bluuebunny/crossref_metadata_2025 huggingface dataset:
UHPLC-UV/PDA Method Validation for Simultaneous Quantification of Luteolin and Apigenin Derivatives from Elaeis guineensis Leaf Extracts: An Application for Antioxidant Herbal Preparation
Authors: Che Zain Mohamad Shazeli , Osman Muhamad Faris , Lee Soo Yee , Shaari Khozirah
Published: February 2021

Luteolin and apigenin derivatives present in oil palm (Elaeis guineensis) leaves (OPL) are reported to possess excellent antioxidant properties relating to numerous health benefits. To meet the global demand for flavonoids, OPL, which is plentifully generated as an agricultural by-product from oil palm plantations, can be further exploited as a new source of natural antioxidant compounds. However, to produce a standardized herbal preparation, validation of the quantification method for these compounds is required. Therefore, in this investigation, we developed and validated an improved and rapid analytical method, ultra-high-performance liquid chromatography equipped with ultraviolet/photodiode array (UHPLC-UV/PDA) for the quantification of 12 luteolin and apigenin derivatives, particularly focusing on flavonoid isomeric pairs: orientin/isoorientin and vitexin/isovitexin, present in various OPL extracts. Several validation parameters were assessed, resulting in the UHPLC-UV/PDA technique offering good specificity, linearity, accuracy, precision, and robustness, where the values were within acceptable limits. Subsequently, the validated method was employed to quantify luteolin and apigenin derivatives from OPL subjected to different drying treatments and extraction with various solvent systems, giving total luteolin (TLC) and apigenin content (TAC) in the range of 2.04–56.30 and 1.84–160.38 µg/mg extract, respectively. Additionally, partial least square (PLS) analysis disclosed the combination of freeze dry-aqueous methanol yielded OPL extracts with high TLC and TAC, which are strongly correlated with antioxidant activity. Therefore, we provide the first validation report of the UHPLC-UV/PDA method for quantification of luteolin and apigenin derivatives present in various OPL extracts, suggesting that this approach could be employed in standardized herbal preparations by adopting orientin, isoorientin, vitexin, and isovitexin as chemical markers.
Ratiometric Fluorescence Assay for Nitroreductase Activity: Locked-Flavylium Fluorophore as a NTR-Sensitive Molecular Probe
Authors: Kim Su Jung , Yoon Jung Won , Yoon Shin A , Lee Min Hee
Published: February 2021

Nitroreductases belong to a member of flavin-containing enzymes that can reduce nitroaromatic compounds to amino derivatives with NADH as an electron donor. NTR activity is known to be elevated in the cancerous environment and is considered an advantageous target in therapeutic prodrugs for the treatment of cancer. Here, we developed a ratiometric fluorescent molecule for observing NTR activity in living cells. This can provide a selective and sensitive response to NTR with a distinct increase in fluorescence ratio (FI530/FI630) as well as color changes. We also found a significant increase in NTR activity in cervical cancer HeLa and lung cancer A549 cells compared to non-cancerous NIH3T3. We proposed that this new ratiometric fluorescent molecule could potentially be used as a NTR-sensitive molecular probe in the field of cancer diagnosis and treatment development related to NTR activity.
Efficient and Reusable Iron Catalyst to Convert CO2 into Valuable Cyclic Carbonates
Authors: Ribeiro Ana P. C. , Goodrich Peter , Martins Luísa M. D. R. S.
Published: February 2021

The production of cyclic carbonates from CO2 cycloaddition to epoxides, using the C-scorpionate iron(II) complex [FeCl2{κ3-HC(pz)3}] (pz = 1H-pyrazol-1-yl) as a catalyst, is achieved in excellent yields (up to 98%) in a tailor-made ionic liquid (IL) medium under mild conditions (80 °C; 1–8 bar). A favorable synergistic catalytic effect was found in the [FeCl2{κ3-HC(pz)3}]/IL system. Notably, in addition to exhibiting remarkable activity, the catalyst is stable during ten consecutive cycles, the first decrease (11%) on the cyclic carbonate yield being observed during the 11th cycle. The use of C-scorpionate complexes in ionic liquids to afford cyclic carbonates is presented herein for the first time.
Cytotoxic Fractions from Hechtia glomerata Extracts and p-Coumaric Acid as MAPK Inhibitors
Authors: Stefani Tommaso , Romo-Mancillas Antonio , Carrizales-Castillo Juan J. J. , Arredondo-Espinoza Eder , Ramírez-Estrada Karla , Alcantar-Rosales Victor M. , González-Maya Leticia , Sánchez-Carranza Jessica Nayelli , Balderas-Renterías Isaías , Camacho-Corona María del Rayo
Published: February 2021

