bluuebunny/crossref_metadata_2025 huggingface dataset:
Simulating Slosh Induced Damping, with Application to Aircraft Wing-like Structures
Authors: Liu Wendi , Mahfoze Omar Ahmed , Longshaw Stephen M. , Skillen Alex , Emerson David R.
Published: August 2022

The added damping generated by liquid sloshing in a tank has been utilized in a number of civil applications, including aviation, to reduce the vibration of the system. As part of a wider EU H2020 project called SLOWD (Sloshing Wing Dynamics), the presented study performed numerical simulations on the slosh-induced damping of liquid in tanks that were under free decay oscillations and embedded in an aircraft wing-like structure. A new open-source partitioned fluid–structure interaction software framework is presented and employed for the numerical simulations. Periodic sloshing waves and violent vertical fluid motions are observed in the study. These demonstrate the effects of slosh-induced damping under different excitation amplitudes of the structure and a varying number of baffled regions within the tank. Various sloshing patterns caused by different combinations of the excitation amplitude and compartment numbers lead to different induced dampings of the free decay motion. We observed a distinctly non-monotonic function on the slosh damping when the initial excitation amplitude is small (i.e., 0.25), with a 59% reduction when we increase the number of baffled compartments from one to four, and a 153% increase when moving from one to eight compartments. This is due to the change in the sloshing wave frequency, resulting in a significant change in the impact of the fluid between the tank ceiling and the wave crests. When the initial excitation amplitude is large (i.e., 1.0), there is no significant change in the slosh-induced damping when changing the number of compartments in the tank, for the range of parameters considered, due to the highly turbulent fluid motion. This work is expected to form the basis of further, more detailed studies within the context of the SLOWD project and its ever-expanding experimental data output.
CNN-Based Model for Landslide Susceptibility Assessment from Multispectral Data
Authors: Renza Diego , Cárdenas Elsa Adriana , Martinez Estibaliz , Weber Serena Sarah
Published: August 2022

In this work, a new convolutional neural network architecture is proposed to evaluate the susceptibility to landslides. It is a supervised learning algorithm that has been trained from data whose labels have been obtained by applying a heuristic method that involves geological, geomorphological and land use information. The attributes contemplated the use of multispectral data and spectral indices, in addition to slope and DEM data. Although the cartographic unit in the proposed method is the pixel, the processing was performed at the patch level since it involved the use of spatial information around each pixel. Therefore, the proposed deep learning architecture is characterized by its simplicity and by applying both spatial and channel processing. The proposed method presents similar performance to state-of-the-art methods, achieving an F1 score higher than 88% on test data with low computational cost and pixel-level accuracy.
Contribution of Strength, Speed and Power Characteristics to Change of Direction Performance in Male Basketball Players
Authors: Papla Monika , Perenc Dawid , Zając Adam , Maszczyk Adam , Krzysztofik Michał
Published: August 2022

This study aimed to investigate the relationships between the modified t−agility test (MAT) time and muscular strength and power of lower limb extensors, adductors (AD), and abductors (AB). Nineteen male basketball players performed: linear sprint tests at 5 m and 20 m, MAT, countermovement (CMJ) and drop jump (DJ), leg press exercise, AD and AB hip maximum isometric strength measurements. All of them were left leg dominant. The correlation analysis showed a significant, moderate to very large negative relationship between MAT test time initiated to the left and height of CMJ and DJ (r = −0.69 and −0.54; p < 0.01, both), left (r = −0.56; p < 0.01) and right leg (r = −0.41; p < 0.05) AD, left leg AB (r = −0.48; p < 0.05) maximum isometric strength, left (r = −0.72; p < 0.01) and right (r = −0.64; p < 0.01) leg power output in leg press. In the case of the MAT test initiated on the right side first, the correlations were found between CMJ height (r = −0.46; p < 0.05), AD and AB maximum isometric strength of left (r = −0.58 and −0.84; p < 0.01, both) and right leg (r = −0.58 and −0.79; p < 0.01, both), and both legs power output in leg press (r = −0.66 for left and r = −0.59 for right; p < 0.01, both). The regression analyses showed that the prediction model of left leg press peak power, left leg AD maximum isometric strength, and CMJ height could explain up to 93% of the MAT test time initiated to the left first. The model, including left leg AB and AD maximum isometric strength, could explain up to 83% of the MAT test time initiated to the right side first. Findings from this study demonstrate that AB and AD maximum isometric muscle strength are highly related to MAT test performance, which is particularly important when the first turn is performed in the non−dominant direction in this test.
Double-Diffusive Effects on the Onset of Rayleigh-Benard Convection of Water-Based Nanofluids
Authors: Corcione Massimo , Quintino Alessandro
Published: August 2022

A numerical study on the Rayleigh–Benard convection in a shallow cavity filled with different metal-oxide water-based nanofluids is presented through a two-phase model, which accounts for the effects of the Brownian diffusion and thermophoresis, at variable properties with temperature. Numerical simulations are executed for different values of the average volume fraction of the nanoparticles, different aspect ratios of the enclosure, as well as for temperature difference between the bottom and the top walls. It is found that the dispersion of the nanoparticle into the base fluid increases the stability of the nanofluid layer, determining the conditions for the onset of convection also with reference to the confinement of the nanofluid.
Rwin-FPN++: Rwin Transformer with Feature Pyramid Network for Dense Scene Text Spotting
Authors: Zeng Chengbin , Liu Yi , Song Chunli
Published: August 2022

