bluuebunny/crossref_metadata_2025 huggingface dataset:
Combining “Deep Learning” and Physically Constrained Neural Networks to Derive Complex Glaciological Change Processes from Modern High-Resolution Satellite Imagery: Application of the GEOCLASS-Image System to Create VarioCNN for Glacier Surges
Authors: Herzfeld Ute C. , Hessburg Lawrence J. , Trantow Thomas M. , Hayes Adam N.
Published: May 2024

The objectives of this paper are to investigate the trade-offs between a physically constrained neural network and a deep, convolutional neural network and to design a combined ML approach (“VarioCNN”). Our solution is provided in the framework of a cyberinfrastructure that includes a newly designed ML software, GEOCLASS-image (v1.0), modern high-resolution satellite image data sets (Maxar WorldView data), and instructions/descriptions that may facilitate solving similar spatial classification problems. Combining the advantages of the physically-driven connectionist-geostatistical classification method with those of an efficient CNN, VarioCNN provides a means for rapid and efficient extraction of complex geophysical information from submeter resolution satellite imagery. A retraining loop overcomes the difficulties of creating a labeled training data set. Computational analyses and developments are centered on a specific, but generalizable, geophysical problem: The classification of crevasse types that form during the surge of a glacier system. A surge is a glacial catastrophe, an acceleration of a glacier to typically 100–200 times its normal velocity. GEOCLASS-image is applied to study the current (2016-2024) surge in the Negribreen Glacier System, Svalbard. The geophysical result is a description of the structural evolution and expansion of the surge, based on crevasse types that capture ice deformation in six simplified classes.
Improved Classification of Coastal Wetlands in Yellow River Delta of China Using ResNet Combined with Feature-Preferred Bands Based on Attention Mechanism
Authors: Li Yirong , Yu Xiang , Zhang Jiahua , Zhang Shichao , Wang Xiaopeng , Kong Delong , Yao Lulu , Lu He
Published: May 2024

The Yellow River Delta wetlands in China belong to the coastal wetland ecosystem, which is one of the youngest and most characteristic wetlands in the world. The Yellow River Delta wetlands are constantly changed by inland sediment and the influence of waves and storm surges, so the accurate classification of the coastal wetlands in the Yellow River Delta is of great significance for the rational utilization, development and protection of wetland resources. In this study, the Yellow River Delta sentinel-2 multispectral data were processed by super-resolution synthesis, and the feature bands were optimized. The optimal feature-band combination scheme was screened using the OIF algorithm. A deep learning model attention mechanism ResNet based on feature optimization with attention mechanism integration into the ResNet network is proposed. Compared with the classical machine learning model, the AM_ResNet model can effectively improve the classification accuracy of the wetlands in the Yellow River Delta. The overall accuracy was 94.61% with a Kappa of 0.93, and they were improved by about 6.99% and 0.1, respectively, compared with the best-performing Random Forest Classification in machine learning. The results show that the method can effectively improve the classification accuracy of the wetlands in the Yellow River Delta.
Synthetic Aperture Radar Image Change Detection Based on Principal Component Analysis and Two-Level Clustering
Authors: Li Liangliang , Ma Hongbing , Zhang Xueyu , Zhao Xiaobin , Lv Ming , Jia Zhenhong
Published: May 2024

Synthetic aperture radar (SAR) change detection provides a powerful tool for continuous, reliable, and objective observation of the Earth, supporting a wide range of applications that require regular monitoring and assessment of changes in the natural and built environment. In this paper, we introduce a novel SAR image change detection method based on principal component analysis and two-level clustering. First, two difference images of the log-ratio and mean-ratio operators are computed, then the principal component analysis fusion model is used to fuse the two difference images, and a new difference image is generated. To incorporate contextual information during the feature extraction phase, Gabor wavelets are used to obtain the representation of the difference image across multiple scales and orientations. The maximum magnitude across all orientations at each scale is then concatenated to form the Gabor feature vector. Following this, a cascading clustering algorithm is developed within this discriminative feature space by merging the first-level fuzzy c-means clustering with the second-level neighbor rule. Ultimately, the two-level combination of the changed and unchanged results produces the final change map. Five SAR datasets are used for the experiment, and the results show that our algorithm has significant advantages in SAR change detection.
Triggering of Land Subsidence in and Surrounding the Hangjiahu Plain Based on Interferometric Synthetic Aperture Radar Monitoring
Authors: He Zixin , Yang Zimeng , Wu Xiaoyong , Zhang Tingting , Song Mengning , Liu Ming
Published: May 2024

In the early stages, uncontrolled groundwater extraction led to the Hangjiahu (HJH) Plain becoming one of the areas with the most severe land subsidence in China. Since the beginning of this century, comprehensive measures have been taken to control the continuous aggravation of large land subsidence patterns in some areas; however, urban land subsidence issues, influenced by various factors, still persist and exhibit complex geographical distribution characteristics. In this study, we utilized Sentinel-1A images and the SBAS-InSAR technique to capture surface deformation over the HJH Plain in Zhejiang from 16 March 2017 to 20 January 2023. Through a comparative analysis with geological conditions, changes in surface mass loading, rainfall and groundwater, and land use types, we discussed the contributions of natural and anthropogenic factors to land subsidence. Augmented with optical remote sensing images and field investigations, we conducted a correlation analysis of the land subsidence status. The preliminary findings suggest that changes in surface mass loading and short-term heavy rainfall under extreme weather conditions can lead to periodic land subsidence changes in the region. Additionally, extensive infrastructure construction triggered by urbanization has resulted in significant and sustained land subsidence deformation. The research findings play an important guiding role in formulating scientifically effective strategies for land subsidence prevention and control, as well as urban planning and construction.
FP-GCN: Frequency Pyramid Graph Convolutional Network for Enhancing Pathological Gait Classification
Authors: Zhao Xiaoheng , Li Jia , Hua Chunsheng
Published: May 2024

