bluuebunny/crossref_metadata_2025 huggingface dataset:
Topside Ionospheric Tomography Exclusively Based on LEO POD GPS Carrier Phases: Application to Autonomous LEO DCB Estimation
Authors: Hernández-Pajares Manuel , Olivares-Pulido Germán , Hoque M. Mainul , Prol Fabricio S. , Yuan Liangliang , Notarpietro Riccardo , Graffigna Victoria
Published: January 2023

This paper presents a novel technique to estimate DCBs from GPS transmitters and receivers on-board Low Earth Orbit (LEO) satellites. The technique consists of obtaining the DCBs as residuals from the difference between the ionospheric combination of the code and the associated ionospheric delay. The ionospheric delay is computed with TOMION, a background-model-free ionospheric tomographic technique based on dual-frequency GPS carrier phase data only, and solved with a Kalman filter. Thus, DCBs are also estimated epoch-wise from the LEO Precise Orbit Determination (POD) GPS receiver as a secondary product. The results for GPS satellite DCBs, obtained exclusively from the three MetOp LEO POD GPS receivers over four consecutive weeks, are in full agreement (i.e., at the level of a few tenths of ns) with those reported independently with other techniques from hundreds of ground-based receivers exclusively, by JPL and CODE analysis centers.
Using a Tandem Flight Configuration between Sentinel-6 and Jason-3 to Compare SAR and Conventional Altimeters in Sea Surface Signatures of Internal Solitary Waves
Authors: Magalhaes Jorge M. , Lapa Ian G. , Santos-Ferreira Adriana M. , da Silva José C. B. , Piras Fanny , Moreau Thomas , Amraoui Samira , Passaro Marcello , Schwatke Christian , Hart-Davis Michael , Maraldi Claire , Donlon Craig
Published: January 2023

Satellite altimetry has been providing a continuous record of ocean measurements with numerous applications across the entire range of ocean sciences. A reference orbit has been used since 1992 with TOPEX/Poseidon, which was repeated in the Jason missions, and in the newly launched Sentinel-6 Michael Freilich (in November 2020) to continually monitor the trends of sea level rise and other properties of the sea surface. These multidecadal missions have evolved alongside major technological advances, whose measurements are unified into a single data record owing to continuous intercalibration and validation efforts. However, the new Sentinel-6 provides synthetic aperture radar (SAR) processing, which improves the along-track resolution of conventional altimeters from a few kilometres (e.g., for Jason-3) to about 300 m. This means a major leap in sampling towards higher frequencies of the ocean spectrum, which inevitably means reconciling the assumption of a uniform Brown surface between the footprints of the larger kilometre-scale conventional altimetry and those of the finer-scale SAR altimetry. To explore this issue, this study uses the vantage point of the Sentinel-6/Jason-3 tandem phase to compare simultaneous sea surface signatures of large-scale Internal Solitary Waves (ISWs) between SAR and conventional altimetry. These waves can modulate the sea surface into arrayed sections of increased and decreased roughness with horizontal scales up to 10 km, which inflict sharp transitions between increased and decreased backscatter in the radar altimeters. It is found that Sentinel-6 can provide more detailed structures of ISWs in standard level-2 products, when compared with those from the conventional Jason-3 (similarly to previous results reported from the SAR altimeter from Sentinel-3). However, a new and striking feature is found when comparing the radar backscatter between Sentinel-6 and Jason-3, which are in opposite phases in the ISWs. These intriguing results are discussed in light of the intrinsically different acquisition geometries of SAR and conventional altimeters as well as possible implications thereof.
Reconstruction of LoD-2 Building Models Guided by Façade Structures from Oblique Photogrammetric Point Cloud
Authors: Wang Feng , Zhou Guoqing , Hu Han , Wang Yuefeng , Fu Bolin , Li Shiming , Xie Jiali
Published: January 2023

Due to the façade visibility, intuitive expression, and multi-view redundancy, oblique photogrammetry can provide optional data for large-scale urban LoD-2 reconstruction. However, the inherent noise in oblique photogrammetric point cloud resulting from the image-dense matching limits further model reconstruction applications. Thus, this paper proposes a novel method for the efficient reconstruction of LoD-2 building models guided by façade structures from an oblique photogrammetric point cloud. First, a building planar layout is constructed combined with footprint data and the vertical planes of the building based on spatial consistency constraints. The cells in the planar layout represent roof structures with a distinct altitude difference. Then, we introduce regularity constraints and a binary integer programming model to abstract the façade with the best-fitting monotonic regularized profiles. Combined with the planar layout and regularized profiles, a 2D building topology is constructed. Finally, the vertices of building roof facets can be derived from the 2D building topology, thus generating a LoD-2 building model. Experimental results using real datasets indicate that the proposed method can generate reliable reconstruction results compared with two state-of-the-art methods.
Non-Destructive Detection of Soybean Pest Based on Hyperspectral Image and Attention-ResNet Meta-Learning Model
Authors: Gui Jiangsheng , Xu Huirong , Fei Jingyi
Published: January 2023

