bluuebunny/crossref_metadata_2025 huggingface dataset:
Sensing and Detection of Traffic Signs Using CNNs: An Assessment on Their Performance
Authors: Canese Lorenzo , Cardarilli Gian Carlo , Di Nunzio Luca , Fazzolari Rocco , Famil Ghadakchi Hamed , Re Marco , Spanò Sergio
Published: November 2022

Traffic sign detection systems constitute a key component in trending real-world applications such as autonomous driving and driver safety and assistance. In recent years, many learning systems have been used to help detect traffic signs more accurately, such as ResNet, Vgg, Squeeznet, and DenseNet, but which of these systems can perform better than the others is debatable. They must be examined carefully and under the same conditions. To check the system under the same conditions, you must first have the same database structure. Moreover, the practice of training under the same number of epochs should be the same. Other points to consider are the language in which the coding operation was performed as well as the method of calling the training system, which should be the same. As a result, under these conditions, it can be said that the comparison between different education systems has been done under equal conditions, and the result of this analogy will be valid. In this article, traffic sign detection was done using AlexNet and XresNet 50 training methods, which had not been used until now. Then, with the implementation of ResNet 18, 34, and 50, DenseNet 121, 169, and 201, Vgg 16_bn and Vgg19_bn, AlexNet, SqueezeNet1_0, and SqueezeNet1_1 training methods under completely the same conditions. The results are compared with each other, and finally, the best ones for use in detecting traffic signs are introduced. The experimental results showed that, considering parameters train loss, valid loss, accuracy, error rate and Time, three types of CNN learning models Vgg 16_bn, Vgg19_bn and, AlexNet performed better for the intended purpose. As a result, these three types of learning models can be considered for further studies.
Performance of Narrow Band Wide Area Networks with Gateway Diversity
Authors: Can Başak , Karaoğlu Bora , Bhat Uttam , Gencel Muhammed Faruk , Chen Thomas
Published: November 2022

This paper quantifies the coverage area of Low-Power Wide-Area Networks (LPWAN) for Packet Success Rates (PSR) above 85%, where acceptable Quality of Service (QoS) can be achieved. The network consists of battery-operated end-nodes (ENs) and multiple stationary gateways (GWs). We consider asynchronous communication that uses ALOHA-based random channel access. Each transmission from the ENs can be received by multiple GWs. Such spatial diversity results in favorable Signal-to-Noise ratios (SNR). The LoRa modulation is assumed and its specific features, such as IQ inversion, further contribute to decreasing the impact of interference. An increase in the GW density improves network performance, which allows support for a larger density of end-nodes as well as increasing the coverage area. Our simulation results show that a suburban area of up to 1.44 km2 can be covered with five GWs with up to fifty end-nodes with a PSR greater than 86%.
SA-FEM: Combined Feature Selection and Feature Fusion for Students’ Performance Prediction
Authors: Ye Mingtao , Sheng Xin , Lu Yanjie , Zhang Guodao , Chen Huiling , Jiang Bo , Zou Senhao , Dai Liting
Published: November 2022

Around the world, the COVID-19 pandemic has created significant obstacles for education, driving people to discover workarounds to maintain education. Because of the excellent benefit of cheap-cost information distribution brought about by the advent of the Internet, some offline instructional activity started to go online in an effort to stop the spread of the disease. How to guarantee the quality of teaching and promote the steady progress of education has become more and more important. Currently, one of the ways to guarantee the quality of online learning is to use independent online learning behavior data to build learning performance predictors, which can provide real-time monitoring and feedback during the learning process. This method, however, ignores the internal correlation between e-learning behaviors. In contrast, the e-learning behavior classification model (EBC model) can reflect the internal correlation between learning behaviors. Therefore, this study proposes an online learning performance prediction model, SA-FEM, based on adaptive feature fusion and feature selection. The proposed method utilizes the relationship among features and fuses features according to the category that achieved better performance. Through the analysis of experimental results, the feature space mined by the fine-grained differential evolution algorithm and the adaptive fusion of features combined with the differential evolution algorithm can better support online learning performance prediction, and it is also verified that the adaptive feature fusion strategy based on the EBC model proposed in this paper outperforms the benchmark method.
Multiagent-Based Data Presentation Mechanism for Multifaceted Analysis in Network Management Tasks
Authors: Sasai Kazuto , Fukutani Ryota , Kitagata Gen , Kinoshita Tetsuo
Published: November 2022

Although network management tasks are highly automated using big data and artificial intelligence technologies, when an unforeseen cybersecurity problem or fault scenario occurs, administrators sometimes directly analyze system data to make a heuristic decision. However, a wide variety of information is required to address complex cybersecurity risks, whereas current systems are focused on narrowing the candidates of information. In this study, we propose a multiagent-based data presentation mechanism (MADPM) that consists of agents operating data-processing tools that store and analyze network data. Agents in MADPM interact with other agents to form data-processing sequences. In this process, we design not only the composition of the sequence according to requirements, but also a mechanism to expand it to enable multifaceted analysis that supports heuristic reasoning. We tested five case studies in the prototype system implemented in an experimental network. The results indicated that the multifaceted presentation of data can support administrators more than the selected single-faceted optimal presentation. The final outcome of our proposed approach is the provision of a multifaceted and cross-system data presentation for heuristic inference in network management tasks.
Parental Warmth and Parent Involvement: Their Relationships to Academic Achievement and Behavior Problems in School and Related Gender Effects
Authors: Parmar Parminder , Nathans Laura
Published: November 2022

