bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparative Analysis of Mechanical Properties of Three Typical Bolts under the Influence of Bed Separation
Authors: Shang Fulu , Lu Zelin , Zhu Zhen , Wang Xuchun , Ma Hao , Du Mingqing , Zhang Peng
Published: November 2023

In order to compare the mechanical characteristics and supporting performance of the lengthened anchored pre-stressed bolt, the full-length anchored bolt and the full-length anchored pre-stressed bolt under the bed separation conditions, theoretical and numerical analysis models of the three typical bolts were established, respectively. The influences of preload, bed separation values, bed separation numbers and bed separation positions on the mechanical properties of the three typical bolts were studied by numerical simulation method, and the mechanical properties of the three typical bolts were compared and analysed, and the sensitivity analysis of the crack opening of the three typical bolts was carried out. Results indicate that the initial preload can exert obvious restraint on the surrounding rock, in which the preload transmission range of the full-length anchored pre-stressed bolt is larger, and the restraint effect on the surrounding rock is better. Under the different bed separation conditions, the stress characteristics of the three typical bolt bodies at the bed separation basically follow the same law except for the free section of the lengthened anchored pre-stressed bolt. Under the action of the bed separation, the initial bonding section of the full-length anchored pre-stressed bolt and the free section of the lengthened anchored bolt have a certain influence on the distribution of the axial force and shear stress at the anchorage interface. The sensitivity of the two kinds of full-length anchored bolts is higher than that of the lengthened anchored pre-stressed bolt under the left bed separation condition. There is little difference in sensitivity between three typical bolts under the middle and right bed separation conditions. The research results can provide theoretical guidance for the selection of bolts in roadway support.
Coastal Flood Mapping with Two Approaches Based on Observations at Furadouro, Northern Portugal
Authors: Carneiro-Barros Jose E. , Plomaritis Theocharis A. , Fazeres-Ferradosa Tiago , Rosa-Santos Paulo , Taveira-Pinto Francisco
Published: November 2023

This study assesses coastal flooding extension mapping based on two innovative approaches. The first is based on the coupling of two robust numerical models (SWASH and LISFLOOD); in this case, discharges were extracted from the wave overtopping results from SWASH 1D and set as boundary conditions for LISFLOOD on the crest of an existing seawall where overtopping typically occurs. The second, hereby called the ‘Tilted Bathtub Approach’ (TBTA), is based on wave run-up levels and buffering the affected area of a prior flooding event, adjusting it for expected sea states according to different return periods. The proposed approaches are applied to a case study on the Northern Portuguese coast, at Furadouro beach, in the municipality of Ovar, which has been facing multiple flooding episodes throughout recent years, including a dramatic storm in February 2014. This event was used as validation for the proposed methods. A 30-year-long hourly local wave climate time series was used both to perform an extreme value analysis in order to obtain expected sea states according to different return periods and also for performing a sensitivity test for established empirical formulas to estimate wave run-up in this particular case. Results indicate both approaches are valuable: they yield coherent flood extension predictions that align well with the real inundated area from the 2014 storm. The convergence of these findings underscores the potential for these methods in future coastal flood risk assessment, planning, and understanding of coastal responses under extreme weather conditions.
Improved Initial Orbit Determination Based on the Gooding Method of Low Earth Orbit Space Debris Using Space-Based Observations
Authors: Yin Yewen , Li Zhenwei , Liu Chengzhi , Kang Zhe , Sun Jiannan , Chen Long
Published: November 2023

Initial orbit determination (IOD), as a basis for initial orbit association and accurate orbit determination (OD), has a crucial role in the process of obtaining space debris orbit information. Among the traditional methods, the Gooding method has better convergence and stability. In this study, the Gooding method is enhanced to solve the issues discovered. A novel initial orbit determination (IOD) method is developed using the proposed improvement measures of the single-parameter initial value determination (SIVD) method, the fitted-curve noise suppression method, the restricted corrective value solution method, the removal of trivial solutions, etc. The experimental results verify the effectiveness of the improved method. The success rate of the initial orbit determination reached 99%, and the accuracy of the solved orbit parameters was significantly improved, especially the semi-major axis (SMA) error of less than 50 km, accounting for 88% of the total. It can be seen that the method meets the demand of space-based space debris cataloging for initial orbit association and can serve in the field of space situational awareness, which has important practical significance and application potential.
Investigating the Identification and Spatial Distribution Characteristics of Camellia oleifera Plantations Using High-Resolution Imagery
Authors: Li Yajing , Yan Enping , Jiang Jiawei , Cao Dan , Mo Dengkui
Published: November 2023

