bluuebunny/crossref_metadata_2025 huggingface dataset:
A Novel and Effective Recyclable BiOCl/BiOBr Photocatalysis for Lignin Removal from Pre-Hydrolysis Liquor
Authors: Zhang Shengyu , Chen Jiachuan , Jia Qianqian , Jiang Qimeng , Yan Jiaqiang , Yang Guihua
Published: October 2021

The presence of lignin hampers the utilization of hemicelluloses in the pre-hydrolysis liquor (PHL) from the kraft-based dissolving pulp production process. In this paper, a novel process for removing lignin from PHL was proposed by effectively recycling catalysts of BiOCl/BiOBr. During the whole process, BiOCl and BiOBr were not only adsorbents for removing lignin, but also photocatalysts for degrading lignin. The results showed that BiOCl and BiOBr treatments caused 36.3% and 33.9% lignin removal, respectively, at the optimized conditions, and the losses of hemicellulose-derived saccharides (HDS) were both 0.1%. The catalysts could be regenerated by simple photocatalytic treatment and obtain considerable CO and CO2. After 15 h of illumination, 49.9 μmol CO and 553.0 μmol CO2 were produced by BiOCl, and 38.7 μmol CO and 484.3 μmol CO2 were produced by BiOBr. Therefore, both BiOCl and BiOBr exhibit excellent adsorption and photocatalytic properties for lignin removal from pre-hydrolysis.
Enhanced Energy Density for P-Doped Hierarchically Porous Carbon-Based Symmetric Supercapacitor with High Operation Potential in Aqueous H2SO4 Electrolyte
Authors: Wu Xiaozhong , Yang Xinping , Feng Wei , Wang Xin , Miao Zhichao , Zhou Pengfei , Zhao Jinping , Zhou Jin , Zhuo Shuping
Published: October 2021

Phosphorus-doped hierarchically porous carbon (HPC) is prepared with the assistance of freeze-drying using colloid silica and phytic acid dipotassium salt as a hard template and phosphorus source, respectively. Intensive material characterizations show that the freeze-drying process can effectively promote the porosity of HPC. The specific surface area and P content for HPC can reach up to 892 m2 g−1 and 2.78 at%, respectively. Electrochemical measurements in aqueous KOH and H2SO4 electrolytes reveal that K+ of a smaller size can more easily penetrate the inner pores compared with SO42−, while the developed microporosity in HPC is conducive to the penetration of SO42−. Moreover, P-doping leads to a high operation potential of 1.5 V for an HPC-based symmetric supercapacitor, resulting in an enhanced energy density of 16.4 Wh kg−1. Our work provides a feasible strategy to prepare P-doped HPC with a low dosage of phosphorus source and a guide to construct a pore structure suitable for aqueous H2SO4 electrolyte.
Photo-Sintered Silver Thin Films by a High-Power UV-LED Module for Flexible Electronic Applications
Authors: Kim Minha , Jee Hongsub , Lee Jaehyeong
Published: October 2021

In recent printed electronics technology, a photo-sintering technique using intense pulsed light (IPL) source has attracted attention, instead of conventional a thermal sintering process with long time and high temperature. The key principle of the photo-sintering process is the selective heating of a thin film with large light absorption coefficients, while a transparent substrate does not heat by the IPL source. Most research on photo-sintering has used a xenon flash lamp as a light source. However, the xenon flash lamp requires instantaneous high power and is unsuitable for large area applications. In this work, we developed a new photo-sintering system using a high-power ultraviolet light emitting diode (UV-LED) module. A LED light source has many merits such as low power consumption and potential large-scale application. The silver nanoparticles ink was inkjet-printed on a polyethylene terephthalate (PET) and photo-sintered by the UV-LED module with the wavelength of 365 and 385 nm. The electrical resistivity as low as 5.44 × 10−6 Ω·cm (just about three times compared to value of bulk silver) was achieved at optimized photo-sintering conditions (wavelength of 365 nm and light intensity of 300 mW/cm2).
Effect of RF Power on the Physical Properties of Sputtered ZnSe Nanostructured Thin Films for Photovoltaic Applications
Authors: Toma Ovidiu , Antohe Vlad-Andrei , Panaitescu Ana-Maria , Iftimie Sorina , Răduţă Ana-Maria , Radu Adrian , Ion Lucian , Antohe Ştefan
Published: October 2021

Zinc selenide (ZnSe) thin films were deposited by RF magnetron sputtering in specific conditions, onto optical glass substrates, at different RF plasma power. The prepared ZnSe layers were afterwards subjected to a series of structural, morphological, optical and electrical characterizations. The obtained results pointed out the optimal sputtering conditions to obtain ZnSe films of excellent quality, especially in terms of better optical properties, lower superficial roughness, reduced micro-strain and a band gap value closer to the one reported for the ZnSe bulk semiconducting material. Electrical characterization were afterwards carried out by measuring the current–voltage (I-V) characteristics at room temperature, of prepared “sandwich”-like Au/ZnSe/Au structures. The analysis of I-V characteristics have shown that at low injection levels there is an Ohmic conduction, followed at high injection levels, after a well-defined transition voltage, by a Space Charge Limited Current (SCLC) in the presence of an exponential trap distribution in the band gap of the ZnSe thin films. The results obtained from all the characterization techniques presented, demonstrated thus the potential of ZnSe thin films sputtered under optimized RF plasma conditions, to be used as alternative environmentally-friendly Cd-free window layers within photovoltaic cells manufacturing.
Sports Nutrition: Diets, Selection Factors, Recommendations
Authors: Malsagova Kristina A. , Kopylov Arthur T. , Sinitsyna Alexandra A. , Stepanov Alexander A. , Izotov Alexander A. , Butkova Tatyana V. , Chingin Konstantin , Klyuchnikov Mikhail S. , Kaysheva Anna L.
Published: October 2021

