bluuebunny/crossref_metadata_2025 huggingface dataset:
A Fuzzy Logic-Based Cost Modelling System for Recycling Carbon Fibre Reinforced Composites
Authors: Shehab Essam , Meiirbekov Arshyn , Amantayeva Akniyet , Suleimen Aidar , Tokbolat Serik , Sarfraz Shoaib , Ali Md Hazrat
Published: December 2021

Carbon Fibre Reinforced Polymers (CFRPs) are commonly used materials in manufacturing components and products in the automotive, aerospace, and wind energy industries generating thousands of tons of waste, thus creating a threat to the environment if not recycled. Therefore, it is important for both academia and industry to investigate various ways of recycling this material. However, there is an urgent need for a reliable cost predication system to assist in making informed decisions, planning sustainable treatment, and developing pricing strategies for different waste treatment scenarios. This research paper presents the development of a fuzzy logic-based system to perform cost estimation of recycling processes of the CFRP. The developed system has taken into consideration uncertainties such as the characteristics of End of Life (EoL) material including its size and weight, its origin and diversity of existing recycling methods, and quantity of recycling waste. Cost drivers were divided into categories such as dismantling, transportation, operation, and capital cost. The system was developed by creating 243 fuzzy rules and three levels of fuzzy sets. Moreover, an interactive user-friendly interface was developed to enable the user to use the system easily and efficiently. Finally, case study results were examined to compare the whole life recycling cost of four different recycling technologies in various scenarios of waste treatment. The developed fuzzy logic-based system has the capability in evaluating the cost structure of CFRP recycling techniques and take into consideration uncertainty factors. Hence, a major contribution of the developed system is its provision of the heuristic rules that aid the decision-making process for selecting a cost-effective recycling method. The visualisation facility of the developed system is also a useful tool in enabling potential users to forecast the cost of the CFRP recycling techniques upfront.
Comparison between Tests and Simulations Regarding Bending Resistance of 3D Printed PLA Structures
Authors: Catana Dorin-Ioan , Pop Mihai-Alin , Brus Denisa-Iulia
Published: December 2021

Additive manufacturing is one of the technologies that is beginning to be used in new fields of parts production, but it is also a technology that is constantly evolving, due to the advances made by researchers and printing equipment. The paper presents how, by using the simulation process, the geometry of the 3D printed structures from PLA and PLA-Glass was optimized at the bending stress. The optimization aimed to reduce the consumption of filament (material) simultaneously with an increase in the bending resistance. In addition, this paper demonstrates that the simulation process can only be applied with good results to 3D printed structures when their mechanical properties are known. The inconsistency of printing process parameters makes the 3D printed structures not homogeneous and, consequently, the occurrence of errors between the test results and those of simulations become natural and acceptable. The mechanical properties depend on the values of the printing process parameters and the printing equipment because, in the case of 3D printing, it is necessary for each combination of parameters to determine their mechanical properties through specific tests.
Features of Functionalization of the Surface of Alumina Nanofibers by Hydrolysis of Organosilanes on Surface Hydroxyl Groups
Authors: Simunin Mikhail M. , Voronin Anton S. , Fadeev Yurii V. , Mikhlin Yurii L. , Lizunov Denis A. , Samoilo Alexandr S. , Chirkov Dmitrii Yu. , Voronina Svetlana Yu. , Khartov Stas V.
Published: December 2021

Small additions of nanofiber materials make it possible to change the properties of polymers. However, the uniformity of the additive distribution and the strength of its bond with the polymer matrix are determined by the surface of the nanofibers. Silanes, in particular, allow you to customize the surface for better interaction with the matrix. The aim of our work is to study an approach to silanization of nanofibers of aluminum oxide to obtain a perfect interface between the additive and the matrix. The presence of target silanes on the surface of nanofibers was shown by XPS methods. The presence of functional groups on the surface of nanofibers was also shown by the methods of simultaneous thermal analysis, and the stoichiometry of functional groups with respect to the initial hydroxyl groups was studied. The number of functional groups precipitated from silanes is close to the number of the initial hydroxyl groups, which indicates a high uniformity of the coating in the proposed method of silanization. The presented technology for silanizing alumina nanofibers is an important approach to the subsequent use of this additive in various polymer matrices.
Effect of Locust Bean Gum-Sodium Alginate Coatings Combined with High CO2 Modified Atmosphere Packaging on the Quality of Turbot (Scophthalmus maximus) during Refrigerated Storage
Authors: Cao Jie , Liu Wenru , Mei Jun , Xie Jing
Published: December 2021

