bluuebunny/crossref_metadata_2025 huggingface dataset:
A Two-Stage SEM–Artificial Neural Network Analysis of Mobile Commerce and Its Drivers
Authors: Vărzaru Anca Antoaneta , Bocean Claudiu George
Published: September 2021

The COVID-19 health and economic crisis has affected all areas of social life globally, including the economy. The world economy has declined due to purchasing power for individuals who have been forced to stay at home and cannot perform work. These restrictions to prevent the spread of SARS-Cov-2 have led to an increase in electronic commerce and mobile commerce as tools for procuring goods and services. In this paper, we conducted a longitudinal analysis of mobile commerce as an essential electronic commerce component, establishing the main drivers of mobile commerce and the intensity of their influences. The research focuses on mobile commerce in the United States (U.S.). It covers the period 2010–2020, the last year of this period capturing the context of the COVID-19 pandemic and its impact on electronic commerce (e-commerce) and mobile commerce (m-commerce). In the macroeconomic analysis of competitiveness, we established the main drivers of m-commerce, using artificial neural networks and the mediation effects found between the variables that describe m-commerce, e-commerce, and total sales, using structural equation modeling. The research results indicate an increase in the share of e-commerce in total sales and a predominance of the m-commerce share in e-commerce on the background of traffic restrictions and social distance rules imposed due to the COVID-19 pandemic. Stakeholders in the m-commerce area should consider the following enhancing drivers: increasing internet speed, expanding 5G and Wi-Fi networks, and increasing accessibility and trust in mobile devices and applications.
Traditional Free-Ranging Livestock Farming as a Management Strategy for Biological and Cultural Landscape Diversity: A Case from the Southern Apennines
Authors: Troiano Claudia , Buglione Maria , Petrelli Simona , Belardinelli Sofia , De Natale Antonino , Svenning Jens-Christian , Fulgione Domenico
Published: September 2021

Mediterranean mountain landscapes are undergoing a widespread phenomenon of abandonment. This brings, as a consequence, the loss of traditional land use practices, such as transhumant pastoralism, as well as shrub and wood encroachment, with repercussions on the biodiversity associated with semi-open, human-managed landscapes. In this study, we focus on a mountain pasture from the Southern Apennines (Italy), where free-ranging transhumant grazing is still carried out, to quantify the effects of grazing presence and exclusion on arthropod diversity, and to qualitatively characterize the plant communities of grazed and ungrazed areas. Using field sampling, remote sensing, and semi-structured interviews, we assessed the validity of traditional cattle farming as a landscape management tool. Indeed, high diversity grasslands excluded from grazing were characterized by significantly less even and more dominated arthropod communities, as well as fewer plant species and families. Moreover, in areas that have been consistently grazed over the years, we found no forest encroachment from 1955 to 2019. However, rural communities are experiencing difficulties in keeping local traditions alive, even with current agri-environmental schemes. Thus, traditional livestock grazing can be a valuable management tool to maintain high biological and cultural diversity, even if stronger cooperation and attention to local needs is necessary.
Antithrombotic Effect of the Ethanol Extract of Angelica gigas Nakai (AGE 232)
Authors: Bravo Pia Loreto Werlinger , Jin Hui , Park Hyunwoo , Kim Min Sang , Matsui Hirofumi , Lee Hanki , Suh Joo-Won
Published: September 2021

Cardiovascular diseases, such as stroke, are the most common causes of death in developed countries. Ischemic stroke accounts for 85% of the total cases and is caused by abnormal thrombus formation in the vessels, causing deficient blood and oxygen supply to the brain. Prophylactic treatments include the prevention of thrombus formation, of which the most used is acetylsalicylic acid (ASA); however, it is associated with a high incidence of side effects. Angelica gigas Nakai (AG) is a natural herb used to improve blood circulation via anti-platelet aggregation, one of the key processes involved in thrombus formation. We examined the antithrombotic effects of AGE 232, the ethanol extract of A. gigas Nakai. AGE 232 showed a significant reduction in death or paralysis in mice caused by collagen/epinephrine-induced thromboembolism in a dose-dependent manner and inhibition of collagen-induced human platelet aggregation in a concentration-dependent manner. Additionally, AGE 232-treated mice did not show severe bleeding in the gut compared to ASA-treated mice. AGE 232 resulted in a decrease in the number of neutrophils attached to the human umbilical vein endothelial cells (HUVECs) and lower inhibition of COX-1 in response to bleeding and damage to blood vessels, a major side effect of ASA. Therefore, AGE 232 can prevent thrombus formation and stroke.
Identifying Lung Cancer Cell Markers with Machine Learning Methods and Single-Cell RNA-Seq Data
Authors: Huang Guo-Hua , Zhang Yu-Hang , Chen Lei , Li You , Huang Tao , Cai Yu-Dong
Published: September 2021

