bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigation on Spatial Transformation and Proportional Coefficient of Vehicle-Mounted Transient Electromagnetic Detection Environments in Operational Tunnels
Authors: Xu Jinhua , Liu Shaohua , Zhou Huaqiu , Zhang Rikai , Wang Bo , Xu Yikang , Qian Wangping
Published: September 2022

The vehicle-mounted transient electromagnetic method (VMTEM) has been proposed to detect tunnel internal defects in operational tunnels based on the ideal space state. However, the space environment of tunnel surrounding rock is different compared with conventional application fields, so the interpretation of detection data has certain inadaptability and unreliability. In this paper, three typical space states involved in the detection process of operational tunnels were analyzed. The diffusion law of the transient electromagnetic response signal under the condition of three typical space states was carried out, the proportional coefficient of different space states was determined, and the spatial transformation problem was also determined. Meanwhile, the results obtained by the numerical simulation calculation and numerical derivation calculation were verified by laboratory experiments. The results showed that the correction coefficient of full space to half space was 2.50, and that of three-quarters space to half space was 1.42. The detection process in operational tunnels involves the mutual transformation process of three typical space states. The critical distance that the spatial transformation does not affect is 300 m. In addition, the results of laboratory experiments verified the typical space proportional coefficient and spatial transformation phenomenon well. The results can provide essential ideas for the subsequent space correction of the detection environment in operational tunnels.
The Development of Rubber Tapping Machines in Intelligent Agriculture: A Review
Authors: Yang Hui , Sun Zejin , Liu Junxiao , Zhang Zhifu , Zhang Xirui
Published: September 2022

In the past decade, intelligent technologies have advanced rapidly, particularly due to improvements in automatic control, which have had a significant impact on forestry, as well as animal husbandry and the future of farm management. However, the degree of production and management mechanization in natural rubber plantations is low, especially since the methods of tapping still rely heavily on labor. The decrease of skilled rubber tappers and the increase in labor costs have led to the development of the mechanization of rubber tapping operations. The application of emerging intelligent agricultural technologies could provide an alternative in order to maximize the potential productivity of natural rubber. Based on this vision, we reviewed the literature on rubber tapping from the past decade for system implementation in rubber plantations. In this review, selected references on rubber tapping were categorized into several directions of research, including rubber tapping machines, the key technologies applied in tapping operations, and some related protective research, analyzing research works from 2010 to 2022 that focused on tapping methods. The review also discusses the application of intelligent agricultural technologies, such as the recognition of tapping trajectory and tapping path planning. A summary of challenges and future trends is also provided in this study. Based on the relevant research, the use of intelligent technologies in rubber tapping machines is still in its initial stage and has broad prospects. Through this study, we aim to provide a reference for researchers in the field of rubber tapping machines and thus to play a positive role in future rubber tapping.
Probabilistic Joint Importance-Based Retrofit Strategy for Seismic Risk Mitigation of Transportation Networks
Authors: Liu Kezhi , Zhai Changhai , Meng Xianghai
Published: September 2022

Seismic mitigation of transportation systems has become a worldwide challenge, because identifying an optimal retrofit strategy entails significant computational efforts, especially for large-scale networks with numerous candidate strategies and time-consuming risk assessment processes. An efficient joint importance-based methodology is proposed in this paper to address the challenge. The proposed method selects the component set (e.g., bridges) that is most decisive to the network seismic risk based on only one set of stochastic samples but takes into account the uncertainty of multiple damage states and the interactive effect between different components. The reliability and stability of the proposed method are verified on a hypothetical transportation network under different conditions.
Task Offloading Strategy of Vehicular Networks Based on Improved Bald Eagle Search Optimization Algorithm
Authors: Shen Xianhao , Chang Zhaozhan , Xie Xiaolan , Niu Shaohua
Published: September 2022

To reduce computing delay and energy consumption in the Vehicular networks, the total cost of task offloading, namely delay and energy consumption, is studied. A task offloading model combining local vehicle computing, MEC (Mobile Edge Computing) server computing, and cloud computing is proposed. The model not only considers the priority relationship of tasks, but also considers the delay and energy consumption of the system. A computational offloading decision method IBES based on an improved bald eagle search optimization algorithm is designed, which introduces Tent chaotic mapping, Levy Flight mechanism and Adaptive weights into the bald eagle search optimization algorithm to increase initial population diversity, enhance local search and global convergence. The simulation results show that the total cost of IBES is 33.07% and 22.73% lower than that of PSO and BES, respectively.
Automatic Cause–Effect Graph Tool with Informal Korean Requirement Specifications
Authors: Jang Woo Sung , Kim R. Young Chul
Published: September 2022

