bluuebunny/crossref_metadata_2025 huggingface dataset:
Biphasic Production of Anti-ApoB100 Autoantibodies in Obese Humans and Mice
Authors: Choe Moon Kyung , Kim Hyung-Ji , Kim Nan Hee , Binas Bert , Kim Hyo Joon
Published: April 2021

Obesity is associated with autoimmunity, a phenomenon considered as harmful. Here we show that obese mice and humans produce IgG-type autoantibodies that specifically recognize apolipoprotein B-100 (ApoB100), its native epitope p210, and the synthetic p210 mimotope pB1. By contrast, antibodies against epitopes p45 and p240, which have been associated with atherosclerosis, were not detected in either the humans or mice. In a longitudinal analysis of high fat diet-fed mice, autoantibody production rose with increasing body weight, then decreased and plateaued at morbid obesity. Likewise, in a cross-sectional analysis of sera from 148 human volunteers spanning a wide BMI range and free of comorbidities, the immunoreactivity increased and then decreased with increasing BMI. Thus, the obesity-related ApoB100-specific natural autoantibodies characteristically showed the same epitope recognition, IgG-type, and biphasic serum levels in humans and mice. We previously reported that a pB1-based vaccine induces similar antibodies and can prevent obesity in mice. Therefore, our present results suggest that autoantibodies directed against native ApoB100 may mitigate obesity, and that the vaccination approach may be effective in humans.
Bacteriophages as Potential Tools for Use in Antimicrobial Therapy and Vaccine Development
Authors: Zalewska-Piątek Beata , Piątek Rafał
Published: April 2021

The constantly growing number of people suffering from bacterial, viral, or fungal infections, parasitic diseases, and cancers prompts the search for innovative methods of disease prevention and treatment, especially based on vaccines and targeted therapy. An additional problem is the global threat to humanity resulting from the increasing resistance of bacteria to commonly used antibiotics. Conventional vaccines based on bacteria or viruses are common and are generally effective in preventing and controlling various infectious diseases in humans. However, there are problems with the stability of these vaccines, their transport, targeted delivery, safe use, and side effects. In this context, experimental phage therapy based on viruses replicating in bacterial cells currently offers a chance for a breakthrough in the treatment of bacterial infections. Phages are not infectious and pathogenic to eukaryotic cells and do not cause diseases in human body. Furthermore, bacterial viruses are sufficient immuno-stimulators with potential adjuvant abilities, easy to transport, and store. They can also be produced on a large scale with cost reduction. In recent years, they have also provided an ideal platform for the design and production of phage-based vaccines to induce protective host immune responses. The most promising in this group are phage-displayed vaccines, allowing for the display of immunogenic peptides or proteins on the phage surfaces, or phage DNA vaccines responsible for expression of target genes (encoding protective antigens) incorporated into the phage genome. Phage vaccines inducing the production of specific antibodies may in the future protect us against infectious diseases and constitute an effective immune tool to fight cancer. Moreover, personalized phage therapy can represent the greatest medical achievement that saves lives. This review demonstrates the latest advances and developments in the use of phage vaccines to prevent human infectious diseases; phage-based therapy, including clinical trials; and personalized treatment adapted to the patient’s needs and the type of bacterial infection. It highlights the advantages and disadvantages of experimental phage therapy and, at the same time, indicates its great potential in the treatment of various diseases, especially those resistant to commonly used antibiotics. All the analyses performed look at the rich history and development of phage therapy over the past 100 years.
Establishment of a Rapid Micropropagation System for Kaempferia parviflora Wall. Ex Baker: Phytochemical Analysis of Leaf Extracts and Evaluation of Biological Activities
Authors: Park Han-Yong , Kim Kyung-Su , Ak Gunes , Zengin Gokhan , Cziáky Zoltán , Jekő József , Adaikalam Kathalingam , Song Kihwan , Kim Doo-Hwan , Sivanesan Iyyakkannu
Published: April 2021

This study aimed to establish a rapid in vitro plant regeneration method from rhizome buds of Kaempferia parviflora to obtain the valuable secondary metabolites with antioxidant and enzyme inhibition properties. The disinfection effect of silver oxide nanoparticles (AgO NPs) on rhizome and effects of plant growth regulators on shoot multiplication and subsequent rooting were investigated. Surface sterilization of rhizome buds with sodium hypochlorite was insufficient to control contamination. However, immersing rhizome buds in 100 mg L−1 AgO NPs for 60 min eliminated contamination without affecting the survival of explants. The number of shoots (12.2) produced per rhizome bud was higher in Murashige and Skoog (MS) medium containing 8 µM of 6-Benzyladenine (6-BA) and 0.5 µM of Thidiazuron (TDZ) than other treatments. The highest number of roots (24), with a mean root length of 7.8 cm and the maximum shoot length (9.8 cm), were obtained on medium MS with 2 µM of Indole-3-butyric acid (IBA). A survival rate of 98% was attained when plantlets of K. parviflora were acclimatized in a growth room. Liquid chromatography with tandem mass spectrometry (LC-MS/MS) was used to determine the chemical profile of K. parviflora leaf extracts. Results showed that several biologically active flavonoids reported in rhizomes were also present in leaf tissues of both in vitro cultured and ex vitro (greenhouse-grown) plantlets of K. parviflora. We found 40 and 36 compounds in in vitro cultured and ex vitro grown leaf samples, respectively. Greenhouse leaves exhibited more potent antioxidant activities than leaves from in vitro cultures. A higher acetylcholinesterase inhibitory ability was obtained for greenhouse leaves (1.07 mg/mL). However, leaves from in vitro cultures exhibited stronger butyrylcholinesterase inhibitory abilities. These results suggest that leaves of K. parviflora, as major byproducts of black ginger cultivation, could be used as valuable alternative sources for extracting bioactive compounds.
Overexpression of Type 1 and 2 Diacylglycerol Acyltransferase Genes (JcDGAT1 and JcDGAT2) Enhances Oil Production in the Woody Perennial Biofuel Plant Jatropha curcas
Authors: Zhang Tian-Tian , He Huiying , Xu Chuan-Jia , Fu Qiantang , Tao Yan-Bin , Xu Ronghua , Xu Zeng-Fu
Published: April 2021