Preliminary bioassay-guided fractionation was performed to identify cytotoxic compounds from Hechtia glomerata, a plant that is used in Mexican ethnomedicine. Organic and aqueous extracts were prepared from H. glomerata’s leaves and evaluated against two cancer cell lines. The CHCl3/MeOH (1:1) active extract was fractionated, and the resulting fractions were assayed against prostate adenocarcinoma PC3 and breast adenocarcinoma MCF7 cell lines. Active fraction 4 was further analyzed by high-performance liquid chromatography–quadrupole time-of-flight–mass spectrometry analysis to identify its active constituents. Among the compounds that were responsible for the cytotoxic effects of this fraction were flavonoids, phenolic acids, and aromatic compounds, of which p-coumaric acid (p-CA) and its derivatives were abundant. To understand the mechanisms that underlie p-CA cytotoxicity, a microarray assay was performed on PC3 cells that were treated or not with this compound. The results showed that mitogen-activated protein kinases (MAPKs) that regulate many cancer-related pathways were targeted by p-CA, which could be related to the reported effects of reactive oxygen species (ROS). A molecular docking study of p-CA showed that this phenolic acid targeted these protein active sites (MAPK8 and Serine/Threonine protein kinase 3) at the same binding site as their inhibitors. Thus, we hypothesize that p-CA produces ROS, directly affects the MAPK signaling pathway, and consequently causes apoptosis, among other effects. Additionally, p-CA could be used as a platform for the design of new MAPK inhibitors and re-sensitizing agents for resistant cancers.
Natural Products from the Marine Sponge Subgenus Reniera
Authors: Bai Xuelian , Liu Yang , Wang Hao , Zhang Huawei
Published: February 2021

Marine sponges are one of the prolific producers of bioactive natural products with therapeutic potential. As an important subgenus of Haliclona, Reniera sponges are mainly distributed in the Mediterranean Sea and Atlantic area, and had been chemically investigated for over four decades. By an extensive literature search, this review first makes a comprehensive summary of all natural products from Reniera sponges and their endozoic microbes, as well as biological properties. Perspectives on strengthening the chemical study of Reniera sponges for new drug-lead discovery are provided in this work.
Animal Protein versus Plant Protein in Supporting Lean Mass and Muscle Strength: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Authors: Lim Meng Thiam , Pan Bernice Jiaqi , Toh Darel Wee Kiat , Sutanto Clarinda Nataria , Kim Jung Eun
Published: February 2021

Although animal protein is usually considered to be a more potent stimulator of muscle protein synthesis than plant protein, the effect of protein source on lean mass and muscle strength needs to be systematically reviewed. This study aimed to examine potential differences in the effect of animal vs. plant protein on lean mass and muscle strength, and the possible influence of resistance exercise training (RET) and age. The following databases were searched: PubMed, Embase, Scopus and CINAHL Plus with Full Text, and 3081 articles were screened. A total of 18 articles were selected for systematic review, of which, 16 were used for meta-analysis. Total protein intakes were generally above the recommended dietary allowance at the baseline and end of intervention. Results from the meta-analyses demonstrated that protein source did not affect changes in absolute lean mass or muscle strength. However, there was a favoring effect of animal protein on percent lean mass. RET had no influence on the results, while younger adults (<50 years) were found to gain absolute and percent lean mass with animal protein intake (weighted mean difference (WMD), 0.41 kg; 95% confidence interval (CI) 0.08 to 0.74; WMD 0.50%; 95% CI 0.00 to 1.01). Collectively, animal protein tends to be more beneficial for lean mass than plant protein, especially in younger adults.
Switchable Metasurface with VO2 Thin Film at Visible Light by Changing Temperature
Authors: Yang Jin-Kyu , Jeong Hyeon-Seok
Published: February 2021

We numerically demonstrated switchable metasurfaces using a phase change material, VO2 by temperature change. The Pancharatnam–Berry metasurface was realized by using an array of Au nanorods on top of a thin VO2 film above an Au film, where the optical property of the VO2 film is switched from the insulator phase at low temperature to the metal phase at high temperature. At the optimal structure, polarization conversion efficiency of the normal incident light is about 75% at low temperature while that is less than 0.5% at high temperature in the visible region (λ∼ 700 nm). Various functionalities of switchable metasurfaces were demonstrated such as polarization conversion, beam steering, Fourier hologram, and Fresnel hologram. The thin-VO2-film-based switchable metasurface can be a good candidate for various switchable metasurface devices, for example, temperature dependent optical sensors, beamforming antennas, and display.
Negative Hydrogen and Deuterium Ion Density in a Low Pressure Plasma in Front of a Converter Surface at Different Work Functions
Authors: Cristofaro Sofia , Friedl Roland , Fantz Ursel
Published: February 2021

Negative ion sources of neutral beam injection (NBI) systems for future fusion devices like ITER (“The Way” in Latin) rely on the surface conversion of hydrogen (or deuterium) atoms and positive ions to negative ions in an inductively coupled plasma (ICP). The efficiency of this process depends on the work function of the converter surface. By introducing caesium into the ion source the work function decreases, enhancing the negative ion yield. In order to study the isotope effect on the negative ion density at different work functions, fundamental investigations are performed in a planar ICP laboratory experiment where the work function and the negative ion density in front of a sample can be simultaneously and absolutely determined. For work functions above 2.7 eV, the main contribution to the negative hydrogen ion density is solely due to volume formation, which can be modeled via the rate balance model YACORA H−, while below 2.7 eV the surface conversion become significant and the negative ion density increases. For a work function of 2.1 eV (bulk Cs), the H− density increases by at least a factor of 2.8 with respect to a non-caesiated surface. With a deuterium plasma, the D− density measured at 2.1 eV is a factor of 2.5 higher with respect to a non-caesiated surface, reaching densities of surface produced negative ions comparable to the hydrogen case.
Hemostatic Dressings Made of Oxidized Bacterial Nanocellulose Membranes
Authors: Queirós E. C. , Pinheiro S. P. , Pereira J. E. , Prada J. , Pires I. , Dourado F. , Parpot P. , Gama M.
Published: February 2021

