bluuebunny/crossref_metadata_2025 huggingface dataset:
Automatic Detection and Identification of Defects by Deep Learning Algorithms from Pulsed Thermography Data
Authors: Fang Qiang , Ibarra-Castanedo Clemente , Garrido Iván , Duan Yuxia , Maldague Xavier
Published: May 2023

Infrared thermography (IRT), is one of the most interesting techniques to identify different kinds of defects, such as delamination and damage existing for quality management of material. Objective detection and segmentation algorithms in deep learning have been widely applied in image processing, although very rarely in the IRT field. In this paper, spatial deep-learning image processing methods for defect detection and identification were discussed and investigated. The aim in this work is to integrate such deep-learning (DL) models to enable interpretations of thermal images automatically for quality management (QM). That requires achieving a high enough accuracy for each deep-learning method so that they can be used to assist human inspectors based on the training. There are several alternatives of deep Convolutional Neural Networks for detecting the images that were employed in this work. These included: 1. The instance segmentation methods Mask–RCNN (Mask Region-based Convolutional Neural Networks) and Center–Mask; 2. The independent semantic segmentation methods: U-net and Resnet–U-net; 3. The objective localization methods: You Only Look Once (YOLO-v3) and Faster Region-based Convolutional Neural Networks (Fast-er-RCNN). In addition, a regular infrared image segmentation processing combination method (Absolute thermal contrast (ATC) and global threshold) was introduced for comparison. A series of academic samples composed of different materials and containing artificial defects of different shapes and nature (flat-bottom holes, Teflon inserts) were evaluated, and all results were studied to evaluate the efficacy and performance of the proposed algorithms.
Research on the Modulation Transfer Function Detection Method of a Bayer Filter Color Camera
Authors: Fan Yuan-Peng , Wei Lei , Li Lin , Yang Lin , Hu Zi-Qiang , Zheng Yuan-Hao , Wang Yu-Hao
Published: May 2023

Bayer filter color cameras are more and more widely used in the field of aerospace remote sensing, but the Bayer filter causes great degradation in image quality; therefore, obtaining a means of achieving the high-precision measurement of the modulation transfer function (MTF) of Bayer filter color cameras is an urgent problem. In order to solve this problem, this paper develops a slanted-edge method via three steps: the detection of the slanted edge, the acquisition and processing of the edge spread function (ESF), and the acquisition and processing of the line spread function (LSF). A combination of the Canny operator and Hough transform is proposed for the detection of the slanted edge, which improves the fitting accuracy and anti-interference ability of the algorithm. Further, the Canny operator is improved by constructing an adaptive filter function and introducing the Otsu method, which can more effectively smooth the image and remove its false edges. A method of processing ESF data by combining cubic spline interpolation and Savitzky–Golay (SG) filtering is proposed, which reduces the effects of noise and the non-uniform sampling of ESF on MTF. A method of LSF processing using Gaussian function fitting is proposed to further reduce the effect of noise on MTF. The improved algorithm is verified by the MTF measurement test applied to a specific type of Bayer filter color space camera. The simulation and test results show that the improved slanted-edge method discussed in this paper has greater precision and a better anti-interference ability, and it can effectively solve the difficult problem associated with MTF detection in Bayer filter color space cameras.
Characterization of the Tunisian Phosphate Rock from Metlaoui-Gafsa Basin and Bio-Leaching Assays
Authors: Messai Boutheina , Taieb Ines , Ben Younes Sonia , Lartiges Bruno , Ben Salem Ezzedine , Ellafi Ali
Published: April 2023

Soil contamination by heavy metals through the application of a phosphate fertilizer is a key issue for sustainable agriculture. Among contaminants, cadmium (Cd) is considered the most hazardous to human beings’ health and the surrounding environment. X-ray diffraction (XRD), combined with binocular mineralogical analysis and chemical analysis, was used to determine the C(I) and C(II) layers’ composition. In the C(II) (+71 µm)-size fraction, the presence of carbonate-fluorapatite, illite, and montmorillonite was revealed, whereas in the C(I) (−71 µm)-size fraction, carbonate-fluorapatite, calcite, quartz, sanidine, clinoptilolite, and taramovite were identified. The P2O5 and CaO contents were greater in the C(II) layer than that in the C(I) layer, whereas SiO2, MgO, CO2, Cd, Zn, and COrg were higher in the C(I) layer than that in the C(II) layer. The bioleaching of Cd from phosphate rock samples from the Kef Eddour deposit was investigated using three bacterial strains isolated from the local phosphate environment. A decrease in cell viability was noticed when the phosphate C(I) and C(II) samples showed toxicity in the samples. In addition, the isolated bacteria, which were initially moderately hydrophobic, changed to strongly hydrophobic. The use of the consortium (S1 + S2 + S3) was the most powerful combination to reduce the Cd content, which increased from 13.31% to 29.07% using S3 and the consortium (S1 + S2 + S3), respectively, when the C(II) (+71 µm)-size fraction sample was added to the medium. The same result was shown when the C(I) (−71 µm)-size fraction sample was used. The isolated strains could be used as a biological tool for bioleaching.
Use of Artificial Intelligence in Terms of Open Innovation Process and Management
Authors: Kuzior Aleksandra , Sira Mariya , Brożek Paulina
Published: April 2023

