bluuebunny/crossref_metadata_2025 huggingface dataset:
Unsustainable Anthropogenic Activities: A Paired Watershed Approach of Lake Urmia (Iran) and Lake Van (Turkey)
Authors: Khoshnood Sajad , Lotfata Aynaz , Sharifi Ayyoob
Published: October 2022

Water availability in lakes must be studied in order to better manage ecosystems within lake basins and meet economic development needs. Despite being Iran’s largest lake, Lake Urmia’s water level and surface area have declined dramatically over the past two decades. During the same period, Lake Van in Turkey maintained a relatively stable water level and surface area. As a result, comparing factors related to water level and surface area in these lakes, which have similar geographical and climate conditions but different management policies, can be an appropriate way to identify the causes of water declines in Lake Urmia. Comparing these variables may help explain observed differences in lake behavior between 2000 and 2016. Hydrometric and climatic parameters, as well as the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI), were used to achieve this goal. Changes in precipitation, temperature, and evapotranspiration in both lakes show essentially identical trends, but this is not a convincing explanation for Lake Urmia’s water surface changes. The results revealed that dam construction and water diversion projects, the expansion of irrigated agriculture, and the lake’s shallow depth in most parts were the primary causes of Lake Urmia’s shrinkage compared to Lake Van.
Design of f-SCAN Acquisition Mode for Synthetic Aperture Radar
Authors: Guccione Pietro , Mapelli Daniele , Giudici Davide , Persico Adriano Rosario
Published: October 2022

This paper presents the design and processing of the SAR acquisition technique named frequency scanning (f-SCAN), aimed to obtain high sensitivity to targets with low backscattering and to improve the signal-to-noise ratio (SNR) in wide-swath systems. The f-SCAN is an interesting alternative to the scanning on receive method (SCORE), which needs multiple phase centres achieved using the digital beam forming (DBF) technique. f-SCAN requires less hardware complexity than SCORE; at the same time, it improves the sidelobes and ambiguities’ suppression. The elements used in f-SCAN to generate the pencil beam are the true time delay lines (TTDLs) and the phase shifters (PSs). The general methodology to design an f-SCAN spaceborne SAR high-resolution wide-swath (HRWS) system is introduced; emphasis is put on the mathematical definition of the timing parameters and on a novel method of using TTDLs to achieve the full spanning of wide swaths. The processing of f-SCAN data is also considered: we introduce a novel algorithm to limit the data volume and to guarantee an almost invariant slant range impulse response function (IRF) by removing spectral distortions. Eventually, new definitions, specific for f-SCAN, of the well-known SAR performance parameters, are provided. Simulation results and performances are presented. The advantages and disadvantages with respect to SCORE are discussed using the design of a real case system.
Test of an Improved DNA and RNA Purification Protocol—Importance of Proteinase K and Co-Purified Small RNAs
Authors: Biskup Edyta , Schejbel Lone , Oliveira Douglas Nogueira Perez de , Høgdall Estrid
Published: October 2022

Optimized and reliable DNA/RNA extraction protocols are a vital tool in clinical practice in the context of molecular testing. Here, we present our successful attempt to enhance the quantity of RNA isolated from clinical specimens, which we originally found challenging (breast and testis). We compared several purification methods with special focus on two AllPrep system-based protocols (QIAGEN). Our data suggest that addition of proteinase K may markedly increase RNA and, in some cases, also DNA yield. The extraction kit used, AllPrep DNA/RNA/miRNA universal kit, provides RNA amounts comparable with the phenol-chloroform extraction method; however, part of the final yield consisted of small RNAs, visible as a thick band in the bioanalyzer gel-like image (5S peak). The 5S peak, albeit in some cases dominating the bioanalyzer image, plays only a small role in RT-qPCR analysis, and Qubit or NanoDrop measurements can still be used as a reliable estimate of starting amounts of mRNA for downstream analyses. In conclusion, we showed that implementing a protocol containing a step of proteinase K digestion markedly increases RNA yield. The AllPrep DNA/RNA/miRNA Universal Kit can be successfully used for simultaneous extraction of DNA and total RNA, irrespective of the tissue of origin, and does not present inconveniences related to phenol-chloroform extraction.
“Just Be Careful, Since Social Media Is Really Not as Safe as It’s Being Portrayed”: Adolescent Views on Adult Support for Safer Social Media Use
Authors: Tokovska Miroslava , Eg Ragnhild , Bell Ashley Rebecca Holt , Tennfjord Merete Kolberg
Published: October 2022

