bluuebunny/crossref_metadata_2025 huggingface dataset:
Sandwich Multi-Material 3D-Printed Polymers: Influence of Aging on the Impact and Flexure Resistances
Authors: Pinho Ana C. , Piedade Ana P.
Published: November 2021

With the advances in new materials, equipment, and processes, additive manufacturing (AM) has gained increased importance for producing the final parts that are used in several industrial areas, such as automotive, aeronautics, and health. The constant development of 3D-printing equipment allows for printing multi-material systems as sandwich specimens using, for example, double-nozzle configurations. The present study aimed to compare the mechanical behavior of multi-material specimens that were produced using a double-nozzle 3D printer. The materials that were included in this study were the copolymer acrylonitrile-butadiene-styrene (ABS), high-impact polystyrene (HIPS), poly(methyl methacrylate) (PMMA), and thermoplastic polyurethane (TPU). The configuration of the sandwich structures consisted of a core of TPU and the outer skins made of one of the other three materials. The mechanical behavior was evaluated through three-point bending (3PB) and transverse impact tests and compared with mono-material printed specimens. The effect of aging in artificial saliva was evaluated for all the processed materials. The main conclusion of this study was that the aging process did not significantly alter the mechanical properties for mono-materials, except for PMMA, where the maximum flexural stress decreased. In the sandwich structures, the TPU core had a softening effect, inducing a significant increase in the resilience and resistance to transverse impact. The obtained results are quite promising for applications in biomedical devices, such as protective mouthguards or teeth aligners. In these specific applications, the changes in the mechanical properties with time and with the contact of saliva assume particular importance.
Development and Characterization of Eudragit-RL-100-Based Aceclofenac Sustained-Release Matrix Pellets Prepared via Extrusion/Spheronization
Authors: Ibrahim Mohamed Abbas , Alshora Doaa Hasan
Published: November 2021

Aceclofenac (AC) is a nonsteroidal anti-inflammatory drug used in the treatment of chronic pain in conditions such as rheumatoid arthritis, with frequent administration during the day. The formulation of sustained release matrix pellets can provide a promising alternative dosage form that controls the release of the drug, with less blood fluctuation and side effects—especially those related to the gastric system. The extrusion/spheronization technique was used to formulate AC matrix pellets. The response surface methodology (version 17.2.02.; Statgraphics Centurion) was used to study the impacts of Eudragit RL 100 and PVP K90 binder solution concentrations on the pellets’ wet mass peak torque, pellet size, and the release of the drug. Statistically, a significant synergistic effect of PVP K90 concentration on the peak torque and pellet size was observed (p = 0.0156 and 0.031, respectively), while Eudragit RL 100 showed significant antagonistic effects (p = 0.042 and 0.013, respectively). The peak torque decreased from 0.513 ± 0.022 to 0.41 ± 0.021 when increasing the Eudragit RL 100 from 0 to 20%, and the pellet size decreased from 0.914 ± 0.047 to 0.789 ± 0.074 nm. The tested independent factors did not significantly affect the drug release in the acidic medium within 2 h, but these pellet formulae maintained the drug release at less than 10% in the acidic medium (pH 1.2), which may decrease gastric irritation side effects. In contrast, a highly significant synergistic effect of Eudragit and highly antagonistic effect of the PVP solution on drug release in the alkaline-pH medium were observed (p = 0.002 and 0.007, respectively). The optimized pellet formula derived from the statistical program, composed of 3.21% Eudragit and 5% PVP solution, showed peak torque of 0.861 ± 0.056 Nm and pellet size of 1090 ± 85 µm, and resulted in a significant retardation effect on the release after 8 h compared to the untreated drug.
Characteristics of Hydrochar and Liquid Products Obtained by Hydrothermal Carbonization and Wet Torrefaction of Poultry Litter in Mixture with Wood Sawdust
Authors: Isemin Rafail , Muratova Natalia , Kuzmin Sergey , Klimov Dmitry , Kokh-Tatarenko Vadim , Mikhalev Alexander , Milovanov Oleg , Dalibard Antoine , Ibitowa Olayinka Ahmed , Nowotny Manuel , Brulé Mathieu , Tabet Fouzi , Rogge Bernd
Published: November 2021

Poultry farms with floor-standing poultry generate large amounts of poultry litter waste. The direct application of this waste as an organic fertilizer does not ensure sustainable and cost-efficient utilization of all waste fractions, and can also be linked to environmental hazards. Therefore, the development of new technologies is required for processing poultry litter into a safe product with higher added value. In this work, the characteristics of activated carbon derived from hydrochar, along with the liquid products obtained from hydrothermal carbonization (HTC) and the wet torrefaction (WT) of poultry litter, were investigated. Poultry litter (PL) was applied in a mixture with sawdust (SD) in the following ratios: 1:0 (PL/SD 1:0), 1:1 (PL/SD 1:1), 1:2 (PL/SD 1:2), and 2:1 (PL/SD 2:1). WT processing took place in an innovative fluidized bed system in a superheated steam medium with low overpressure (less than 0.07 MPa) at 300 °C and 350 °C for 30–45 min. Conventional HTC processing was performed in a water medium at 220 °C for 1–4 h. The hydrochar produced in the experiments was activated with steam for 1 h at 450–750 °C. The porosity characteristics of activated hydrochar were measured, including pore size, pore volume, and specific surface area, in view of potential industrial applications as an adsorbent. Additionally, the contents of 5-hydroxymethylfurfural (HMF), as high-value product, were determined in the liquid products obtained from HTC processing, as well as in the condensate obtained after WT processing. Specific surface areas of the activated hydrochars may still be too low for application as adsorbent material. Hence, its use as a biofertilizer and soil improver should be preferred. Interestingly, the liquid fraction obtained from the innovative WT process displayed a significantly higher 5-HMF content compared to the conventional HTC process.
Handling Missing Responses in Psychometrics: Methods and Software
Authors: Dai Shenghai
Published: November 2021