Surgicel® (regenerated oxidized cellulose) is a bio-absorbable hemostatic material widely applied to prevent surgery-derived adhesions. Some critical issues have been reported associated with this biomaterial, which we aimed to overcome by producing bacterial nanocellulose (BNC) membranes with hemostatic activity, through electrochemical oxidation using the tetramethylpiperidine-1-oxyl (TEMPO) radical. Samples were characterized by FTIR, NMR, SEM, XRD and their degree of polymerization. The oxidation degree was evaluated by titration of the carboxyl groups and the hemostatic behavior by whole-blood-clotting assays. In vitro and in vivo biodegradability of oxidized BNC membranes were evaluated and compared with that of Surgicel®. The oxidation degree increased from 4% to 7% and up to 15%, corresponding to an applied charge of 400, 700 and 1200 Coulombs, respectively. The oxidized BNC preserved the crystallinity and the 3D nano-fibrillar network, and demonstrated hemostatic activity, although not as effective as that of Surgicel®. In vivo assays demonstrated that the oxidized membranes did not induce an inflammatory response, revealing a good biocompatibility. However, non-degraded oxidized BNC was still detected at the implantation site after 56 days.
A Bioreactor Designed for Restricting Oversize of Aerobic Granular Sludge
Authors: Feng Hongbo , Yang Honggang , Sheng Jianlong , Pan Zengrui , Li Jun
Published: February 2021

Aerobic granular sludge (AGS) with oversized diameter commonly affects its stability and pollutant removal. In order to effectively restrict the particle size of AGS, a sequencing batch reactor (SBR) with a spiny aeration device was put forward. A conventional SBR (R1) and an SBR (R2) with the spiny aeration device treating tannery wastewater were compared in the laboratory. The result indicates that the size of the granular sludge from R2 was smaller than that from R1 with sludge granulation. The spines and air bubbles could effectively restrict the particle size of AGS by collision and abrasion. Nevertheless, there was no significant change in mixed liquor suspended solids (MLSS) and the sludge volume index (SVI) in either bioreactors. The removal (%) of chemical oxygen demand (COD) and ammonia nitrogen (NH4+-N) in these two bioreactors did not differ from each other greatly. The analysis of biological composition displays that the proportion of Proteobacteria decreased slightly in R2. The X-ray fluorescence (XRF) analysis revealed less accumulation of Fe and Ca in smaller granules. Furthermore, a pilot-scale SBR with a spiny aeration device was successfully utilized to restrict the diameter of granules at about 300 μm.
A Review on the Synthesis, Characterization, and Modeling of Polymer Grafting
Authors: Vega-Hernández Miguel Ángel , Cano-Díaz Gema Susana , Vivaldo-Lima Eduardo , Rosas-Aburto Alberto , Hernández-Luna Martín G. , Martinez Alfredo , Palacios-Alquisira Joaquín , Mohammadi Yousef , Penlidis Alexander
Published: February 2021

A critical review on the synthesis, characterization, and modeling of polymer grafting is presented. Although the motivation stemmed from grafting synthetic polymers onto lignocellulosic biopolymers, a comprehensive overview is also provided on the chemical grafting, characterization, and processing of grafted materials of different types, including synthetic backbones. Although polymer grafting has been studied for many decades—and so has the modeling of polymer branching and crosslinking for that matter, thereby reaching a good level of understanding in order to describe existing branching/crosslinking systems—polymer grafting has remained behind in modeling efforts. Areas of opportunity for further study are suggested within this review.
The Effectiveness of Different Household Storage Strategies and Plant-Based Preservatives for Dehulled and Sun-Dried Breadfruit Seeds
Authors: Ndukwu Macmanus C. , Onwude Daniel I. , Ehiem James , Abada Ugochukwu C. , Ekop Inemesit E. , Chen Guangnan
Published: February 2021

In a tropical rainforest environment, different storage strategies are often adopted in the preservation of primary processed food crops, such as maize, sorghum, etc., after drying and dehulling to increase shelf-life. For breadfruit seeds (Treculia Africana), the current challenge is identifying the most appropriate short-term storage and packaging methods that can retain the quality of stored products and extend shelf-life. In this regard, we compared the performance of a plastic container, a weaved silo bag and a locally developed silo bin for the short-term storage of parboiled, dehulled and dried breadfruit seeds treated with locally sourced and affordable alligator pepper (Zingiberaceaeaframomum melegueta) and bitter kola (garcinia) powder as preservatives. We show that the concentration of CO2 was lower in the silo bin treated with 150 g alligator pepper and higher in the silo bag-treated with 100 g bitter kola nut. A higher CO2 concentration resulted in limited oxygen availability, higher water vapor, and a higher heat release rate. Non-treated bag storage had the highest average mold count of 1.093 × 103 CFU/mL, while silo bin-stored breadfruit treated with 150 g of alligator pepper had the lowest mold count of 2.6 × 102 CFU/mL. The storage time and botanical treatments influenced both the crude protein and crude fiber content. Average insect infestations were low (0–4.5) in the silo bin with breadfruits treated with alligator pepper powder, as the seeds seemed to continue to desorb moisture in storage, unlike in other treatments. The obtained results revealed the high potential of alligator pepper (Zingiberaceaeaframomum melegueta) as a botanical insecticide in preventing insect infestation and mold growth in stored breadfruit instead of using synthetic insecticide. An aluminum silo bin with alligator pepper powder is recommended to store dried and dehulled breadfruit seeds as a baseline for other tropical crops.
Assessment of Annual Composite Images Obtained by Google Earth Engine for Urban Areas Mapping Using Random Forest
Authors: Zhang Zhaoming , Wei Mingyue , Pu Dongchuan , He Guojin , Wang Guizhou , Long Tengfei
Published: February 2021

