bluuebunny/crossref_metadata_2025 huggingface dataset:
Laboratory Test of a Vehicle Active Noise-Control System Based on an Adaptive Step Size Algorithm
Authors: Jiang Tao , Liu Jiang , Peng Cheng , Wang Shuliang
Published: December 2022

NVH (noise, vibration, and harshness) is a key factor affecting vehicle comfort. Compared with traditional sound absorption and isolation methods, active noise control (ANC) offers a significant advantage in solving the problem of low- and medium-frequency noise from road surfaces. However, the classic filtered-x least mean squares (FxLMS) algorithm is ineffective in terms of adapting to different road noises to ensure a stable noise reduction effect when facing the complex and changeable noise environment of moving vehicles. Therefore, an adaptive step size algorithm (ASSFxLMS) is proposed in this paper, which can adjust the step size according to the size of the reference signal to ensure the stability of the adaptive process. In order to improve the performance of the algorithm, a particle swarm optimization algorithm is also used to automatically adjust the parameters, so that the step size of the adaptive algorithm always maintains a relatively ideal size. The simulated pulse noise of standard SαS distribution was used as the reference signal for the simulation. The simulation results show that compared with other algorithms, the proposed algorithm under different degrees of pulse noise conditions, noise reduction stability, and noise reduction amplitude are improved. In order to further verify the feasibility of the algorithm in vehicle road noise reduction, this paper also conducted a hardware-in-the-loop noise reduction experiment in the laboratory, employing the road noise data collected by the real vehicle. Under different interior noise conditions, the proposed active noise-control system has a maximum noise reduction effect of 12 dB for low-frequency noise below 100 Hz.
Predicting Ceramic Wool Diameter by Motor Frequency Using Improved BP Neural Network
Authors: Xu Tengzhou , Huang Jie , Li Yang , Chen Tao
Published: December 2022

Ceramic wool was prepared by the melt-spinning method, and the diameter was the main factor severely affecting the performance of the final product which was difficult to check online. The current study discusses the approximate simulation of the fiber formation and presents a fast precision measuring method to predict the ceramic wool diameter using an improved Back-Propagation (BP) neural network. Particle Swarm Optimizer (PSO) was employed to optimize the neural network structure for its presentation of the relationship between the motor frequency of the spinning wheel and the ceramic wool diameter. The superiority of this method was demonstrated by experiment compared with the least square method (LSM). The mean measurement error of PSO-BP was 0.471%, which was lower than that of LSM. The presented PSO-BP method was very valuable for predicting the wool diameter, and the neural networks could solve nonlinear problems successfully, which was certified by the actual prediction of ceramic wool diameter.
Severity Prediction of Highway Crashes in Saudi Arabia Using Machine Learning Techniques
Authors: Aldhari Ibrahim , Almoshaogeh Meshal , Jamal Arshad , Alharbi Fawaz , Alinizzi Majed , Haider Husnain
Published: December 2022

Kingdom of Among the G20 countries, Saudi Arabia (KSA) is facing alarming traffic safety issues compared to other G-20 countries. Mitigating the burden of traffic accidents has been identified as a primary focus as part of vision 20230 goals. Driver distraction is the primary cause of increased severity traffic accidents in KSA. In this study, three different machine learning-based severity prediction models were developed and implemented for accident data from the Qassim Province, KSA. Traffic accident data for January 2017 to December 2019 assessment period were obtained from the Ministry of Transport and Logistics Services. Three classifiers, two of which are ensemble machine learning methods, namely random forest, XGBoost, and logistic regression, were used for crash injury severity classification. A resampling technique was used to deal with the problem of bias due to data imbalance issue. SHapley Additive exPlanations (SHAP) analysis interpreted and ranked the factors contributing to crash injury. Two forms of modeling were adopted: multi and binary classification. Among the three models, XGBoost achieved the highest classification accuracy (71%), precision (70%), recall (71%), F1-scores (70%), and area curve (AUC) (0.87) of receiver operating characteristic (ROC) curve when used for multi-category classifications. While adopting the target as a binary classification, XGBoost again outperformed the other classifiers with an accuracy of 94% and an AUC of 0.98. The SHAP results from both global and local interpretations illustrated that the accidents classified under property damage only were primarily categorized by their consequences and the number of vehicles involved. The type of road and lighting conditions were among the other influential factors affecting injury s severity outcome. The death class was classified with respect to temporal parameters, including month and day of the week, as well as road type. Assessing the factors associated with the severe injuries caused by road traffic accidents will assist policymakers in developing safety mitigation strategies in the Qassim Region and other regions of Saudi Arabia.
Analytical Study on the Frictional Behavior of Sliding Surfaces Depending on Ceramic Friction Materials
Authors: Han Oneil , Kwark Jong-Won , Lee Jung-Woo , Han Woo-Jin
Published: December 2022