Camellia oleifera is a vital economic crop of southern China. Accurate mapping and monitoring of Camellia oleifera plantations are essential for promoting sustainable operations within the Camellia oleifera industry. However, traditional remote sensing interpretation methods are no longer feasible for the large-scale extraction of plantation areas. This study proposes a novel deep learning-based method that utilizes GF-2 remote sensing imagery to achieve precise mapping and efficient monitoring of Camellia oleifera plantations. First, we conducted a comparative analysis of the performance of various semantic segmentation models using a self-compiled dataset of Camellia oleifera plantations. Subsequently, we proceeded to validate the prediction results obtained from the most effective deep-learning network model for Camellia oleifera plantations in Hengyang City. Finally, we incorporated DEM data to analyze the spatial distribution patterns. The findings indicate that the U-Net++ network model outperforms other semantic segmentation methods when applied to our self-generated dataset of Camellia oleifera plantations. It achieves a recall rate of 0.89, a precision rate of 0.92, and an mIOU of 0.83, demonstrating the effectiveness of the proposed method in identifying and monitoring Camellia oleifera plantations. By combining the predicted results with the data from DEM, we discovered that these plantations are typically situated at elevations ranging from 50 to 200 m, with slopes below 25°, and facing south or southeast. Moreover, a significant positive spatial correlation and clustering phenomenon are observed among the townships in Hengyang City. The method proposed in this study facilitates rapid and precise identification and monitoring of Camellia oleifera plantations, offering significant theoretical support and a scientific foundation for the management and ecological conservation of Camellia oleifera plantations.
Wavelet Analysis of a Sentinel-2 Time Series to Detect Land Use Changes in Agriculture in the Vega Alta of the Guadalquivir River: Cantillana Case Study (Seville)
Authors: Ramírez-Juidias Emilio , Amaro-Mellado José-Lázaro , Antón Daniel
Published: November 2023

Historically, the Vega Alta of the Guadalquivir River (southern Spain) has been an anthropized space. Over time, the dominance of latifundia agriculture has evolved towards more intensive citrus-based agriculture. In this study, wavelet algorithms applied to Sentinel-2 time series were used to determine both the expansion of citrus plantations and the level of intensification of these plantations within the municipality of Cantillana. Sentinel-2 provides comprehensive global coverage from March 2017 to the present. Our study applied a 90% power wavelet transformation for the creation of a wavelet-smoothed time series for four years of Sentinel-2 NDVI data. Based on the data, it can be stated that within our research region covering 5000 hectares of agricultural land, over a span of four years (2017 to 2020), more than 980 hectares of native vegetation and pasture were transformed into citrus orchards, giving rise, at the end of 2020, to a total area of 3250 ha. Analyzing unique spatial patterns within a wavelet-smoothed time series data is very useful for land management, as it allows land use changes to be controlled. For this reason, it becomes feasible to assess the reliability of the wavelet method using both remote sensing and GIS tools.
A Multi-Stream Attention-Aware Convolutional Neural Network: Monitoring of Sand and Dust Storms from Ordinary Urban Surveillance Cameras
Authors: Wang Xing , Yang Zhengwei , Feng Huihui , Zhao Jiuwei , Shi Shuaiyi , Cheng Lu
Published: November 2023

Sand and dust storm (SDS) weather has caused several severe hazards in many regions worldwide, e.g., environmental pollution, traffic disruptions, and human casualties. Widespread surveillance cameras show great potential for high spatiotemporal resolution SDS observation. This study explores the possibility of employing the surveillance camera as an alternative SDS monitor. Based on SDS image feature analysis, a Multi-Stream Attention-aware Convolutional Neural Network (MA-CNN), which learns SDS image features at different scales through a multi-stream structure and employs an attention mechanism to enhance the detection performance, is constructed for an accurate SDS observation task. Moreover, a dataset with 13,216 images was built to train and test the MA-CNN. Eighteen algorithms, including nine well-known deep learning models and their variants built on an attention mechanism, were used for comparison. The experimental results showed that the MA-CNN achieved an accuracy performance of 0.857 on the training dataset, while this value changed to 0.945, 0.919, and 0.953 in three different real-world scenarios, which is the optimal performance among the compared algorithms. Therefore, surveillance camera-based monitors can effectively observe the occurrence of SDS disasters and provide valuable supplements to existing SDS observation networks.
Improving 3D Digital Soil Mapping Based on Spatialized Lab Soil Spectral Information
Authors: Sun Zheng , Liu Feng , Wang Decai , Wu Huayong , Zhang Ganlin
Published: November 2023