Urban areas represent the primary source region of greenhouse gas emissions. Mapping urban areas is essential for understanding land cover change, carbon cycles, and climate change (urban areas also refer to impervious surfaces, i.e., artificial cover and structures). Remote sensing has greatly advanced urban areas mapping over the last several decades. At present, we have entered the era of big data. Long time series of satellite data such as Landsat and high-performance computing platforms such as Google Earth Engine (GEE) offer new opportunities to map urban areas. The objective of this research was to determine how annual time series images from Landsat 8 Operational Land Imager (OLI) can effectively be composed to map urban areas in three cities in China in support of GEE. Three reducer functions, ee.Reducer.min(), ee.Reducer.median(), and ee.Reducer.max() provided by GEE, were selected to construct four schemes to synthesize the annual intensive time series Landsat 8 OLI data for three cities in China. Then, urban areas were mapped based on the random forest algorithm and the accuracy was evaluated in detail. The results show that (1) the quality of annual composite images was improved significantly, particularly in reducing the impact of cloud and cloud shadows, and (2) the annual composite images obtained by the combination of multiple reducer functions had better performance than that obtained by a single reducer function. Further, the overall accuracy of urban areas mapping with the combination of multiple reducer functions exceeded 90% in all three cities in China. In summary, a suitable combination of reducer functions for synthesizing annual time series images can enhance data quality and ensure differences between characteristics and higher precision for urban areas mapping.
A Workflow Based on SNAP–StaMPS Open-Source Tools and GNSS Data for PSI-Based Ground Deformation Using Dual-Orbit Sentinel-1 Data: Accuracy Assessment with Error Propagation Analysis
Authors: Mancini Francesco , Grassi Francesca , Cenni Nicola
Published: February 2021

This paper discusses a full interferometry processing chain based on dual-orbit Sentinel-1A and Sentinel-1B (S1) synthetic aperture radar data and a combination of open-source routines from the Sentinel Application Platform (SNAP), Stanford Method for Persistent Scatterers (StaMPS), and additional routines introduced by the authors. These are used to provide vertical and East-West horizontal velocity maps over a study area in the south-western sector of the Po Plain (Italy) where land subsidence is recognized. The processing of long time series of displacements from a cluster of continuous global navigation satellite system stations is used to provide a global reference frame for line-of-sight–projected velocities and to validate velocity maps after the decomposition analysis. We thus introduce the main theoretical aspects related to error propagation analysis for the proposed methodology and provide the level of uncertainty of the validation analysis at relevant points. The combined SNAP–StaMPS workflow is shown to be a reliable tool for S1 data processing. Based on the validation procedure, the workflow allows decomposed velocity maps to be obtained with an accuracy of 2 mm/yr with expected uncertainty levels lower than 2 mm/yr. Slant-oriented and decomposed velocity maps provide new insights into the ground deformation phenomena that affect the study area arising from a combination of natural and anthropogenic sources.
Influence of Soil Moisture vs. Climatic Factors in Pinus Halepensis Growth Variability in Spain: A Study with Remote Sensing and Modeled Data
Authors: González-Zamora Ángel , Almendra-Martín Laura , de Luis Martín , Martínez-Fernández José
Published: February 2021

The influence of soil water content on Aleppo pine growth variability is analyzed against climatic variables, using satellite and modeled soil moisture databases. The study was made with a dendrochronological series of 22 forest sites in Spain with different environmental conditions. From the results of the correlation analysis, at both daily and monthly scales, it was observed that soil moisture was the variable that correlated the most with tree growth and the one that better identified the critical periods for this growth. The maximum correlation coefficients obtained with the rest of the variables were less than half of that obtained for soil moisture. Multiple linear regression analysis with all combinations of variables indicated that soil moisture was the most important variable, showing the lowest p-values in all cases. While identifying the role of soil moisture, it was noted that there was appreciable variability between the sites, and that this variability is mainly modulated by water availability, rather than thermal conditions. These results can contribute to new insights into the ecohydrological dynamics of Aleppo pine and a methodological approach to the study of many other species.
Boundary-Assisted Learning for Building Extraction from Optical Remote Sensing Imagery
Authors: He Sheng , Jiang Wanshou
Published: February 2021