Parent involvement and parental warmth have been extensively studied in the global literature. However, limited research has been conducted on parent involvement and parental warmth in India. This study examined parental warmth and parent involvement as predictors of academic achievement and behavior problems. Because behavior problems scores differed gender, gender differences om these relationships were explored. Study questions were framed in terms of Epstein’s theory of school, family, and community partnerships and Rohner’s parental acceptance-rejection theory. A sample of Indian seventh through tenth graders gave ratings of parental warmth and parent involvement. Their teachers gave ratings of academic achievement and behavior problems. Results showed that parental warmth and parent involvement were significant predictors of academic achievement and behavior problems for boys. Parental warmth was a significant predictor of academic achievement and behavior problems for girls. The results regarding parental warmth supported parental acceptance-rejection theory. Results suggested the need to increase the awareness of the importance of parent involvement for children in India and to continue to support parents in maintaining warm and accepting relationships with their children.
Deep Drainage Lowers Methane and Nitrous Oxide Emissions from Rice Fields in a Semi-Arid Environment in Rwanda
Authors: Tuyishime Olive , Strömgren Monika , Joel Abraham , Messing Ingmar , Naramabuye Francois Xavier , Wesström Ingrid
Published: November 2022

Few studies have explored greenhouse gas (GHG) emissions from arable land in sub-Saharan Africa (SSA), and particularly from rice paddy fields, which can be a major source of methane (CH4) and nitrous oxide (N2O) emissions. This study examined the effect of drainage on CH4 and N2O emissions from rice fields in Rwanda under shallow drainage to 0.6 m, with the drain weir open four times per week, and deep drainage to 1.2 m with the weir open four times or two times per week. CH4 and N2O fluxes from the soil surface were measured on nine occasions during rice flowering and ripening, using a closed chamber method. Measured fluxes made only a minor contribution to total GHG emissions from rice fields. However, drainage depth had significant effects on CH4 emissions, with shallow drainage treatment giving significantly higher emissions (~0.8 kg ha−1 or ~26 kg CO2-equivalents ha−1) than deep drainage (0.0 kg) over the 44-day measurement period. No treatment effect was observed for N2O fluxes, which ranged from low uptake to low release, and were generally not significantly different from zero, probably due to low nitrogen (N) availability in soil resulting from low N fertilization rate (in the region). Overall, the results suggest that deep drainage can mitigate CH4 emissions compared with traditional shallow drainage, while not simultaneously increasing N2O emissions.
Reflexive Sustainable Technology Labs: Combining Real-World Labs, Technology Assessment, and Responsible Research and Innovation
Authors: Parodi Oliver , Bögel Paula , Beecroft Richard , Seebacher Andreas , Wagner Felix , Hahn Julia
Published: November 2022

There is an increasing call for science to contribute more to real-world solutions for a sustainability transformation. At the same time, the scientific landscape encompasses different concepts, which are characterized as practice-oriented, addressing social challenges and wicked problems, which thus offer potential to contribute to a transformation, notably: technology assessment (TA), responsible research and innovation (RRI), and real-world labs (RwLs). This article deals with the question of how these different concepts can be better integrated to contribute to a transformation. With this goal in mind, we analyze the three concepts, show their core characteristics, and identify their common key similarities. TA and RRI have rarely been connected to transformative sustainability research in general or RwLs in particular. Based on the key similarities and respective strengths of the three concepts, we suggest four ways to integrate the approaches, including the novel endeavor of a Reflexive Sustainable Technology Lab as the highest level of the concepts’ synthesis.
EMCS: An Energy-Efficient Makespan Cost-Aware Scheduling Algorithm Using Evolutionary Learning Approach for Cloud-Fog-Based IoT Applications
Authors: Sing Ranumayee , Bhoi Sourav Kumar , Panigrahi Niranjan , Sahoo Kshira Sagar , Bilal Muhammad , Shah Sayed Chhattan
Published: November 2022