The presence of missing responses in assessment settings is inevitable and may yield biased parameter estimates in psychometric modeling if ignored or handled improperly. Many methods have been proposed to handle missing responses in assessment data that are often dichotomous or polytomous. Their applications remain nominal, however, partly due to that (1) there is no sufficient support in the literature for an optimal method; (2) many practitioners and researchers are not familiar with these methods; and (3) these methods are usually not employed by psychometric software and missing responses need to be handled separately. This article introduces and reviews the commonly used missing response handling methods in psychometrics, along with the literature that examines and compares the performance of these methods. Further, the use of the TestDataImputation package in R is introduced and illustrated with an example data set and a simulation study. Corresponding R codes are provided.
Tobacco Profile and Evaluation of the DS14 Scale in Patients with Coronary Syndrome
Authors: Bálint Gabriel , Slezáková Zuzana , Miklovičová Emília
Published: November 2021

Background: the prevalence of current smokers in patients with coronary syndrome is high. This risk behaviour significantly increases the risk of cardiovascular complications. In the recommendations for the management of cardiovascular diseases, psychosocial and psychological factors are still neglected in practice. The aim of study was to verify the prevalence of tobacco use in hospitalized patients with coronary syndrome, notably to verify the type-D personality and tobacco use in the groups obtained from the evaluation of the DS14 scale. Methods: in this cross-sectional study, we addressed 100 hospitalized patients with coronary syndrome. Results: in the cohort, 48% patient were current smokers, 21% were never smokers, 24% were former smokers, 4% were occasional smokers, and 3% were quitters. Based on the evaluation of DS14, 21% of patients were classified as type-D personality and 38% as non-type-D; we identified two subtypes: the NA group at 23% and the SI group at 18%. In the group of the current smokers, 81% declared that they wanted to quit smoking, 15% of the patients were undecided, and 4% of current smokers did not want to quit. Conclusions: cardiac patients are aware that their disease is related to smoking; despite the severity of their disease, patients’ motivation to change their risky behaviour is low.
Encountering the Goddess in the Indian Himalaya: On the Contribution of Ethnographic Film to the Study of Religion
Authors: Moran Arik
Published: November 2021

This paper examines the benefits of ethnographic film for the study of religion. It argues that the exploration of gaps between colloquial descriptions of divinities and their practical manifestation in ritual is instructive of the way religious categories are conceptualized. The argument is developed through an analysis of selected scenes from the documentary AVATARA, a meditation on goddess worship (Śaktism) among the Khas ethnic majority of the Hindu Himalaya (Himachal Pradesh, India). Centering on embodiments of the goddess in spirit possession séances, it points to a fundamental difference between the popular depiction of the deity as a virgin-child (kanyā) who visits followers in their dreams and her actual manifestation as a menacing mother (mātā) during ritual activities. These ostensibly incongruent images are ultimately bridged by the anthropologically informed edition of the material caught on camera, illustrating the added advantage of documentary filmmaking for approximating religious experiences.
Through the Eyes of a Mapmaker: Maritime Shrines on Cyprus during the Late Middle Ages
Authors: Perdiki Ourania
Published: November 2021

Cyprus acquired special importance, especially from the thirteenth century onwards, on the Eastern Mediterranean’s pilgrimage network. Described by contemporary pilgrims as “Terra christianorum ultima”, the island was considered to be the last Christian land in the south-eastern Mediterranean on the pilgrims’ itinerary on their journey to the Holy Land. This study is concentrated on two maps of Cyprus dated to the fourteenth century and preserved in Milan: Biblioteca Ambrosiana, A95 sup. and Venice: Biblioteca Nazionale Marciana, gr. XI.21. It aims to explore the physical and spiritual mobility and interconnectivity in Cyprus during the late Middle Ages and to consider how these contribute to the development of pilgrimage sites directly related with maritime routes, seamen and travellers. These unique nautical maps captured the sea voyage which had Cyprus as a stopover, bringing to light new insights into fourteenth century Cyprus. The maritime shrines discussed in this article, which are usually “mixed” sacred sites, are directly related with sailors’ needs. They integrate into a wide network of communication, removing them partially from their local dimension.
The Variability of Summer Atmospheric Water Cycle over the Tibetan Plateau and Its Response to the Indo-Pacific Warm Pool
Authors: Meng Deli , Song Wanjiao , Dong Qing , Yin Zi , Zhao Wenbo
Published: November 2021

