Canhui Cheng, Zhong Xing, Lin Ye, Junyue Yang, Zhuoming Xie
Small-scale agroforestry patches possess irreplaceable value compared to large-scale patches. In southwestern mountainous cities of China, the complex terrain and urbanization have led to the presence of numerous small, fragmented agroforestry patches around urban areas. These patches serve as crucial habitats for endemic species and provide essential space for wild food sources, thereby contributing to a range of ecosystem services. Consequently, their proper conservation and utilization planning are of paramount importance. This study investigates the transformation characteristics of landscape patterns of mountainous small-scale agroforestry patches and their constituent elements across urban–rural gradients, identifying the driving factors behind these transformations to support conservation and utilization planning. From an urban–rural gradient perspective, four directional transects were selected and divided into uniform sample grids. Using Fragstats 4.3, landscape indices of small-scale agroforestry patches were calculated, analyzing the transformation characteristics of these patches and their elements across different gradients. Spearman correlation coefficients in SPSS were employed to assess the influence of terrain and relevant anthropogenic factors on the transformation of agroforestry patches. The findings reveal the following: (1) Small-scale agroforestry patches and their elements exhibit similar patterns in terms of size, fragmentation, dispersion, and connectivity, showing an “increasing trend in size and connectivity, decreasing fragmentation, and fluctuating dispersion” from urban centers to natural areas, with slight variations in orchard patches. However, patch cohesion and shape complexity display nonlinear differentiated transformation characteristics. (2) Overall, small-scale agroforestry patches are significantly influenced by anthropogenic construction factors, with the landscape pattern of forest patches notably affected by terrain factors. (3) Across urban–rural gradient zones, the landscape patterns of small-scale agroforestry patches in urban centers, suburbs, and rural natural areas are more affected by terrain factors, whereas those in urban construction zones are significantly influenced by anthropogenic construction factors. The findings of this study provide a scientific basis for the conservation and planning of mountainous small-scale agroforestry patches.
{"title":"Characteristics and Influencing Factors of Landscape Pattern Gradient Transformation of Small-Scale Agroforestry Patches in Mountain Cities","authors":"Canhui Cheng, Zhong Xing, Lin Ye, Junyue Yang, Zhuoming Xie","doi":"10.3390/su16156322","DOIUrl":"https://doi.org/10.3390/su16156322","url":null,"abstract":"Small-scale agroforestry patches possess irreplaceable value compared to large-scale patches. In southwestern mountainous cities of China, the complex terrain and urbanization have led to the presence of numerous small, fragmented agroforestry patches around urban areas. These patches serve as crucial habitats for endemic species and provide essential space for wild food sources, thereby contributing to a range of ecosystem services. Consequently, their proper conservation and utilization planning are of paramount importance. This study investigates the transformation characteristics of landscape patterns of mountainous small-scale agroforestry patches and their constituent elements across urban–rural gradients, identifying the driving factors behind these transformations to support conservation and utilization planning. From an urban–rural gradient perspective, four directional transects were selected and divided into uniform sample grids. Using Fragstats 4.3, landscape indices of small-scale agroforestry patches were calculated, analyzing the transformation characteristics of these patches and their elements across different gradients. Spearman correlation coefficients in SPSS were employed to assess the influence of terrain and relevant anthropogenic factors on the transformation of agroforestry patches. The findings reveal the following: (1) Small-scale agroforestry patches and their elements exhibit similar patterns in terms of size, fragmentation, dispersion, and connectivity, showing an “increasing trend in size and connectivity, decreasing fragmentation, and fluctuating dispersion” from urban centers to natural areas, with slight variations in orchard patches. However, patch cohesion and shape complexity display nonlinear differentiated transformation characteristics. (2) Overall, small-scale agroforestry patches are significantly influenced by anthropogenic construction factors, with the landscape pattern of forest patches notably affected by terrain factors. (3) Across urban–rural gradient zones, the landscape patterns of small-scale agroforestry patches in urban centers, suburbs, and rural natural areas are more affected by terrain factors, whereas those in urban construction zones are significantly influenced by anthropogenic construction factors. The findings of this study provide a scientific basis for the conservation and planning of mountainous small-scale agroforestry patches.","PeriodicalId":509360,"journal":{"name":"Sustainability","volume":"78 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141807972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ana Rita Ferreira, Eduardo Noronha, Ricardo Sousa, G. Serra
The children’s toy market is increasingly dominated by products that rely heavily on visual appeal. This article presents the development of ‘bumpi’, a cork toy specially developed for young children who experience visual impairments or blindness. Research was conducted about these children’s needs and the existing assistive products for them in the market. This research revealed that they often face developmental challenges, including delays in achieving key milestones such as crawling and walking, which happens because blind and visually impaired children are less confident to moving and exploring. A significant gap in the market for toys and assistive devices for blind young children was identified. Bumpi aims to fill such a gap. It is designed to stimulate and foster the earlier development of motor skills in children between one and five years old, leading to greater independence. This toy enhances sensory experiences through touch and sound to stimulate children’s urge to move. The toy set includes a puzzle-like mat, a toy cart that follows a predefined path, building blocks for constructing a ramp, and sensory balls that emit sounds when they move. Agglomerated cork, chosen for its unique properties such as lightness, durability and its hypoallergenic nature, is the primary material used. Furthermore, it is not only safe and comfortable for children to handle but also offers great stimulation to their senses. In addition, this is a sustainable material that offers several benefits for the toy industry.