The tremendous expansion of the Internet of Things (IoTs) has generated an enormous volume of near and remote sensing data, which is increasing with the emergence of new solutions for sustainable environments. Cloud computing is typically used to help resource-constrained IoT sensing devices. However, the cloud servers are placed deep within the core network, a long way from the IoT, introducing immense data transactions. These transactions require heavy electricity consumption and release harmful CO2 to the environment. A distributed computing environment located at the edge of the network named fog computing has been promoted to reduce the limitation of cloud computing for IoT applications. Fog computing potentially processes real-time and delay-sensitive data, and it reduces the traffic, which minimizes the energy consumption. The additional energy consumption can be reduced by implementing an energy-aware task scheduling, which decides on the execution of tasks at cloud or fog nodes on the basis of minimum completion time, cost, and energy consumption. In this paper, an algorithm called energy-efficient makespan cost-aware scheduling (EMCS) is proposed using an evolutionary strategy to optimize the execution time, cost, and energy consumption. The performance of this work is evaluated using extensive simulations. Results show that EMCS is 67.1% better than cost makespan-aware scheduling (CMaS), 58.79% better than Heterogeneous Earliest Finish Time (HEFT), 54.68% better than Bees Life Algorithm (BLA) and 47.81% better than Evolutionary Task Scheduling (ETS) in terms of makespan. Comparing the cost of the EMCS model, it uses 62.4% less cost than CMaS, 26.41% less than BLA, and 6.7% less than ETS. When comparing energy consumption, EMCS consumes 11.55% less than CMaS, 4.75% less than BLA and 3.19% less than ETS. Results also show that with an increase in the number of fog and cloud nodes, the balance between cloud and fog nodes gives better performance in terms of makespan, cost, and energy consumption.
A New p–y Curve for Laterally Loaded Large-Diameter Monopiles in Soft Clays
Authors: Wang Mingyuan , Wang Miao , Cheng Xinglei , Lu Qun , Lu Jiaqing
Published: November 2022

In harsh offshore environmental conditions, the monopile foundations supporting offshore wind turbines must be designed for lateral loads such as winds, waves, and currents. The Beam on Nonlinear Winkler Foundation (BNWF) method has been widely used because of its clear concept and lower calculation cost. The selection of a reasonable p–y curve is critical to the calculation accuracy of this method. This paper clarified the defects of widely used API p–y curves for soft clays and then proposed a new p–y curve with better versatility and applicability. The suitability of the proposed p–y curve was validated by comparing it with the calculation results from the three-dimensional finite element method (3D FEM). Compared with the API p–y curve, the proposed p–y curve can better predict the lateral behavior of large-diameter piles in soft clays, such as the load–displacement curve of the pile head, lateral deflection profile, and bending moment profile. The research findings can provide guidance for the design of monopile foundations supporting offshore wind turbines in soft clays.
Distribution Pattern of Coral Reef Fishes in China
Authors: Shi Juan , Li Chunhou , Wang Teng , Zhao Jinfa , Liu Yong , Xiao Yayuan
Published: November 2022

Coral reefs are known as “tropical rain forests” in the ocean. Fish diversity is extremely high, accounting for one-third of marine fishes. To better protect and manage coral reef fishes, this study systematically compiled documents and databases published in China. We counted 2855 species of coral reef fishes in China, which belong to 3 classes, 41 orders, 252 families, and 1017 genera. Among these, Perciformes was the dominant order, accounting for 57.31% of the total species. Gobiidae (7.43%), Labridae (5.36%), Pomacentridae (4.52%), and Serranidae (4.38%) were the main families, while other families accounted for less than 4%. Furthermore, 5.56% of coral reef fish species have entered the IUCN Red List. The present study found that coral reef fishes can be divided into nearshore and offshore. This was mainly because the nearshore coral reef fishes were more affected by human disturbance and runoff from the mainland, whereas offshore coral reef fishes were in areas with high salinity and temperature far from the mainland, where human disturbance was less. Coral reef fish species’ diversity had a significant positive correlation with coral species diversity (p < 0.05), mainly because corals provide habitat and shelter. This study is the first systematic compilation and analysis of coral reef fishes in China and provides a basic reference for global protection management and biological geographical analysis.
ICT and Economic Resilience during COVID-19: Cross-Country Analysis
Authors: Kim Jungsuk , Estrada Gemma , Jinjarak Yothin , Park Donghyun , Tian Shu
Published: November 2022

The central objective of this paper is to empirically assess whether countries with better information and communication technology (ICT) infrastructure suffered less GDP growth deceleration during COVID-19. The scope of this paper is to apply linear estimation to a sample of 117 economies, including 86 emerging market and developing economies and 31 advanced economies, to analyze the relationship between ICT and GDP growth deceleration during the pandemic period. Controlling for other variables that can also influence economic performance, we find empirical support for a positive impact of ICT. For a given COVID-19 infection rate, we find that economies with better internet access showed greater resilience, defined as less in terms of economic growth. The obvious policy implication is that governments should invest more in ICT infrastructure to strengthen the resilience of their economies in the face of major shocks.
Comparative Life Cycle Assessment of the Manufacturing of Conventional and Innovative Aerators: A Case Study in China
Authors: Hou Haochen , Wang Haiheng , Ren Anqi , Zhang Yun , Liu Ying
Published: November 2022