Readily available environmental covariates in current digital soil mapping usually do not indicate the spatial differences between deep soil attributes. This, to a large extent, leads to a decrease in the accuracy of 3D soil mapping with depth, which seriously affects the quality of soil information generated. This study tested the hypothesis that spatialized laboratory soil spectral information can be used as environmental covariates to improve the accuracy of 3D soil attribute mapping and proposed a new type of environmental covariable. In the first step, with soil-forming environmental covariates and independent soil profiles, laboratory vis-NIR spectral data of soil samples resampled into six bands in Anhui province, China, were spatially interpolated to generate spatial distributions of soil spectral measurements at multiple depths. In the second step, we constructed three sets of covariates using the laboratory soil spectral distribution maps at multiple depths: conventional soil-forming variables (C), conventional soil-forming variables plus satellite remote sensing wavebands (C+SRS) and conventional soil-forming variables plus spatialized laboratory soil spectral information (C+LSS). In the third step, we used the three sets of environmental covariates to develop random forest models for predicting soil attributes (pH; CEC, cation exchange capacity; Silt; SOC, soil organic carbon; TP, total phosphorus) at multiple depths. We compared the 3D soil mapping accuracies between these three sets of covariates based on another dataset of 132 soil profiles (collected in the 1980s). The results show that the use of spatialized laboratory soil spectral information as additional environmental covariates has a 50% improvement in prediction accuracy compared with that of only conventional covariates, and a 30% improvement in prediction accuracy compared with that of the satellite remote sensing wavebands as additional covariates. This indicates that spatialized laboratory soil spectral information can improve the accuracy of 3D digital soil mapping.
Improving Cloud Detection in WFV Images Onboard Chinese GF-1/6 Satellite
Authors: Chang Hao , Fan Xin , Huo Lianzhi , Hu Changmiao
Published: November 2023

We have developed an algorithm for cloud detection in Chinese GF-1/6 satellite multispectral images, allowing us to generate cloud masks at the pixel level. Due to the lack of shortwave infrared and thermal infrared bands in the Chinese GF-1/6 satellite, bright land surfaces and snow are frequently misclassified as clouds. To mitigate this issue, we utilized MODIS standard snow data products for reference data to determine the presence of snow cover in the images. Subsequently, our algorithm was utilized to correct misclassifications in snow-covered mountainous regions. The experimental area selected was the perpetually snow-covered Western mountains in the United States. The results indicate the accurate labeling of extensive snow-covered areas, achieving an overall cloud detection accuracy of over 91%. Our algorithm enables users to easily determine whether pixels are affected by cloud contamination, effectively improving accuracy in annotating data quality and greatly facilitating subsequent data retrieval and utilization.
Statistical Seismic Analysis by b-Value and Occurrence Time of the Latest Earthquakes in Italy
Authors: Lacidogna Giuseppe , Borla Oscar , De Marchi Valentina
Published: November 2023

The study reported in this paper concerns the temporal variation in the b-value of the Gutenberg–Richter frequency–magnitude law, applied to the earthquakes that struck Italy from 2009 to 2016 in the geographical areas of L’Aquila, the Emilia Region, and Amatrice–Norcia. Generally, the b-value varies from one region to another dependent on earthquake incidences. Higher values of this parameter are correlated to the occurrence of low-magnitude events spread over a wide geographical area. Conversely, a lower b-value may lead to the prediction of a major earthquake localized along a fault. In addition, it is observed that each seismic event has a different “occurrence time”, which is a key point in the statistical study of earthquakes. In particular, its results are absolutely different for each specific event, and may vary from years to months or even just a few hours. Hence, both short- and long-term precursor phenomena have to be examined. Accordingly, the b-value analysis has to be performed by choosing the best time windows to study the foreshock and aftershock activities.
Single Line-to-Ground Fault Type Multilevel Classification in Distribution Network Using Realistic Recorded Waveform
Authors: Liu Jiajun , Li Chenjing , Liu Yue , Sun Ji , Lin Haokun
Published: November 2023

The further identification of fault types for single line-to-ground faults (SLGFs) in distribution networks is conducive to determining the cause of grounding faults and formulating targeted measures for hidden danger treatment and fault prevention. For the six types of SLGFs generated in the actual power grid, this paper deeply studies their fault characteristics. Firstly, the classification criterion of fault transition resistance is derived by the generation mechanism of fault zero sequence voltage (ZSV). At the same time, by comparing and analyzing the same and different characteristics between faults, three criteria for fault classification are obtained. Based on the above four criteria, a multilevel and multicriteria fault classification method is proposed to judge six types of SLGFs. Then, the proposed method is verified by various fault state simulations of the distribution network model with a balanced topology and unbalanced topology. The engineering application of the method is demonstrated by the verification of actual power grid data. Finally, noise and data loss interference test results show the robustness of the method.
Research on the Recognition and Tracking of Group-Housed Pigs’ Posture Based on Edge Computing
Authors: Zha Wenwen , Li Hualong , Wu Guodong , Zhang Liping , Pan Weihao , Gu Lichuan , Jiao Jun , Zhang Qiang
Published: November 2023