Diacylglycerol acyltransferase (DGAT) is the only enzyme that catalyzes the acyl-CoA-dependent acylation of sn-1, 2-diacylglycerol (DAG) to form triacylglycerol (TAG). The two main types of DGAT enzymes in the woody perennial biofuel plant Jatropha curcas, JcDGAT1 and JcDGAT2, were previously characterized only in heterologous systems. In this study, we investigated the functions of JcDGAT1 and JcDGAT2 in J. curcas.JcDGAT1 and JcDGAT2 were found to be predominantly expressed during the late stages of J. curcas seed development, in which large amounts of oil accumulated. As expected, overexpression of JcDGAT1 or JcDGAT2 under the control of the CaMV35S promoter gave rise to an increase in seed kernel oil production, reaching a content of 53.7% and 55.7% of the seed kernel dry weight, respectively, which were respectively 25% and 29.6% higher than that of control plants. The increase in seed oil content was accompanied by decreases in the contents of protein and soluble sugars in the seeds. Simultaneously, there was a two- to four-fold higher leaf TAG content in transgenic plants than in control plants. Moreover, by analysis of the fatty acid (FA) profiles, we found that JcDGAT1 and JcDGAT2 had the same substrate specificity with preferences for C18:2 in seed TAGs, and C16:0, C18:0, and C18:1 in leaf TAGs. Therefore, our study confirms the important role of JcDGAT1 and JcDGAT2 in regulating oil production in J. curcas.
A New Species of Argophyllum (Argophyllaceae) with Notes on the Species from New Caledonia and Nickel Hyperaccumulation
Authors: Pillon Yohan , Hequet Vanessa
Published: April 2021

The taxonomy of Argophyllum (Argophyllaceae) in New Caledonia is reviewed here. All names validly published in Argophyllum in this archipelago are discussed and lectotypified when necessary. A new species is described, Argophyllum riparium (The LSID for the name Argophyllum riparium is: 77216335-1) Pillon and Hequet sp. nov. Argophyllum grunowii and A. ellipticum are both species complexes in which several species previously recognized are included here as well. Seven species are recognized in New Caledonia: A. brevipetalum, A. ellipticum, A. grunowii, A. montanum, A. nitidum, A. riparium and A. vernicosum, all endemic. Leaf nickel content of A. riparium can exceed 1000 μg·g−1, which makes this species a nickel hyperaccumulator. Measurements with a handheld X-Ray Fluorescence (XRF) spectrometer confirmed that this was also the case for all other species from New Caledonia, except A. nitidum. An identification key of New Caledonian species is provided.
Generation of a Metal Ion Beam Using a Vacuum Magnetron Discharge
Authors: Vizir Alexey V. , Oks Efim M. , Shandrikov Maxim V. , Yushkov Georgy Yu.
Published: April 2021

We have designed, fabricated and characterized an ion source based on a vacuum magnetron discharge. The magnetron discharge is initiated by a vacuum arc discharge, the plasma of which flows onto the magnetron sputtering target working surface. The vacuum arc material is usually the same as that of the magnetron target. The discharges operate at a residual pressure of 3 × 10−6 Torr without working gas feed. Pulses of vacuum arc (30 μs) and magnetron discharge (up to 300 μs) are applied simultaneously. After ignition by the vacuum arc, the magnetron discharge runs in a self-sustained mode. Cu–Cu, Ag–Ag, Zn–Zn, and Pb–Pb pairs of magnetron target material and vacuum arc cathode material were tested, as well as mixed pairs; for example, Cu vacuum arc cathode and Pb magnetron target. An ion beam was extracted from the discharge plasma by applying an accelerating voltage of up to 20 kV between the plasma expander and grounded electrodes. The ion beam collector current reached 80 mA. The ion beam composition, analyzed by a time-of-flight spectrometer, shows that the beam consists mainly of singly-charged (about 90%) and doubly-charged (about 10% current fraction) magnetron target material ions. The ion beam radial current density non-uniformity was as low as ±5% over a diameter of 6.6 cm, which is the diameter of the source output aperture.
The Double-Faced Electrostatic Behavior of PNIPAm Microgels
Authors: Sennato Simona , Chauveau Edouard , Casciardi Stefano , Bordi Federico , Truzzolillo Domenico
Published: April 2021