Social media is an integral part of the lives of adolescents, but they are also closed arenas concealed from the next of kin and are resistant to parental mediation. Consequently, this study aims to investigate how adolescents reflect on the safe use of social media and the conversations they have with their parents. The present study used data from 8 focus group interviews with adolescents aged from 15 to 19 years in Norway. Data were analysed using systematic text condensation—an inductive thematic cross-case analysis. The results showed three themes: (1) next of kin encourage caution, (2) safety is created through mutual learning, and (3) adolescents expect parental mediation. The present study has important implications for policymakers, media educators, and education institutions and its findings will enable better preparation and targeting of curricula and education from basic to secondary schools on a national level.
Cross-Cultural Adaption and Validation of the Dutch Version of the Kerlan-Jobe Orthopaedic Clinic Questionnaire in Juvenile Baseball Pitchers
Authors: Leenen A. J. R. , Hurry Amber , van Dis Femke , van der Graaff Erik , Veeger H. E. J. , Hoozemans M. J. M.
Published: October 2022

Monitoring the performance and functional status of baseball pitchers’ upper extremity is important in maintaining the athlete’s health and performance. This study validated a Dutch translation of the original English Kerlan-Jobe Orthopaedic Clinic (KJOC) against the previously validated Disabilities of the Arm, Shoulder and Hand (DASH) and Western Ontario Shoulder Instability Index (WOSI) questionnaires in a group of talented juvenile Dutch baseball pitchers. Three times, from 2014–2016, 107 pitchers completed the Dutch KJOC, DASH and WOSI questionnaires. Participants’ questionnaire scores were analysed for the whole group and the symptomatic player subgroup separately. Internal consistency, construct validity and ceiling and floor effects were examined. Cronbach’s alpha was consistently above 0.8 for the three time periods for the whole group, and ranged between 0.62 and 0.86 for the symptomatic subgroup. Spearman’s rank correlation coefficients ranged from 0.47 to 0.67 for the whole group and 0.32 to 0.99 for the symptomatic subgroup. No floor effects were observed in the scores of the KJOC and only a ceiling effect for the whole group (15.2%) at one time period. The Dutch version of the KJOC has shown acceptable internal consistency and construct validity and can be used to assess overhead athletes’ shoulder and elbow functionality.
Research on the Impact Path of the Sustainable Development of Green Buildings: Evidence from China
Authors: Wang Yihong , Chen Da , Tian Pingye
Published: October 2022

Green buildings are not only the optimum avenue to reduce the adverse effects of buildings, but also the inevitable requirement for implementing the concepts of sustainable development in construction. As they are more complicated engineering systems, green buildings face more influencing factors from various aspects than traditional ones. Therefore, those factors and their driving effects must be considered carefully for the purposes of the sustainable development of green buildings. The research samples selected in this paper are 23 typical green building cases in Tianjin. This paper employs the clear set csQCA method to explore the linkage effect of incentive policies, technical support, enterprise recognition, the evaluation standard system, and development cost on the sustainable development of green buildings and path selection. The results show that a single condition is far from enough for the sustainable development of green buildings. Multiple antecedent conditions are developed concurrently to form the diversified configuration driving it. There are three ways to initiate this; the first is a three-element driving system, including incentive policies, enterprise recognition, and development cost; the second is another three-element driving system including technical support, enterprise recognition, and an evaluation standard system; and the last is a four-element driving system, including incentive policy, technical support, evaluation standard system, and development cost. The conclusion of this paper contributes to a deepening of the rational understanding of the nature of the complex interaction of the multiple factors that are behind the sustainable development of green buildings in China, and it, therefore, brings beneficial practical enlightenment for the purposes of sustainable development.
Sustainability of Coastal Agriculture in the Face of Soil Degradation: The Influence of Water Salinization as an Example
Authors: Kholaiq Mariame , Benmessaoud Safaa , Kara Mohammed , Assouguem Amine , Abbasi Arshad Mehmood , Al-Ghamdi Abdullah Ahmed , Elshikh Mohamed S. , Rahimi Abdelmajid , Saber Najib
Published: October 2022

The pump-irrigated soils of the coastal Chaouia in Morocco are subject to changes in their qualities due to the quality of the irrigation water and their proximity to the sea. This work aims to approach irrigation water quality and the influence of these waters on the quality of agricultural soils. The study is based on the systematic and selective sampling of water and soils (19 water samples and 19 soil samples). Analyzed parameters mainly include the salinity and pH of the soil and water samples. The main results show that soil pH varies from 6.81 to 7.7. However, the pH of the water varies from 6.22 to 8.13. The electrical conductivity in soils varies from 12,260 μs/cm to 700 μs/cm and from 1123 μs/cm to 8120 μs/cm. The results of the analysis of soil salinity show that in moving away from the sea, the salinity decreases, and the salinity of the water samples follows the same trend. The Richard and Wilcox graphs show that most water samples taken near the sea are highly mineralized and have poor water quality. This paper presents important aspects of the feasibility of coastal agriculture and can be a source of inspiration for future research and planning of coastal agriculture.
Entrepreneurial Competencies and SMEs’ Performance in a Developing Economy
Authors: Sakib Md. Nazmus , Rabbani Mustafa Raza , Hawaldar Iqbal Thonse , Jabber Mohammad Abdul , Hossain Jubait , Sahabuddin Mohammad
Published: October 2022