Organizations see open innovation as important to their future growth strategy. The increasing interest in artificial intelligence has led to a heightened interest in its potential applications in many industries. Many firms invest heavily in artificial intelligence intending to innovate their business models, though managers often lack understanding when trying to implement artificial intelligence in their operations. The data was retrieved from the Scopus database and was analyzed using the R Bibliometrix Biblioshiny and VOSviewer software. The aim of the article is to indicate the consistency in the formation of open innovation processes while applying artificial intelligence and to provide the profile of perspectives on artificial intelligence adoption in innovation management. This paper provides a deeper perception of artificial intelligence and how it can be used to drive open innovation processes and business model innovation within the use of artificial intelligence in open innovation processes and artificial intelligence in the management of open innovation. The authors discuss how recent advances in artificial intelligence have created new opportunities for increased external collaboration. The study found that the rise of artificial intelligence as a key technology for promoting openness and collaboration has ushered in a new era of achievable open innovation. Our presented findings suggest the sequence of open innovation processes powered by artificial intelligence and insights into the artificial intelligence application to innovation management.
Intellectual Capital, Firm Performance, and Sustainable Growth: A Study on DSE-Listed Nonfinancial Companies in Bangladesh
Authors: Sohel Rana Md. , Hossain Syed Zabid
Published: April 2023

Intellectual Capital (IC) stimulates corporate competitive advantages that can enhance firm performance and sustainable growth (SG). This study investigates IC’s affinity with and impact on accounting and market performance and SG of listed nonfinancial companies in Bangladesh. Data were collected from 69 nonfinancial companies for five years during 2017–2021, forming 345 observations. Modified Value Added Intellectual Coefficient (MVAIC) and steady-state models consecutively measured IC efficiency and Sustainable Growth Rate (SGR). The Robust fixed effect model was applied to confirm the highest reliable results. Results of MVAIC, Intellectual Capital Efficiency (ICE), and Human Capital Efficiency (HCE) showed a positive affinity with and impact on firm performance and SGR. Structural Capital Efficiency (SCE) showed an insignificant association with and impact on explained variables, whereas Relational Capital Efficiency (RCE) showed a significant negative relationship with and impact on the same. Tangible capital employed efficiency (CEE) enhanced firm performance but failed to confirm sustainable growth. The findings help business executives, government, and policymakers formulate strategic plans for sustainable resource utilization and can create value, competitive edges, and survival for firms. The study recommends that corporate entities should strive to enhance their efficiency in internal structural resources and relational activities to achieve better firm performance and sustainable growth.
Satisfaction on the Driving Seat: Exploring the Influence of Social Media Marketing Activities on Followers’ Purchase Intention in the Restaurant Industry Context
Authors: Anas Ashraf Mohamed , Abdou Ahmed Hassan , Hassan Thowayeb H. , Alrefae Wael Mohamed Mahmoud , Daradkeh Fathi Mohammed , El-Amin Maha Abdul-Moniem Mohammed , Kegour Adam Basheer Adam , Alboray Hanem Mostafa Mohamed
Published: April 2023

Recently, social media marketing has become an effective tool for restaurants to gain visibility, increase customer engagement, and boost sales. Through social media marketing activities (SMMAs) including customization (CUST), entertainment (ENTR), trendiness (TRND), and interaction (INTR), restaurants can connect with their customers in a dynamic way that may affect their satisfaction and purchasing behavioral intention. Hence, this study primarily aims to empirically explore the individual influence of SMMAs namely CUST, ENTR, TRND, and INTR on social media followers’ satisfaction and purchase intention in a sample of casual-dining restaurants in Saudi Arabia. Furthermore, drawing on the Stimulus-Organism-Response (S-O-R) model, we also seek to investigate the influence of customer satisfaction as a mediating variable in the relationship between CUST-PI, ENTR-PI, TRND-PI, and INTR-PI. Furthermore, to examine the direct influence of CS on PI. In order to meet these objectives, an online survey was created to collect data from a convenience sample of restaurant social media followers. Data from 415 followers were analyzed using the PLS-SEM with a bootstrapping technique to confirm the research hypotheses. The findings of the study illustrated the significant positive effect of CUST, ENTR, and INTR on followers’ purchase intention, respectively. Trendy social media marketing activities did not significantly affect purchase intention. Additionally, CS partially mediated the relationships between CUST, ENTR, INTR, and PI but fully mediated the trendiness-purchase intention relationship. The results from this research can assist restaurant operators to leverage the benefits of social media more effectively by understanding how SMMAs influence customers’ purchase intentions and enhancing their understanding of how customer satisfaction can be used to capitalize on the benefits of social media.
Geospatial Visualization and Ecological Risk Assessment of Heavy Metals in Rice Soil of a Newly Developed Industrial Zone in Bangladesh
Authors: Akter Mahmuda , Kabir Mohammad Humayun , Alam Mohammad Ashraful , Al Mashuk Hammadullah , Rahman Mohammad Mizanur , Alam Mohammad Saiful , Brodie Graham , Islam S. M. Mofijul , Gaihre Yam Kanta , Rahman Golum Kibria Muhammad Mustafizur
Published: April 2023