Scene text spotting has made tremendous progress with the in-depth research on deep convolutional neural networks (DCNN). Previous approaches mainly focus on the spotting of arbitrary-shaped scene text, on which it is difficult to achieve satisfactory results on dense scene text containing various instances of bending, occlusion, and lighting. To address this problem, we propose an approach called Rwin-FPN++, which incorporates the long-range dependency merit of the Rwin Transformer into the feature pyramid network (FPN) to effectively enhance the functionality and generalization of FPN. Specifically, we first propose the rotated windows-based Transformer (Rwin) to enhance the rotation-invariant performance of self-attention. Then, we attach the Rwin Transformer to each level on our feature pyramids to extract global self-attention contexts for each feature map produced by the FPN. Thirdly, we fuse these feature pyramids by upsampling to predict the score matrix and keypoints matrix of the text regions. Fourthly, a simple post-processing process is adopted to precisely merge the pixels in the score matrix and keypoints matrix and obtain the final segmentation results. Finally, we use the recurrent neural network to recognize each segmentation region and thus achieve the final spotting results. To evaluate the performance of our Rwin-FPN++ network, we construct a dense scene text dataset with various shapes and occlusion from the wiring of the terminal block of the substation panel cabinet. We train our Rwin-FPN++ network on public datasets and then evaluate the performance on our dense scene text dataset. Experiments demonstrate that our Rwin-FPN++ network can achieve an F-measure of 79% and outperform all other methods in F-measure by at least 2.8%. This is because our proposed method has better rotation invariance and long-range dependency merit.
Study on the Influence of Ultrasound Homogenisation on the Physical Properties of Vegan Ice Cream Mixes
Authors: Kot Anna , Kamińska-Dwórznicka Anna , Jakubczyk Ewa
Published: August 2022

This study investigated the effect of ultrasound homogenisation on the physical properties of vegan ice cream mixes. Samples were prepared based on vegan recipes with different sorts of stabilisers such as iota carrageenan and iota carrageenan’s acid and enzymatic hydrolysates. Ice cream mixes were compared for stability, particle size distribution, rheological properties and morphological structure. All mentioned analyses were conducted before and after 24 h of maturation at 4 °C. It was found that the ultrasound treatment decreased the size of particles and, in conjunction with the maturation stage, a significant reduction was visible (the lowest value was at 9.76 µm). The addition of the hydrolysates of iota carrageenan had a considerably better effect in reducing the size of particles than iota carrageenan. The range of TSI values was from 1.7 to 4.2. Additionally, two sorts of destabilisation occurred: sedimentation and coalescence, during the maturation of ice cream mixes, which was also visible in the images. According to the rheological properties, ice cream mixes, with the addition of stabilisers, showed non-Newtonian shear-thinning (pseudoplastic) behaviour. Moreover, the effect of ultrasound treatment on the consistency index was only pivotal for ice cream mixes with an addition of iota carrageenan and with enzymatic β-galactosidase hydrolysates of iota carrageenan.
Electromagnetic Force Induced Structural Vibration Analysis and Experiment of Brushless Direct Current Motors for Operating Speed Range
Authors: Cho Seunghyeon , Jeon Kyunghun , Lee Ki-Deok , Kim Chang-Wan
Published: August 2022

In this study, an electromagnetic force induced structural vibration for a brushless direct current (BLDC) motor with variable speed is performed using finite element analysis, as well as an experiment for operating speed range. The 3-D entire finite element model was used to predict the vibration characteristics for the operating speed range of a BLDC motor. To validate the finite element (FE) model, the modal analysis was compared with the results of a modal test. Then, for variable speed, electromagnetic force induced vibration characteristics for the range of operating speeds are predicted using the electromagnetic-structural vibration coupled analysis method. The predicted vibration characteristics are compared and validated with vibration experiment under the same operating conditions. Finally, it was found that the vibration characteristics predicted using the 3-D entire FE model can accurately reflect the actual vibration characteristics for variable speed.
Super-Operator Linear Equations and Their Applications to Quantum Antennas and Quantum Light Scattering
Authors: Slepyan Gregory , Boag Amir
Published: August 2022

In this paper, we develop a resolvent method for super-operator equations with applications in quantum optics. Our approach is based on the novel concept of a linear super-operator acting on the Hilbert subspace of vector or scalar linear operators satisfying physically reasonable commutation relations. The super-operator equations for the electromagnetic (EM) field operators are formulated for the problems of quantum antenna emission and quantum light scattering by a dielectric body. The general solution of super-operator equation is presented in terms of the classical resolvent. In contrast to the classical case, it includes the ancillary components associated with the quantum noise even in the absence of absorption. The reason for this lies in the energy exchange between different spatial regions with various bases for the field presentation (which looks like losses or gain from the point of view of the correspondent region). A number of examples (a two-element dipole antenna, a plane dielectric layer, and a dielectric cylinder with a circular cross section) which demonstrate the physical mechanism of the appearance of noise are considered. It is shown that antenna emission or scattering transforms the coherent properties of quantum light. This leads to a new way of controlling coherence in a direction-dependent manner, a feature that can be useful in various applications of quantum technologies, including quantum radars and lidars, and quantum antennas.
Event-Based Emergency Detection for Safe Drone
Authors: Kim Isaac , Kim Hyun-geun , Kim In-young , Ohn Sung-yup , Chi Sung-do
Published: August 2022