Friction material, as the main component in a bearing support, allows frictionless behavior between the two connected structures. Previous studies on friction material considered polytetrafluoroethylene (PTFE) and attempted to analyze the resulting friction behavior balance. However, aging PTFE loses its frictionless performances, because PTFE is crushed, causing it to tear, or the lubricant is removed. The performances of the friction material should thus be maintained to preserve the performance of structures. To overcome these issues, this study applies a ceramic friction material owing to its advantages of high strength, low friction, and low deformation. The frictional behavior is investigated on a full-scale model using Finite Element Analysis (FEA) according to the edge type of the ceramic friction material. The main design variables include four edge types, namely, general, camber, round and taper types. The results confirm that the modified edge types (camber, round and taper type) reduced the stress and deformation which, in turn, improved the friction behavior.
Controlling Laser Irradiation with Tissue Temperature Feedback Enhances Photothermal Applications: Ex-Vivo Evaluation on Bovine Liver
Authors: Kaya Özgür , Düzgören İpek , Çilesiz İnci , Gülsoy Murat
Published: December 2022

Achieving repeatable and successful results without causing excessive collateral damage is of paramount importance for photothermal laser applications. Predetermined laser parameters cannot ensure patient safety and treatment success due to variance between optical and thermal characteristics among subjects. Controlling laser irradiation with tissue temperature feedback is the current gold standard for various photothermal treatments (PTT) which are rate processes described by the Arrhenius temperature integral. This study establishes the validity of our low-cost design that makes tissue surface temperature control during photothermal laser applications more accessible in resource limited clinical environments. We demonstrated the practical performance and potential of our system with ex-vivo bovine liver irradiation using an ytterbium fiber laser (λ=1071 nm) with two independent variables: laser power (3.4 W, 6.8 W and 10.2 W) and target surface temperature (55 °C, 65 °C and 75 °C). Our system efficiently maintained tissue surface temperatures at target values in all laser power groups. In contrast, fixed-dose application groups displayed a high final temperature range and variation in the control experiment. Temperature–time responses of samples varied significantly, in agreement with a wide range of optical and thermal coefficients. Long exposure duration groups (lower power, higher target temperature) displayed more radical differences suggesting a dominance of optical and thermal characteristics over the response. The low-cost surface-temperature-controlled medical laser system we have developed is capable of ensuring the success and reproducibility of PTT modalities and patient safety.
A Numerical Analysis of Active Flow Control Techniques for Aerodynamic Drag Reduction in the Square-Back Ahmed Model
Authors: Phan Thanh-Long , Pham Quoc Thai , Nguyen Thi Kim Loan , Nguyen Tien Thua
Published: December 2022

Aerodynamic drag reduction is required with new stringent constraints on pollutant emissions and fuel efficiency of ground vehicles. In this context, active flow control is a promising approach to achieve this target. This study focuses on applying different flow control strategies on the square-back Ahmed model to reduce aerodynamic drag. A steady blowing jet, a synthetic jet and an unsteady jet are located at the back edges of the model as flow control devices. A numerical study based on the 3D WMLES simulation was performed to evaluate the drag reduction capabilities of these devices at different operating conditions. The results showed that a maximum aerodynamic drag reduction of 26.51% was achieved when using a steady blowing jet, and 17.27% with an unsteady jet. In contrast, the effect of the synthetic jet on the aerodynamic drag of the model is solely at high control frequencies.
Beyond the Calcium Score: What Additional Information from a CT Scan Can Assist in Cardiovascular Risk Assessment?
Authors: Bernardini Federico , Gelfusa Martina , Celeski Mihail , Coletti Federica , Nusca Annunziata , De Stefano Domenico , Piccirillo Francesco , Mangiacapra Fabio , Gallo Paolo , Cammalleri Valeria , Cocco Nino , Rinaldi Raffaele , Quattrocchi Carlo Cosimo , Ussia Gian Paolo , Grigioni Francesco
Published: December 2022

Coronary artery disease (CAD) still represents a leading cause of mortality worldwide. Early identification of patients at the highest risk of CAD is crucial to prevent acute adverse events and reduce morbidity and mortality. The coronary artery calcium (CAC) score is a reliable cardiovascular (CV) risk index with an independent prognostic value. Guidelines recommend using it as a risk enhancer in individuals with low or moderate CV risk. However, other computed tomography (CT) measurable parameters have recently been proposed as CV risk markers. Increasing evidence demonstrates the association between epicardial fat volume and coronary atherosclerosis in chronic and acute coronary syndromes. Furthermore, other parameters obtainable from CT, such as aortic stiffness, liver fat, aortic calcium, and myocardial scarring, are under investigation. This review aims to describe all CT potential in atherosclerosis detection and cardiovascular risk assessment beyond the CAC, trying to understand how to integrate CT parameters with traditional risk factors and to improve clinicians' ability to detect CAD early, allowing appropriate therapies promptly.
Impedance Spectroscopy and Its Application in Measurement and Sensor Technology
Authors: Kanoun Olfa , Himmel Jörg , Errachid Abdelhamid
Published: December 2022

Impedance spectroscopy is a key enabling measurement method that exploits the measurement of the complex impedance of a material or a system to characterize it or to track its changes over time [...]
A Novel Disassembly Strategy of Hexagonal Screws Based on Robot Vision and Robot-Tool Cooperated Motion
Authors: Chen Jianzhou , Liu Zhifeng , Xu Jingjing , Yang Congbin , Chu Hongyan , Cheng Qiang
Published: December 2022