The Tibetan Plateau (TP), atmosphere, and Indo-Pacific warm pool (IPWP) together constitute a regional land–atmosphere–ocean water vapor transport system. This study uses remote sensing data, reanalysis data, and observational data to explore the spatiotemporal variations of the summer atmospheric water cycle over the TP and its possible response to the air-sea interaction in the IPWP during the period 1958–2019. The results reveal that the atmospheric water cycle process over the TP presented an interannual and interdecadal strengthening trend. The climatic precipitation recycle ratio (PRR) over the TP was 18%, and the stronger the evapotranspiration, the higher the PRR. On the interdecadal scale, the change in evapotranspiration has a significant negative correlation with the Pacific Decadal Oscillation (PDO) index. The variability of the water vapor transport (WVT) over the TP was controlled by the dynamic and thermal conditions inside the plateau and the external air-sea interaction processes of the IPWP. When the summer monsoon over the TP was strong, there was an anomalous cyclonic WVT, which increased the water vapor budget (WVB) over the TP. The central and eastern tropical Pacific, the maritime continent and the western Indian Ocean together constituted the triple Sea Surface Temperature (SST) anomaly, which enhanced the convective activity over the IPWP and induced a significant easterly wind anomaly in the middle and lower troposphere, and then generated pronounced easterly WVT anomalies from the tropical Pacific to the maritime continent and the Bay of Bengal. Affected by the air-sea changes in the IPWP, the combined effects of the upstream strengthening and the downstream weakening in the water vapor transport process, directly and indirectly, increased the water vapor transport and budget of TP.
The Geological History of the Chang’e-5 Sample Return Region
Authors: Deng Jiayin , Cheng Weiming , Jiao Yimeng , Liu Jianzhong , Chen Jianping , Wang Baixue
Published: November 2021

Chang’e-5 (CE-5), China’s first sample-return mission, has successfully landed in Oceanus Procellarum near Mons Rümker. It is important to have a detailed study of the geological evolution of the CE-5 sample return region. This work aims to study the geological background, topography, geomorphology, major chemical composition, mineralogy, and chronology of the landing site region. First, we used the map of topography obtained by the Kaguya TC merged Digital Terrain Model (DTM) to analyze the topographic characteristics. Then, we used the Kaguya Multiband Imager (MI) reflectance data to derive FeO and TiO2 abundance and the hyperspectral data of the Moon Mineralogy Mapper (M3) onboard the Chandrayaan-1 spacecraft to study the mineralogy of the landing site region. Later, we defined and dated the geological units of the landing area using the crater size–frequency distribution (CSFD) method. Finally, we conducted a detailed analysis of the volcanism and tectonism that occurred in the CE-5 landing area. The study region has experienced multi-stage magmatic activities (~3.36 Ga to ~1.22 Ga) and formed multiple mare units with different chemical and mineral compositions. The relationship between the wrinkle ridges cut by small impact craters suggests that the U7/Em5 has experienced Copernican aged tectonism recently ~320 Ma. The U7/Em5 unit where the Chang’e-5 sample return mission landed is dominantly composed of mature pyroxene and the basalts are mainly high-iron and mid-titanium basalts. Additionally, the analysis of pure basalt in the U7/Em5 suggests that the samples returned by the CE-5 mission may contain the ejecta and ray materials of young craters, including sharp B, Harding, Copernicus, and Aristarchus.
Sea Ice Monitoring with CFOSAT Scatterometer Measurements Using Random Forest Classifier
Authors: Zhai Xiaochun , Wang Zhixiong , Zheng Zhaojun , Xu Rui , Dou Fangli , Xu Na , Zhang Xingying
Published: November 2021

The Ku-band scatterometer called CSCAT onboard the Chinese–French Oceanography Satellite (CFOSAT) is the first spaceborne rotating fan-beam scatterometer (RFSCAT). This paper performs sea ice monitoring with the CSCAT backscatter measurements in polar areas. The CSCAT measurements have the characteristics of diverse incidence and azimuth angles and separation between open water and sea ice. Hence, five microwave feature parameters, which show different sensitivity to ice or water, are defined and derived from the CSCAT measurements firstly. Then the random forest classifier is selected for sea ice monitoring because of its high overall accuracy of 99.66% and 93.31% in the Arctic and Antarctic, respectively. The difference of features ranked by importance in different seasons and regions shows that the combination of these parameters is effective in discriminating sea ice from water under various conditions. The performance of the algorithm is validated against the sea ice edge data from the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF) on a global scale in a period from 1 January 2019 to 10 May 2021. The mean sea ice area differences between CSCAT and OSI SAF product in the Arctic and Antarctic are 0.2673 million km2 and −0.4446 million km2, respectively, and the sea ice area relative errors of CSCAT are less than 10% except for summer season in both poles. However, the overall sea ice area derived from CSCAT is lower than the OSI SAF sea ice area in summer. This may be because the CSCAT is trained by radiometer sea ice concentration data while the radiometer measurement of sea ice is significantly affected by melting in the summer season. In conclusion, this research verifies the capability of CSCAT in monitoring polar sea ice using a machine learning-aided random forest classifier. This presented work can give guidance to sea ice monitoring with radar backscatter measurements from other spaceborne scatterometers, particular for the recently launched FY-3E scatterometer (called WindRad).
AEM in Norway: A Review of the Coverage, Applications and the State of Technology
Authors: Harrison Edward J. , Baranwal Vikas C. , Pfaffhuber Andreas A. , Christensen Craig W. , Skurdal Guro H. , Rønning Jan Steinar , Anschütz Helgard , Brönner Marco
Published: November 2021

