bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Greenhouse vs. Growth Chamber and Different Blue-Light Percentages on the Growth Performance and Quality of Broccoli Microgreens
Authors: Palmitessa Onofrio Davide , Gadaleta Alessio , Leoni Beniamino , Renna Massimiliano , Signore Angelo , Paradiso Vito Michele , Santamaria Pietro
Published: May 2022

Microgreens are a product category with a biochemical content that is currently earning them the status of a functional food. The genotype of the microgreens, and environmental factors, such as the photosynthetic photon flux density (PPFD) and light spectra, can influence the yield and biochemical profile. A landrace of broccoli called ‘Mugnoli’ was compared with a commercial variety (‘Broccolo Natalino’) in two microgreen growing systems (greenhouse vs. growth chamber) and under three growth chamber light spectra (blue, control, control + blue). The results showed that both Mugnoli and Broccolo Natalino can be used to produce microgreens, achieving similar yields, but that Mugnoli showed notably higher polyphenols and antioxidant contents. Due the higher PFFD of the greenhouse environment, microgreens yields were 18% higher than the yields from cultivation in the growth chamber. Regarding the results under different growth chamber spectra, monochromatic blue caused reductions in the microgreens yield and polyphenols content of 13.5% and 14.2%, respectively. In conclusion, Mugnoli can be considered a valuable genetic source for the production of microgreens given its fast crop cycle, good fresh weight production, and, compared to Broccolo Natalino, its superior biochemical content and lower susceptibility to PPFD variations.
Matter Production Characteristics and Nitrogen Use Efficiency under Different Nitrogen Application Patterns in Chinese Double-Cropping Rice Systems
Authors: Zhou Wentao , Long Wenfei , Wang Hongrui , Long Pan , Xu Ying , Fu Zhiqiang
Published: May 2022

Panicle-stage nitrogen fertilizer is popular in parts of China due to its higher nitrogen recovery efficiency compared to basal and tiller nitrogen. However, the effect of conversion from basal to panicle-stage nitrogen on matter production, grain yield, and nitrogen use efficiencies (NUE) in Chinese double-cropping rice systems remains largely unknown. Here, we elucidate the effect by using two types of one-time basal nitrogen patterns (A and B), three panicle-N allocation patterns (C, D, and E), and the local conventional patterns (CK). The two-year experiment demonstrates that E (basal/tiller/spikelet-promoting /spikelet-developing nitrogen = 0:4:3:3) produced the greatest annual grain yield, nitrogen agronomic efficiency, and nitrogen partial productivity. The annual dry matter weight and nitrogen increment of panicle, nitrogen transportation of stems contributes the most to annual yield and NUE. Furthermore, the yield increase could be attributed to the higher effective panicles, plant dry matter weight at tillering, and net photosynthesis rate at heading. Moreover, years and varieties affect the yield in different N treatments. The improvement in the net photosynthesis rate at the milk stage also significantly increases nitrogen recovery efficiency. These findings suggest that it is worth paying attention to the rational ratio of tillering to panicle fertilizer without applying a base fertilizer, to synchronously increase the grain yield, NUE in Chinese double-cropping rice systems.
Occurrence of Fibropapillomatosis in Green Turtles (Chelonia mydas) in Relation to Environmental Changes in Coastal Ecosystems in Texas and Florida: A Retrospective Study
Authors: Manes Costanza , Pinton Daniele , Canestrelli Alberto , Capua Ilaria
Published: May 2022