China aims to achieve a 50% rate of mechanization for aquaculture by 2025. Aerators are crucial mechanical equipment in aquaculture for increasing yield, but their manufacturing has an environmental impact. Improving the yield and controlling the environmental impacts of aerators in China is an important issue have to be considered, as is comparing the environmental impact of manufacturing innovative and conventional aerators. Herein, life cycle assessment (LCA) as a quantitative analysis method was used, and six models of three widely used aerators (impeller, paddle wheel, and wave) were selected as an example to compare the environmental impacts of conventional and innovative aerators from large-scale aerator manufacturing enterprises in Taizhou, China. The results showed that the conventional paddle wheel aerator (SC-1.5) had the largest environmental impact, while the innovative paddle wheel aerator (GSC-1.5) had the lowest environmental impact, reduced by 30%. In addition, the environmental impact of the innovative impeller aerator (SYL-1.5) and wave aerator (GYL-1.5) was less than that of the conventional impeller aerator (YL-1.5) wave aerator (SW-1.5), but only by 0.21% and 0.02%, respectively. Human toxic potential (HTP) made the largest contribution, and the manufacturing of copper wire was critical; the environmental impact was from 96.50% to 98.21% for all material inputs. The contributions of iron and stainless steel were 1.05–1.28% and 0.74–1.04%, respectively. Therefore, conductive materials with excellent environmental performance, such as carbon nanomaterials and nano copper wire, should replace copper wire in aerator manufacturing. The results expand aquaculture life cycle knowledge and could reduce the environmental impacts of aerator manufacturing in China.
Optimal Structuring of Investments in Electricity Generation Projects in Colombia with Non-Conventional Energy Sources
Authors: Saldarriaga-Loaiza Juan D. , Saldarriaga-Zuluaga Sergio D. , López-Lezama Jesús M. , Villada-Duque Fernando , Muñoz-Galeano Nicolás
Published: November 2022

Taking full advantage of fiscal and economic incentives has become a complex process for investors, who must find the right portfolio or capital structure to obtain viable and competitive generation projects. In this context, this paper proposes a methodology for the optimal structuring of investments in non-conventional energy sources (NCRES) considering fiscal and economic incentives. Three methods were evaluated: (1) levelized cost of electricity (LCOE) combined with three metaheuristic techniques; (2) discounted cash flow (DCF) with Monte Carlo simulation and value at risk (VaR); and (3) real options with Black and Scholes. The proposed approach presents as the main financial indicator the generation cost (GC), as well as three other financial indicators, namely: net present value (NPV), value at risk (VaR) and net present value for real options (NPVRO). The propose approach allows for defining different investment portfolios from where an investor can choose; each of which minimizes the GC. Furthermore, the methodology can be adapted to countries with different policies and fiscal incentives for the development of NCRES projects. The results show that for each metaheuristic, an optimal capital structure that minimizes GC is obtained; in this way, a GC of 0.032 (USD/kWh) is achieved for solar photovoltaic technology, with a reduction of 49.2%, when tax incentives are considered.
Numerical Simulation of the Thermal Environment during Summer in Coastal Open Space and Research on Evaluating the Cooling Effect: A Case Study of May Fourth Square, Qingdao
Authors: Zhang Ying , Hu Xijun , Cao Xilun , Liu Zheng
Published: November 2022

Urban green space is considered an important part of urban ecological construction be-cause of the efficiency of green space in reducing ambient temperature. It was previously reported that the quantity and layout of arbors and paving are very important factors for cooling. To research the combination mode of the quantity and layout of arbors and paving able to effectively lower the temperature during the summer in a coastal open space environment where little architecture exists, we built a numerical model of heat transfer using ENVI–met numerical modeling simulation, for which the May Fourth Square in Qingdao was selected. The results showed that the ratio coverage of the arbor layer and pavement fragmentation were positively correlated with the cooling effect. We found that setting the passageway conformed to the sea breeze by arbors and close planting at the air outlet effectively reduced the site temperature. After optimizing the site’s greening layout, the cooling effect over the process of time decreased in the height direction. At the same time, the cooling effect increased before 15:00 and then reduced gradually in the time dimension. Compared to the original site, the total cooling efficiency reached 1.41 × 108 J, equaling electric energy of about 39.2 kW·h. This research solves the issue of the synergy between planting and pavement for cooling coastal open spaces in summer and provides a basis to formulate a promotion strategy for landscape design areas with similar geographical and climatic conditions.
The Role of Intra-Industry Trade, Foreign Direct Investment, and Renewable Energy on Portuguese Carbon Dioxide Emissions
Authors: Leitão Nuno Carlos , Koengkan Matheus , Fuinhas José Alberto
Published: November 2022