An athlete’s diet is influenced by external and internal factors that can reduce or exacerbate exercise-induced food intolerance/allergy symptoms. This review highlights many factors that influence food choices. However, it is important to remember that these food choices are dynamic, and their effectiveness varies with the time, location, and environmental factors in which the athlete chooses the food. Therefore, before training and competition, athletes should follow the recommendations of physicians and nutritionists. It is important to study and understand the nutritional strategies and trends that athletes use before and during training or competitions. This will identify future clinical trials that can be conducted to identify specific foods that athletes can consume to minimize negative symptoms associated with their consumption and optimize training outcomes.
The Nutritional Supply of Iodine and Selenium Affects Thyroid Hormone Axis Related Endpoints in Mice
Authors: Lossow Kristina , Renko Kostja , Schwarz Maria , Schomburg Lutz , Schwerdtle Tanja , Kipp Anna Patricia
Published: October 2021

Selenium and iodine are the two central trace elements for the homeostasis of thyroid hormones but additional trace elements such as iron, zinc, and copper are also involved. To compare the primary effects of inadequate intake of selenium and iodine on the thyroid gland, as well as the target organs of thyroid hormones such as liver and kidney, mice were subjected to an eight-week dietary intervention with low versus adequate selenium and iodine supply. Analysis of trace element levels in serum, liver, and kidney demonstrated a successful intervention. Markers of the selenium status were unaffected by the iodine supply. The thyroid gland was able to maintain serum thyroxine levels even under selenium-deficient conditions, despite reduced selenoprotein expression in liver and kidney, including deiodinase type 1. Thyroid hormone target genes responded to the altered selenium and iodine supply, whereas the iron, zinc, and copper homeostasis remained unaffected. There was a notable interaction between thyroid hormones and copper, which requires further clarification. Overall, the effects of an altered selenium and iodine supply were pronounced in thyroid hormone target tissues, but not in the thyroid gland.
Histamine H3 Receptor Ligands—KSK-59 and KSK-73—Reduce Body Weight Gain in a Rat Model of Excessive Eating
Authors: Mika Kamil , Szafarz Małgorzata , Bednarski Marek , Latacz Gniewomir , Sudoł Sylwia , Handzlik Jadwiga , Pociecha Krzysztof , Knutelska Joanna , Nicosia Noemi , Szczepańska Katarzyna , Kuder Kamil J. , Kieć-Kononowicz Katarzyna , Kotańska Magdalena
Published: October 2021

Noting the worldwide rapid increase in the prevalence of overweight and obesity new effective drugs are now being sought to combat these diseases. Histamine H3 receptor antagonists may represent an effective therapy as they have been shown to modulate histamine synthesis and release and affect a number of other neurotransmitters (norepinephrine, acetylcholine, γ-aminobutyric acid, serotonin, substance P) thus influencing the food intake. Based on the preliminary studies determining affinity, intrinsic activity, and selected pharmacokinetic parameters, two histamine H3 receptor ligands were selected. Female rats were fed palatable food for 28 days and simultaneously administered the tested compounds intraperitoneally (i.p.) at a dose of 10 or 1 mg/kg b.w./day. Weight was evaluated daily and calorie intake was evaluated once per week. The plasma levels of cholesterol, triglycerides, leptin, adiponectin, ghrelin, corticosterone, CRP and IL-6 were determined at the end of experiment. The glucose tolerance test was also performed. To exclude false positives, the effect of tested compounds on spontaneous activity was monitored during the treatment, as well as the amount of consumed kaolin clay was studied as a reflection of possible gastrointestinal disturbances comparable to nausea. The histamine H3 receptor antagonists KSK-59 and KSK-73 administered i.p. at a dose of 10 mg/kg b.w. prevented weight gain in a rat model of excessive eating. They reduced adipose tissue deposits and improved glucose tolerance. Both compounds showed satisfying ability to penetrate through biological membranes determined in in vitro studies. Compound KSK-73 also reduced the caloric intake of the experimental animals what indicates its anorectic effect. These results show the pharmacological properties of histamine H3 receptor antagonists, (4-pyridyl)piperazine derivatives, as the compounds causing not only slower weight gain but also ameliorating some metabolic disorders in rats having the opportunity to overeat.
Binder Jet 3D Printing of Compound LEV-PN Dispersible Tablets: An Innovative Approach for Fabricating Drug Systems with Multicompartmental Structures
Authors: Hong Xiaoxuan , Han Xiaolu , Li Xianfu , Li Jiale , Wang Zengming , Zheng Aiping
Published: October 2021