{"title":"A Sustainable Cork Toy That Promotes the Development of Blind and Visually Impaired Young Children","authors":"Ana Rita Ferreira, Eduardo Noronha, Ricardo Sousa, G. Serra","doi":"10.3390/su16156312","DOIUrl":"https://doi.org/10.3390/su16156312","url":null,"abstract":"The children’s toy market is increasingly dominated by products that rely heavily on visual appeal. This article presents the development of ‘bumpi’, a cork toy specially developed for young children who experience visual impairments or blindness. Research was conducted about these children’s needs and the existing assistive products for them in the market. This research revealed that they often face developmental challenges, including delays in achieving key milestones such as crawling and walking, which happens because blind and visually impaired children are less confident to moving and exploring. A significant gap in the market for toys and assistive devices for blind young children was identified. Bumpi aims to fill such a gap. It is designed to stimulate and foster the earlier development of motor skills in children between one and five years old, leading to greater independence. This toy enhances sensory experiences through touch and sound to stimulate children’s urge to move. The toy set includes a puzzle-like mat, a toy cart that follows a predefined path, building blocks for constructing a ramp, and sensory balls that emit sounds when they move. Agglomerated cork, chosen for its unique properties such as lightness, durability and its hypoallergenic nature, is the primary material used. Furthermore, it is not only safe and comfortable for children to handle but also offers great stimulation to their senses. In addition, this is a sustainable material that offers several benefits for the toy industry.","PeriodicalId":509360,"journal":{"name":"Sustainability","volume":"61 43","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141807179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Z. Kaliniewicz, Stanisław Konopka, Z. Krzysiak, Paweł Tylek
The aim of this study was to measure the physical attributes of seeds of selected lilac species and to describe the correlations between these properties and seed mass for seed processing and treatment. Basic physical parameters were measured in the seeds of five lilac species and the results were used to calculate aspect ratios describing seed shape and size. The average values of the measured properties ranged from 3.57 to 5.98 m s−1 for terminal velocity, from 6.20 to 9.61 mm for seed length, from 2.19 to 3.94 mm for seed width, from 0.85 to 1.21 mm for seed thickness, from 5.9 to 19.2 mg for seed mass, and from 32° to 44° for the angle of external friction. Seed mass was bound by the strongest correlations with terminal velocity (Amur lilac, Hungarian lilac, and Pekin lilac), thickness (broadleaf lilac), and width (Japanese tree lilac). Seed thickness followed by terminal velocity were the primary distinguishing features of lilac seeds. Therefore, lilac seeds should be sorted with the use of sieve separators with longitudinal openings or pneumatic separators. These devices effectively sort lilac seeds into fractions with uniform seed mass, which can facilitate the propagation of lilacs in nurseries and the production of high-quality seedlings, thus promoting the sustainable use of natural resources and production materials. In medium-sized and large seed fractions, the coefficient of variation of seed mass can be decreased by up to 50% relative to unsorted seeds.