This paper revisited the link between intra-industry trade (IIT) between Portugal and Spain and Portuguese carbon dioxide (CO2) emissions. The research also considers the effects of foreign direct investment (FDI) on CO2 emissions, pondering the arguments of the pollution haven hypothesis and the halo hypothesis. As an econometric strategy, this investigation has applied panel data, namely a Pooled Mean Group of an Autoregressive Distributed Lag (ARDL) model and Panel Quantile Regression (PQR). The preliminary unit root tests indicated that IIT, Portuguese and Spanish renewable energy, and Portuguese FDI are integrated into the first differences and stationary with the second generation test (Pesaran methodology). In the next step, this study applied the multicollinearity test and cross-dependence between the variables. The variance inflation factor test demonstrated that FDI and IIT have no multicollinear problems. However, as expected, collinearity exists between Portuguese and Spanish renewable energy. Regarding the cross-sectional dependence test, this investigation concluded that the variables have a dependence between them. The cointegration test revealed that the variables are overall cointegrated. In the econometric results with the ARDL estimator, this investigation has found that IIT between Portugal and Spain is negatively correlated with Portuguese CO2 emissions, showing that this type of trade encourages environmental improvements. However, the PQR demonstrates that there is an opposite relationship. According to this, Portuguese and Spanish renewable energy is negatively impacted by CO2 emissions, revealing that renewable energy aims to decrease pollution. Finally, Portuguese FDI reduces CO2 emissions, which is explained by product differentiation, innovation, and monopolistic competition.
Suitable Tillage Depth Promotes Maize Yields by Changing Soil Physical and Chemical Properties in A 3-Year Experiment in the North China Plain
Authors: Wang Lishu , Guo Haigang , Wang Lixuan , Cheng Dongjuan
Published: November 2022

Rotary tillage is a common farming method because of its ease of operation and low cost in the North China Plain. However, the rotary tillage depth is generally no more than 20 cm, and successive years of rotary tillage harden the root soil layers, which reduces maize’s ability to take root into the deep layer and decreases maize yields. The impact of the different rotary tillage depths and different plow pan thicknesses on maize yields was unclear and needs further study. In this study, a 3-year experiment was conducted, and three rotary tillage depths were designed: 20 cm tillage depth (D20), 25 cm tillage depth (D25), and 30 cm tillage depth (D30). The effects of different rotary tillage depths on soil’s physical and chemical properties, water use efficiency, photosynthetic rate, and maize yields were investigated. The results showed that soil bulk density significantly decreased and field capacity significantly increased in 10–30 cm soil layers by increasing the rotary tillage depths; soil water consumption, photosynthetic rate, and maize yields of D25 significantly increased in comparison to those of D20 and D30; soil bulk density, plow pan thickness, total nitrogen, total phosphorus, and total potassium had an obvious negative correlation with tillage depth and field capacity; the Denitrification–Decomposition (DNDC) model predicted maize yields well; structural equation models (SEM) revealed that rotary tillage depths and soil water consumption played an important role on maize yields; and D25 could increase maize yields by improving maize water use efficiency and photosynthetic rate. The tillage depth of 25 cm is a suitable rotary tillage depth for the increase in maize yields in the North China Plain.
The Flexural Performance of BFRP-Reinforced UHPC Beams Compared to Steel and GFRP-Reinforced Beams
Authors: Alhoubi Yazan , Mahaini Zin , Abed Farid
Published: November 2022

The performance of ultra-high-performance concrete (UHPC) reinforced with BFRP bars was investigated in this research study. To achieve the objectives of this study, a total of six UHPC beams were cast and tested for flexure, under displacement-controlled loading conditions. The performance of BFRP-reinforced beams was compared against GFRP and steel reinforced beams. All beams had a cross-section of 185 mm × 250 mm, and a total length of 2200 mm. The experimental results were presented and discussed in terms of cracking moments, cracking patterns, failure modes, flexural capacity, midspan deflection, as well as strains in concrete and reinforcement. Results showed that UHPC enhanced the flexural performance of BFRP-reinforced beams in terms of moment capacity, deflection response and cracking patterns. The experimental results were complimented with analytical results that were calculated using the ACI 440 and CAN/CSA S806 code provisions. It was found that moment predictions using relevant ACI equations are acceptable for under-reinforced beams, but were slightly unconservative for the over-reinforced beams.
The Effects of Household Debt and Oil Price Shocks on Economic Growth in the Shadow of the Pandemic
Authors: Li Xiangfa , Zhang Zhe , Xue Weixian , Wang Hua
Published: November 2022

In a sample of 34 countries during 1965Q2 to 2021Q3, this paper offers an empirical analysis of how household debt and oil price shocks influence economic growth in the shadow of the pandemic. We exploit the quarter lags inherent in the response of debt and the oil price to output to pin down the relationship between household debt, the oil price, and economic growth in an unrestricted panel VAR model. We find that household debt has a short-term positive impact on economic growth, and this impact is lagged, while oil price shocks have a negative effect on economic growth. Pandemic uncertainty has an obvious and positive effect on household debt, while it has an obvious and negative effect on economic growth and oil price. The results hold under several robustness tests.
Approximation of the Discharge Coefficient of Radial Gates Using Metaheuristic Regression Approaches
Authors: Sihag Parveen , Nouri Meysam , Ahmadpari Hedieh , Seyedzadeh Amin , Kisi Ozgur
Published: November 2022