PNIPAm microgels synthesized via free radical polymerization (FRP) are often considered as neutral colloids in aqueous media, although it is well known, since the pioneering works of Pelton and coworkers, that the vanishing electrophoretic mobility characterizing swollen microgels largely increases above the lower critical solution temperature (LCST) of PNIPAm, at which microgels partially collapse. The presence of an electric charge has been attributed to the ionic initiators that are employed when FRP is performed in water and that stay anchored to microgel particles. Combining dynamic light scattering (DLS), electrophoresis, transmission electron microscopy (TEM) and atomic force microscopy (AFM) experiments, we show that collapsed ionic PNIPAm microgels undergo large mobility reversal and reentrant condensation when they are co-suspended with oppositely charged polyelectrolytes (PE) or nanoparticles (NP), while their stability remains unaffected by PE or NP addition at lower temperatures, where microgels are swollen and their charge density is low. Our results highlight a somehow double-faced electrostatic behavior of PNIPAm microgels due to their tunable charge density: they behave as quasi-neutral colloids at temperature below LCST, while they strongly interact with oppositely charged species when they are in their collapsed state. The very similar phenomenology encountered when microgels are surrounded by polylysine chains and silica nanoparticles points to the general character of this twofold behavior of PNIPAm-based colloids in water.
Synthesis, Optical, Chemical and Thermal Characterizations of PMMA-PS/CeO2 Nanoparticles Thin Film
Authors: Bani-Salameh Areen A. , Ahmad A. A. , Alsaad A. M. , Qattan I. A. , Aljarrah Ihsan A.
Published: April 2021

We report the synthesis of hybrid thin films based on polymethyl methacrylate) (PMMA) and polystyrene (PS) doped with 1%, 3%, 5%, and 7% of cerium dioxide nanoparticles (CeO2 NPs). The As-prepared thin films of (PMMA-PS) incorporated with CeO2 NPs are deposited on a glass substrate. The transmittance T% (λ) and reflectance R% (λ) of PMMA-PS/CeO2 NPs thin films are measured at room temperature in the spectral range (250–700) nm. High transmittance of 87% is observed in the low-energy regions. However, transmittance decreases sharply to a vanishing value in the high-energy region. In addition, as the CeO2 NPs concentration is increased, a red shift of the absorption edge is clearly observed suggesting a considerable decrease in the band gap energy of PMMA-PS/CeO2 NPs thin film. The optical constants (n and k) and related key optical and optoelectronic parameters of PMMA-PS/Ce NPs thin films are reported and interpreted. Furthermore, Tauc and Urbach models are employed to elucidate optical behavior and calculate the band gaps of the as-synthesized nanocomposite thin films. The optical band gap energy of PMMA-PS thin film is found to be 4.03 eV. Optical band gap engineering is found to be possible upon introducing CeO2 NPs into PMMA-PS polymeric thin films as demonstrated clearly by the continuous decrease of optical band gap upon increasing CeO2 content. Fourier-transform infrared spectroscopy (FTIR) analysis is conducted to identify the major vibrational modes of the nanocomposite. The peak at 541.42 cm−1 is assigned to Ce–O and indicates the incorporation of CeO2 NPs into the copolymers matrices. There were drastic changes to the width and intensity of the vibrational bands of PMMA-PS upon addition of CeO2 NPs. To examine the chemical and thermal stability, thermogravimetric (TGA) thermograms are measured. We found that (PMMA-PVA)/CeO2 NPs nanocomposite thin films are thermally stable below 110 °C. Therefore, they could be key candidate materials for a wide range of scaled multifunctional smart optical and optoelectronic devices.
Synthesis, Characterization of Chitosan-Aluminum Oxide Nanocomposite for Green Synthesis of Annulated Imidazopyrazol Thione Derivatives
Authors: Abdel-Naby Abir S. , Nabil Sara , Aldulaijan Sarah , Ababutain Ibtisam M. , Alghamdi Azzah I. , Almubayedh Somaiah , Khalil Khaled D.
Published: April 2021

Chitosan-aluminum oxide nanocomposite was synthesized, characterized, and used as a green heterogeneous catalyst to synthesize novel imidazopyrazolylthione derivatives. Nanocomposite polymeric material was characterized by EDS-SEM and XRD. The powerful catalytic activity, and its base character of the nanocomposite, was used to synthesize imidazopyrazolylthione (1) in a good yield compared to traditional cyclocondensation synthesis. Using the nanocomposite catalyst, substitution of the thiol group (1) afforded the corresponding thiourea (2) and the corresponding ester (3). The efficiency of the nanocomposite over the traditional base organic catalyst, Et3N and NaOH, makes it an effective, economic, and reproducible nontoxic catalyst. Moreover, the heterogeneous nanocomposite polymeric film was easily isolated from the reaction medium, and recycled up to four times, without a significant loss of its catalytic activity. The newly synthesized derivatives were screened as antibacterial agents and showed high potency. Molecular docking was also performed for a more in-depth investigation. The results of the docking studies have demonstrated that the docked compounds have strong interaction energies with both Gram-positive and Gram-negative bacteria.
An Integrated Multicriteria Decision-Making Approach for Collection Modes Selection in Remanufacturing Reverse Logistics
Authors: Zhang Xumei , Li Zhizhao , Wang Yan , Yan Wei
Published: April 2021