Soybean plays an important role in food, medicine, and industry. The quality inspection of soybean is essential for soybean yield and the agricultural economy. However, soybean pest is an important factor that seriously affects soybean yield, among which leguminivora glycinivorella matsumura is the most frequent pest. Aiming at the problem that the traditional detection methods have low accuracy and need a large number of samples to train the model, this paper proposed a detection method for leguminivora glycinivorella matsumura based on an A-ResNet (Attention-ResNet) meta-learning model. In this model, the ResNet network was combined with Attention to obtain the feature vectors that can better express the samples, so as to improve the performance of the model. As well, the classifier was designed as a multi-class support vector machine (SVM) to reduce over-fitting. Furthermore, in order to improve the training stability of the model and the prediction performance on the testing set, the traditional Batch Normalization was replaced by the Layer Normalization, and the Label Smooth method was used to punish the original loss. The experimental results showed that the accuracy of the A-ResNet meta-learning model reached 94.57 ± 0.19%, which can realize rapid and accurate nondestructive detection, and provides theoretical support for the intelligent detection of soybean pests.
A System-Dynamic Model for Human–Robot Interaction; Solving the Puzzle of Complex Interactions
Authors: Steijn Wouter Martinus Petrus , Van Gulijk Coen , Van der Beek Dolf , Sluijs Teun
Published: January 2023

Cooperative robots in the workspace have an effect on safety that is not yet fully understood. This work collates pre-existing knowledge on human, technological and organizational factors for human-robot interaction and develops a system dynamics model that captures the complex interactions. Expert consultation in the form of a Delphi study is used to derive a tractable model from pre-existing puzzle pieces. A final model is presented, which contains 10 nodes and 20 relationships containing the three key outcome factors of human-robot interaction, viz. Safety, Efficiency and Sustainability. By combining these factors into a single tractable framework, this model bridges the gap between individual efforts from previous works in the field of robotics.
Differences in Pedestrian Behavior at Crosswalk between Communicating with Conventional Vehicle and Automated Vehicle in Real Traffic Environment
Authors: Taima Masahiro , Daimon Tatsuru
Published: January 2023

In this study, we examine the differences in pedestrian behavior at crosswalks between communicating with conventional vehicles (CVs) and automated vehicles (AVs). To analyze pedestrian behavior statistically, we record the pedestrian’s position (x- and y-coordinates) every 0.5 s and perform a hot spot analysis. A Toyota Prius (ZVW30) is used as the CV and AV, and the vehicle behavior is controlled using the Wizard of Oz method. An experiment is conducted on a public road in Odaiba, Tokyo, Japan, where 38 participants are recruited for each experiment involving a CV and an AV. The participants cross the road after communicating with the CV or AV. The results show that the pedestrians can cross earlier when communicating with the CV as compared with the AV. The hot spot analysis shows that pedestrians who communicate with the CV decide to cross the road before the CV stops; however, pedestrians who communicate with the AVs decide to cross the road after the AV stops. It is discovered that perceived safety does not significantly affect pedestrian behavior; therefore, earlier perceived safety by drivers’ communication and external human–machine interface is more important than higher perceived safety for achieving efficient communication.
Flash Flood Risk Assessment Due to a Possible Dam Break in Urban Arid Environment, the New Um Al-Khair Dam Case Study, Jeddah, Saudi Arabia
Authors: Hamza Mohamed Hafedh , Saegh Afnan Mohammed
Published: January 2023

Recent years have seen an increase in floods with severe damage due to the intensity and frequency of rains. One of the periodic hydrological problems affecting Jeddah city, the second-biggest city in Saudi Arabia, is unexpected flash flooding. In dam breaks, water that has been retained is released uncontrollably. This study is related to a flood simulation methodology after a possible break of the New Um Al-Khair Dam, a dam built in 2012 outside residential areas, to replace the Old Um Al-Khair Dam built inside a residential area, which broke in January 2011. In fact, we simulated the impact on flood wave propagation in the study area through the use of GIS techniques coupled with hydrological/hydraulic modeling tools and the development of a flood inundation model. Planning a good emergency response in the future is possible by analyzing a supposed disaster. Based on the likelihood that there will be a flood and the corresponding inundation depth, a flood risk matrix is created as a quantitative tool to estimate flood damage, which is crucial to decision-makers. Negligible, low, moderate, high, and very high-risk categories are assigned according to that flood risk matrix. The results indicated a low to very high risk for 5 years, 50 years and 100 years return periods and a negligible to very high risk for a 200 years return period. To estimate the extent of damage, a quantitative summary of the results has been outlined graphically in order to visualize the scope of the inundation areas.
Potential of Regulating Ecosystem Services in Relation to Natural Capital in Model Regions of Slovakia
Authors: Makovníková Jarmila , Kološta Stanislav , Flaška Filip , Pálka Boris
Published: January 2023