Deep learning methods have been shown to significantly improve the performance of building extraction from optical remote sensing imagery. However, keeping the morphological characteristics, especially the boundaries, is still a challenge that requires further study. In this paper, we propose a novel fully convolutional network (FCN) for accurately extracting buildings, in which a boundary learning task is embedded to help maintain the boundaries of buildings. Specifically, in the training phase, our framework simultaneously learns the extraction of buildings and boundary detection and only outputs extraction results while testing. In addition, we introduce spatial variation fusion (SVF) to establish an association between the two tasks, thus coupling them and making them share the latent semantics and interact with each other. On the other hand, we utilize separable convolution with a larger kernel to enlarge the receptive fields while reducing the number of model parameters and adopt the convolutional block attention module (CBAM) to boost the network. The proposed framework was extensively evaluated on the WHU Building Dataset and the Inria Aerial Image Labeling Dataset. The experiments demonstrate that our method achieves state-of-the-art performance on building extraction. With the assistance of boundary learning, the boundary maintenance of buildings is ameliorated.
A New Coupled Elimination Method of Soil Moisture and Particle Size Interferences on Predicting Soil Total Nitrogen Concentration through Discrete NIR Spectral Band Data
Authors: Zhou Peng , Yang Wei , Li Minzan , Wang Weichao
Published: February 2021

Rapid and accurate measurement of high-resolution soil total nitrogen (TN) information can promote variable rate fertilization, protect the environment, and ensure crop yields. Many scholars focus on exploring the rapid TN detection methods and corresponding soil sensors based on spectral technology. However, soil spectra are easily disturbed by many factors, especially soil moisture and particle size. Real-time elimination of the interferences of these factors is necessary to improve the accuracy and efficiency of measuring TN concentration in farmlands. Although, many methods can be used to eliminate soil moisture and particle size effects on the estimation of soil parameters using continuum spectra. However, the discrete NIR spectral band data can be completely different in the band attribution with continuum spectra, that is, it does not have continuity in the sense of spectra. Thus, relevant elimination methods of soil moisture and particle size effects on continuum spectra do not apply to the discrete NIR spectral band data. To solve this problem, in this study, moisture absorption correction index (MACI) and particle size correction index (PSCI) methods were proposed to eliminate the interferences of soil moisture and particle size, respectively. Soil moisture interference was decreased by normalizing the original spectral band data into standard spectral band data, on the basis of the strong soil moisture absorption band at 1450 nm. For the PSCI method, characteristic bands of soil particle size were identified to be 1361 and 1870 nm firstly. Next, normalized index Np, which calculated wavelengths of 1631 and 1870 nm, was proposed to eliminate soil particle size interference on discrete NIR spectral band data. Finally, a new coupled elimination method of soil moisture and particle size interferences on predicting TN concentration through discrete NIR spectral band data was proposed and evaluated. The six discrete spectral bands (1070, 1130, 1245, 1375, 1550, and 1680 nm) used in the on-the-go detector of TN concentration were selected to verify the new method. Field tests showed that the new coupled method had good effects on eliminating interferences of soil moisture and soil particle size.
Discontinuity Predictions of Porosity and Hydraulic Conductivity Based on Electrical Resistivity in Slopes through Deep Learning Algorithms
Authors: Lee Seung-Jae , Yoon Hyung-Koo
Published: February 2021

Electrical resistivity is used to obtain various types of information for soil strata. Hence, the prediction of electrical resistivity is helpful to predict the future behavior of soil. The objective of this study is to apply deep learning algorithms, including deep neural network (DNN), long-short term memory (LSTM), and gated recurrent unit (GRU), to determine the reliability of electrical resistivity predictions to find the discontinuity of porosity and hydraulic conductivity. New DNN-based algorithms, i.e., LSTM-DNN and GRU-DNN, are also applied in this study. The electrical resistivity values are obtained using 101 electrodes installed at 2 m intervals on a mountaintop, and a Wenner array is selected to simplify the electrode installation and measurement. A total of 1650 electrical resistivity values are obtained for one measurement considering the electrode spacing, and accumulated data measured for 15 months are used in the deep learning analysis. A constant ratio of 6:2:2 among the training, validation, and test data, respectively, is used for the measured electrical resistivity, and the hyperparameters in each algorithm are moderated to improve the reliability. Based on the deep learning model results, the distributions of porosity and hydraulic conductivity are deduced, and an average depth of 25 m is estimated for the discontinuity depth. This paper shows that the deep learning technique is well used to predict electrical resistivity, porosity, hydraulic conductivity, and discontinuity depth.
The Use of a Micro Near Infrared Portable Instrument to Predict Bioactive Compounds in a Wild Harvested Fruit—Kakadu Plum (Terminalia ferdinandiana)
Authors: Bobasa Eshetu , Phan Anh Dao T. , Netzel Michael , Smyth Heather E. , Sultanbawa Yasmina , Cozzolino Daniel
Published: February 2021