Quadrotor drones have rapidly gained interest recently. Numerous studies are underway for the commercial use of autonomous drones, and distribution businesses especially are taking serious reviews on drone-delivery services. However, there are still many concerns about urban drone operations. The risk of failures and accidents makes it difficult to provide drone-based services in the real world with ease. There have been many studies that introduced supplementary methods to handle drone failures and emergencies. However, we discovered the limitation of the existing methods. Most approaches were improving PID-based control algorithms, which is the dominant drone-control method. This type of low-level approach lacks situation awareness and the ability to handle unexpected situations. This study introduces an event-based control methodology that takes a high-level diagnosing approach that can implement situation awareness via a time-window. While low-level controllers are left to operate drones most of the time in normal situations, our controller operates at a higher level and detects unexpected behaviors and abnormal situations of the drone. We tested our method with real-time 3D computer simulation environments and in several cases, our method was able to detect emergencies that typical PID controllers were not able to handle. We were able to verify that our approach can provide enhanced double safety and better ensure safe drone operations. We hope our discovery can possibly contribute to the advance of real-world drone services in the near future.
Integrated Adaptive Steering Stability Control for Ground Vehicle with Actuator Saturations
Authors: Zhang Jinhua , Wang Mingyu
Published: August 2022

During a steering manoeuvre in a ground vehicle, both yaw motion and roll motion can occur simultaneously, and their dynamics can be coupled, as the roll motion is generalized directly from the tires’ lateral force under steering. Hence, it is of significance to analyze them as an integrated plant in the vehicle steering stability control problem. Furthermore, the actuator saturation of yaw control cannot be neglected, as vehicles often steer at a high velocity or on low-friction roads. In this paper, an integrated steering dynamics model is established considering the coupling between the roll motion and lateral motion, then a novel nonlinear adaptive controller is proposed to stabilize the steering motion considering the actuator saturation of yaw motion control. Simulation results indicate that the designed integrated controller is effective in improving the performance of both the yaw rate tracking error and ride comfort taking into account vehicle parameter uncertainties and actuator saturation; the steering stability of ground vehicles can consequently be guaranteed.
Hybrid Discrete Particle Swarm Optimization Algorithm with Genetic Operators for Target Coverage Problem in Directional Wireless Sensor Networks
Authors: Fan Yu-An , Liang Chiu-Kuo
Published: August 2022

For a sensing network comprising multiple directional sensors, maximizing the number of covered targets but minimizing sensor energy use is a challenging problem. Directional sensors that can rotate to modify their sensing directions can be used to increase coverage and decrease the number of activated sensors. Solving this target coverage problem requires creating an optimized schedule where (1) the number of covered targets is maximized and (2) the number of activated directional sensors is minimized. Herein, we used a discrete particle swarm optimization algorithm (DPSO) combined with genetic operators of the genetic algorithm (GA) to compute feasible and quasioptimal schedules for directional sensors and to determine the sensing orientations among the directional sensors. We simulated the hybrid DPSO with GA operators and compared its performance to a conventional greedy algorithm and two evolutionary algorithms, GA and DPSO. Our findings show that the hybrid scheme outperforms the greedy, GA, and DPSO algorithms up to 45%, 5%, and 9%, respectively, in terms of maximization of covered targets and minimization of active sensors under different perspectives. Finally, the simulation results revealed that the hybrid DPSO with GA produced schedules and orientations consistently superior to those produced when only DPSO was used, those produced when only GA was used, and those produced when the conventional greedy algorithm was used.
Cloud Gaming Video Coding Optimization Based on Camera Motion-Guided Reference Frame Enhancement
Authors: Wang Yifan , Wang Hao , Wang Kaijie , Zhang Wei
Published: August 2022

Recent years have witnessed tremendous advances in clouding gaming. To alleviate the bandwidth pressure due to transmissions of high-quality cloud gaming videos, this paper optimized existing video codecs with deep learning networks to reduce the bitrate consumption of cloud gaming videos. Specifically, a camera motion-guided network, i.e., CMGNet, was proposed for the reference frame enhancement, leveraging the camera motion information of cloud gaming videos and the reconstructed frames in the reference frame list. The obtained high-quality reference frame was then added to the reference frame list to improve the compression efficiency. The decoder side performs the same operation to generate the reconstructed frames using the updated reference frame list. In the CMGNet, camera motions were used as guidance to estimate the frame motion and weight masks to achieve more accurate frame alignment and fusion, respectively. As a result, the quality of the reference frame was significantly enhanced and thus being more suitable as a prediction candidate for the target frame. Experimental results demonstrate the effectiveness of the proposed algorithm, which achieves 4.91% BD-rate reduction on average. Moreover, a cloud gaming video dataset with camera motion data was made available to promote research on game video compression.
Model-Assisted Reduced-Order ESO Based Command Filtered Tracking Control of Flexible-Joint Manipulators with Matched and Mismatched Disturbances
Authors: Pan Changzhong , Fei Xiangyin , Xiao Jinsen , Xiong Peiyin , Li Zhijing , Huang Hao
Published: August 2022