{"title":"An Evaluation of the Physical Characteristics of Seeds of Selected Lilac Species for Seed Sorting Purposes and Sustainable Forest Management","authors":"Z. Kaliniewicz, Stanisław Konopka, Z. Krzysiak, Paweł Tylek","doi":"10.3390/su16156340","DOIUrl":"https://doi.org/10.3390/su16156340","url":null,"abstract":"The aim of this study was to measure the physical attributes of seeds of selected lilac species and to describe the correlations between these properties and seed mass for seed processing and treatment. Basic physical parameters were measured in the seeds of five lilac species and the results were used to calculate aspect ratios describing seed shape and size. The average values of the measured properties ranged from 3.57 to 5.98 m s−1 for terminal velocity, from 6.20 to 9.61 mm for seed length, from 2.19 to 3.94 mm for seed width, from 0.85 to 1.21 mm for seed thickness, from 5.9 to 19.2 mg for seed mass, and from 32° to 44° for the angle of external friction. Seed mass was bound by the strongest correlations with terminal velocity (Amur lilac, Hungarian lilac, and Pekin lilac), thickness (broadleaf lilac), and width (Japanese tree lilac). Seed thickness followed by terminal velocity were the primary distinguishing features of lilac seeds. Therefore, lilac seeds should be sorted with the use of sieve separators with longitudinal openings or pneumatic separators. These devices effectively sort lilac seeds into fractions with uniform seed mass, which can facilitate the propagation of lilacs in nurseries and the production of high-quality seedlings, thus promoting the sustainable use of natural resources and production materials. In medium-sized and large seed fractions, the coefficient of variation of seed mass can be decreased by up to 50% relative to unsorted seeds.","PeriodicalId":509360,"journal":{"name":"Sustainability","volume":"9 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141809011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Green investments help to create less harmful alternatives and adequate funds that contribute to economic growth, sustainable development, and social well-being. The paper aims to evaluate decision making on the choice of green investments based on multi-criteria decision making (MCDM). The applied methods are empirical and analytical based on the study of the literature, multi-criteria modeling, the determination of weights, and the ranking of criteria in deciding the green investment mapping of indicators, and mapping the indicators. The research used groups of indicators that reflect the main characteristics of green growth from the OECD database. The idea is to decide on the best green investment based on green growth criteria, which consist of grouped indicators according to the areas of the green economy rather than according to their values. The results of the Analytical Hierarchy Process (AHP method) showed that half of the investments in the green economy come from public sources (0.51) and the other half are private (0.25) and institutional investors (0.24), while the Best/Worst Method (BWM) revealed that the best criterion for the decision to invest in the green economy is the environmental and resource productivity of the economy, and the worst is the base of natural assets. This paper aims to enable decision-makers to use these results as weights for the overall assessment of green investments in ESG and to simplify the decision-making approach in future analyses.
{"title":"The Importance of Green Investments in Developed Economies—MCDM Models for Achieving Adequate Green Investments","authors":"V. Ristanović, D. Primorac, B. Dorić","doi":"10.3390/su16156341","DOIUrl":"https://doi.org/10.3390/su16156341","url":null,"abstract":"Green investments help to create less harmful alternatives and adequate funds that contribute to economic growth, sustainable development, and social well-being. The paper aims to evaluate decision making on the choice of green investments based on multi-criteria decision making (MCDM). The applied methods are empirical and analytical based on the study of the literature, multi-criteria modeling, the determination of weights, and the ranking of criteria in deciding the green investment mapping of indicators, and mapping the indicators. The research used groups of indicators that reflect the main characteristics of green growth from the OECD database. The idea is to decide on the best green investment based on green growth criteria, which consist of grouped indicators according to the areas of the green economy rather than according to their values. The results of the Analytical Hierarchy Process (AHP method) showed that half of the investments in the green economy come from public sources (0.51) and the other half are private (0.25) and institutional investors (0.24), while the Best/Worst Method (BWM) revealed that the best criterion for the decision to invest in the green economy is the environmental and resource productivity of the economy, and the worst is the base of natural assets. This paper aims to enable decision-makers to use these results as weights for the overall assessment of green investments in ESG and to simplify the decision-making approach in future analyses.","PeriodicalId":509360,"journal":{"name":"Sustainability","volume":"36 22","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141809957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
E. Manea, C. Bumbac, L. Dinu, M. Bumbac, C. Nicolescu
With increases in global population and urbanization, the production of Municipal Solid Waste (MSW) is growing rapidly, thus contributing to social and environmental concerns for sustainable waste management. This study addresses the research gap in optimizing composting, hypothesizing that integrating best practices and recent innovations can enhance the efficiency of the process. Data were collected through a systematic review of existing literature using Google Scholar and Scopus databases. The review provides an overview of municipal organic waste composting, outlining its processes, benefits, and challenges with the aim of identifying key area of further improvement and possibilities of adopting recent technological innovations. The analysis emphasized that technological advances in composting, as microbial inoculants or in-vessel composting have greatly improved the efficiency and quality of the resulting compost. However, several challenges remain, including managing contaminants such as heavy metals and microplastics, ensuring the compost quality and safety and addressing socioeconomic barriers that prevent widespread adoption. Moreover, process optimization, environmental and economic evaluation, as well as political and public involvement are essential to unlock the whole potential of composting systems.