Fibropapillomatosis is a neoplastic disease of marine turtles, with green turtles (Chelonia mydas) being the most affected species. Fibropapillomatosis causes debilitating tumor growths on soft tissues and internal organs, often with lethal consequences. Disease incidence has been increasing in the last few decades and the reason is still uncertain. The potential viral infectious agent of Fibropapillomatosis, chelonid herpesvirus 5, has been co-evolving with its sea turtle host for millions of years and no major mutation linked with increased disease occurrence has been detected. Hence, frequent outbreaks in recent decades are likely attributable to external drivers such as large-scale anthropogenic changes in the green turtle coastal marine ecosystem. This study found that variations in sea surface temperature, salinity, and nutrient effluent discharge from nearby rivers were correlated with an increased incidence of the disease, substantiating that these may be among the significant environmental drivers impacting Fibropapillomatosis prevalence. This study offers data and insight on the need to establish a baseline of environmental factors which may drive Fibropapillomatosis and its clinical exacerbation. We highlight the multifactorial nature of this disease and support the inclusion of interdisciplinary work in future Fibropapillomatosis research efforts.
Key Factors in Effective Patient-Tailored Dosing of Fluoroquinolones in Urological Infections: Interindividual Pharmacokinetic and Pharmacodynamic Variability
Authors: Estradé Oskar , Vozmediano Valvanera , Carral Nerea , Isla Arantxa , González Margarita , Poole Rachel , Suarez Elena
Published: May 2022

Fluoroquinolones (FQs) are a critical group of antimicrobials prescribed in urological infections as they have a broad antimicrobial spectrum of activity and a favorable tissue penetration at the site of infection. However, their clinical practice is not problem-free of treatment failure, risk of emergence of resistance, and rare but important adverse effects. Due to their critical role in clinical improvement, understanding the dose-response relation is necessary to optimize the effectiveness of FQs therapy, as it is essential to select the right antibiotic at the right dose for the right duration in urological infections. The aim of this study was to review the published literature about inter-individual variability in pharmacological processes that can be responsible for the clinical response after empiric dose for the most commonly prescribed urological FQs: ciprofloxacin, levofloxacin, and moxifloxacin. Interindividual pharmacokinetic (PK) variability, particularly in elimination, may contribute to treatment failure. Clearance related to creatinine clearance should be specifically considered for ciprofloxacin and levofloxacin. Likewise, today, undesired interregional variability in FQs antimicrobial activity against certain microorganisms exists. FQs pharmacology, patient-specific characteristics, and the identity of the local infecting organism are key factors in determining clinical outcomes in FQs use.
Optimization of a Monobromobimane (MBB) Derivatization and RP-HPLC-FLD Detection Method for Sulfur Species Measurement in Human Serum after Sulfur Inhalation Treatment
Authors: Roda Barbara , Zhang Nan , Gambari Laura , Grigolo Brunella , Eller-Vainicher Cristina , Gennari Luigi , Zappi Alessandro , Giordani Stefano , Marassi Valentina , Zattoni Andrea , Reschiglian Pierluigi , Grassi Francesco
Published: May 2022

(1) Background: Hydrogen sulfide (H2S) is a widely recognized gasotransmitter, with key roles in physiological and pathological processes. The accurate quantification of H2S and reactive sulfur species (RSS) may hold important implications for the diagnosis and prognosis of diseases. However, H2S species quantification in biological matrices is still a challenge. Among the sulfide detection methods, monobromobimane (MBB) derivatization coupled with reversed phase high-performance liquid chromatography (RP-HPLC) is one of the most reported. However, it is characterized by a complex preparation and time-consuming process, which may alter the actual H2S level; moreover, a quantitative validation has still not been described. (2) Methods: We developed and validated an improved analytical protocol for the MBB RP-HPLC method. MBB concentration, temperature and sample handling were optimized, and the calibration method was validated using leave-one-out cross-validation and tested in a clinical setting. (3) Results: The method shows high sensitivity and allows the quantification of H2S species, with a limit of detection of 0.5 µM. Finally, it can be successfully applied in measurements of H2S levels in the serum of patients subjected to inhalation with vapors rich in H2S. (4) Conclusions: These data demonstrate that the proposed method is precise and reliable for measuring H2S species in biological matrices and can be used to provide key insights into the etiopathogenesis of several diseases and sulfur-based treatments.
Endothelial Cell Protein Targeting by Myeloperoxidase-Derived 2-Chlorofatty Aldehyde
Authors: Shakya Shubha , Herr Roger A. , Carlson Haley L. , Zoeller Raphael A. , Albert Carolyn J. , Ford David A.
Published: May 2022