In requirement engineering, it is a very important issue to generate test cases with natural language automatically. However, no test case tools deal with informal Korean requirement specifications. In the Korean military software system and airspace industrial area, it is strongly suggested to automatically make just 30% of all possible test cases with requirements. Unlike the previous approaches, we adapted Gary E. Mogyorodi’s cause-effect graphing approach and the model-driven architecture (MDA) approach for automatic test case generation with natural language. In order to generate test cases with informal Korean requirement specifications, we propose an automatic cause–effect tool as an intermediate model for (1) simplifying complicated requirements; (2) modeling the C3Tree (that is, condition and result); (3) identifying incomplete requirements; (4) constructing causes, effects, and relationships; and (5) integrating with two units (that is, similar causes or effects) to remove redundant requirements. We evaluated the accuracy of two generated cause–effect graphs in two ways. With our approach, we can also remove requirement redundancy.
A Hybrid Methodology to Improve Speaking Skills in English Language Learning Using Mobile Applications
Authors: Criollo-C Santiago , Guerrero-Arias Andrea , Vidal Jack , Jaramillo-Alcazar Ángel , Luján-Mora Sergio
Published: September 2022

The main objective of this research is a working example of how a hybrid methodology combining traditional methodologies and mobile devices can be used to contribute to the literature on mobile learning in teaching English as a second language. This work was carried out because, in many Latin American countries, students are taught English as a second language throughout their primary and secondary education. However, at the end of their studies, most students are unable to communicate with other people in English, let alone with native speakers. Moreover, it must be taken into account that nowadays English is the most widely used language in international communications, business transactions, finance and science. The professional who knows how to communicate in English has a positive differentiator in his or her professional profile and can easily access more relevant positions in any institution. For this purpose, a review of different methodologies for teaching oral expression in English has been carried out. Metrics have also been used to choose an effective mobile application to reinforce English speaking. These analyzed methodologies have been combined with the use of a mobile application to propose a hybrid methodology that contemplates an eight-week class guide. Due to the characteristics of mobile learning, this work can help to motivate students in their learning and in improving their communicative skills in the English language. High school teachers can use this methodology as an innovation in their educational programs.
Study of Cocoa Pod Husks Thermal Decomposition
Authors: Londoño-Larrea Pablo , Villamarin-Barriga Estefania , García Angela N. , Marcilla Antonio
Published: September 2022

Thermal decomposition of cocoa pod husks under inert and oxidizing atmospheres was studied. Samples from Cotopaxi, Ecuador were used as raw material. Thermogravimetry based experiments were used to obtain decomposition data vs. temperature. A novel strategy to fit the TG and DTG curves was used giving good fit by considering, in the kinetic model, four biomass fractions following independent reactions. Analytical pyrolysis was used to determine the composition of volatile compounds obtained in slow (150–350, 350–500 °C) and flash pyrolysis (400 °C). The results indicate that in the slow pyrolysis experiments at low temperatures (150–350 °C), the highest area percentages correspond to ketones (7.5%), organic acids (12.5%) and phenolic derivatives (10%), while at increased temperatures (350–500 °C) the higher percentages are clearly focused on phenolic derivatives (12%) and aromatic compounds (10%). Comparing the results of flash pyrolysis at 400 °C (i.e., higher heating rate but lower final temperature), an increase in the yield of ketones and organic acids is observed compared to slow pyrolysis, but the percentage of phenols and aromatics decreases. The results obtained allow deducing the operating conditions to maximize the mass fraction of the different functional groups identified.
Variation of Fracture Toughness with Biaxial Load and T-Stress under Mode I Condition
Authors: Chen Chentong , Li Zhanfeng , Xu Chang , Zhu Ze , Zou Sheng
Published: September 2022

The effect of a biaxial load on brittle fractures of solids under predominantly elastic deformation and mode I loading conditions is studied in this article. A cross-shaped specimen is used in this work, and the variation of T-stress is achieved by changing the load applied to the arm parallel to the crack. In the tests, under a series of different loads parallel to the crack, a series of load values perpendicular to the crack are obtained, and the stress intensity factor is calculated by FEM (Finite Element Analysis). The test data demonstrate that the apparent fracture toughness of the material varies with the load parallel to the crack and the T-stress, since the T-stress is directly related to the load parallel to the crack. If only the first term of the Williams series solution is used to describe the stress field near the crack tip, the variation of KC is unexplained; therefore, more than one term in the Williams series solutions is used to develop the theory of biaxial effect on solid fracture behavior. The fracture criterion based on this consideration is also used to predict crack instability or crack curving under mode I load conditions. Experimental data are presented and compared with the theory.
ReSTiNet: On Improving the Performance of Tiny-YOLO-Based CNN Architecture for Applications in Human Detection
Authors: Sumit Shahriar Shakir , Awang Rambli Dayang Rohaya , Mirjalili Seyedali , Ejaz Muhammad Mudassir , Miah M. Saef Ullah
Published: September 2022