The growing demands of satisfying human well-being call for a sustainable way of managing the landscape, which requires the introduction of tools for evaluating and assessing ecosystem services. The aim of the study is to evaluate regional differentiations in the values of regulating ecosystem services in relation to natural potential in four small pilot regions of the Slovak Republic with the application of the modified matrix approach. The results in the pilot regions of the Slovak Republic indicated that the spatial distribution of individual ecosystems in the country, in combination with a higher altitude and a larger area of forests and protected areas, can represent significant factors influencing the potential of the territory to provide benefits resulting from regulating ecosystem services. Mountain areas generally have a higher capacity to provide regulating ecosystem services, mainly due to their rich forest vegetation. Regulating ecosystem services, to the greatest extent, reflects the multifunctionality of the territory.
Green Innovation as a Mediator between Green Human Resource Management Practices and Sustainable Performance in Palestinian Manufacturing Industries
Authors: Kanan Mohammad , Taha Baha , Saleh Yahya , Alsayed Mohammed , Assaf Ramiz , Ben Hassen Mohamed , Alshaibani Elham , Bakir Ali , Tunsi Weam
Published: January 2023

Green human resources management (GHRM) is a critical research issue that has emerged in recent decades. This study aims to investigate the effect of GHRM practices on sustainable performance, with green innovation as a mediating variable, in manufacturing firms in Palestine. To this end, a research model was developed, and a self-administered questionnaire was designed and distributed to a random sample of top management personnel in manufacturing firms in Palestine. The research model was assessed via the partial least squares structural equation modeling (PLS-SEM) using the Smart-PLS software, based on a sample of 58 responses. The model revealed that GHRM practices, green innovation, and sustainable performance are implemented at a moderate level. Moreover, the results confirmed that GHRM practices and green innovation have significant positive effects on sustainable performance. GHRM practices also positively and significantly affect green innovation. Green innovation partially mediates the relation between GHRM practices and sustainable performance. The results of this research present a conceptual framework and a guideline for policymakers in manufacturing firms on how to use GHRM practices to strengthen employees’ commitment to the environment in order to maximize sustainable performance. Furthermore, the study provides a holistic view of GHRM practices, green innovation, and sustainable performance; such a perspective is considered a foundation for future research directions and provides empirical evidence about the relationships between these variables.
The Organizational Learning Role in Construction Organizations Resilience during the COVID-19 Pandemic
Authors: AlMaian Rufaidah , Bu Qammaz Amani
Published: January 2023

The speed of the COVID-19 outbreak forced decision-makers to implement emergency plans to mitigate the impact of the pandemic on their business. This research is conducted to study the role of organizational learning (OL) practices in construction organizations’ resilience during the COVID-19 pandemic. The strengths, weaknesses, opportunities, and threats (SWOT) analysis was implemented together with the results of semi-structured interviews that were conducted immediately before the pandemic to learn how OL would help construction organizations survive during crises similar to the pandemic and create potential opportunities after the crisis that could contribute to ensure long-term sustainability. The results show that OL practices can assist construction organizations in surviving the threats of the pandemic and creating opportunities. The defined opportunities were distributed on three interrelated dimensions: management awareness, investing in information, communication technology (ICT), and standardized business practices. The results of the SWOT analysis revealed the inevitable need for OL-based business cultures. Therefore, it is essential for construction organizations to focus on implementing OL practices that would best assist them in being robust and resilient during crises and ensure their sustainable status in the long term.
Perceptions of Climate Adaptation and Mitigation: An Approach from Societies in Southern Ecuadorian Andes
Authors: Iñiguez-Gallardo Verónica , Tzanopoulos Joseph
Published: January 2023

Climate research has steadily identified that public responses to the impacts associated with climate change are locally adjusted. These responses are mostly shaped by the prevailing socio-cultural knowledge systems underpinned by resilience thinking in the face of change and adversity. Despite the increasing scientific and policy attention to peoples’ perceptions of climatic changes and adaptive responses, there is still a lag in the more detailed probing and exploration of the local level demographic profiles related to the perceptions of and attitudes and responses to mitigation and adaptation strategies. This is of particular importance as the research, planning, and action concerning climate change mitigation and adaptation needs to be informed by and implemented within specific place contexts. Based largely on semi-structured interviews and complementary face-to-face questionnaires, this study focuses on southern Ecuador to identify people’s stances on climate change mitigation and adaptation and to investigate further the perceptions of farmers on adaptation. The results indicate a tendency among urban residents towards a pro-mitigation stance. Those with a pro-adaptation stance are mainly the residents of rural areas and farmers. Farmers appeared to be highly adaptive to climatic changes and are led by a self-assessed ability to adapt. Their adaptive responses vary according to the geographical place of residence, type of farmer, and age. The findings offer local level empirical evidence for designing effective adaptation strategies.
Predicting Chain’s Manufacturing SME Credit Risk in Supply Chain Finance Based on Machine Learning Methods
Authors: Xia Yu , Xu Ta , Wei Ming-Xia , Wei Zhen-Ke , Tang Lian-Jie
Published: January 2023