This research was conducted to investigate the effect of active coatings composed of locust bean gum (LBG) and sodium alginate (SA) containing daphnetin emulsions (DEs) combined with modified atmosphere packaging (MAP) on the microbiological and physicochemical properties of turbot during 4 °C refrigerated storage for 32 days. The results revealed that LBG-SA-DE coatings together with high CO2 MAP (60% CO2/35% N2/5% O2) maintained the total viable count (TVC) of H2S-producing bacteria in 4–6 lg CFU/g, which is lower than the limit (7 lg CFU/g). In addition, LBG-SA-DE coatings together with high CO2 MAP (60% CO2/35% N2/5% O2) inhibited the production of odor compounds, including thiobarbituric acid (TBA), trimethylamine-nitrogen (TMA-N), K value, and total volatile basic nitrogen (TVB-N). The low-field NMR analysis (LF-NMR) and magnetic resonance imaging (MRI) indicated that LBG-SA-DE coatings together with high CO2 MAP (60% CO2/35% N2/5% O2) treatments could delay the release of water located in muscle fiber macromolecules or convert it into free water based on muscle fiber destruction, thus maintaining the water content and migration. The results of the sensory evaluation showed that turbot treated with LBG-SA-DE coatings together with MAP could maintain its freshness during refrigerated storage.
Experimental Evaluation of Tensile Performance of Aluminate Cement Composite Reinforced with Weft Knitted Fabrics as a Function of Curing Temperature
Authors: Adosi Bentolhoda , Mirjalili Seyed Abbas , Adresi Mostafa , Tulliani Jean-Marc , Antonaci Paola
Published: December 2021

Cement composites (CC) are among the composites most widely used in the construction industry, such as a durable waterproof and fire-resistant concrete layer, slope protection, and application in retaining wall structures. The use of 3D fabric embedded in the cement media can improve the mechanical properties of the composites. The use of calcium aluminate cement (CAC) can accelerate the production process of the CC and further contribute to improving the mechanical properties of the cement media. The purpose of this study is to promote the use of these cementitious composites by deepening the knowledge of their tensile properties and investigating the factors that may affect them. Therefore, 270 specimens (three types of stitch structure, two directions of the fabric, three water temperature values, five curing ages, with three repetitions) were made, and the tensile properties, absorbed energy, and the inversion effects were evaluated. The results showed that the curing conditions of the reinforced cementitious composite in water with temperature values of 7, 23, and 50 °C affect the tensile behavior. The tensile strength of the CCs cured in water with a temperature of 23 °C had the highest tensile strength, while 7 and 50 °C produced a lower tensile strength. The inversion effect has been observed in CC at 23 °C between 7 and 28 days, while this effect has not occurred in other curing temperature values. By examining three commercial types of stitches in fabrics and the performance of the reinforced cementitious composites in the warp direction, it was found that the structure of the “Tuck Stitch” has higher tensile strength and absorbed energy compared to “Knit stitch” and “Miss Stitch”. The tensile strength and fracture energy of the CC reinforced with “Tuck Stitch” fabric in the warp direction, by curing in 23 °C water for 7 days, were found to be 2.81 MPa and 1.65 × 103 KJ/m3, respectively. These results may be helpful in selecting the design and curing parameters for the purposes of maximizing the tensile properties of textile CAC composites.
Compression Behaviour of Bio-Inspired Honeycomb Reinforced Starfish Shape Structures Using 3D Printing Technology
Authors: Saufi S. A. S. A. , Zuhri M. Y. M. , Dezaki M. Lalegani , Sapuan S. M. , Ilyas R. A. , As’arry A. , Ariffin M. K. A. , Bodaghi M.
Published: December 2021

The bio-inspired structure (e.g., honeycomb) has been studied for its ability to absorb energy and its high strength. The cell size and wall thickness are the main elements that alter the structural ability to withstand load and pressure. Moreover, adding a secondary structure can increase the compressive strength and energy absorption (EA) capability. In this study, the bio-inspired structures are fabricated by fused deposition modelling (FDM) technology using polylactic acid (PLA) material. Samples are printed in the shape of a honeycomb structure, and a starfish shape is used as its reinforcement. Hence, this study focuses on the compression strength and EA of different cell sizes of 20 and 30 mm with different wall thicknesses ranging from 1.5 to 2.5 mm. Subsequently, the deformation and failure of the structures are determined under the compression loading. It is found that the smaller cell size with smaller wall thickness offered a crush efficiency of 69% as compared to their larger cell size with thicker wall thickness counterparts. It is observed that for a 20 mm cell size, the EA and maximum peak load increase, respectively, when the wall thickness increases. It can be concluded that the compression strength and EA capability increase gradually as the cell size and wall thickness increase.
Modulating Structure and Properties of Glutinous Rice Flour and Its Dumpling Products by Annealing
Authors: Shi Chengming , Zhu Song , Ding Guangqin , Du Chaodong , Huang Dejian , Li Yue
Published: December 2021

