bluuebunny/crossref_metadata_2025 huggingface dataset:
Computational Fluid Dynamic Applications for Solar Stills Efficiency Assessment: A Review
Authors: AlSaleem Saleem S. , Al-Qadami Ebrahim , Korany Hussein Zein , Shafiquzzaman Md. , Haider Husnain , Ahsan Amimul , Alresheedi Mohammad , AlGhafis Abdullah , AlHarbi Abdulaziz
Published: August 2022

Even though water is a renewable resource, the majority of the available water on the planet is unfit for human use. Moreover, the drinkable water demand is ever-increasing as a result of rising population, urbanization, and life standards, which makes the needs for sustainable, economic, and environment-friendly treatment alternatives of utmost importance. Seawater desalination using solar stills has been proposed as a promising alternative that may help to solve drinkable water scarcity issues. In the past decades, many studies have been conducted to assess the performance of different types of solar stills aiming to enhance their productivity. Computational fluid dynamic (CFD) numerical simulation is one of the approaches that have been used recently to assess the performance of solar stills. The present study performed a systematic review and bibliometric analysis to provide a comprehensive overview of CFD numerical simulation uses as a tool to assess solar stills performance. A total of 486 publications were collected initially from different databases for the period between 2012 and 2022. The collected publications were filtered through several stages reaching 43 publications of highest significance. The collected data were analyzed descriptively, and the bibliometric mapping was presented. Furthermore, the basics and principles of CFD numerical simulation of solar stills efficiency were described and discussed. Later, the previous studies were analyzed to understand the algorithms, methods, and still types used. Finally, future research scopes and conclusions were stated. The presented knowledge in this study can help to provide a deep overview of using CFD in studying the efficiency of solar stills and inspire researchers to identify future research ways and gaps.
Response of Castor Seedling Roots to Combined Pollution of Cd and Zn in Soils
Authors: Wang Feifei , Yang Linlin , Zhao Yanping , Zhao Zhenzhen , Oh Kokyo , He Chiquan
Published: August 2022

Castors are used to remediate heavy-metal-polluted soils due to their good ability to accumulate heavy metals. However, only limited studies addressed the interaction between heavy metals and castor seedling roots. In this study, the physiological response of castor seedling roots to Cd and Zn stress, and the change in trace elements in rhizosphere and non-rhizosphere soils were investigated. The results showed that, with an increase in Cd concentration, the accumulation of Zn in roots decreased by 20%, indicating a competition between Cd and Zn accumulation. The increase in Cd content enlarged the difference in nutrient contents at different depths: the amounts of P, Fe, and Mn were more in rhizosphere soils than in non-rhizosphere soils, while the amount of K showed an opposite trend. The addition of Cd and Zn stimulated root growth, but root activity was reduced. The addition of Cd and Zn affected the root cell morphology, including increases in the root cortex thickness and the root xylem area. The contents of the enzymes SOD, POD, and MDA increased with the addition of Cd and Zn, while the activity of CAT first increased and then decreased. There was no significant change in the soluble protein content. The decrease in IAA oxidase content, from 40.1% to 72.7%, was conducive to plant growth. To sum up, high contents of Cd and Zn in soils not only affect the root morphology and increase the gap in the contents of K, P, Fe, and Mn between rhizosphere and non-rhizosphere soils but also change the SOD, POD, MDA, and IAA contents in the root, so as to reduce the amount of root damage caused by the external environment.
Product Innovation, Market Intelligence and Pricing Capability as a Competitive Advantage in the International Performance of Startups: Case of Peru
Authors: Gómez-Prado Romina , Alvarez-Risco Aldo , Cuya-Velásquez Berdy , Arias-Meza Marián , Campos-Dávalos Nilda , Juarez-Rojas Luis , Anderson-Seminario Maria , Del-Aguila-Arcentales Shyla , Yáñez Jaime
Published: August 2022

Since the COVID-19 pandemic arrived, various options have been created to export products, with the creation and development of startups becoming a viable and significant option. Previous research has described the influence of competitive business advantage on international performance. However, the novelty of the current research was to evaluate the influence of the company’s capabilities, through the competitive advantage of the company as a mediator in international performance. The study was based on the responses of 200 active startups in Peru. The PLS-SEM technique was utilized with the company’s capabilities linked to internationalization processes as independent variables, as well as market intelligence, product innovation, and pricing. The mediating variable was competitive advantage, and the dependent variable was international performance. It was found that all three capabilities influenced competitive advantage and, ultimately, international performance. It was concluded that competitive advantage does not act as a mediator between pricing capabilities and the international performance of startups. Moreover, it was determined that competitive advantage acts as a mediator between two of the three assessed capabilities: market intelligence capabilities and product innovation capabilities. The results were supported by the reflective and formative evaluation of the results obtained through the applied technique. These results could help create better programs to promote startups interested in internationalizing and exporting products.
Insider Perspectives on Saudi Arabia’s Fakher Disability Sports Programme
Authors: Alhumaid Majed M. , Brooke Mark , Khoo Selina
Published: August 2022