Radial gates are widely used for agricultural water management, flood controlling, etc. The existence of methods for the calculation of the discharge coefficient (Cd) of such gates are complex and they are based on some assumptions. The development of new usable and simple models is needed for the prediction of Cd. This study investigates the viability of a metaheuristic regression method, the Gaussian Process (GP), for the determination of the discharge coefficient of radial gates. For this purpose, a total of 2536 experimental data were compiled that cover a wide range of all the effective parameters. The results of GP were compared with the Group Method of Data Handling (GMDH), Multivariate Adaptive Regression Splines (MARS), and linear and nonlinear regression models for predicting Cd of radial gates in both free-flow and submerged-flow conditions. The results revealed that the radial basis function-based GP model performed the best in free-flow condition with a Correlation Coefficient (CC) of 0.9413 and Root Mean Square Error (RMSE) of 0.0190 while the best accuracy was obtained from the Pearson VII kernel function-based GP model for the submerged flow condition with a CC of 0.9961 and RMSE of 0.0132.
Seismicity and Stress State in the Ryukyu Islands Subduction Zone
Authors: Xie Zhuojuan , Wang Enhui , Lyu Yuejun
Published: November 2022

Based on the newly compiled and mostly complete unified earthquake catalogue for China’s seas and adjacent areas, further information was obtained about the structural shape and dip angle of the Benioff zone in the Ryukyu Islands subduction zone during the different subduction stages. In addition, using the damped regional stress tensor inversion method, we were able to investigate the complex stress field characteristics and the dynamic significance of the shallow and intermediate earthquakes in the Ryukyu Islands subduction zone. The results show that the tectonic stress field of the Ryukyu Islands subduction zone was extensional along the subduction direction in the northern area of the Tokara Strait and was compressional along the subduction direction in the southern area of the Tokara Strait. The R value of the shallow stress field of the Okinawa Trough was low, and the σ3 was stable in the NNW direction with a small dip angle (>30°). The type of stress field in the shallow part of the Okinawa Trough transitioned from strike-slip type to normal fault type from north to south, reflecting the difference in the degree of development of the trough, and the southern segment of the trough began to transform into the expansion stage. The northeastern portion of the study area and southeast Taiwan constituted the high R value (0.68–0.87) region where the σ2 had tensile components. The stress state was biaxial tension–uniaxial compression, and the principal compressive stress was determined to be in the SEE direction with a large dip angle (>30°). The σ1 in northeast Taiwan exhibited a nearly vertical (>60°) plunge, while the σ2 and σ3 were nearly horizontal. The σ2 was thrust in the ENE–WSW direction, and the σ3 was extended in the NNW direction. Through this research, a greater understanding has been gained of the seismicity characteristics and shape of the Ryukyu Islands subduction zone. Supplementary research has also been completed on the focal mechanism solution and stress field of the Ryukyu Islands subduction zone. Finally, this research is important for earthquake hazard analysis and earthquake engineering safety evaluation in this area.
Productive and Nutritional Characteristics of Native Grasses from the Floodplain Banks Ecosystem in the Colombian Orinoquia
Authors: Salamanca-Carreño Arcesio , Vélez-Terranova Mauricio , Vargas-Corzo Oscar M. , Parés-Casanova Pere M. , Bentez-Molano Jannet
Published: November 2022

Productive and nutritional evaluations of native grasses are usually scarce, limiting their use in the feeding of herbivorous species. This study aims to determine the forage yield and nutritional value of native grasses from the floodplain “banks” ecosystem in the Colombian Orinoquia. Four native grasses (Paspalum plicatulum, Axonopus compresus, Axonopus purpussi, and Paspalum spp.) and a “control” grass (introduced Brachiaria hybrid cv. Mulato) were sown and sampled at 30, 40, and 50 days of age. On each sampling date, biomass production in a 1 m2 frame was estimated, and the chemical composition was analyzed using near-infrared spectroscopy. Data analysis included repeated measures analysis, correlations, and multiple linear regression. The grasses’ nutritional characteristics varied as follows: dry matter (DM, 0.9–2.5 ton/ha), crude protein (CP, 4.3–10.2%), neutral detergent fiber (NDF, 61–73.9%) ash (3.2–8.7%), and dry matter digestibility (DMD, 50.8–56.3%). P. plicatulum achieved comparable forage production to that of the “control” grass. A. purpussi, Paspalum sp., and P. plicatulum presented similar CP and ash contents, and a higher Ca:P ratio. Regression analysis indicated that DMD was affected by the CP and acid detergent fiber (ADF) levels. These native grasses constitute promising nutritional alternatives that must be considered in the region’s livestock-production systems; however, detailed studies to evaluate animal performance and consumption are still required.
Study on Cyclic Bearing Capacity of Suction Pile Based on Equivalent Cyclic Creep Model
Authors: Huang Kang , Zhu Wenbo , Liu Xin , Yao Zhongyuan , Zhang Yu , Yan Shu , Guo Xiaojiang , Dai Guoliang
Published: November 2022