This paper aims to empirically test the impact of entrepreneurial competencies on the performances of SMEs in Bangladesh. The data are obtained from 115 entrepreneurs by a structured questionnaire. The partial least square structural equation modeling (PLS-SEM) method is applied to find the causal relationship between exogenous and endogenous variables. The results reveal that the organizing and leading, learning, relationship, and commitment competencies of entrepreneurs have a meaningful impact on SME performance. On the contrary, strategic and opportunity competencies have no effect on the performance of SMEs. The contribution of this study is to find out the relevant entrepreneurial competencies and to empirically test their impacts on the performance of SMEs in a developing country setting. This study gives insights into the policymakers regarding the entrepreneurship training and development program. Finally, the competency measurement of this study provides a unique scope for designing such training and development programs for entrepreneurs.
Consumption Upgrading and Industrial Structural Change: A General Equilibrium Analysis and Empirical Test with Low-Carbon Green Transition Constraints
Authors: Xing Xiaowei , Ye Azhong
Published: October 2022

To clarify the relations between low-carbon green transition, consumption upgrading, and industrial structure change, this paper firstly builds a dynamic model of the three, then uses the PVAR Model and panel data of 30 Chinese provinces from 2008 to 2020 to carry out empirical study from the rationalization and upgrading dimensions of industrial structural change, respectively. The results are as follows: (1) Low-carbon green transition and consumption upgrading are Granger causes of each other. In this causal relationship, low-carbon green transition hinders consumption upgrading, but consumption upgrading significantly promotes low-carbon green transition. (2) Low-carbon green transition plays a facilitating and hindering role in industrial structure rationalization and upgrading, respectively. However, from the different dimensions of industrial structure change, only industrial structure upgrading has a significant reverse hindering effect on low-carbon green transition, and the reverse effect of industrial structure rationalization on low-carbon green transition is not significant. (3) Consumption upgrading has a hindering and promoting effect on the rationalization of industrial structure in the short- and long-run respectively, and a promoting and hindering effect on the industrial structure upgrading respectively; however, only industrial structure upgrading significantly promotes consumption upgrading in the opposite direction, while industrial structure rationalization has no significant effect on consumption upgrading. These findings propose some suggestions such as advocating the new way of green consumption, constructing and improving the green whole industry chain, and strengthening the synergy between imitative innovation and independent innovation.
Retail Apocalypse as a Differential Urbanisation Symptom? Analysis of Ground Floor Premises’ Evolution in Barcelona between 2016 and 2019
Authors: Morcuende Alejandro , Lloberas David
Published: October 2022

The current health and economic crisis resulting from the COVID-19 pandemic has accentuated some of the trends that began with the counter-reform of capitalism in 1970. This paper deals with one of those trends—the retail apocalypse. The starting hypothesis is that this phenomenon takes part in an implosion (the massive and permanent closing of retail premises in agglomeration) and an explosion (a change of land uses in an urban agglomeration and beyond). In order to determine the reach of those trends, the last two commercial censuses of the City Council (2016 and 2019) are analysed using a one-to-one relation matrix and map representation. This phenomenon, which is not just economic but also urban, is expressed differentially according to the dynamics between the upper and lower circuits of the urban economy. An implosion is detected as a general form for the whole city; in contrast, an explosion is expressed in more dynamic areas.
Modeling the Level of Drinking Water Clarity in Surabaya City Drinking Water Regional Company Using Combined Estimation of Multivariable Fourier Series and Kernel
Authors: Ampa Andi Tenri , Budiantara I Nyoman , Zain Ismaini
Published: October 2022

The purpose of this study is to propose an appropriate model to predict chemical composition during water purification at the Regional Water Company (PDAM) Surabaya, in order to achieve proper drinking water standards. Drinking water treatment is very expensive, so the model serves as a basis for determining the composition of chemicals used in the water purification process at PDAM Surabaya. This study examines a model of the relationship between the level of clarity of drinking water and the composition of the chemicals used. The government can obtain important benefits from the forecasting model to formulate policies for the company. One of the objectives of developing the estimation method involved in this research is to efficiently determine the exact chemical composition resulting from the water purification process, which will inform the financing and control of water quality. We used a multivariable linear approach for some parametric components, a multivariable Fourier Series approach for some nonparametric components, and a multivariable Kernel approach for semiparametric regression. Using the penalized least square (PLS) approach, a mixed estimator of the Fourier and Kernel Series was obtained with semiparametric regression. The smoothing parameters were selected using a common cross-validation technique (GCV). The performance of this technique was evaluated using the Gaussian Kernel and Fourier Series with data trends in the drinking water clarity level obtained from PDAM Surabaya. The findings showed that this technique performed well, so we recommend that the government conduct an in-depth analysis to determine correct chemical composition so that the cost of water treatment can be minimized.
Comparison of the Performance of Hybrid Traffic Signal Patterns and Conventional Alternatives When Accounting for Both Pedestrians and Vehicles
Authors: Montazeri Farzaneh , Errico Fausto , Pellecuer Luc
Published: October 2022