Gait, a manifestation of one’s walking pattern, intricately reflects the harmonious interplay of various bodily systems, offering valuable insights into an individual’s health status. However, the current study has shortcomings in the extraction of temporal and spatial dependencies in joint motion, resulting in inefficiencies in pathological gait classification. In this paper, we propose a Frequency Pyramid Graph Convolutional Network (FP-GCN), advocating to complement temporal analysis and further enhance spatial feature extraction. specifically, a spectral decomposition component is adopted to extract gait data with different time frames, which can enhance the detection of rhythmic patterns and velocity variations in human gait and allow a detailed analysis of the temporal features. Furthermore, a novel pyramidal feature extraction approach is developed to analyze the inter-sensor dependencies, which can integrate features from different pathways, enhancing both temporal and spatial feature extraction. Our experimentation on diverse datasets demonstrates the effectiveness of our approach. Notably, FP-GCN achieves an impressive accuracy of 98.78% on public datasets and 96.54% on proprietary data, surpassing existing methodologies and underscoring its potential for advancing pathological gait classification. In summary, our innovative FP-GCN contributes to advancing feature extraction and pathological gait recognition, which may offer potential advancements in healthcare provisions, especially in regions with limited access to medical resources and in home-care environments. This work lays the foundation for further exploration and underscores the importance of remote health monitoring, diagnosis, and personalized interventions.
The Micro-Politics of Artistic Production among Artists with a Migration Background
Authors: Rezanezhad Pishkhani Golnesa , De Backer Mattias
Published: May 2024

Based on two research projects in the Brussels-based artistic workspace and NGO Globe Aroma, this paper shows how artists with a (recent) migration background make sense of the arts and the space in which they are produced. Born out of a need to counter the dominant presence of men in this artistic workspace and create a welcoming environment, textile-making and live radio were used as means of reclaiming space, fostering solidarity, and sharing personal narratives. Textile-making, traditionally associated with domesticity, was repurposed for public exhibition, challenging the dichotomy between private and public spheres. Furthermore, the projects challenged neo-colonial dynamics and traditional research methodologies. While asking which (micro-)political meaning these artists give to their works and practices, the paper also reflects on the cultural thresholds experienced by migrant artists wishing to access hegemonic arts institutions.
Andiroba Oil (Carapa guianensis Aubletet) as a Functionalizing Agent for Titica Vine (Heteropsis flexuosa) Nanofibril Films: Biodegradable Products from Species Native to the Amazon Region
Authors: Paiva Cleyson Santos de , Batista Felipe Gomes , Silva Danillo Wisky , Scatolino Mário Vanoli , Medeiros Dayane Targino de , Mascarenhas Adriano Reis Prazeres , Lago Rafael Carvalho do , Setter Carine , Borges Ianca Oliveira , Tonoli Gustavo Henrique Denzin , Souza Tiago Marcolino de , Mendes Lourival Marin , Bufalino Lina , Alves Junior Francisco Tarcísio , Felix Fabiana da Silva , Dias Marali Vilela
Published: May 2024

The diversity of species in Amazonia is exceptionally vast and unique, and it is of great interest for industry sectors to explore the potential of derivatives with functional properties for packaging applications. This study proposes the functionalization of cellulose micro/nanofibril (MFC/NFC) suspensions from Heteropsis flexuosa with andiroba oil to produce films with packaging potential. MFC/NFC was produced by using mechanical fibrillation from suspensions of H. flexuosa fibers. Proportions of 1, 3, and 5% of andiroba oil were added to make films with concentrations of 1% (m/m). Suspensions with andiroba oil provided greater viscosity, with changes in the physical properties of the films. Functionalization with andiroba oil provided films with lower degradation in water, greater contact angle, and lower wettability despite high permeability to water vapor. The films with 1% andiroba oil showed a hydrophobic characteristic (contact angle > 90°) and greater puncture resistance (6.70 N mm−1). Films with 3% oil showed a more transparent appearance and high biodegradation, while 1% oil generated more opaque films with a higher thermal degradation temperature and high antioxidant activity. It was concluded that films produced from H. flexuosa fibers functionalized with andiroba oil showed packaging potential for light, low-moisture products due to their adequate thermal and barrier characteristics.
Practice of Ecological Aesthetics in Green Production of Bimetallic Carbide Catalyst for Oxygen Reduction Reaction: Integrating Technological Development with Ecological Protection
Authors: Zhang Meiping , Wang Kailun , Yan Zaoxue
Published: May 2024