The existing algorithms for identifying and tracking pigs in barns generally have a large number of parameters, relatively complex networks and a high demand for computational resources, which are not suitable for deployment in embedded-edge nodes on farms. A lightweight multi-objective identification and tracking algorithm based on improved YOLOv5s and DeepSort was developed for group-housed pigs in this study. The identification algorithm was optimized by: (i) using a dilated convolution in the YOLOv5s backbone network to reduce the number of model parameters and computational power requirements; (ii) adding a coordinate attention mechanism to improve the model precision; and (iii) pruning the BN layers to reduce the computational requirements. The optimized identification model was combined with DeepSort to form the final Tracking by Detecting algorithm and ported to a Jetson AGX Xavier edge computing node. The algorithm reduced the model size by 65.3% compared to the original YOLOv5s. The algorithm achieved a recognition precision of 96.6%; a tracking time of 46 ms; and a tracking frame rate of 21.7 FPS, and the precision of the tracking statistics was greater than 90%. The model size and performance met the requirements for stable real-time operation in embedded-edge computing nodes for monitoring group-housed pigs.
Vehicle State Joint Estimation Based on Lateral Stiffness
Authors: Quan Lingxiao , Chang Ronglei , Guo Changhong , Li Bin
Published: November 2023

In this study, a vehicle state joint estimation method based on lateral stiffness was applied to estimate the running states of electric vehicles driven by rear-drive, in-wheel motors. Different from the estimation methods used in other research, the joint estimator designed in this study uses the least-squares (LS) algorithm to estimate the lateral stiffness of the front and rear axles of the vehicle, deploying the high-degree cubature Kalman filter algorithm to estimate the vehicle state. We establish a three-degree-of-freedom nonlinear vehicle model with longitudinal velocity, lateral velocity, and yaw rate, and the lateral stiffness of the front and rear axles as the principal parameters. For the low-speed running state of the vehicle, a linearized magic tire model with high fitting accuracy was used to calculate the lateral force of the entire vehicle. The LS algorithm with a forgetting factor was used to design a lateral stiffness estimator to assess the front-axle and rear-axle lateral stiffness of the entire vehicle. The generalized high-degree cubature Kalman filter (GHCKF) algorithm was used to design the vehicle state estimator and further improve the GHCKF algorithm. A vehicle state estimator, using the square root generalized high-degree cubature Kalman filter (SRGHCKF), was designed. Therefore, the joint estimator, comprising a lateral stiffness estimator and a vehicle state estimator, adopts the LS-GHCKF/SRGHCKF algorithm and enables the estimation of the lateral stiffness, the longitudinal velocity, the lateral velocity, and the yaw rate of the entire vehicle during the driving process. A double lane change and slalom simulation were performed to analyze the feasibility and accuracy of the joint estimation algorithm and verify the results of the LS-GHCKF algorithm and the LS-SRGHCKF algorithm. Further, a low-speed driving experiment was carried out for electric vehicles driven by rear in-wheel motors. The inertial navigation system (INS), the global positioning system (GPS), the real-time kinematic (RTK), and an angle sensor were used to collect real-time vehicle data. The results were compared to verify the feasibility of the joint estimator and the progressiveness of the algorithm. The experimental verification and simulation both show that the vehicle state joint estimator, designed based on the LS-GHCKF/SRGHCKF algorithm, can accurately estimate the real-time state of the vehicle. Additionally, the LS-SRGHCKF algorithm shows better effectiveness and robustness than the LS-GHCKF algorithm.
FT-Raman Methodology Applied to Study the Effect of Time and Type of Seasoning in the Crafting of Sherry Casks® Used in the Aging of Brandy De Jerez
Authors: Guerrero-Chanivet María , Guillén-Sánchez Dominico A. , Valcárcel-Muñoz Manuel José , García-Moreno M. Valme , Anjos Ofelia
Published: November 2023

Brandy de Jerez is a grape-derived spirit produced in Southern Spain with specific characteristics that come from the casks where it is produced, which must have previously contained some type of Sherry wine for at least 12 months. These casks are known as Sherry Cask®. In this work, Brandies de Jerez aged for different aging times (0, 3, 6 and 12 months) in casks seasoned with three different types of Sherry wines (Fino, Oloroso and Amontillado) have been studied. The samples have been analyzed using FT-Raman spectroscopy, and their chemical characterization has also been realized by studying their total content of organic acid, volatile compounds, and phenolic and furanic compounds. Their chemical study showed that the main differences between the studied samples were due to the duration and the type of seasoning performed. However, the spectra obtained through FT-Raman presented noticeable differences according to cask seasoning time and the Sherry wine used for the process. A PCA (Principal Component Analysis) confirmed that the Brandies de Jerez presented significant differences depending on the seasoning time and type that the casks were subjected to. A PLS-R (Partial Least Squares Regression) study enabled establishing a close correlation between specific regions of the FT-Raman spectra and cask seasoning time.
Heritage and Railways: Sustainable Tourism Opportunities Boosted by Digital Transformation
Authors: Quattrini Ramona , Berrocal Menárguez Ana B. , Zamorano Martin Clara
Published: November 2023