Supply chain finance is an effective way to solve the financial problems of small and medium-sized manufacturing enterprises, and the assessment of credit risk is one of the key issues in supply chain financing. However, traditional credit risk assessment models cannot truly reflect the credit status of financing companies. In recent years, scholars working in this field have proposed using machine learning methods to predict the credit risk of supply chain enterprises, achieving good results. Nonetheless, there is no consensus on which approach is the most suitable for manufacturing companies. This study took small and medium-sized manufacturing enterprises as the research object, selected risk evaluation indicators according to the characteristics of the small and medium-sized manufacturing enterprises, and built a credit risk evaluation system. On this basis, we selected SMEs on China’s stock market from 2015 to 2020 as the sample data and evaluated corporate credit risk based on four commonly used machine learning algorithms. Then, combined with the evaluation results, a partial dependence plot method was used to visually analyze the important indicators. The results showed that a credit risk evaluation system for supply chain finance for manufacturing SMEs could be composed of the profile of the financing companies, the asset status of the financing companies, the profile of the core companies, and the operation of supply chains. The use of a random forest algorithm made it possible to more accurately assess the credit risk of manufacturing supply chain finance. Since the impacts of different indicators on the evaluation results were quite different, supply chain enterprises and financial service institutions should formulate corresponding strategies according to specific situations.
Study on the Characteristics of Coal Ultrasonic Response during Loading and Its Influence Mechanism
Authors: Xu Gang , Ma Tingting , Wang Chaofeng , Jin Hongwei , Wang Yunlong
Published: January 2023

The prediction and prevention· of mine disasters are crucial to identifying the stress and strain state of coal using ultrasonic response characteristics. In this study, ultrasonic testing experiments of primary structure coal samples under uniaxial loading were conducted using a low-frequency rock physics measuring device. Based on the experimental results, the study focused on analyzing the relationship of the stress–strain state of coal samples with the ultrasonic velocity and quality factor of coal samples during stress loading, and exploring the influence mechanism of ultrasonic propagation in coal during stress loading. The results demonstrated that the stress-loading process of coal samples falls into the elastic deformation stage and the plastic deformation stage. In the elastic deformation stage, the ultrasonic velocity and the quality factor of the coal sample increased with the increase in the coal axial strain. In the plastic deformation stage, the ultrasonic velocity and quality factor of coal samples decreased as the axial strain of coal samples increased. Coal porosity was the fundamental factor affecting the coal wave velocity variation and the coal quality factor variation. In the elastic deformation stage, increased coal axial stress was accompanied by decreased coal porosity, contributing to the increase in coal wave velocity and coal quality factor. In the plastic deformation stage, the increase in the coal axial strain increased coal porosity and thus curtailed the wave velocity and quality factor of coal. Significant differences were observed in ultrasonic response characteristics of coal under various stress and strain states. The research results can lay a theoretical foundation for the safe and efficient development of coal resources and the prevention and control of mine disasters.
Physiological, Morphological and Biochemical Responses of Exogenous Hydrogen Sulfide in Salt-Stressed Tomato Seedlings
Authors: Yildirim Ertan , Ekinci Melek , Turan Metin , Ors Selda , Dursun Atilla
Published: January 2023

Salinity causes yield and quality losses in agricultural production and therefore great economic losses around the world. Hydrogen sulfide (H2S) is known to play a crucial role to ease physiological and metabolic processes in plants, and also increases the tolerance of the plant against many abiotic stress conditions. In this study, we investigated the effects of H2S treatments (0, 25, 50, 75 and 100 µM NaHS were applied as H2S donor) to the tomato seedlings to alleviate the harmful effects of salt stress (0, 75 and 150 mM NaCl). There was a significant decrease in plant growth and development in parallel with the increased salt level. Visible changes in plant development were observed after the dose of 75 mM NaCl in the tomato seedling. The effects of different doses of exogenous H2S treatment were found to be significant. H2S treatment increased the stress tolerance in tomato seedlings by arranging the mineral element and hormone content. Furthermore, H2S relieved the effect of stress in plants by increasing photosynthetic activity (photosynthesis rate (Pn), transpiration rate (Tr), stomatal conductivity (gs) and intercellular CO2 concentration (Ci)) of the plant. In addition, the effect of H2S on salt stress tolerance in tomato seedlings may be due to its positive effect on mineral element contents. As a result, based on the beneficial effects of H2S in tomato seedlings under salt stress, this treatment can be considered as an alternative resilience method for cultivation in saline soils or irrigation with low quality waters.
The Red Tide Organism Chaetoceros sp. Responding to Exposure to Oil and Dispersant
Authors: Lv Xin , Liu Xin , Hu Xiaoke , Geng Ruiying , Tang Cheng , Xing Qianguo
Published: January 2023