In this study, annealed glutinous rice flour treated under different conditions (ANN1, ANN2 and ANN3) were prepared. The structure as well as physicochemical characteristics of the flour and its dumpling products were investigated. The crystallinity of the annealed flour samples increased, while the hydration ability decreased. The content of bound water raised, and immobilized water as well as the freezing enthalpy value decreased for the fast-frozen dumplings made from annealed flour samples. It showed that annealed treatment could reduce the formation of large ice crystals, thus decrease the cracking of fast-frozen dumplings. The freezing enthalpy value of annealed dumplings decreased which was conducive to protect the structure and quality of products. The boiled dumplings made of annealed flour had better eating quality as demonstrated by the increase in the transmittance of the soup. It indicated that moderate annealed glutinous rice flour ANN2 had optimal physicochemical properties to make high quality dumplings. This study would pave the way for further study of the annealing glutinous rice flour and provide theoretical guidance for the application of annealing treatment in starchy food product.
Comparison of the Accelerated and Spontaneous Deactivation of the HDS Catalyst
Authors: Jaklová Karolína Dlasková , Šindelářová Lucie , Kohout Jan , Hradecká Ivana , Sharkov Nikita , Vráblík Aleš
Published: December 2021

Owing to the increased use of secondary materials for diesel production, refineries must confront bad quality parameters. Therefore, catalysts with certain capabilities (to remove heteroatoms and improve quality parameters at low hydrogen consumption) and their lifetimes are required. An important parameter that influences the quality of the products and the economy of the unit is the activity of the catalyst. Prior to industrial use, the catalyst is typically tested in a pilot unit. This is necessary to obtain a considerable amount of data on the lifetime of the catalyst in the shortest feasible time. Here, deactivation steps were used to test the catalyst. Two experiments were performed to evaluate the effect of two types of accelerated deactivations on the catalyst activity and product properties. The first type of deactivation proceeded for 6 h and comprised a tripling of the amount of incoming feedstock, and the second type proceeded for 18 h without an increase in the amount of feedstock. For both cases, the pressure and hydrogen flow were minimised. Both types of accelerated deactivations had similar effects on the quality of the final products and catalyst. The only difference was in the duration of catalyst recovery after deactivation. The results were compared with those of a test in which the spontaneous deactivation of the catalyst was studied.
Macroscopic Behavior and Microscopic Structure Evolution of Marine Clay in One-Dimensional Compression Revealed by Discrete Element Simulation
Authors: Luo Lisha , Shen Zhifu , Gao Hongmei , Wang Zhihua , Zhou Xin
Published: December 2021

Marine clay has been attracting in-depth research on its mechanical behavior and internal structure evolution, which are crucial to marine infrastructure safety. In the formation process of marine clay, including the sedimentation and consolidation stages, the compression behavior and internal structure evolution are highly dependent on the pore water salinity. Discrete element method (DEM) simulation is a powerful tool to study the microscopic mechanics behind the complicated macroscopic mechanical behavior of marine clay. In this study, a DEM simulation scheme is systematically proposed to numerically study the macroscopic beahvior and microscopic structure evolution of marine clay in one-dimensional compression that mimics the marine clay formation process. First, the proposed calculation scheme for double layer repulsive interaction and van der Waals interaction is introduced. Then, the developed DEM simulation scheme is validated by satisfactorily reproducing the experimentally observed one-dimensional compression curves and internal structure transition from an edge-to-edge/edge-to-face flocculated structure to a face-to-face dispersed structure. Finally, evolutions of coordinate number and fabric anisotropy are quantitatively evaluated in the microscopic view. The noticeable effects of ion concentration on the internal structure evlotion and mechanical behavior of marine clay have been examined and discussed.
Jewish-Christian Identities in Conflict: The Cases of Fr. Daniel Rufeisen and Fr. Elias Friedman
Authors: Polyakov Emma O’Donnell
Published: December 2021

The status of Jewish identity in cases of conversion to another religion is a contentious issue and was brought to the forefront of public attention with the 1962 court case of Oswald Rufeisen, a Jewish convert to Christianity known as Br. Daniel, which led to a shift in the way that the state of Israel defines Jewish identity for the purposes of citizenship. At the same time, however, another test case in conflicting interpretations of Jewish identity after conversion was playing out in Rufeisen’s own monastery, hidden to the public eye. Of the fifteen monks who lived together in the Stella Maris Monastery in Haifa, two were Jewish converts, both of whom converted during the Second World War and later immigrated to Israel. Both outspoken advocates for their own understanding of Jewish identity, Rufeisen and his fellow Carmelite Fr. Elias Friedman expressed interpretations of Jewish-Christian religious identity that are polarized and even antagonistically oppositional at times. This paper argues that the intimately related histories and opposing interpretations of Rufeisen and Friedman parallel the historical contestation between Judaism and Christianity. It investigates their overlapping and yet divergent views, which magnify questions of Jewish identity, Catholic interpretations of Judaism, Zionism, Holocaust narratives, and proselytism.
The Relationship between Religion and Society in the COVID-19 Era: The Case of Protestantism in South Korea
Authors: Kim Minah
Published: December 2021