Neutrophils are important cellular mediators of injury and repair in diseases including ischemic heart disease, atherosclerosis, and sepsis. Myeloperoxidase-derived (MPO)-oxidants released from neutrophils are potential mediators of endothelial injury in disease. MPO-derived HOCl attacks plasmalogen phospholipid to liberate 2-chlorofatty aldehyde (2-ClFALD). Both 2-ClFALD and its oxidation product, 2-chlorofatty acid (2-ClFA), are electrophilic lipids, and both probably react with proteins through several mechanisms. In the present study, we investigate protein modification specifically by 2-ClFALD under non-reducing conditions (e.g., without stabilizing Schiff base bonds), which likely reflects nucleophilic targeting of the electrophilic chlorinated carbon. Protein modification by the ω-alkyne analog of 2-chlorohexadecanal (2-ClHDA), 2-ClHDyA, was compared to that with the ω-alkyne analog of 2-chlorohexadecanoic acid (2-ClHA), 2-ClHyA, in multiple cell lines, which demonstrated 2-ClFALD preferentially modifies proteins compared to 2-ClFA. The 2-ClHDyA modified proteins from EA.hy926 cells and human lung microvascular endothelial cells analyzed by shotgun proteomics and over-representation analysis included adherens junction, cell adhesion molecule binding, and cell substrate junction enrichment categories. It is possible that proteins in these groups may have roles in previously described 2-ClFALD-elicited endothelial barrier dysfunction.
Intervening Effects and Molecular Mechanism of Quercitrin on PCV2-Induced Histone Acetylation, Oxidative Stress and Inflammatory Response in 3D4/2 Cells
Authors: Chen Qi , Wei Yuheng , Zhao Yi , Xie Xiaodong , Kuang Na , Wei Yingyi , Yu Meiling , Hu Tingjun
Published: May 2022

Porcine circovirus type 2 (PCV2) is the main pathogen causing porcine circovirus-associated diseases (PCVD/PCVADs), and infection of the host induces immunosuppression. Since quercitrin (QUE) has anti-inflammatory and antiviral activity, it is worth exploiting in animal diseases. In this study, the interventional effects and the molecular mechanism of QUE on PCV2-induced oxidative stress and inflammatory responses in 3D4/2 cells and the modulation of histone acetylation modifications were investigated. The ROS production was measured by DCFH-DA fluorescent probes. HAT and HDAC enzyme activity were determined by ELISA. Histone acetylation, oxidative stress and inflammation-related gene expression levels were measured by q-PCR. Histone H3 and H4 (AcH3 and AcH4) acetylation, oxidative stress and inflammation-related protein expression levels were measured by Western blot. The results showed that QUE treatment at different concentrations on PCV2-infected 3D4/2 cells was able to attenuate the production of ROS. Moreover, QUE treatment could also intervene in oxidative stress and decrease the enzyme activity of HAT and the mRNA expression level of HAT1, while it increased the enzyme activity of HDAC and HDAC1 mRNA expression levels and downregulated histone H3 and H4 (AcH3 and AcH4) acetylation modification levels. In addition, QUE treatment even downregulated the mRNA expression levels of IL-6, IL-8, IκB, AKT and p38, but upregulated the mRNA expression levels of IL-10, SOD, GPx1, p65, Keap1, Nrf2, HO-1 and NQO1. As to protein expression, QUE treatment downregulated the levels of iNOS, p-p65 and IL-8 as well as the phosphorylation expression of IκB and p38, while it upregulated the levels of HO-1 and NQO1. It was shown that QUE at 25, 50 or 100 μmol/L regulated p38MAPK and PI3K/AKT signaling pathways by downregulating cellular histone acetylation modification levels while inhibiting the NF-κB inflammatory signaling pathway and activating the Nrf2/HO-1 antioxidant signaling pathway, thus regulating the production of inflammatory and antioxidant factors and exerting both anti-inflammatory and antioxidant effects.
Metabolism Dysregulation in Retinal Diseases and Related Therapies
Authors: Chen Yingying , Coorey Nathan J. , Zhang Meixia , Zeng Shaoxue , Madigan Michele C. , Zhang Xinyuan , Gillies Mark C. , Zhu Ling , Zhang Ting
Published: May 2022