Three-dimensional (3D) printing is an emerging technology that has high application potential for individualized medicines and complex solid dosage forms. This study is designed to explore binder jet 3D printing (BJ-3DP) for the development of high-precision and repeatable compound levetiracetam-pyridoxine hydrochloride (LEV-PN) multicompartmental structure dispersible tablets. PN was dissolved in printing ink directly and accurately jetted into the middle, nested layer of the tablet, and precise control of the drug dose was achieved through the design of printing layers. With modification of the drying method, the “coffee ring” effect caused by drug migration during the curing and molding of the tablets was overcome. Furthermore, 3D topography showed that the tablets have a promising surface morphology. Scanning electron microscopy and porosity results indicated that the tablets have a loose interior and tight exterior, which would ensure good mechanical properties while enabling the tablet to disintegrate quickly in the mouth and achieve rapid release of the two drugs. This study used BJ-3DP technology to prepare personalized multicompartmental structures of drug systems and provides a basis for the development of complex preparations.
Genome-Wide Transcriptomic and Proteomic Exploration of Molecular Regulations in Quinoa Responses to Ethylene and Salt Stress
Authors: Ma Qian , Su Chunxue , Dong Chun-Hai
Published: October 2021

Quinoa (Chenopodiumquinoa Willd.), originated from the Andean region of South America, shows more significant salt tolerance than other crops. To reveal how the plant hormone ethylene is involved in the quinoa responses to salt stress, 4-week-old quinoa seedlings of ‘NL-6′ treated with water, sodium chloride (NaCl), and NaCl with ethylene precursor 1-aminocyclopropane-1-carboxylic acid (ACC) were collected and analyzed by transcriptional sequencing and tandem mass tag-based (TMT) quantitative proteomics. A total of 9672 proteins and 60,602 genes was identified. Among them, the genes encoding glutathione S-transferase (GST), peroxidase (POD), phosphate transporter (PT), glucan endonuclease (GLU), beta-galactosidase (BGAL), cellulose synthase (CES), trichome birefringence-like protein (TBL), glycine-rich cell wall structural protein (GRP), glucosyltransferase (GT), GDSL esterase/lipase (GELP), cytochrome P450 (CYP), and jasmonate-induced protein (JIP) were significantly differentially expressed. Further analysis suggested that the genes may mediate through osmotic adjustment, cell wall organization, reactive oxygen species (ROS) scavenging, and plant hormone signaling to take a part in the regulation of quinoa responses to ethylene and salt stress. Our results provide a strong foundation for exploration of the molecular mechanisms of quinoa responses to ethylene and salt stress.
Understanding Wheat Starch Metabolism in Properties, Environmental Stress Condition, and Molecular Approaches for Value-Added Utilization
Authors: Kim Kyung-Hee , Kim Jae-Yoon
Published: October 2021

Wheat starch is one of the most important components in wheat grain and is extensively used as the main source in bread, noodles, and cookies. The wheat endosperm is composed of about 70% starch, so differences in the quality and quantity of starch affect the flour processing characteristics. Investigations on starch composition, structure, morphology, molecular markers, and transformations are providing new and efficient techniques that can improve the quality of bread wheat. Additionally, wheat starch composition and quality are varied due to genetics and environmental factors. Starch is more sensitive to heat and drought stress compared to storage proteins. These stresses also have a great influence on the grain filling period and anthesis, and, consequently, a negative effect on starch synthesis. Sucrose metabolizing and starch synthesis enzymes are suppressed under heat and drought stress during the grain filling period. Therefore, it is important to illustrate starch and sucrose mechanisms during plant responses in the grain filling period. In recent years, most of these quality traits have been investigated through genetic modification studies. This is an attractive approach to improve functional properties in wheat starch. The new information collected from hybrid and transgenic plants is expected to help develop novel starch for understanding wheat starch biosynthesis and commercial use. Wheat transformation research using plant genetic engineering technology is the main purpose of continuously controlling and analyzing the properties of wheat starch. The aim of this paper is to review the structure, biosynthesis mechanism, quality, and response to heat and drought stress of wheat starch. Additionally, molecular markers and transformation studies are reviewed to elucidate starch quality in wheat.
Genome-Wide Analysis of the Homeobox Gene Family and Identification of Drought-Responsive Members in Populus trichocarpa
Authors: Hou Jing , Sun Yan , Wang Lei , Jiang Yuanzhong , Chen Ningning , Tong Shaofei
Published: October 2021