Laboratory experiments were conducted to study the effects of oil spills and dispersants on the growth of the red tide organism Chaetoceros sp. Crude oil produced from the Chinese Bohai Sea, diesel oil, and the chemical dispersant (GM-2) produced in China were added into Chaetoceros sp. cultures. The results showed that both crude oil and diesel oil could enhance the growth of Chaetoceros sp. Data were analyzed by one-way ANOVA, and the confidence interval was 95%. At a concentration of 20 mg L−1 crude oil and a concentration of 10 μL L−1 diesel oil, Chaetoceros sp. bloomed to 1.57 × 105 cells mL−1 (p < 0.01) at day 14 and 3.55 × 104 cells mL−1 (p < 0.05) at day 10, respectively. A concentration of 10 μL L−1 diesel oil stimulated the specific growth rate for Chaetoceros sp. of 0.49 d−1 over 10 days. The specific growth rate of Chaetoceros sp. with 20 mg L−1 crude oil alone was 0.46 d−1 over 14 days. However, the mixture of oil and dispersant did not enhance the growth of Chaetoceros sp. as significantly as oil alone. These results implied that oil spills in coastal waters can stimulate Chaetoceros sp., and the specific dispersant GM-2 applied following oil spills may be unlikely to further enhance the growth of Chaetoceros sp.
Prediction of Shipping Cost on Freight Brokerage Platform Using Machine Learning
Authors: Jang Hee-Seon , Chang Tai-Woo , Kim Seung-Han
Published: January 2023

Not having an exact cost standard can present a problem for setting the shipping costs on a freight brokerage platform. Transport brokers who use their high market position to charge excessive commissions can also make it difficult to set rates. In addition, due to the absence of a quantified fare policy, fares are undervalued relative to the labor input. Therefore, vehicle owners are working for less pay than their efforts. This study derives the main variables that influence the setting of the shipping costs and presents the recommended shipping cost given by a price prediction model using machine learning methods. The cost prediction model was built using four algorithms: multiple linear regression, deep neural network, XGBoost regression, and LightGBM regression. R-squared was used as the performance evaluation index. In view of the results of this study, LightGBM was chosen as the model with the greatest explanatory power and the fastest processing. Furthermore, the range of the predicted shipping costs was determined considering realistic usage patterns. The confidence interval was used as the method of calculation for the range of the predicted shipping costs, and, for this purpose, the dataset was classified using the K-fold cross-validation method. This paper could be used to set the shipping costs on freight brokerage platforms and to improve utilization rates.
Simplified Model for Concentration Analysis of Catalytic Conversion of Carbon Gas into Hydrogen
Authors: Furlan Jacqueline , Siqueira Adriano Francisco , Romão Estaner Claro
Published: January 2023

The annual energy matrix has been changing in the last years because of the necessity of less dependence on fossil fuels, which are running out on the planet. Therefore, a study was begun to simulate the most efficient production of H2 through COMSOL Multiphysics®, as it is a gas that in the future will be essential to supply the world’s energy necessities, due to it being easy to access and insert in gas pipes. From this study, we were able to present an optimization of parameters that presents good indications of how to obtain efficient hydrogen production in an idealized reactor.
Determination of the Influence of the Disturbance Caused by Traversing Cross-Type Deep Foundation Pit Excavations
Authors: Wang Shuhong , Yang Bo , Dong Furui , Maxim Marinichev , Zhang Ze
Published: January 2023

Accurately recognizing the influence of excavation disturbance on the traversing cross-type deep foundation pit of the subway, determining the active range of the disturbance, and reasonably arranging the structure within its range can effectively ensure the safety of the project and save resources to achieve the goal of sustainable development. A three-dimensional model was established using the soil small strain hardening model to examine the subway deep foundation pit project in the CBD (central business district) core area of Fuzhou Coastal New City, where the soil is mainly soft soil with high natural water content, high compressibility, and weak permeability. The model was verified against the theoretical solution of Melan, and the deformation characteristics of the cross-asymmetric foundation pit excavation were analyzed. The results show that, due to repeated disturbance from excavation and unloading between the foundation pits, the soil arching effect, and changes in the boundary conditions, the structure at the intersection and the surrounding soil interact. The horizontal displacement of the retaining structure and the surrounding surface settlement are quite different from those observed from a single foundation pit excavation. For instance, the maximum horizontal displacement of profile 1-3 in Zone I decreases by 26.1%, while the maximum horizontal displacement of profile 1-1 in Zone II increases by 20.4%, and the maximum surface settlement around the profiles also has similar characteristics. The disturbance on the retaining structure and soil in different areas at the intersection can be divided into positive and negative effects. The active range of the “disturbance influence zone” is determined: the foundation pit of Metro Line 6 is 3.5 He and the foundation pit of Metro Line F1 is 3.0 He. Finally, the influence of changes in the groundwater level on the active range of the “disturbance influence zone” is discussed.
Prediction of Main Parameters of Steam in Waste Incinerators Based on BAS-SVM
Authors: Chen Lianhong , Wang Chao , Zhong Rigang , Li Zhuoge , Zhao Zheng , Zhou Ziyu
Published: January 2023