This work summarizes the disciplinary connotation of ecological aesthetics, discusses the social and philosophical background of the origination of ecological aesthetics, and applies ecological aesthetics to the research on the production processes of catalytic materials. It is found that compared with conventional chemical processes, catalytic materials synthesized using green chemical processes that conform to ecological aesthetics have advantages in raw material cost, energy consumption, environmental protection, operational complexity, and product performance. Based on this, it is proposed that, as green chemical processes develop to a certain extent, they will unify anthropocentrism and ecocentrism, and meet both human needs and ecological protection requirements. The mentioned green chemical processes adopt biomass lotus leaf stems as a carbon source to produce non-noble metal bimetallic carbide (C19Cr7Mo24)-based catalysts for oxygen reduction reaction (ORR). Its initial half-wave potential (E1/2) for catalyzing ORR in an alkaline medium is 0.903 V, the E1/2 retention rate after 50,000 cycles is 98.9%, and its peak power density in H2/O2 fuel cell reaches 1.47 W cm−2, making it one of the most active non-noble metal catalysts for ORR reported so far; its stability is unparalleled.
A Multi-Temporal Analysis on the Dynamics of the Impact of Land Use and Land Cover on NO2 and CO Emissions in Argentina for Sustainable Environmental Management
Authors: Fernández-Maldonado Viviana , Navas Ana Laura , Fabani María Paula , Mazza Germán , Rodríguez Rosa
Published: May 2024

This study presents an analysis of NO2 and CO emissions in Argentina, utilizing remote sensing data. This research aims to determine the spatiotemporal distribution of NO2 and CO emissions from 2019 to 2021. It examines the influence of land use and cover on NO2 and CO emissions using various climatic, anthropic, and natural indicators. The year with the highest CO and NO2 concentration was 2020. NO2 exhibited the highest concentrations in built-up urban areas and croplands, notably impacting the capital city and the northern region of Buenos Aires province. Also, CO concentration was influenced by anthropic variable distances to national route, mining extraction, power plants, airports, and urban index (UI). They were also influenced by climatic and natural variables (Palmer drought index, vapor pressure, maximum environment temperature, wind speed, DEM, humidity, and normalized difference vegetation index (NDVI)) for the different uses and land covers. NO2 concentrations were influenced by anthropic (distance to airports, service stations, open dumpsites, power plants, and factories), climatic, and natural variables (Palmer drought index, vapor pressure, wind speed, and DEM) for the different uses and land cover. This research supports sustainable environmental management by guiding the development of effective emission mitigation strategies for improved community health and well-being.
Enhancing Road Crack Localization for Sustainable Road Safety Using HCTNet
Authors: Yadav Dhirendra Prasad , Sharma Bhisham , Chauhan Shivank , Amin Farhan , Abbasi Rashid
Published: May 2024

Road crack detection is crucial for maintaining and inspecting civil infrastructure, as cracks can pose a potential risk for sustainable road safety. Traditional methods for pavement crack detection are labour-intensive and time-consuming. In recent years, computer vision approaches have shown encouraging results in automating crack localization. However, the classical convolutional neural network (CNN)-based approach lacks global attention to the spatial features. To improve the crack localization in the road, we designed a vision transformer (ViT) and convolutional neural networks (CNNs)-based encoder and decoder. In addition, a gated-attention module in the decoder is designed to focus on the upsampling process. Furthermore, we proposed a hybrid loss function using binary cross-entropy and Dice loss to evaluate the model’s effectiveness. Our method achieved a recall, F1-score, and IoU of 98.54%, 98.07%, and 98.72% and 98.27%, 98.69%, and 98.76% on the Crack500 and Crack datasets, respectively. Meanwhile, on the proposed dataset, these figures were 96.89%, 97.20%, and 97.36%.
Ash Properties and Environmental Impact of Coal and Its Blend with Patent Fuel for Climate Sustainability
Authors: Trkmić Marija , Ćurković Lidija , Ašperger Danijela , Ujević Bošnjak Magdalena , Vinković Vrček Ivana , Matečić Mušanić Sanja
Published: May 2024

Fossil fuels are still widely used today, and exploring more sustainable ways of using coal is crucial. One promising approach is to develop a patented fuel with reduced harmful gas emissions during combustion. This study aims to investigate the properties of the ash produced by burning steam coal mixed with various ratios of patent fuel. The combustion process was carried out using a standard solid fuel boiler with a power output of 70 kW. The ash samples were analyzed using various analytical methods, and ash leaching tests were conducted. The study found that adding patent fuel to coal affects combustion and ash composition. Determining the thermal stability of ash samples showed that adding patent fuel to coal results in decomposition starting earlier and in stronger combustion. The ash produced by patent fuel–coal mixtures contains lower concentrations of Ba, Cr, Ga, Li, Mn, V, and Zn than pure coal combustion. Leaching tests showed that coal ash leachates had higher concentrations of environmental pollutants, such as As, Cd, Co, Mn, Mo, Sb, and U, than patent fuel leachates. Adding patent fuel to coal affects combustion, ash properties, emissions, and disposal. Understanding these implications can help to develop sustainable coal usage and reduce environmental impact.
Internal Force Mechanism of Pisha Sandstone as a Soil Amendment to Improve Sandy Soil Structural Stability in Mu Us Sandy Land
Authors: Liu Zhe , Zhou Lin , Zhang Yang , Han Jichang , Sun Yingying , Zhang Ruiqing , Li Xuxiang , Hu Feinan
Published: May 2024