Human detection is a special application of object recognition and is considered one of the greatest challenges in computer vision. It is the starting point of a number of applications, including public safety and security surveillance around the world. Human detection technologies have advanced significantly in recent years due to the rapid development of deep learning techniques. Despite recent advances, we still need to adopt the best network-design practices that enable compact sizes, deep designs, and fast training times while maintaining high accuracies. In this article, we propose ReSTiNet, a novel compressed convolutional neural network that addresses the issues of size, detection speed, and accuracy. Following SqueezeNet, ReSTiNet adopts the fire modules by examining the number of fire modules and their placement within the model to reduce the number of parameters and thus the model size. The residual connections within the fire modules in ReSTiNet are interpolated and finely constructed to improve feature propagation and ensure the largest possible information flow in the model, with the goal of further improving the proposed ReSTiNet in terms of detection speed and accuracy. The proposed algorithm downsizes the previously popular Tiny-YOLO model and improves the following features: (1) faster detection speed; (2) compact model size; (3) solving the overfitting problems; and (4) superior performance than other lightweight models such as MobileNet and SqueezeNet in terms of mAP. The proposed model was trained and tested using MS COCO and Pascal VOC datasets. The resulting ReSTiNet model is 10.7 MB in size (almost five times smaller than Tiny-YOLO), but it achieves an mAP of 63.74% on PASCAL VOC and 27.3% on MS COCO datasets using Tesla k80 GPU.
A Novel Approach for Micro-Antenna Fabrication on ZrO2 Substrate Assisted by Laser Printing for Smart Implants
Authors: Moura C. G. , Dinis H. , Carvalho O. , Mendes P. M. , Nascimento R. M. , Silva F. S.
Published: September 2022

The use of Yttria-stabilized tetragonal zirconia polycrystals (Y-TZP) in medicine has rapidly expanded over the past decade, driven by its advantageous properties, showing potential to overcome titanium alloy in implant fabrication. The release of metal ions and the aesthetic problems of titanium alloy implants are the main reasons for this trend. In addition to meeting expectations regarding its properties, an implant must possess intrinsic capacities such as auto-diagnostic and auto-treatment. Thus, based on the concept of smart implants, this work proposes a hybrid approach for printing a part of the communication system of a zirconia implant by resorting to laser technology, aiming to endow the implant with intrinsic capacities. Therefore, the antenna was designed and then printed on the zirconia surface. The laser was applied as a versatile tool, whether for preparing the surface of the material in a subtractive way, by creating the micro-cavity, or for printing the silver-based antenna in an additive way through laser technology. The silver powder was used as the conductor material of the antenna. The results revealed that the antenna is capable of communicating from inside the body with the outside world without needing to have an exterior antenna attached to the skin.
LQI Control System Design with GA Approach for Flying-Type Firefighting Robot Using Waterpower and Weight-Shifting Mechanism
Authors: Dinh Cao-Tri , Huynh Thinh , Kim Young-Bok
Published: September 2022

This study proposes a flying robot using waterpower and a novel weight-shifting mechanism, whose purpose is to be applied in firefighting tasks in water areas that are difficult to access and are suppressed by conventional firefighting methods. The sufficient amount of water in the area is used for propelling the robot, as well as fire suppression activity. A weight-shifting mechanism governs the weight distribution of the robot head in order to perform the robot motions. In this paper, the system’s dynamical characteristics are analyzed in detail through mathematical models. A linear-quadratic integrator (LQI) is designed for controlling the system motion. Additionally, the LQI is tuned with the genetic algorithm (GA) so that both system performance and robustness are optimally preserved. Simulation studies are carried out, in which the proposed system is compared with a cascade proportional-integral-derivative (PID) control system. The results validate the feasibility of the design and show the superiority of the proposed control system in motion performances. Moreover, the LQI-GA consumes 2.28% less water and uses 83.85% less kinetic energy of the actuator than the PID control system.
Special Issue: “Physics and Mechanics of New Materials and Their Applications”
Authors: Kim Yun-Hae , Parinov Ivan A. , Chang Shun-Hsyung , Wang Hung-Yu
Published: September 2022

Solid-state physics, directed to the design, manufacture, research, and further application of advanced materials and composites, play one of the most important roles in the quick development of modern science, techniques, and technologies [...]
Special Features and Applications on Applied Metaheuristic Computing
Authors: Yin Peng-Yeng , Chang Ray-I
Published: September 2022

In recent years, many important yet complex problems, either continuous or combinatorial, suffer the intractability of the problem of nature [...]
Assessment of Soil Heavy Metal Pollution and Its Ecological Risk for City Parks, Vicinity of a Landfill, and an Industrial Area within Guangzhou, South China
Authors: Zhou Huimin , Ouyang Tingping , Guo Yu , Peng Shasha , He Chenjian , Zhu Zhaoyu
Published: September 2022