随着全球人口和城市化进程的加快，城市固体废物（MSW）的产生量也在迅速增长，从而引发了社会和环境对可持续废物管理的关注。本研究填补了优化堆肥方面的研究空白，并假设将最佳实践与最新创新相结合可以提高堆肥过程的效率。通过使用 Google Scholar 和 Scopus 数据库对现有文献进行系统回顾，收集了相关数据。综述概述了城市有机废物堆肥，概述了其流程、优点和挑战，旨在确定进一步改进的关键领域和采用最新技术创新的可能性。分析强调，堆肥技术的进步，如微生物接种剂或容器内堆肥，大大提高了堆肥的效率和质量。然而，仍然存在一些挑战，包括管理重金属和微塑料等污染物、确保堆肥质量和安全以及解决阻碍广泛采用的社会经济障碍。此外，工艺优化、环境和经济评估以及政治和公众参与对于释放堆肥系统的全部潜力至关重要。
{"title":"Composting as a Sustainable Solution for Organic Solid Waste Management: Current Practices and Potential Improvements","authors":"E. Manea, C. Bumbac, L. Dinu, M. Bumbac, C. Nicolescu","doi":"10.3390/su16156329","DOIUrl":"https://doi.org/10.3390/su16156329","url":null,"abstract":"With increases in global population and urbanization, the production of Municipal Solid Waste (MSW) is growing rapidly, thus contributing to social and environmental concerns for sustainable waste management. This study addresses the research gap in optimizing composting, hypothesizing that integrating best practices and recent innovations can enhance the efficiency of the process. Data were collected through a systematic review of existing literature using Google Scholar and Scopus databases. The review provides an overview of municipal organic waste composting, outlining its processes, benefits, and challenges with the aim of identifying key area of further improvement and possibilities of adopting recent technological innovations. The analysis emphasized that technological advances in composting, as microbial inoculants or in-vessel composting have greatly improved the efficiency and quality of the resulting compost. However, several challenges remain, including managing contaminants such as heavy metals and microplastics, ensuring the compost quality and safety and addressing socioeconomic barriers that prevent widespread adoption. Moreover, process optimization, environmental and economic evaluation, as well as political and public involvement are essential to unlock the whole potential of composting systems.","PeriodicalId":509360,"journal":{"name":"Sustainability","volume":"93 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141807802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study explores students’ perceptions of the advantages of academic campuses as the location of studies that involve social interaction, with a focus on the role of social interaction in the learning experience. The study examines students’ perspectives approximately five years after the time of COVID-19, when online studies have become more prevalent. Participants were 1048 students from several departments at two academic institutions, a university and a college, of whom 39.1% (407) were male and 60.9% (633) female. The age of the respondents ranged from 18–23 (30.4%), 24–30 (60.3%), and 31–63 (9.3%). Among all respondents, 64.2% were studying social sciences and 35.8% engineering. A mixed methods research design was employed, combining qualitative and quantitative analysis. Structural equation modeling (SEM) was utilized to test the goodness-of-fit of the presented model. The research findings showed that measures of comprehensibility, concentration, and contact with the lecturer enhance learning in a physical classroom more than learning via online teaching. However, interaction with peers does not improve one’s studies at all and is not a sufficient reason to attend classes. These findings are based on analysis of survey responses, after applying SEM to test the goodness-of-fit of the presented model. The final model showed a good fit: CMIN/DF = 1.26, CFI = 0.999, NFI = 0.996, TLI = 0.994, RMSEA = 0.02. The findings of this study may hold importance for leaders of higher education when endeavoring to plan teaching, learning, and evaluation at academic institutions and for shaping the academic campus as a significant educational space in the future. Moreover, the findings may have important implications for education management strategies towards sustainable development. Higher education institutions need to re-evaluate the role of the physical campus and social interaction within it in the era of remote learning.