The main steam parameters of a waste-to-energy plant are the key indicator of the safety and stability of its combustion process. Accurate prediction of the main steam parameters can help the control system to reasonably analyze the combustion conditions and, thus, to greatly improve the combustion efficiency. In this paper, we propose an optimized method for predicting the main steam parameters of waste incinerators. Firstly, a grey relational analysis (GRA) is used to obtain the ranking of the correlation degree between 114 characteristic variables in the furnace and the main steam parameters, and 13 characteristic variables are selected as model inputs. A Spearman-based time delay compensation method is proposed to effectively overcome the influence of time asynchrony on the prediction accuracy. At last, the beetle antennae search (BAS) optimized support vector machine (SVM) model is proposed. Taking advantage of the fast iteration of the beetle antennae search algorithm to find the key hyperparameters of the support vector machine, the optimized main steam parameter prediction model is finally obtained. The simulation results show that the prediction accuracy of this model is greatly improved compared with traditional neural network models, such as long short-term memory neural networks (LSTMs) and convolutional neural networks (CNNs), as well as a single SVM.
An Intelligent Question-Answering Model over Educational Knowledge Graph for Sustainable Urban Living
Authors: Fang Yutong , Deng Jianzhi , Zhang Fengming , Wang Hongyan
Published: January 2023

With the development of education informatization and the accumulation of massive educational resources and teaching data in urban environments, educational knowledge graphs that provide good conditions for developing data-driven intelligent education have been proposed. Based on such educational knowledge graphs, the question-answering method can provide students with immediate coaching and significantly increase their learning interest and productivity. However, there is little research on knowledge graph question-answering focused on the educational field. Students tend to consult complex questions that require reasoning; however, the existing QA system cannot satisfy their complex information needs. To help improve sustainable learning efficiency, we propose a novel intelligent question-answering model applied in smart cities, which can reason over the educational knowledge graph to locate the answers to given questions. Our approach uses a highly expressive bilinear graph neural network technology to perform forward reasoning, utilizing the contextual information between graph nodes to improve reasoning ability. On this basis, we propose two-teacher knowledge distillation. We construct two distinct teacher networks by combining forward and backward reasoning, then incorporate the intermediate supervision signals from the two networks to guide the reasoning process, thereby mitigating the phenomenon of spurious path reasoning. Extensive experiments on the MOOC Q&A dataset prove the effectiveness of our approach.
Morphometric Evaluation and Its Incidence in the Mass Movements Present in the Chicamocha Canyon, Colombia
Authors: Valencia Ortiz Joaquín Andrés , Martínez-Graña Antonio Miguel
Published: January 2023

The dynamic behavior of the basins evaluated by their morphometric parameters establishes a relationship with the endogenous and exogenous factors of the earth that control the modeling of the rocky massif by weathering and erosion processes. The characterization of these relationships can define the degree of affectation of the surfaces and the agents that control them as a categorical element in the definition of scenarios within the planning of physical and natural territory. This evaluation considers parameters contained within the characterization of the relief, shape and texture of the drainage and the mobility of the flow in the basin. As a result of this evaluation, three factors were obtained that control the processes in the basins: a tectonic structural factor followed by climate control and, finally, seismic activity that plays an important role in the mechanical weathering of surfaces. The correlation of these factors showed that the Umpalá, Guaca, Río Negro, Cantabara and La Cureña basins display a high degree of physical and mechanical weathering of the rocky massif and that the Manco, Talarcuta, Las Pavas, Felisco and El Abra basins are more likely to generate torrential flows. The joint evaluation of these parameters provides a useful tool to understand the dynamic behavior of basins and their impact on anthropogenic setting.
Study of the Effects of Daylighting and Artificial Lighting at 59° Latitude on Mental States, Behaviour and Perception
Authors: Favero Federico , Lowden Arne , Bresin Roberto , Ejhed Jan
Published: January 2023

Although there is a documented preference for daylighting over artificial electric lighting indoors, there are comparatively few investigations of behaviour and perception in indoor day-lit spaces at high latitudes during winter. We report a pilot study designed to examine the effects of static artificial lighting conditions (ALC) and dynamic daylighting conditions (DLC) on the behaviour and perception of two groups of participants. Each group (n = 9 for ALC and n = 8 for DLC) experienced one of the two conditions for three consecutive days, from sunrise to sunset. The main results of this study show the following: indoor light exposure in February in Stockholm can be maintained over 1000 lx only with daylight for most of the working day, a value similar to outdoor workers’ exposure in Scandinavia; these values can be over the recommended Melanopic Equivalent Daylight Illuminance threshold; and this exposure reduces sleepiness and increases amount of activity compared to a static artificial lighting condition. Mood and feeling of time passing are also affected, but we do not exactly know by which variable, either personal or group dynamics, view or variation of the lighting exposure. The small sample size does not support inferential statistics; however, these significant effects might be large enough to be of importance in practice. From a sustainability point of view, daylighting can benefit energy saving strategies and well-being, even in the Scandinavian winter.
Effect of Aggregate Size and Compaction on the Strength and Hydraulic Properties of Pervious Concrete
Authors: Ferić Kajo , Sathish Kumar Veerappan , Romić Ana , Gotovac Hrvoje
Published: January 2023