With rapid industrialization in Gazipur areas of Bangladesh, untreated industrial effluents have been polluting rice soils which could exert potential ecological risk. Therefore, four different types of industries including chemical (SL), textile and paints (MIX), dyeing (CK), and sweater and dyeing (RD) were selected to monitor the intensity of heavy metal pollution in rice soils and ecological risk assessment. The di-acid digestion method was used for the determination of Pd, Cd, and Ni, and the DTPA extraction method was used for Fe, Zn, and Cu. ArcGIS was used to visualize the spatial patterns of heavy metal pollution, and different pollution indices were calculated to assess the ecological risk. The highest concentration (mg kg−1) of Cd (0.72), Pb (104.20), and Ni (5.02) was found in soils of the MIX industrial area. The highest concentration (mg kg−1) of Fe (147.65) and Zn (11.27) was found in the SL industry, while the highest Cu (7.67) was found in the CK industry. It was evident from the spatial distribution that the soils of paddy fields adjacent to the different industries are more contaminated than background soil. Although the potential ecological risk of heavy metal was low, different pollution indices indicated low to high pollution. Thus, the adjacent rice field soil of different industries is being contaminated by different heavy metals which may raise ecological risk.
Spatiotemporal Dynamic Characteristics and Causes of China’s Population Aging from 2000 to 2020
Authors: Zhang Xiaodong , Han Haoying
Published: April 2023

Aging involves the transformation of the population reproduction mode under the rapid development of the social economy. We studied population survey data based on the WorldPop population statistics website and used ArcGIS to construct a spatial database and implement spatial analysis methods. In this study, we analyzed the spatiotemporal evolution characteristics of population aging and its main influencing factors in counties of China, in order to provide a reference for the formulation of a national population development policy and the construction of a pension system. The results are as follows: ① The situation of population aging in China is becoming more serious, showing a point-line-area spatial pattern and two core–periphery aging patterns of high core–low periphery and low core–high periphery. ② The speed of population aging in China is characterized by rapid growth, large scale, and a high degree. Large areas of growing old before getting rich have emerged in the central and western regions. ③ The aging of the population has gradually spread to the northeast, southwest, northwest, and other regions. Influenced by factors such as population migration, population structure change, transportation facility construction, and geographic environment changes, a trend of aging that has spread across the Hu Huan-Yong line has appeared.
Hybrid Multichannel-Based Deep Models Using Deep Features for Feature-Oriented Sentiment Analysis
Authors: Ahmad Waqas , Khan Hikmat Ullah , Iqbal Tasswar , Khan Muhammad Attique , Tariq Usman , Cha Jae-hyuk
Published: April 2023

With the rapid growth of user-generated content on social media, several new research domains have emerged, and sentiment analysis (SA) is one of the active research areas due to its significance. In the field of feature-oriented sentiment analysis, both convolutional neural network (CNN) and gated recurrent unit (GRU) performed well. The former is widely used for local feature extraction, whereas the latter is suitable for extracting global contextual information or long-term dependencies. In existing studies, the focus has been to combine them as a single framework; however, these approaches fail to fairly distribute the features as inputs, such as word embedding, part-of-speech (PoS) tags, dependency relations, and contextual position information. To solve this issue, in this manuscript, we propose a technique that combines variant algorithms in a parallel manner and treats them equally to extract advantageous informative features, usually known as aspects, and then performs sentiment classification. Thus, the proposed methodology combines a multichannel convolutional neural network (MC-CNN) with a multichannel bidirectional gated recurrent unit (MC-Bi-GRU) and provides them with equal input parameters. In addition, sharing the information of hidden layers between parallelly combined algorithms becomes another cause of achieving the benefits of their combined abilities. These abilities make this approach distinctive and novel compared to the existing methodologies. An extensive empirical analysis carried out on several standard datasets confirms that the proposed technique outperforms the latest existing models.
Analysis of Urban Ecological Quality Spatial Patterns and Influencing Factors Based on Remote Sensing Ecological Indices and Multi-Scale Geographically Weighted Regression
Authors: Yang Pan , Zhang Xinxin , Hua Lizhong
Published: April 2023