From the first use of airborne electromagnetic (AEM) systems for remote sensing in the 1950s, AEM data acquisition, processing and inversion technology have rapidly developed. Once used extensively for mineral exploration in its early days, the technology is increasingly being applied in other industries alongside ground-based investigation techniques. This paper reviews the application of onshore AEM in Norway over the past decades. Norway’s rugged terrain and complex post-glacial sedimentary geology have contributed to the later adoption of AEM for widespread mapping compared to neighbouring Nordic countries. We illustrate AEM’s utility by using two detailed case studies, including time-domain and frequency domain AEM. In both cases, we combine AEM with other geophysical, geological and geotechnical drillings to enhance interpretation, including machine learning methods. The end results included bedrock surfaces predicted with an accuracy of 25% of depth, identification of hazardous quick clay deposits, and sedimentary basin mapping. These case studies illustrate that although today’s AEM systems do not have the resolution required for late-phase, detailed engineering design, AEM is a valuable tool for early-phase site investigations. Intrusive, ground-based methods are slower and more expensive, but when they are used to complement the weaknesses of AEM data, site investigations can become more efficient. With new developments of drone-borne (UAV) systems and increasing investment in AEM surveys, we see the potential for continued global adoption of this technology.
Improved Bi-Angle Aerosol Optical Depth Retrieval Algorithm from AHI Data Based on Particle Swarm Optimization
Authors: Jin Chunlin , Xue Yong , Jiang Xingxing , Sun Yuxin , Wu Shuhui
Published: November 2021

The Advanced Himawari Imager (AHI) aboard the Himawari-8, a new generation of geostationary meteorological satellite, has high-frequency observation, which allows it to effectively capture atmospheric variations. In this paper, we have proposed an Improved Bi-angle Aerosol optical depth (AOD) retrieval Algorithm (IBAA) from AHI data. The algorithm ignores the aerosol effect at 2.3 μm and assumes that the aerosol optical depth does not change within one hour. According to the property that the reflectivity ratio K of two observations at 2.3 μm does not change with wavelength, we constructed the equation for two observations of AHI 0.47 μm band. Then Particle Swarm Optimization (PSO) was used to solve the nonlinear equation. The algorithm was applied to the AHI observations over the Chinese mainland (80°–135°E, 15°–60°N) between April and June 2019 and hourly AOD at 0.47 μm was retrieved. We validated IBAA AOD against the Aerosol Robotic Network (AERONET) sites observation, including surrounding regions as well as the Chinese mainland, and compared it with the AHI L3 V030 hourly AOD product. Validation with AERONET of 2079 matching points shows a correlation coefficient R = 0.82, root-mean-square error RMSE = 0.27, and more than 62% AOD retrieval results within the expected error of ±(0.05 + 0.2 × AODAERONET). Although IBAA does not perform very well in the case of coarse-particle aerosols, the comparison and validation demonstrate it can estimate AHI AOD with good accuracy and wide coverage over land on the whole.
Comparison of Tree-Structured Parzen Estimator Optimization in Three Typical Neural Network Models for Landslide Susceptibility Assessment
Authors: Rong Guangzhi , Li Kaiwei , Su Yulin , Tong Zhijun , Liu Xingpeng , Zhang Jiquan , Zhang Yichen , Li Tiantao
Published: November 2021

Landslides pose a constant threat to the lives and property of mountain people and may also cause geomorphological destruction such as soil and water loss, vegetation destruction, and land cover change. Landslide susceptibility assessment (LSA) is a key component of landslide risk evaluation. There are many related studies, but few analyses and comparisons of models for optimization. This paper aims to introduce the Tree-structured Parzen Estimator (TPE) algorithm for hyperparameter optimization of three typical neural network models for LSA in Shuicheng County, China, as an example, and to compare the differences of predictive ability among the models in order to achieve higher application performance. First, 17 influencing factors of landslide multiple data sources were selected for spatial prediction, hybrid ensemble oversampling and undersampling techniques were used to address the imbalanced sample and small sample size problem, and the samples were randomly divided into a training set and validation set. Second, deep neural network (DNN), recurrent neural network (RNN), and convolutional neural network (CNN) models were adopted to predict the regional landslides susceptibility, and the TPE algorithm was used to optimize the hyperparameters respectively to improve the assessment capacity. Finally, to compare the differences and optimization effects of these models, several objective measures were applied for validation. The results show that the high-susceptibility regions mostly distributed in bands along fault zones, where the lithology is mostly claystone, sandstone, and basalt. The DNN, RNN, and CNN models all perform well in LSA, especially the RNN model. The TPE optimization significantly improves the accuracy of the DNN and CNN (3.92% and 1.52%, respectively), but does not improve the performance of the RNN. In summary, our proposed RNN model and TPE-optimized DNN and CNN model have robust predictive capability for landslide susceptibility in the study area and can also be applied to other areas containing similar geological conditions.
Vertical Differences in the Long-Term Trends and Breakpoints of NDVI and Climate Factors in Taiwan
Authors: Tsai Hui Ping , Wang Geng-Gui , Zhuang Zhong-Han
Published: November 2021