In the process of cyclic loading, strain development not only presents the strain softening phenomenon, but also a strain hardening phenomenon, depending on the different values of static deflection stress. The strain hardening and strain softening characteristics of soft clay are studied by cyclic triaxial tests. The test results show that when the static deflection stress is zero, the value of cyclic cumulative strain is small, and the strain development presents the softening phenomenon. When the static deflection stress is greater than zero, the accumulation strain increases with increasing cyclic deflection stress, and the strain development present strain hardening phenomenon. Therefore, a strain softening index and strain hardening index were proposed to describe the cyclic characteristics of soil. Moreover, an equivalent cyclic creep model was established by considering the strain hardening index to describe cyclic characteristics of suction pile. The results obtained using the proposed method are in reasonably good agreement with the measured results. This can provide a new method for analyzing the cyclic characteristics of soil and the suction pile.
Size Estimation of Bulk Capacitor Removal Using Limited Power Quality Monitors in the Distribution Network
Authors: Tan Mingang , Zhang Chaohai , Chen Bin
Published: November 2022

With a large number of distributed generators (DG) and sensitive power loads connected to the distribution network, power quality issues have increasingly become the focus of users’ attention. Accurate and quick estimation of the amount of bulk capacitor removal that causes voltage sag is helpful to maintain power quality management equipment in time. This paper presents a novel size estimation of bulk capacitor removal using a limited power quality monitor (PQM) in the distribution network, including PQM deployment optimization, feeder localization, and capacitor removal amount calculation. The PQM placement is optimized by taking the estimated capacitance removal sizes of all buses as a constraint. The change of reactive power consumption before and after removing the capacitor at each power line is adopted to determine the feeder where the disturbance is located. Based on the impedance characteristics of the power grid components, the steady estimation method (SEM) is deduced using the fundamental voltage and current. Applying the sampling points of instantaneous voltage and current waveform, the transient estimation method (TEM) is constructed by data fitting. Case studies and index analysis for the IEEE 13 bus test work are presented to verify the reasonableness and accuracy of the proposed method for disturbed bus, capacitor size, load symmetry, disturbance duration, and DGs. SEM shows more stability and accuracy, while TEM performs faster and is more robust. The new methods provide a reliable and acceptable disturbance size estimation with several limited PQMs.
Research Status, Hotspots, and Evolutionary Trends of Global Digital Education via Knowledge Graph Analysis
Authors: Yang Duo , Zhou Jincheng , Shi Dingpu , Pan Qingna , Wang Dan , Chen Xiaohong , Liu Jiu
Published: November 2022

With the rapid development of emerging technologies such as big data, artificial intelligence, and blockchain and their wide application in education, digital education has received widespread attention in the international education field. The outbreak of COVID-19 in December 2019 further catalyzed the digitalization process in various industries, including education, and forced the education system to carry out digital reform and innovation. Digital education transformation has become a new hotspot of great interest in countries around the world and a major direction for education reform practices. Therefore, to better understand the status of global digital education research, this study uses CiteSpace (6.1.R2) visual analysis software to visualize and quantitatively analyze the literature on digital education research in the social science citation index (SSCI). First, the basic information of digital education was analyzed in terms of annual publication volume, authors, countries, and research institutions. Secondly, the main fields, basic contents, and research hotspots of digital education research were analyzed by keyword co-occurrence analysis mapping and keyword time zone mapping. Finally, the research frontiers and development trends of digital education between 2000 and 6 September 2022 were analyzed by cocitation clustering and citations. The results show that, based on the changes in annual publication volume, we can divide the development pulse of the digital education research field into three stages: the budding stage (2000–2006), the slow development stage (2007–2017), and the rapid development stage (6 September 2018–2022); there are 26 core authors in this field of research, among which Selwyn N has the highest number of publications; the USA, England, Spain, Australia, and Germany have the highest number of publications; Open Univ is the institution with the most publications; digital education’s research hotspots are mainly focused on interdisciplinary field practice research and adaptive education research based on big data support. The research frontiers are mainly related to five areas: interdisciplinary development, educational equity, digital education practice, digital education evaluation, and digital education governance. This paper systematically analyzes the latest developments in global digital education research, and objectively predicts that human–computer interdisciplinary teaching models and smart education may become a future development trend of digital education. The findings of this study are useful to readers for understanding the full picture of digital education research so that researchers can conduct more in-depth and targeted research to promote better development of digital education.
Effects of Physical Exercise on Executive Function in Adults with Depression: A Systematic Review and Meta-Analysis Protocol
Authors: Contreras-Osorio Falonn , Ramirez-Campillo Rodrigo , Cerda-Vega Enrique , Campos-Jara Rodrigo , Martínez-Salazar Cristian , Reigal Rafael E. , Morales-Sanchez Verónica , Araya Sierralta Sergio , Campos-Jara Christian
Published: November 2022