The relationship between Korean Protestantism and society at large can be divided into three parts in terms of the religion’s participation in society following the Korean Peninsula’s liberation from Japanese colonial rule: (1) conservative social non-participation, (2) far-right social participation, and (3) progressive social participation. In the COVID-19 era, conservative Protestants reluctantly followed the government’s quarantine guidelines but remained wary of state control over religion. Far-right Protestants placed a greater emphasis on religious values than on public safety and maintained face-to-face worship services against the government’s ban on religious and other largescale gatherings. Progressive Protestants participated in social movements to benefit the public good and were willing to forgo religious gatherings to that end. Overcoming COVID-19 requires many things, particularly material support for the marginalized, an establishment of an intimacy network beyond church-centered communities, ethics of respect for life, and the promotion of ecological justice, and with this in mind, the progressive Protestants’ participation in society can be considered an appropriate model.
ESG as a Measure of Credit Ratings
Authors: Chodnicka-Jaworska Patrycja
Published: December 2021

The aim of this study was to examine the impact of environmental, social, and governance (ESG) measures on credit ratings given to non-financial institutions by the largest credit rating agencies according to economic sector divisions. The hypotheses were as follows: a strong negative impact on non-financial institutions’ credit rating changes will result from ESG risk changes, and the reaction of credit rating changes will vary in different sectors. Panel event models were used to verify these hypotheses. The study used data from the Thomson Reuters Database for the period 2010–2020. The analysis was based on the literature on credit rating determinants and on papers and reports on COVID-19, ESG factors, and their impact on credit rating changes. Linear decomposition was used for the analysis. To verify these hypotheses, long-term issuer credit ratings presented by Moody’s and Fitch for European companies listed on these stock exchanges have been used. In the analyses, financial and non-financial factors were also considered. The results suggested that, within the last year, the methodology presented by credit rating agencies has changed, and ESG factors are one of the basic measures that are used to verify credit rating changes, especially those related to the pandemic.
Spatial Multi-Criterion Decision Making (SMDM) Drought Assessment and Sustainability over East Africa from 1982 to 2015
Authors: Kalisa Wilson , Zhang Jiahua , Igbawua Tertsea , Kayiranga Alexis , Ujoh Fanan , Aondoakaa Igbalumun Solomon , Tuyishime Pacifique , Li Shuaishuai , Simbi Claudien Habimana , Nibagwire Deborah
Published: December 2021

Droughts are ranked among the most devastating agricultural disasters that occur naturally in the world. East Africa is the most vulnerable and drought-prone region worldwide. In this study, four drought indices were used as input variables for drought assessment from 1982 to 2015. This work applied the SMDM algorithm to the integrated approach of OLR and Hurst exponent. The Detrended Fluctuation Analysis (DFA) and Ordinary Least Square (OLR) were merged to compute the trend and persistence (Hurst exponent) of the drought indices. Result indicates that the OLR at time scale 1, 6, and 12 shows a similar distribution with positive (negative) trends scattered in the Northwest (Northeast and Southern) parts of the study area which differs with the OLR aggregated at a 3-month time scale. The percentage pixel distribution for OLR-1, OLR-3, OLR-6, and OLR-12 is 18.2 (81.8), 72.5 (27.5), 32.9 (67.1), and 36.9 (63.1) for increasing (decreasing) trends respectively. Additionally, results indicate that DFA-1 is highly persistent with few random pixels scattered around Ethiopia, South Sudan and Tanzania, with percentage pixels as 88.7, 11.3 and 0.1 representing h > 0.5, h = 0.5, and h < 0.5, respectively. DFA-6 shows high (low) pixels representing h > 0.5 (h > 1), respectively. Meanwhile, for DFA-3 and DFA-12, the distribution shows persistence and a random walk, respectively. Drought conditions may eventually persist, reverse or vary drastically in an unpredictable manner depending on the driving forces. Overall, the drought risk map at 1-, 3-, and 6-month aggregates has shown severe degradation in Southern Kenya and Tanzania while noticeable improvements are seen in western Ethiopia and South Sudan.
Assessing Spatial Heterogeneity of Factor Interactions on PM2.5 Concentrations in Chinese Cities
Authors: Jin Yuhao , Zhang Han , Shi Hong , Wang Huilin , Wei Zhenfeng , Han Yuxing , Cong Peitong
Published: December 2021

The identification of fine particulate matter (PM2.5) concentrations and its driving factors are crucial for air pollution prevention and control. The factors that influence PM2.5 in different regions exhibit significant spatial heterogeneity. Current research has quantified the spatial heterogeneity of single factors but fails to discuss the interactions between factors. In this study, we first divided the study area into subregions based on the spatial heterogeneity of factors in a multi-scale geographically weighted regression model. We then investigated the interactions between different factors in the subregions using the geographical detector model. The results indicate that there was significant spatial heterogeneity in the interactions between the driving factors of PM2.5. The interactions between natural factors have significant uncertainty, as do those between the normalized difference vegetation index (NDVI) and socioeconomic factors. The interactions between socioeconomic factors in the subregions were consistent with those in the whole region. Our findings are expected to deepen the understanding of the mechanisms at play among the aforementioned drivers and aid policymakers in adopting unique governance strategies across different regions.
Global Vegetation Photosynthetic Phenology Products Based on MODIS Vegetation Greenness and Temperature: Modeling and Evaluation
Authors: Xu Xiaojun , Tang Yan , Qu Yiling , Zhou Zhongsheng , Hu Junguo
Published: December 2021