Pervious concrete is one of the emerging sustainable materials that has recently gained the attention of many researchers. The importance of pervious concrete mainly depends on its application and on a modern integrated approach in which it is employed to reduce the effects of flooding. The main goal of this experimental analysis is to study the significance of aggregate size and the degree of compaction on the mechanical and hydraulic properties of pervious concrete. Eleven concrete mixture proportions were investigated by controlling the constituents with different aggregate fractions. The important variables considered were the aggregate sizes, viz., 0/4 mm, 4/8 mm, and 8/16 mm, with four different degrees of compaction. The porosity of the concrete structure was obtained by the partial filling of the voids in the aggregates with cement paste. The ingredients of the pervious concrete were also varied to study their significance and to evaluate the predominant factor that controls the mechanical and hydraulic properties based on the test results. Tests were conducted to determine properties such as compacting factor, compressive strength, splitting tensile strength, abrasion resistance, porosity, and hydraulic conductivity. The study revealed that the degree of compaction was one of the critical factors governing the strength and hydraulic properties of the pervious concrete; the maximum strength and minimum hydraulic conductivity were achieved with a higher degree of compaction. The test results imply that the cement content is the predominant factor determining the fresh and tensile properties of the pervious concrete, rather than the size of the aggregates used. In addition, the results also illustrated that the highly compacted pervious concrete samples made with 4/8 mm aggregates exhibited improved abrasion resistance and strength properties, but slightly reduced hydraulic conductivity, despite the designed porosity.
Causality between Financial Inclusion, Financial Stability and Economic Growth in Sub-Saharan Africa
Authors: Jima Meshesha Demie , Makoni Patricia Lindelwa
Published: January 2023

Financial inclusion has become a policy agenda for financial stability and sustainable economic growth for the developing world. However, there seems to be a lack of consensus across the literature on the relationships between financial inclusion, financial stability and economic growth. Given the divergent views, this paper aims to examine the causal relationships between financial inclusion, financial stability and economic growth in the Sub-Saharan African (SSA) countries. In this study, panel data were used for twenty six selected SSA economies and a principal component analysis (PCA) was applied to construct a composite index for financial inclusion. In addition, an autoregressive distributed lags (ARDL) cointegration test was applied to examine the short- and long-run relationships between the variables of interest. Separate and joint Granger causality tests were used to assess the direction of causality. The result of the study indicated that there are both short-run and long-run relationships between financial inclusion, financial stability and economic growth in the SSA countries. Moreover, the Granger causality tests revealed that there are separate two-way causalities and joint uni-directional causalities, indicating complementarity between these variables. It is, therefore, necessary for policy makers, regulators and financial sector advisors to follow a holistic approach while developing and implementing policies and strategies that promote financial inclusion in order to attain sustainable economic growth in the region.
Soil Salinity Weakening and Soil Quality Enhancement after Long-Term Reclamation of Different Croplands in the Yellow River Delta
Authors: Liu Shanbao , Zhang Qiuying , Li Zhao , Tian Chao , Qiao Yunfeng , Du Kun , Cheng Hefa , Chen Gang , Li Xiaoyan , Li Fadong
Published: January 2023

Saline soils are of great concern globally. Selecting the Yellow River Delta as a model site, the influence of reclamation on soil salinity and saline soil quality was investigated. Soil quality index (SQI) was applied to statistically analyze 210 soil profile samples collected at seven depth layers in 30 sampling sites among native saline soils and three croplands (peanut, cotton, and wheat) in May 2020. After reclamation, the soil salt content (SSC) reduced from 4.52 g/kg to 1.44 g/kg after reclamation, with the degree of soil salinity reducing from severe to slight. The nitrate nitrogen (NO3−-N) contents of peanut, cotton, and wheat croplands were 1.90, 2.02, and 4.29 times higher and the available phosphorus (AP) contents were 5.43, 3.57, and 8.77 mg/kg higher than that of the saline soils, respectively, while the soil ammonium nitrogen (NH4+-N) and available potassium (AK) contents were decreased. The NO3−-N, AN, and AP contents of the three croplands showed a significant surface aggregation at depth of 0–30 cm. SQI increased by 0.10, 0.09, and 0.02 after the reclamation with the enhancement effect of wheat and cotton was more pronounced. It was discovered that reclamation notably improved the soil quality as a result of crop growth and field management of fertilization and irrigation.
Effort to Mitigate Volatile Fatty Acid Inhibition by Using Mixed Inoculum and Compost for the Degradation of Food Waste and the Production of Biogas
Authors: Shyan Lai Llih , Mat Nanyan Noreen Suliani , Ismail Norli , Al-Gheethi Adel , T. Nguyen Hong-Ha , Vo Dai-Viet N. , El Enshasy Hesham Ali
Published: January 2023