Disassembly plays an important role in the production process. Screw automatic unfastening guided by a robot has been widely used in the fields of industrial manufacturing and maintenance. Different from the previous studies that have used a flexible effector and expensive sensors, this paper presents a novel unfastening strategy based on robot vision for a hexagonal screw with an arbitrary loose state. In a robotic system, an industrial camera and a servo unfastening tool are installed at a robotic end-effector. The main contributions of this work are as follows. A camera pose adjustment method is proposed to obtain high-quality images of a target screw. The hexagonal screw pose calculation method based on the geometric analysis is developed to complete the screw–tool engagement. The cooperated motion of a robot and an unfastening tool is planned for the screw unfastening action. The effectiveness of the proposed control strategy is verified by experiments, and the influence of the motion speed on the unfastening quality is analyzed using the torque data collected by the unfastening tool. The analysis results can provide a significant foundation for the motion parameter selection in the proposed strategy.
Vibration Characteristics and Experimental Research of an Improved Bistable Piezoelectric Energy Harvester
Authors: Zhang Xuhui , Tian Hao , Pan Jianan , Chen Xiaoyu , Huang Mengyao , Xu Hengtao , Zhu Fulin , Guo Yan
Published: December 2022

Bistable piezoelectric energy harvester (BPEH) can remove mechanical energy waste, which is expected to realize the self-power supply of wireless sensors. To further improve the energy harvesting efficiency, we designed an improved bistable piezoelectric energy harvester (IBPEH). The restoring force model of the composing beam is acquired based on fitting experimental data, and the nonlinear magnetic model is obtained by using the magnetic dipole method. The electromechanical coupling dynamics model of the system is established based on Newton’s second law and Kirchhoff’s law. Based on the control variable method, the influences of excitation frequency and excitation amplitude on the vibration characteristics of IBPEH and BPEH are compared in simulation analysis. Moreover, the correctness of the theoretical analyses is verified by experiments. The results show that variations in the number of magnets and appropriate adjustments in their positions can broaden the operating frequency bandwidth of the bistable piezoelectric energy harvester, and realize large-amplitude periodic motion at lower excitation amplitudes. IBPEH can yield a higher voltage than BPEH under the same excitation conditions. This paper provides a theoretical basis for optimizing the potential well and further improving the electric energy harvest efficiency of the bistable piezoelectric energy harvester device.
Fusion Segmentation Network Guided by Adaptive Sampling Radius and Channel Attention Mechanism Module for MLS Point Clouds
Authors: Cheng Peng , Guo Ming , Wang Haibo , Fu Zexin , Li Dengke , Ren Xian
Published: December 2022

Road high-precision mobile LiDAR measurement point clouds are the digital infrastructures for high-precision maps, autonomous driving, digital twins, etc. High-precision automated semantic segmentation of road point clouds is a crucial research direction. Aiming at the problem of low semantic segmentation accuracy of existing deep learning networks for inhomogeneous sparse point clouds of mobile LiDAR system measurements (MLS), a deep learning method that adaptively adjusts the sampling radius of region groups according to the point clouds density is proposed. We construct a deep learning road point clouds dataset based on a self-developed mobile LiDAR system to train and test road point clouds semantic segmentation. The overall accuracy of the method for road point clouds segmentation is 98.08%, with an overall mIOU of 0.73 and mIOUs of 0.99, 0.983, 0.99, 0.66, and 0.51 for roads, guardrails, signs, streetlights, and lane lines, respectively. The experimental result shows that the method can achieve more accurate segmentation for inhomogeneous sparse road point clouds of mobile LiDAR systems. Compared with the existing methods, the segmentation accuracy is significantly improved.
A Study on Improving the Machining Performance of Scrolls
Authors: Lin Yi-Tsung , Jhang Jia-Lun , Schabacker Michael , Tsay Der-Min , Hwang Guan-Shong , Lin Bor-Jeng
Published: December 2022

To improve machining efficiency and product precision in scroll manufacturing, we studied three adaptive milling processes: adaptive feed rate planning, chatter suppression measures, and optimization of milling parameters during the rough, semi-fine, and fine machining of scrolls. In the rough machining of scrolls, adaptive feed rate planning was used to compute the cutting area per cutter tooth in real time in order to adjust the feed rate and optimize the material removal rate (MRR) under a given maximum acceptable cutting load. To suppress the possibility of chatter in the semi-fine and fine machining processes, the chatter frequencies were detected with a microphone and the spindle speeds were promptly modified using a developed program in combination with the controller of the milling machine. Based on the Taguchi method and analysis of variance (ANOVA), we determined the optimum milling parameters for the fine machining processes to improve contour characteristics, such as the profile errors and surface roughness of scrolls. Experimental tests were implemented to demonstrate and verify the feasibility of the adaptive milling processes proposed in this study.
Analysis of Flow Structures and Global Parameters across a Heated Square Cylinder in Forced and Mixed Convection
Authors: Ali Rashid , Hasan Nadeem
Published: December 2022