This study explored the long-term trends and breakpoints of vegetation, rainfall, and temperature in Taiwan from overall and regional perspectives in terms of vertical differences from 1982 to 2012. With time-series Advanced Very-High-Resolution Radiometer (AVHRR) normalized difference vegetation index (NDVI) data and Taiwan Climate Change Estimate and Information Platform (TCCIP) gridded monthly climatic data, their vertical dynamics were investigated by employing the Breaks for Additive Seasonal and Trend (BFAST) algorithm, Pearson’s correlation analysis, and the Durbin–Watson test. The vertical differences in NDVI values presented three breakpoints and a consistent trend from positive (1982 to 1989) to negative at varied rates, and then gradually increased after 2000. In addition, a positive rainfall trend was discovered. Average and maximum temperature had similar increasing trends, while minimum temperature showed variations, especially at higher altitudes. In terms of regional variations, the vegetation growth was stable in the north but worse in the central region. Higher elevations revealed larger variations in the NDVI and temperature datasets. NDVI, along with average and minimum temperature, showed their largest changes earlier in higher altitude areas. Specifically, the increasing minimum temperature direction was more prominent in the mid-to-high-altitude areas in the eastern and central regions. Seasonal variations were observed for each region. The difference between the dry and wet seasons is becoming larger, with the smallest difference in the northern region and the largest difference in the southern region. Taiwan’s NDVI and climatic factors have a significant negative correlation (p < 0.05), but the maximum and minimum temperatures have significant positive effects at low altitudes below 500 m. The northern and central regions reveal similar responses, while the south and east display different feedbacks. The results illuminate climate change evidence from assessment of the long-term dynamics of vegetation and climatic factors, providing valuable references for establishing correspondent climate-adaptive strategies in Taiwan.
Improving Urban Land Cover Classification in Cloud-Prone Areas with Polarimetric SAR Images
Authors: Ling Jing , Zhang Hongsheng , Lin Yinyi
Published: November 2021

Urban land cover (ULC) serves as fundamental environmental information for urban studies, while accurate and timely ULC mapping remains challenging due to cloud contamination in tropical and subtropical areas. Synthetic aperture radar (SAR) has excellent all-weather working capability to overcome the challenge, while optical SAR data fusion is often required due to the limited land surface information provided by SAR. However, the mechanism by which SAR can compensate optical images, given the occurrence of clouds, in order to improve the ULC mapping, remains unexplored. To address the issue, this study proposes a framework, through various sampling strategies and three typical supervised classification methods, to quantify the ULC classification accuracy using optical and SAR data with various cloud levels. The land cover confusions were investigated in detail to understand the role of SAR in distinguishing land cover under different types of cloud coverage. Several interesting experimental results were found. First, 50% cloud coverage over the optical images decreased the overall accuracy by 10–20%, while the incorporation of SAR images was able to improve the overall accuracy by approximately 4%, by increasing the recognition of cloud-covered ULC information, particularly the water bodies. Second, if all the training samples were not contaminated by clouds, the cloud coverage had a higher impact with a reduction of 35% in the overall accuracy, whereas the incorporation of SAR data contributed to an increase of approximately 5%. Third, the thickness of clouds also brought about different impacts on the results, with an approximately 10% higher reduction from thick clouds compared with that from thin clouds, indicating that certain spectral information might still be available in the areas covered by thin clouds. These findings provide useful references for the accurate monitoring of ULC over cloud-prone areas, such as tropical and subtropical cities, where cloud contamination is often unavoidable.
Review of Image Classification Algorithms Based on Convolutional Neural Networks
Authors: Chen Leiyu , Li Shaobo , Bai Qiang , Yang Jing , Jiang Sanlong , Miao Yanming
Published: November 2021

Image classification has always been a hot research direction in the world, and the emergence of deep learning has promoted the development of this field. Convolutional neural networks (CNNs) have gradually become the mainstream algorithm for image classification since 2012, and the CNN architecture applied to other visual recognition tasks (such as object detection, object localization, and semantic segmentation) is generally derived from the network architecture in image classification. In the wake of these successes, CNN-based methods have emerged in remote sensing image scene classification and achieved advanced classification accuracy. In this review, which focuses on the application of CNNs to image classification tasks, we cover their development, from their predecessors up to recent state-of-the-art (SOAT) network architectures. Along the way, we analyze (1) the basic structure of artificial neural networks (ANNs) and the basic network layers of CNNs, (2) the classic predecessor network models, (3) the recent SOAT network algorithms, (4) comprehensive comparison of various image classification methods mentioned in this article. Finally, we have also summarized the main analysis and discussion in this article, as well as introduce some of the current trends.
Longitudinal Structure in the Altitude of the Sporadic E Observed by COSMIC in Low-Latitudes
Authors: Liu Zhendi , Li Qingfeng , Fang Hanxian , Gao Ze
Published: November 2021