Flexible-joint manipulators (FJMs) have been widely used in the fields of industry, agriculture, medical service, aerospace, etc. However, the FJMs in practical applications inevitably encounter various uncertainties including matched and mismatched disturbances. In this paper, we consider the high precision tracking control problem of FJMs in the presence of unknown lumped matched and mismatched disturbances. An efficient model-assisted composite control approach is proposed by integrating two reduced-order extended state observers (RESOs), a second-order command filtered backstepping (SCFB) technique and an error compensation dynamic system. Unlike some existing methods, the RESOs constructed with partial known model information are capable of estimating and compensating the matched and mismatched disturbances simultaneously. In addition, by employing the SCFB with an error compensation system, the proposed approach can not only overcome the problem of “explosion of complexity” inherent in backstepping, but also reduce the filtering errors arising from the command filters. The stability of the resulting control system and the convergence of error signals are guaranteed by Lyapunov stability theory. Comparative simulations are conducted for a single-link FJM with both matched and mismatched disturbances, and the results show that the proposed approach achieves a better tracking performance, i.e., compared with conventional backstepping method and adaptive fuzzy command filtered control method, the tracking accuracy is improved by 99.5% and 99.2%, respectively.
Online Peer-Tutoring for Programming Languages Based on Programming Ability and Teaching Skill
Authors: Kuo Yu-Chen , Yao Ching-Bang , Wu Zhe-Yu
Published: August 2022

Web-based cooperative learning could enhance students’ learning motivation; however, learning activities in this process are rather confusing because of the lack of structured learning strategies, resulting in unfavorable learning achievements. With the peer tutoring learning environment to encourage students’ mutual learning and development, an online peer-tutoring platform for programming languages with peer mentoring is established herein for one-to-one peer tutoring activities. With students with higher learning ability as tutors and those with lower learning ability as tutees, tutors can provide online peer tutoring for programming languages via demonstrations and flowcharts to discuss the effects of using different teaching methods for learning activities on the learning achievement of tutees. Based on these teaching methods for peer learning, 52 undergraduates were divided into experimental groups A and B; each group was further divided into peer mentoring group and non-peer mentoring group based on the ability levels. The results show that learning activities with the online peer-tutoring platform for programming languages could assist both groups in enhancing their learning achievement and ensure positive attitudes toward programming languages. In the analyses, the peer mentoring group was preferable in peer tutoring for programming languages with demonstration, while the non-peer mentoring group did not appear significant.
Design of an Interface Layer Using CPW between an Array Antenna and TRM in X-Band Radar Systems to Minimize Leakage Fields and Improve Transmission Characteristics
Authors: Cho Jeongmin , Jang Doyoung , Lee Chang-Hyun , Choo Hosung
Published: August 2022

In this paper, we propose an interface layer using the coplanar waveguide (CPW) between an array antenna and transmitting receiver modules (TRMs) for X-band military ship radar systems. To improve transmission characteristics, the interface layer with the CPW has three transition parts: Transition part A is between the sub miniature push-on (SMP) connector and the interface layer. Transition part B is the CPW in which the thickness gradually increases. Transition part C is for connecting the interface layer and the antenna. The measured reflection and transmission coefficients of the fabricated interface layer are −22.4 dB and −0.82 dB, respectively. To verify the proposed interface layer, we then apply the layer to a 2 × 2 X-band array antenna and measure the array antenna characteristics, such as reflection coefficients, array antenna gain, and half-power beam widths (HPBWs). The measured reflection coefficient is under −10 dB from 8.6 GHz to 10.2 GHz, and the bore-sight array gain of the 2 × 2 array antenna is 10.5 dBi at 9.5 GHz. In addition, the measured HPBWs under the same conditions are 47.8° and 39.1° in the zx- and zy-planes, respectively. The results demonstrate that the proposed interface layer using the CPW is suitable for X-band radar systems.
Lazy Aggregation for Heterogeneous Federated Learning
Authors: Xu Gang , Kong De-Lun , Chen Xiu-Bo , Liu Xin
Published: August 2022

Federated learning (FL) is a distributed neural network training paradigm with privacy protection. With the premise of ensuring that local data isn’t leaked, multi-device cooperation trains the model and improves its normalization. Unlike centralized training, FL is susceptible to heterogeneous data, biased gradient estimations hinder convergence of the global model, and traditional sampling techniques cannot apply FL due to privacy constraints. Therefore, this paper proposes a novel FL framework, federated lazy aggregation (FedLA), which reduces aggregation frequency to obtain high-quality gradients and improve robustness in non-IID. To judge the aggregating timings, the change rate of the models’ weight divergence (WDR) is introduced to FL. Furthermore, the collected gradients also facilitate FL walking out of the saddle point without extra communications. The cross-device momentum (CDM) mechanism could significantly improve the upper limit performance of the global model in non-IID. We evaluate the performance of several popular algorithms, including FedLA and FedLA with momentum (FedLAM). The results show that FedLAM achieves the best performance in most scenarios and the performance of the global model can also be improved in IID scenarios.
Multi-Objective Hybrid Flower Pollination Resource Consolidation Scheme for Large Cloud Data Centres
Authors: Usman Mohammed Joda , Gabralla Lubna A. , Aliyu Ahmed , Gabi Danlami , Chiroma Haruna
Published: August 2022