Non-small cell lung cancer is a major lethal subtype of epithelial lung cancer, with high morbidity and mortality. The single-cell sequencing technique plays a key role in exploring the pathogenesis of non-small cell lung cancer. We proposed a computational method for distinguishing cell subtypes from the different pathological regions of non-small cell lung cancer on the basis of transcriptomic profiles, including a group of qualitative classification criteria (biomarkers) and various rules. The random forest classifier reached a Matthew’s correlation coefficient (MCC) of 0.922 by using 720 features, and the decision tree reached an MCC of 0.786 by using 1880 features. The obtained biomarkers and rules were analyzed in the end of this study.
Polymer-Derived Biosilicate®-like Glass-Ceramics: Engineering of Formulations and Additive Manufacturing of Three-Dimensional Scaffolds
Authors: Dogrul Fulden , Ożóg Paulina , Michálek Martin , Elsayed Hamada , Galusek Dušan , Liverani Liliana , Boccaccini Aldo R. , Bernardo Enrico
Published: September 2021

Silicone resins, filled with phosphates and other oxide fillers, yield upon firing in air at 1100 °C, a product resembling Biosilicate® glass-ceramics, one of the most promising systems for tissue engineering applications. The process requires no preliminary synthesis of parent glass, and the polymer route enables the application of direct ink writing (DIW) of silicone-based mixtures, for the manufacturing of reticulated scaffolds at room temperature. The thermal treatment is later applied for the conversion into ceramic scaffolds. The present paper further elucidates the flexibility of the approach. Changes in the reference silicone and firing atmosphere (from air to nitrogen) were studied to obtain functional composite biomaterials featuring a carbon phase embedded in a Biosilicate®-like matrix. The microstructure was further modified either through a controlled gas release at a low temperature, or by the revision of the adopted additive manufacturing technology (from DIW to digital light processing).
Structural, Mechanical, and Decorative Properties of Sputtered TiN and Ti (N, C) Films for Orthodontic Applications; an In Vitro Study
Authors: Suciu Victor , Ferreira Armando , Correa Marcio A. , Vaz Filipe , Munteanu Daniel
Published: September 2021

In this paper, we explore and modify the structural, mechanical, and decorative properties of films composed by TiN and Ti (N, C) with a wide range of N2 gas flow during the deposition in order to be used on orthodontic systems. The films were grown using reactive DC magnetron sputtering from a pure Ti target and customized with C pellets onto Si and stainless steel 316L substrates. The structural properties were studied using X-ray diffraction and scanning electron microscopy, while the mechanical ones were obtained through hardness, elastic modulus, and friction coefficient. Moreover, the wear rate has been measured under an artificial saliva medium to simulate the oral cavity. The color of the films deposited onto stainless steel 316 L substrate was characterized through CIELab color code. Our findings show that the addition of N2 and C in the Ti matrix improves the mechanical properties of the films. With the increase in the amount of N2 and C, the hardness reaches a value of 739 HV, higher than the one reported in the literature (600 HV), a low value of the coefficient of elasticity (8.0 GPa), and also a low friction coefficient (0.30). Moreover, with the addition of N2 and C in the Ti films, the color of the films changes from metallic aspect until “with” gold, which means that our coatings exhibit versatile mechanical and color characteristics to be used in orthodontic wires applications.
Recent Advancements in Carbon Nano-Infused Cementitious Composites
Authors: Goldmann Eryk , Górski Marcin , Klemczak Barbara
Published: September 2021

A rising demand for efficient functional materials brings forth research challenges regarding improvements in existing materials. Carbon infused cementitious composites, regardless of being an important research topic worldwide, still present many questions concerning their functionality and properties. The paper aims to highlight the most important materials used for cementitious composites, their properties, and their uses while also including the most relevant of the latest research in that area.
Multi-Layer Technique (MLT) with Porcine Collagenated Cortical Bone Lamina for Bone Regeneration Procedures and Immediate Post-Extraction Implantation in the Esthetic Area: A Retrospective Case Series with a Mean Follow-Up of 5 Years
Authors: Schuh Paul Leonhard , Wachtel Hannes , Beuer Florian , Goker Funda , Del Fabbro Massimo , Francetti Luca , Testori Tiziano
Published: September 2021

Background: Augmentation of the edentulous atrophic anterior region is a challenging situation. The purpose of this article was to evaluate the effectiveness of a collagenated cortical bone lamina of porcine origin for horizontal ridge augmentation in patients with inadequate alveolar ridge width undergoing immediate post-extraction implantation in the anterior sites, and to report on implant survival rates/complications. Materials and methods: The cases were extracted electronically from a large database according to these specific inclusion criteria: patients with inadequate alveolar ridge width in the anterior maxilla or mandible, who underwent immediate post-extraction implant placement and simultaneous alveolar bone reconstruction using xenogeneic cortical bone lamina. An additional layer of palatal connective tissue graft was inserted between lamina and the vestibular mucosa, for improving soft tissue healing. A collagenated bone substitute was additionally placed in the gap between the lamina and implant surface in all patients. The main outcomes were implant survival and complications. Results: Forty-nine patients with 65 implants were included. Patients’ mean age at the time of implant surgery was 60.0 ± 13.6 years. The mean follow-up was 60.5 ± 26.6 months after implant placement. The implant survival was 100%. Four postoperative complications occurred in four patients. No specific factor was found to be associated with complication occurrence. Conclusion: The use of collagenated cortical bone lamina can be considered as a successful option for alveolar reconstruction in immediate post-extraction implant insertion procedures in anterior regions with inadequate alveolar ridge width.
Estimation of the Compressive Strength of Corrugated Board Boxes with Shifted Creases on the Flaps
Authors: Mrówczyński Damian , Garbowski Tomasz , Knitter-Piątkowska Anna
Published: September 2021