In recent years, Saudi Arabia has made many efforts to support people with disabilities. One of these efforts is the Fakher Programme Initiative. The programme provides substantial financial support and training for around 350 para-athletes with physical disabilities or cerebral palsy. This research sought to provide a thick description of the programme’s aims, its successes, and the challenges faced, based on the reports of significant stakeholders. In-depth interviews with 26 participants from different stakeholder groups (para-athletes, coaches, administrators, para-athlete families, individuals interested in para-sports, and the CEO of the Fakher Programme) were conducted individually to provide rich insider perspectives. An interpretive phenomenological analysis approach was applied to analyse the interviews. Two main dimensions were identified: (i) the positive impacts of the Fakher Programme Initiative and (ii) further recommended improvements to the Fakher Programme Initiative. Although most of the participants expressed positive perspectives on the programme (e.g., developing collaboration, health benefits, infrastructural support, and raising awareness of people with disabilities), improvements can be made in the form of psychological support for elite para-athletes in training and more developed national and international media coverage of disability sports in Saudi Arabia.
Can the Establishment of University Science and Technology Parks Promote Urban Innovation? Evidence from China
Authors: Xiong Ying , Li Shengsheng
Published: August 2022

China’s university science and technology parks (USTPs) were established with the aim of closely combining the scientific and educational intellectual resources of universities with the advantageous innovation resources of the market to form a fusion of industry and education. This paper uses the establishment of national university science and technology parks (NUSTPs) as a “quasi-natural experiment.” We used the panel data of 293 cities from 1999 to 2017 as a sample to analyze the impact of NUSTP establishment on urban innovation, using the difference-in-difference method. The research found the following: (1) The establishment of NUSTPs significantly improves the level of urban innovation, and the conclusion is still valid after a series of robustness tests. The urban innovation effect of the establishment of NUSTPs is dynamic, non-lagging, and continuous. (2) The innovation effect differs significantly, depending on the city region, the city scale, and the university level. Specifically, the innovation effect of the establishment of NUSTPs is significant for cities in middle and western cities, large-scale cities, and cities with double first-class and local universities setting up USTPs, while the effect is not significant for cities in eastern cities, small- and medium-scale cities, and non-double first-class and ministry-affiliated institutions. (3) The impact mechanism test shows that NUSTPs contribute to urban innovation by increasing the city’s human capital, enhancing the degree of industrial agglomeration, and creating an innovation space effect.
Evaluation of Air Pollutants in Extra-Long Road Tunnel with the Combination of Pollutants Nonlinear Evolution and Machine Learning Method
Authors: Chang Hongtao , Ren Rui , Wang Yaqiong , Li Jiaqi
Published: August 2022

The extra-long expressway tunnel has a high socio-economic effect on inter-regional development, with high traffic and strong traffic winds. Nevertheless, the impacts of the tunnel traffic volume on pollutant evolution are rarely considered. This study conducted a field measurement in a real-world extra-long highway tunnel for 578 days. For the first time, the nonlinear dynamics of traffic pollutants (CO, VOCs, NO2, PM2.5, PM10) were analyzed using the Multifractal Detrended Fluctuation Analysis approach. Using the Random Forest model, the impacts of traffic and environmental parameters on air quality were quantified. The findings indicated that COVID-19 had a considerable impact on tunnel traffic, although the variance in pollutant concentration was not very noteworthy. The bidirectional effect of traffic was the main reason for this phenomenon. The Canonical Correlation Analysis was unable to quantify the correlation between pollutants and environmental parameters. The pollutant concentration evolution has a steady power-law distribution structure. Further, an inverse Random Forest model was proposed to predict air pollutants. Compared with other prediction models (baseline and machine learning), the proposed model provided higher goodness of fit and lower prediction error, and the prediction accuracy was higher under the semi-enclosed structure of the tunnel. The relative deviations between the predictions and measured data are less than 5%. These findings ascertain the nonlinear evolutionary mechanisms of pollutants inside the expressway tunnel, thus eventually improving tunnel environmental sustainability. The data in this paper can be used to clarify the changes in the traffic environment under the COVID-19 lockdown.
Supply Chain Resilience in Reality VUCA—An International Delphi Study
Authors: Grzybowska Katarzyna , Tubis Agnieszka A.
Published: August 2022