In the present study, numerical simulations are performed to identify the role of Reynolds number (Re), Richardson number (Ri) and free-stream orientations (α) on flow structures, aerodynamic parameters and heat transfer characteristics for the conditions (20 ≤ Re ≤ 120, 0° ≤ α ≤ 90° and 0 ≤ Ri ≤ 1.6). Prandtl number (Pr) and cylinder orientation (ϕ) are kept fixed at 0.71 and 0°. The Oberbeck–Boussinesq approximation is used to account for buoyancy effects. The governing equations of continuity, momentum and energy are discretized on a colocated body-fitted grid by employing a finite difference method. A viscous implicit pressure correction scheme is employed to advance the discrete solution in time. Contour maps of mean/steady drag coefficient and Nusselt number on (α-Ri) plane are plotted for 20 ≤ Re ≤ 120. From these contour maps, it is possible to identify the ranges of parameters (α, Ri) that can yield a relatively high mean/steady heat transfer rate accompanied by relatively low values of mean/steady drag coefficient. For [70° ≤ α ≤ 90°, 0 ≤ Ri ≤ 1.6], such a scenario is possible for any Re ∈ [20, 120]. The Strouhal number is observed to be maximum for Re = 120 at α = 45° and Ri = 1.2. Mean or steady coefficient of lift for any free-stream orientation (α ≠ 0°) is found to be highest at Re = 20 and Ri = 1.6. Sensitivity of (CD)Ri = 0.0 to α is observed to be minimum for Re = 20 and maximum for Re = 120. Sensitivity of the ratio CD(Ri,α)/CD(0,α) to Re is observed to be lower for unsteady flows than for steady flows, and it decreases with an increase in Re at a fixed value of Ri. Mean Nusselt number (Nu) in the forced flow regime increases significantly with an increase in Re at a fixed α. The Nusselt number is observed to be more sensitive to Ri for steady flows than for unsteady flows. The percentage increase in the ratio Nu(Ri,α)/Nu(0,α) for the entire range of Re is found to be 14.07%, 14.13%, 11.74% and 10.62% at α = 30°, 45°, 60° and 90°. At a fixed Ri, the Nusselt number ratio is found to decrease with an increase in Re for the entire range of α except for α = 90°. It is observed that the rate of heat transfer from the faces of the cylinder increases with an increase in Re for the entire ranges of α and Ri.
Biomonitoring Atmospheric Pollution of Polycyclic Aromatic Hydrocarbons Using Mosses
Authors: Gao Guiping , Zeng Hui , Zhou Qixing
Published: December 2022

Polycyclic aromatic hydrocarbons (PAHs), as the main components of petroleum hydrocarbons (PHCs), are carcinogenic organic pollutants that occur widely in the atmospheric environment with increasing concentration. Moreover, PAHs are widespread all over the world due to their high volatility and long-range transport potential. The monitoring of atmospheric PAHs is often limited by working conditions, especially around oil field operation areas and other industrial areas. Mosses (Bryophyta), the most sensitive atmosphere pollution indicators, can be easily collected and have been used to monitor atmospheric pollutants including PAHs. Thus, characteristics and influencing factors of mosses’ absorption and accumulation of PAHs in the atmosphere were discussed, and the application of mosses in the biomonitoring of atmospheric PAHs were summarized. Biomonitoring mosses include Dicranum scoparium, Hypnum cupressiforme, Thamnobryum alopecurum, Thuidium tamariscinum, Hylocomium splendens, Pleurozium scheberi, etc. Currently, the main methods for monitoring PAHs by mosses are biomonitoring with the chemical analysis method, the index of atmospheric purity (IAP) method, the ecological survey method, and the Moss-bag technique. Biomonitoring of atmospheric PAHs using mosses has a relatively wide range of prospects.
Hourly Valley Concentration of Air Pollutants Associated with Increased Acute Myocardial Infarction Hospital Admissions in Beijing, China
Authors: Fu Jia , Liu Yanbo , Zhao Yakun , Tang Siqi , Chen Yuxiong , Liu Yijie , Han Yitao , Fan Zhongjie
Published: December 2022

(1) Background: Acute myocardial infarction (AMI) imposes a great burden on global health. Few studies have demonstrated the effects of valley concentration of air pollutants on AMI hospital admissions. (2) Methods: Hospitalizations for AMI from 1 May 2014 to 31 December 2019 were analyzed. Generalized additive models (GAM) were used to quantify the exposure–response association between the hourly peak, mean, and valley concentration of six air pollutants and AMI hospital admissions. Stratification analyses were conducted to identify the susceptible population. (3) Results: Hourly peak, mean, and valley concentrations of PM2.5, PM10, SO2, NO2, and CO were significantly associated with AMI hospital admissions. Each 10-unit increase in the hourly valley concentration of them led to 0.50% (0.35–0.66%), 0.44 % (0.32–0.56%), 0.84% (0.47–1.22%), 1.86% (0.73–3.01%), and 44.6% (28.99–62.10%) excess risk in AMI hospital admissions, respectively. In addition, the effects of hourly valley concentration were larger than mean and peak concentrations. The effects in the female or older than 65 groups were larger than that in the male or younger than 65 groups. (4) Conclusions: PM2.5, PM10, SO2, NO2, and CO exposure contributed to increased AMI hospital admissions. Hourly valley concentration might be a more potent indicator of adverse cardiovascular events. Females and individuals older than 65 were more susceptible to ambient air pollutant exposure.
Can Pollution Regulations Enable Key Industries to Reduce CO2 Emissions?—Empirical Evidence from China, Based on Green Innovative Technology Patents and Energy Efficiency Perspectives
Authors: Li Jin , Zhang Huarong
Published: December 2022