{"title":"Who Needs Academic Campuses? Are There Advantages to Studying on an Academic Campus Considering the Experience of Online Teaching Five Years after COVID-19?","authors":"N. Davidovitch, Eyal Eckhaus","doi":"10.3390/su16156324","DOIUrl":"https://doi.org/10.3390/su16156324","url":null,"abstract":"This study explores students’ perceptions of the advantages of academic campuses as the location of studies that involve social interaction, with a focus on the role of social interaction in the learning experience. The study examines students’ perspectives approximately five years after the time of COVID-19, when online studies have become more prevalent. Participants were 1048 students from several departments at two academic institutions, a university and a college, of whom 39.1% (407) were male and 60.9% (633) female. The age of the respondents ranged from 18–23 (30.4%), 24–30 (60.3%), and 31–63 (9.3%). Among all respondents, 64.2% were studying social sciences and 35.8% engineering. A mixed methods research design was employed, combining qualitative and quantitative analysis. Structural equation modeling (SEM) was utilized to test the goodness-of-fit of the presented model. The research findings showed that measures of comprehensibility, concentration, and contact with the lecturer enhance learning in a physical classroom more than learning via online teaching. However, interaction with peers does not improve one’s studies at all and is not a sufficient reason to attend classes. These findings are based on analysis of survey responses, after applying SEM to test the goodness-of-fit of the presented model. The final model showed a good fit: CMIN/DF = 1.26, CFI = 0.999, NFI = 0.996, TLI = 0.994, RMSEA = 0.02. The findings of this study may hold importance for leaders of higher education when endeavoring to plan teaching, learning, and evaluation at academic institutions and for shaping the academic campus as a significant educational space in the future. Moreover, the findings may have important implications for education management strategies towards sustainable development. Higher education institutions need to re-evaluate the role of the physical campus and social interaction within it in the era of remote learning.","PeriodicalId":509360,"journal":{"name":"Sustainability","volume":"12 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141808593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Max Cichocki, Eva Buchmayer, Fabian Theurl, Christoph Schmied
In a sustainable circular economy, the composting of organic waste plays an essential role. This paper presents the design and technical development of a smart and self-driving compost turner. The architecture of the hardware, including the sensor setup, navigation module, and control module, is presented. Furthermore, the methodological development using model-based systems engineering of the architecture of concepts, models, and their subsequent software integration in ROS is discussed. The validation and verification of the overall system are carried out in an industrial environment using three scenarios. The capabilities of the compost turner are demonstrated by requiring it to autonomously follow pre-defined trajectories at the composting plant and perform required composting tasks. The results prove that the autonomous compost turner can perform the required activities. In addition to autonomous driving, the compost turner is capable of intelligent processing of the compost data and of transferring, visualizing, and storing them in a cloud server. The overall system of the intelligent, autonomous compost turner can provide essential leverage for improving sustainability efforts, thus contributing substantially to an environmentally friendly and sustainable future.