Homeobox (HB) genes play critical roles in the regulation of plant morphogenesis, growth and development. Here, we identified a total of 156 PtrHB genes from the Populus trichocarpa genome. According to the topologies and taxonomy of the phylogenetic tree constructed by Arabidopsis thaliana HB members, all PtrHB proteins were divided into six subgroups, namely HD-ZIP, ZF-HD, HB-PHD, TALE, WOX and HB-OTHERS. Multiple alignments of conserved homeodomains (HDs) revealed the conserved loci of each subgroup, while gene structure analysis showed similar exon–intron gene structures, and motif analysis indicated the similarity of motif number and pattern in the same subgroup. Promoter analysis indicated that the promoters of PtrHB genes contain a series of cis-acting regulatory elements involved in responding to various abiotic stresses, indicating that PtrHBs had potential functions in these processes. Collinearity analysis revealed that there are 96 pairs of 127 PtrHB genes mainly distributing on Chromosomes 1, 2, and 5. We analyzed the spatio-temporal expression patterns of PtrHB genes, and the virus-induced gene silencing (VIGS) of PtrHB3 gene resulted in the compromised tolerance of poplar seedlings to mannitol treatment. The bioinformatics on PtrHB family and preliminary exploration of drought-responsive genes can provide support for further study of the family in woody plants, especially in drought-related biological processes. It also provides a direction for developing new varieties of poplar with drought resistance. Overall, our results provided significant information for further functional analysis of PtrHB genes in poplar and demonstrated that PtrHB3 is a dominant gene regulating tolerance to water stress treatment in poplar seedlings.
Undiscovered Biodiversity of the European Moss Flora: Neodicranella hamulosa (Aongstroemiaceae), a New Genus and Species from SW Portugal
Authors: Porley Ronald D. , Fedosov Vladimir , Plášek Vítězslav , Fedorova Alina
Published: October 2021

A new genus is described to accommodate Neodicranella hamulosa, a novel species resolved in the family Aongstroemiaceae, from the Monchiquense district in SW Portugal. Characterized by its small size, erect spreading to subsecund non-sheathing leaves, plane bistratose leaf margins, and rhizoidal gemmae with slightly protruberant cells, it differs from all other European Dicranellaceae in the uniquely patterned distal peristome segments with backward-pointing papillae resembling hooked barbs. The species appears to be endemic to the sub-Mediterranean bioclimatic zone, in wooded biomes where humidity remains relatively high throughout the year. Morphological and molecular data strongly support the singularity of this new taxon. The species is illustrated by photomicrographs and SEM, and its ecology and conservation are discussed.
Assessing the Response of Diverse Sesame Genotypes to Waterlogging Durations at Different Plant Growth Stages
Authors: Habibullah Mohammad , Sarkar Shahnaz , Islam Mohammad Mahbub , Ahmed Kamal Uddin , Rahman Md. Zillur , Awad Mohamed F. , ElSayed Abdelaleim I. , Mansour Elsayed , Hossain Md. Sazzad
Published: October 2021

Sesame is sensitive to waterlogging, and its growth is devastatingly impacted under excess moisture conditions. Thus, waterlogging tolerance is crucial to alleviate yield constraints, particularly under expected climate change. In this study, 119 diverse sesame genotypes were screened for their tolerance to 12, 24, 48, and 72 h of waterlogging relative to non-waterlogged conditions. All plants died under 72 h of waterlogging, while 13.45%, 31.93%, and 45.38% of genotypes survived at 48, 24, and 12 h, respectively. Based on the seedling parameters and waterlogging tolerance coefficients, genotypes BD-7008 and BD-6985 exhibited the highest tolerance to waterlogging, while BD-6996 and JP-01811 were the most sensitive ones. The responses of these four genotypes to waterlogged conditions were assessed at different plant growth stages—30, 40, and 50 days after sowing (DAS)—versus normal conditions. Waterlogging, particularly when it occurred within 30 DAS, destructively affected the physiological and morphological characteristics, which was reflected in the growth and yield attributes. Genotype BD-7008, followed by BD-6985, exhibited the highest chlorophyll and proline contents as well as enzymatic antioxidant activities, including superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT). These biochemical and physiological adjustments ameliorated the adverse effects of waterlogging, resulting in higher yields for both genotypes. Conversely, JP-01811 presented the lowest chlorophyll and proline contents as well as enzymatic antioxidant activities, resulting in the poorest growth and seed yield.
Determination of Antibiotics, Pesticides, Herbicides, Fungicides and Hormones in Water Bodies in Italy in Occurrence with European Watch List Mechanism by Using an UHPLC-MS/MS System: Method Validation, Quantification and Evaluations
Authors: Barreca Salvatore , Busetto Maddalena , Forni Carola , Colzani Luisa , Clerici Laura , Daverio Daniela , Balzamo Stefania , Calabretta Elisa , Peleggi Massimo , Dellavedova Pierluisa
Published: October 2021

In recent years, the quality of aquatic ecosystems has received increasing attention from European institutions. The Commission Implementing Decision (EU) 2018/840 drafted a Watch List (WL) of compounds to be monitored in Europe. In this study, we report a method based on solid phase extraction with ultra-high-performance liquid chromatography, coupled with a triple-quadrupole mass spectrometer (UHPLC-MS/MS) to analyze the whole water sample. The method was developed and validated for the determination of 12 listed compounds. The employment of solid-phase extraction by a horizon system ensures the analysis of the entire body of samples and minimizes sample manipulation. Different ng L−1 detection limits (from 2 to 50 ng L−1), linearities (from 2 to 500 ng L−1), accuracy (from 70 to 130%) and levels of precision (RSD less 20% at LOQs levels) were assessed to be satisfactory for quantification and confirmation at the levels of interest. The developed method was applied for quantitative analysis for Watch List compounds (with the exception of hormones) in surface water samples from different Italian sites during monitoring activities by the Regional Environmental Protection Agencies in the years 2019 and 2020.
The Room Temperature Highly Sensitive Ammonia Gas Sensor Based on Polyaniline and Nitrogen-Doped Graphene Quantum Dot-Coated Hollow Indium Oxide Nanofiber Composite
Authors: Hong Sheng-Zhe , Huang Qing-Yi , Wu Tzong-Ming
Published: October 2021