The longitudinal structure in the altitude of the Sporadic E (Es) was investigated for the first time based on the S4 index provided by the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) in low latitudes. The longitudinal structure is identified as a symmetrically located wavenumber-4 (WN4) pattern within 30°S–30°N. The WN4 occurs primarily during the daytime at the June solstice and equinoxes, with the largest amplitude at the September equinox and the smallest one at the March equinox. It moves eastward with a speed of ~90°/day. The strongest WN4 appears within 10–20°N and 5–15°S in the Northern and Southern hemispheres, respectively. At the June solstice and the September equinox, the WN4 is stronger in the Northern hemisphere than in the Southern hemisphere, while the situation is reversed at the March equinox. The altitude distribution of the convergence null in the diurnal eastward non-migrating tide with zonal wavenumber-3 (DE3) for the zonal wind is similar to that of the WN4. This and other similar features, such as the seasonal variation, eastward speed, and the symmetrical locations, support the dominant role of the DE3 tide for the formation of the WN4 structure.
Recent Development of Multifunctional Sensors Based on Low-Dimensional Materials
Authors: Xu Qian , Dai Yang , Peng Yiyao , Hong Li , Yang Ning , Wang Zhiqiang
Published: November 2021

With the demand for accurately recognizing human actions and environmental situations, multifunctional sensors are essential elements for smart applications in various emerging technologies, such as smart robots, human-machine interface, and wearable electronics. Low-dimensional materials provide fertile soil for multifunction-integrated devices. This review focuses on the multifunctional sensors for mechanical stimulus and environmental information, such as strain, pressure, light, temperature, and gas, which are fabricated from low-dimensional materials. The material characteristics, device architecture, transmission mechanisms, and sensing functions are comprehensively and systematically introduced. Besides multiple sensing functions, the integrated potential ability of supplying energy and expressing and storing information are also demonstrated. Some new process technologies and emerging research areas are highlighted. It is presented that optimization of device structures, appropriate material selection for synergy effect, and application of piezotronics and piezo-phototronics are effective approaches for constructing and improving the performance of multifunctional sensors. Finally, the current challenges and direction of future development are proposed.
A Hierarchical Feature Extraction Network for Fast Scene Segmentation
Authors: Miao Liu , Zhang Yi
Published: November 2021

Semantic segmentation is one of the most active research topics in computer vision with the goal to assign dense semantic labels for all pixels in a given image. In this paper, we introduce HFEN (Hierarchical Feature Extraction Network), a lightweight network to reach a balance between inference speed and segmentation accuracy. Our architecture is based on an encoder-decoder framework. The input images are down-sampled through an efficient encoder to extract multi-layer features. Then the extracted features are fused via a decoder, where the global contextual information and spatial information are aggregated for final segmentations with real-time performance. Extensive experiments have been conducted on two standard benchmarks, Cityscapes and Camvid, where our network achieved superior performance on NVIDIA 2080Ti.
Landlord Perceptions on Homelessness in Northern Utah
Authors: Walters Jayme E. , Lucero Jessica , Wever Claire , Post Amber
Published: November 2021

Homeless programs often rely on landlord engagement for successful implementation. However, there is very little research that examines landlord perspectives related to homelessness. Better understanding landlords’ opinions and attitudes regarding those experiencing homelessness can inform program development and policy in the efforts to prevent and mitigate homelessness in the U.S. A 49-question survey was created and administered by social work faculty and students to landlords and property managers throughout the Bear River Region of northern Utah (N = 134). The survey contained a variety of questions that assessed landlord attitudes and knowledge toward those experiencing homelessness as well as their comfortability in renting to these individuals. Results revealed that landlords would like to help solve homelessness in their community, but they do not know where to start. Additionally, results showed that landlords’ willingness to rent to individuals experiencing homelessness is dependent on contextual factors, such as having more information regarding the individual, their income, past rental history, and other factors. Finally, results showed that landlords had biases toward specific groups of individuals experiencing homelessness (e.g., landlords felt more comfortable renting to those with physical disabilities than those with substance misuse histories). Results are discussed in context of program, policy, and research implications.
The 2021 Bitcoin Bubbles and Crashes—Detection and Classification
Authors: Shu Min , Song Ruiqiang , Zhu Wei
Published: November 2021