Cloud Computing has rapidly emerged as a successful paradigm for providing Information and Communication Technology (ICT) infrastructure. Resource allocation is used to execute user applications in the form of requests for consolidated resources in order to minimize energy consumption and violation of the Service Level Agreement (SLA) for large-scale data centers resource utilization. The energy consumption is usually caused due to local entrapment and violation of SLA during resource assigning and execution. Several researchers have proposed solutions to reduce local entrapments and violations of SLA, to minimize the energy consumption of the entire data center. However, strategies employed in their solutions face entrapment in either local searches or at the global search level with a certain level of SLA violation. In this light, a Multi-Objective Hybrid Flower Pollination Resource Consolidation (MOH-FPRC) scheme for efficient and optimal resource consolidation of data center resources is put forward. The Local Neighborhood Search (LNS) algorithm has been employed for addressing entrapment at the local search level, while the prominent flower pollination algorithm is used to solve the problem of entrapment at the global search level. This, in turn, reduces the energy consumption of the data centers. In addition, clustering strategies have been introduced with a robust migration mechanism to minimize the violation of SLA while also satisfying minimum energy consumption. The simulation results using the MultiRecCloudSim simulator have shown that our proposed MOH-FPRC demonstrates an improved performance on the data center energy consumption, resource utilization, and SLA violation with a 20.5% decrease, 23.9% increase, and 13.5% reduction, respectively, as compared with the benchmarked algorithms. The proposed scheme has proven its efficiency in minimizing energy consumption while at the same time improving the data center resource allocation with minimum SLA violations.
Ecosystem Services: A Systematic Literature Review and Future Dimension in Freshwater Ecosystems
Authors: Deeksha  , Shukla Anoop Kumar
Published: August 2022

Ecosystem services are part and parcel of human lives. It is of paramount importance to understand the interaction between these ecosystem services, as they are directly related to human life. In the modern era, quantification of ecosystem services (ES) is playing an important role in the proper understanding and efficient management of social–ecological systems. Even though a significant amount of literature is available to present on the topic, there is a need to build an adequate amount of knowledge repository. Hence, a systematic literature review method is used, in which research question and searching stages are defined. This review study is conducted on ecosystem services and remote-sensing-related keywords in the Scopus database. After a systematic analysis of the papers retrieved from the Elsevier, Scopus database, MDPI, and open source, a total of 140 primary articles were categorized according to their relationship with other ecosystem services, land use, land cover, and planning management. Major issue findings and important aspects have been analyzed and reported in each category. With this analysis and developments in the existing literature, we have potential areas for future research. Findings pointed out that regional or local-level ecosystem services-related work is immensely important, and a hotspot of current research aiming to understand the variability and spatiotemporal dynamics in terrestrial and aquatic ecosystems.
Triskeles and Symmetries of Mean Global Sea-Level Pressure
Authors: Lopes Fernando , Courtillot Vincent , Le Mouël Jean-Louis
Published: August 2022

The evolution of mean sea-level atmospheric pressure since 1850 is analyzed using iterative singular spectrum analysis. Maps of the main components (the trends) reveal striking symmetries of order 3 and 4. The Northern Hemisphere (NH) displays a set of three positive features, forming an almost perfect equilateral triangle. The Southern Hemisphere (SH) displays a set of three positive features arranged as an isosceles triangle, with a possible fourth (weaker) feature. This geometry can be modeled as the Taylor–Couette flow of mode 3 (NH) or 4 (SH). The remarkable regularity and three-order symmetry of the NH triskeles occurs despite the lack of cylindrical symmetry of the northern continents. The stronger intensity and larger size of features in the SH is linked to the presence of the annular Antarctic Oscillation (AAO), which monitors the periodic reinforcement and weakening of the circumpolar vortex; it is a stationary mode. These components represent 70% of the variance in total pressure since 1850 and are stable in both time and space. In the remaining 30% of the variance, we have extracted quasi-periodical components with periods larger than 1 year (2% of the variance) and a harmonic sequence of the 1-year period (20% of the variance).
The Impact of Low-Carbon City Pilot Policies on Air Quality: Quasi-Natural Experimental Evidence from China
Authors: Zhang Jingran , Gao Lei , Wang Wukui , Deng Zhenzhu , Zhang Xi
Published: August 2022