Reverse logistics (RL) is closely related to remanufacturing and could have a profound impact on the remanufacturing industry. Different from sustainable development which is focused on economy, environment and society, circular economy (CE) puts forward more requirements on the circularity and resource efficiency of manufacturing industry. In order to select the best reverse logistics provider for remanufacturing, a multicriteria decision-making (MCDM) method considering the circular economy is proposed. In this article, a circularity dimension is included in the evaluation criteria. Then, analytic hierarchy process (AHP) is used to calculate the global weights of each criterion, which are used as the parameters in selecting RL providers. Finally, technique for order of preference by similarity to ideal solution (TOPSIS) is applied to rank reverse logistics providers with three different modes. A medium-sized engine manufacturer in China is taken as a case study to validate the applicability and effectiveness of the proposed framework.
The Potential of Fibroblast Transdifferentiation to Neuron Using Hydrogels
Authors: Kantawong Fahsai
Published: April 2021

Currently there is a big drive to generate neurons from differentiated cells which would be of great benefit for regenerative medicine, tissue engineering and drug screening. Most studies used transcription factors, epigenetic reprogramming and/or chromatin remodeling drugs which might reflect incomplete reprogramming or progressive deregulation of the new program. In this review, we present a potential different method for cellular reprogramming/transdifferentiation to potentially enhance regeneration of neurons. We focus on the use of biomaterials, specifically hydrogels, to act as non-invasive tools to direct transdifferentiation, and we draw parallel with existing transcriptional and epigenetic methods. Hydrogels are attractive materials because the properties of hydrogels can be modified, and various natural and synthetic substances can be employed. Incorporation of extracellular matrix (ECM) substances and composite materials allows mechanical properties and degradation rate to be controlled. Moreover, hydrogels in combinations with other physical and mechanical stimuli such as electric current, shear stress and tensile force will be mentioned in this review.
Emulsion Formation and Stabilizing Properties of Olive Oil Cake Crude Extracts
Authors: Fainassi Firdaous , Taarji Noamane , Benkhalti Fatiha , Hafidi Abdellatif , Neves Marcos A. , Isoda Hiroko , Nakajima Mitsutoshi
Published: April 2021

The surface-active and emulsifying properties of crude aqueous ethanolic extracts from untreated olive oil cake (OOC) were investigated. OOC extracts contained important concentrations of surface-active components including proteins, saponins and polyphenols (1.2–2.8%, 7.8–9.5% and 0.7–4.5% (w/w), respectively) and reduced the interfacial tension by up to 46% (14.0 ± 0.2 mN m−1) at the oil–water interface. The emulsifying ability of OOC extracts was not correlated, however, with their interfacial activity or surface-active composition. Eighty percent aqueous ethanol extract produced the most stable oil-in-water (O/W) emulsions by high-pressure homogenization. The emulsions had average volume mean droplet diameters of approximately 0.4 µm and negative ζ-potentials of about −45 mV, and were stable for up to 1 month of storage at 5, 25 and 50 °C. They were sensitive, however, to acidic pH conditions (<5) and NaCl addition (≥25 mM), indicating that the main stabilization mechanism is electrostatic due to the presence of surface-active compounds with ionizable groups, such as saponins.
Building and Rebuilding Buddhist Monasteries in Tang China: The Reconstruction of the Kaiyuan Monastery in Sizhou
Authors: Sokolova Anna
Published: April 2021

This article explores regional Buddhist monasteries in Tang Dynasty (618–907 CE) China, including their arrangement, functions, and sources for their study. Specifically, as a case study, it considers the reconstruction of the Kaiyuan monastery 開元寺 in Sizhou 泗州 (present-day Jiangsu Province) with reference to the works of three prominent state officials and scholars: Bai Juyi 白居易 (772–846), Li Ao 李翱 (772–841), and Han Yu 韓愈 (768–824). The writings of these literati allow us to trace the various phases of the monastery’s reconstruction, fundraising activities, and the network of individuals who participated in the project. We learn that the rebuilt multi-compound complex not only provided living areas for masses of pilgrims, traders, and workers but also functioned as a barrier that protected the populations of Sizhou and neighboring prefectures from flooding. Moreover, when viewed from a broader perspective, the renovation of the Kaiyuan monastery demonstrates that Buddhist construction projects played a pivotal role in the social and economic development of Tang China’s major metropolises as well as its regions.
An Introduction to Patterns for the Internet of Robotic Things in the Ambient Assisted Living Scenario
Authors: Andò Bruno , Cantelli Luciano , Catania Vincenzo , Crispino Ruben , Guastella Dario Calogero , Monteleone Salvatore , Muscato Giovanni
Published: April 2021

The Internet of Things paradigm envisions the interoperation among objects, people, and their surrounding environment. In the last decade, the spread of IoT-based solutions has been supported in various domains and scenarios by academia, industry, and standards-setting organizations. The wide variety of applications and the need for a higher level of autonomy and interaction with the environment have recently led to the rise of the Internet of Robotic Things (IoRT), where smart objects become autonomous robotic systems. As mentioned in the recent literature, many of the proposed solutions in the IoT field have to tackle similar challenges regarding the management of resources, interoperation among objects, and interaction with users and the environment. Given that, the concept of the IoT pattern has recently been introduced. In software engineering, a pattern is defined as a general solution that can be applied to a class of common problems. It is a template suggesting a solution for the same problem occurring in different contexts. Similarly, an IoT pattern provides a guide to design an IoT solution with the difference that the software is not the only element involved. Starting from this idea, we propose the novel concept of the IoRT pattern. To the authors’ knowledge, this is the first attempt at pattern authoring in the Internet of Robotic Things context. We focus on pattern identification by abstracting examples also in the Ambient Assisted Living (AAL) scenario. A case study providing an implementation of the proposed patterns in the AAL context is also presented and discussed.
Velocity Analysis Using Separated Diffractions for Lunar Penetrating Radar Obtained by Yutu-2 Rover
Authors: Li Chao , Zhang Jinhai
Published: April 2021