Traffic control systems are crucial for managing traffic flows. Their main function is to reduce interactions among users for safety reasons, while minimizing the travel times. Researchers often concentrate on the cycle length, whose impact on travel times is directly measurable. However, the choice of the signal pattern may also have a great potential to reduce travel times and unsafe situations. This potential is yet to be thoroughly investigated. In this work, we are interested in comparing different signal patterns in terms of the number of potential conflicts and delay time for both drivers and pedestrians. To this end, we first select three commonly adopted signal patterns, namely the Exclusive Pedestrian Phase (EPP), the Leading Through Interval (LTI) and the Two-Way Crossing (TWC). We then generalize existing methods for measuring user delay and safety for these three signal patterns. Moreover, we investigate a hypothetical hybrid pattern obtained by dynamically adapting the signal pattern to real-time data. The proposed methodology is applied to a case study considering an isolated intersection in Montreal, Canada. We perform computational experiments geared towards determining the best pattern according to ad hoc performance indicators and user flows. Results show that the EPP and LTI patterns generally perform better than TWC. EPP generally outperforms LTI when measuring the number of potential conflicts, while LTI outperforms EPP when considering delay times. Furthermore, the hypothetical hybrid pattern shows a positive but overall limited impact regarding both delay times and number of potential conflicts.
A Robust Possibilistic Bi-Objective Mixed Integer Model for Green Biofuel Supply Chain Design under Uncertain Conditions
Authors: Savoji Hossein , Mousavi Seyed Meysam , Antucheviciene Jurgita , Pavlovskis Miroslavas
Published: October 2022

In recent years, concerns regarding issues such as climate change, greenhouse gas emissions, fossil reserve dependency, and petroleum price fluctuation have led countries to focus on renewable energies. Meanwhile, in developing countries, designing an appropriate biofuel supply chain network regarding environmental competencies is an important problem. This paper presents a new bi-objective mixed integer mathematical model aiming to minimize CO2 emission and total costs in the process of the biofuel supply chain, creating a suitable green supply chain network. In this respect, CO2 emission and biofuel demand are regarded as uncertain data to address the real complex cases. Moreover, the SAUGMECON approach was implemented to construct a single objective model, and the obtained Pareto optimal points were depicted and analyzed. Thereby, a robust possibilistic programming approach was implemented to the proposed model to handle existing imprecise data. Furthermore, the applicability and performance of the proposed model were demonstrated based on an experimental example. In this respect, the obtained results from the proposed robust possibilistic programming model were compared with its crisp form to show the robustness and reliability of the proposed uncertain mathematical model.
Agronomic Evaluation of Recycled Polyurethane Foam-Based Growing Media for Green Roofs
Authors: Cannavo Patrice , Artous Mathieu , Lemmel Olivier , Buord Hervé , Vidal-Beaudet Laure , Guénon René
Published: October 2022

Green roofs are very popular and their individual surface area is constantly growing. Considering that the organo-mineral materials used in planting growing media (GM) are often non-renewable resources, the search for alternative materials from waste recycling is a challenge. Among these, recycled polyurethane (PU) foams are light and porous. The objective of this study was to evaluate the potential agronomic valorisation of PU foams for extensive green roofs. Three GM based on compost, PU foam and topsoil were developed and tested in situ for 18 months along with four plant species in containers containing 15 cm of GM. The agronomic properties of the GM and their contaminant contents were evaluated, as well as the plant aerial and root biomasses and trace element levels. The main results of this work are that GM are suitable for plant growth. Compost ratio effect resulted in a lower pH and higher exchangeable cations in GM1, whereas topsoil proportion effect mainly decreased macroporosity and increased nutrient contents. Furthermore, due to the high trace element load in the compost, hyperaccumulator plants such as Hypericum calycinum and Stipa tenuissima should be preferred. Ecotoxicological analyses will be carried out to validate the absence of risk of PU foam contaminants being released in the environment before proposing these types of GM to green roof developers.
Techno-Economic Analysis of Integrated Solar Photovoltaic Winnower-Cum Dryer for Drying Date Palm Fruit
Authors: Poonia Surendra , Singh Anil Kumar , Jain Dilip , Kumar Nallapaneni Manoj , Singh Digvijay
Published: October 2022