Low-carbon cities have become a new trend in regional development around the world. Whether they can improve the environment in China, especially the air quality, remains to be tested. In this paper we take low-carbon city construction as a quasi-natural experiment and empirically test the net effects, influencing factors, and dynamic effects of low-carbon city construction on air quality by constructing a multistage propensity score matching and Difference-in-Differences model. After a series of robustness tests, the following conclusions are drawn: first, low-carbon city construction reduces the regional Air Quality Index, inhalable particulate matter, fine particulate matter, and NO2 concentrations. Among them, the construction effect in 2017 was the most significant. Therefore, it is necessary to continue to promote low-carbon city policies and accurately identify different types of air pollutants to improve the overall effectiveness of low-carbon city policies. Second, temperature, humidity, wind level, and other meteorological factors, as well as gross domestic product for the proportion of secondary industry, will affect air quality. Therefore, it is necessary to comprehensively consider meteorological, economic, social, and other influencing factors in an early stage of the construction of the next batch of low-carbon cities, so as to avoid falling into the trap of “building first and managing later”. Third, the impact of secondary industry on air quality is significantly greater than that of tertiary industry. Therefore, the upgrading of industrial structure promoted by low-carbon city policy is effective in improving air quality. Fourth, the construction of low-carbon cities in western China has the most significant impact on air quality improvement. Therefore, the joint prevention and control mechanism of air pollution control in urban agglomeration should be established.
Preliminary Application of a Multi-Physical Ensemble Transform Kalman Filter in Cloud and Precipitation Forecasts
Authors: Mei Qin , Wang Jia , Zhi Xiefei , Zhang Hanbin , Gao Ya , Yi Chuanxiang , Yang Yang
Published: August 2022

In this study, based on the retrieval data from the Fengyun geostationary meteorological satellite and the Tropical Rainfall Measuring Mission satellite, a large-scale precipitation case in eastern China is selected to address the systematic deviations of deterministic forecasts for clouds and precipitation. A multi-physical ensemble transform Kalman filter (ETKF) is constructed in this research based on the Weather Research and Forecast model version 3.6, and its forecasting ability in terms of cloud-top height and temperature, hydrometeors, and precipitation is evaluated by quantitatively comparing three microphysical parameterization schemes (Lin, Morrison, and CAM5.1 schemes) and their corresponding multi-physical ensemble mean. The results show that the Lin, Morrison, and CAM5.1 schemes all underestimate the range of cloud systems and have different advantages and disadvantages in forecasting different elements, while the forecasting improvement of the multi-physical ensemble mean is limited. However, the multi-physical ETKF can effectively improve the forecast accuracy of the cloud system range. In addition, the multi-physical ETKF has the advantages of different physical parameterization schemes, which can dramatically improve the forecast accuracy of cloud hydrometeors, reduce precipitation forecast errors, and improve threat scores.
Long-Term Variability of Summer Temperature in the Southern Part of South America—Is There a Connection with Changes in Solar Activity?
Authors: Ogurtsov Maxim
Published: August 2022

Reconstruction of the summer (December–February) temperature of the southern part of the South American continent was studied in the time interval 900–1995. Significant temporal variations with periods of ca 520 years, ca 220 years, and 90–150 years have been found. Since bicentennial and century-type climatic oscillations can be a manifestation of the respective solar cycles of Suess and Gleissberg, the correlation between the corresponding climatic and solar periodicities was investigated. Data on the concentration of cosmogenic beryllium in the ice of the South Pole, solar modulation potential, and total solar irradiance, reconstructed using cosmogenic isotopes, were used as indicators of activity of the Sun. It turned out that there was no correlation between bicentennial and century-long variations in solar activity and temperature in the southern part of the South American continent. On the other hand, a fairly significant (c.l. 0.92–0.94) correlation between the multi-centennial (periods of 393–548 years) temperature variations and solar proxies was found. Based on these results, it is difficult to draw an unambiguous conclusion about the solar forcing on the climate of South America. It is more important that the results obtained confirm the existence of natural variations in the Earth’s climate with periods close to solar cycles but independent of changes in solar activity. The presence of such periodicities can seriously complicate the identification of the solar influence on the climate, which should be taken into account in further solar-climatic studies.
Spatiotemporal Variations of XCH4 across China during 2003–2021 Based on Observations from Multiple Satellites
Authors: Qin Jiayao , Zhang Xiuying , Zhang Linjing , Cheng Miaomiao , Lu Xuehe
Published: August 2022

Atmospheric methane (CH4) is an important greenhouse gas that can reflect variations of CH4 emissions and sinks. This study aimed to detect spatial and temporal variations of atmospheric CH4 concentrations in China during 2003–2021 based on CH4 column-averaged dry-air mole fraction (XCH4) products from three satellites, namely, Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), Greenhouse Gases Observing Satellite (GOSAT), and Copernicus Sentinel-5 Precursor (S5P). The results revealed that XCH4 observed from three satellites showed high agreement in spatiotemporal variations and demonstrated good consistency with ground station measurements. The correlation coefficients (r) between the three satellites were 0.72 and 0.73, and the correlation coefficients for the ground stations were 0.79, 0.66, 0.03, 0.21, 0.70, and 0.80. The spatial distribution of XCH4 in China was generally high in the east and low in the west and close to that of CH4 emissions, indicating that CH4 emission sources dominated the spatial variations of atmospheric XCH4. From 2003 to 2006, XCH4 remained stable with an annual growth rate of 0.51 ppb·yr−1 and then abruptly increased with an overall growth rate of 6.96 ppb·yr−1. There were obvious seasonal changes in XCH4, with peaks in autumn and summer and nadir in winter and spring. These seasonal variations of XCH4 were related to CH4 emissions from rice planting. Rice cultivation areas generally had high XCH4 concentrations, and the growth cycle of rice plants significantly contributed to seasonal variations of XCH4 in the main rice planting areas. These results provide scientific data that could encourage decision-makers to enact policies and processes to reduce methane emissions.
Green Supplier Selection in an Uncertain Environment in Agriculture Using a Hybrid MCDM Model: Z-Numbers–Fuzzy LMAW–Fuzzy CRADIS Model
Authors: Puška Adis , Božanić Darko , Nedeljković Miroslav , Janošević Miljojko
Published: August 2022