Hollow indium trioxide (In2O3) nanofibers fabricated via an effectively combined method of electrospinning and high-temperature calcination were coated with nitrogen-doped graphene quantum dots (N-GQDs) prepared by a hydrothermal process through electrostatic interaction. The N-GQD-coated hollow In2O3 nanofibers served as a core for the synthesis of polyaniline (PANI)/N-GQD/hollow In2O3 nanofiber ternary composites using in situ chemical oxidative polymerization. The chemical structure and morphology of the fabricated ternary composites were characterized using Fourier transform infrared, field-emission scanning electron microscopy, and transmission electron microscopy. The gas-sensing performances of the ternary composites were estimated by a homemade dynamic test system which was supplied with a real-time resistance acquisition platform at room temperature. The response value of the PANI/N-GQD/hollow In2O3 nanofiber sensor with a loading of 20 wt% N-GQD-coated hollow In2O3 nanofiber and an exposure of 1 ppm NH3 was 15.2, which was approximately more than 4.4 times higher than that of the PANI sensor. This ternary composite sensor was proved to be very sensitive in the detection of NH3 at a range of concentration between 0.6 ppm and 2.0 ppm at room temperature, which is crucial in the detection of hepatic or kidney disease in human breath. The PANI/N-GQD/hollow In2O3 nanofiber sensor also revealed higher selectivity and repeatability when exposed to 1.0 and 2.0 ppm NH3 at room temperature. Because of the excellent selectivity and repeatability in the detection of 1.0 and 2.0 ppm NH3 at room temperature achieved in this study, it is considered that the PANI/N-GQD/hollow In2O3 nanofiber composite sensor will be a favored gas-sensing material applied on human breath for the detection of hepatic or kidney disease.
Conversion of Organic Matter of Carbonate Deposits in the Hydrothermal Fluid
Authors: Petrov Sergey M. , Lakhova Alfiya I. , Safiulina Aliya G. , Ignashev Nikita E. , Khelkhal Mohammed A. , Vakhin Alexey V.
Published: October 2021

This present paper investigates the conversion of organic matter in carbonate rocks of the Semiluksko-Mendymsky horizon Volga-Ural Basin under hydrothermal conditions with excess water in subcritical conditions at 613–653 K and 170–200 Bar. It has been found that the content of hydrocarbon extracts increases (relatively) which indicates the oil-generating potential of the studied deposits. Besides, it has been shown that organic matter undergoes oxidation reactions under hydrothermal conditions, as indicated by the presence of oxidized structures in the extracted hydrocarbons. Moreover, our results indicate that increasing the temperature and pressure of the used hydrothermal fluid leads to an increase in the content of n-alkanes C25-C30 and asphaltenes in the extracts. On the other hand, it has been found that saturated, aromatic hydrocarbons and resins content decreases at this stage. The obtained data about the geochemical parameters dependencies of the hydrocarbons obtained from the studied carbonate rock on temperature and pressure associated to hydrothermal effect show possible pathways of migration, genesis, and formation of hydrocarbon deposits.
Multi-Variable Multi-Objective Optimization Algorithm for Optimal Design of PMa-SynRM for Electric Bicycle Traction Motor
Authors: Son Ji-Chang , Yi Kyung-Pyo , Lim Dong-Kuk
Published: October 2021

In this paper, internal division point genetic algorithm (IDP-GA) was proposed to lessen the computational burden of multi-variable multi-objective optimization problem using finite element analysis such as optimal design of electric bicycles. The IDP-GA could consider various objectives with normalized weighted sum method and could reduce the number of function calls with novel crossover strategy and vector-based pattern search method. The superiority of the proposed algorithm was verified by comparing performances with conventional optimization method at two mathematical test functions. Finally, the applicability of the IDP-GA in practical electric machine design was verified by successfully deriving an improved design of electric bicycle propulsion motor.
Recycling of WEEE Plastics Waste in Mortar: The Effects on Mechanical Properties
Authors: Merlo Alessandra , Lavagna Luca , Suarez-Riera Daniel , Pavese Matteo
Published: October 2021

This work focused on the recycling of WEEE plastic waste as a partial substitute for aggregate in light mortars. The plastic mix, provided by the IREN group, was used as a replacement of aggregate in 15, 30, 45, 60, 75, and 90%vol in mortars. Worsening of the mechanical performance of around 50% was detected already at only 15%vol of mineral aggregate substituted with plastic waste. The explanation of this phenomenon was found in both the scarce mechanical properties of the used plastic and in the poor adhesion between matrix and plastics that resulted in extra-porosity formation, as also demonstrated by comparing the results with several models in the literature. However, the use of plastic waste as a partial replacement of natural aggregate contributes to the preservation of natural resources and, in any case, does not limit the application of these materials in non-structural applications.
DisasterGAN: Generative Adversarial Networks for Remote Sensing Disaster Image Generation
Authors: Rui Xue , Cao Yang , Yuan Xin , Kang Yu , Song Weiguo
Published: October 2021