In this study, the Log-Periodic Power Law Singularity (LPPLS) model is adopted for real-time identification and monitoring of Bitcoin bubbles and crashes using different time scale data, and the modified Lagrange regularization method is proposed to alleviate the impact of potential LPPLS model over-fitting to better estimate bubble start time and market regime change. The goal here is to determine the nature of the bubbles and crashes (i.e., whether they are endogenous due to their own price evolution or exogenous due to external market and/or policy influences). A systematic market event analysis is performed and correlated to the Bitcoin bubbles detected. Based on the daily LPPLS confidence indictor from 1 December 2019 to 24 June 2021, this analysis has disclosed that the Bitcoin boom from November 2020 to mid-January 2021 is an endogenous bubble, stemming from the self-reinforcement of cooperative herding and imitative behaviors of market players, while the price spike from mid-January 2021 to mid-April 2021 is likely an exogenous bubble driven by extrinsic events including a series of large-scale acquisitions and adoptions by well-known institutions such as Visa and Tesla. Finally, the utilities of multi-resolution LPPLS analysis in revealing both short-term changes and long-term states have also been demonstrated in this study.
Examining Factors Influencing COVID-19 Vaccine Tourism for International Tourists
Authors: Kaewkitipong Laddawan , Chen Charlie , Ractham Peter
Published: November 2021

Since early 2020, the COVID-19 pandemic has had a devastating impact on global tourism. Vaccine tourism is a novel health tourism concept, which provides an opportunity for countries with a vaccine surplus to offer medical tourism packages to entice international tourists from countries with vaccine shortages to visit for sightseeing and receive vaccine inoculations. Understanding the factors that influence people to adopt vaccine tourism is one of the strategies that could boost a country’s tourism sector and help to revive the local economy. This study aims to examine the factors influencing the intention to adopt and recommend COVID-19 vaccine tourism among young travelers. A total of 179 questionnaire surveys were collected from traveling-related social media outlets. Partial least squares structural equation modeling (PLS-SEM) was performed to analyze the data. The results indicate that young tourists in Thailand are inclined to promote vaccine tourism to others. Price value appears to be the most significant influencing factor on intentions to both adopt and recommend vaccine tourism. Additionally, trust in the foreign healthcare system was positively associated with young travelers’ intention to recommend vaccine tourism to others. Theoretically, this research adds to the medical tourism literature, suggesting that, while trust is an important factor influencing the medical tourism decision, it appears to be insignificant in the context of vaccine tourism.
Quasi-Periodic Oscillatory Motion of Particles Orbiting a Distorted, Deformed Compact Object
Authors: Faraji Shokoufe , Trova Audrey
Published: November 2021

This work explores the dynamic properties of test particles surrounding a distorted, deformed compact object. The astrophysical motivation was to choose such a background as to constitute a more reasonable model of a real situation that arises in the vicinity of compact objects with the possibility of having parameters such as the extra physical degrees of freedom. This can facilitate associating observational data with astrophysical systems. This work’s main goal is to study the dynamic regime of motion and quasi-periodic oscillation in this background, depending on different parameters of the system. In addition, we exercise the resonant phenomena of the radial and vertical oscillations at their observed quasi-periodic oscillations frequency ratio 3:2 and show that the oscillatory frequencies of charged particles can be adequately related to the frequencies of the twin high-frequency quasi-periodic oscillations observed in some sources of the microquasar observational data.
Particle-in-Cell Simulations of Astrophysical Relativistic Jets
Authors: Meli Athina , Nishikawa Ken-ichi
Published: November 2021

Astrophysical relativistic jets in active galactic nuclei, gamma-ray bursts, and pulsars is the main key subject of study in the field of high-energy astrophysics, especially regarding the jet interaction with the interstellar or intergalactic environment. In this work, we review studies of particle-in-cell simulations of relativistic electron–proton (e−−p+) and electron–positron (e±) jets, and we compare simulations that we have conducted with the relativistic 3D TRISTAN-MPI code for unmagnetized and magnetized jets. We focus on how the magnetic fields affect the evolution of relativistic jets of different compositions, how the jets interact with the ambient media, how the kinetic instabilities such as the Weibel instability, the kinetic Kelvin–Helmholtz instability and the mushroom instability develop, and we discuss possible particle acceleration mechanisms at reconnection sites.
Wave Functional of the Universe and Time
Authors: Gorobey Natalia , Lukyanenko Alexander , Goltsev Alexander V.
Published: November 2021

A version of the quantum theory of gravity based on the concept of the wave functional of the universe is proposed. To determine the physical wave functional, the quantum principle of least action is formulated as a secular equation for the corresponding action operator. Its solution, the wave functional, is an invariant of general covariant transformations of spacetime. In the new formulation, the history of the evolution of the universe is described in terms of coordinate time together with arbitrary lapse and shift functions, which makes this description close to the formulation of the principle of general covariance in the classical theory of Einstein’s gravity. In the new formulation of quantum theory, an invariant parameter of the evolutionary time of the universe is defined, which is a generalization of the classical geodesic time measured by a standard clock along time-like geodesics.
Validation of Pretreatment Methods for the In-Process Quantification of Foot-and-Mouth Disease Vaccine Antigens
Authors: Kim Ah-Young , Park Sun Young , Park Sang Hyun , Jin Jong Sook , Kim Eun-Sol , Kim Jae Young , Park Jong-Hyeon , Ko Young-Joon
Published: November 2021