In the modern world, all manufacturers strive for the optimal design of their products. This general trend is recently also observed in the corrugated board packaging industry. Colorful prints on displays, perforations in shelf-ready-packaging and various types of ventilation holes in trays, although extremely important for ergonomic or functional reasons, weaken the strength of the box. To meet the requirements of customers and recipients, packaging manufacturers outdo each other with new ideas for the construction of their products. Often the aesthetic qualities of the product become more important than the attention to maintaining the standards of the load capacity of the packaging (which, apart from their attention-grabbing functions, are also intended to protect transported products). A particular flaps design (both top and bottom) and its influence on the strength of the box are investigated in this study. An updated analytical–numerical approach is used here to predict the strength of packaging with various flap offsets. Experimental results indicated a significant decrease in the static load-bearing capacity of packaging in the case of shifted flap creases. The simulation model proposed in our previous work has been modified and updated to take into account this effect. The results obtained by the model presented in this paper are in satisfactory agreement with the experimental data.
Types of Component Interfaces in Metal Matrix Composites on the Example of Magnesium Matrix Composites
Authors: Braszczyńska-Malik Katarzyna N.
Published: September 2021

In this paper, a summary of investigations of the microstructure of cast magnesium matrix composites is presented. Analyses of the interfaces between the reinforcing particles and the magnesium alloy matrices were performed. Technically pure magnesium and four various alloys with aluminum and rare earth elements (RE) were chosen as the matrix. The composites were reinforced with SiC and Ti particles, as well as hollow aluminosilicate cenospheres. Microstructure analyses were carried out by light, scanning, and transmission electron microscopy. The composites with the matrix of magnesium and magnesium–aluminum alloys with SiC and Ti particles exhibited coherent interfaces between the components. In the composites based on ternary magnesium alloy with Al and RE with Ti particles, a high-melting Al2RE phase nucleated on the titanium. Different types of interfaces between the components were observed in the composites based on the magnesium–rare earth elements alloy with SiC particles, in which a chemical reaction between the components caused formation of the Re3Si2 phase. Intensive chemical reactions between the components were also observed in the composites with aluminosilicate cenospheres. Additionally, the influence of coatings created on the aluminosilicate cenospheres on the bond with the magnesium matrix was presented. A scheme of the types of interfaces between the components is proposed.
Testing the Sandblasting Process in the Manufacturing of Reference Spheres for Non-Contact Metrology Applications
Authors: Meana Víctor , Cuesta Eduardo , Álvarez Braulio J.
Published: September 2021

To ensure that measurements can be made with non-contact metrology technologies, it is necessary to use verification and calibration procedures using precision artefacts as reference elements. In this environment, the need for increasingly accurate but also more cost-effective calibration artefacts is a clear demand in industry. The aim of this work is to demonstrate the feasibility of using low-cost precision spheres as reference artefacts in calibration and verification procedures of non-contact metrological equipment. Specifically, low-cost precision stainless steel spheres are used as reference artefacts. Obviously, for such spheres to be used as standard artefacts, it is necessary to change their optical behavior by removing their high brightness. For this purpose, the spheres are subjected to a manual sandblasting process, which is also a very low-cost process. The equipment used to validate the experiment is a laser triangulation sensor mounted on a Coordinate Measuring Machine (CMM). The CMM touch probe, which is much more accurate, will be used as a device for measuring the influence of sandblasting on the spheres. Subsequently, the influence of this post-processing is also checked with the laser triangulation sensor. Ultimately, the improvement in the quality of the point clouds captured by the laser sensor will be tested after removing the brightness, which distorts and reduces the quantity of points as well as the quality of the point clouds. In addition to the number of points obtained, the parameters used to study the effect of sandblasting on each sphere, both in contact probing and laser scanning, are the measured diameter, the form error, as well as the standard deviation of the point cloud regarding the best-fit sphere.
Performance Testing and Rapid Solidification Behavior of Stainless Steel Powders Prepared by Gas Atomization
Authors: Qi Hang , Zhou Xianglin , Li Jinghao , Hu Yunfei , Xu Lianghui
Published: September 2021

Gas atomization is a widely used method to produce the raw powder materials for additive manufacturing (AM) usage. After the metal alloy is melted to fusion, gas atomization involves two relatively independent processes: liquid breakup and droplet solidification. In this paper, the solidification behavior of powder during solidification is analyzed by testing the powder’s properties and observing microstructure of a martensitic stainless steel (FeCrNiBSiNb). The powder prepared by gas atomization has high sphericity and smooth surface, and the yield of qualified fine powder is 35%. The powder has typical rapid solidification structure. Collision between powders not only promotes nucleation, but also produces more satellite powder. The segregation of elements in powder is smaller as the result of high cooling rate which can reaches 4.2 × 105 K/s in average. Overall, the powder prepared by gas atomization is found to have good comprehensive properties, desired microstructure, and accurate chemical component, and it is suitable for various additive manufacturing techniques.
Review of Magnetic Shape Memory Polymers and Magnetic Soft Materials
Authors: van Vilsteren Sanne J. M. , Yarmand Hooman , Ghodrat Sepideh
Published: September 2021