Kakadu plum (KP; Terminalia ferdinandiana Exell, Combretaceae) is an emergent indigenous fruit originating from Northern Australia, with valuable health and nutritional characteristics and properties (e.g., high levels of vitamin C and ellagic acid). In recent years, the utilization of handheld NIR instruments has allowed for the in situ quantification of a wide range of bioactive compounds in fruit and vegetables. The objective of this study was to evaluate the ability of a handheld NIR spectrophotometer to measure vitamin C and ellagic acid in wild harvested KP fruit samples. Whole and pureed fruit samples were collected from two locations in the Kimberley region (Western Australia, Australia) and were analysed using both reference and NIR methods. The standard error in cross validation (SECV) and the residual predictive deviation (RPD) values were 1.81% dry matter (DM) with an RPD of 2.1, and 3.8 mg g−1 DM with an RPD of 1.9 for the prediction of vitamin C and ellagic acid, respectively, in whole KP fruit. The SECV and RPD values were 1.73% DM with an RPD of 2.2, and 5.6 mg g−1 DM with an RPD of 1.3 for the prediction of vitamin C and ellagic acid, respectively, in powdered KP samples. The results of this study demonstrated the ability of a handheld NIR instrument to predict vitamin C and ellagic acid in whole and pureed KP fruit samples. Although the RPD values obtained were not considered adequate to quantify these bioactive compounds (e.g., analytical quantification), this technique can be used as a rapid tool to screen vitamin C in KP fruit samples for high and low quality vitamin C.
Feature Space Transformation for Fault Diagnosis of Rotating Machinery under Different Working Conditions
Authors: Jang Gye-Bong , Cho Sung-Bae
Published: February 2021

In recent years, various deep learning models have been developed for the fault diagnosis of rotating machines. However, in practical applications related to fault diagnosis, it is difficult to immediately implement a trained model because the distribution of source data and target domain data have different distributions. Additionally, collecting failure data for various operating conditions is time consuming and expensive. In this paper, we introduce a new transformation method for the latent space between domains using the source domain and normal data of the target domain that can be easily collected. Inspired by semantic transformations in an embedded space in the field of word embedding, discrepancies between the distribution of the source and target domains are minimized by transforming the latent representation space in which fault attributes are preserved. To match the feature area and distribution, spatial attention is applied to learn the latent feature spaces, and the 1D CNN LSTM architecture is implemented to maximize the intra-class classification. The proposed model was validated for two types of rotating machines such as a dataset of rolling bearings as CWRU and a gearbox dataset of heavy machinery. Experimental results show the proposed method has higher cross-domain diagnostic accuracy than others, therefore showing reliable generalization performance in rotating machines operating under various conditions.
Estimation of the External Knee Adduction Moment during Gait Using an Inertial Measurement Unit in Patients with Knee Osteoarthritis
Authors: Iwama Yu , Harato Kengo , Kobayashi Shu , Niki Yasuo , Ogihara Naomichi , Matsumoto Morio , Nakamura Masaya , Nagura Takeo
Published: February 2021

Although the external knee adduction moment (KAM) during gait was shown to be a quantitative parameter of medial knee osteoarthritis (OA), it requires expensive equipment and a dedicated large space to measure. Therefore, it becomes a major reason to limit KAM measurement in a clinical environment. The purpose of this study was to estimate KAM using a single inertial measurement unit (IMU) during gait in patients with knee OA. A total of 22 medial knee OA patients (44 knee joints) performed conventional gait analysis using three-dimensional (3D) motion capture system. At the same time, we attached commercial IMUs to six body segments (sternum, pelvis, both thighs, and both shanks), and IMU signals during gait were recorded synchronized with the motion capture system. The peak-to-peak difference of acceleration in the lateral/medial axis immediately after heel contact was defined as the thrust acceleration (TA). We hypothesized that TA would represent the lateral thrust of the knee during the stance phase and correlate with the first peak of KAM. The relationship between the peak KAM and TA of pelvis (R = 0.52, p < 0.001), shanks (R = 0.57, p < 0.001) and thighs (R = 0.49, p = 0.001) showed a significant correlation. The root mean square error (RMSE) of linear regression models of pelvis, shanks, and thighs to estimate KAM were 0.082, 0.079, and 0.084 Nm/(kg·m), respectively. Our newly established parameter TA showed a moderate correlation with conventional KAM. The current study confirmed our hypothesis that a single IMU would predict conventional KAM during gait. Since KAM is known as an indicator for prognosis and severity of knee OA, this new parameter has the potential to become an accessible predictor for medial knee OA instead of KAM.
An Evaluation of Different NIR-Spectral Pre-Treatments to Derive the Soil Parameters C and N of a Humus-Clay-Rich Soil
Authors: Heil Kurt , Schmidhalter Urs
Published: February 2021

Near-infrared reflectance spectroscopy (NIRS) was successfully used in this study to measure soil properties, mainly C and N, requiring spectral pre-treatments. Calculations in this evaluation were carried out using multivariate statistical procedures with preceding pre-treatment procedures of the spectral data. Such transformations could remove noise, highlight features, and extract essential wavelengths for quantitative predictions. This frequently significantly improved the predictions. Since selecting the appropriate transformation was not straightforward due to the large numbers of available methods, more comprehensive insight into choosing appropriate and optimized pre-treatments was required. Therefore, the objectives of this study were (i) to compare various pre-processing transformations of spectral data to determine their suitability for modeling soil C and N using NIR spectra (55 pre-treatment procedures were tested), and (ii) to determine which wavelengths were most important for the prediction of C and N. The investigations were carried out on an arable field in South Germany with a soil type of Calcaric Fluvic Relictigleyic Phaeozem (Epigeoabruptic and Pantoclayic), created in the flooding area of the Isar River. The best fit and highest model accuracy for the C (Ct, Corg, and Ccarb) and N models in the calibration and validation modes were achieved using derivations with Savitzky–Golay (SG). This enabled us to calculate the Ct, Corg, and N with an R2 higher than 0.98/0.86 and an ratio of performance to the interquartile range (RPIQ) higher than 10.9/4.1 (calibration/validation).
A Coherence Improvement Method Based on Sub-Aperture InSAR for Human Activity Detection
Authors: Wang Zhongbin , Wang Bingnan , Xiang Maosheng , Hu Xiaoning , Song Chong , Wang Shuai , Wang Yachao
Published: February 2021