The goal of this research was to find a selection of green suppliers (GSS) that will, in the best way, help agricultural producers to apply green agricultural production using uncertainty in decision making. In order to avoid the possibility of uncertainty in the expert decision making, Z-numbers were used together with the fuzzy LMAW (Logarithm Methodology of Additive Weights) method and fuzzy CRADIS (Compromise Ranking of Alternatives from Distance to Ideal Solution) method. By applying Z-numbers and the fuzzy LMAW method, the weighting coefficients of the criteria were determined, where the experts, in addition to the criteria ratings, also defined the degrees of certainty in the criteria ratings they gave. The obtained results indicated that the criteria related to price and qualities are the most important during the selection process. To select the best alternative, the CRADIS method modified with Z-numbers and fuzzy numbers was applied. The results obtained by applying this method showed that suppliers A2 and A3 have the best characteristics and are the first choice for the procurement of raw and production materials. As part of the paper, the validation of the results and the sensitivity analysis of the model were carried out by conducting the procedure of comparing the obtained results with the results obtained by other MCDM methods and changing the weighting coefficients of the criteria. These analyses indicated that the model presented provides stable results. The conducted research showed how Z-numbers can be used to reduce uncertainty in decision making and how Z-numbers can be used with other fuzzy methods to perform GSS.
Remarks on Radial Solutions of a Parabolic Gelfand-Type Equation
Authors: Miyasita Tosiya
Published: August 2022

We consider an equation with exponential nonlinearity under the Dirichlet boundary condition. For a one- or two-dimensional domain, a global solution has been obtained. In this paper, to extend the result to a higher dimensional case, we concentrate on the radial solutions in an annulus. First, we construct a time-local solution with an abstract theory of differential equations. Next, we show that decreasing energy exists in this problem. Finally, we establish a global solution for the sufficiently small initial value and parameter by Sobolev embedding and Poincaré inequalities together with some technical estimates. Moreover, when we take the smaller parameter, we prove that the global solution tends to zero as time goes to infinity.
Machine Learning-Based Modelling and Meta-Heuristic-Based Optimization of Specific Tool Wear and Surface Roughness in the Milling Process
Authors: Pedrammehr Siamak , Hejazian Mahsa , Chalak Qazani Mohammad Reza , Parvaz Hadi , Pakzad Sajjad , Ettefagh Mir Mohammad , Suhail Adeel H.
Published: August 2022

The purpose of this research is to investigate different milling parameters for optimization to achieve the maximum rate of material removal with the minimum tool wear and surface roughness. In this study, a tool wear factor is specified to investigate tool wear parameters and the amount of material removed during machining, simultaneously. The second output parameter is surface roughness. The DOE technique is used to design the experiments and applied to the milling machine. The practical data is used to develop different mathematical models. In addition, a single-objective genetic algorithm (GA) is applied to numerate the optimal hyperparameters of the proposed adaptive network-based fuzzy inference system (ANFIS) to achieve the best possible efficiency. Afterwards, the multi-objective GA is employed to extract the optimum cutting parameters to reach the specified tool wear and the least surface roughness. The proposed method is developed under MATLAB using the practically extracted dataset and neural network. The optimization results revealed that optimum values for feed rate, cutting speed, and depth of cut vary from 252.6 to 256.9 (m/min), 0.1005 to 0.1431 (mm/rev tooth), and from 1.2735 to 1.3108 (mm), respectively.
Microglia Contributes to BAF-312 Effects on Blood–Brain Barrier Stability
Authors: Spampinato Simona Federica , Costantino Giuseppe , Merlo Sara , Canonico Pier Luigi , Sortino Maria Angela
Published: August 2022