Magnetic soft materials (MSMs) and magnetic shape memory polymers (MSMPs) have been some of the most intensely investigated newly developed material types in the last decade, thanks to the great and versatile potential of their innovative characteristic behaviors such as remote and nearly heatless shape transformation in the case of MSMs. With regard to a number of properties such as shape recovery ratio, manufacturability, cost or programming potential, MSMs and MSMPs may exceed conventional shape memory materials such as shape memory alloys or shape memory polymers. Nevertheless, MSMs and MSMPs have not yet fully touched their scientific-industrial potential, basically due to the lack of detailed knowledge on various aspects of their constitutive response. Therefore, MSMs and MSMPs have been developed slowly but their importance will undoubtedly increase in the near future. This review emphasizes the development of MSMs and MSMPs with a specific focus on the role of the magnetic particles which affect the shape memory recovery and programming behavior of these materials. In addition, the synthesis and application of these materials are addressed.
Transformational Creativity: The Link between Creativity, Wisdom, and the Solution of Global Problems
Authors: Sternberg Robert J.
Published: September 2021

This article introduces the concept of transformational creativity, which is creativity that is deployed to make a positive, meaningful, and potentially enduring difference to the world. Transformational creativity is compared to transactional creativity, which is creativity deployed in search of a reward, whether externally or internally generated. The article also discusses different kinds of transactional and transformational creativity. For example, some transactional creativity is inert, meaning that it never comes to fruition. Transformational creativity can be directed inward, outward, or both ways. The article also discusses pseudo-transformational creativity, which is offered by the creator as making the world a better place, when in fact its goal is to improve the lot of the person who is pseudo-transformationally creative. Many charismatic leaders are pseudo-transformational autocrats. It is concluded that, at this point in time, the world desperately needs the work of transformationally creative individuals.
Identification of the Temperature Dependence of the Thermal Expansion Coefficient of Polymers
Authors: Shardakov Igor N. , Trufanov Aleksandr N.
Published: September 2021

In this paper, we proposed an approach to study the strain response of polymer film samples under various temperature effects and note their corresponding effects. The advantages of the developed approach are determined by the fact that thin films of material are used as samples where it is possible to generate a sufficiently uniform temperature field in a wide range of temperature change rates. A dynamic mechanical analyzer was used for the experimental implementation of the above approach for two UV-curable polymers and one type of epoxy resin. Experimental results have shown that the thermal expansion coefficients for these polymers depend significantly not only on the temperature but also on its change rate. The strain response of the polymer to heating and cooling, with the same absolute values of the rate of temperature change, differs significantly, and this dissimilarity becomes stronger with its increasing. The results of thermomechanical experiments for massive samples on traditional dilatometer are shown to compare with the results for film samples. The discovered dependences of the temperature expansion coefficient on the temperature and its change rate can be used for mathematical modeling of thermomechanical processes arising during the operation of products made of polymers.
Rheological and Aging Properties of Composite Modified Bitumen by Styrene–Butadiene–Styrene and Desulfurized Crumb Rubber
Authors: Xu Gang , Yu Yunhong , Yang Jingyao , Wang Tianling , Kong Peipei , Chen Xianhua
Published: September 2021

Taking advantage of crumb rubber from waste tires to modify bitumen is widely for the environmentally friendly and sustainable development of pavement. This study investigated the modification mechanism, rheological, and aging properties of styrene–butadiene–styrene (SBS)/desulfurized crumb rubber (DCR) composite modified bitumen (SBS/DCRMB). Morphological features and chemical characteristics were assessed by fluorescence intensity measurement and gel permeation chromatography (GPC), respectively, and results demonstrated that the DCR and SBS modifier in SBS/DCRMB had been vulcanized and formed a three-dimensional network structure. Moreover, a comparison of the GPC elution curve showed the residual bitumen hardly changed due to carbon black released from DCR of SBS/DCRMB during the aging process of SBS/DCRMB, and the polymer molecules condensed to larger units. However, the remaining bitumen in SBSMB had changed evidently and the polymer degraded to smaller molecules. Meanwhile the rheological testing results, including multiple stress creep recovery, linear amplitude sweep and bending beam rheometer, declared that the SBS/DCRMB is superior to SBSMB before and after aging.
Cost Analysis of Various Factors for Geopolymer 3D Printing of Construction Products in Factories and on Construction Sites
Authors: Munir Qaisar , Kärki Timo
Published: September 2021