Rapid progress on disaster detection and assessment has been achieved with the development of deep-learning techniques and the wide applications of remote sensing images. However, it is still a great challenge to train an accurate and robust disaster detection network due to the class imbalance of existing data sets and the lack of training data. This paper aims at synthesizing disaster remote sensing images with multiple disaster types and different building damage with generative adversarial networks (GANs), making up for the shortcomings of the existing data sets. However, existing models are inefficient in multi-disaster image translation due to the diversity of disaster and inevitably change building-irrelevant regions caused by directly operating on the whole image. Thus, we propose two models: disaster translation GAN can generate disaster images for multiple disaster types using only a single model, which uses an attribute to represent disaster types and a reconstruction process to further ensure the effect of the generator; damaged building generation GAN is a mask-guided image generation model, which can only alter the attribute-specific region while keeping the attribute-irrelevant region unchanged. Qualitative and quantitative experiments demonstrate the validity of the proposed methods. Further experimental results on the damaged building assessment model show the effectiveness of the proposed models and the superiority compared with other data augmentation methods.
MIMO-SAR Interferometric Measurements for Structural Monitoring: Accuracy and Limitations
Authors: Baumann-Ouyang Andreas , Butt Jemil Avers , Salido-Monzú David , Wieser Andreas
Published: October 2021

Terrestrial Radar Interferometry (TRI) is a measurement technique capable of measuring displacements with high temporal resolution at high accuracy. Current implementations of TRI use large and/or movable antennas for generating two-dimensional displacement maps. Multiple Input Multiple Output Synthetic Aperture Radar (MIMO-SAR) systems are an emerging alternative. As they have no moving parts, they are more easily deployable and cost-effective. These features suggest the potential usage of MIMO-SAR interferometry for structural health monitoring (SHM) supplementing classical geodetic and mechanical measurement systems. The effects impacting the performance of MIMO-SAR systems are, however, not yet sufficiently well understood for practical applications. In this paper, we present an experimental investigation of a MIMO-SAR system originally devised for automotive sensing, and assess its capabilities for deformation monitoring. The acquisitions generated for these investigations feature a 180∘ Field-of-View (FOV), distances of up to 60 m and a temporal sampling rate of up to 400 Hz. Experiments include static and dynamic setups carried out in a lab-environment and under more challenging meteorological conditions featuring sunshine, fog, and cloud-cover. The experiments highlight the capabilities and limitations of the radar, while allowing quantification of the measurement uncertainties, whose sources and impacts we discuss. We demonstrate that, under sufficiently stable meteorological conditions with humidity variations smaller than 1%, displacements as low as 25 μm can be detected reliably. Detecting displacements occurring over longer time frames is limited by the uncertainty induced by changes in the refractive index.
Constraint Loss for Rotated Object Detection in Remote Sensing Images
Authors: Zhang Luyang , Wang Haitao , Wang Lingfeng , Pan Chunhong , Liu Qiang , Wang Xinyao
Published: October 2021

Rotated object detection is an extension of object detection that uses an oriented bounding box instead of a general horizontal bounding box to define the object position. It is widely used in remote sensing images, scene text, and license plate recognition. The existing rotated object detection methods usually add an angle prediction channel in the bounding box prediction branch, and smooth L1 loss is used as the regression loss function. However, we argue that smooth L1 loss causes a sudden change in loss and slow convergence due to the angle solving mechanism of open CV (the angle between the horizontal line and the first side of the bounding box in the counter-clockwise direction is defined as the rotation angle), and this problem exists in most existing regression loss functions. To solve the above problems, we propose a decoupling modulation mechanism to overcome the problem of sudden changes in loss. On this basis, we also proposed a constraint mechanism, the purpose of which is to accelerate the convergence of the network and ensure optimization toward the ideal direction. In addition, the proposed decoupling modulation mechanism and constraint mechanism can be integrated into the popular regression loss function individually or together, which further improves the performance of the model and makes the model converge faster. The experimental results show that our method achieves 75.2% performance on the aerial image dataset DOTA (OBB task), and saves more than 30% of computing resources. The method also achieves a state-of-the-art performance in HRSC2016, and saved more than 40% of computing resources, which confirms the applicability of the approach.
Enhanced Sensitivity and Detection of Near-Infrared Refractive Index Sensor with Plasmonic Multilayers
Authors: Nguyen Tan Tai , Van Sau Nguyen , Ngo Quang Minh , Eppe Gauthier , Tran Ngoc Quyen , Thi Phuong Anh Nguyen
Published: October 2021

In this work, the multilayer of the surface plasmon resonance (SPR) sensor was optimized to achieve the maximum sensor sensitivity. By optimizing the thickness of the silver layer (Ag) and dielectric films (TiO2 and AlAs), the optimum sensitivity of the SPR sensor could be obtained. The performance of the SPR sensor proposed was compared with control simulations utilizing zinc oxide (ZnO) and molybdenum oxide (MoO3). The numerical results indicate that the figure-of-merits (FOM) of the SPR sensor was achieved around 150/RIU, corresponding to the sensor sensitivity of 162.79°/RIU with the optimized thicknesses of the TiO2, Ag, and AlAs layers of 140 nm, 60 nm, and 25 nm, respectively. This refractive index sensor shows the FOM to have high detection accuracy and high sensitivity that lead to finding potential application in bio-chemical detection with a small volume of liquid used in biological diagnosis.
Detecting Phase-Synchrony Connectivity Anomalies in EEG Signals. Application to Dyslexia Diagnosis
Authors: Formoso Marco A. , Ortiz Andrés , Martinez-Murcia Francisco J. , Gallego Nicolás , Luque Juan L.
Published: October 2021