As a primary sink of pollutants, urban soil heavy metal pollution and its influence on urban residents and ecosystems has been becoming one of the most important environmental problems. In the present study, four indices, the Geoaccumulation index (Igeo), improved Nemerow index (IMN), degree of contamination (mCd), and contamination security index (CSI), as well as potential ecological risk (RI), were used to evaluate individual or integrated heavy metal pollution and its ecological risk for soil samples collected from city parks, the vicinity of a landfill, and an industrial area within the city of Guangzhou. The results indicated that the improved Nemerow index (IMN) calculated from the Geoaccumulation index was suitable for heavy metal pollution assessment of soils within landfills and industrial areas. As for soils collected from city parks, degree of contamination (mCd) was more suitable than IMN. Heavy metals Cd, Hg, Zn, and As were the main pollution elements in urban soils of Guangzhou. Potential ecological risks were mainly caused by Cd and Hg in urban soil of Guangzhou. Soil samples collected from city parks and the vicinity of the industrial area were moderately to highly and even extremely seriously polluted by heavy metals. Differing from the traditional cognition of the public, the ecological impact of heavy metal in soil in the vicinity of the landfill was similar to or even better than that within city parks.
Potential of Fluid Dynamic Bowtie Filter for Dose Reduction and Image Quality Improvement of Cone-Beam CT
Authors: Lin Xin , Zhuo Weihai , Liu Haikuan , Xie Tianwu
Published: September 2022

Reducing radiation dose to patients without compromising imaging quality has been an important issue in the medical use of X-ray computed tomography (CT). In this study, based on the conceptual designs of different types of attenuation filters, the radiation doses to patients who undergo a typical head, thorax and abdomen scan using a cone-beam CT with different scanning protocols were simulated using the Monte Carlo method, and the isotropy of the noise power spectrum (NPS) of the reconstructed images was also calculated. Compared to the scanning protocol without attenuation and tube current modulation (TCM), the results showed that the fluid dynamic bowtie filter (FDB) combined with the TCM technique reduced the average organ dose by 70%, 34% and 60% for a typical head, thorax and abdomen scan, respectively, and the NPS isotropy of the reconstructed images was also significantly improved. Compared to most currently used static bowtie filters, the FDB has a higher potential to reduce the dose for patients undergoing CT scans. Further efforts are warranted to make the FDB technique clinically useful.
Modeling the Ignition Risk: Analysis before and after Megafire on Maule Region, Chile
Authors: Azócar de la Cruz Gabriela Azócar de la , Alfaro Gabriela , Alonso Claudia , Calvo Rubén , Orellana Paz
Published: September 2022

Wildland fires are a phenomenon of broad interest due to their relationship with climate change. The impacts of climate change are related to a greater frequency and intensity of wildland fires. In this context, megafires have become a phenomenon of particular concern. In this study, we develop a model of ignition risk. We use factors such as human activity, geographic, topographic, and land cover variables to develop a bagged decision tree model. The study area corresponds to the Maule region in Chile, a large zone with a Mediterranean climate. This area was affected by a megafire in 2017. After generating the model, we compared three interface zones, analyzing the scar and the occurrences of ignition during and after the megafire. For the construction of georeferenced data, we used the geographic information system QGIS. The results show a model with high fit goodness that can be replicated in other areas. Fewer ignitions are observed after the megafire, a high recovery of urban infrastructure, and a slow recovery of forest plantations. It is feasible to interpret that the lower number of ignitions observed in the 2019–2020 season is a consequence of the megafire scar. It is crucial to remember that the risk of ignition will increase as forest crops recover. Wildland fire management requires integrating this information into decision-making processes if we consider that the impacts of climate change persist in the area.
Passive Array-Invariant-Based Localization for a Small Horizontal Array Using Two-Dimensional Deconvolution
Authors: Wang Yujie , Chi Cheng , Li Yu , Ju Donghao , Huang Haining
Published: September 2022

Recently, the array-invariant method was proposed to passively localize sources of opportunity in shallow water. It exploits multiple arrivals which are different in terms of beam angle and travel time. Conventional plane-wave beamforming in the existing array-invariant method is used to obtain beam-time migration. The resolution capability of conventional plane-wave beamforming is determined by array aperture, which, however, limits the localization accuracy of the existing array-invariant method. To improve the localization accuracy, this study proposes the use of two-dimensional (2D) deconvolution to obtain a better beam-time migration than in conventional plane-wave beamforming. Our simulation with a small horizontal array showed that the range estimation error of the proposed array-invariant method based on 2D deconvolution was only one-third of that of the existing method. The experiment also demonstrated the validity of our proposed method.
Performance of Textile Mask Materials in Varied Humidity: Filtration Efficiency, Breathability, and Quality Factor
Authors: Segovia Joelle M. , Huang Ching-Hsuan , Mamishev Maxwell , Yuan Nanhsun , He Jiayang , Novosselov Igor
Published: September 2022