The high-frequency channel of lunar penetrating radar (LPR) onboard Yutu-2 rover successfully collected high quality data on the far side of the Moon, which provide a chance for us to detect the shallow subsurface structures and thickness of lunar regolith. However, traditional methods cannot obtain reliable dielectric permittivity model, especially in the presence of high mix between diffractions and reflections, which is essential for understanding and interpreting the composition of lunar subsurface materials. In this paper, we introduce an effective method to construct a reliable velocity model by separating diffractions from reflections and perform focusing analysis using separated diffractions. We first used the plane-wave destruction method to extract weak-energy diffractions interfered by strong reflections, and the LPR data are separated into two parts: diffractions and reflections. Then, we construct a macro-velocity model of lunar subsurface by focusing analysis on separated diffractions. Both the synthetic ground penetrating radar (GPR) and LPR data shows that the migration results of separated reflections have much clearer subsurface structures, compared with the migration results of un-separated data. Our results produce accurate velocity estimation, which is vital for high-precision migration; additionally, the accurate velocity estimation directly provides solid constraints on the dielectric permittivity at different depth.
A New Method for Determining an Optimal Diurnal Threshold of GNSS Precipitable Water Vapor for Precipitation Forecasting
Authors: Li Haobo , Wang Xiaoming , Wu Suqin , Zhang Kefei , Fu Erjiang , Xu Ying , Qiu Cong , Zhang Jinglei , Li Li
Published: April 2021

Nowadays, precipitable water vapor (PWV) retrieved from ground-based Global Navigation Satellite Systems (GNSS) tracking stations has heralded a new era of GNSS meteorological applications, especially for severe weather prediction. Among the existing models that use PWV timeseries to predict heavy precipitation, the “threshold-based” models, which are based on a set of predefined thresholds for the predictors used in the model for predictions, are effective in heavy precipitation nowcasting. In previous studies, monthly thresholds have been widely accepted due to the monthly patterns of different predictors being fully considered. However, the primary weakness of this type of thresholds lies in their poor prediction results in the transitional periods between two consecutive months. Therefore, in this study, a new method for the determination of an optimal set of diurnal thresholds by adopting a 31-day sliding window was first proposed. Both the monthly and diurnal variation characteristics of the predictors were taken into consideration in the new method. Then, on the strength of the new method, an improved PWV-based model for heavy precipitation prediction was developed using the optimal set of diurnal thresholds determined based on the hourly PWV and precipitation records for the summer over the period 2010–2017 at the co-located HKSC–KP (King’s Park) stations in Hong Kong. The new model was evaluated by comparing its prediction results against the hourly precipitation records for the summer in 2018 and 2019. It is shown that 96.9% of heavy precipitation events were correctly predicted with a lead time of 4.86 h, and the false alarms resulting from the new model were reduced to 25.3%. These results suggest that the inclusion of the diurnal thresholds can significantly improve the prediction performance of the model.
Rice-Yield Prediction with Multi-Temporal Sentinel-2 Data and 3D CNN: A Case Study in Nepal
Authors: Fernandez-Beltran Ruben , Baidar Tina , Kang Jian , Pla Filiberto
Published: April 2021

Crop yield estimation is a major issue of crop monitoring which remains particularly challenging in developing countries due to the problem of timely and adequate data availability. Whereas traditional agricultural systems mainly rely on scarce ground-survey data, freely available multi-temporal and multi-spectral remote sensing images are excellent tools to support these vulnerable systems by accurately monitoring and estimating crop yields before harvest. In this context, we introduce the use of Sentinel-2 (S2) imagery, with a medium spatial, spectral and temporal resolutions, to estimate rice crop yields in Nepal as a case study. Firstly, we build a new large-scale rice crop database (RicePAL) composed by multi-temporal S2 and climate/soil data from the Terai districts of Nepal. Secondly, we propose a novel 3D Convolutional Neural Network (CNN) adapted to these intrinsic data constraints for the accurate rice crop yield estimation. Thirdly, we study the effect of considering different temporal, climate and soil data configurations in terms of the performance achieved by the proposed approach and several state-of-the-art regression and CNN-based yield estimation methods. The extensive experiments conducted in this work demonstrate the suitability of the proposed CNN-based framework for rice crop yield estimation in the developing country of Nepal using S2 data.
Crop Monitoring and Classification Using Polarimetric RADARSAT-2 Time-Series Data Across Growing Season: A Case Study in Southwestern Ontario, Canada
Authors: Xie Qinghua , Lai Kunyu , Wang Jinfei , Lopez-Sanchez Juan M. , Shang Jiali , Liao Chunhua , Zhu Jianjun , Fu Haiqiang , Peng Xing
Published: April 2021