Human activity detection plays an important role in social security monitoring. Since human activity is very weak, it is necessary to employ the repeat-pass Interferometric Synthetic Aperture Radar (InSAR) technique to detect the potential activity between two data acquisitions; a high level of coherence is required for detection. With the object of detecting human activity of interest, this paper presents a coherence improvement approach based on sub-aperture InSAR for human activity detection. Different sub-apertures contain different scattering information of the target, as they represent the backscatter of the target from a different range of angles. Integrating corresponding sub-aperture interferometric results can improve the coherence between two complex images compared to the entire synthetic aperture, as well as removing a little disturbance in some circumstances. To validate the method presented in this paper, the actual airborne Ka-band frequency modulated continuous wave (FMCW) InSAR data acquired by the Aerospace Information Research Institute, Chinese Academy of Sciences (AIRCAS) are utilized. The experimental results demonstrate that the proposed method can effectively improve the coherence between two complex SAR images and can validly detect human activity of interest.
Holistic Vehicle Instrumentation for Assessing Driver Driving Styles
Authors: Garrosa María , Olmeda Ester , Fuentes del Toro Sergio , Díaz Vicente
Published: February 2021

Nowadays, autonomous vehicles are increasing, and the driving scenario that includes both autonomous and human-driven vehicles is a fact. Knowing the driving styles of drivers in the process of automating vehicles is interest in order to make driving as natural as possible. To this end, this article presents a first approach to the design of a controller for the braking system capable of imitating the different manoeuvres that any driver performs while driving. With this aim, different experimental tests have been carried out with a vehicle instrumented with sensors capable of providing real-time information related to the braking system. The experimental tests consist of reproducing a series of braking manoeuvres at different speeds on a flat floor track following a straight path. The tests distinguish between three types of braking manoeuvre: maintained, progressive and emergency braking, which cover all the driving circumstances in which the braking system may intervene. This article presents an innovative approach to characterise braking types thanks to the methodology of analysing the data obtained by sensors during experimental tests. The characterisation of braking types makes it possible to dynamically classify three driving styles: cautious, normal and aggressive. The proposed classifications allow it possible to identify the driving styles on the basis of the pressure in the hydraulic brake circuit, the force exerted by the driver on the brake pedal, the longitudinal deceleration and the braking power, knowing in all cases the speed of the vehicle. The experiments are limited by the fact that there are no other vehicles, obstacles, etc. in the vehicle’s environment, but in this article the focus is exclusively on characterising a driver with methods that use the vehicle’s dynamic responses measured by on-board sensors. The results of this study can be used to define the driving style of an autonomous vehicle.
Investigation on Wireless Link for Medical Telemetry Including Impedance Matching of Implanted Antennas
Authors: Kim Ilkyu , Lee Sun-Gyu , Nam Yong-Hyun , Lee Jeong-Hae
Published: February 2021

The development of biomedical devices benefits patients by offering real-time healthcare. In particular, pacemakers have gained a great deal of attention because they offer opportunities for monitoring the patient’s vitals and biological statics in real time. One of the important factors in realizing real-time body-centric sensing is to establish a robust wireless communication link among the medical devices. In this paper, radio transmission and the optimal characteristics for impedance matching the medical telemetry of an implant are investigated. For radio transmission, an integral coupling formula based on 3D vector far-field patterns was firstly applied to compute the antenna coupling between two antennas placed inside and outside of the body. The formula provides the capability for computing the antenna coupling in the near-field and far-field region. In order to include the effects of human implantation, the far-field pattern was characterized taking into account a sphere enclosing an antenna made of human tissue. Furthermore, the characteristics of impedance matching inside the human body were studied by means of inherent wave impedances of electrical and magnetic dipoles. Here, we demonstrate that the implantation of a magnetic dipole is advantageous because it provides similar impedance characteristics to those of the human body.
Electrical Percolation Threshold and Size Effects in Polyvinylpyrrolidone-Oxidized Single-Wall Carbon Nanohorn Nanocomposite: The Impact for Relative Humidity Resistive Sensors Design
Authors: Serban Bogdan-Catalin , Cobianu Cornel , Dumbravescu Niculae , Buiu Octavian , Bumbac Marius , Nicolescu Cristina Mihaela , Cobianu Cosmin , Brezeanu Mihai , Pachiu Cristina , Serbanescu Matei
Published: February 2021