{"title":"Design, Technical Development, and Evaluation of an Autonomous Compost Turner: An Approach towards Smart Composting","authors":"Max Cichocki, Eva Buchmayer, Fabian Theurl, Christoph Schmied","doi":"10.3390/su16156347","DOIUrl":"https://doi.org/10.3390/su16156347","url":null,"abstract":"In a sustainable circular economy, the composting of organic waste plays an essential role. This paper presents the design and technical development of a smart and self-driving compost turner. The architecture of the hardware, including the sensor setup, navigation module, and control module, is presented. Furthermore, the methodological development using model-based systems engineering of the architecture of concepts, models, and their subsequent software integration in ROS is discussed. The validation and verification of the overall system are carried out in an industrial environment using three scenarios. The capabilities of the compost turner are demonstrated by requiring it to autonomously follow pre-defined trajectories at the composting plant and perform required composting tasks. The results prove that the autonomous compost turner can perform the required activities. In addition to autonomous driving, the compost turner is capable of intelligent processing of the compost data and of transferring, visualizing, and storing them in a cloud server. The overall system of the intelligent, autonomous compost turner can provide essential leverage for improving sustainability efforts, thus contributing substantially to an environmentally friendly and sustainable future.","PeriodicalId":509360,"journal":{"name":"Sustainability","volume":"20 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141806190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Alsulaili, Noor Aboramyah, Nasser Alenezi, M. Alkhalidi
This study investigated the impact of meteorological factors on electricity consumption in arid regions, characterized by extreme temperatures and high humidity. Statistical approaches such as multiple linear regression (MLR) and multiplicative time series (MTS), alongside the advanced machine learning method Extreme Gradient Boosting (XGBoost) were utilized to analyze historical consumption data. The models developed were rigorously evaluated using established measures such as the Coefficient of Determination (R2), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE). The performance of the models was highly accurate, with regression-type models consistently achieving an R2 greater than 0.9. Additionally, other metrics such as RMSE and MAPE demonstrated exceptionally low values relative to the overall data scale, reinforcing the models’ precision and reliability. The analysis not only highlights the significant meteorological drivers of electricity consumption but also assesses the models’ effectiveness in managing seasonal and irregular variations. These findings offer crucial insights for improving energy management and promoting sustainability in similar climatic regions.
{"title":"Advancing Electricity Consumption Forecasts in Arid Climates through Machine Learning and Statistical Approaches","authors":"A. Alsulaili, Noor Aboramyah, Nasser Alenezi, M. Alkhalidi","doi":"10.3390/su16156326","DOIUrl":"https://doi.org/10.3390/su16156326","url":null,"abstract":"This study investigated the impact of meteorological factors on electricity consumption in arid regions, characterized by extreme temperatures and high humidity. Statistical approaches such as multiple linear regression (MLR) and multiplicative time series (MTS), alongside the advanced machine learning method Extreme Gradient Boosting (XGBoost) were utilized to analyze historical consumption data. The models developed were rigorously evaluated using established measures such as the Coefficient of Determination (R2), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE). The performance of the models was highly accurate, with regression-type models consistently achieving an R2 greater than 0.9. Additionally, other metrics such as RMSE and MAPE demonstrated exceptionally low values relative to the overall data scale, reinforcing the models’ precision and reliability. The analysis not only highlights the significant meteorological drivers of electricity consumption but also assesses the models’ effectiveness in managing seasonal and irregular variations. These findings offer crucial insights for improving energy management and promoting sustainability in similar climatic regions.","PeriodicalId":509360,"journal":{"name":"Sustainability","volume":"17 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141806701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Qi Da, Ying Chen, Bing Dai, Danli Li, Longqiang Fan
This paper proposes a new method for predicting slope safety factors that combines convolutional neural networks (CNNs), gated recurrent units (GRUs), and attention mechanisms. This method can better capture long-term dependencies, enhance the ability to model sequential data, and reduce the dependence on noisy data, thereby reducing the risk of overfitting. The goal is to improve the accuracy of slope safety factor prediction, detect potential slope stability issues in a timely manner, and take corresponding preventive and control measures to ensure the long-term stability and safety of infrastructure and promote sustainable development. The Pearson correlation coefficient is used to analyze the relationship between the target safety factor and the collected parameters. A one-dimensional CNN layer is used to extract high-dimensional features from the input data, and then a GRU layer is used to capture the correlation between parameters in the sequence. Finally, an attention mechanism is introduced to optimize the weights of the GRU output, enhance the influence of key information, and optimize the overall prediction model. The performance of the proposed model is evaluated using metrics such as the mean absolute error (MAE), mean absolute percentage error (MAPE), mean squared error (MSE), root-mean-square error (RMSE), and R2. The results show that the CNN-GRU-SE model outperforms the GRU, CNN, and CNN-GRU models in terms of prediction accuracy for slope safety factors, with improvements of 4%, 2%, and 1%, respectively. Overall, the research in this paper makes valuable contributions to the field of slope safety factor prediction, and the proposed method also has the potential to be extended to other time-series prediction fields, providing support for a wide range of engineering applications and further promoting the realization of sustainable development.