The utilization of geopolymer 3D printing for construction products in recent years has been exceptionally substantial, owing to their low carbon dioxide emissions, high-performance properties such as durability, and good thermal and mechanical properties. This automated manufacturing process reduces the need for additional formworks, capital investments, and human resources. Geopolymer 3D printing development is emerging because of its advanced use in construction applications. However, high costs of the initial stages of geopolymer production and 3D printing has inhibited the development of this technology in many countries. This research presents a comprehensive economic evaluation of the investment for each principal stage that facilitates a better deployment of the resources. The study investigated all phases of geopolymer production, from the extraction of raw materials to printing. The cost for the four fundamental stages, namely raw material availability and transportation, pretreatments for raw materials, parameter selection and strength requirements, and printing in factories and on construction sites, were analyzed. The results show that 3D printing of a geopolymer on a construction site is economically more advantageous compared to printing in the factory. The study also verified that raw material transportation cost has the least effect on the finished product cost, whereas pretreatments of raw material and mixing parameters significantly influenced the ultimate cost of the product. Finally, research work suggested the need for future tasks to make geopolymer 3D printing a viable construction approach.
Edge-Preserving Convolutional Generative Adversarial Networks for SAR-to-Optical Image Translation
Authors: Guo Jie , He Chengyu , Zhang Mingjin , Li Yunsong , Gao Xinbo , Song Bangyu
Published: September 2021

With the ability for all-day, all-weather acquisition, synthetic aperture radar (SAR) remote sensing is an important technique in modern Earth observation. However, the interpretation of SAR images is a highly challenging task, even for well-trained experts, due to the imaging principle of SAR images and the high-frequency speckle noise. Some image-to-image translation methods are used to convert SAR images into optical images that are closer to what we perceive through our eyes. There exist two weaknesses in these methods: (1) these methods are not designed for an SAR-to-optical translation task, thereby losing sight of the complexity of SAR images and the speckle noise. (2) The same convolution filters in a standard convolution layer are utilized for the whole feature maps, which ignore the details of SAR images in each window and generate images with unsatisfactory quality. In this paper, we propose an edge-preserving convolutional generative adversarial network (EPCGAN) to enhance the structure and aesthetics of the output image by leveraging the edge information of the SAR image and implementing content-adaptive convolution. The proposed edge-preserving convolution (EPC) decomposes the content of the convolution input into texture components and content components and then generates a content-adaptive kernel to modify standard convolutional filter weights for the content components. Based on the EPC, the EPCGAN is presented for SAR-to-optical image translation. It uses a gradient branch to assist in the recovery of structural image information. Experiments on the SEN1-2 dataset demonstrated that the proposed method can outperform other SAR-to-optical methods by recovering more structures and yielding a superior evaluation index.
An Investigation of Extreme Weather Impact on Precipitable Water Vapor and Vegetation Growth—A Case Study in Zhejiang China
Authors: Xiong Si , Guo Fei , Zhao Qingzhi , Huang Liangke , He Lin , Zhang Tengxu
Published: September 2021

Zhejiang province in China experienced an extreme climate phenomenon in August 2014 with temperature rises, sunshine duration decreases, and precipitation increases, particularly, the successive heavy rainfall events occurring from 16 to 20 August 2014 that contributed to this climate anomaly. This study investigates the spatial-temporal variation characteristics of precipitable water vapor (PWV) and the normalized difference vegetation index (NDVI) associated with this phenomenon. Multiple sources of PWV values derived from the Global Positioning System (GPS), Radiosonde (RS) and European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim data are used with different spatiotemporal resolutions. The monthly averaged PWV in August 2014 exceeded the 95% percentiles of climatological value (53 mm) while the monthly averaged temperature was less than the 5% percentiles of climatological value (26.6 °C). Before the extreme precipitation, the PWV increased from the yearly averaged value of about 35 mm to more than 60 mm and gradually returned to the August climatological average of 50 mm after the precipitation ended. A large-scale atmospheric water vapor was partially conveyed by the warm wet air current of anticyclones which originated over the South China Sea (25° N, 130° E) and the Western Pacific Ocean. The monthly NDVI variation over the past 34 years (1982–2015) was investigated in this paper and the significant impact of extreme climate on vegetation growth in August 2014 was found. The extreme negative temperature anomaly and positive PWV anomaly are the major climate-driven factors affecting vegetation growth in the north and south of Zhejiang province with correlation coefficients of 0.83 and 0.72, respectively, while the extreme precipitation does not show any apparent impact on NDVI.
A Method for Reducing Timing Jitter’s Impact in Through-Wall Human Detection by Ultra-Wideband Impulse Radar
Authors: Shi Cheng , Ni Zhi-Kang , Pan Jun , Zheng Zhijie , Ye Shengbo , Fang Guangyou
Published: September 2021