During the COVID-19 pandemic, reusable masks became ubiquitous; these masks were made from various fabrics without guidance from the research community or regulating agencies. Though reusable masks reduce the waste stream associated with disposable masks and promote the use of masks by the population, their efficacy in preventing the transmission of infectious agents has not been evaluated sufficiently. Among the unknowns is the effect of relative humidity (RH) on fabrics’ filtration efficiency (FE) and breathability. This study evaluates the FE and breathability of several readily accessible mask materials in an aerosol chamber. Sodium chloride aerosols were used as the challenge aerosol with aerodynamic particle diameter in the 0.5 to 2.5 µm range. To mimic the variability in RH in the environment and the exhaled-breath condition, the chamber was operated at RH of 30% to 70%. The face velocity was varied between 0.05 m/s and 0.19 m/s to simulate different breathing rates. The FE and pressure drop were used to determine the quality factor of the materials. Among the tested materials, the 3M P100 filter has the highest pressure drop of 140 Pa; the N95 mask and the 3M P100 have almost 100% FE for all sizes of particles and tested face velocities; the surgical mask has nearly 90% FE for all the particles and the lowest pressure drop among the certified materials, which ranks it the second to the N95 mask in the quality factor. Other material performance data are presented as a function of relative humidity and aerosol size. The quality factor for each material was compared against reference filtration media and surgical masks. Multiple layers of selected materials are also tested. While the additional layers improve FE, the pressure drop increases linearly. Additionally, the certified materials performed approximately three times better than the highest performing non-certified material.
Underwater Compressed Gas Energy Storage (UWCGES): Current Status, Challenges, and Future Perspectives
Authors: Wang Hu , Wang Zhiwen , Liang Chengyu , Carriveau Rupp , Ting David S.-K. , Li Peng , Cen Haoyang , Xiong Wei
Published: September 2022

Underwater compressed air energy storage was developed from its terrestrial counterpart. It has also evolved to underwater compressed natural gas and hydrogen energy storage in recent years. UWCGES is a promising energy storage technology for the marine environment and subsequently of recent significant interest attention. However, it is still immature. In this study, the latest progress in both academic and industrial fields is summarized. Additionally, challenges facing this emerging technology are analyzed. The pros and cons of UWCGES are provided and are differentiated from the terrestrial variant. Technical, economic, environmental, and policy challenges are examined. In particular, the critical issues for developing artificial large and ultra-large underwater gas storage accumulators and effective underwater gas transportation are comprehensively analyzed. Finally, the demand for marine energy storage technology is briefly summarized, and the potential application scenarios and application modes of underwater compressed gas energy storage technology are prospected. This study aims to highlight the current state of the UWCGES sector and provide some guidance and reference for theoretical research and industrial development.
The Wiener–Hopf Equation with Probability Kernel and Submultiplicative Asymptotics of the Inhomogeneous Term
Authors: Sgibnev Mikhail
Published: September 2022

We consider the inhomogeneous Wiener–Hopf equation whose kernel is a nonarithmetic probability distribution with positive mean. The inhomogeneous term behaves like a submultiplicative function. We establish asymptotic properties of the solution to which the successive approximations converge. These properties depend on the asymptotics of the submultiplicative function.
Particle Number and Size Distributions (PNSD) from a Hybrid Electric Vehicle (HEV) over Laboratory and Real Driving Emission Tests
Authors: Thomas Daisy , Li Hu , Wang Xin , Ropkins Karl , Tomlin Alison S. , Bannister Chris D. , Hawley Gary
Published: September 2022

Particle number (PN) emissions from hybrid electric vehicles (HEV) during engine ignition and re-ignition events are an important but scarcely reported area. The objectives of the present work are to study the effects of drive cycle properties on the engine behaviour of a hybrid electric vehicle (HEV) and to investigate how this impacts the tailpipe PN emissions and their size distributions (PNSD). Worldwide harmonised light vehicles test cycle (WLTC) testing was conducted, as well as chassis dynamometer emission measurements over a realistic real driving emissions (RDE) speed pattern, using a Euro 5 Toyota Prius HEV with a Cambustion DMS500 sampling PN concentrations at the tailpipe. It is shown that the number of vehicle stops during a test cycle has a direct impact on the re-ignition activity for the HEV. 64 ± 3% of the total PN from WLTC testing was produced during engine re-ignition events while only 6 ± 1% was from stabilised engine operation. Similar proportions were observed for the RDE-style test cycle. The majority of engine reignition and destabilised activity, and hence PN emission, was during the low-speed sections of the drive cycles used. The average PNSD across cycle phases was different between cycles, due to the influence of dynamic properties on engine behaviour and hence the PN emission profile. The PNSD at the engine re-ignition and destabilised events had a merged wide peak with a maximum at 60 nm diameter and a shoulder at 12 nm diameter. The HEV had increased emissions of particles smaller than 23 nm under cold start, but similar overall PN emission values, compared to a warm start. The results of this work highlight the importance of controlling HEV PN emissions to limit human exposure to PN in urban environments where the majority of PN emissions occur. The sensitivity of HEV PN emission factors and PNSD to engine behaviour and, in turn, test cycle dynamic properties, is important to note when considering legislative test cycles, particularly with reference to the freedoms afforded by the RDE test cycle. The results also indicate that substantial improvements to air quality could be made by reducing the particle measurement protocol PN cut-off size to 10 nm.
Aerosol Property Analysis Based on Ground-Based Lidar in Sansha, China
Authors: Kong Deyi , He Hu , Zhao Jingang , Ma Jianzhe , Gong Wei
Published: September 2022