The modern business world operates in the VUCA environment or reality; volatility and unpredictability are the only constants in it. It is challenging for entrepreneurs to predict the future, and the tested routines, proven habits, or the developed patterns of action no longer function properly, e.g., the logistic strategy of JIT does not fit the new rules of the business game and begins to be treated as a relic. From a business perspective, this new reality is profoundly changing how enterprises and supply chains operate, as well as how we approach supply chain resilience. As a result, we observe a picture of a highly volatile and unpredictable business environment in which vulnerable supply chains operate. The following research questions were asked in the paper: (1) What are the barriers to realizing the concept of Supply Chain Resilience in the reality of VUCA?; and (2) What can be the lead time for the Supply Chain Resilience in reality VUCA? The article presents the results of an expert study using the Delphi method. High-class experts from the scientific community were selected for the research. The results of the research allowed us to answer the research questions posed. Internal barriers to realizing a resilient supply chain in reality VUCA are listed. Based on the indications of experts, three scenarios have also been developed that relate to the speed of the expected lead time of a resilient supply chain, in fact, VUCA. Further research directions on the resilience of supply chains have also been marked out.
Effect of Environmental, Social, and Governance Performance on Corporate Financialization: Evidence from China
Authors: Zhang Shuxia , Yin Xiangyang , Xu Liping , Li Ziyu , Kong Deyue
Published: August 2022

Many nonfinancial firms in China invest increasingly in financial assets. To understand the driving factors behind this phenomenon, this paper examines the effect of environmental, social, and governance (ESG) performance on corporate financialization. The empirical results show that ESG performance has a positive effect on corporate financialization, suggesting that ESG activities are a tool for firms to seek financial arbitrage. Further examination confirms that corporate financialization of Chinese nonfinancial listed firms is motivated mainly by maximizing short-term financial returns, rather than reserving funds for long-term development. Heterogeneity analysis shows that the positive effect is more significant in non-state-owned firms and in firms located in regions with a low degree of marketization. This study enriches the existing literature on the economic consequences of ESG performance and the influential factors of corporate financialization and provides practical guidance for government regulators to strengthen stricter regulation on ESG activities and financial asset investment to ensure sustainable and healthy economic development.
Removal of Nitrogen and Phosphorus from Wastewater Using Layered Filter Media
Authors: Mažeikienė Aušra , Šarko Julita
Published: August 2022

After biological wastewater treatment, ammonium nitrogen (NH4-N), nitrate nitrogen (NO3-N), and phosphate phosphorus (PO4-P) remain in the effluent, which is discharged into natural water bodies. For further removal of these wastewater compounds, three selected materials were used as filter media: quartz sand used in drinking water treatment plants, Purolite A502PS resin, and natural zeolite. After placing all selected materials in the first filtration column (height of each layer-30 cm), the concentration of NH4-N in the wastewater was reduced by 5 times (from 8.22 to 1.5 mg/L), the concentration of NO3-N by 6 times (from 2.46 to 0.44 mg/L), and the concentration of PO4-P by 3 times (from 1.56 to 0.45 mg/L). The second column was without a Purolite A502PS layer, so the concentration of NO3-N in the filtrate from the second column was not reduced. The filtration columns were operated for about 2 months, and the filtration was stopped due to clogging with suspended solids (TSS) with an average concentration of 53.2 mg/L. The preliminary removal of TSS from wastewater before filtration through sorbents is recommended. The tested materials effectively treat wastewater of nitrogen (average efficiency 80–83%) or phosphorus (average efficiency 65–67%) and do not pollute the wastewater with environmentally hazardous substances, so they can be used in the development of tertiary wastewater treatment filters.
Urban Wastewater Reuse for Citrus Irrigation in Algarve, Portugal—Environmental Benefits and Carbon Fluxes
Authors: Moreira da Silva Manuela , Resende Flávia C. , Freitas Bárbara , Aníbal Jaime , Martins António , Duarte Amílcar
Published: August 2022

Water scarcity is increasing in the Mediterranean and alternative sources of water are needed to meet food production needs, protect the environment and reduce the effects of climate change. Currently, many urban wastewater treatment plants (WWTP) produce high volumes of treated effluents which can be an alternative source of water for agriculture irrigation, since they fulfill the quality requirements for crops and the environment. This work analyzed the quantity and quality of a treated effluent produced by an urban WWTP in Algarve, and the environmental benefits of its use on the irrigation of a citrus orchard, as an alternative to groundwater. Carbon dioxide emissions related to orange production were quantified and the orchard’s potential to sequester CO2 was estimated. The reuse of this urban wastewater is revealed to be technologically feasible and environmentally advantageous, avoiding the overexploitation of the local aquifer and preventing the eutrophication of aquatic ecosystems, contributing to the improvement of soil characteristics and decreasing the carbon emissions in orange production. Furthermore, it was found that during the five-month experimental period, the citrus orchard sequestered 87.5% of the CO2e emitted by WWTP in the effluent treatment, converting 72,623 kg of sequestered CO2 into orange biomass.
Progress and Prospects of Destination Image Research in the Last Decade
Authors: Chu Qi , Bao Guang , Sun Jiayu
Published: August 2022