Compounding Pisha sandstone (PSS) with sandy soil in Mu Us Sandy Land is a viable agronomical measure to effectively reduce soil erosion and improve soil quality due to the complementary characters and structures of the two materials. Aggregate stability is an important indicator to assess sandy soil erosion resistance and quality, which could be largely affected by soil surface electrochemical properties and particle interaction forces. However, the effect of the compound ratio and particle interaction forces on the aggregate stability of compound soils with Pisha sandstone and sandy soil is still unclear. Therefore, in this study, the electrochemical properties, particle interaction forces, and their effects on the aggregate stability of PSS and sandy soil at five volume ratios (0:1, 1:5, 1:2, 1:1, and 1:0) were determined to clarify the internal force mechanism of PSS to increase sandy soil structural stability in a 10-year field experiment. Experiments were measured by a combined method for the determination of surface properties and aggregate water stability. A ten-year field study revealed that the incorporation of Pisha sandstone significantly enhanced the soil organic carbon (SOC) and cation exchange capacity (CEC) (p < 0.05), while the CEC value notably increased from 4.68 to 13.76 cmol·kg−1 (p < 0.05). The soil surface potential (absolute value) and the electric field intensity gradually decreased with the increase in the Pisha sandstone content. For the compound soil particle interaction force, the addition of Pisha sandstone enhanced the van der Waals attraction force, reduced the net repulsive force between compound soil particles, and promoted the agglomeration of aeolian sandy soil. The overall trend of the aggregate breaking strength of compound soils under different addition ratios of PSS was 1:0 > 1:1 > 0:1 > 1:5 > 1:2. When the Pisha sandstone content in the compound soils was <50%, the aggregate stability was mainly influenced by compound soil particle interaction forces, and the interaction force increase was the key reason for the aggregate breakdown. When the Pisha sandstone content in the compound soils was ≥50%, the aggregate stability was affected by the combined effects of the compound soil particle composition and particle interaction forces. These results indicate that PSS addition ratios and particle interaction force are important factors affecting the structural stability of compound soils, in which the volume ratio of PSS to sandy soil of 1:2 is the appropriate ratio. Our study provides some theoretical references for further understanding of the compound soil structure improvement and sandy soil erosion control in Mu Us Sandy Land.
Digital Economy Development and Green Innovation Efficiency from a Two-Stage Innovation Value Chain Perspective
Authors: Fan Danxue , Li Meiyue
Published: May 2024

Resolving the conflict between economic growth and ecological sustainability is crucial when transitioning from traditional economic development towards a sustainable green model. In this context, the super-NSBM model was applied to measure the efficiency of green innovation technology research and development. Additionally, it was applied to measure the efficiency of the green innovation achievement transformation among 30 Chinese provinces. This evaluation was conducted for the period from 2011 to 2021, and it utilized a two-stage innovation value chain perspective. The entropy method was used to comprehensively calculate the digital economy development index, and the impact of digital economy development on the two-stage green innovation effect was empirically explored using SDM. The findings revealed the following: Firstly, both two-stage green innovation efficiency and digital economy development exhibited significant spatial characteristics. Secondly, digital economy development had a positive effect on two-stage green innovation efficiency not only in the local region but also in neighboring regions. This conclusion remained valid throughout a series of robustness tests. Thirdly, in terms of regional heterogeneity, the eastern region and non-resource-based regions had greater digital economy development dividends than the central, western, and resource-based regions; therefore, the effect on two-stage green innovation efficiency was more significant. Lastly, both intellectual property protection and data factor endowment exerted positive moderating effects on the influence of the digital economy on two-stage green innovation efficiency. The conclusions of this research provide a theoretical backing for and empirical proof of the mechanism of digital economy development and its impact on two-stage green innovation efficiency. Policy implications are suggested based on these findings, such as reinforcing digitalization, establishing targeted policies, and fostering a favorable external environment conducive to technological innovation.
Healthy Neighbourhoods Hub (HNH) Framework: A Practical Guide for Fostering Healthy and Inclusive Living in Florence’s Urban Environment
Authors: Macchi Alessia , Busciantella-Ricci Daniele , Caruso Elisa , Setola Nicoletta
Published: May 2024

By 2050, an estimated 69% of the global population will reside in urban areas, underscoring the pivotal role of city neighbourhoods in enhancing quality of life by respecting and accommodating diverse identities and needs. The physical environment of neighbourhoods significantly influences community health and well-being, alongside social factors and access to health services. In Italy, prioritising health-promoting and accessible designs in neighbourhoods can form a solid foundation for urban health strategies. This study introduces a theoretical framework developed for the Healthy Neighbourhoods Hub (HNH) project in Florence, Italy, aiming to enhance health and accessibility across different scales. The HNH framework categorises healthy and inclusive neighbourhoods into 7 themes, 25 general characteristics, and 67 specific attributes, supported by verifiable variables derived from comprehensive research and design tools. This innovative framework addresses the need for multilevel, multidisciplinary approaches, and spatialization efforts to ensure equitable benefits for all community members.
A Novel Hybrid Fuzzy Multiple-Criteria Decision-Making Model for the Selection of the Most Suitable Land Reclamation Variant at Open-Pit Coal Mines
Authors: Dimitrijević Bojan , Šubaranović Tomislav , Stević Željko , Kchaou Mohamed , Alqurashi Faris , Subotić Marko
Published: May 2024