Marine aerosol is one of the most important natural aerosols. It has a significant impact on marine climate change, biochemical cycling and marine ecosystems. Previous studies on marine aerosols, especially in the South China Sea, were carried out by satellite and shipborne measurements. The above methods have drawbacks, such as low temporal–spatial resolution and signal interference. However, lidar has high accuracy and high temporal–spatial resolution, so it is suitable for high-precision long-term observations. In this work, we obtain marine aerosol data using Mie Lidar in Sansha, an island in the South Chain Sea. Firstly, by comparing boundary layer height (BLH) between Sansha and Hefei, we found that Sansha’s boundary layer height has significant differences with that of inland China. Secondly, we compare the aerosol extinction coefficients and their variation with height in Sansha and Hefei. Finally, we obtain hourly averaged aerosol optical depth at Sansha and explore its relation with weather. To analyze the AOD–weather relation, we select three meteorological factors (sea surface temperature, mean sea level pressure and 10 m u-component of wind) based on their feature importance, which is determined by random forest regression. We also analyze the relationship between AOD and the above meteorological factors in each season separately. The results show that there is a strong relation between the meteorological factors and AOD in spring and summer, while there is no clear correlation in fall and winter. These analyses can provide valid data for future researches on marine aerosols in the South China Sea.
Optimization Design of Velocity Distribution in the Airways of the Fluidized Bed Based on CFD and Taguchi Algorithm
Authors: Yan Hao , Liu Shisong , Wang Fei , Xu Wei , Li Jian , Xie Tengzhou , Zeng Yishan
Published: September 2022

A vital component that is frequently employed in the industrial powder conveying sector is the fluidized bed. In the light of powder unloading with a fluidized bed as the research object, an orthogonal experiment with two factors and four levels was established for the structural parameters of the fluidized bed. In the case of different noise factors, 16 schemes are designed and all schemes via computational fluid dynamics numerical simulation. The Taguchi method and regression analysis are used to analyze the response. Finally, the accuracy of the optimization results is tested. The results show that gas velocity decreases sharply at the airway’s entrance and, then, gas flows to the second half of the airway and velocity decreases steadily and uniformly. Airway arc length L exerts a greater effect on the signal-to-noise ratio (SNR) than airway height H. The parameter combination of 180 mm L and 17 mm H for obtaining the optimal velocity distribution uniformity is determined. The test results indicate that the overall fluidization effect of the fluidized bed with the optimal parameters is better. The linked research findings can be used as a guide when designing a fluidized bed system for transporting comparable powder.
Comprehensive Evaluation of Odor-Causing VOCs from the Painting Process of the Automobile Manufacturing Industry and Its Sustainable Management
Authors: Kultan Vanitchaya , Thepanondh Sarawut , Pinthong Nattaporn , Keawboonchu Jutarat , Robson Mark
Published: September 2022

Automotive manufacturing is one of the potential sources of air pollution particularly involving volatile organic compounds (VOCs). This study intensively evaluated VOC emissions and their dispersion from the industry. The measured VOCs were speciated for further evaluation of their odor threats according to the characteristics of each compound. Mathematical emission and air dispersion models were applied to assist in elaborating the source–receptor relationship allowing the determining of existing business-as-usual conditions with proposed mitigation measures to manage the pollution of the factory studied in this paper. Seven VOC species potentially caused odor problems to the surrounding community, including 1-butanol, ethyl benzene, toluene, m,p xylene, o xylene, methyl ethyl ketone, and methyl isobutyl ketone. The results from the AERMOD dispersion model revealed that the smell from these chemicals could reach up to about 800 m from the source. Analysis of mitigation measures indicated that two interesting scenarios should be considered according to their effectiveness. The concentrations of VOCs can decrease by up to 4.7, 14.0 and 24.9% from increasing the physical stack height by +1, +3 and +5 m from its existing height, respectively. Modification of the aeration tank of the wastewater treatment unit to a closed system also helped to reduce about 27.8% of emissions resulting in about a 27.6% decreased ambient air concentration. This study provided useful information on the characteristics of VOCs emitted by the automobile manufacturing industry. It also demonstrated the relevant procedures and highlights the necessity to comprehensively analyze the source–receptor relationship to evaluate the most appropriate measures in managing industrial air pollution.
The Performance of S2S Models on Predicting the 21.7 Extreme Rainfall Event in Henan China
Authors: Wang Xiaojuan , Li Shuai , Liu Li , Bai Huimin , Feng Guolin
Published: September 2022