Destination image influences tourists’ perceptions and opinions of destinations and plays a crucial role in tourist behavior and travel-purchase-related decisions. This study summarizes and reviews 151 pieces of literature on destination image published in six major international hospitality and tourism academic journals in the last decade (January 2012–February 2022). By combing through the literature, we found that research on destination image in the previous decade has focused on the following four major areas: (1) the structure of destination image; (2) the measurement and branding of destination image, (3) the influencing factors of destination image, and (4) the influence of destination image on tourists’ behavioral intentions. These results revealed and clarified the latest international research dynamics. The findings provide an all-encompassing understanding of destination image, illustrate the academic evolution of the topic, and point to crucial directions for future research.
Seismic Performance of a Sliding Isolation Bridge System with a New Spring Re-Centering Device
Authors: Yin Pengcheng , Wang Jianguo , Pang Yutao
Published: August 2022

Residual displacements between the girder and piers were observed in previous strong earthquakes. These are caused by the limited re-centering capacity of sliding isolation bearings. With this concern, a spring re-centering device is proposed to improve the re-centering capacity of sliding isolation systems. The working mechanism is illustrated, and the force–deformation relationship of this device was investigated in theoretical, experimental, and finite element methods. An extra-dosed multi-pylon cable-stayed bridge was introduced to demonstrate the re-centering effect. The results show that this spring re-centering device could slightly mitigate the seismic forces and significantly mitigate the residual displacement between the girder and piers. After that, the parametric analysis was conducted to investigate the effect of critical parameters of re-centering bearings on seismic performances.
Identifying Exposure of Urban Area to Certain Seismic Hazard Using Machine Learning and GIS: A Case Study of Greater Cairo
Authors: Hamdy Omar , Gaber Hanan , Abdalzaher Mohamed S. , Elhadidy Mahmoud
Published: August 2022

The 1992 Cairo earthquake, with a moment magnitude of 5.8, is the most catastrophic earthquake to shock the Greater Cairo (GC) in recent decades. According to the very limited number of seismological stations at that time, the peak ground acceleration (PGA) caused by this event was not recorded. PGA calculation requires identification of nature of the earthquake source, the geologic setting of the path between the source and site under investigation and soil dynamic properties of the site. Soil dynamic properties are acquired by geotechnical investigations and/or geophysical survey. These two methods are costly and are not applicable in regional studies. This study presents an adaptive and reliable PGA prediction model using machine learning (ML) along with six standard geographic information system (GIS) interpolation methods (IDW, Kriging, Natural, Spline, TopoToR, and Trend) to predict the spatial distribution of PGA caused by this event over the GC. The model is employed to estimate the exposure of the urban area and population in the GC based on the available geotechnical and geophysical investigations. The exposure (population) data is from free and easy-access sources, e.g., Landsat images and the Global Human Settlement Population Grid (GHS-POP). The results show that Natural, Spline, and Trend are not suitable GIS interpolation techniques for generating seismic hazard maps (SHMs), while the Kriging Method shows sufficient prediction. Interestingly, with an accuracy of 96%, the ML model outperforms the classical GIS methodologies.
Real-Time Maintenance Policy Optimization in Manufacturing Systems: An Energy Efficiency and Emission-Based Approach
Authors: Bányai Ágota , Bányai Tamás
Published: August 2022

Within the frame of the Fourth Industrial Revolution, the application of Internet of Things technologies makes it possible to convert conventional manufacturing systems into cyber-physical systems, where the used new technologies enable the improvement of maintenance and operation processes. The aim of this work is to develop and validate a new real-time maintenance policy model and optimization algorithm based on digital twin simulation. The maintenance policy model is based on the conventional failure and operation data from ERP (enterprise resource planning) and the real-time and forecasted failure and operation data from digital twin simulation. The described maintenance policy model and its optimization algorithm represent an innovative way to manage predictive, preventive, corrective, and opportunistic maintenance strategies. The novelty of the presented method is that the real-time data generated by the digital twin solution allow the definition of a more accurate maintenance strategy. The optimization algorithm is characterized by a standard evolutionary algorithm. The impact of maintenance policy optimization on the energy efficiency and emission was analyzed in the case of both conventional and cyber-physical manufacturing systems with and without digital-twin-based simulation. The results showed that the energy consumption and the greenhouse gas emission in the real-time maintenance policy optimization scenario decreased by 21%, depending on the electricity generation source.
Analysis of Ecological Environmental Quality Change in the Yellow River Basin Using the Remote-Sensing-Based Ecological Index
Authors: Yang Zekang , Tian Jia , Su Wenrui , Wu Jingjing , Liu Jie , Liu Wenjuan , Guo Ruiyan
Published: August 2022