The expansion of the open-pit exploitation of mineral raw materials, and especially the energy resources of fossil fuels, makes open-pit coal mines spatially dominant objects of large mining basins. Exploitation activities are accompanied by negative ecological impacts on the environment, which requires the integral planning, revitalization, reclamation, and rehabilitation of the disturbed area for human use in the post-exploitation period. The post-exploitation remediation and rehabilitation of open-pit mining areas and disposal sites, i.e., space disturbed by mining activities and accompanying facilities, are complex synthetic multidisciplinary multiphase engineering project tasks. In this paper, a hybrid fuzzy MCDM model (Multiple-Criteria Decision-Making) was developed for the selection of a reclamation solution for the Tamnava-West Field open-pit mine. IMF SWARA (Improved Fuzzy Stepwise Weight Assessment Ratio Analysis) was applied to define the weights of 12 criteria of different structures used in the evaluation of reclamation solutions. The Fuzzy ROV (Range of Value) method was applied to select the reclamation solution from a total of 11 solutions previously obtained using a process approach. The results of the hybrid IMF SWARA—Fuzzy ROV model show that forestry is the best solution for the Tamnava-West Field open-pit mine. After the results had been obtained, verification analyses of the proposed model were performed and the best stable proposed reclamation solution was determined.
Investigating the Key Factors Affecting Public Transport Ridership in Developing Countries through Structural Equation Modeling
Authors: Ahmad Mudassir , Anwer Izza , Yousuf Muhammad Irfan , Javid Muhammad Ashraf , Ali Nazam , Tesoriere Giovanni , Campisi Tiziana
Published: May 2024

Every country requires efficient public transportation to reduce the reliance on motor vehicles, decrease harmful emissions and noise pollution, and, most importantly, provide accessible transportation for urban populations with limited resources. Yet, several challenges hinder the efficiency of the public transportation system, affecting factors like daily ridership, infrastructure, revenue, and operations. Therefore, this research investigated barriers and their impact on the daily ridership of rail transit services, especially in densely populated areas characterized by high automobile usage, inadequate pedestrian facilities, and limited connectivity to other transportation modes. To accomplish this goal, a self-administered questionnaire was developed, and a survey was conducted to collect responses from commuters at various public transport hubs. Structural equation modeling (SEM) was used to analyze data gathered from a sample of 1000 participants. The findings from the SEM model indicated a positive correlation between Instrumental Attractiveness (IA) and Facility Design and Operation (FDO) with daily travel. Conversely, Service and Information (SI) along with Environmental Comfort (EC) exhibited a negative correlation with daily travel. Private sector employees without personal vehicles and a monthly income below fifty thousand exhibited a strong preference for public transport. Individuals with higher incomes who owned vehicles showed lower preferences towards public transport usage. The main contributors to low ridership in public transport included poor connectivity with metro and feeder buses, lack of availability of discount tickets, insufficient seating at stations, and inadequate route map information. Gasoline prices have a notable impact on daily ridership too, as higher fuel prices tend to attract more travelers to use public transport. The ridership data demonstrate a positive trend in response to increased gasoline prices. The findings from this study are useful for transportation engineers, practitioners, planners, and policymakers.
Assessment of Pistachio Shell-Based Biochar Application in the Sustainable Amendment of Soil and Its Performance in Enhancing Bell Pepper (Capsicum annuum L.) Growth
Authors: Sanchez Eliana , Zabaleta Romina , Navas Ana Laura , Torres-Sciancalepore Rodrigo , Fouga Gastón , Fabani Maria Paula , Rodriguez Rosa , Mazza Germán
Published: May 2024

This study aimed to (a) analyze the influence of pyrolysis temperature on pistachio shell-based biochar (PSB) properties and (b) assess the PSB effect on green bell pepper (Capsicum annuum L.) growth. Pyrolysis experiments were conducted at different temperatures, determining 450 °C as optimal for soil amendment. The effect of PSB addition at different mass ratios was analyzed considering the physicochemical properties of the mixtures and the agronomic parameters of green bell pepper plants and fruits under greenhouse conditions. Results demonstrated enhancements in soil properties upon biochar incorporation, including a decrease in pH by 1%, a decrease in electrical conductivity (EC) by 4–14%, and increases in cation exchange capacity (CEC) by 4–8%, organic matter (OM) and organic carbon (OC) by 100–200%, and total nitrogen (TN) by 35%, relative to unamended soil. Agronomic variables revealed improvements, particularly during the reproductive and maturity stages, with plants treated with 1% biochar (SB1) exhibiting enhanced growth and chlorophyll content, alongside increased flower and fruit yields. Notably, the 2% biochar treatment (SB2) yielded superior fruit weight and length results, suggesting the potential for biochar to enhance both the quality and quantity of green bell pepper fruits, thereby contributing to sustainable agricultural practices.
Digital Technologies Adoption and Economic Benefits in Agriculture: A Mixed-Methods Approach
Authors: Geng Wenxuan , Liu Liping , Zhao Junye , Kang Xiaoru , Wang Wenliang
Published: May 2024