This Special Issue focuses on the debate and recent trends in research dealing with railways, touristic itineraries, landscape and heritage digital documentation, while keeping in mind the goals of “The European Year of Rail” [...]
A Bibliometric Analysis on Cooperatives in Circular Economy and Eco-Innovation Studies
Authors: Guerreschi Asia , Díaz López Fernando J.
Published: November 2023

Cooperatives address societal challenges embracing values beyond mere profit-oriented production. Considering the ongoing shift to achieve efficient use of resources and increased circularity, cooperatives should be better equipped to incorporate circular economy (CE) and eco-innovation (EI) into their strategies (compared to regular enterprises). This paper reviews the scholarly literature focusing on the application of CE and EI within cooperative studies with the aim to understand the relationships between these topics, identify the existing scholarly communities, and to observe salient research themes. This study refined the method of van den Hoven and Rubalcaba (2016) to conduct a two-step bibliographic review of documents: a thematic analysis of citation data from Scopus (including a manual review of 16 papers) was followed by a bibliometric analysis of 101 documents from Web of Science (using R-Studio’s Biblioshiny). Our results identified three intellectual clusters of cooperative studies focusing on the downstream of CE: (1) industrial ecology; (2) recycling; and (3) waste management. Our study also revealed an emerging scholarly field focused on cooperatives and CE, and with little attention to EI. These findings aim at catalyzing the integration of cooperatives more effectively into scholarly discussions, suggesting that environmental sustainability should be recognized as an additional principle of the cooperative identity—providing a wider perspective that enhances interest in the research of these topics and their interconnections.
Does Digital Transformation Promote Green and Low-Carbon Synergistic Development in Enterprises? A Dynamic Analysis Based on the Perspective of Chinese Listed Enterprises in the Heavy Pollution Industry
Authors: Wang Sen , Li Jinye
Published: November 2023

Digital transformation has become essential in promoting and upgrading enterprise elements and reshaping the market’s competitive landscape. However, whether digital transformation can further promote green and low-carbon synergistic development is still being determined. Using data from 2008 to 2014 matched between A-share listed enterprises in China’s heavily polluting industries and China’s industrial enterprise pollution emission database (robustness tests were used city panel data from 2013 to 2019 to overcome the timeliness of enterprise-level data), we measured the green total factor productivity, carbon emission efficiency, and joint emission reduction efficiency of heavily polluting listed companies. We examined the dynamic impact of corporate digital transformation on corporate pollution and carbon emission reduction. The empirical results show that (1) digital transformation inhibits the enterprise’s all-green factor productivity, carbon emission efficiency, and joint emission reduction efficiency in the short term but promotes them in the long term. Digital transformation can improve these three efficiencies by enhancing the enterprise’s green technology innovation ability and optimizing factor allocation efficiency. (2) A heterogeneity analysis found that, in the external environment, the increase in environmental regulation enhances the impact of digital transformation on these three efficiencies; in the internal environment, the improvement of the competitiveness of the enterprise’s products strengthens the promotion of digital transformation on the three efficiencies of pollution emission reduction and carbon emission reduction. (3) Further research shows that, in the long run, digital transformation can improve the synergistic effect of the pollution reduction and carbon emission reduction of enterprises. This is instructive for Chinese enterprises to achieve the synergistic development of digital transformation and green, low-carbon production.
Elemental Profile in Chicken Egg Components and Associated Human Health Risk Assessment
Authors: Voica Cezara , Cristea Gabriela , Iordache Andreea Maria , Roba Carmen , Curean Victor
Published: November 2023

Egg is a food product of high nutritional quality, extensively consumed worldwide. The objectives of this study were the determination of the elemental profile in eggs (egg white, yolk, and eggshell), the estimation of the non-carcinogenic health risk associated with the presence of heavy metals in investigated egg samples, and the development of statistical models to identify the best predictors for the differentiation of egg components. The assessments were carried out in a total set of 210 samples, comprising home-produced and commercial eggs, using inductively coupled plasma mass spectrometry. The results suggested measurable differences amongst hen eggs coming from different husbandry systems. The statistical models employed in this study identified several elemental markers that can be used for discriminating between market and local producer samples. The non-carcinogenic risk related to the consumption of the analyzed egg samples was generally in the safe range for the consumers, below the maximum permitted levels set by Romanian and European legislation. Food contamination is a public health problem worldwide, and the risk associated with exposure to trace metals from food products has aroused widespread concern in human health, so assessing the heavy metal content in food products is mandatory to evaluate the health risk.
Independent Protection and Influence of the Spike-Specific Antibody Response of SARS-CoV-2 Nucleocapsid Protein (N) in Whole-Virion Vaccines
Authors: Yang Huijie , Xie Ying , Lu Shuaiyao , Sun Yufang , Wang Kaiqin , Li Shuyan , Wang Junzhi , Liao Guoyang , Li Changgui
Published: November 2023