The human retina, which is part of the central nervous system, has exceptionally high energy demands that requires an efficient metabolism of glucose, lipids, and amino acids. Dysregulation of retinal metabolism disrupts local energy supply and redox balance, contributing to the pathogenesis of diverse retinal diseases, including age-related macular degeneration, diabetic retinopathy, inherited retinal degenerations, and Macular Telangiectasia. A better understanding of the contribution of dysregulated metabolism to retinal diseases may provide better therapeutic targets than we currently have.
Transcription Factor NRF2 Participates in Cell Cycle Progression at the Level of G1/S and Mitotic Checkpoints
Authors: Lastra Diego , Escoll Maribel , Cuadrado Antonio
Published: May 2022

Transcription factor NRF2 is a master regulator of the multiple cytoprotective responses that confer growth advantages on a cell. However, its participation in the mechanisms that govern the cell division cycle has not been explored in detail. In this study, we used several standard methods of synchronization of proliferating cells together with flow cytometry and monitored the participation of NRF2 along the cell cycle by the knockdown of its gene expression. We found that the NRF2 levels were highest at S phase entry, and lowest at mitosis. NRF2 depletion promoted both G1 and M arrest. Targeted transcriptomics analysis of cell cycle regulators showed that NRF2 depletion leads to changes in key cell cycle regulators, such as CDK2, TFDP1, CDK6, CDKN1A (p21), CDKN1B (p27), CCNG1, and RAD51. This study gives a new dimension to NRF2 effects, showing their implication in cell cycle progression.
Baicalein Exerts Therapeutic Effects against Endotoxin-Induced Depression-like Behavior in Mice by Decreasing Inflammatory Cytokines and Increasing Brain-Derived Neurotrophic Factor Levels
Authors: Liu Hsin-Tzu , Lin Yu-Ning , Tsai Ming-Cheng , Wu Ya-Chi , Lee Ming-Chung
Published: May 2022

Inflammation plays an important role in the pathophysiology of depression. This study aims to elucidate the antidepressant effect of baicalein, an anti-inflammatory component of a traditional Chinese herbal medicine (Scutellaria baicalensis), on lipopolysaccharide (LPS)-induced depression-like behavior in mice, and to investigate the underlying mechanisms. In vitro, baicalein exhibited antioxidant activity and protected macrophages from LPS-induced damage. The results of the tail suspension test and forced swimming test (tests for despair potential in mice) showed the antidepressant effect of baicalein on LPS-treated mice. It also substantially decreased the production of pro-inflammatory cytokines, including IL-6, TNF-α, MCP-1, and eotaxin, elicited by LPS in the plasma. Baicalein downregulated NF-κB-p65 and iNOS protein levels in the hippocampus, demonstrated its ability to mitigate neuroinflammation. Additionally, baicalein increased the levels of the mature brain-derived neurotrophic factor (mBDNF) in the hippocampus of LPS-treated mice, and elevated the ratio of mBDNF/proBDNF, which regulates neuronal survival and synaptic plasticity. Baicalein also promoted the expression of CREB, which plays a role in a variety of signaling pathways. In summary, the findings of this study demonstrate that the administration of baicalein can attenuate LPS-induced depression-like behavior by suppressing neuroinflammation and inflammation induced by the peripheral immune response.
Identification of a Novel Class of Anti-Melanogenic Compounds, (Z)-5-(Substituted benzylidene)-3-phenyl-2-thioxothiazolidin-4-one Derivatives, and Their Reactive Oxygen Species Scavenging Activities
Authors: Jeong Yeongmu , Hong Sojeong , Jung Hee Jin , Ullah Sultan , Hwang YeJi , Choi Heejeong , Ko Jeongin , Lee Jieun , Chun Pusoon , Chung Hae Young , Moon Hyung Ryong
Published: May 2022