Governments globally aim to boost productivity and enhance farmers’ livelihoods, addressing challenges like climate change, food security, and labor shortages through digital technologies. However, adoption rates in developing countries remain low due to uncertainties regarding expected returns and obstacles stemming from subjective and objective factors among farmers. This study takes China as a case study to examine the internal and external factors influencing growers’ adoption intensity of digital technology and its impact on enhancing economic benefits, aiming to provide valuable insights for the promotion of digital technology in other countries and regions. This study employs a mixed-methods approach, integrating qualitative and quantitative methodologies, utilizing data from Shandong and Liaoning provinces. The findings underscore the significant role of growers’ knowledge, technology compatibility, government support, and competitive pressure in driving the adoption of digital technology among growers, with male growers and those managing larger cultivation areas demonstrating higher adoption intensity. Digital technologies can enhance growers’ economic benefits by reducing labor and input costs, increasing yields, and improving quality, with a 30.4% increase in economic benefits for each unit increase in adoption intensity of digital technologies. Technology promoters can use these findings to enhance growers’ awareness, highlight the practical benefits, and offer agricultural socialized services to promote digital technology adoption.
Effect of Flowering Strips in Associated Broccoli and Lettuce Crops on Increasing Land Use Efficiency
Authors: Martinez Eliana , Marcillo-Paguay Carlos Alberto , Revelo-Gomez Eliana Gisela , Cuervo Mónica , Igua-Urbano Erika Paola
Published: May 2024

Diversifying agroecosystems enhance the sustainability of agricultural production and reduce input dependency during agroecological transitions. To achieve this objective, a study was conducted to assess the impact of intercropping and the introduction of flowering plant strips on land use efficiency and crop damage in a lettuce and broccoli association. The results indicated that the introduction of flowering plant strips alone led to a significant increase in land use efficiency, while intercropping alone did not have any such effect. The efficiency was measured using the land use equivalent ratio (LER), which consistently showed values greater than 1, suggesting a significant increase in efficiency. It should be noted that the presence of flower strips in the crop fields were found to increase the incidence of molluscs and Plutella xyllostella. Additionally, the competitive ratio analysis revealed that broccoli was more competitive than lettuce in the intercropping system. Therefore, farmers can increase the efficiency of land use and profitability by incorporating flower strips in the intercropping systems of broccoli and lettuce.
Towards Sustainable Urban Futures: Integrating a Novel Grey Multi-Criteria Decision Making Model for Optimal Pedestrian Walkway Site Selection
Authors: Reyes-Norambuena Pedro , Martinez-Torres Javier , Nemati Alireza , Hashemkhani Zolfani Sarfaraz , Antucheviciene Jurgita
Published: May 2024

Today, urban development faces complex global challenges that require new approaches to influence its practices and policies. By prioritizing sustainability, mobility, and community resilience, we are moving towards a holistic approach that protects the well-being of residents and the environment. In this dynamic urban design environment, finding ways to identify pedestrian-friendly spaces and create safe, efficient, and sustainable urban environments is a major challenge, and it requires research that seeks to optimize this choice, especially in terms of integrating numerical modeling methods and a wide range of measurement tasks. This research is concerned with optimizing pedestrian accessibility, which directly contributes to reducing environmental impact, improving non-motorized transport, and reducing traffic congestion. It integrates a novel, mixed multi-criteria decision-making (MCDM) model that benefits from the use of Grey’s theory. This research’s purpose goes beyond addressing cities’ immediate challenges; it seeks to contribute to a broader understanding of sustainable urban planning. This study represents a pioneering effort to identify the challenges of optimal site selection for pedestrian walkways. By using a multi-criteria decision-making approach based on mathematical modelling and facility engineering, this effort addresses gaps in the current understanding of site selection criteria and aims to lead a paradigm shift toward a sustainable, efficient, and inclusive urban environment. The results show that the updated RANCOM-PIV greyscale is quite robust and reliable, when comparing the final results of the PIV greyscale and the MARCOS greyscale.
RETRACTED: Lin et al. A Perception Study for Unit Charts in the Context of Large-Magnitude Data Representation. Symmetry 2023, 15, 219
Authors: Lin Yun , Tang Yi , Zhu Yanfei , Song Fangbin , Tang Wenzhe
Published: May 2024

The Symmetry Editorial Office retracts the article titled “A Perception Study for Unit Charts in the Context of Large-Magnitude Data Representation” [...]
Determination of Patulin in Apple Juice and Apple-Derived Products Using a Robotic Sample Preparation System and LC-APCI-MS/MS
Authors: Zhang Kai , Zhang Lauren
Published: May 2024