With the acceleration of urbanization, problems such as urban ecological environment quality have become increasingly prominent. How to scientifically analyze and evaluate the spatial pattern of urban ecological environment changes and influential variables is a prerequisite for achieving green development and ecological priority new in urban planning. Our study was conducted on Pingtan Island, located in Fujian Province, China. First, we selected Landsat 8 OLI images in 2013, 2017, and 2021. Second, we extracted the remote sensing ecological index (RSEI) from these images and created RSEI maps to assess the spatial-temporal variations and spatial autocorrelation of the ecological environment condition in Pingtan Island. Third, the proportion of land-use types, road, and population density were selected as independent variable factors, RSEI as the dependent variable, least squares regression (OLS), geographically weighted regression (GWR), and multi-scale geographically weighted regression (MGWR) were used to establish global and local regression models. According to the regression coefficients of the model and its spatial distribution, the spatial heterogeneity between the ecological environment and the influencing factors was assessed. The results indicated that: (1) the mean value of the RSEI increased from 0.422 to 0.504 during 2013–2021, indicating that the overall ecological environment improved. (2) Based on the global Moran’s I value, the distribution of ecological environment quality was positively correlated. The local Moran’s I cluster map showed that the high-high cluster gradually extended to the northwest high-altitude region. Low-low clustering gradually extended to the more populous areas in the southeast. (3) The Radj2 of the MGWR model was 0.866, which was better than the results of the OLS model and GWR model, indicating that MGWR had obvious advantages in revealing the spatial heterogeneity between the ecological environment and the influencing factors. Importantly, the results indicate that population density, road density, and the proportion of cropland land and impervious surface in land-use types have varying degrees of negative effects on the urban ecological environment, with the impervious surface being more severe, followed by population density, while forest land in land-use types shows significant positive effects.
Spatial Characteristics and Influencing Factors of the Coupling and Coordination of High-Quality Development in Eastern Coastal Areas of China
Authors: Yuan Dan , Guo Jiapei , Zhu Chuangeng
Published: April 2023

China’s pursuit of sustainable and healthy economic growth requires the promotion of high-quality development. While many scholars have studied high-quality development, few have examined the coupling and coordination among its internal systems. The study aims to analyze the influencing factors of high-quality coordinated development, identify problem areas based on the five development statuses, and provide practical recommendations for optimizing the spatial layout of high-quality development in these areas. By applying a coupling coordination model and a geographically weighted regression model, the comprehensive level of high-quality coordinated development in the eastern coastal areas was evaluated. The results revealed that the majority of the eastern coastal region exhibited weak coordination and significant spatial differences in their comprehensive level. The problem cities were predominantly located in the southern and northern coastal areas. An economic foundation and innovation potential have a positive and stable impact on high-quality coordinated development.
Promoting Rural Regeneration and Sustainable Farming near Cities Thanks to Facilitating Operators in France? The Case of the Versailles Plain’s Association Governance Model
Authors: Robert-Boeuf Camille
Published: April 2023

Food and agricultural systems in rural areas close to cities have been the subject of much academic research, revealing difficulties due to the proximity of cities, land pressure, and complex governance between cities and rural areas. This article aims to analyze the case study of the Versailles Plain Association (VPA), which proposes an original form of facilitation that contributes to the effectiveness of territorial governance in a rural area close to Paris. It is based on a qualitative method, gathering 52 interviews and heritage audits that were carried out in the framework of the European project H2020 Ruralization. The analysis shows that the VPA is a facilitating operator that brings together stakeholders from both the agricultural and urban worlds, allowing collective projects around a territorial identity. This territorial identity promotes agriculture and rural lifestyles, which become positive embodiments of local development. This facilitating operator thus offers an alternative to urbanization and produces forms of ruralization processes.
Stability-Level Evaluation of the Construction Site above the Goaf Based on Combination Weighting and Cloud Model
Authors: Wang Liang , Guo Qingbiao , Yu Xuexiang
Published: April 2023

Mineral resource-based cities have formed a large number of goafs due to the long-term mining of coal. It is of great significance to make full use of the abandoned land resources above the goaf to promote the transformation and development of resource-based cities. In order to avoid the threat of surface residual deformation to the proposed construction project, it is an urgent problem to obtain the stability results of the construction site accurately. First of all, based on the principles of relevance, hierarchy, representativeness and feasibility of index selection, 10 indexes are selected to construct the stability evaluation index system. Then the subjective weight and objective weight of evaluation indexes are determined based on improved AHP, rough set and CRITIC methods, which improves the accuracy of the determination of the index weights. In addition, the membership degree of each index is determined using the cloud model. Finally, the stability grade can be obtained according to the maximum membership degree theory. The above researches are applied to evaluate the stability of the Mianluan expressway construction site, and the results show that the stability level of the study area is not uniform and that there are two states: stable and basically stable. Finally, a sensitivity analysis of the subjective weight of each index is carried out, the index stopping time has the highest sensitivity to weight (12.44%), which is far lower than the corresponding weight change rate of 100%, indicating that the determination of weight is scientific and reasonable. These things considered, the reliability of the evaluation result is indirectly verified according to the field leveling. This research can provide a reference for the effective utilization of land resources above an old goaf.
The Game Analysis among Governments, the Public and Green Smart Supply Chain Enterprises in Necessity Purchase and Supply during COVID-19 Pandemic
Authors: Xu Ruzhi , Yan Chenglong , Wang Chenlong , Zhao Huawei
Published: April 2023