Extreme rainfall may cause meteorological disasters and has tremendous impact on societies and economics. Assessing the capability of current dynamic models for rainfall prediction, especially extreme rainfall event prediction, at sub-seasonal to seasonal (S2S) scale and diagnosing the probable reasons are quite important topics in the current climate study field. This study analyzes the formation mechanisms of the extreme rainfall event during 18–22 July 2021 in Henan Province and introduces the Tanimoto Coefficient (TC) to evaluate the prediction performance of S2S models. The results show that confrontation between low-latitude typhoon “In-Fa” and subtropical highs leads to sufficient water vapor transporting to Henan, and that remarkable upward air motion causes strong convergence of water vapor, thereby providing atmospheric conditions for this extreme rainfall event. Furthermore, five S2S models showed limited capability in predicting this extreme rainfall event 20 days in advance with the TCs of four models being below 0.1. Models could capture this event signal 6 days ahead with most TCs above 0.2. The performances of model prediction for this extreme rainfall event were closely related to the fact that the water vapor convergence, vertical movements, relative vorticity, and geopotential height predicted by the NCEP model 20 days ahead were close to the actual situation, in contrast to the other four models 6 days in advance. This study implies that S2S model predictions for this extreme rainfall event show obvious differences, and the application of S2S models in the prediction of extreme events needs to fully consider their prediction uncertainties. The capability of the models to properly reproduce local water vapor convergence and vertical motions is also shown to be crucial for correctly simulating the extreme event, which might provide some hints for the further amelioration of models.
Variability of Equatorial Ionospheric Bubbles over Planetary Scale: Assessment of Terrestrial Drivers
Authors: Joshi Lalit Mohan , Tsai Lung-Chih , Su Shin-Yi , Dey Abhijit
Published: September 2022

Nighttime F-region field-aligned irregularities (FAIs) associated with equatorial plasma bubbles (EPBs) are impacted by terrestrial factors, such as solar irradiance and geomagnetic activity. This paper examines the impact of the planetary-scale periodic variability of terrestrial processes on EPB activity. Continual observations of the Equatorial Atmosphere Radar (EAR) have been utilized to derive the intra-seasonal variability of nighttime F-region FAIs in the context of the terrestrial factors mentioned above. A periodicity analysis using wavelet and Lomb–Scargle (LS) spectral analysis indicated significant amplitudes of the long-period planetary-scale variability in the F-region FAI signal-to-noise ratio (SNR), 10.7 cm flux, and geomagnetic indices, as well as a shorter period of variability. Interestingly, a careful inspection of the time series indicated the planetary-scale variability of F-region FAIs to be reasonably out of phase with the periodic geomagnetic variability. EPB occurrence and the FAI signal-to-noise ratio presented a systematic decrease with an increase in the level of geomagnetic activity. Non-transient quiet-time geomagnetic activity has been found to suppress both the occurrence as well as the strength of F-region FAIs. The impacts of planetary-scale geomagnetic activity appear to be non-identical in the summer and equinoctial EPBs. The results highlight the importance of periodic terrestrial processes in driving the planetary-scale variability of EPBs.
Holiday Climate Index: Urban—Application for Urban and Rural Areas in Romania
Authors: Velea Liliana , Gallo Alessandro , Bojariu Roxana , Irimescu Anisoara , Craciunescu Vasile , Puiu Silvia
Published: September 2022

Nature, landscape, relaxation, and outdoor activities are important motivations when choosing rural destinations for vacations. Therefore, when selecting a rural area as a vacation destination, we assume that climate features are important. We investigated the appropriateness of the holiday climate index: urban (HCI:urban) in quantitatively describing the relationship between climate and tourism fluxes in such destinations. We employed data from 94 urban and rural tourist destinations in Romania and correlated the monthly mean HCI:urban values with sectoral data (overnight tourists) for 2010–2018. The results show that weather and climate influenced tourism fluxes similarly in rural and urban destinations, supporting the hypothesis that HCI:urban may be used for rural areas as well. The information derived from HCI:urban may be useful for tourists when planning their vacations as well as for tourism investors in managing their businesses and reducing the weather and climate-related seasonality in tourism fluxes.
Evaluation of ECMWF Lightning Flash Forecast over Indian Subcontinent during MAM 2020
Authors: Sarkar Rituparna , Mukhopadhyay Parthasarathi , Bechtold Peter , Lopez Philippe , Pawar Sunil D. , Chakravarty Kaustav
Published: September 2022

During the pre-monsoon season (March–April–May), the eastern and northeastern parts of India, Himalayan foothills, and southern parts of India experience extensive lightning activity. Mean moisture, surface and upper-level winds, the sheared atmosphere in the lower level, and high positive values of vertically integrated moisture flux convergence (VIMFC) create favorable conditions for deep convective systems to occur, generating lightning. From mid-2018, the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS) operationally introduced lightning flash density on a global scale. This study evaluates the ECMWF lightning forecasts over India during the pre-monsoon season of 2020 using the Indian Institute of Tropical Meteorology (IITM) Lightning Location Network (LLN) observation data. Qualitative and quantitative analysis of the ECMWF lightning forecast has shown that the lightning forecast with a 72-h lead time can capture the spatial and temporal variation of lightning with a 90% skill score.
Attention-Based BiLSTM Model for Pavement Temperature Prediction of Asphalt Pavement in Winter
Authors: Bai Shumin , Yang Wenchen , Zhang Meng , Liu Duanyang , Li Wei , Zhou Linyi
Published: September 2022