Under the influence of the dual policies of sustainable economic development and the national dual-carbon target, the establishment of an environmental protection department for the treatment of heavily polluting industries is imminent, and the country has launched pollution control policies and regulations to restrict the emission rights of heavily polluting industries. Therefore, this paper focuses on whether the restriction of emission rights in key industries has reduced carbon emissions. To achieve this, this paper uses panel data of prefecture-level cities in China from 2006 to 2019 and adopts a two-way fixed-effects DID model to systematically analyze the impact of the key pollution industry governance policies launched by the Ministry of Environmental Protection on CO2 emissions in 2017. And further analyze the role of variables such as green technology innovation patents and energy efficiency using this model, while parallel trend tests and placebo tests, and related policies are used to ensure the robustness of the regression results. This paper reveals that: (1) The heavy pollution industry governance policy implemented in 2017 can effectively reduce CO2 emissions in the cities of the treated group, and the effect is more significant in the year of policy implementation; (2) Green utility patents and energy-use efficiency are the effective mediating mechanisms to reduce CO2 emissions; (3) Over time, the effect of heavy pollution industry governance policy on CO2 emissions gradually decreases; (4) The reliability of the baseline regression results of this paper is proved by the use of parallel trend tests, placebo tests, and tests excluding the influence factors such as relevant policies in the same period. Therefore, the key polluting industries treatment policy launched by China’s Ministry of Environmental Protection in 2017 under the recent dual-carbon policy development goals formulated by China, can effectively reduce carbon emissions; however, in the future economic development process, the government should give more consideration to the continuity of the policy impact and its coherence on economic development when implementing the policy.
Climate Indicators of Landslide Risks on Alaska National Park Road Corridors
Authors: Lader Rick , Sousanes Pamela , Bhatt Uma S. , Walsh John E. , Bieniek Peter A.
Published: December 2022

Landslides along road corridors in Alaska national parks pose threats to public safety, visitor access, subsistence activities, and result in costly remediation of damaged infrastructure. Landslide risk in these areas, which contain near-surface permafrost, is associated with mean annual air temperatures (MAATs) above freezing and heavy precipitation events. Historical (1981–2020) values of MAAT and summer precipitation (JJA PCPT) from the fifth generation European Centre for Medium-Range Weather Forecasts (Reading, UK) atmospheric reanalysis (ERA5) were compared to mid-century (2021–2060) and late-century (2061–2100) downscaled climate model projections across Gates of the Arctic National Park and Preserve (GAAR), Denali National Park and Preserve (DENA), and Wrangell-St. Elias National Park and Preserve (WRST). ERA5 showed that all locations historically had MAAT values below freezing, but all three parks were warming significantly (0.3–0.6 °C per decade). Observed trends of MAAT from 18 stations showed warming trends with 11 of the 18 being significant at the 95% confidence level using the Mann–Kendall non-parametric test. Road corridor values are given for the: (1) proposed Ambler Road through GAAR, (2) Denali Park Road in DENA, and (3) McCarthy Road in WRST. Elevated risk from MAAT was projected in the mid-century period for the Denali Park Road and McCarthy Road and across all three park road corridors in the late-century period; elevated risk from JJA PCPT was projected in all periods for all road corridors.
Impacts of Observed Extreme Antarctic Sea Ice Conditions on the Southern Hemisphere Atmosphere
Authors: Zhu Zhu , Song Mirong
Published: December 2022

The Antarctic sea ice has undergone dramatic changes in recent years, with the highest recorded sea ice extent in 2014 and the lowest in 2017. We investigated the impacts of the observed changes in these two extremes of Antarctic sea ice conditions on the atmospheric circulation in the Southern Hemisphere. We conducted three numerical simulations with different seasonal cycles of Antarctic sea ice forcings using the Community Atmosphere Model Version 5: the maximum sea ice extent in 2014 (ICE_14), the minimum sea ice extent in 2017 (ICE_17), and the average sea ice extent between 1981 and 2010 (ICE_clm, reference simulation). Our results suggest that the atmospheric response in the Southern Hemisphere showed strong seasonal variations and the atmospheric circulation in winter was more sensitive to the decreased Antarctic sea ice in 2017 than the increased sea ice in 2014. In ICE_14, the westerlies over the polar region were enhanced in summer, but there was no significant change in the zonal-averaged wind in winter. In contrast, in ICE_17, there was a clear equatorward shift in the subtropical jet in winter, but no significant change in summer. The temperature responses were limited to the Antarctic coast, where there were changes in the sea ice in ICE_14 and ICE_17. The warming on the coast of the Amundsen Sea in summer led to a slight increase in precipitation in both simulations.
Numerical Study on Storm Surge Level Including Astronomical Tide Effect Using Data Assimilation Method
Authors: Xu Junli , Ma Kai , Nie Yuling , Liu Chuanyu , Bi Xin , Shi Wenqi , Lv Xianqing
Published: December 2022