Multitemporal polarimetric synthetic aperture radar (PolSAR) has proven as a very effective technique in agricultural monitoring and crop classification. This study presents a comprehensive evaluation of crop monitoring and classification over an agricultural area in southwestern Ontario, Canada. The time-series RADARSAT-2 C-Band PolSAR images throughout the entire growing season were exploited. A set of 27 representative polarimetric observables categorized into ten groups was selected and analyzed in this research. First, responses and temporal evolutions of each of the polarimetric observables over different crop types were quantitatively analyzed. The results reveal that the backscattering coefficients in cross-pol and Pauli second channel, the backscattering ratio between HV and VV channels (HV/VV), the polarimetric decomposition outputs, the correlation coefficient between HH and VV channelρ ρHHVV, and the radar vegetation index (RVI) show the highest sensitivity to crop growth. Then, the capability of PolSAR time-series data of the same beam mode was also explored for crop classification using the Random Forest (RF) algorithm. The results using single groups of polarimetric observables show that polarimetric decompositions, backscattering coefficients in Pauli and linear polarimetric channels, and correlation coefficients produced the best classification accuracies, with overall accuracies (OAs) higher than 87%. A forward selection procedure to pursue optimal classification accuracy was expanded to different perspectives, enabling an optimal combination of polarimetric observables and/or multitemporal SAR images. The results of optimal classifications show that a few polarimetric observables or a few images on certain critical dates may produce better accuracies than the whole dataset. The best result was achieved using an optimal combination of eight groups of polarimetric observables and six SAR images, with an OA of 94.04%. This suggests that an optimal combination considering both perspectives may be valuable for crop classification, which could serve as a guideline and is transferable for future research.
Presence of the Past: Digital Narrative of the Dennys Lascelles Concrete Wool Store; Geelong, Australia
Authors: Rashid Md Mizanur , Khoo Chin Koi , Kaljevic Sofija , Pancholi Surabhi
Published: April 2021

Recreation of the past—of historical buildings—sits at the intersection of the spatio-temporal manifestation of cultural memories, socio-cultural meanings, values, and identity remolds, and refines the existing understanding and sense of place. Digital technologies have become a popular tool in recreation of the past by creating a new body of knowledge and historical discourse based on identifying the gaps within our written histories. Designers and policymakers around the world have been exploring various tools and technologies, such as diachronic modeling, yet there is a gap in evidence-based understanding regarding the actual functioning and success of applications for placemaking. This paper, therefore, sets out to scrutinize the role of digital technologies in facilitating digital placemaking. To do so, it investigates the potential of a new “digital heritage” narrative in the revival of the lost architectural narrative of the Dennys Lascelles wool store, Geelong. The proposed paper aims to investigate the potential of a new “digital heritage” narrative and storytelling as a means towards a digital placemaking framework. While exploring the new and unique capabilities provided by the digital narrative in capturing, simulating, and disseminating lost heritage, it will further imbue a sense of place by connecting the everyday city dweller.
Urban Heat Island Formation in Greater Cairo: Spatio-Temporal Analysis of Daytime and Nighttime Land Surface Temperatures along the Urban–Rural Gradient
Authors: Athukorala Darshana , Murayama Yuji
Published: April 2021

An urban heat island (UHI) is a significant anthropogenic modification of urban land surfaces, and its geospatial pattern can increase the intensity of the heatwave effects. The complex mechanisms and interactivity of the land surface temperature in urban areas are still being examined. The urban–rural gradient analysis serves as a unique natural opportunity to identify and mitigate ecological worsening. Using Landsat Thematic Mapper (TM), Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS), Land Surface Temperature (LST) data in 2000, 2010, and 2019, we examined the spatial difference in daytime and nighttime LST trends along the urban–rural gradient in Greater Cairo, Egypt. Google Earth Engine (GEE) and machine learning techniques were employed to conduct the spatio-temporal analysis. The analysis results revealed that impervious surfaces (ISs) increased significantly from 564.14 km2 in 2000 to 869.35 km2 in 2019 in Greater Cairo. The size, aggregation, and complexity of patches of ISs, green space (GS), and bare land (BL) showed a strong correlation with the mean LST. The average urban–rural difference in mean LST was −3.59 °C in the daytime and 2.33 °C in the nighttime. In the daytime, Greater Cairo displayed the cool island effect, but in the nighttime, it showed the urban heat island effect. We estimated that dynamic human activities based on the urban structure are causing the spatial difference in the LST distribution between the day and night. The urban–rural gradient analysis indicated that this phenomenon became stronger from 2000 to 2019. Considering the drastic changes in the spatial patterns and the density of IS, GS, and BL, urban planners are urged to take immediate steps to mitigate increasing surface UHI; otherwise, urban dwellers might suffer from the severe effects of heatwaves.
A Novel Strategy to Reconstruct NDVI Time-Series with High Temporal Resolution from MODIS Multi-Temporal Composite Products
Authors: Zeng Linglin , Wardlow Brian D. , Hu Shun , Zhang Xiang , Zhou Guoqing , Peng Guozhang , Xiang Daxiang , Wang Rui , Meng Ran , Wu Weixiong
Published: April 2021