Establishing a method for characterizing spatiotemporal changes in the quality of the ecological environment in a timely and accurate manner is of great significance for the protection and sustainable development of the ecological environment in the Yellow River Basin (YRB). In this study, the Google Earth Engine (GEE) platform was used as a basis for constructing the remote-sensing-based ecological index (RSEI), and the RSEI was used to evaluate the quality of the ecological environment in the YRB. The results indicated that the mean of the RSEI values showed two stages of rapid improvement and slow improvement during 1990–2020. From 1990 to 2000, the average growth trend was 0.005/a with a growth rate of 21.15%, with the main contributions of bad to poor (101,800 km2), poor to medium (56,900 km2), and medium to good (70,800 km2) ecological environmental quality levels. From 2000 to 2020, the average growth trend was 0.002/a with a growth rate of 2.13%, with main contributions of poor to bad (65,100 km2) and good to medium (35,200 km2) ecological environmental quality levels. From 1990 to 2020, there was a 76.38% improvement in the ecological environmental quality of the entire YRB, in which significant improvement accounted for 26.14%. The reductions in the ecological environmental quality accounted for 23.62%, of which significant reductions accounted for just 1.46%. The improvement in the ecological environmental quality of the YRB showed a trend of increasing sustainability, which is expected to continue. The distribution of the ecological environmental quality in the YRB showed obvious regional aggregation, whereby cold spots were concentrated in the northern and central regions of the YRB, which are the sandy and hilly ravine areas of the Loess Plateau. However, the areas corresponding to hot spot clusters decreased with time, and their significance also decreased. Thus, our study demonstrates that the GEE platform can be used to determine the spatiotemporal changes in the ecological environmental quality of the YRB in a timely and accurate manner.
Behavioral Approach to the COVID-19 Vaccination Policy: An Empirical Study in Serbia
Authors: Mojašević Aleksandar S. , Vučetić Dejan , Vučković Jelena , Stefanović Stefan
Published: August 2022

The article presents the results of empirical research on the general population’s attitudes towards the COVID-19 vaccination policy in the Republic of Serbia. The research aims to examine if and to what extent the respondents were vaccinated against COVID-19, their attitudes towards the vaccination policy, and, especially, why they did not get vaccinated or were hesitant. The research was conducted on a sample of the general population (n = 501) by distributing a specially designed questionnaire comprising twelve open and closed questions. The starting hypothesis was that there was significant resistance to vaccination and that respondents were reluctant to get vaccinated due to distrust not only of the COVID-19 vaccines but also of the Serbian health authorities and the public vaccination policy. The findings confirm this hypothesis and reveal specific reasons for resistance and hesitancy, including concerns about the vaccine’s safety, side effects, and insufficiently tested vaccines. A large number of respondents disclosed distrust in the health authorities and noted that they were not prone to changing their minds. The authors explain these reasons by numerous cognitive biases. The conclusion provides an overview of specific behavioral measures for improving the effectiveness of the vaccination policy in Serbia.
Dynamic Evaluation and Spatial Characteristics of Smart Manufacturing Capability in China
Authors: Xue Jie , Li Zhenyan , Wang Xian , Ji Yanli
Published: August 2022

Smart manufacturing is an important development mode in the transition of China’s industry from weak to strong, and the realization of comprehensive smart manufacturing demands the coordinated efforts of all regions in China. Based on the panel data of 30 provincial administrative regions in China from 2014 to 2019, this paper constructs an index system for the development environment, infrastructure facilities, and industrial development. This paper uses methods of entropy weight TOPSIS and the dynamic comprehensive evaluation based on the time ordered weighted averaging (TOWA) operator to evaluate the smart manufacturing capability in China and analyze its characteristics of spatial difference for exploring the appropriate paths for development. The result shows that there are only two provinces, Guangdong and Jiangsu, with the values of dynamic comprehensive evaluation greater than 0.5, seven provinces with values between 0.25 and 0.5, and 21 provinces with values less than 0.25. This reflects the fact that the gradient difference in provincial smart manufacturing capability in China is obvious and most provinces are not good. The decline in the Theil index from 0.17 to 0.15 indicates that the difference in capability between provinces is narrowing, which is a good phenomenon. The increase in the Global Moran’s index from 0.1156 to 0.1478 shows that the capability in each province has a significant positive spatial correlation, and the correlation is strengthening. Moreover, during the six years, the spatial aggregation models of most provinces have not changed. The smart manufacturing capability of the Yangtze River Delta constitutes a stable high-high aggregation region. Guangdong and Chongqing have been in high-low aggregation regions for a long time, while most of the low-low aggregation regions are in the west.
Beyond Airbnb. Determinants of Customer Satisfaction in P2P Accommodation in Time of COVID-19
Authors: Pawlicz Adam , Petaković Ema , Vrtodušić Hrgović Ana-Marija
Published: August 2022