The rate-determining role of tyrosinase makes it a critical component in the mechanism that is responsible for melanogenesis. Thirteen (Z)-5-(substituted benzylidene)-3-phenyl-2-thioxothiazolidin-4-one ((Z)-BPTT) analogs were designed based on the structural features of two potent tyrosinase inhibitors, viz. (Z)-5-(3-hydroxy-4-methoxybenzylidene)-2-thioxothiazolidin-4-one (5-HMT) and (Z)-2-(2,4-dihydroxybenzylidene)benzo[4,5]imidazo[2,1-b]thiazol-3(2H)-one (compound I). The trisubstituted double bond geometry of the (Z)-BPTT analogs that were generated by Knoevenagel condensation was determined using vicinal 1H and 13C coupling constants in 13C NMR spectra. Four analogs, numbers 1–3 and 6, inhibited mushroom tyrosinase 9 to 29 times more potently than kojic acid did. Kinetic study results indicated that these four analogs inhibited mushroom tyrosinase competitively and this was supported by docking simulation. Also, docking results using human tyrosinase suggested that analogs 2 and 3 might be potent human tyrosinase inhibitors. In vitro studies using B16F10 cells (a melanoma cell line) showed that analogs 1, 2, 3, and 6 inhibited cellular tyrosinase and melanin production more than kojic acid did, without perceptible cytotoxicity. In particular, analog 2, which possesses a catechol group, exerted an extremely potent anti-melanogenic effect. In addition, analog 2 showed strong scavenging activity against DPPH and ABTS radicals. Furthermore, analog 2 not only reduced ROS levels, which induce melanogenesis, but it also suppressed tyrosinase and MITF (microphthalamia-associated transcription factor) protein levels and the expressions of melanogenesis-related genes. These results suggest that analog 2 is an efficient tyrosinase inhibitor that alleviates melanogenesis by dual mechanisms of (i) the inhibition of melanogenesis-related proteins and genes and (ii) the direct inhibition of tyrosinase activity.
Whole-Body Cryostimulation: A Rehabilitation Booster in Post-COVID Patients? A Case Series
Authors: Piterà Paolo , Gobbi Michele , Fontana Jacopo Maria , Cattaldo Stefania , Massucci Maurizio , Capodaglio Paolo
Published: May 2022

Given the severity and prevalence of post-COVID-19 symptoms in the general population, the identification of boosters for rehabilitation programs appears to be of paramount importance. The purpose of this case series is to provide some preliminary evidence about the role of whole-body cryostimulation (WBC) as an effective adjuvant for the recovery of patients with the post-COVID-19 condition (PCC). We recruited seven patients with previously confirmed SARS-CoV-2 infection and symptoms of PCC of different severities for a comprehensive rehabilitation program, including WBC. The main symptoms were dyspnea, chronic and muscular fatigue, chronic pain, and poor sleep quality. Moreover, some patients presented high levels of hematological markers of inflammation. Because we provided a range of interventions, including nutritional and psychological support along with physical exercise and physiotherapy, we could not determine to what extent WBC may per se have accounted for the clinical and functional improvements. However, for all reported cases, it was observed that the introduction of WBC sessions represented a turning point in the patient’s subjective and objective improvements related to health and functioning.
Gall Nuts Cynips quercusfolii (Linnaeus) and Andricus infectorius (Hartig) as Tannin Raw Materials
Authors: Bilek Maciej , Czerniakowski Zbigniew , Kozłowska-Tylingo Katarzyna , Gostkowski Michał , Olbrycht Tomasz , Cicek Cuneyt , Staniszewski Paweł , Dudek Tomasz
Published: May 2022