Land surface phenology (LSP) products that are derived from different data sources have different definitions and biophysical meanings. Discrepancies among these products and their linkages with carbon fluxes across plant functional types and climatic regions remain somewhat unclear. In this study, to differentiate LSP related to gross primary production (GPP) from LSP related to remote sensing data, we defined the former as vegetation photosynthetic phenology (VPP), including the starting and ending days of GPP (SOG and EOG, respectively). Specifically, we estimated VPP based on a combination of observed VPP from 145 flux-measured GPP sites together with the vegetation index and temperature data from MODIS products using multiple linear regression models. We then compared VPP estimates with MODIS LSP on a global scale. Our results show that the VPP provided better estimates of SOG and EOG than MODIS LSP, with a root mean square error (RMSE) for SOG of 12.7 days and a RMSE for EOG of 10.5 days. The RMSE was approximately three weeks for both SOG and EOG estimates of the non-forest type. Discrepancies between VPP and LSP estimates varied across plant functional types (PFTs) and climatic regions. A high correlation was observed between VPP and LSP estimates for deciduous forest. For most PFTs, using VPP estimates rather than LSP improved the estimation of GPP. This study presents a useful method for modeling global VPP, investigates in detail the discrepancies between VPP and LSP, and provides a more effective global vegetation phenology product for carbon cycle modeling than the existing ones.
Quantifying Influences of Natural and Anthropogenic Factors on Vegetation Changes Based on Geodetector: A Case Study in the Poyang Lake Basin, China
Authors: Wang Yiming , Zhang Zengxin , Chen Xi
Published: December 2021

Understanding the driving mechanism of vegetation changes is essential for vegetation restoration and management. Vegetation coverage in the Poyang Lake basin (PYLB) has changed dramatically under the context of climate change and human activities in recent decades. It remains challenging to quantify the relative contribution of natural and anthropogenic factors to vegetation change due to their complicated interaction effects. In this study, we selected the Normalized Difference Vegetation Index (NDVI) as an indicator of vegetation growth and used trend analysis and the Mann-Kendall test to analyze its spatiotemporal change in the PYLB from 2000 to 2020. Then we applied the Geodetector model, a novel spatial analysis method, to quantify the effects of natural and anthropogenic factors on vegetation change. The results showed that most regions of the basin were experiencing vegetation restoration and the overall average NDVI value in the basin increased from 0.756 to 0.809 with an upward yearly trend of +0.0026. Land-use type exerted the greatest influence on vegetation change, followed by slope, elevation, and soil types. Except for conversions to construction land, most types of land use conversion induced an increase in NDVI in the basin. The influence of one factor on vegetation NDVI was always enhanced when interacting with another. The interaction effect of land use types and population density was the largest, which could explain 45.6% of the vegetation change, indicating that human activities dominated vegetation change in the PYLB. Moreover, we determined the ranges or types of factors most suitable for vegetation growth, which can be helpful for decision-makers to optimize the implementation of ecological projects in the PYLB in the future. The results of this study could improve the understanding of the driving mechanisms of vegetation change and provide a valuable reference for ecological restoration in subtropical humid regions.
Practical Dynamical-Statistical Reconstruction of Ocean’s Interior from Satellite Observations
Authors: Yan Hengqian , Zhang Ren , Wang Huizan , Bao Senliang , Bai Chengzu
Published: December 2021

The algorithms based on Surface Quasi-Geostrophic (SQG) dynamics have been developed and validated by many researchers through model products, however it is still doubtful whether these SQG-based algorithms are worth using in terms of observed data. This paper analyzes the factors impeding the practical application of SQG and makes amends by a simple “first-guess (FG) framework”. The proposed framework includes the correction of satellite salinity and the estimation of the FG background, making the SQG-based algorithms applicable in realistic circumstances. The dynamical-statistical method SQG-mEOF-R is thereafter applied to satellite data for the first time. The results are compared with two dynamical algorithms, SQG and isQG, and three empirical algorithms, multivariate linear regression (MLR), random forest (RF), and mEOF-R. The validation against Argo profiles showed that the SQG-mEOF-R presents a robust performance in mesoscale reconstruction and outperforms the other five algorithms in the upper layers. It is promising that the SQG-mEOF-R and the FG framework are applicable to operational reconstruction.
A Novel Training and Collaboration Integrated Framework for Human–Agent Teleoperation
Authors: Huang Zebin , Wang Ziwei , Bai Weibang , Huang Yanpei , Sun Lichao , Xiao Bo , Yeatman Eric M.
Published: December 2021