Date palm (Phoenix dactylifera L.) fruits are widely grown in rural areas of arid Rajasthan of India. The grown date palm fruits are generally dried in forced convection mode. However, given the socio-economic status of farmers, dryer facility affordability has become crucial. Additionally, there is a critical need for a simple winnower, especially with its operation. To address the highlighted issues with the dryer and winnower and given a location already receiving abundant solar radiation, a solar photovoltaic (PV) winnower cum-dryer was designed and developed. The developed winnower cum-dryer was tested in actual conditions to realize the performance. First, the drying experiment for dehydrating date palm fruits and, second, the winnower experiment for separating grains from straw were carried out. The date palm fruits used for experimentation have a moisture content of 65% on a wet basis. During the drying trial, the dryer reduced this moisture content by 39% in 6 days. In contrast, in the open sun drying, it took 8 days. The drying chamber’s temperature gradient was reduced to 2–3 °C from 6–8 °C in the system provided with a preheater, resulting in uniform drying. The observed effective moisture diffusivity and the dryer’s efficiency are 4.34 × 10−9 m2·s−1 and 16.1%, respectively. A high IRR of 57.4% and a shorter payback period of 2.10 years were found in the economic analysis, indicating that the dryer is cost-effective. The winnower operation results suggest that about 200–300 kg grains could be separated daily when used as a winnower without natural wind. Overall, the developed winnower cum-dryer produced better-quality dried date palms in a shorter time than open drying by efficiently using solar energy and separating the grains from straw to enhance the utility throughout the year.
Long-Term Effects of COVID-19, and Its Impact on Business, Employees, and CO2 Emissions, a Study Using Arc-GIS Survey 123 and Arc-GIS Mapping
Authors: Gary Vegh , Sarah Sajedi , Deborah Naybor
Published: October 2022

Further investigation is needed to study the impacts of the COVID-19 lockdown and subsequent lifestyle changes. The global pandemic caused a high degree of uncertainty, leading to extreme anxiety. These feelings were also compounded by the sudden changes in lifestyle at home, within families, work, studies, and recreation. With the end of the lockdown approaching in most regions of the world, many of these lifestyle changes, including work-from-home, might remain for a good percentage of the workforce. The primary objective of this research is to explore employees’ work-from-home model and its impact on commute time, job satisfaction, and carbon footprint. Quantitative variables include data from North America and Global country-specific carbon dioxide (CO2) emissions, and quantitative data, including employee satisfaction, commute time, miles traveled, and more, was collected using ArcGIS Survey123. This research focus on CO2 emissions data, comparing 2019 data (March to May) as a baseline to 2020, 2021, and 2022 (March to May) as the target year. The hypothesis is that the work-from-home order had a significant impact on short-term CO2 reductions and could have potential long-term impacts due to many corporations’ adoption of the “work-from-home” model. The data collected regarding CO2 were analyzed using ArcGIS Pro and Geostatistical Interpolation. This study also explored the potential impacts of this adoption on employee job satisfaction and CO2 emissions reductions based on surveyed employees. Another objective of this research is to look at the relationship between the COVID-19 lockdown with the work-from-home model and the reduction in air emissions, namely CO2.
Evaluation of Green Manufacturing Level in China’s Provincial Administrative Regions Based on Combination Weighting Method and TOPSIS
Authors: Wang Mingtao , Ye Chunming , Zhang Dingkun
Published: October 2022

Green manufacturing is becoming an important emerging field in the new round of global industrial revolution and scientific and technological competition. Scientific evaluation of China’s regional green manufacturing level has far-reaching significance for promoting the transformation and upgrading of the manufacturing industry and enhancing international competitiveness. This paper defines the connotation of green manufacturing in China in the new era, proposes four dimensions of green production, green emission, green technology, and green benefit as the framework of the evaluation system, and constructs the evaluation index system. By taking 30 provincial administrative regions as research samples, based on the data from 2017 to 2020, the combination weighting method and TOPSIS are used for evaluation from the perspective of “static” and “dynamic” to identify the current situation and development of green manufacturing level in each region. It was found that the important factors affecting the green manufacturing level in each region are green products, green invention patents, sulfur dioxide, green factories, and coal consumption. The “static” evaluation results show that the green manufacturing level varies significantly among regions. The eastern area is generally better than the central and western areas, and only six regions are at high-level and medium to high-level. In addition, the four dimensions in most regions are imbalanced, with an obvious Matthew effect. The “dynamic” evaluation results show that the green manufacturing level in 30 regions appears to have six different types of dynamic trends. There is a small change in the ranking of most regions, indicating that the dynamic development of green manufacturing level has clear regional dependence, which is difficult to change in the short term. The research results show that the index system and model can effectively evaluate the regional green manufacturing level. Finally, combined with the important influencing factors, some suggestions are proposed to enhance the regional green manufacturing level.
Manure Effect on Soil–Plant Interactions in Capia Pepper Crops under Semiarid Climate Conditions
Authors: Yakupoğlu Gökçen , Saltalı Kadir , Rodrigo-Comino Jesus , Yakupoğlu Tuğrul , Cerda Artemi
Published: October 2022