The study included gall nuts caused by Cynips quercusfolii collected from Quercus robur and Andricus infectorius, harvested from Quercus infectoria. The evaluation of the percentage content of tannins expressed as a pyrogallol was performed using the analytical methodology recommended by the current “European Pharmacopoeia 10”. In order to compare the chemical composition of the tested samples, chromatographic profiles and ion mass distribution spectra were made using high-performance liquid chromatography techniques coupled with two types of detection: spectrophotometry and mass spectrometry. The average content of tannins expressed as pyrogallol for C. quercusfolii ranged from 13.36% to 14.74%, while for A. infectorius it was from 34.77% to 39.95%. The comparison of both the mass spectra and the chromatographic profiles shows a high similarity of all samples of C. quercusfolii and large differences in the chemical composition compared to A. infectorius. The tested C. quercusfolii should be considered a much poorer tannin source than A. infectorius. It cannot be simultaneously treated as its substitute raw material due to the lower tannins percentage content and different chemical composition. However, compared to other Central European herbal raw materials, C. quercusfolii gall nuts are an alternative tannin source with potential use in herbal medicine and the pharmaceutical industry.
A Novel RBFNN-CNN Model for Speaker Identification in Stressful Talking Environments
Authors: Nassif Ali Bou , Alnazzawi Noha , Shahin Ismail , Salloum Said A. , Hindawi Noor , Lataifeh Mohammed , Elnagar Ashraf
Published: May 2022

Speaker identification systems perform almost ideally in neutral talking environments. However, these systems perform poorly in stressful talking environments. In this paper, we present an effective approach for enhancing the performance of speaker identification in stressful talking environments based on a novel radial basis function neural network-convolutional neural network (RBFNN-CNN) model. In this research, we applied our approach to two distinct speech databases: a local Arabic Emirati-accent dataset and a global English Speech Under Simulated and Actual Stress (SUSAS) corpus. To the best of our knowledge, this is the first work that addresses the use of an RBFNN-CNN model in speaker identification under stressful talking environments. Our speech identification models select the finest speech signal representation through the use of Mel-frequency cepstral coefficients (MFCCs) as a feature extraction method. A comparison among traditional classifiers such as support vector machine (SVM), multilayer perceptron (MLP), k-nearest neighbors algorithm (KNN) and deep learning models, such as convolutional neural network (CNN) and recurrent neural network (RNN), was conducted. The results of our experiments show that speaker identification performance in stressful environments based on the RBFNN-CNN model is higher than that with the classical and deep machine learning models.
Hyperspectral Imaging for the Detection of Bitter Almonds in Sweet Almond Batches
Authors: Torres-Rodríguez Irina , Sánchez María-Teresa , Entrenas José-Antonio , Vega-Castellote Miguel , Garrido-Varo Ana , Pérez-Marín Dolores
Published: May 2022

A common fraud in the sweet almond industry is the presence of bitter almonds in commercial batches. The presence of bitter almonds not only causes unpleasant flavours but also problems in the commercialisation and toxicity for consumers. Hyperspectral Imaging (HSI) has been proved to be suitable for the rapid and non-destructive quality evaluation in foods as it integrates the spectral and spatial dimensions. Thus, we aimed to study the feasibility of using an HSI system to identify single bitter almond kernels in commercial sweet almond batches. For this purpose, sweet and bitter almond batches, as well as different mixtures, were analysed in bulk using an HSI system which works in the spectral range 946.6–1648.0 nm. Qualitative models were developed using Partial Least Squares-Discriminant Analysis (PLS-DA) to differentiate between sweet and bitter almonds, obtaining a classification success of over the 99%. Furthermore, data reduction, as a function of the most relevant wavelengths (VIP scores), was applied to evaluate its performance. Then, the pixel-by-pixel validation of the mixtures was carried out, identifying correctly between 61–85% of the adulterations, depending on the group of mixtures and the cultivar analysed. The results confirm that HSI, without VIP scores data reduction, can be considered a promising approach for classifying the bitterness of almonds analysed in bulk, enabling identifying individual bitter almonds inside sweet almond batches. However, a more complex mathematical analysis is necessary before its implementation in the processing lines.
Generation of Synthetic Rat Brain MRI Scans with a 3D Enhanced Alpha Generative Adversarial Network
Authors: Ferreira André , Magalhães Ricardo , Mériaux Sébastien , Alves Victor
Published: May 2022