Microglia, together with astrocytes and pericytes, cooperate to ensure blood–brain barrier (BBB) stability, modulating endothelial responses to inflammatory insults. Agonists of the sphingosine 1 phosphate (S1P) receptors, such as siponimod (BAF-312), are important pharmacological tools in multiple sclerosis and other inflammatory diseases. Modulation of S1P receptors may result in a reduced inflammatory response and increased BBB stability. An in vitro BBB model was reproduced using human-derived endothelial cells, astrocytes and microglia. Co-cultures were exposed to inflammatory cytokines (TNFα, 10 UI and IFNγ, 5 UI) in the presence of BAF-312 (100 nM), and the BBB properties and microglia role were evaluated. The drug facilitated microglial migration towards endothelial/astrocyte co-cultures, involving the activity of the metalloprotease 2 (MMP2). Microglia actively cooperated with astrocytes in the maintenance of endothelial barrier stability: in the triple co-culture, selective treatment of microglial cells with BAF-312 significantly prevented cytokines’ effects on the endothelial barrier. In conclusion, BAF-312, modulating S1P receptors in microglia, may contribute to the reinforcement of the endothelial barrier at the BBB, suggesting an additional effect of the drug in the treatment of multiple sclerosis.
Comparative Analyses of Bioactive Compounds in Inonotus obliquus Conks Growing on Alnus and Betula
Authors: Drenkhan Rein , Kaldmäe Hedi , Silm Maidu , Adamson Kalev , Bleive Uko , Aluvee Alar , Erik Mart , Raal Ain
Published: August 2022

Inonotus obliquus grows in the Northern Hemisphere on some living broadleaved tree species as a pathogen, causing stem rot. In Estonia, the fungus is well known in the Betula species but can also be found on Alnus. Sterile conks of I. obliquus contain different bioactive compounds, but the quantitative and comparative research of these compounds in conks on different host species is limited. In the current work, I. obliquus was isolated and, evidently, determined from Alnus incana (L.) Moench., Alnus glutinosa (L.) Gaertn., and Betula pendula Roth, and the content of bioactive compounds in conks on these hosts were analysed. All the analysed conks sampled from A. incana and B. pendula contained betulin that varied from 111 to 159 µg/g. A significantly (p < 0.05) higher betulinic acid content was found in conks sampled from A. incana when compared with B. pendula: 474–635 and 20–132 µg/g, respectively. However, the conks from Betula were richer in total polyphenols, flavonols, and glucans. The content of inotodiol was quite similar in the conks from A. incana (7455–8961 µg/g) and B. pendula (7881–9057 µg/g). Also, no significant differences in the lanosterol content were found between the samples from these two tree species. To the best of our knowledge, this study is the first investigation of the chemical composition of I. obliquus parasitizing on Alnus. The results demonstrate that the bioactive compounds are promising in conks of I. obliquus growing not only on Betula but also on the Alnus species. It supports the opportunity to cultivate I. obliquus, also on the Alnus species, thus increasing the economic value of growing this tree species in forestry.
Tailoring of TiAl6V4 Surface Nanostructure for Enhanced In Vitro Osteoblast Response via Gas/Solid (Non-Line-of-Sight) Oxidation/Reduction Reactions
Authors: Ogura Naotaka , Berger Michael B. , Srivas Pavan , Hwang Sunghwan , Li Jiaqi , Cohen David Joshua , Schwartz Zvi , Boyan Barbara D. , Sandhage Kenneth H.
Published: August 2022

An aging global population is accelerating the need for better, longer-lasting orthopaedic and dental implants. Additive manufacturing can provide patient-specific, titanium-alloy-based implants with tailored, three-dimensional, bone-like architecture. Studies using two-dimensional substrates have demonstrated that osteoblastic differentiation of bone marrow stromal cells (MSCs) is enhanced on surfaces possessing hierarchical macro/micro/nano-scale roughness that mimics the topography of osteoclast resorption pits on the bone surface. Conventional machined implants with these surfaces exhibit successful osseointegration, but the complex architectures produced by 3D printing make consistent nanoscale surface texturing difficult to achieve, and current line-of-sight methods used to roughen titanium alloy surfaces cannot reach all internal surfaces. Here, we demonstrate a new, non-line-of-sight, gas/solid-reaction-based process capable of generating well-controlled nanotopographies on all open (gas-exposed) surfaces of titanium alloy implants. Dense 3D-printed titanium-aluminum-vanadium (TiAl6V4) substrates were used to evaluate the evolution of surface nanostructure for development of this process. Substrates were either polished to be smooth (for easier evaluation of surface nanostructure evolution) or grit-blasted and acid-etched to present a microrough biomimetic topography. An ultrathin (90 ± 16 nm) conformal, titania-based surface layer was first formed by thermal oxidation (600 °C, 6 h, air). A calciothermic reduction (CaR) reaction (700 °C, 1 h) was then used to convert the surface titania (TiO2) into thin layers of calcia (CaO, 77 ± 16 nm) and titanium (Ti, 51 ± 20 nm). Selective dissolution of the CaO layer (3 M acetic acid, 40 min) then yielded a thin nanoporous/nanorough Ti-based surface layer. The changes in surface nanostructure/chemistry after each step were confirmed by scanning and transmission electron microscopies with energy-dispersive X-ray analysis, X-ray diffraction, selected area electron diffraction, atomic force microscopy, and mass change analyses. In vitro studies indicated that human MSCs on CaR-modified microrough surfaces exhibited increased protein expression associated with osteoblast differentiation and promoted osteogenesis compared to unmodified microrough surfaces (increases of 387% in osteopontin, 210% in osteocalcin, 282% in bone morphogenic protein 2, 150% in bone morphogenic protein 4, 265% in osteoprotegerin, and 191% in vascular endothelial growth factor). This work suggests that this CaR-based technique can provide biomimetic topography on all biologically facing surfaces of complex, porous, additively manufactured TiAl6V4 implants.