During the COVID-19 pandemic, panic buying, price inflation, and the pollution of production processes led to economic and social unrest. In response to the current situation, the current research takes less account of the subjective perception of public panic buying and the lack of reference to the reality of effective governance. First, this paper uses prospect theory to portray the public’s perceived value of goods in panic buying and non-panic buying situations. Then, drawing on the experience of effective governance in China, a tripartite evolutionary game model of local government, the public and green smart supply chain enterprises is constructed under the reward and punishment mechanism of the central government. Then, this paper analyzes the strategic choices of each game player and the stability of the system equilibrium. The structure of the study suggests the following. (1) Improving local government subsidies and penalties, the cost of positive response and the probability of response can lead to an evolutionary direction where the public chooses not to panic buy and green smart supply chain enterprises choose to ensure a balance between supply and demand and increase pollution control in the production process. (2) Our study yields three effective combinations of evolutionary strategies, of which an ideal combination of evolutionary strategies exists. Non-ideal evolutionary strategy combinations can occur due to improper incentives and penalties of local governments and misallocation of limited resources. However, we find four paths that can transform the non-ideal evolutionary strategy combination into an ideal evolutionary strategy combination. (3) The central government’s reward and punishment mechanism is an important tool to stabilize the tripartite strategy, but the central government cannot achieve effective governance by replacing incentives with punishment.
Mapping Provincial Stocks and Wastes of Passenger-Vehicle Plastics in China Based on Dynamic Material Flow Analysis and GIS: 1985–2019
Authors: Chen Youliang , Quan Yingxiang , Karimian Hamed , Yang Xuexi
Published: April 2023

As a polymer material, plastic is widely used in passenger vehicles for its light weight and low-cost advantages. China has accumulated a large amount of discarded automotive plastic in recent years, which has put increasing pressure on the environment and the recycling industry. A dynamic material flow model for estimating the plastic stock and waste in passenger vehicles was developed. Additionally, geospatial models were used to study the spatiotemporal evolution trend of passenger vehicle plastics. The results show: (1) passenger-vehicle plastic stock and waste in China increased rapidly from 1985 to 2019. By 2019, the passenger-vehicle plastic stock was 36.94 million tons, and the waste amount was 1.64 million tons, of which polypropylene accounted for the greatest proportion, and polyoxymethylene (POM) accounted for the least. (2) The stock and waste of passenger-vehicle plastics showed spatial dependency. (3) The spatial center of plastic waste was located in Henan Province, and the spatial center is shifting from north to south. (4) The GDP and the annual population are the main driving factors of passenger-vehicle plastic waste. This study will improve plastic waste management, resource recovery, and environmental sustainability decisions.
A New Type of Mineral Admixture and Its Impact on the Carbonation Resistance of EPS Concrete
Authors: He Haijie , Wang Yuxuan , Yuan Ji , Xu Ke , Wang Shifang , Qiao Hongxia , Wu Tao , Yang Jie , Liu Junding , Yu Jing , Wang Bin
Published: April 2023

In this study, the effect of microbead dosages (0%, 5%, 10%, 15%, and 20%) on the carbonation resistance of expanded polystyrene (EPS) concrete was investigated. Five groups of EPS concrete specimens were produced and underwent rapid carbonation testing. The carbonation depth and strength after carbonation of the specimens were measured at different carbonation ages (7 days, 14 days, and 28 days) and analyzed to determine the effect of microbead dosages and compressive strength on carbonation resistance. Results indicated that the carbonation depth increased with the progression of carbonation time. The introduction of microbeads was found to significantly improve the carbonation resistance of EPS concrete, leading to a reduction in carbonation depth of over 50% after 28 days and an increase in strength after carbonation by 18–56%. A relative compressive strength model for EPS concrete after carbonation was developed, which could accurately characterize the growth of compressive strength. Based on the analysis of EPS concrete carbonation depth data, a prediction model for the carbonation depth of EPS concrete with microbead dosage was established through fitting, providing improved accuracy in predicting carbonation resistance. The microstructure of EPS concrete was also examined using scanning electron microscopy to uncover the underlying mechanisms of microbead enhancement on carbonation resistance. These findings have potential implications for future research and engineering applications in the carbonation resistance of EPS concrete.
A Bibliometric Analysis of Augmented Reality in Language Learning
Authors: Min Wenhe , Yu Zhonggen
Published: April 2023