This paper reports, for the first time, on the electrical percolation threshold in oxidized carbon nanohorns (CNHox)–polyvinylpyrrolidone (PVP) films. We demonstrate—starting from the design and synthesis of the layers—how these films can be used as sensing layers for resistive relative humidity sensors. The morphology and the composition of the sensing layers are investigated through Scanning Electron Microscopy (SEM), Atomic Force Microscopy (AFM), and RAMAN spectroscopy. For establishing the electrical percolation thresholds of CNHox in PVP, these nanocomposite thin films were deposited on interdigitated transducer (IDT) dual-comb structures. The IDTs were processed both on a rigid Si/SiO2 substrate with a spacing of 10 µm between metal digits, and a flexible substrate (polyimide) with a spacing of 100 µm. The percolation thresholds of CNHox in the PVP matrix were equal to (0.05–0.1) wt% and 3.5 wt% when performed on 10 µm-IDT and 100 µm-IDT, respectively. The latter value agreed well with the percolation threshold value of about 4 wt% predicted by the aspect ratio of CNHox. In contrast, the former value was more than an order of magnitude lower than expected. We explained the percolation threshold value of (0.05–0.1) wt% by the increased probability of forming continuous conductive paths at much lower CNHox concentrations when the gap between electrodes is below a specific limit. The change in the nanocomposite’s longitudinal Young modulus, as a function of the concentration of oxidized carbon nanohorns in the polymer matrix, is also evaluated. Based on these results, we identified a new parameter (i.e., the inter-electrode spacing) affecting the electrical percolation threshold in micro-nano electronic devices. The electrical percolation threshold’s critical role in the resistive relative-humidity sensors’ design and functioning is clearly emphasized.
Physical-Layer Security Improvement with Reconfigurable Intelligent Surfaces for 6G Wireless Communication Systems
Authors: Youn Janghyuk , Son Woong , Jung Bang Chul
Published: February 2021

Recently, reconfigurable intelligent surfaces (RISs) have received much interest from both academia and industry due to their flexibility and cost-effectiveness in adjusting the phase and amplitude of wireless signals with low-cost passive reflecting elements. In particular, many RIS-aided techniques have been proposed to improve both data rate and energy efficiency for 6G wireless communication systems. In this paper, we propose a novel RIS-based channel randomization (RCR) technique for improving physical-layer security (PLS) for a time-division duplex (TDD) downlink cellular wire-tap network which consists of a single base station (BS) with multiple antennas, multiple legitimate pieces of user equipment (UE), multiple eavesdroppers (EVEs), and multiple RISs. We assume that only a line-of-sight (LOS) channel exists among the BS, the RISs, and the UE due to propagation characteristics of tera-hertz (THz) spectrum bands that may be used in 6G wireless communication systems. In the proposed technique, each RIS first pseudo-randomly generates multiple reflection matrices and utilizes them for both pilot signal duration (PSD) in uplink and data transmission duration (DTD) in downlink. Then, the BS estimates wireless channels of UE with reflection matrices of all RISs and selects the UE that has the best secrecy rate for each reflection matrix generated. It is shown herein that the proposed technique outperforms the conventional techniques in terms of achievable secrecy rates.
A Modular Design for Distributed Measurement of Human–Robot Interaction Forces in Wearable Devices
Authors: Ghonasgi Keya , Yousaf Saad N. , Esmatloo Paria , Deshpande Ashish D.
Published: February 2021

Measurement of interaction forces distributed across the attachment interface in wearable devices is critical for understanding ergonomic physical human–robot interaction (pHRI). The main challenges in sensorization of pHRI interfaces are (i) capturing the fine nature of force transmission from compliant human tissue onto rigid surfaces in the wearable device and (ii) utilizing a low-cost and easily implementable design that can be adapted for a variety of human interfaces. This paper addresses both challenges and presents a modular sensing panel that uses force-sensing resistors (FSRs) combined with robust electrical and mechanical integration principles that result in a reliable solution for distributed load measurement. The design is demonstrated through an upper-arm cuff, which uses 24 sensing panels, in conjunction with the Harmony exoskeleton. Validation of the design with controlled loading of the sensorized cuff proves the viability of FSRs in an interface sensing solution. Preliminary experiments with a human subject highlight the value of distributed interface force measurement in recognizing the factors that influence ergonomic pHRI and elucidating their effects. The modular design and low cost of the sensing panel lend themselves to extension of this approach for studying ergonomics in a variety of wearable applications with the goal of achieving safe, comfortable, and effective human–robot interaction.
Sensor Development for Corrosion Monitoring of Stainless Steels in H2SO4 Solutions
Authors: Hren Miha , Kosec Tadeja , Lindgren Mari , Huttunen-Saarivirta Elina , Legat Andraž
Published: February 2021

Equipment made of different stainless steels is often used in the hydrometallurgical processing industry. In this study, an electrical resistance sensor was developed for monitoring corrosion in acidic solutions at high temperature. Two types of stainless steel were used as the electrode materials, namely grade 316L stainless steel (EN 1.4404) and grade 2507 duplex stainless steel (EN 1.4410). The materials and sensors were exposed to a 10% H2SO4 solution containing 5000 mg/L of NaCl at various temperatures. Results from the sensors were verified using electrochemical techniques and postexposure examination. Results showed that the microstructure played an important role in the interpretation of corrosion rates, highlighting the importance of using an appropriate stainless steel for the production of sensors. Electrochemical tests and postexposure examination both showed that the grade 2507 had a significantly lower corrosion rate compared to the grade 316L. Under industrial‑process conditions, the results for the grade 2507 sensor were promising with respect to sensor durability and performance, despite the extremely harsh operating environment.