Human operators have the trend of increasing physical and mental workloads when performing teleoperation tasks in uncertain and dynamic environments. In addition, their performances are influenced by subjective factors, potentially leading to operational errors or task failure. Although agent-based methods offer a promising solution to the above problems, the human experience and intelligence are necessary for teleoperation scenarios. In this paper, a truncated quantile critics reinforcement learning-based integrated framework is proposed for human–agent teleoperation that encompasses training, assessment and agent-based arbitration. The proposed framework allows for an expert training agent, a bilateral training and cooperation process to realize the co-optimization of agent and human. It can provide efficient and quantifiable training feedback. Experiments have been conducted to train subjects with the developed algorithm. The performances of human–human and human–agent cooperation modes are also compared. The results have shown that subjects can complete the tasks of reaching and picking and placing with the assistance of an agent in a shorter operational time, with a higher success rate and less workload than human–human cooperation.
RBFNN Design Based on Modified Nearest Neighbor Clustering Algorithm for Path Tracking Control
Authors: Zheng Dongxi , Jung Wonsuk , Kim Sunghoon
Published: December 2021

Radial basis function neural networks are a widely used type of artificial neural network. The number and centers of basis functions directly affect the accuracy and speed of radial basis function neural networks. Many studies use supervised learning algorithms to obtain these parameters, but this leads to more parameters that need to be determined, thereby making the system more complex. This study proposes a modified nearest neighbor-based clustering algorithm for training radial basis function neural networks. The calculation of this clustering algorithm is not large, and it can adapt to varying densities. Furthermore, it does not require researchers to set parameters based on experience. Simulation proves that the clustering algorithm can effectively cluster samples and optimize the abnormal samples. The radial basis function neural network based on modified nearest neighbor-based clustering has higher accuracy in curve fitting than the conventional radial basis function neural network. Finally, the path tracking control based on a radial basis function neural network of a magnetic microrobot is investigated, and its effectiveness is verified through simulation. The test accuracy and training accuracy of the radial basis function neural network was improved by 23.5% and 7.5%, respectively.
Temperature Sensor Based on Periodically Tapered Optical Fibers
Authors: Guzowski Bartlomiej , Łakomski Mateusz
Published: December 2021

In this paper, the fabrication and characterization of a temperature sensor based on periodically tapered optical fibers (PTOF) are presented. The relation between the geometry of the sensors and sensing ability was investigated in order to find the relatively simple structure of a sensor. Four types of PTOF structures with two, four, six and eight waists were manufactured with the fusion splicer. For each PTOF type, the theoretical free spectral range (FSR) was calculated and compared with measurements. The experiments were conducted for a temperature range of 20–70 °C. The results proved that the number of the tapered regions in PTOF is crucial, because some of the investigated structures did not exhibit the temperature response. The interference occurring inside the structures with two and four waists was found be too weak and, therefore, the transmission dip was hardly visible. We proved that sensors with a low number of tapered regions cannot be considered as a temperature sensor. Sufficiently more valuable results were obtained for the last two types of PTOF, where the sensor’s sensitivity was equal to 0.07 dB/°C with an excellent linear fitting (R2 > 0.99). The transmission dip shift can be described by a linear function (R2 > 0.97) with a slope α > 0.39 nm/°C.
Sustainability of Livestock Systems in the Pampa Biome of Brazil: An Analysis Highlighting the Rangeland Dilemma
Authors: Viana João Garibaldi Almeida , Vendruscolo Rafaela , Silveira Vicente Celestino Pires , de Quadros Fernando Luiz Ferreira , Mezzomo Mariana Patricia , Tourrand Jean François
Published: December 2021

The objective of this study was to analyse the sustainability of different livestock systems in the Brazilian Pampa biome, from the perspective of the rangeland dilemma. We used the indicator-based framework for evaluating the sustainability of natural resource management systems (MESMIS). These were constructed for social, economic and environmental dimensions, and they were measured across a study suite of 115 establishments, representing the rangeland livestock system (RLS), intensive livestock system, and livestock–agricultural system (ALS). Indicator averages were compared between three systems via ANOVA and Tukey test. The results allocated a higher level of sustainability to RLS. When the three land-use systems were analysed across the dimensions, significant differences were found in their environmental sustainability, with the ALS presenting poorer results. Within each dimension, there were significant differences in the indicators for production systems, social participation and capital flow. We discussed two main points: the results found through the concept of the rangeland dilemma, by exploring its conditions, in addition to exposing the concept of functional integrity. In conclusion, an approach to develop policies for the Pampa is to recognize the rangeland as a “common good”, to generate income and stimulate the local economy.
Aggregated Electric Vehicle Fast-Charging Power Demand Analysis and Forecast Based on LSTM Neural Network
Authors: Chang Munseok , Bae Sungwoo , Cha Gilhwan , Yoo Jaehyun
Published: December 2021