Food waste is a rich organic matter that can potentially be converted into biogas as a source of renewable energy. The limitation in energy production lies in the presence of volatile fatty acid (VFA) during the anaerobic digestion of food waste due to the high degradation rate. The accumulation of VFA leads to a decrease in pH that exceeds the optimal pH range of 6.8–7.6 for methanogens, thus inhibiting methanogenesis and affecting biogas production. In the present study, a symbiotic culture of bacteria and yeast (SCOBY) and kombucha mixed inoculum and compost was applied as an alternative treatment method to alleviate inhibition. The digestion efficiency was evaluated on pH, total alkalinity (TA), total volatile fatty acid (TVFA), total solid (TS), and volatile solid (VS) throughout the digestion period of 80 days to analyse the stability of the system. The results revealed that SCOBY and kombucha mixed inoculum caused system instability, inducing inhibition at TVFA of 12,874.1 mg/L, while the pH dropped to 5.23. The inhibition in the digestion system with only the SCOBY inoculum occurred at TVFA of 11,908.3 mg/L, and the pH dropped to 5.67. The biogas and methane yield quantified from the mixed inoculum is 8.792E−4 L/L d, comparatively lower than the ethanol pre-fermentation treatment method. These findings indicate that the addition of compost improved the pH, VS, and TVFA.
Digital Finance and Advanced Manufacturing Industry Development in China: A Coupling Coordination Analysis
Authors: Ma Kun , Xia Xuehui , Liu Lijun
Published: January 2023

The coordinated development of digital finance and the advanced manufacturing industry is vital for high-quality economic development. Based on the provincial data of China from 2012 to 2020, this study applied the coupling coordination degree model, σ convergence model and Dagum–Gini coefficient decomposition method to analyze the coupling coordination level, convergence characteristics, spatial differences and sources of digital financial and advanced manufacturing industry development in China. The results show that the coupling coordination level between the two has crossed from the run-in transition stage to the coordinated development stage and shows a rapid growing trend. The coupling coordination degree of the eastern region is the highest, followed by the central and western regions. It has an obvious convergence trend, and the overall difference is significantly reduced. The intra-regional difference of coupling coordination degree in the western region is the largest, indicating the comparatively larger gap in the development of digital finance and the advanced manufacturing industry among western provinces. The inter-regional difference between the east–west regions is the largest and is the main source of overall differences, which proves the fact of unbalanced development between regions. It is suggested to adopt differentiated regional policies to promote the coordinated development of digital finance and the advanced manufacturing industry.
Sleepless Pandemic: A Cross-Sectional Analysis of Insomnia Symptoms among Professionally Active Romanians during the COVID-19 Pandemic
Authors: Ionescu Tiberiu Constantin , Fetecau Bogdana Ioana , Zaharia Stefan , Mînecan Elma-Maria , Tudose Catalina
Published: January 2023

Background: The COVID-19 pandemic put considerable strain on individual mental health. The current study aimed to determine the prevalence and severity of insomnia symptoms among students and employees during this period. Methods: This paper is a cross-sectional analysis using convenience sampling. A web-based anonymous survey was developed and included questions about socio-demographic characteristics, contact with COVID-19, and the Athens Insomnia Scale. Results: 620 participants, 331 students, and 289 employees were included in the final sample. According to the current findings, 21.29% (n = 132) of participants met the criteria for insomnia, and 39.03% (n = 242) met the criteria for mild sleep disturbances. Conclusions: Although respondents reported an increased prevalence of sleep disorders, these changes were not directly related to the presence or severity of the infection but rather to a variety of socio-demographic and lifestyle-related variables. Students associated more frequently with the next-day consequences of insomnia (overall functioning and sleepiness during the day), while for employees, the most prevalent were awakenings during the night and early morning awakenings. Furthermore, sleep difficulties were more prevalent in women, single people, sedentary people, and those with psychiatric disorders.
Pluvial Flash Flood Hazard and Risk Mapping in Croatia: Case Study in the Gospić Catchment
Authors: Krvavica Nino , Šiljeg Ante , Horvat Bojana , Panđa Lovre
Published: January 2023

Since the beginning of the 21st Century, Europe has been affected by destructive floods. European Union Member States have an obligation to develop flood hazard and flood risk maps as support to the Flood Risk Management Plan (FRMP). The main objective of this study is to propose a methodological framework for hazard and risk assessment of pluvial flash floods in Croatia at the catchment level, which can be integrated into the FRMP. Therefore, a methodology based on the source–pathway–consequence approach for flood risk assessment is presented, which complies with the EU Floods Directive. This integrated and comprehensive methodology is based on high-resolution open data available for EU Member States. Three scenarios are defined for a low, medium, and high probability, defined by design storms of different durations. The proposed methodology consists of flood hazard analysis, vulnerability assessment, and risk analysis. Pluvial flash flood hazards are analyzed using a 2D hydrologic–hydraulic model. The flood vulnerability assessment consists of a GIS analysis to identify receptors potentially at risk of flooding and an assessment of susceptibility to potential flood damage using depth–damage curves. Flood risk is assessed both qualitatively in terms of risk levels and quantitatively in terms of direct damages expressed in monetary terms. The developed methodology was applied and tested in a case study in the Gospić catchment in Croatia, which surrounds a small rural town frequently affected by pluvial flash floods.