One of the biggest threats to agro-ecosystems, especially in arid and semiarid areas, is the deterioration of soil quality, which is associated with low soil organic matter levels. Despite the elevated volume of publications related to soil quality and crops, information about specific plants such as the Capia pepper (Capsicum annuum L. cv.) with clear economic relevance in semiarid environments is missing. The aim of present study is to investigate the effects of different doses of manure on Capia pepper focusing on soil–plant interaction, soil quality, and plant yield in an experimental area located in Turkey. Key soil properties were monitored and relationships between plant and soil properties were evaluated using the principal component analysis (PCA). At the end of the first and second growing season, the effects of manure application on some plant and soil characteristics were statistically significant at different levels. According to the PCA result, 15 plant characteristics and 7 soil characteristics were grouped into five factors and defined 85.4% and 90.9% of the total variability in the population in the first and second growing seasons, respectively. Our research concluded that sustainable soil management such as the use of specific dose of manure improves soil quality and plant productivity.
Monitoring Marine Oil Spills in Hyperspectral and Multispectral Remote Sensing Data by the Spectral Gene Extraction (SGE) Method
Authors: Zhao Dong , Tan Bin , Zhang Haitao , Deng Rui
Published: October 2022

Oil spill incidents threaten the marine ecological environment. Detecting sea surface oil slicks by remote sensing images provides support for the efficient treatment of oil spills. This is important for sustainable marine development. However, traditional methods based on field analysis are time-consuming. Spectral indices lack applicability. In addition, traditional machine learning methods strictly rely on training and testing samples which are in short supply in oil spill images. Inspired by the spectral DNA encoding method, a spectral gene extraction (SGE) method was proposed to detect oil spills in hyperspectral images (HSI) and multispectral images (MSI). The SGE method contained a parameter and two strategies. The parameter of elimination was designed based on the population genetic frequency. It was used to control the number of spectral genes. The spectral gene extraction strategies, named largest in-class similarity (LIS) strategy and largest inter-class difference (LID) strategy, were proposed to mine the spectral genes by oil spill samples. The oil spills would be determined by calculating the similarity of the extracted spectral genes to the DNA encoded images. In this research, the SGE method was validated by two AVIRIS images of the Gulf of Mexico oil spill, one MODIS image of the Gulf of Mexico oil spill, and one Landsat 8 image of a Persian Gulf oil spill. The oil spills in different remote sensing images could be detected accurately by the proposed method in a small set of samples. Experimental results indicated that the proposed method was suitable for detecting marine oil spills in AVIRIS, MODIS, and Landsat 8 images. In addition, the SGE method with the LIS strategy was more suitable for detecting oil spills in HSI. Its proper elimination rates were 0.8~1.0. The SGE method with the LID strategy was more suitable for detecting oil spills in MSI. Its proper elimination rates were 0.5~0.7.
Sustained Social Entrepreneurship: The Moderating Roles of Prior Experience and Networking Ability
Authors: Obi-Anike Happiness Ozioma , Okafor Chikodili Nkiruka , Daniel Cross Ogohi , Onodugo Ifeoma Joanes , Ukpere Wilfred I. , Udoh Ben Etim
Published: October 2022

The intention to set up social ventures remains an unpopular choice for intending entrepreneurs due to its obvious limitations of resource constraints. Yet it remains a vital means of making social goods available to disadvantaged people, especially in developing countries. Our study aims to investigate how prior experience and networking ability interacts with empathy, moral obligation, self-efficacy, and social support to induce social entrepreneurial intentions in budding entrepreneurs in Nigeria. Using simultaneous linear regression, we analyzed data from a collection of 315 respondents enrolled in the National Youth Service Corps (NYSC)—a one-year mandatory national service scheme for graduates of higher institutions who are on the verge of making critical career choices. Our findings show that the main effects were statistically significant, while networking ability, more than prior experience, moderated the main effects. Conclusively, budding entrepreneurs need to hone their networking skills in order to exploit their social networks and complement the benefits of prior experiences as they contemplate social entrepreneurship. Future investigations can focus on determining how other environmental factors such as government/institutional support, technological adoption, and infrastructure would affect social entrepreneurial intentions.
Sustainable Soilless Cultivation Mode: Cultivation Study on Droplet Settlement of Plant Roots under Ultrasonic Aeroponic Cultivation
Authors: Yang Xiwen , Luo Yahui , Jiang Ping
Published: October 2022