With the widespread use of electric vehicles, their charging power demand has increased and become a significant burden on power grids. The uncoordinated deployment of electric vehicle charging stations and the uncertainty surrounding charging behaviors can cause harmful impacts on power grids. The charging power demand during the fast charging process especially is severely fluctuating, because its charging duration is short and the rated power of the fast chargers is high. This paper presents a methodology to analyze and forecast the aggregated charging power demand from multiple fast-charging stations. Then, pattern of fast-charging power demand is analyzed to identify its irregular trend with the distribution of peak time and values. The forecasting model, based on long short-term memory neural network, is proposed in this paper to address the fluctuating of fast-charging power demand. The forecasting performance of the proposed model is validated in comparison with other deep learning approaches, using real-world datasets measured from fast-charging stations in Jeju Island, South Korea. The results show that the proposed model outperforms forecasting fast-charging power demand aggregated by multiple charging stations.
Comparative Evaluation of Simplified Surface Energy Balance Index-Based Actual ET against Lysimeter Data in a Tropical River Basin
Authors: Kumar Utkarsh , Rashmi  , Chatterjee Chandranath , Raghuwanshi Narendra Singh
Published: December 2021

In the past decades, multispectral and multitemporal remote sensing has been popularly used for estimating actual evapotranspiration (ETc) across the globe. It has been proven to be a cost-effective tool for understanding agricultural practices in a region. Today, because of the availability of different onboard sensors on an increasing number of different satellites, land surface activity can be captured at fine spatial and time scales. In the present study, three multi-date satellite imageries were used for the evaluation of remote sensing-based estimation of actual evapotranspiration in paddy in the command area of the tropical Kangsabati river basin. A surface energy balance model, the Simplified-Surface Energy Balance Index (S-SEBI), was applied for all three dates of the Rabi season (2014–2015) for the estimation of actual evapotranspiration. The crop coefficient was calculated using the exhaustive survey data collected from the command area and adjusted to local conditions. The ETc estimated using the S-SEBI-based model was compared with the Food and Agriculture Organization Penman–Monteith (FAO-56 PM) method multiplied by the adjusted local crop coefficient and lysimeter data in the command area. The coefficient of determination (r2) was applied to examine the accuracy of the S-SEBI model with respect to lysimeter data and the FAO-56 PM-based ETc. The results showed that the S-SEBI model performed well with the lysimeter (r2 = 0.90) in comparison with FAO-56 PM, with an r2 of 0.65. In addition to this, the S-SEBI-based ET estimates correlated well with the FAO-56 PM, with r and RMSE values of 0.06 and 1.13 mm/day (initial stage), 0.85 and 0.48 mm/day (development stage), and 0.77 and 0.52 (maturity stage) for paddy, respectively. The S-SEBI-based ETc estimate varied with different stages of crop growth and successfully captured the spatial heterogeneity within the command area. In general, this study showed that the S-SEBI method has the potential to calculate spatial evapotranspiration and provide useful information for efficient water management. The results revealed the applicability and accuracy of remote sensing-based ET for managing water resources in a command area with scarce data.
Physical Activity and Sports Practice in Children and Adolescents at the Time of the COVID-19 Pandemic: Hypothetical Future Scenarios and Preventive Practical Applications
Authors: Battaglia Giuseppe , Palma Antonio
Published: December 2021

As a logical and direct consequence of the closure of schools and sports facilities, an expected reduction in the practice of physical activity (PA) and sports has been detected in both children and adolescents all over the world. Hence, we analysed the short-term and long-term consequences of the lack/low level of PA and sports activity in this population, which we referred to as primary and secondary risks, respectively, the latter of which have to be considered in hypothetical future scenarios.
Inequality in the Initial Wage of College Graduates at the College-Level Perspective
Authors: Li Yanming , Lu Kangyin , Wang Kaiyuan
Published: December 2021

College graduates, as a labor force with high human capital accumulation, have the problem of initial wage inequality, which is worth paying attention to. Based on the collated micro-survey data form “Employment and Entrepreneurship Development Report of Chinese College Graduates”, which contains 339 samples from vocational colleges, 453 from common colleges, and 360 from key colleges, this study empirically analyzed the inequality of college graduates’ initial wages at the college level. We found that the initial wage income level of college graduates is significantly influenced by the college level. The higher the level is, the higher the initial wage. The initial wage of graduates from key colleges is the highest, and the income inequality between them and vocational college graduates is the most significant. Moreover, there are structural differences in the wage premium effect of the college level on college graduates with a change in wage level. In addition, the study found that there is an obvious gender wage difference among college graduates, and political status, academic ranking, and student cadre experience as well as the nature of the workplace all contributed to the formation of wage premiums to a certain extent.
Sustainable Strategy to Sustainable Business: An Empirical Analysis on Energy-Efficient Light Bulb
Authors: Zahan Muslima
Published: December 2021