Of all of the components in SARS-CoV-2 inactivated vaccines, nucleocapsid protein (N) is the most abundant and highly conserved protein. However, the function of N in these vaccines, especially its influence on the targeted spike protein’s response, remains unknown. In this study, the immunization of mice with the N protein alone was shown to reduce the viral load, alleviating pulmonary pathological lesions after challenge with the SARS-CoV-2 virus. In addition, co-immunization and pre-immunization with N were found to induce higher S-specific antibody titers rather than compromise them. Remarkably, the same trend was also observed when N was administered as the booster dose after whole inactivated virus vaccination. N-specific IFN-γ-secreting T cell response was detected in all groups and exhibited a certain relationship with S-specific IgG antibody improvements. Together, these data indicate that N has an independent role in vaccine-induced protection and improves the S-specific antibody response to inactivated vaccines, revealing that an interplay mechanism may exist in the immune responses to complex virus components.
Parabens and Methylisotiazolinone (MIT): Preservatives with Different Behaviors When Subjected to Ozone and Ultraviolet Light Treatments
Authors: López-Timoner Rubén , Duarte-Alvarado Victoria , Castillo María Ángeles , Santos-Juanes Lucas , Arques Antonio , Amat Ana María
Published: November 2023

The influence that contaminants exert on the degradation of other substances commonly found in the same water bodies drives this study, which aims to investigate the simultaneous degradation of preservatives such as parabens and methylisothiazolinone (MIT). Mixtures of five parabens, MIT solutions, and mixtures of all five parabens plus MIT (each at 5 mg/L) were treated using 254 nm UV light, ozone treatments, and simultaneous ozone and UV light treatments at three different pH levels (3, 5, and 9). Regardless of pH, UV light is inefficient in degrading parabens, whereas MIT is efficiently degraded under this radiation. On the other hand, ozone treatments rapidly degrade the paraben mixture at any pH, with a basic pH resulting in faster degradation due to the predominance of the indirect mechanism. MIT, due to its structural characteristics, reacts minimally with ozone, and the process is enhanced at basic pH when hydroxyl radicals are involved. The simultaneous treatment with ozone and UV light proves to be the fastest method for eliminating both parabens and MIT at any pH. However, when treating joint mixtures of parabens and MIT, behaviors change notably, particularly for processes involving UV light due to the interfering effect of MIT. Both parabens and MIT require more time to degrade, except at an acidic pH. Only MIT reduces its ozone treatment time when treated alongside parabens due to the distinct degradation mechanisms that each type of contaminant has in the presence of ozone.
Comparative Experimental Study of Geotube Groins and Mixed Clay–Geotube Groins under Various Flow Conditions
Authors: Tu Xiaobing , Gao Hongxiang , Fan Kejie , Xu Jiahao , Li Jianxiong , Xia Chunchen , Pang Xinjie
Published: November 2023

During the cofferdam construction of the toe reinforcement project at the Qiantang River Estuary, the scouring of the riverbed at the groin head often led to the collapse of geotube groins due to strong tidal currents. Based on field experience, employing a combination of clay and geotubes proved to be a more effective solution to this problem. This study adopted a flume model experiment to investigate the scouring and deposition around geotube groins and mixed clay–geotube groins. The results indicated that the influence of tidal surges on geomorphic changes surrounding the groins was more pronounced during spring tides than during neap tides. Under the same flow conditions, the scour depth at the head of the geotube groin was notably deeper than that of the mixed clay–geotube groin. Additionally, sediment silting behind the mixed clay–geotube groin was significantly greater than that behind the geotube groin. The clay component of the mixed clay–geotube groin served to mitigate the head scour, enhancing the overall structural stability to a certain extent. The geotube groin, with its surrounding scour pits expanding over time, experienced increasing tensile strain. This resulted in the rupture of the geotextile material, the loss of internal sand and, ultimately, groin collapse. It was found that mixed clay–geotube groins were better suited for cofferdam construction in strong tidal estuaries compared to geotube groin alternatives.
The system of graphical display of thematic information in digital cartography
Authors:   Remote Sensing and Digital Cartography Department, State University of Land Use Planning, Moscow, Lebedev P. P., , Skorobogatova U. E. ,   Remote Sensing and Digital Cartography Department, State University of Land Use Planning, Moscow
Published: November 2023

The analysis of the graphic support of thematic mapping has been carried out in this paper. The authors propose the theory of graphic display of information, based on which a new universal system of displaying thematic data has been built as well.
Geodetic support for the construction of in-farm roads in rural settlements
Authors:   Geodesy and Remote Sensing Department, FSFEI HE Omsk State Agrarian University, Omsk, Parkhomenko N. A. , Garagul A. S. ,   Geodesy and Remote Sensing Department, FSFEI HE Omsk State Agrarian University, Omsk
Published: November 2023