In the storm surge model, the wind drag coefficient Cd is a critical parameter that has a great influence on the forecast of the storm surge level. In the present study, the effect of various wind drag coefficient parameterizations on the storm surge level is investigated in the Bohai Sea, Yellow Sea and East China Sea for Typhoons 7203 and 7303. Firstly, the impacts of initial values of a and b in the linear expression Cd = (a + b × U10) × 10−3 on the pure storm surge model are evaluated based on the data assimilation method. Results indicate that when a and b (i.e., the wind drag coefficients given by Smith, Wu, Geernaert et al. and Mel et al.) are non-zeros, the performance of the model has little difference, and the result from Wu is slightly better. However, they are superior to the performance of the model adopting zero initial values. Then, we discuss the influences of diverse ways of calculating wind drag coefficients, which are inverted by data assimilation method (including both linear and constant Cd) and given in the form of linear formulas, on simulating pure storm surge level. They show that the data assimilation-based coefficients greatly exceed those of the ordinary coefficient formulas. Moreover, the wind drag coefficient in the linear form is a little better than that in constant form when the data assimilation method is used. Finally, the assessment of the impact of astronomical tides on the storm surge level is conducted, and the simulation demonstrates that the storm surge model, which has the combination of four constituents (M2, S2, K1, O1) and wind drag coefficient inverted by the data assimilation method with the linear Cd, exhibits the best performance.
Application of Radar Radial Velocity Data Assimilation Based on Different Momentum Control Variables in Forecasting Typhoon Kompasu
Authors: Yang Gangjie , Min Jinzhong , Shen Feifei
Published: December 2022

The study is based on the Weather Research and Forecasting Model (WRF) and the three-dimensional variational (3DVAR) data assimilation system. Based on two different control variables, the effects of radar radial velocity assimilation in forecasting of the tropical cyclone (TC) Kompasu were evaluated. The single observation experiment showed that DA_ψχ produces cyclonic increments, while DA_UV only produces increments in the same direction as the observation. DA_ψχ significantly enhances the wind field at 850 hPa with a large number of unphysical cyclonic increments. On the other hand, DA_UV produces reasonable cyclonic increments to enhance the TC. The assimilation of DA_UV makes the surface wind enhanced and the sea level pressure at the TC center reduced. The circular structure of the DA_ψχ wind field is not clear and neither is the large wind area concentrated. In addition, the DA_ψχ shows spurious convection at the high altitude of the vertical cross section, while the DA_UV presents enhanced large wind area at the bottom. The RMSE of the radial velocity is smaller during the circular assimilation in DA_UV. DA_ψχ does not improve the track forecast of Kompasu, while DA_UV shows a significant improvement by the track forecast.
Simulation Study of the Applicability of the “Slice” Approach to Assessing the Water Content in Clouds from the Radar Return Signal
Authors: Yurchak Boris S.
Published: December 2022

By computer simulation, the main consequences of the “slice” approach to assessing the power of a radar return signal from an atmospheric water cloud were verified. The cloud was modeled as a set of slices, which are thin layers coinciding with the wavefront of the probing radar radiation. The return signal was calculated as the convolution of the probe pulse with the cloud. The simulation was based on the previously derived “slice” radar equation, which determines the received power taking into account the statistical characteristics of fluctuations in the number of slice droplets and their water content. Estimates of the magnitude of the simulated return signal were compared with the theoretical formula for various statistical characteristics of the ensemble of droplets that make up the cloud model. The simulation result confirmed the validity of using the slice approach to interpret radar measurements of water content in clouds.
Atmospheric Effects of Magnetosheath Jets
Authors: Dmitriev Alexei V. , Suvorova Alla V.
Published: December 2022

We report effects in the upper high-latitude atmosphere related to the interaction of fast magnetosheath plasma streams, so-called jets, with the dayside magnetopause. The jets were observed by THEMIS mission in the dayside magnetosphere during a quiet day on 12 July 2009. It was found that the jet interaction was accompanied by strong localized compression and penetration of suprathermal magnetosheath plasma inside the dayside magnetosphere. The compression caused prominent magnetic variations with amplitudes up to 100 nT observed by ground-based magnetic networks SuperMAG and CARISMA. The magnetic variations were also visible in the geomagnetic Dst and AE indices. The jets also resulted in intense precipitation of the suprathermal ions with energies < 10 keV and energetic electrons with energies > 30 keV observed by low-altitude NOAA/POES satellites in a wide longitudinal range. The precipitations produced enhancements of ionization with an amplitude of ~1 TECU (~30% in relative units) and intensification of the ionospheric E and F1 layers as observed in the FORMOSAT-3/COSMIC misson. The enhanced ionization in the upper atmosphere might affect radio communication and navigation in the high-latitude regions. These results also provide new insight into the contribution of magnetospheric forcing to day-to-day ionospheric variability.
On Fuzzy Implications Derived from General Overlap Functions and Their Relation to Other Classes
Authors: Pinheiro Jocivania , Santos Helida , Dimuro Graçaliz P. , Bedregal Benjamin , Santiago Regivan H. N. , Fernandez Javier , Bustince Humberto
Published: December 2022

There are distinct techniques to generate fuzzy implication functions. Despite most of them using the combination of associative aggregators and fuzzy negations, other connectives such as (general) overlap/grouping functions may be a better strategy. Since these possibly non-associative operators have been successfully used in many applications, such as decision making, classification and image processing, the idea of this work is to continue previous studies related to fuzzy implication functions derived from general overlap functions. In order to obtain a more general and flexible context, we extend the class of implications derived by fuzzy negations and t-norms, replacing the latter by general overlap functions, obtaining the so-called (GO,N)-implication functions. We also investigate their properties, the aggregation of (GO,N)-implication functions, their characterization and the intersections with other classes of fuzzy implication functions.
Pre-Emptive-Weights Goal-Programming for a Multi-Attribute Decision-Making Problem with Positive Correlation among Finite Criteria
Authors: Chen Juin-Han , Tang Hui-Chin
Published: December 2022