As the P2P (peer-to-peer) accommodation market is expanding, there is a growing interest in the factors affecting customer satisfaction. The previous literature largely concentrates on Airbnb users and tends to use online questionnaires as research data. To address this gap, we analyze the key attributes affecting customer satisfaction in the P2P accommodation market in 2020, the first year of the pandemic, based on onsite research. This will allow the authors to examine the key determinants of customer satisfaction across many platforms. Based on previous research, a conceptual model was developed, and two dimensions of service quality were created: host service quality and facility service quality. An offline primary survey was conducted, and the model was tested using exploratory factor analysis, correlation analysis, and regression analysis. The empirical results show a strong relationship between host service quality and facility service quality and customer satisfaction. This study provides clear theoretical insights to advance our knowledge about the determinants of customer satisfaction. Our results are in line with previous research, despite the survey being conducted during the first year of the pandemic and with the use of offline questionnaires. Furthermore, this study offers practical implications for both peer-to-peer and institutional market actors.
Moving towards Valorization of Biowastes Issued from Biotrickling Filtration of Contaminated Gaseous Streams: A Thermochemical Analysis-Based Perspective
Authors: Lisa Gabriela , Anghel Ion , Preda Dana-Maria , Lisa Catalin , Cretescu Igor , Buciscanu Ingrid Ioana , Diaconu Mariana , Soreanu Gabriela
Published: August 2022

This paper investigates the valorization potential of two biowaste types resulting from biotrickling filtration of volatile organic compounds (i.e., ethanol) and carbon dioxide from air by co-immobilized microalgae and compost heterotrophs, which were either attached on polypropylene spheres or entrapped within the alginate beads. In this regard, biomass samples from the surface of the packing spheres (S1) and the waste alginate beads (S2) underwent thermal and energy characterization via thermogravimetry and calorimetry techniques as a screening step for establishing some possible biomass valorization pathways. The heat release capacity (HRC) values for the samples S1 and S2 were 95.67 J/(g·K) and 44.11 J/(g·K), respectively, while the total heat release (THR) values were 11.03 kJ/g and 3.64 kJ/g, respectively. The results of this study indicate that the S1 biomass could be suitable for undergoing thermal decomposition processes-based applications, while the S2 biomass could have a potential application for improving flame retardancy of some materials. These findings show that the biowaste issued from such air biotreatment can become a valuable resource for different applications instead of being disposed of. Further research referring to the implementation of these solutions for the development of the final applications is needed.
Productive Livestock Characterization and Recommendations for Good Practices Focused on the Achievement of the SDGs in the Ecuadorian Amazon
Authors: Torres Bolier , Andrade Verónica , Heredia-R Marco , Toulkeridis Theofilos , Estupiñán Kleber , Luna Marcelo , Bravo Carlos , García Antón
Published: August 2022

The increase in livestock production in the Ecuadorian Amazon Region has caused an increase in deforestation and the advance of the agricultural frontier. The aim of the current study was to conduct a socioeconomic and productive characterization in Andean-Amazonian livestock systems in Ecuador. The study area was part of the Sumaco Biosphere Reserve (SBR) and three other zones: low (400 to 700 masl), middle (701 to 1600 masl), and high (701 to 1600 masl). Data were collected from 167 ranching households. There are significant differences (p ≤ 0.001) in the results. It was identified that 56.1% of the producers in the middle zone are indigenous (Kichwa). The largest (p ≤ 0.01) average household size (6.7 household members) and the highest level of household heads without schooling (16%) were found in the same area. Heads of households over 54 years of age were reported throughout the gradient. The largest farms were also found in the middle zone, with an average of 62.3 ha, of which an average of 32.9 ha is native forest, 2.1 ha is agricultural land, and 27.2 ha is cattle pasture. The household economy is driven by a greater investment in livestock in the upper area, and therefore their annual gross income has a high impact on their economy. With these results, this study presents recommendations to achieve the Sustainable Development Goals.
Study on Natural Settlement Index Characteristics of Iron-Bearing Tailings Applied to Goaf Filling Treatment
Authors: Liu Zhouji , Deng Daiqiang , Feng Junfa , Wang Runze , Fan Jinkuan , Ma Yunfan
Published: August 2022