Objective Dyslexia diagnosis is a challenging task, since traditional diagnosis methods are not based on biological markers but on behavioural tests. Although dyslexia diagnosis has been addressed by these tests in clinical practice, it is difficult to extract information about the brain processes involved in the different tasks and, then, to go deeper into its biological basis. Thus, the use of biomarkers can contribute not only to the diagnosis but also to a better understanding of specific learning disorders such as dyslexia. In this work, we use Electroencephalography (EEG) signals to discover differences among controls and dyslexic subjects using signal processing and artificial intelligence techniques. Specifically, we measure phase synchronization among channels, to reveal the functional brain network activated during auditory processing. On the other hand, to explore synchronicity patterns risen by low-level auditory processing, we used specific stimuli consisting in band-limited white noise, modulated in amplitude at different frequencies. The differential information contained in the functional (i.e., synchronization) network has been processed by an anomaly detection system that addresses the problem of subjects variability by an outlier-detection method based on vector quantization. The results, obtained for 7 years-old children, show that the proposed method constitutes an useful tool for clinical use, with the area under ROC curve (AUC) values up to 0.95 in differential diagnosis tasks.
Model Test Study on Deformation of Snowflake Shaped Steel Sheet Pile Based on OFDR
Authors: Gao Lei , Xu Zhongquan , Wang Quan , Zhang Zhenlei , Li Ping
Published: October 2021

As a newly developed pile foundation, the snowflake shaped steel sheet pile is composed of three Y-shaped sections with an included angle of 120° and has a large specific surface area, which can give full play to the side friction of pile and improve the bearing capacity of single pile. At the same time, the snowflake shaped steel sheet pile has a high strength, relatively few materials, and it has good prospects with engineering applications. In order to accurately grasp the mechanical characteristics of the snowflake shaped steel sheet pile, this paper carried out the model test of snowflake shaped steel sheet pile based on OFDR (optical frequency domain reflector) distributed optical fiber sensor technology. The results show that: (1) OFDR distributed optical fiber sensing technology can effectively monitor the strain of snowflake steel sheet pile; (2) under the vertical load, the strain of snowflake steel sheet pile decreases along the length of the pile; (3) the strain of the same section of snowflake steel sheet pile is different at different positions, the strain at the junction between web and web is basically the same as the junction between web and flange, and the strain of the pile shaft on the flange edge is larger.
2D Quantitative Imaging of Magnetic Nanoparticles by an AC Biosusceptometry Based Scanning Approach and Inverse Problem
Authors: Biasotti Gabriel Gustavo de Albuquerque , Próspero Andre Gonçalves , Alvarez Marcelo Dante Tacconi , Liebl Maik , Pinto Leonardo Antonio , Soares Guilherme Augusto , Bakuzis Andris Figueiroa , Baffa Oswaldo , Wiekhorst Frank , Miranda José Ricardo de Arruda
Published: October 2021

The use of magnetic nanoparticles (MNPs) in biomedical applications requires the quantitative knowledge of their quantitative distribution within the body. AC Biosusceptometry (ACB) is a biomagnetic technique recently employed to detect MNPs in vivo by measuring the MNPs response when exposed to an alternate magnetic field. The ACB technique presents some interesting characteristics: non-invasiveness, low operational cost, high portability, and no need for magnetic shielding. ACB conventional methods until now provided only qualitative information about the MNPs’ mapping in small animals. We present a theoretical model and experimentally demonstrate the feasibility of ACB reconstructing 2D quantitative images of MNPs’ distributions. We employed an ACB single-channel scanning approach, measuring at 361 sensor positions, to reconstruct MNPs’ spatial distributions. For this, we established a discrete forward problem and solved the ACB system’s inverse problem. Thus, we were able to determine the positions and quantities of MNPs in a field of view of 5×5×1 cm3 with good precision and accuracy. The results show the ACB system’s capabilities to reconstruct the quantitative spatial distribution of MNPs with a spatial resolution better than 1 cm, and a sensitivity of 1.17 mg of MNPs fixed in gypsum. These results show the system’s potential for biomedical application of MNPs in several studies, for example, electrochemical-functionalized MNPs for cancer cell targeting, quantitative sensing, and possibly in vivo imaging.
Bluetooth Low Energy Beacon Sensors to Document Handheld Magnifier Use at Home by People with Low Vision
Authors: Bittner Ava K. , Estabrook Max , Dennis Niki
Published: October 2021