As an emerging technology, augmented reality has been increasingly entering the educational field. Previous studies of AR are strongly associated with scientific education but lack the mention of language learning. This study aimed to analyze the use of AR tools in language learning contexts using the bibliometric tools VOSviewer and CitNetExplorer using both qualitative and quantitative research methods. This study analyzed the top ten authors, sources, countries, and organizations using VOSviewer and established citation networks using CitNetExplorer. The study found that both teachers and students showed a positive attitude toward AR tools in language learning. Games, 3D images, and videos are the main ways to instantiate virtual elements into the real world, and the most widely used tool in AR-assisted learning was HP Reveal. Moreover, the study also found that AR tools could enhance language learning by presenting an immersive learning context, increasing motivation, providing interaction, and reducing anxiety. Future research will contribute to how AR tools influence students’ learning performance and teachers’ teaching activities.
Research on Real-Time Prediction of Hydrogen Sulfide Leakage Diffusion Concentration of New Energy Based on Machine Learning
Authors: Tang Xu , Wu Dali , Wang Sanming , Pan Xuhai
Published: April 2023

China’s sour gas reservoir is very rich in reserves, taking the largest whole offshore natural gas field in China-Puguang gas field as an example, its hydrogen sulfide content reaches 14.1%. The use of renewable energy, such as solar energy through photocatalytic technology, can decompose hydrogen sulfide into hydrogen and monomeric sulfur, thus realizing the conversion and resourceization of hydrogen sulfide gas, which has important research value. In this study, a concentration sample database of a hydrogen sulfide leakage scenario in a chemical park is constructed by Fluent software simulation, and then a leakage concentration prediction model is constructed based on the data samples to predict the hydrogen sulfide leakage diffusion concentration in real-time. Several machine learning algorithms, such as neural networks, support vector machines, and deep confidence networks, are implemented and compared to find the model algorithm with the best prediction performance. The prediction performance of the support vector machine model optimized by the sparrow search algorithm is found to be the best. The prediction model ensures the accuracy of the prediction results while greatly reducing the computational time cost, and the accuracy meets the requirements of practical engineering applications.
Impact of Wood Ash and Sewage Sludge on Elemental Content in Hybrid Alder Clone
Authors: Bertins Maris , Paiste Paarn , Makovskis Kristaps , Ansone-Bertina Linda , Busa Lauma , Lazdina Dagnija , Lazdins Andis , Kirsimäe Kalle , Klavins Maris , Viksna Arturs
Published: April 2023

In this study, the focus was on evaluating the effects of the initial treatment of wood ash and sewage sludge on hybrid alder clones’ aboveground biomass and elemental content. To measure the element concentrations in the tree rings, laser ablation–inductively coupled plasma–mass spectrometry (LA-ICP-MS) was utilized, which is a valuable tool for dendrochemistry research, albeit with some challenges in accurate quantification. One important aspect of the study was the development and comparison of different “in-house” matrix-matched standards for the precise quantification of element concentrations in tree rings. It was found that the commercially available reference materials, IAEA 413 (algae) and IAEA 392 (algae), were the best choices due to their homogeneity. The study also revealed that the use of sewage sludge and wood ash as soil improvers significantly benefited the increase in hybrid alder biomass. However, no significant increase in element content was found in the obtained wood mass, and for some elements, there was a decrease in concentration.
Challenges and Opportunities in the Use of Nature-Based Solutions for Urban Adaptation
Authors: Castelo Sofia , Amado Miguel , Ferreira Filipa
Published: April 2023

The concept of nature-based solutions (NbS) has been endorsed by multiple international organizations as one of the priority approaches to address climate-related challenges. These solutions are versatile, and can simultaneously address challenges such as climate impacts, public health, inequality, and the biodiversity crisis, being uniquely suited for urban adaptation. NbS are particularly relevant in the developing world, where strategies should be as self-reliant as possible, reducing the need for technological processes that require expensive and complex maintenance. NbS can also promote political, societal, cultural, and ultimately, systems change. The purpose of this paper is to present a literature review on the use of NbS for urban adaptation, identifying the main opportunities, challenges, and, most specifically, knowledge gaps, which can be addressed in subsequent research. The present paper identifies four types of knowledge gaps that are particularly relevant for the use of NbS for urban adaptation: future climate uncertainty, lack of site-specific technical design criteria, governance strategies, and effectiveness assessment evaluation. To overcome local governments’ limitations, specific implementation strategies and structures should be considered, centered on knowledge transfer within a transdisciplinary and participatory framework. These should be developed in partnership with urban planning entities, seeking to consolidate these approaches in policies that support social resilience and institutional capacity. Therefore, urban adaptation should be initiated with pilot projects to simultaneously address the urgency for implementation, while allowing urban planning practices the time to adjust, building capacity at the local level, and filling knowledge gaps through the assessment of effectiveness. The climate-resilience of urban tree species adequate to the future climate was identified as a relevant knowledge gap for the implementation of NbS.
Assessing Critical Road Sections: A Decision Matrix Approach Considering Safety and Pavement Condition
Authors: Angelo Asnake Adraro , Sasai Kotaro , Kaito Kiyoyuki
Published: April 2023