This paper analyzes the various properties of the positively correlated weights related to the subset of finite criteria in a multi-attribute decision-making problem. Given a finite number of criteria, the exact constraints of the positively correlated weights related to the subset of criteria are presented. Introducing the non-Archimedean number, the associated bounded polyhedral-set is shown. The number of the extreme points in the bounded polyhedral-set will increase as the number of criteria increase. Applying the proposed efficient extreme-point method, the pre-emptive-weights-goal-programming optimal solution is shown. These theoretical global-maximum values of the positively correlated weights related to the subset of finite criteria are useful for practical applications.
How Micelles Influence the Optical Limiting Properties of Zinc Porphyrins and J-Aggregates for Picosecond Pulse Trains
Authors: Miao Quan , Sun Erping , Xu Yan
Published: December 2022

In this work, we studied nonlinear dynamics and optical limiting (OL) effects of pulse trains in zinc porphyrins meso-tetrakis methylpyridiniumyl (Zn2+TMPyP) and meso-tetrakis sulfonatophenyl (Zn2+TPPS) and porphyrin J-aggregates. The environments of zinc porphyrins were selected as aqueous solutions and micelles of sodium dodecyl sulfate (SDS) and cetyltrimethyl ammonium bromide (CTAB). Our numerical results show that both Zn2+TMPyP and Zn2+TPPS are good optical limiters in all solutions. Zn2+TPPS in aqueous solutions shows the best OL effect. Micelles of SDS and CTAB produced less OL effects than the aqueous solutions. The main reason lies in the first excited singlet state and intersystem crossing depending on the electronic structures in different environments.
On Classes of Non-Carathéodory Functions Associated with a Family of Functions Starlike in the Direction of the Real Axis
Authors: Karthikeyan Kadhavoor R. , Cho Nak Eun , Murugusundaramoorthy Gangadharan
Published: December 2022

In this paper, we introduce a new class of analytic functions subordinated by functions which is not Carathéodory. We have obtained some interesting subordination properties, inclusion and integral representation of the defined function class. Several corollaries are presented to highlight the applications of our main results.
Hyers Stability in Generalized Intuitionistic P-Pseudo Fuzzy 2-Normed Spaces
Authors: Movahednia Ehsan , De la Sen Manuel
Published: December 2022

In this article, we defined the generalized intuitionistic P-pseudo fuzzy 2-normed spaces and investigated the Hyers stability of m-mappings in this space. The m-mappings are interesting functional equations; these functional equations are additive for m = 1, quadratic for m = 2, cubic for m = 3, and quartic for m = 4. We have investigated the stability of four types of functional equations in generalized intuitionistic P-pseudo fuzzy 2-normed spaces by the fixed point method.
Influence of Breathing and Swelling on the Jelly-Roll Case Gap of Cylindrical Lithium-Ion Battery Cells
Authors: Spielbauer Markus , Steinhardt Marco , Singer Jan , Aufschläger Andreas , Bohlen Oliver , Jossen Andreas
Published: December 2022

Cylindrical 18650 and 21700 lithium-ion batteries are produced with small gaps between the jelly roll and the case. The size of these gaps and the mechanical attachment of the jelly roll to the case can have a significant impact on the thermal and mechanical properties of cells. To investigate the influence of the state of charge (SOC) and state of health (SOH) on the size of the gap, computed tomography (CT) and gray-value analysis was conducted with various cell types at 0% and 100% SOC and after cycling. The results show a significant influence of the SOC on the gap for new cells and a substantial reduction in the gap during the first cycles.
An Efficient Approach to Predict Eye Diseases from Symptoms Using Machine Learning and Ranker-Based Feature Selection Methods
Authors: Marouf Ahmed Al , Mottalib Md Mozaharul , Alhajj Reda , Rokne Jon , Jafarullah Omar
Published: December 2022

The eye is generally considered to be the most important sensory organ of humans. Diseases and other degenerative conditions of the eye are therefore of great concern as they affect the function of this vital organ. With proper early diagnosis by experts and with optimal use of medicines and surgical techniques, these diseases or conditions can in many cases be either cured or greatly mitigated. Experts that perform the diagnosis are in high demand and their services are expensive, hence the appropriate identification of the cause of vision problems is either postponed or not done at all such that corrective measures are either not done or done too late. An efficient model to predict eye diseases using machine learning (ML) and ranker-based feature selection (r-FS) methods is therefore proposed which will aid in obtaining a correct diagnosis. The aim of this model is to automatically predict one or more of five common eye diseases namely, Cataracts (CT), Acute Angle-Closure Glaucoma (AACG), Primary Congenital Glaucoma (PCG), Exophthalmos or Bulging Eyes (BE) and Ocular Hypertension (OH). We have used efficient data collection methods, data annotations by professional ophthalmologists, applied five different feature selection methods, two types of data splitting techniques (train-test and stratified k-fold cross validation), and applied nine ML methods for the overall prediction approach. While applying ML methods, we have chosen suitable classic ML methods, such as Decision Tree (DT), Random Forest (RF), Naive Bayes (NB), AdaBoost (AB), Logistic Regression (LR), k-Nearest Neighbour (k-NN), Bagging (Bg), Boosting (BS) and Support Vector Machine (SVM). We have performed a symptomatic analysis of the prominent symptoms of each of the five eye diseases. The results of the analysis and comparison between methods are shown separately. While comparing the methods, we have adopted traditional performance indices, such as accuracy, precision, sensitivity, F1-Score, etc. Finally, SVM outperformed other models obtaining the highest accuracy of 99.11% for 10-fold cross-validation and LR obtained 98.58% for the split ratio of 80:20.
COI Haplotyping and Comparative Microbiomics of the Peach Fruit Fly, an Emerging Pest of Egyptian Olive Orchards
Authors: Awad Mona , Ben Gharsa Haifa , ElKraly Omnia Abdullah , Leclerque Andreas , Elnagdy Sherif M.
Published: December 2022