In order to provide a technical basis for the subsequent concentration and utilization of the tailings treatment process in an iron ore mine, and to achieve the objectives of cost reduction and sustainable development, the settling concentration and settling capacity of a tailings slurry with an initial concentration of 40% in its natural state were tested in conjunction with the pumping supply concentration index of the beneficiation tailings slurry in a metal mine. The test results show that the iron ore tailings particles settle at an overall fast rate: basically, within 10 to 20 min they are able to reach or approach 85 to 99.5% of the final settling state-related index. During the settling process in the fixed container, at first, the clarified water at the top of the tailings slurry is very turbid. With the passage of time, the clarified water gradually becomes blurred and clear from turbidity, and the interface between the slurry and the water gradually becomes clearer. From the phenomena observed during the settling process and the test parameters such as the net increase in clear water and slurry variation, the maximum settling concentration and settling capacity indicators of 50% and 90% can be reached or approached in 5.5 to 7.25 and 10.5 to 15.5 min after settling, and the maximum settling concentration and settling capacity can be reached or approached in 10 to 20 min after the settling process. As the settling tests and observations continued, the relevant settling parameters basically reached the final settling state within the time period of 20 to 1440 min, during which the settling concentration of the tailing sand was 71.33 to 73.42% and the settling capacity was 1.85 to 1.91 g/cm3. It can be judged from the test results that the natural settling of the low concentration tailings slurry can meet the technical specifications required for the filling process, and that the natural settling and concentration of dewatering can save the costs of the relevant facilities and flocculation chemicals, and therefore has good technical and economic feasibility.
Digital Transformation—Top Priority in Difficult Times: The Case Study of Romanian Micro-Enterprises and SMEs
Authors: Vuță Daniela Roxana , Nichifor Eliza , Chițu Ioana Bianca , Brătucu Gabriel
Published: August 2022

Ever since the pandemic context accelerated technology adoption, the digital transformation of enterprises has become part of consumers’ daily lexicon. The highly demanded necessity of companies to integrate digital solutions and provide services and goods in virtual spaces provokes both managers and academia to identify new perspectives. In this context, can digital transformation through marketing represent an option in difficult times? The authors aimed to reveal an answer to this question by researching the attitudes of 837 entrepreneurs involved in digital marketing activity before and during the pandemic, following their behaviour in the post-pandemic context. With quantitative and qualitative methods, unexpected results were unveiled. Financial losses or low performance in terms of profit or turnover do not negatively influence the attitude of the subjects towards digital marketing adoption. Moreover, the most unexpected result was the evolution of turnover from 2020 compared to 2019 as a determining factor for entrepreneurs’ perceptions of their level of digital knowledge. However, the results are discussed in the context of digital transformation through the method of providing services and goods in the virtual space with digital techniques, enriching the literature with the Romanian micro, small and medium-sized enterprises evidence.
Space-Time Pattern of Coupling Coordination between Environmental Regulation and Green Water Resource Efficiency in China
Authors: Pan Zhongwen , Wang Zhigang , Li Xiaoxiang , Li Jingrong , Zhou Yujiao
Published: August 2022

Based on the coupling coordination model, this paper intends to use the panel data of 31 provinces in China from 2000 to 2019, analyze the coupling and coupling coordination relationship between environmental regulation and green water resource efficiency (GWRE), and explore the space-time pattern of coupling coordination. The results show that: (1) The overall level of environmental regulation in China is showing increasingly stringent characteristics, and the overall GWRE is showing an upward trend. Both show spatial differences, and there is a strong correlation between the spatial spillover of environmental regulation and the improvement of GWRE. (2) The environmental regulation and GWRE in China have not yet achieved the benign resonance goal of high coupling. It is overall manifested as a medium-coupled run-in and a medium-coupled coordination. (3) The space-time evolution characteristics are prominent, and the coupling coordination degree of different provinces (regions) shows a more significant difference, showing the spatial pattern of higher in the eastern region and lower in the west region. Therefore, some policy suggestions are put forward on how to break through the bottleneck of environmental regulation for the improvement of GWRE and how to optimize the external environment in which the government optimizes environmental regulation to inhibit the efficiency of green water resources.
Drivers in the Eco-Innovation Road to the Circular Economy: Organiational Capabilities and Exploitative Strategies
Authors: Peyravi Bahman , Jakubavičius Artūras
Published: August 2022

This article contributes to the empirical literature on the drivers of eco-innovation within the context of an organizational capability and exploitative strategies towards a circular economy. It explores the dynamics of the determinants of eco-innovation. The aim of this study is to contribute to this debate by analyzing evidence regarding the different factors influencing organizational capabilities in “transformative innovation” to support transition while eliminating obstacles to sustainability. The practical contribution of this paper is a consolidated, complete framework of eco-innovation that provides substantial insights to practitioners and facilitates the spread of eco-innovative practices. This study will benefit policy makers, key institutions, and firms to leverage the organizational capability with the effective implementation of eco-innovation processes towards a circular economy, where structural changes and transformative eco-innovation are the main determinants. However, the exploration of eco-innovation dynamics within a circular economy is still widely disregarded, especially concerning the trends and dynamics in policy-making processes and strategy development. The research employed the multi-criteria SAW method. The purpose of the suggested methodology is to establish the criteria for ranking the drivers of eco-innovation adoption. Research findings indicate the nexus between the drivers in eco-innovation and social behavior, eco-design, infrastructural changes, and political approaches. This study provides a comprehensive framework for understanding the drivers of eco-innovation towards a circular economy with regard to organizational capabilities and exploitative strategies.
Fintech, Board of Directors and Corporate Performance in Saudi Arabia Financial Sector: Empirical Study
Authors: Al-Matari Ebrahim Mohammed , Mgammal Mahfoudh Hussein , Alosaimi Mushari Hamdan , Alruwaili Talal Fawzi , Al-Bogami Sultan
Published: August 2022