Vegetation indices (VIs) data derived from satellite imageries play a vital role in land surface vegetation and dynamic monitoring. Due to the excessive noises (e.g., cloud cover, atmospheric contamination) in daily VI data, temporal compositing methods are commonly used to produce composite data to minimize the negative influence of noise over a given compositing time interval. However, VI time series with high temporal resolution were preferred by many applications such as vegetation phenology and land change detections. This study presents a novel strategy named DAVIR-MUTCOP (DAily Vegetation Index Reconstruction based on MUlti-Temporal COmposite Products) method for normalized difference vegetation index (NDVI) time-series reconstruction with high temporal resolution. The core of the DAVIR-MUTCOP method is a combination of the advantages of both original daily and temporally composite products, and selecting more daily observations with high quality through the temporal variation of temporally corrected composite data. The DAVIR-MUTCOP method was applied to reconstruct high-quality NDVI time-series using MODIS multi-temporal products in two study areas in the continental United States (CONUS), i.e., three field experimental sites near Mead, Nebraska from 2001 to 2012 and forty-six AmeriFlux sites evenly distributed across CONUS from 2006 to 2010. In these two study areas, the DAVIR-MUTCOP method was also compared to several commonly used methods, i.e., the Harmonic Analysis of Time-Series (HANTS) method using original daily observations, Savitzky–Golay (SG) filtering using daily observations with cloud mask products as auxiliary data, and SG filtering using temporally corrected composite data. The results showed that the DAVIR-MUTCOP method significantly improved the temporal resolution of the reconstructed NDVI time series. It performed the best in reconstructing NDVI time-series across time and space (coefficient of determination (R2 = 0.93 ~ 0.94) between reconstructed NDVI and ground-observed LAI). DAVIR-MUTCOP method presented the highest robustness and accuracy with the change of the filtering parameter (R2 = 0.99 ~ 1.00, bias = 0.001, root mean square error (RMSE) = 0.020). Only MODIS data were used in this study; nevertheless, the DAVIR-MUTCOP method proposed a universal and potential way to reconstruct daily time series of other VIs or from other operational sensors, e.g., AVHRR and VIIRS.
The Impact of Short-Term Exposure to Air Pollution on the Exhaled Breath of Healthy Adults
Authors: Lammers Ariana , Neerincx Anne H. , Vijverberg Susanne J. H. , Longo Cristina , Janssen Nicole A. H. , Boere A. John F. , Brinkman Paul , Cassee Flemming R. , van der Zee Anke H. Maitland
Published: April 2021

Environmental factors, such as air pollution, can affect the composition of exhaled breath, and should be well understood before biomarkers in exhaled breath can be used in clinical practice. Our objective was to investigate whether short-term exposures to air pollution can be detected in the exhaled breath profile of healthy adults. In this study, 20 healthy young adults were exposed 2–4 times to the ambient air near a major airport and two highways. Before and after each 5 h exposure, exhaled breath was analyzed using an electronic nose (eNose) consisting of seven different cross-reactive metal-oxide sensors. The discrimination between pre and post-exposure was investigated with multilevel partial least square discriminant analysis (PLSDA), followed by linear discriminant and receiver operating characteristic (ROC) analysis, for all data (71 visits), and for a training (51 visits) and validation set (20 visits). Using all eNose measurements and the training set, discrimination between pre and post-exposure resulted in an area under the ROC curve of 0.83 (95% CI = 0.76–0.89) and 0.84 (95% CI = 0.75–0.92), whereas it decreased to 0.66 (95% CI = 0.48–0.84) in the validation set. Short-term exposure to high levels of air pollution potentially influences the exhaled breath profiles of healthy adults, however, the effects may be minimal for regular daily exposures.
Long-Range UHF RFID Tag for Automotive License Plate
Authors: Chung Youchung , Berhe Teklebrhan H.
Published: April 2021

In this paper, various locations of an Ultra High Frequency (UHF) Radio Frequency Identification (RFID) tag on automotive license plates have been considered based on the radiation pattern of the tag antenna. A small, 130 × 50 mm, passive loop antenna type UHF RFID tag for an automotive license plate was simulated with an EM simulation CST program. It was designed to have a larger back-lobe radiation pattern since the front side of the tag faces the back side of the plate holder to protect the tag antenna from bugs and dust when the automobile runs. The tag was attached to the side of a license plate holder with a dimension of 520 × 110 mm, the typical size of the standard license plate. The reflection coefficient of the tag antenna is −21 dB at 920 MHz, and the gain of the tag antenna is 6.29 dBi at the back-lobe. The reading range of the tag antenna with the plate holder, which was measured in an open field, is about 10.3 m, and the reading range of the tag installed on the bumper from the front of the vehicle is 9.4 m. The tag antenna is small enough to apply to a real automobile, and it is applicable because it uses the back-lobe pattern, so it does not require an extra device for protection from damage.
The Fiber Optic Reel System: A Compact Deployment Solution for Tethered Live-Telemetry Deep-Sea Robots and Sensors
Authors: Phillips Brennan T. , Chaloux Nicholas , Shomberg Russell , Muñoz-Soto Adriana , Owens Jim
Published: April 2021

Tethered deep-sea robots and instrument platforms, such as Remotely Operated Vehicles (ROVs) and vertical-profiling or towed instrument arrays, commonly rely on fiber optics for real-time data transmission. Fiber optic tethers used for these applications are either heavily reinforced load-bearing cables used to support lifting and pulling, or bare optical fibers used in non-load bearing applications. Load-bearing tethers directly scale operations for deep-sea robots as the cable diameter, mass, and length typically require heavy winches and large surface support vessels to operate, and also guide the design of the deep-sea robot itself. In an effort to dramatically reduce the physical scale and operational overhead of tethered live-telemetry deep-sea robots and sensors, we have developed the Fiber Optic Reel System (FOReelS). FOReelS utilizes a customized electric fishing reel outfitted with a proprietary hollow-core braided fiber optic fishing line and mechanical termination assembly (FOFL), which offers an extremely small diameter (750 μm) load-bearing (90 lb/400 N breaking strength) tether to support live high-bandwidth data transmission as well as fiber optic sensing applications. The system incorporates a novel epoxy potted data payload system (DPS) that includes high-definition video, integrated lighting, rechargeable battery power, and gigabit ethernet fiber optic telemetry. In this paper we present the complete FOReelS design and field demonstrations to depths exceeding 780 m using small coastal support vessels of opportunity. FOReelS is likely the smallest form factor live-telemetry deep-sea exploration tool currently in existence, with a broad range of future applications envisioned for oceanographic sensing and communication.
High Precision Optical Tracking System Based on near Infrared Trinocular Stereo Vision
Authors: Bi Songlin , Gu Yonggang , Zou Jiaqi , Wang Lianpo , Zhai Chao , Gong Ming
Published: April 2021