Ultra-wideband (UWB) impulse radar is widely used for through-wall human respiration detection due to its high range resolution and high penetration capability. UWB impulse radar emits very narrow time pulses, which can directly obtain the impulse response of the target. However, the time interval between successive pulses emitted is not ideally fixed because of timing jitter. This results in the impulse response position of the same target not being fixed, but it is related to slow-time. The clutter scattered by the stationary target becomes non-stationary clutter, which affects the accurate extraction of the human respiration signal. In this paper, we propose a method for reducing timing jitter’s impact in through-wall human detection by UWB impulse radar. After the received signal is processed by the Fast Fourier transform (FFT) in slow-time, we model the range-frequency matrix in the frequency domain as a superposition of the low-rank representation of jitter-induced clutter data and the sparse representation of human respiratory data. By only extracting the sparse component, the impact of timing jitter in human respiration detection can be reduced. Both numerical simulated data and experimental data demonstrate that our proposed method can effectively remove non-stationary clutter induced by timing jitter and improve the accuracy of the human target signal extraction.
Decision-Level Fusion with a Pluginable Importance Factor Generator for Remote Sensing Image Scene Classification
Authors: Shen Junge , Zhang Chi , Zheng Yu , Wang Ruxin
Published: September 2021

Remote sensing image scene classification acts as an important task in remote sensing image applications, which benefits from the pleasing performance brought by deep convolution neural networks (CNNs). When applying deep models in this task, the challenges are, on one hand, that the targets with highly different scales may exist in the image simultaneously and the small targets could be lost in the deep feature maps of CNNs; and on the other hand, the remote sensing image data exhibits the properties of high inter-class similarity and high intra-class variance. Both factors could limit the performance of the deep models, which motivates us to develop an adaptive decision-level information fusion framework that can incorporate with any CNN backbones. Specifically, given a CNN backbone that predicts multiple classification scores based on the feature maps of different layers, we develop a pluginable importance factor generator that aims at predicting a factor for each score. The factors measure how confident the scores in different layers are with respect to the final output. Formally, the final score is obtained by a class-wise and weighted summation based on the scores and the corresponding factors. To reduce the co-adaptation effect among the scores of different layers, we propose a stochastic decision-level fusion training strategy that enables each classification score to randomly participate in the decision-level fusion. Experiments on four popular datasets including the UC Merced Land-Use dataset, the RSSCN 7 dataset, the AID dataset, and the NWPU-RESISC 45 dataset demonstrate the superiority of the proposed method over other state-of-the-art methods.
Digital Elevation Models: Terminology and Definitions
Authors: Guth Peter L. , Van Niekerk Adriaan , Grohmann Carlos H. , Muller Jan-Peter , Hawker Laurence , Florinsky Igor V. , Gesch Dean , Reuter Hannes I. , Herrera-Cruz Virginia , Riazanoff Serge , López-Vázquez Carlos , Carabajal Claudia C. , Albinet Clément , Strobl Peter
Published: September 2021

Digital elevation models (DEMs) provide fundamental depictions of the three-dimensional shape of the Earth’s surface and are useful to a wide range of disciplines. Ideally, DEMs record the interface between the atmosphere and the lithosphere using a discrete two-dimensional grid, with complexities introduced by the intervening hydrosphere, cryosphere, biosphere, and anthroposphere. The treatment of DEM surfaces, affected by these intervening spheres, depends on their intended use, and the characteristics of the sensors that were used to create them. DEM is a general term, and more specific terms such as digital surface model (DSM) or digital terrain model (DTM) record the treatment of the intermediate surfaces. Several global DEMs generated with optical (visible and near-infrared) sensors and synthetic aperture radar (SAR), as well as single/multi-beam sonars and products of satellite altimetry, share the common characteristic of a georectified, gridded storage structure. Nevertheless, not all DEMs share the same vertical datum, not all use the same convention for the area on the ground represented by each pixel in the DEM, and some of them have variable data spacings depending on the latitude. This paper highlights the importance of knowing, understanding and reflecting on the sensor and DEM characteristics and consolidates terminology and definitions of key concepts to facilitate a common understanding among the growing community of DEM users, who do not necessarily share the same background.
Machine Learning Analysis for Phenolic Compound Monitoring Using a Mobile Phone-Based ECL Sensor
Authors: Taylor Joseph , Ccopa-Rivera Elmer , Kim Solomon , Campbell Reise , Summerscales Rodney , Kwon Hyun
Published: September 2021

Machine learning (ML) can be an appropriate approach to overcoming common problems associated with sensors for low-cost, point-of-care diagnostics, such as non-linearity, multidimensionality, sensor-to-sensor variations, presence of anomalies, and ambiguity in key features. This study proposes a novel approach based on ML algorithms (neural nets, Gaussian Process Regression, among others) to model the electrochemiluminescence (ECL) quenching mechanism of the [Ru(bpy)3]2+/TPrA system by phenolic compounds, thus allowing their detection and quantification. The relationships between the concentration of phenolic compounds and their effect on the ECL intensity and current data measured using a mobile phone-based ECL sensor is investigated. The ML regression tasks with a tri-layer neural net using minimally processed time series data showed better or comparable detection performance compared to the performance using extracted key features without extra preprocessing. Combined multimodal characteristics produced an 80% more enhanced performance with multilayer neural net algorithms than a single feature based-regression analysis. The results demonstrated that the ML could provide a robust analysis framework for sensor data with noises and variability. It demonstrates that ML strategies can play a crucial role in chemical or biosensor data analysis, providing a robust model by maximizing all the obtained information and integrating nonlinearity and sensor-to-sensor variations.
Erratum: Wei et al. Tilted-Beam Antenna Based on SSPPs-TL with Stable Gain. Sensors 2021, 21, 3288
Authors: Wei Dujuan , Geng Youlin , Zhang Pengquan , Zhang Zhonghai , Yin Chuan
Published: September 2021