On a global scale, the Fintech sector has become increasingly important for keeping abreast of developments and progressions in the financial field. This study aimed to examine the impact of Fintech on the financial sector of Saudi Arabia and the role of Fintech in the relationship between the board of directors and corporate performance among Saudi financial firms listed on the stock market. Data were obtained from financial sector firms, covering banks and insurance firms from 2014 to 2020. The results revealed that board size, board independence, board meeting, board experience, and Fintech have a significant relationship with corporate performance. In relation to additional analyses, this study found that the board of directors’ score has a significant association with performance. Moreover, this study found that Fintech does not moderate the relationship between the board of directors’ score and corporate performance. This study sheds light on the effect of Fintech on the financial sector of Saudi Arabia, contributing new information to the literature. The study results are expected to have implications for several stakeholder groups. First, the study findings can be beneficial to academics, in terms of new knowledge and understanding of Fintech in the context of Saudi Arabia, a country that represents the Gulf region and the Arab World. The findings also have implications for policy-makers and practitioners in the Saudi and Middle-Eastern countries, Asia, and developing nations that have a similar culture, socio-economic institutions, or socio-economic environments.
Carbon Emission Reduction Cost Assessment Using Multiregional Computable General Equilibrium Model: Guangdong–Hong Kong–Macao Greater Bay Area
Authors: Zhou Jin-Feng , Wu Juan , Chen Wei , Wu Dan
Published: August 2022

Carbon emissions reduction is an urgent global call to action, and for China, the nation with the largest carbon dioxide emissions, the task is especially arduous. For a country like China with many provinces and cities and unbalanced regional economic development, how to balance carbon emission reduction targets with economic development goals has become a social concern. Estimating the emission reduction costs of economic entities at all levels and reasonably allocating emission reduction tasks are the basic prerequisites for sustainable urban development. Based on an input–output (IO) table analysis of the socioeconomic data of Guangdong Province from 2017, this paper uses RAS and other data reconciliation methods to decompose various statistical data based on cities and industries. A multiregional IO table of nine cities in Guangdong Province in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) is obtained, and a multiregional computable general equilibrium (CGE) model of Guangdong Province is established. Using this model, this paper explores city-level differences in carbon emissions reduction costs while accounting for differences in economic development under industry-wide coverage. A scientific basis for the allocation of urban carbon quotas is provided, which is particularly important for the sustainable development of cities. First, the carbon emissions reduction cost (carbon price) of each city is related to the intensity of emissions reduction and the present carbon intensity, both of which are affected by cities’ industrial and trade structures. Second, under neoclassical closure conditions, carbon emissions reduction is found to have less impact on the overall gross domestic product (GDP). At the industrial level, the high-carbon sectors are the most affected, whereas the low-carbon sectors are less affected. Notably, some industries become beneficiary sectors. Under Keynesian closure conditions, carbon emissions reduction has a greater impact on overall GDP, and all cities and industries are generally affected, especially those that are currently carbon- and trade-intensive. Third, to ensure the achievement of emissions reduction targets and minimize negative economic impacts, it is determined that the direct and opportunity costs of carbon emissions reduction must be fully considered when allocating carbon allowances, and optimal solutions should be derived from the combined perspective of fairness and efficiency.
Improved Neural Network Algorithm Based Flow Characteristic Curve Fitting for Hydraulic Turbines
Authors: Pan Hong , Hang Chenyang , Feng Fang , Zheng Yuan , Li Fang
Published: August 2022

One of the most important characteristic curves in the economic operation of hydropower plants is the turbine flow characteristic curve, which illustrates the law of fluctuation between the characteristic parameters of the turbine under various operating situations. This article proposes an IPSO-LSTM-based refinement method for fitting the turbine flow characteristic curve using deep learning methods, and verifies the effectiveness of the method by comparison to solve the problem that traditional mathematical fitting methods are difficult to meet the requirements of today’s many complex working conditions. Firstly, a deep LSTM network model is established based on the input and output quantities, and then the IPSO method is used to find the optimum number of neurons, the learning rate and the maximum number of iterations of the LSTM units in the network model and other key parameters to determine the relevant training parameters. The results show that the model can effectively improve the accuracy of fitting and predicting the turbine flow characteristics, which is of great significance to the study of the economic operation of hydropower plants and the non-linear characteristics of the turbine.