In order to solve the effects of environmental factors on the droplet settlement of a nutrient solution on plant roots when planting plants with ultrasonic aeroponic cultivation, this study aimed to obtain a suitable wind speed range and atomization time through a nutrient solution atomization experiment, to obtain the best control scheme through a multi-environmental parameter combination cultivation experiment. Taking an ultrasonic aeroponic cultivation device as the research object, and lettuce as the test material, experiments were carried out on two factors affecting the wind speed of an axial fan and the atomization time of the nutrient amount of ultrasonic aeroponic cultivation plants; the suitable wind speed range was 1.0–2.5 m/s. The temperatures of the lettuce root zones in the upper, middle, and lower layers of the ultrasonic aeroponic cultivation device at different time periods were obtained by atomizing the nutrient solution. When the optimum temperature for the root growth of lettuce was 15–20 °C and the wind speed was 1.0–2.5 m/s, the continuous atomization time of the nutrient solution was 66–184 min. Using a quadratic orthogonal rotation combination design method, three main factors, namely wind speed, ambient temperature, and atomization time, were selected to test droplet settlement in the lettuce roots. The droplet settlement in the lettuce root system was measured. The droplet settlement regression equation in the lettuce root system was established. The reliability of the regression model was tested according to the significance condition, and a simplified quadratic orthogonal regression equation was obtained. The main effect analysis, single factor analysis, and interaction effect analysis were used to analyze the model, and the model was further verified. The verification results showed that the relative error between the predicted value and the actual value of the average root droplet sedimentation was 5.8%. The optimum wind speed was 2.5 m/s, the ambient temperature was 16 °C, and the atomization time was 184 min when the ultrasonic aeroponic cultivation device designed in this study was used to cultivate lettuce. It could provide a theoretical reference and an experimental basis for the control of the related growth environment parameters of plants cultivated using ultrasonic aeroponic cultivation.
Visualizing Temporal and Spatial Distribution Characteristic of Traffic Accidents in China
Authors: Yang Yingliu , Jin Lianghai
Published: October 2022

The interaction among social economy, geography, and environment leads to the occurrence of traffic accidents, which shows the relationship between time and space. Therefore, it is necessary to study the temporal and spatial correlation and provide a theoretical basis for formulating traffic accident safety management policies. This paper aims to explore the traffic accident patterns in 31 provinces of China by using statistical analysis and spatial clustering analysis. The results show that there is a significant spatial autocorrelation among traffic accidents in various provinces and cities in China, which means that in space, the number of traffic accidents and deaths is high with high aggregation and low with low aggregation. Positive spatial autocorrelation is primarily concentrated in the southeast coastal areas, while negative spatial autocorrelation is mainly concentrated in the western areas. Jiangsu, Anhui, Fujian, and Shandong are typical areas of traffic accidents, which deviate from the overall positive spatial autocorrelation trend. Traffic accidents in Sichuan are much more serious than those in neighboring provinces and cities; however, in recent years, this situation has disappeared.
Emergency Decision-Making for Middle Route of South-to-North Water Diversion Project Using Case-Based Reasoning and Prospect Theory
Authors: Li Feng , Zhang Pengchao , Huang Xin , Sun Jiabin , Li Qian
Published: October 2022

The middle route of the South-to-North Water Diversion Project is one of the crucial frameworks of China’s water network and an essential channel for water resource allocation in North China. The safe operation of the project has a huge impact on regional economic development, social stability and other aspects. The objectives of this research are to improve the disposal efficiency of all kinds of accidents during the operation of the Middle Route of the South-to-North Water Diversion Project, reduce people’s property losses and ensure the safety of water supply along the line. This paper will put forward a new emergency decision-making method based on case-based reasoning technology and prospect theory. The method is divided into two parts: (1) Collecting the historical case information and building the case library. The frame representation in the case-based reasoning technology is used to describe the characteristics of historical cases and adopt the two-level method of historical cases fast retrieval and similarity fuzzy matching retrieval to complete the preliminary selection of emergency plans; (2) The decision-making and optimization model of disposal plans based on prospect theory, namely, using the value function and probability weight classification to measure the prospect value of similar schemes and selecting the optimal disposal scheme, in order to improve the science and rationality of the decision-making results. Finally, examples are taken to verify the feasibility and effectiveness of the method.
Optimal Multi-Objective Power Scheduling of a Residential Microgrid Considering Renewable Sources and Demand Response Technique
Authors: Gamil Mahmoud M. , Ueda Soichirou , Nakadomari Akito , Konneh Keifa Vamba , Senjyu Tomonobu , Hemeida Ashraf M. , Lotfy Mohammed Elsayed
Published: October 2022

Microgrid optimization is one of the most promising solutions to power system issues and new city electrification. This paper presents a strategy for optimal power scheduling of a residential microgrid depending on renewable generating sources and hydrogen power. Five scenarios of the microgrid are introduced to show the effect of using biomass energy and a seawater electrolyzer on microgrid cost and CO2 emissions. Time of use demand response is applied to reshape the electric load demand and decrease the dependence on grid power. The obtained results from the multi-objective optimization verify that biomass has a significant role in minimizing the cost and CO2 emissions; the cost is decreased by 37.9% when comparing scenarios with and without biomass. Besides, the FC integration with seawater electrolyzer and tanks reduces the microgrid emissions by around 40%.
Environmental Regulation and Sustainable Growth of Enterprise Value: Mediating Effect Analysis Based on Technological Innovation
Authors: Qian Jingjing , Chen Chao , Zhong Yun
Published: October 2022

