linear positive correlation. The reduction benefits of nutrient losses on CT in runoff and sediment can reach 57.7% to 100% and 45.5% to 100%, respectively. In conclusion, CT is an effective tillage practice to control soil erosion and nutrient losses. This study can provide a reference for soil erosion and nutrient loss control on sloping farmland on the Loess Plateau.