We explored the feasibility of using Bluetooth low energy (BLE) beacon sensors to determine when individuals with low vision (LV) use handheld magnifiers at home. Knowing the frequency and duration of magnifier use would be helpful to document increased magnifier use after successful rehabilitation training, or conversely, to know when someone has abandoned a magnifier and requires assistance. Estimote Sticker BLE beacon sensors were attached to the handles of optical handheld magnifiers and dispensed to eight LV subjects to use at home. Temperature and motion data from the BLE beacon sensors were collected every second by a custom mobile application on a nearby smartphone and transmitted to a secure database server. Subjects noted the date and start/end times of their magnifier use in a diary log. Each of the 99 diary-logged self-reports of magnifier use across subjects was associated with BLE beacon sensor recordings of motion (mean 407 instances; SD 365) and increased temperature (mean 0.20 °C per minute; SD 0.16 °C) (mean total magnitude 5.4 °C; SD 2.6 °C). Diary-logged duration of magnifier use (mean 42 min; SD 24) was significantly correlated with instances of motion (p < 0.001) and rate of temperature increase (p < 0.001) recorded by the BLE beacon sensors. The BLE beacon sensors reliably detected meaningfully increased temperature, coupled with numerous instances of motion, when magnifiers were used for typical reading tasks at home by people with LV.
Refining Atmosphere Profiles for Aerial Target Detection Models
Authors: Grimming Robert , Leslie Patrick , Burrell Derek , Holst Gerald , Davis Brian , Driggers Ronald
Published: October 2021

Atmospheric path radiance in the infrared is an extremely important quantity in calculating system performance in certain infrared detection systems. For infrared search and track (IRST) system performance calculations, the path radiance competes with the target for precious detector well electrons. In addition, the radiance differential between the target and the path radiance defines the signal level that must be detected. Long-range, high-performance, offensive IRST system design depends on accurate path radiance predictions. In addition, in new applications such as drone detection where a dim unresolved target is embedded into a path radiance background, sensor design and performance are highly dependent on atmospheric path radiance. Being able to predict the performance of these systems under particular weather conditions and locations has long been an important topic. MODTRAN has been a critical tool in the analysis of systems and prediction of electro-optical system performance. The authors have used MODTRAN over many years for an average system performance using the typical “pull-down” conditions in the software. This article considers the level of refinement required for a custom MODTRAN atmosphere profile to satisfactorily model an infrared camera’s performance for a specific geographic location, date, and time. The average difference between a measured sky brightness temperature and a MODTRAN predicted value is less than 0.5 °C with sufficient atmosphere profile updates. The agreement between experimental results and MODTRAN predictions indicates the effectiveness of including updated atmospheric composition, radiosonde, and air quality data from readily available Internet sources to generate custom atmosphere profiles.
CMOS Implementation of ANNs Based on Analog Optimization of N-Dimensional Objective Functions
Authors: Medina-Santiago Alejandro , Hernández-Gracidas Carlos Arturo , Morales-Rosales Luis Alberto , Algredo-Badillo Ignacio , Amador García Monica , Orozco Torres Jorge Antonio
Published: October 2021

The design of neural network architectures is carried out using methods that optimize a particular objective function, in which a point that minimizes the function is sought. In reported works, they only focused on software simulations or commercial complementary metal-oxide-semiconductor (CMOS), neither of which guarantees the quality of the solution. In this work, we designed a hardware architecture using individual neurons as building blocks based on the optimization of n-dimensional objective functions, such as obtaining the bias and synaptic weight parameters of an artificial neural network (ANN) model using the gradient descent method. The ANN-based architecture has a 5-3-1 configuration and is implemented on a 1.2 μm technology integrated circuit, with a total power consumption of 46.08 mW, using nine neurons and 36 CMOS operational amplifiers (op-amps). We show the results obtained from the application of integrated circuits for ANNs simulated in PSpice applied to the classification of digital data, demonstrating that the optimization method successfully obtains the synaptic weights and bias values generated by the learning algorithm (Steepest-Descent), for the design of the neural architecture.
Deep Convolutional Neural Network Optimization for Defect Detection in Fabric Inspection
Authors: Ho Chao-Ching , Chou Wei-Chi , Su Eugene
Published: October 2021

This research is aimed to detect defects on the surface of the fabric and deep learning model optimization. Since defect detection cannot effectively solve the fabric with complex background by image processing, this research uses deep learning to identify defects. However, the current network architecture mainly focuses on natural images rather than the defect detection. As a result, the network architecture used for defect detection has more redundant neurons, which reduces the inference speed. In order to solve the above problems, we propose network pruning with the Bayesian optimization algorithm to automatically tune the network pruning parameters, and then retrain the network after pruning. The training and detection process uses the above-mentioned pruning network to predict the defect feature map, and then uses the image processing flow proposed in this research for the final judgment during fabric defect detection. The proposed method is verified in the two self-made datasets and the two public datasets. In the part of the proposed network optimization results, the Intersection over Union (IoU) of four datasets are dropped by 1.26%, 1.13%, 1.21%, and 2.15% compared to the original network model, but the inference time is reduced to 20.84%, 40.52%, 23.02%, and 23.33% of the original network model using Geforce 2080 Ti. Furthermore, the inference time is also reduced to 17.56%, 37.03%, 19.67%, and 22.26% using the embedded system AGX Xavier. After the image processing part, the accuracy of the four datasets can reach 92.75%, 94.87%, 95.6%, and 81.82%, respectively. In this research, Yolov4 is also trained with fabric defects, and the results showed this model are not conducive to detecting long and narrow fabric defects.