Patulin, a toxic mycotoxin, can contaminate apple-derived products. The FDA has established an action level of 50 ppb (ng/g) for patulin in apple juice and apple juice products. To effectively monitor this mycotoxin, there is a need for adequate analytical methods that can reliably and efficiently determine patulin levels. In this work, we developed an automated sample preparation workflow followed by liquid chromatography–atmospheric pressure chemical ionization tandem mass spectrometry (LC-APCI-MS/MS) detection to identify and quantify patulin in a single method, further expanding testing capabilities for monitoring patulin in foods compared to traditional optical methods. Using a robotic sample preparation system, apple juice, apple cider, apple puree, apple-based baby food, applesauce, fruit rolls, and fruit jam were fortified with 13C-patulin and extracted using dichloromethane (DCM) without human intervention, followed by an LC-APCI-MS/MS analysis in negative ionization mode. The method achieved a limit of quantification of 4.0 ng/g and linearity ranging from 2 to 1000 ng/mL (r2 > 0.99). Quantitation was performed with isotope dilution using 13C-patulin as an internal standard and solvent calibration standards. Average recoveries (relative standard deviations, RSD%) in seven spike matrices were 95% (9%) at 10 ng/g, 110% (5%) at 50 ng/g, 101% (7%) at 200 ng/g, and 104% (4%) at 1000 ng/g (n = 28). The ranges of within-matrix and between-matrix variability (RSD) were 3–8% and 4–9%, respectively. In incurred samples, the identity of patulin was further confirmed with a comparison of the information-dependent acquisition-enhanced product ion (IDA-EPI) MS/MS spectra to a reference standard. The metrological traceability of the patulin measurements in an incurred apple cider (21.1 ± 8.0 µg/g) and apple juice concentrate (56.6 ± 15.6 µg/g) was established using a certified reference material and calibration data to demonstrate data confidence intervals (k = 2, 95% confidence interval).
Mapping of Groundwater Recharge Zones in Hard Rock Aquifer through Analytic Hierarchy Process in Geospatial Platform
Authors: Subramani Deepa , Kamaraj Pradeep , Saravana Kumar Umayadoss , Sabarathinam Chidambaram
Published: May 2024

Extensive use of groundwater is a result of the growing population; in relation to this, studies have focused on groundwater conservation measures. This study identified groundwater artificial recharge zones (GWARZs) in the upper Manimuktha sub-basin through the application of remote sensing and GIS. A spatial analysis using the analytical hierarchical process (AHP) and weighted overlay analysis (WOA) was employed by integrating several spatial thematic layers such as geology, geomorphology, aquifer thickness, lineament density (LD), drainage density (DD), soil, slope, rainfall, and land use/land cover (LULC) in order to classify the GWARZs. The geomorphology along with lithology, higher aquifer thickness, low lineament densities, higher drainage densities, and gentle slope regions, were identified as suitable areas for artificial recharge zones. The study area was divided up into five classifications based on the integration analysis: excellent (41.1 km2), good (150.6 km2), moderate (123.9 km2), bad (125.5 km2), and very poor (57.7 km2). Excellent and good GWARZs were identified in the eastern and central regions of the study area. The final outcomes of this research were evaluated with seasonal electrical conductivity (EC) variations. The majority of samples with minor seasonal EC variations were observed in the excellent and good GWARZ categories. The results showed that the spatial analysis tool is useful for GWARZ delineation and sustainably managing groundwater resources.
Optimization of Hydraulic Efficiency and Internal Flow Characteristics of a Multi-Stage Pump Using RBF Neural Network
Authors: Zhang Lei , Wang Dayong , Yang Gang , Pan Qiang , Shi Weidong , Zhao Ruijie
Published: May 2024

In order to improve the hydraulic efficiency and internal flow pattern of a multi-stage pump under multiple flow conditions, an intelligent optimization design was proposed for its hydraulic components. Sensitivity analysis was used to select the key parameters influencing the hydraulic efficiency of a multi-stage pump. The optimal Latin hypercube sampling and non-dominated sorting genetic algorithm Ⅱ were employed to build a multi-objective optimization system. Moreover, a radial basis function neural network was adopted as the surrogate model of hydraulic efficiency. The research results showed that the impeller outlet width, impeller blade wrap angle, impeller outlet blade angle, and diffuser inlet width were the key factors affecting the hydraulic efficiency. The efficiency of the optimized model increased by 4.35% under the design condition and the matching of the internal flow between the optimized impeller and diffuser was significantly enhanced under the nominal condition. The improved flow pattern could be clearly observed in the flow passage of both the pump impeller and the diffuser. After optimization, the wear performance of the model was also improved compared to the original design. The wear area decreased in size and was distributed more evenly, resulting in a noticeable decrease in the maximum amount of wear.
Stable Isotope Hydrology of Karst Groundwaters in Romania
Authors: Feher Renata , Bădăluță Carmen-Andreea , Brad Traian , Drăgan Călin , Drăgușin Virgil , Măntoiu Dragoș Ștefan , Perșoiu Aurel , Tîrlă Maria-Laura
Published: May 2024

In this article we present the first investigation of the stable isotope composition of groundwater in Romania, East-Central Europe, with a focus on the karst areas. Our aim is twofold: (1) to provide a countrywide map with the distribution of stable oxygen and hydrogen isotope ratios in groundwater, and (2) to assess the recharge patterns of karst water. We collected more than 600 water samples from springs and wells across Romania for stable isotope analyses and monitored in detail the stable isotope composition of the waters as they pass through five cave systems. Our data show a spatial distribution of the stable isotope composition of the groundwater with low values in the mountainous area and high values in the surrounding lowlands and the central Transylvanian Depression. However, waters in karst areas induce departures from this distribution, resulting from the fast (hours to days) transfer of waters from high (ponor) to low (spring) altitudes. Water emerging from the karst springs has generally lower δ values than before sinking through the ponors, thus indicating a substantial contribution of winter recharge through diffuse infiltration and seepage. This contribution results in overall dilution of the water entering through ponors, likely resulting in changes in the chemical composition of the water and diluting potential pollutants. Our data call for careful separation between karst and non-karst spring/well waters, as indiscriminate common treatment might lead to erroneous interpretations.
Space-Time Variability of Drought Characteristics in Pernambuco, Brazil
Authors: da Silva Júnior Ivanildo Batista , da Silva Araújo Lidiane , Stosic Tatijana , Menezes Rômulo Simões Cezar , da Silva Antonio Samuel Alves
Published: May 2024