Foot-and-mouth disease (FMD), caused by the FMD virus (FMDV), is controlled by vaccine policy in many countries. For vaccine potency, the content of intact virus particles (146S antigens) is critical, and the sucrose density gradient (SDG) fractionation is the gold standard for the quantification of 146S antigens. However, this method has several drawbacks. Although size-exclusion high-performance liquid chromatography (SE-HPLC) was introduced to replace the classic method, its application is generally confined to purified samples owing to the interfering signals. Therefore, we aimed to develop optimal pretreatment methods for SE-HPLC quantification in less purified samples. Crude virus infection supernatant (CVIS) and semi-purified samples with PEG precipitation (PEG-P) were used. Chloroform pretreatment was essential to remove a high level of non-specific signals in CVIS, whereas it caused loss of 146S antigens without the distinctive removal of non-specific signals in PEG-P. Benzonase pretreatment was required to improve the resolution of the target peak in the chromatogram for both CVIS and PEG-P. Through spiking tests with pure 146S antigens, it was verified that the combined pretreatment with chloroform and benzonase was optimal for the CVIS, while the sole pretreatment of benzonase was beneficial for PEG-P.
Effect of Copper, Zinc, and Selenium on the Migration of Bovine Neutrophils
Authors: Wang Hai , Lv Guanxin , Lian Shuai , Wang Jianfa , Wu Rui
Published: November 2021

Neutrophils represent the first line of mammary gland defense against invading pathogens by transmigration across the mammary epithelial cell barrier. The effect of trace elements on the migration of bovine neutrophils is not clear. In this study, we investigated the effect of copper (Cu; 0.5, 1.0 and 1.5 mg/L), zinc (Zn; 1.0, 5.0 and 10 mg/L) and selenium (Se; 0.1, 1.0 and 2.0 mg/L) on the migration of bovine neutrophils by using a Transwell assay. The results showed that Cu, Zn and Se promoted the number of neutrophils in the trans-mammary epithelium. With the increased concentration of Cu at 1.5 mg/L, the number of neutrophils in the trans-mammary epithelium was increased significantly (p < 0.05). Zn (5.0 mg/L) and Se (0.1 mg/L) increased the migrated number of neutrophils (p < 0.01) to an extremely significant degree. These findings provided a theoretical and experimental basis for mammary gland immunity in dairy cows. Thus, we suggest that adding moderate amounts of different trace elements can improve the immune function of dairy cows.
Failure to Eliminate Persistent Anaplasma marginale Infection from Cattle Using Labeled Doses of Chlortetracycline and Oxytetracycline Antimicrobials
Authors: Curtis Andrew K. , Kleinhenz Michael D. , Anantatat Tippawan , Martin Miriam S. , Magnin Geraldine C. , Coetzee Johann F. , Reif Kathryn E.
Published: November 2021

Bovine anaplasmosis, caused by the intracellular rickettsial pathogen Anaplasma marginale, is the most prevalent tick-transmitted disease of cattle worldwide. In the U.S., tetracycline antimicrobials are commonly used to treat and control anaplasmosis. Oxytetracycline, administered by injection, is indicated for treatment of clinical anaplasmosis in beef and dairy cattle and calves. Chlortetracycline, administered orally, is indicated for control of active anaplasmosis infection in beef and nonlactating dairy cattle. Tetracyclines have been demonstrated to be effective for treating active anaplasmosis, but their ability to eliminate A. marginale at currently approved therapeutic doses or dosing regimens remains unclear. In the absence of approved dosing regimens for A. marginale clearance, a study was conducted to determine the effect of approved oxytetracycline and chlortetracycline indications on A. marginale bacteremia. Fifteen animals with persistent anaplasmosis were enrolled and divided into three treatment groups. Group 1 (n = 6) received oral chlortetracycline (1.1 mg/kg bodyweight) administered via hand-fed medicated feed for 60 consecutive days. Group 2 (n = 6) received injectable oxytetracycline administered subcutaneously at 19.8 mg/kg bodyweight three times in 3-week intervals. Group 3 (n = 3) served as an untreated control. After 60 days, bacteremia failed to permanently decrease in response to treatment. This result indicates that clearance of A. marginale is unlikely to be reliably achieved using currently approved tetracycline-based regimens to manage anaplasmosis.
Research on New Energy Vehicle Market Penetration Rate Based on Nested Multinominal Logit Model
Authors: Liu Kexin , Shi Hong , Liu Bin , Jian Xiaorong
Published: November 2021

This article uses the NMNL (nested multinominal logit) model to analyze the impact of different policies on the cost of owning a vehicle by a consumer and discusses the changes in the share of various fuel-driven types of passenger vehicles that may be brought by different policy portfolios. This article also considers the differences in the development of various technical routes, conducts the nested classification calculation of different models, divides the differences in product preferences and obtains the market share results that are more in line with the market development status, providing a basis for the formulation of policies related to new energy vehicles. The study found that the popularization of NEVs requires more cost-reducing measures. As policies that consumers can perceive, consumers are more sensitive to fiscal and taxation policies than other types of policies. Based on the calculation of policy effects, this article recommends a policy plan to gradually impose vehicle purchase tax on NEVs after 2024, increase the fuel tax rate in stages after 2025, and impose an excise tax on BEVs and FCEVs after 2030. The plan can guarantee the stability of support for NEVs and the gradual reduction of financial investment.