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Hybrid Active-and-Passive Relaying Model for 6G-IoT Greencom Networks with SWIPT
Authors: Gautam Sumit , Solanki Sourabh , Sharma Shree Krishna , Chatzinotas Symeon , Ottersten Björn
Published: September 2021

In order to support a massive number of resource-constrained Internet-of-Things (IoT) devices and machine-type devices, it is crucial to design a future beyond 5G/6G wireless networks in an energy-efficient manner while incorporating suitable network coverage expansion methodologies. To this end, this paper proposes a novel two-hop hybrid active-and-passive relaying scheme to facilitate simultaneous wireless information and power transfer (SWIPT) considering both time-switching (TS) and power-splitting (PS) receiver architectures, while dynamically modelling the involved dual-hop time-period (TP) metric. An optimization problem is formulated to jointly optimize the throughput, harvested energy, and transmit power of a SWIPT-enabled system with the proposed hybrid scheme. In this regard, we provide two distinct ways to obtain suitable solutions based on the Lagrange dual technique and Dinkelbach method assisted convex programming, respectively, where both the approaches yield an appreciable solution within polynomial computational time. The experimental results are obtained by directly solving the primal problem using a non-linear optimizer. Our numerical results in terms of weighted utility function show the superior performance of the proposed hybrid scheme over passive repeater-only and active relay-only schemes, while also depicting their individual performance benefits over the corresponding benchmark SWIPT systems with the fixed-TP.
Identification of Ictal Tachycardia in Focal Motor- and Non-Motor Seizures by Means of a Wearable PPG Sensor
Authors: Glasstetter Martin , Böttcher Sebastian , Zabler Nicolas , Epitashvili Nino , Dümpelmann Matthias , Richardson Mark P. , Schulze-Bonhage Andreas
Published: September 2021

Photoplethysmography (PPG) as an additional biosignal for a seizure detector has been underutilized so far, which is possibly due to its susceptibility to motion artifacts. We investigated 62 focal seizures from 28 patients with electrocardiography-based evidence of ictal tachycardia (IT). Seizures were divided into subgroups: those without epileptic movements and those with epileptic movements not affecting and affecting the extremities. PPG-based heart rate (HR) derived from a wrist-worn device was calculated for sections with high signal quality, which were identified using spectral entropy. Overall, IT based on PPG was identified in 37 of 62 (60%) seizures (9/19, 7/8, and 21/35 in the three groups, respectively) and could be found prior to the onset of epileptic movements affecting the extremities in 14/21 seizures. In 30/37 seizures, PPG-based IT was in good temporal agreement (<10 s) with ECG-based IT, with an average delay of 5.0 s relative to EEG onset. In summary, we observed that the identification of IT by means of a wearable PPG sensor is possible not only for non-motor seizures but also in motor seizures, which is due to the early manifestation of IT in a relevant subset of focal seizures. However, both spontaneous and epileptic movements can impair PPG-based seizure detection.
A Blockchain-Based Multi-Factor Authentication Model for a Cloud-Enabled Internet of Vehicles
Authors: Kebande Victor R. , Awaysheh Feras M. , Ikuesan Richard A. , Alawadi Sadi A. , Alshehri Mohammad Dahman
Published: September 2021

Continuous and emerging advances in Information and Communication Technology (ICT) have enabled Internet-of-Things (IoT)-to-Cloud applications to be induced by data pipelines and Edge Intelligence-based architectures. Advanced vehicular networks greatly benefit from these architectures due to the implicit functionalities that are focused on realizing the Internet of Vehicle (IoV) vision. However, IoV is susceptible to attacks, where adversaries can easily exploit existing vulnerabilities. Several attacks may succeed due to inadequate or ineffective authentication techniques. Hence, there is a timely need for hardening the authentication process through cutting-edge access control mechanisms. This paper proposes a Blockchain-based Multi-Factor authentication model that uses an embedded Digital Signature (MFBC_eDS) for vehicular clouds and Cloud-enabled IoV. Our proposed MFBC_eDS model consists of a scheme that integrates the Security Assertion Mark-up Language (SAML) to the Single Sign-On (SSO) capabilities for a connected edge to cloud ecosystem. MFBC_eDS draws an essential comparison with the baseline authentication scheme suggested by Karla and Sood. Based on the foundations of Karla and Sood’s scheme, an embedded Probabilistic Polynomial-Time Algorithm (ePPTA) and an additional Hash function for the Pi generated during Karla and Sood’s authentication were proposed and discussed. The preliminary analysis of the proposition shows that the approach is more suitable to counter major adversarial attacks in an IoV-centered environment based on the Dolev–Yao adversarial model while satisfying aspects of the Confidentiality, Integrity, and Availability (CIA) triad.
Biometric Identification Based on Eye Movement Dynamic Features
Authors: Harezlak Katarzyna , Blasiak Michal , Kasprowski Pawel
Published: September 2021