Drought is the most complex natural hazard that can occur over large spatial scales and during long time periods. It affects more people than any other natural hazard, particularly in areas with a dry climate, such as the semiarid region of the Brazilian Northeast (NEB), which is the world’s most populated dry area. In this work, we analyzed trends and the spatial distribution of drought characteristics (frequency, affected area, and intensity) based on the Standardized Precipitation Index (SPI) on annual (SPI-12) and seasonal (SPI-3) scales. The study used monthly precipitation data recorded between 1962 and 2012 at 133 meteorological stations in Pernambuco State, Brazil, which is located in the eastern part of the NEB and has more than 80% of its territory characterized by a semiarid climate. The regions of Sertão, Agreste, and Zona da Mata of Pernambuco were considered for comparison. The Mann–Kendall and Sen’s slope tests were used to detect the trend and determine its magnitude, respectively. The results indicated that annual droughts in the state of Pernambuco became more frequent from the 1990s onwards, with summer having the greatest spatial coverage, followed by winter, autumn, and spring. Sertão presented a greater number of stations with a significant positive trend in drought frequency. Regarding the drought-affected area, global events occurred in a greater number of years on an annual scale and during the summer. Trend analysis pointed to an increase in areas with drought events on both scales. As for the drought intensity, the entire state of Pernambuco experienced drought events with high intensity during the autumn. The relationship between drought characteristics indicated an increase in the affected area as the result of an increase in drought intensity.
Arap Dilbilimci Munzir ‘Atâ el-‘Ayyâşî’nin Üslûp ve Üslûpbilim’e Dair Görüşleri
Authors: Dede Mazhar
Published: May 2024

Üslup, kavramsal çerçevesi oluşmamış olsa da klasik kaynaklarda çokça işlenmiş bir konudur. Özellikle Kur’an’ın lafzi ve mana yönünden eşsizliğini konu alan kaynaklarda bu kavramla sıkça karşılaşmak mümkündür. Günümüzde ise dilbilim alanında yaşanan gelişmelerle birlikte üslup ve üslupbilim daha da önemli bir alan haline gelmiştir. Doğulu ve batılı dilbilimciler, ittifak edilen bir tanımı olmamakla beraber kişinin kendisine özgü dil kullanımı denilebilecek üslûp ve dil üslûplarını inceleyen üslupbilimle ilgili kayda değer çalışmalar yapmışlardır. Bu konuları müstakil bir eserle ele alıp inceleyen modern Arap dilbilimcilerden biri de Suriye asıllı Munzir Atâ el-‘Ayyâşî’dir. el-Üslūb ve Tahlîlu’l-Hitâb adlı eseri alanla ilgili çalışma yapan araştırmacıların başucu kaynağı konumundadır. Bununla birlikte el-‘Ayyâşî’nin, başta üslûpbilim olmak üzere farklı alanlarda tercümeleri de bulunmaktadır. Özellikle Fransız Pierre Guiraud’a ait Fransızca’dan Arapça’ya tercüme ettiği Stylistique (الأسلوبية) adlı eser alana ciddi katkılar sağlamıştır. Klasik ve modern Arap dilbilimcilerin üslûp ve üslûpbilim hakkındaki görüşlerin ele alındığı çalışmalardan farklı olarak söz konusu şahsın doğrudan konuyla ilgili eserlerinden hareketle fikirlerini ortaya koymak oldukça önemlidir. Bu çalışmanın amacı Munzir Atâ el-‘Ayyâşî’nin çalışmaları genel olarak taranarak üslûp ve üslûpbilimine dair görüşlerini tespit etmektir. Ayrıca tespit edilen görüşlerin özgün yönlerinin ortaya konması hedeflenmektedir.
Avaliação de computador de placa única como ferramenta para estudantes e professores em ensino remoto
Authors: Hara Marcos Santos , Tefili Diego , Pês Beatriz dos Santos , Scarpin Gabriel Schwartz , Falarz Eduardo Jean , Padilha Alexandre
Published: May 2024

A falta de disponibilidade de computador doméstico em grande parte das residências brasileiras dificulta o ensino remoto. Este trabalho traz uma proposta de um dispositivo para o acesso ao ensino remoto de baixo custo, utilizando um microcomputador tipo Raspberry Pi. Para o desenvolvimento do sistema foram feitos estudos teóricos sobre o tema, testes de utilização em atividades típicas relacionadas a ensino. Também foram utilizadas ferramentas em software de avaliação de desempenho e comparação entre plataformas para selecionar as melhores opções de hardware, sistema operacional, aplicativos e configurações. Após a realização destes procedimentos, chegou-se a uma lista de recomendações que pode ser considerada como alternativa a uso de computadores e celulares no ensino remoto tanto por estudantes para tarefas básicas quanto por professores para atividades mais avançadas como captura de tela para gravação de aulas.