{"title":"Prediction of Slope Safety Factor Based on Attention Mechanism-Enhanced CNN-GRU","authors":"Qi Da, Ying Chen, Bing Dai, Danli Li, Longqiang Fan","doi":"10.3390/su16156333","DOIUrl":"https://doi.org/10.3390/su16156333","url":null,"abstract":"This paper proposes a new method for predicting slope safety factors that combines convolutional neural networks (CNNs), gated recurrent units (GRUs), and attention mechanisms. This method can better capture long-term dependencies, enhance the ability to model sequential data, and reduce the dependence on noisy data, thereby reducing the risk of overfitting. The goal is to improve the accuracy of slope safety factor prediction, detect potential slope stability issues in a timely manner, and take corresponding preventive and control measures to ensure the long-term stability and safety of infrastructure and promote sustainable development. The Pearson correlation coefficient is used to analyze the relationship between the target safety factor and the collected parameters. A one-dimensional CNN layer is used to extract high-dimensional features from the input data, and then a GRU layer is used to capture the correlation between parameters in the sequence. Finally, an attention mechanism is introduced to optimize the weights of the GRU output, enhance the influence of key information, and optimize the overall prediction model. The performance of the proposed model is evaluated using metrics such as the mean absolute error (MAE), mean absolute percentage error (MAPE), mean squared error (MSE), root-mean-square error (RMSE), and R2. The results show that the CNN-GRU-SE model outperforms the GRU, CNN, and CNN-GRU models in terms of prediction accuracy for slope safety factors, with improvements of 4%, 2%, and 1%, respectively. Overall, the research in this paper makes valuable contributions to the field of slope safety factor prediction, and the proposed method also has the potential to be extended to other time-series prediction fields, providing support for a wide range of engineering applications and further promoting the realization of sustainable development.","PeriodicalId":509360,"journal":{"name":"Sustainability","volume":"58 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141809489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The braided cord vineyard management system of the La Orotava Valley (Canary Islands, Spain) is a unique technique in the world that has been developed in the northern area of the island of Tenerife since the introduction of the first strains from Europe after the conquest of the Canary Islands and that synthesizes the unique wine cultural landscape of the territory. The future sustainability of this landscape seems to be inescapably linked to policies in favour of environmental, social and economic development, primarily through wine tourism. To do this, the methodology addresses the opinions of 16 in-depth interviews of key informants from the sector to understand this cultural landscape’s degree of use and enhancement. The results indicate significant progress in the revaluation and sustainability of the braided cord system (BCS) as part of the public–private strategy in search of its recognition as a BIC. Likewise, the winery sector recognizes the need to move towards a management model for the wine sector of the La Orotava Valley, where wine tourism has a more significant role, that seems to be closed based on the projects and initiatives under development.
{"title":"The Potential of Wine Tourism in the Innovation Processes of Tourism Experiences in the Canary Islands—An Approach to the Case of the Canary Brand","authors":"Agustín Dorta Rodriguez, J. Quintela","doi":"10.3390/su16156314","DOIUrl":"https://doi.org/10.3390/su16156314","url":null,"abstract":"The braided cord vineyard management system of the La Orotava Valley (Canary Islands, Spain) is a unique technique in the world that has been developed in the northern area of the island of Tenerife since the introduction of the first strains from Europe after the conquest of the Canary Islands and that synthesizes the unique wine cultural landscape of the territory. The future sustainability of this landscape seems to be inescapably linked to policies in favour of environmental, social and economic development, primarily through wine tourism. To do this, the methodology addresses the opinions of 16 in-depth interviews of key informants from the sector to understand this cultural landscape’s degree of use and enhancement. The results indicate significant progress in the revaluation and sustainability of the braided cord system (BCS) as part of the public–private strategy in search of its recognition as a BIC. Likewise, the winery sector recognizes the need to move towards a management model for the wine sector of the La Orotava Valley, where wine tourism has a more significant role, that seems to be closed based on the projects and initiatives under development.","PeriodicalId":509360,"journal":{"name":"Sustainability","volume":"78 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141807979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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