The article is about the analysis of geodetic methods used to realize in-farm road projects. The issue of high-quality provision of geospatial data is considered in this paper. The authors compared two methods: using electronic total station, and GNSS technology in RTK mode. The paper presents the sequence of research and the results, and proposes the most effective method to ensure quality and save time during construction.
Formation of gis projects in order to assess the level of antropogenic load on water bodies and develop recommendations for optimizing land use (by the example of Altai region and the Republic of Altai)
Authors:   FSBI ", Kurepina N. Yu. ,   Institute of Water and Environmental Problems of the Siberian Branch",   of the Russian Academy of Sciences, Barnaul, Rybkina I. D. ,   FSBI "Institute of Water and Environmental Problems of the Siberian Branch" of the Russian Academy of Sciences, Barnaul, Stoyashcheva N.V. ,   FSBI "Institute of Water and Environmental Problems of the Siberian Branch" of the Russian Academy of Sciences, Barnaul
Published: November 2023

Currently, open databases (DB) of potential sources of water pollution of small water bodies located in the territories of the anthropogenically affected Altai Krai and the Republic of Altai are not available. Therefore, we have implemented the inventory works in order to identify and systematize such sources; developed a conceptual scheme of the cartographic GIS database and the geodatabase structure; completed the database filling, and prepared GIS projects based on modern GIS technologies. The proposed new methodological approach to collection and generalization of spatial information within the boundaries of water management sites and model basins makes it possible to perform a comparative cartographic analysis of anthropogenic loads (including direct and indirect impacts) on water bodies, to reveal most problem sites for their further detailed study and to develop recommendations for land use optimization.
Designing New Metaheuristics: Manual Versus Automatic Approaches
Authors: Camacho-Villalón Christian L. , Stützle Thomas , Dorigo Marco
Published: November 2023

A metaheuristic is a collection of algorithmic concepts that can be used to define heuristic methods applicable to a wide set of optimization problems for which exact/analytical approaches are either limited or impractical. In other words, a metaheuristic can be considered a general algorithmic framework that can be easily adapted to different optimization problems. In this article, we discuss the two main approaches used to create new metaheuristics: manual design, which is based on the designer’s “intuition” and often involves looking for inspiration in other fields of knowledge, and automatic design, which seeks to reduce human involvement in the design process by harnessing recent advances in automatic algorithm configuration methods. In this context, we discuss the trend of manually designed “novel” metaphor-based metaheuristics inspired by natural, artificial, and even supernatural behaviors. In recent years, this trend has been strongly criticized due to the uselessness of new metaphors in devising truly novel algorithms and the confusion such metaheuristics have created in the literature. We then present automatic design as a powerful alternative to manual design that has the potential to render the “novel” metaphor-based metaheuristics trend obsolete. Finally, we examine several fundamental aspects of the field of metaheuristics and offer suggestions for improving them.
Terahertz Emission in Quantum Materials
Authors: Yang Surui , Cheng Liang , Qi Jingbo
Published: November 2023

The study of the interaction between terahertz (THz) radiation and quantum materials has been an active area of research due to its potential for understanding fundamental physics and the development of novel technologies. In this review, we focus on the time-dependent photocurrents, behind which are the up-to-date understanding of the physical processes. We provide the recent advancements in revealing the unique properties of quantum materials via the THz emission spectroscopy. Because the theoretical interpretation of some new experimental results is still evolving, this review is intended to inspire further research in this exciting and rapidly growing field.
Comparative Analysis of Mathematics Curriculum in Elementary School between Korea and Ontario, Canada: Focusing on Data and Possibility
Authors:   Education Research Institute, Ko JungHwa
Published: November 2023

This study compared and analyzed data and possibility among the mathematics curriculum in Ontario, Canada, revised in 2020 and the mathematics curriculum in Korea revised in 2022. To this end, the contents of the two curricula were compared focusing on the organization, timing of introduction, and content elements, and how the related contents were reflected in the textbooks were analyzed. As a result, the Ontario curriculum has a significantly higher volume and proportion of data and possibility than Korea, deals with various contents from an early stage, and repeats and expands learning contents as the grade goes up. This analysis provides important implications for revising the Korean curriculum and writing textbooks for future data and possibility.
The Mediating Effect of Conversation Time Between Positive & Negative Parenting Attitudes and Children's Happiness: Multi-group Analysis between Elementary and Middle school Students in South Korea
Authors:   Education Research Institute, Ryu ShinHye , Park SuAh
Published: November 2023