Energy Efficiency is one of the key elements of the Environment-Economic aspect of the three spheres of sustainability. To make any business sustainable in the light bulb industry, it could be applied as a strategy to gain competitive advantage in the functional level. This paper investigates the market awareness of environmentally friendly products such as the energy efficient light bulb (or energy bulb) and its market availability, demand, quality and brightness, low waste (e-waste), sustainable consumption (durability), warranty, commission rate, and profitability. It also finds that energy efficiency and low waste are valuable strategies to create market demand for energy bulbs to make sustainable profit and product stewardship eventually to contribute to the e-waste management. A 500 sample survey is conducted in Bangladesh to analyze the energy bulb buyers’ and sellers’ view about this product locally. After the results and interpretation through descriptive statistics and regression of the variables, this study finally draws a pathway model to show that sustainable energy definitely leads to sustainable business. From the buyers’ point of view, sustainable consumption and low waste as well as from the sellers’ point of view profit and sustainable product both support sustainable business backed by sustainable strategy, energy efficiency being the key. To make the competitive advantage enduring, ensure profitability and profit growth for the shareholders of the corporate world, especially the electrical and electronics industry; with the energy bulb in particular, an energy efficiency strategy could be implemented in businesses worldwide. As the COP26 (The 2021 United Nations Conference on Climate Change) limits the global warming rise by 1.5%, energy bulb has been the pioneer in promoting sustainable products to adopt the sustainable strategy to limit carbon emissions globally.
Teachers in the Top Management Team and Corporate Social Responsibility
Authors: Liu Wenyuan , Ren Ting , Tang Weishan
Published: December 2021

Firms are required to consider all stakeholders’ interests and achieve coordinated development of the company, society, and the environment. Teachers are often associated with high moral standards and dedication to others. Top managers in the top management team (TMT) are responsible as corporate executives for corporate governance and outcomes. How top managers’ teaching experience affects corporate social responsibility (CSR) therefore becomes a meaningful question. Based on A-share listed firms in China from 2010 to 2019, we empirically analyze the effects of teachers as top managers on firm CSR performance. According to our sample, 13.75% of A-share listed firms have top managers with teaching experience in the TMT. We find that the occurrence of teachers in the TMT has a positive impact on CSR, especially on sub-indicators like shareholder responsibility; employee responsibility; supplier, customer, and consumer responsibility; and environmental responsibility. Firms with more teachers in the TMT exhibit higher CSR performance. Further results indicate that this effect is significant only when top managers are also directors on the board. We use the propensity score matching method to alleviate the endogeneity problem and obtain robust results.
Perceived Economic Value of Ecosystem Services in the US Rio Grande Basin
Authors: Wang Weiwei , Mu Jianhong E. , Ziolkowska Jadwiga R.
Published: December 2021

In recent decades, the US Rio Grande Basin has experienced serious ecosystem degradation as a result of recurring severe droughts and a growing population. Monetary valuation of ecosystem services is essential for encouraging conservation where natural resources such as freshwater are limited. Research in this field is still very limited, and economic estimations of ecosystem services in the US Rio Grande Basin have not been undertaken extensively. This study adds to the existing contemporary literature by means of the willingness-to-pay evaluation. We found the mean household wiliness to pay of total ecosystem services across the Rio Grande Basin to amount to USD 62/year, and the average perceived economic value was estimated to be USD 26.2, USD 19.7, USD 8.1, and USD 7.1 yearly for conservation of habitat for wildlife, provision of freshwater supplies, recreational activities, and cultural heritage, respectively. The income and perceptions about the importance of various ecosystem services in the Rio Grande Basin were among the main determinants of respondents’ assessments. The findings provide an appropriate foundation for incorporating perceived economic value into watershed management and conservation.
Development of an Algorithm for Regulating the Load Schedule of Educational Institutions Based on the Forecast of Electric Consumption within the Framework of Application of the Demand Response
Authors: Zhukovskiy Yuriy Leonidovich , Kovalchuk Margarita Sergeevna , Batueva Daria Evgenievna , Senchilo Nikita Dmitrievich
Published: December 2021

There is a tendency to increase the use of demand response technology in the Russian Federation along with other developing countries, covering not only large industries, but also individual households and organizations. Reducing peak loads of electricity consumption and increasing energy efficient use of equipment in the power system is achieved by applying demand management technology based on modeling and predicting consumer behavior in an educational institution. The study proposes to consider the possibility of participating in the concept of demand management of educational institutions with a typical workload schedule of the work week. For the study, statistical data of open services and sources, Russian and foreign research on the use of digital and information technologies, analytical methods, methods of mathematical modeling, methods of analysis, and generalization of data and statistical methods of data processing are used. An algorithm for collecting and processing power consumption data and a load planning algorithm were developed, including all levels of interaction between devices. A comparison was made between the values of the maximum daily consumption before and after optimization, as well as the magnitude of the decrease in the maximum consumption after applying the genetic algorithm. The developed algorithm has the ability to scale, which will increase the effect of using the results of this study to more significant values. Load switching helps to reduce peak consumption charges, which often represent a significant portion of the electricity cost.