Identifying critical road sections that require prompt attention is essential for road agencies to prioritize monitoring, maintenance, and rehabilitation efforts and improve overall road conditions and safety. This study suggests a decision matrix with a hierarchical structure that factors in the pavement deterioration rate, infrastructure safety, and crash history to identify these sections. A Markov mixed hazard model was used to assess each section’s deterioration rate. The safety of the road sections was rated with the International Road Assessment Program star rating protocol considering all road users. Early detection of sections with fast deterioration and poor safety conditions allows for preventive measures to be taken and to reduce further deterioration and traffic crashes. Additionally, including crash history data in the decision matrix helps to understand the possible causes of a crash and is useful in developing safety policies. The proposed method is demonstrated using data from 4725 road sections, each 100 m, in Addis Ababa, Ethiopia. The case study results show that the proposed decision matrix can effectively identify critical road sections which need close attention and immediate action. As a result, the proposed method can assist road agencies in prioritizing inspections, maintenance, and rehabilitation decisions and effectively allocate budgets and resources.
A Novel Green Ocean Strategy for Financial Sustainability (GOSFS) in Higher Education Institutions: King Abdulaziz University as a Case Study
Authors: Al-Filali Isam Y. , Abdulaal Reda M. S. , Melaibari Ammar A.
Published: April 2023

Financing education has recently been a big concern since educational expenditure continues to rise. As a result, there will be a gradual shift away from the “unilateral approach” to funding and toward the “diversification of financing resources”. The aim of this paper is to propose an innovative strategy plan to optimize universities’ investment sources and maintain their financial sustainability. This approach was known as the Green Ocean Strategy for Financial Sustainability (GOSFS). To effectively implement GOSFS in higher education institutions, a roadmap of 18 steps is constructed around three primary key performance areas (resource development, good governance, and regulations and legislation). The GOSFS was applied within four successive stages at King Abdulaziz University as a case study. With 18 pillars found under these three key performance areas, a long-term target for 2045 and an overall goal for 2025 were defined. In addition, the paper created novel versions of the Business Model Canvas to meet the GOSFS plan concept. To effectively employ GOSFS, four recommendations are offered to accelerate business growth and engage the university investment ecosystem, including whether to invest in highly qualified human capital, expand financial resources, or leverage technical resources. Future directions are also provided.
A Simulation Approach for the Design of More Sustainable and Resilient Supply Chains in the Pharmaceutical Industry
Authors: Silva Ana Carolina , Marques Catarina Moreira , de Sousa Jorge Pinho
Published: April 2023

In a world facing unprecedented challenges, such as climate changes and growing social problems, the pharmaceutical industry must ensure that its supply chains are environmentally sustainable and resilient, guaranteeing access to key medications even when faced with unanticipated disruptions or crises. The core goal of this work is to develop an innovative simulation-based approach to support more informed and effective decision making, while establishing reasonable trade-offs between supply chain robustness and resiliency, operational efficiency, and environmental and social concerns. Such a decision-support system will contribute to the development of more resilient and sustainable pharmaceutical supply chains, which are, in general, critical for maintaining access to essential medicines, especially during times of crises or relevant disruptions. The system will help companies to better manage and design their supply chains, providing a valuable tool to achieve higher levels of resilience and sustainability. The study we conducted has two primary contributions that are noteworthy. Firstly, we present a new advanced approach that integrates multiple simulation techniques, allowing for the modeling of highly complex environments. Secondly, we introduce a new conceptual framework that helps to comprehend the interplay between resiliency and sustainability in decision-making processes. These two contributions provide valuable insights into understanding complex systems and can aid in designing more resilient and sustainable systems.
China’s Incentives and Efforts against IUU Fishing in the South China Sea
Authors: Yu Chengyong , Chang Yen-Chiang
Published: April 2023

Illegal, unreported, and unregulated (IUU) fishing is a massive problem that poses a significant threat to the sustainability of marine ecosystems and the livelihoods of millions of people who depend on fishing for their food and income. Many issues have emerged, such as declining fishery resources, regional fishery incidents, political impacts, and disputes over sovereignty, which all have mutual and complicated effects on IUU fishing, eventually hindering the sustainability of marine fisheries. In this situation, the People’s Republic of China (hereinafter referred to as China) has tried to undertake some efforts to combat IUU fishing over the past few years using domestic regulation and international cooperation, especially in the South China Sea. This article discusses the seriousness of IUU fishing; examines the causes of IUU fishing in the South China Sea; analyzes why frequent fishing conflicts have increased in the South China Sea; identifies what IUU fishing is, based on its definition in the International Plan of Action to Prevent, Deter and Eliminate Illegal, Unreported and Unregulated Fishing (IPOA-IUU) and in other countries; and examines what actions have been undertaken to prevent IUU fishing in China from international and national perspectives. By analyzing the cause of IUU fishing, identifying its scope and nature, and demonstrating China’s position on it, this study aims to prove that China has taken some positive measures to combat IUU fishing in the South China Sea. To promote the sustainable development of fisheries in the South China Sea, uniting China and other South China Sea states against IUU fishing could be an efficient way in the future.
Dynamics of Teleworking and Impact on Stakeholders in the Current Pandemic Context
Authors: Stanciu Pavel , Neamțu Daniela Mihaela , Condratov Iulian Alexandru , Hapenciuc Cristian-Valentin , Bejinaru Ruxandra
Published: April 2023