This research aims to analyze the nonlinear relationship among environmental regulation, technology innovation and enterprise value and provide a micro level of enterprise view on environmental regulation. Taking 1714 A-share listed companies in China’s manufacturing industry from 2017 to 2020, a panel regression model was conducted to explore how environmental regulation influences enterprise value. The empirical research results show that: (1) the total effect of environmental regulation on enterprise value is U-shaped and that the technological innovation of enterprises has a partial intermediary effect between environmental regulation and enterprise value; (2) financial flexibility can significantly mitigate the impact of environmental regulations on enterprise value. This study provides a micro-level view of the influencing effect of environmental regulation on enterprise value.
Image-Analysis-Based Approach for Identification of Air Cooler Heat Transfer Degradation during Frosting Process
Authors: Jakończuk Paweł , Śmierciew Kamil , Gagan Jerzy , Butrymowicz Dariusz
Published: October 2022

Fin-and-tube heat exchangers have been extensively used in many fields, especially in heat, ventilation, air-conditioning, and refrigeration systems. In the case of the operation of a fin-and-tube heat exchanger as an air cooler, frost formation is an important effect that should be taken into account. The frost accumulation process is undesirable since it deteriorates heat transfer due to the insulation of the frost layer as well as causing excessive pressure loss. The analysis of the effect of the frosting process on a fin-and-tube air cooler performance is presented in this paper. Based on long-term experimental investigations applied to the air cooler in a cold storage chamber, the general degradation of the heat exchanger performance is discussed. The influence of frost on the cooling capacity, by-pass factor, and thermal resistance is analysed. The temperature distribution of the air passing through the air cooler before and after the defrosting process is presented and discussed. A method for the assessment of the amount of frost formed at the air cooler surface, based on visualisation of the air cooler during operation and synchronised with the thermal measurements, is developed. The results show that the frosting process causes deterioration of the cooling capacity by up to 40% in the analysed case. Correlation is demonstrated between frost formation and heat transfer degradation in the air cooler.
Constitutive Behaviour of a Clay Stabilised with Alkali-Activated Cement Based on Blast Furnace Slag
Authors: Corrêa-Silva Manuela , Cristelo Nuno , Rouainia Mohamed , Araújo Nuno , Miranda Tiago
Published: October 2022

Alkaline cements have been extensively tested for soil stabilisation in the last decade. However, only a few studies have focused on the assessment of such performance by establishing the constitutive behaviour of the cement. In this paper, we focus on the mechanical behaviour, using triaxial testing of a clay with high water content stabilised with an alkali-activated binder and the subsequent prediction of the experimental stress–strain response using a kinematic hardening constitutive model initially developed for natural clays. Monotonic consolidated undrained triaxial tests were conducted on reconstituted and stabilised clay specimens cured for 28 days to evaluate the effects of cementation on the overall shear behaviour. Alkali-activated binder was synthetised from blast furnace slag and sodium hydroxide. Scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and X-ray diffraction (XRD) were performed to study the microstructure, whereas leachate analyses were performed after 28 and 90 days of curing to investigate the contamination potential. The main product formed was calcium aluminosilicate hydrate (C-A-S-H) with a low CaO/SiO2 ratio, and no risk of soil contamination was found. The compressibility and undrained shear strength in the pre-yield state was found to be independent of the initial mean effective stress (p’0), unlike what was observed in the post-yield state, where the shear strength seemed to be affected by p’0. The model provided reliable predictions of the experimental results and captured the main features of the artificially cemented clay for the tested p’0 range. Such studies are fundamental to establish adequate confidence in such alternative binders—an essential aspect if their use is to become widespread in the near future.
Comparative Study of Artificial Neural Network and Random Forest Model for Susceptibility Assessment of Landslides Induced by Earthquake in the Western Sichuan Plateau, China
Authors: Kamal Mustafa , Zhang Baolei , Cao Jianfei , Zhang Xin , Chang Jun
Published: October 2022

Earthquake-induced landslides are one of the most dangerous secondary disasters in mountainous areas throughout the world. The nowcasting of coseismic landslides is crucial for planning land management, development, and urbanization in mountainous areas. Taking Wenchuan County in Western Sichuan Plateau (WPS) as the study area, a landslide inventory was built using historical records. Herein, eight causative factors were selected for a library of factors, and then a landslide susceptibility assessment (LSA) was performed based on the machine learning techniques of Random Forest (RF) and Artificial Neural Network (ANN) models, respectively. The prediction abilities of the above two LSM models were assessed using the area under curve (AUC) value of the receiver operating characteristics (ROC) curve, precision, recall ratio, accuracy, and specificity. The performances of both machine learning techniques were found to be excellent, but RF outperformed in accuracy. There were still some differences between the models’ performances shown by the results: RF (AUC = 0.966) outperformed ANN (AUC = 0.914). The RF model demonstrated a higher degree of correlation between the areas classified as very low and high susceptibility in comparison to the ANN model. The results provided a theoretical framework upon which machine learning applications could be applied (e.g., RF and ANN), a reliable and low-cost tool to assess landslide susceptibility. This comparative study will provide a useful description of earthquake-induced landslides in the study area, which can be used to anticipate the features of landslides in the future, and have played a very important role in proper anthropogenic activities, resource management, and infrastructural development of the mountainous areas.