A high precision optical tracking system (OTS) based on near infrared (NIR) trinocular stereo vision (TSV) is presented in this paper. Compared with the traditional OTS on the basis of binocular stereo vision (BSV), hardware and software are improved. In the hardware aspect, a NIR TSV platform is built, and a new active tool is designed. Imaging markers of the tool are uniform and complete with large measurement angle (>60°). In the software aspect, the deployment of extra camera brings high computational complexity. To reduce the computational burden, a fast nearest neighbor feature point extraction algorithm (FNNF) is proposed. The proposed method increases the speed of feature points extraction by hundreds of times over the traditional pixel-by-pixel searching method. The modified NIR multi-camera calibration method and 3D reconstruction algorithm further improve the tracking accuracy. Experimental results show that the calibration accuracy of the NIR camera can reach 0.02%, positioning accuracy of markers can reach 0.0240 mm, and dynamic tracking accuracy can reach 0.0938 mm. OTS can be adopted in high-precision dynamic tracking.
Fourier-Transform-Based Surface Measurement and Reconstruction of Human Face Using the Projection of Monochromatic Structured Light
Authors: Chen Bingquan , Li Hongsheng , Yue Jun , Shi Peng
Published: April 2021

This work presents a new approach of surface measurement of human face via the combination of the projection of monochromatic structured light, the optical filtering technique, the polarization technique and the Fourier-transform-based image-processing algorithm. The theoretical analyses and experimental results carried out in this study showed that the monochromatic feature of projected fringe pattern generated using our designed laser-beam-based optical system ensures the use of optical filtering technique for removing the effect of background illumination; the linearly-polarized characteristic makes it possible to employ a polarizer for eliminating the noised signal contributed by multiply-scattered photons; and the high-contrast sinusoidal fringes of the projected structured light provide the condition for accurate reconstruction using one-shot measurement based on Fourier transform profilometry. The proposed method with the portable and stable optical setup may have potential applications of indoor medical scan of human face and outdoor facial recognition without strict requirements of a dark environment and a stable object being observed.
Measuring Kinematic Viscosity of Engine Oils: A Comparison of Data Obtained from Four Different Devices
Authors: Wolak Artur , Zając Grzegorz , Słowik Tomasz
Published: April 2021

The aim of this paper is to compare the results of kinematic viscosity of lubricating oils measurements at 40 °C, obtained with three different rapid evaluation devices, and the standardized method using an Ubbelohde Capillary viscometer. The following instruments were selected to measure: a mid-FTIR spectrophotometer, a microchannel viscometer, and a Stabinger viscometer. The study material comprised 42 fresh engine oils, all of which are commercially available. The main data analysis tools used in the study were multiple regression, Mahala Nobis distance, post-hoc analysis, and the Wilcoxon signed-rank test with the Bonferroni correction. Consistent outcomes were obtained for the Stabinger viscometer only, whereas the microchannel viscometer and the mid-FTIR spectrophotometer were not as precise as the reference method. It was also found that the results obtained with the use of the mid-FTIR spectrophotometer were burdened with a very large measurement error. Therefore, a very careful approach is suggested when choosing these instruments. The study fills an important gap in empirical research in the context of the reliability of measurement results obtained using various research techniques.
Ultrasensitive Strain Sensor Based on Pre-Generated Crack Networks Using Ag Nanoparticles/Single-Walled Carbon Nanotube (SWCNT) Hybrid Fillers and a Polyester Woven Elastic Band
Authors: Ko Yelin , Kim Ji-seon , Vu Chi Cuong , Kim Jooyong
Published: April 2021

Flexible strain sensors are receiving a great deal of interest owing to their prospective applications in monitoring various human activities. Among various efforts to enhance the sensitivity of strain sensors, pre-crack generation has been well explored for elastic polymers but rarely on textile substrates. Herein, a highly sensitive textile-based strain sensor was fabricated via a dip-coat-stretch approach: a polyester woven elastic band was dipped into ink containing single-walled carbon nanotubes coated with silver paste and pre-stretched to generate prebuilt cracks on the surface. Our sensor demonstrated outstanding sensitivity (a gauge factor of up to 3550 within a strain range of 1.5–5%), high stability and durability, and low hysteresis. The high performance of this sensor is attributable to the excellent elasticity and woven structure of the fabric substrate, effectively generating and propagating the prebuilt cracks. The strain sensor integrated into firefighting gloves detected detailed finger angles and cyclic finger motions, demonstrating its capability for subtle human motion monitoring. It is also noteworthy that this novel strategy is a very quick, straightforward, and scalable method of fabricating strain sensors, which is extremely beneficial for practical applications.