This study attempted to verify the mediating effect of positive and negative parenting attitudes on their children’s happiness through conversation time with parents and to determine whether there are differences between elementary and middle school students in such effects. To this end, the response data of elementary and middle school students collected in the third year (2020) of the Korean Children and Youth Panel Survey conducted by the Korea Youth Policy Institute were used. The analysis was conducted using structural equations and M-plus. The analysis results are as follows: First, in the case of elementary school students, positive parenting attitudes significantly affected happiness overall. In addition, in the case of middle school students, support for autonomy among positive parenting attitudes positively affected happiness. Second, in the case of middle school students, warmth and structural provision among positive parenting attitudes positively affected happiness by mediating conversation time with parents. Third, the mediating path of conversation time was not significant for autonomy support and coercion in common for all ages. Fourth, rejection of negative parenting attitudes in all ages negatively affected happiness by negatively mediating conversation time. Also, the inconsistency negatively affected happiness by negatively mediating conversation time. In conclusion, this study confirmed the positive effect of a positive parenting attitude on happiness rather than the amount of conversation time with parents. Moreover, it proved that a positive parenting attitude (warmness, structure provision) for middle school students positively affects happiness by mediating conversation time. These results are of great significance in that they provided evidence for the necessity of parental education considering the age of children.
Analysis of the Pre-service Elementary Teachers Science Lesson Plan: The Volume Change of Gas according to the Pressure
Authors:   Education Research Institute, Sung SeungMin
Published: November 2023

The purpose of this study is to analysis of the pre-service elementary teachers science lesson plan focusing on the volume change of gas according to the pressure. The subjects of the study were 26 pre-service elementary teachers at a university of education, and they were used for analysis based on the framework(instructional model, lesson course, lesson environment, lesson evaluation) of science lesson plan in previous studies. The results of the study were as follows. Looking at the instructional model sub-domain, pre-service elementary teachers selected and applied most of the discovery learning model and POE model in this lesson. And in the sub-domain of the lesson course, it was found that the lesson plan reflected the efforts to increase curiosity and cooperation among scientific attitudes, and to focus on observation, discussion·debate, and small group cooperation based on experiments. In addition, it was founded that there was a tendency to compare and reconstruct various activities in the lesson course, and the level of students was considered when guiding terms or concepts. Finally, it was analyzed that the level of each detailed factors was mostly good in the lesson environment and lesson evaluation sub-domains. Based on these research results, the level of pre-service elementary teachers’ science teaching professionalism and ways to improve them were reviewed.
The Differences of the Influence of Adult Attachment on their Self-compassion of Teachers in the Early Childhood Education and Care According to Types of Stress Coping
Authors:   Education Research Institute, Choi JiYoon , Chae JinYoung
Published: November 2023

The purpose of this study is to investigate differences in the adult attachment and self-compassion l evels of early childhood teachers according to their stress coping style, the effect of adult attachmen t on self-compassion, and differences in the effect of adult attachment on self-compassion in early c hildhood teachers according to their stress coping style. The survey was conducted with 490 early c hildhood teachers who had been working as homeroom teachers or assistant teachers at daycare cen ters and kindergartens in Korea. Data was analyzed using the SPSS 25.0 program with descriptive s tatistics, frequency analysis, one-way ANOVA, Scheffé's post hoc test, and the Pearson product-mo ment correlation coefficient. In addition, confirmatory factor analysis and multiple group analysis wer e performed using the AMOS 25.0. The results of this study are as follows: First, regarding the diff erences between adult attachment and self-compassion levels in the early childhood teachers, signific ant differences were found according to their stress coping styles, including task-oriented, emotion-o riented, and avoidance-oriented styles. Adult attachment levels showed significant differences in emo tion-, task-, and avoidance-oriented styles. Self-compassion levels also showed significant difference s in all three types. Second, the adult attachment levels of the survey participants with task- and a voidance-oriented coping styles showed a significant positive effect on self-compassion. In addition, the effect of the early childhood teachers’ adult attachment on self-compassion showed a significant difference according to their stress coping style; the adult attachment of the group with a task-orien ted coping style had a greater effect on self-compassion than that with an avoidance-oriented copin g style. This implies that the formation of stable adult attachment in early childhood teachers increa ses self-compassion levels and that task-oriented coping style further enhances such an effect.
Digital Literacy Seminar: "Caring for Personal Data Security in the Digital World"
Authors: Yudhana Anton , Umar Rusydi , Djou M. Rosyidi , Maulana Muhammad Jogo Samodro  , Makku Awaludin
Published: November 2023

Technology is becoming a tool to improve human performance, especially in the era of the Industrial Revolution 4.0, which is currently developing rapidly. The connectedness of various systems through the internet has led Indonesia to have 212.9 million internet users, covering 77% of the total population, with 78.5% of them active on social media. This phenomenon has brought about unprecedented growth in collecting and storing personal data that should be watched out for. Protecting personal data is essential, especially as internet users grow, increasing individuals' vulnerability to cybercrime. From 2022 to 2023, scams via WhatsApp messages manipulated with malicious attachments of images or links have become prevalent. To overcome this challenge, MTI UAD, in collaboration with the Regional Leadership of 'Aisyiyah Alor Regency, organized a digital literacy seminar to increase mothers' knowledge about the importance of protecting personal data in the digital world to minimize the risk of fraud. As a result, after attending the seminar, participants' knowledge increased significantly from under 50% to around 73%. Personal data protection efforts include sharing information, avoiding receiving files or applications from unknown sources, social engineering, and installing applications only from trusted sources.