The paper presents studies on biometric identification methods based on the eye movement signal. New signal features were investigated for this purpose. They included its representation in the frequency domain and the largest Lyapunov exponent, which characterizes the dynamics of the eye movement signal seen as a nonlinear time series. These features, along with the velocities and accelerations used in the previously conducted works, were determined for 100-ms eye movement segments. 24 participants took part in the experiment, composed of two sessions. The users’ task was to observe a point appearing on the screen in 29 locations. The eye movement recordings for each point were used to create a feature vector in two variants: one vector for one point and one vector including signal for three consecutive locations. Two approaches for defining the training and test sets were applied. In the first one, 75% of randomly selected vectors were used as the training set, under a condition of equal proportions for each participant in both sets and the disjointness of the training and test sets. Among four classifiers: kNN (k = 5), decision tree, naïve Bayes, and random forest, good classification performance was obtained for decision tree and random forest. The efficiency of the last method reached 100%. The outcomes were much worse in the second scenario when the training and testing sets when defined based on recordings from different sessions; the possible reasons are discussed in the paper.
Monitoring the Cortical Activity of Children and Adults during Cognitive Task Completion
Authors: Khramova Marina V. , Kuc Alexander K. , Maksimenko Vladimir A. , Frolov Nikita S. , Grubov Vadim V. , Kurkin Semen A. , Pisarchik Alexander N. , Shusharina Natalia N. , Fedorov Alexander A. , Hramov Alexander E.
Published: September 2021

In this paper, we used an EEG system to monitor and analyze the cortical activity of children and adults at a sensor level during cognitive tasks in the form of a Schulte table. This complex cognitive task simultaneously involves several cognitive processes and systems: visual search, working memory, and mental arithmetic. We revealed that adults found numbers on average two times faster than children in the beginning. However, this difference diminished at the end of table completion to 1.8 times. In children, the EEG analysis revealed high parietal alpha-band power at the end of the task. This indicates the shift from procedural strategy to less demanding fact-retrieval. In adults, the frontal beta-band power increased at the end of the task. It reflects enhanced reliance on the top–down mechanisms, cognitive control, or attentional modulation rather than a change in arithmetic strategy. Finally, the alpha-band power of adults exceeded one of the children in the left hemisphere, providing potential evidence for the fact-retrieval strategy. Since the completion of the Schulte table involves a whole set of elementary cognitive functions, the obtained results were essential for developing passive brain–computer interfaces for monitoring and adjusting a human state in the process of learning and solving cognitive tasks of various types.
Site Investigations of the Lacustrine Clay in Taihu Lake, China, Using Self-Boring Pressuremeter Test
Authors: Wang Bin , Liu Kang , Wang Yong , Jiang Quan
Published: September 2021

Site investigations of the soils are considered very important for evaluation of the site conditions, as well as the design and construction for the project built in it. Taihu tunnel is thus far the longest tunnel constructed in the lake in China, with an entire length of over 10 km. However, due to the very insufficient site data obtained for the lacustrine clay in the Taihu lake area, a series of self-boring pressuremeter (SBPM) field tests was therefore carried out. Undrained shear strengths were deduced from the SBPM test, with the results showing generally higher than those obtained from the laboratory tests, which may be attributed to the disturbance to the soil mass during the sampling process. Degradation characteristics of the soil shear modulus (Gs) were mainly investigated, via a thorough comparison between different soil layers, and generally, the shear modulus would cease its decreasing trends and become stable when the shear strain reaches over 1%. Meanwhile, it was found that a linear relationship between the plasticity index and the shear modulus, and between the decay rate of the shear modulus and the plasticity index as well, could be developed. Further statistical analysis over the undrained shear strength and shear modulus distribution of the soils shows that the undrained shear strength of the soils follows a normal distribution, while the shear modulus follows a log-normal distribution. More importantly, the spatial correlation length of the shear modulus is found much smaller than that of the undrained strength.
HalluciNet-ing Spatiotemporal Representations Using a 2D-CNN
Authors: Parmar Paritosh , Morris Brendan
Published: September 2021

Spatiotemporal representations learned using 3D convolutional neural networks (CNN) are currently used in state-of-the-art approaches for action-related tasks. However, 3D-CNN are notorious for being memory and compute resource intensive as compared with more simple 2D-CNN architectures. We propose to hallucinate spatiotemporal representations from a 3D-CNN teacher with a 2D-CNN student. By requiring the 2D-CNN to predict the future and intuit upcoming activity, it is encouraged to gain a deeper understanding of actions and how they evolve. The hallucination task is treated as an auxiliary task, which can be used with any other action-related task in a multitask learning setting. Thorough experimental evaluation, it is shown that the hallucination task indeed helps improve performance on action recognition, action quality assessment, and dynamic scene recognition tasks. From a practical standpoint, being able to hallucinate spatiotemporal representations without an actual 3D-CNN can enable deployment in resource-constrained scenarios, such as with limited computing power and/or lower bandwidth. We also observed that our hallucination task has utility not only during the training phase, but also during the pre-training phase.