The peach fruit fly, Bactrocera zonata (Tephritidae), is economically relevant as a highly polyphagous pest infesting over 50 host plants including commercial fruit and horticultural crops. As an invasive species, B. zonata was firmly established in Egypt and holds potential to spread further across the Mediterranean basin. The present study demonstrated that the peach fruit fly was found multiplying in olive orchards at two distant locations in Egypt. This is the first report of B. zonata developing in olives. COI barcoding has revealed evidence for high diversity across these peach fruit fly populations. These data are consistent with multiple rather than a single event leading to both peach fruit fly invasion to Egypt and its adaptation to olive. Comparative microbiomics data for B. zonata developing on different host plants were indicative for microbiome dynamics being involved in the adaptation to olive as a new niche with a potential adaptive role for Erwinia or Providencia bacteria. The possibility of symbiont transfer from the olive fruit fly to the peach fruit fly is discussed. Potentially host switch relevant bacterial symbionts might be preferred targets of symbiosis disruption strategies for integrated pest management or biological control of B. zonata.
Biology, Genetic Diversity, and Conservation of Wild Bees in Tree Fruit Orchards
Authors: Kline Olivia , Phan Ngoc T. , Porras Mitzy F. , Chavana Joshua , Little Coleman Z. , Stemet Lilia , Acharya Roshani S. , Biddinger David J. , Reddy Gadi V. P. , Rajotte Edwin G. , Joshi Neelendra K.
Published: December 2022

Different species of bees provide essential ecosystem services by pollinating various agricultural crops, including tree fruits. Many fruits and nuts depend on insect pollination, primarily by wild and managed bees. In different geographical regions where orchard crops are grown, fruit growers rely on wild bees in the farmscape and use orchard bees as alternative pollinators. Orchard crops such as apples, pears, plums, apricots, etc., are mass-flowering crops and attract many different bee species during their bloom period. Many bee species found in orchards emerge from overwintering as the fruit trees start flowering in spring, and the active duration of these bees aligns very closely with the blooming time of fruit trees. In addition, most of the bees in orchards are short-range foragers and tend to stay close to the fruit crops. However, the importance of orchard bee communities is not well understood, and many challenges in maintaining their populations remain. This comprehensive review paper summarizes the different types of bees commonly found in tree fruit orchards in the fruit-growing regions of the United States, their bio-ecology, and genetic diversity. Additionally, recommendations for the management of orchard bees, different strategies for protecting them from multiple stressors, and providing suitable on-farm nesting and floral resource habitats for propagation and conservation are discussed.
Assessing the Effects of Human Activities on Terrestrial Net Primary Productivity of Grasslands in Typical Ecologically Fragile Areas
Authors: Huang Qing , Zhang Fangyi , Zhang Qian , Jin Yunxiang , Lu Xuehe , Li Xiaoqing , Liu Jia
Published: December 2022

Global enhanced human activities have deeply influenced grassland ecosystems. Quantifying the impact of human activities on grasslands is crucial to understanding the grassland dynamic change mechanism, such as grassland degradation, and to establishing ecosystem protection measures. In this study, potential net primary productivity (PNPP), actual NPP (ANPP), and the forage harvest NPP (HNPP) were employed to establish the human activities index (HAI) to reveal the spatiotemporal changes of the effects of human activities on grassland ecosystems in eastern Inner Mongolia from 2000 to 2017, and to further explore the relationship between human activities and grassland degradation. The results showed that the total average PNPP, ANPP, and HNPP of grasslands in eastern Inner Mongolia were 187.2 Tg C yr−1, 152.3 Tg C yr−1, and 8.9 Tg C yr−1, respectively, during the period of 2000 to 2017. The HAI exhibited a clear decreasing trend during the study period, with annual mean values ranging from 0.75 to 0.47, which indicates that the NPP loss induced by human activities is weakening, and this trend is dominated by the difference between potential NPP and actual NPP. About 42.4% of the study area was non-degraded grassland, and the declining grassland degradation index (GDI) indicated that the degradation grade in eastern Inner Mongolia improved from moderate to light degradation. A positive relationship was found between HAI and GDI. This relationship was more significant in Xilingol League, which is a typical ecologically fragile area, than that in Xing’an League and Hulunbuir City.