The exponential development of information and communication technology (ICT) through computer networks, Wi-Fi systems, wireless signals, and information storage systems has contributed to the transition to the so-called new economy, which is becoming increasingly digital and global. Due to the COVID-19 pandemic, teleworking has begun to dramatically change the work dynamics for all stakeholders. The aim of this research was to identify the main impacting factors and their level of influence in relation to the macroeconomic context of teleworking, public policies, and the legal framework regarding quality of life, as well as the effects of teleworking on employees and employers. Through empirical research, we explored the perspectives of employees and employers as main stakeholders who had operated in the teleworking field within Suceava County in Romania during 2020. In this regard, we undertook exploratory research, the results of which were processed using SPSS v.20. The insightful results have practical implications for the labor market, where an obvious increase in the share of teleworking in the total forms of work has already occurred, and the relations between employer and employee are expected to become based more and more on cooperation and less on subordination. The results also revealed an important tendency of employees to appreciate the positive effects of teleworking on other aspects of life.
Trace Metals in Rice Grains and Their Associated Health Risks from Conventional and Non-Conventional Rice Growing Areas in Punjab-Pakistan
Authors: Zeeshan Nukshab , Farooqi Zia Ur Rahman , Ahmad Iftikhar , Murtaza Ghulam , Jamal Aftab , Saifullah  , Abdul Qadir Ayesha , Radicetti Emanuele
Published: April 2023

Rice (Oryza sativa L.) is cultivated and consumed worldwide, but the contamination of rice grains with trace metals (TMs) could cause adverse impacts on human health. The aims of this study were to determine the concentrations of TMs in different rice varieties available for sale in local markets and to determine whether consumers are likely to be at risk via the consumption of these rice cultivars. For this purpose, samples of rice grains were collected from 12 rice growing districts (administrative units) in Punjab, Pakistan. These districts were further classified based on rice growing methods due to specific soil type. In conventional districts, the puddling method was used, while direct seeding was used for rice cultivation in non-conventional districts. The samples were collected and analyzed for the determination of essential (Cu, Fe, Zn, and Mn) and non-essential (Cd, Ni, and Pb) TMs using an atomic absorption spectrophotometer (AAS). The results showed that the maximum respective concentrations of Cd, Ni, and Pb (0.54, 0.05, 1.10 mg kg−1) were found in rice grains in conventional areas, whereas values of 0.47, 0.20, and 1.20 mg kg−1 were found in non-conventional rice growing areas. The maximum concentrations of essential TMs (Cu, Fe, Mn, and Zn) were 4.54, 66.01, 4.82, and 21.51 mg kg−1 in conventional areas and 3.76, 74.11, 5.66, 19.63 mg kg−1 in non-conventional areas. In the conventional rice growing areas, Fe and Zn concentrations exceeded the permissible limits in the 27 and 7% samples, respectively. In the non-conventional rice areas, the concentrations of Cu, Fe, and Mn exceeded the permissible limits in the 15, 26, and 3% samples, respectively, while its Zn concentration was found within the permissible limits. The estimated weekly intake (EWI) and maximum tolerable dietary intake (MTDI) values for all studied metals were found within the permissible values set by WHO, except for Fe, in both sampled areas. It was concluded that no health risks were associated by utilizing the rice grains. However, the mean values of TMs were found considerably higher in collected rice samples from non-conventional areas than the conventional areas. Therefore, the concentrations of TMs should be monitored properly.
Assessing Strategic Management of E-Waste in Developing Countries
Authors: Awasthi Abhishek Kumar , Iacovidou Eleni , Awasthi Mrigendra Kumar , Johnson Michael , Parajuly Keshav , Zhao Min , Mishra Saket , Pandey Akhilesh Kumar
Published: April 2023

E-waste is one of the fastest growing waste streams in the world, paradoxically containing both hazardous components and substances which can adversely impact on both the environment and public health, as well as valuable secondary resources and raw materials that could be recovered if e-waste is processed properly. Developing countries not only lack the infrastructure and technology required to manage e-waste appropriately, they largely rely on a fragmented informal sector for the management of a large fraction of e-waste that is either recognized by the state, or is marginalized and suppressed. This article examines the current situation with e-waste management in the developing countries, and assesses these countries’ challenges. The study highlights that there is an urgent need to design more better framework for e-waste that protect these countries from the problems caused by e-waste that are beyond repair and refurbishment, and to help these countries to advance their e-waste recycling and disposal facilities to prevent open burning on and dumping in the environment that can result in deleterious effects on communities at a local as well as at a global level.