Physical exercise is a low-cost and easy-to-implement therapeutic option proposed to reduce the negative effect of depression on the executive function cognitive dimension, including working memory, inhibition, and cognitive flexibility. Although a considerable amount of scientific literature on the topic is currently available, the effects of physical exercise interventions on the executive functions in adults with depression remain unclear. The aim of this review protocol is to synthesize the effects of physical exercise interventions on executive functions in adults with depression. Databases including Web of Science, PubMed, Scopus, and EBSCO will be searched for studies by combining keywords and different medical subject headings to identify and evaluate the relevant studies from inception up to September 2022. This study will consider longitudinal studies (duration, ≥3 weeks) with a minimum of one experimental group and pre- and post-intervention measurements involving adults with depression aged 18–65 years. Studies will be included if these reported ≥1 measures of executive function, including dimensions of working memory, inhibition, and cognitive flexibility. The Physiotherapy Evidence Database (PEDro) scale will be used to assess the methodological quality of studies. The DerSimonian and Laird random-effects model will be used for meta-analyses, with effect size (ES, i.e., Hedges’ g) values reported with 95% confidence intervals (95% CIs), and p ≤ 0.05 will indicate statistical significance. The ES values will be calculated for working memory, inhibition, and cognitive flexibility in the experimental and control groups before and after the intervention program. Our results can help professionals and stakeholders in making better evidence-based decisions regarding the implementation of physical exercise programs in adults with depression and providing relevant information to facilitate the functional performance of this population in complex daily tasks where executive functions are essential. No ethical approval is required for this study. PROSPERO registration number: CRD42022358339.
Security Challenges and Economic-Geographical Metrics for Analyzing Safety to Achieve Sustainable Protection
Authors: Jekl Jan , Jánský Jiří
Published: November 2022

In this article, we aim to develop the theoretical background for the possible application of Economic-Geographical metrics in the field of population protection. We deal with various options for analyzing the availability of “safety” for citizens using studied metrics. Among others, we apply well-known metrics such as the Gini coefficient, Hoover index and even establish their generalizations. We develop a theoretical background and evaluate our findings on generated and actual data. We find that the metrics used can have an opposite interpretation depending on the scenario we are considering. We also discover that some scenarios demand a modification to the usual metric. We conclude that Economic-Geographical metrics give valuable tools to address specific security challenges. Metric’s generalizations could serve as a potent tool for other authors working in the field of population protection. Nevertheless, we must keep in mind that metrics also have drawbacks.
Study on Land Use Changes in Changsha–Zhuzhou–Xiangtan under the Background of Cultivated Land Protection Policy
Authors: Fan Xuejiao , Quan Bin , Deng Zhiwei , Liu Jianxiong
Published: November 2022

The Changsha–Zhuzhou–Xiangtan region has experienced rapid social and economic development over the past 40 years, and cultivated land has changed dramatically. The contradiction between built and cultivated land has intensified, for which the local government has implemented a series of policies related to cultivated land protection. However, thus far, it is not clear what the substantial effects of the cultivated land protection policies are. To this end, this paper quantitatively characterizes the changes in the Changsha–Zhuzhou–Xiangtan region during the 20 years before and after the implementation of the cultivated land occupation balance policy, based on land use data from 1980, 2000, and 2020 using intensity analysis. In this paper, we examine the types of spatial land use patterns occurring in Changsha–Zhuzhou–Xiangtan since 1980 and explore the transition path of land use types in urban–rural integration. After the cultivated land protection policy, the transformation relationship between land use types and the changing trend of the cultivated land area was analyzed from the landscape scale. The influence of policy factors on the transformation of land use types was revealed. The results show that, from 1980 to 2020, the changing intensity of construction land and unused land was relatively large and was in an active state; the amount of built land in the Changsha–Zhuzhou–Xiangtan region has been growing, with a net increase of 1101 km2, while the amount of cultivated land has been showing a net decrease, with a net reduction of 677 km2. Moreover, the cultivated land has mainly been converted into built land, and the lost cultivated land area in Changsha–Zhuzhou–Xiangtan has not been fully compensated elsewhere in the region, indicating that the cultivated land protection policy has not been able to maintain the cultivated land area in Changsha–Zhuzhou–Xiangtan. From 2000 to 2020, cultivated land change was mainly due to exchange, which indicates that the policy has had a particular effect on the protection of cultivated land. Still, if the government wants to achieve the “balance of cultivated land occupation and compensation” goal, it must establish a complete system for the allocation of cultivated land resources. This study can provide a scientific reference for further implementing the cultivated land protection policy, which is thus of great significance for promoting the construction of the Changsha–Zhuzhou–Xiangtan region and its high-quality economic and social development.
Environmental Auditing in Rural Areas: Current Patterns and Future Challenges in Central Asia
Authors: Brunelli Sandro , Murzakhmetova Anel , Falivena Camilla
Published: November 2022

Environmental audit (EA) is a systematic process of collecting and objectively evaluating information, whether certain environmental activities are in compliance with audit standards, criteria, and control systems. Due to the former use of the Soviet Union regime, Central Asia, with vast resources and a growing population, is still confronting a number of environmental issues. The increasing number of businesses in Central Asian countries has an impact on the local environment and the population’s health. As a response, EA is one of the instruments that businesses may use to improve their environmental performance, protect nature, and ensure public-health safety. This paper, after providing a scoping review concerning the academic literature, investigates, by using secondary data, the current trends and challenges in practical application of EAs in five Central Asian countries. Our findings point out a list of shortcomings in applying the EA tools in Central Asia, which mainly derive from implementation, legislative, and resource gaps. Thus, the road towards a concrete implementation of EA is still far from being achieved. The study ends with some pieces of advice for EA policy makers and opens up avenues for future research, which can also be applied outside Central Asia.