Pavement temperature is the main factor determining road icing, and accurate and timely pavement temperature prediction is of significant importance to regional traffic safety management and preventive maintenance. The prediction of pavement temperature at the micro-scale has been a challenge to be tackled. To solve this problem, a bidirectional extended short-term memory network model based on the attention mechanism (Att-BiLSTM) was proposed to improve the prediction performance by using the time series features of pavement temperature and meteorological factors. Pavement temperature data and climatic data were collected from a road weather station in Yunnan, China. The results show that the MAE, MSE, and MAPE of the proposed Att-BiLSTM model were 0.330, 0.339, and 10.1%, respectively, which were better than the other baseline models. It was shown that 93.4% of the predicted values had an error less than 1 °C, and 82.1% had an error less than 0.5 °C, indicating that the proposed Att-BiLSTM model enables significant performance improvement. In addition, this paper quantified and analyzed the effects of parameters such as the size of the sliding window, the number of hidden layer neurons, and the optimizer on the performance of the prediction model.
Air Pollution and Economic Impact from Ships Operating in the Port of Varna
Authors: Garbatov Yordan , Georgiev Petar
Published: September 2022

The present work develops a multidisciplinary approach for evaluating the air pollution and economic impact from ships operating in the port of Varna. The work collects and analyses automatic identification system (AIS) data of the arriving and queuing dry cargo ships in the seaport of Varna in identifying the statistical descriptors of the length of the ships, gross tonnage (GT), and ship engine power. The queueing theory (QT) is employed to analyse the ship operations in a single queue and is processed by three parallel terminals, satisfying the port regulations. The Gaussian dispersion model (GDM) is adopted to predict the pollution concentration from ships arriving at the seaport, queuing, approaching, waiting, processing at the berth, and departing. The gas emission is estimated as a function of the ship movement trajectory, and the time duration at any stage is defined by QT for the most critical surrounding areas, considering the wind speed, as well as horizontal and vertical dispersion as a function of the location of the ship, accounting for the effective emission height, weather conditions, and speed. To mitigate the potential impact on health, the gas emissions of oxides of nitrogen (NOx), sulphur dioxide (SO2), and air-borne particles (PM10) generated by ships during the queuing and port operation are evaluated. Potential cleaning measures for any ship are implemented to satisfy the maximum allowable concentrations (MAC) in surrounding areas. The implemented ship pollution cleaning measures and overall ship and terminal operating costs are minimised to identify the most efficient berth operation. The developed approach is flexible and can be used for any particular conditions for ships operating in ports.
Method for Measuring the Pseudomomentum of Hydrogen Atoms by the Number of Observable Hydrogen Lines Controlled by the Diamagnetism
Authors: Oks Eugene , Angelo Paulo , Dalimier Elisabeth
Published: September 2022

Hydrogen atoms, being subjected to a strong magnetic field, exhibit an additional, delocalized potential well at almost a microscopic distance from the nucleus. We studied the influence of the delocalized states of hydrogen atoms on the number of observable hydrogen lines in strongly magnetized plasmas. We show that, for sufficiently large values of the pseudomomentum K (K being the integral of the motion controlling the separation of the center of mass and the relative motions), this effect dominates other factors potentially influencing the number of observable hydrogen lines in strongly magnetized plasmas. We provide examples for plasma parameters relevant to edge plasmas of contemporary and future tokamaks, as well as for DA white dwarfs. We demonstrate that our results open up an avenue for the experimental determination of the pseudomomentum K. This is the first proposed method for the experimental determination of the pseudomomentum—to the best of our knowledge.
A New Emergency-Risk-Evaluation Approach under Spherical Fuzzy-Information Environments
Authors: Chang Kuei-Hu
Published: September 2022

When major emergencies or accidents occur, risk evaluation and prediction are the most important means to reduce their impact. Typical risk evaluation uses the failure mode and effects analysis (FMEA) method for failure-risk ranking and control. However, when faced with severe special infectious diseases such as COVID-19, there are many cognitive and information uncertainties that the FMEA method is unable to effectively handle. To effectively deal with the issue of risk evaluation when major emergencies or accidents occur, this paper integrated the risk-priority number and spherical fuzzy-sets methods to propose a novel emergency-risk-evaluation method. In the numerical verification, this paper applied the example of preventing secondary COVID-19 transmissions in hospitals to explain the calculation procedure and validity of the proposed new emergency-risk-evaluation approach. The calculation results were also compared with the typical RPN, fuzzy-set, and intuitionistic fuzzy-set methods. The calculation results showed that the proposed new emergency-risk-evaluation approach could effectively handle the cognitive and informational uncertainties of emergency-risk-evaluation issues during the COVID-19 pandemic.
Degenerate Fubini-Type Polynomials and Numbers, Degenerate Apostol–Bernoulli Polynomials and Numbers, and Degenerate Apostol–Euler Polynomials and Numbers
Authors: Jin Siqintuya , Dağli Muhammet Cihat , Qi Feng
Published: September 2022

In this paper, by introducing degenerate Fubini-type polynomials, with the help of the Faà di Bruno formula and some properties of partial Bell polynomials, the authors provide several new explicit formulas and recurrence relations for Fubini-type polynomials and numbers, associate the newly defined degenerate Fubini-type polynomials with degenerate Apostol–Bernoulli polynomials and degenerate Apostol–Euler polynomials of order α. These results enable one to present additional relations for some degenerate special polynomials and numbers.