Translational brain research using Magnetic Resonance Imaging (MRI) is becoming increasingly popular as animal models are an essential part of scientific studies and more ultra-high-field scanners are becoming available. Some disadvantages of MRI are the availability of MRI scanners and the time required for a full scanning session. Privacy laws and the 3Rs ethics rule also make it difficult to create large datasets for training deep learning models. To overcome these challenges, an adaptation of the alpha Generative Adversarial Networks (GANs) architecture was used to test its ability to generate realistic 3D MRI scans of the rat brain in silico. As far as the authors are aware, this was the first time a GAN-based approach was used to generate synthetic MRI data of the rat brain. The generated scans were evaluated using various quantitative metrics, a Turing test, and a segmentation test. The last two tests proved the realism and applicability of the generated scans to real problems. Therefore, by using the proposed new normalisation layer and loss functions, it was possible to improve the realism of the generated rat MRI scans, and it was shown that using the generated data improved the segmentation model more than using the conventional data augmentation.
Study on the Restraint Effect of Isolation Pile on Surface Settlement Trough Induced by Shield Tunnelling
Authors: Huang Kan , Sun Yiwei , Kuang Xilong , Huang Xianqiang , Liu Runing , Wu Qijiang
Published: May 2022

Isolation piles are widely used to control the influence of shield tunnelling on adjacent buildings as an effective protective measure. However, the restraint effect of isolation pile on surface settlement trough is rarely explored from the internal mechanism. Firstly, the restraint mechanism of isolation piles is investigated from the pile-soil-tunnel interaction mechanism. Secondly, based on the Melan solution and the Loganathan formula, the analytical solution of surface settlement trough under the influence of adjacent isolation piles is derived. Thirdly, in order to satisfy the engineering analysis scale and reflect the friction characteristics between isolation pile and soil particles simultaneously, the FDM-DEM coupling technique is introduced to establish a numerical model including discrete medium and continuum medium. Finally, the applicability and reliability of the analytical solution and the FDM-DEM coupling numerical solution are verified by comparing field measured data. The results indicate that the surface settlement trough under the influence of isolation piles will have an asymmetric distribution. Surface settlement tends to develop more to the opposite side of the tunnel when isolation piles are pre-installed on one side. The findings of the study have substantial theoretical significance and engineering reference value.
A Novel Space-Borne High-Resolution SAR System with the Non-Uniform Hybrid Sampling Technology for Space Targets Imaging
Authors: Xia Zhenghuan , Jin Shichao , Yue Fuzhan , Yang Jian , Zhang Qingjun , Zhao Zhilong , Zhang Chuang , Gao Wenning , Zhang Tao , Zhang Yao , Liu Xin , Peng Tao
Published: May 2022

In order to reduce the complexity of the receiving system for wideband signals, a novel space-borne high-resolution synthetic aperture radar (SAR) system with the non-uniform hybrid sampling technology is proposed in this paper. The non-uniform hybrid sampling technology is firstly applied in the SAR imaging system for the detection of space targets. The non-uniform hybrid sampling technology is able to optimize the transmitted and receiving timing of SAR signals, reducing the requirement of the sampling rate of the analog-to-digital converter (ADC) for the reception of the wideband echoes from space targets. Meanwhile, according to the oversampling requirement of SAR imaging in the azimuth direction, a theoretical model of non-uniform hybrid sampling parameters and relative velocity between the SAR system and the space targets is established. A series of simulation experiments with different targets and different non-uniform hybrid parameters are performed, and an X-band SAR imaging experimental system is constructed to verify the effectiveness of the proposed non-uniform hybrid sampling technology. The experimental results show that the imaging resolution is better than 8 cm. When the non-uniform hybrid sampling interval is 15 us, the imaging quality is consistent with imaging results of the Nyquist real-time sampling, and it is easier to implement in the high-resolution imaging for space targets.
Finite Element Analysis of the Limit Load of Straight Pipes with Local Wall-Thinning Defects under Complex Loads
Authors: Li Yan , Gao Bingjun , Liu Shuo , Lin Kaiming , Ding Juncai
Published: May 2022

Local wall thinning is a common defect on the surface of pipelines, which can cause damage to the pipeline under complex pipeline loads. Based on the study on the limit load of straight pipes with defects, the nonlinear finite element method was used to analyze the limit load of straight pipes with local wall-thinning defects under internal pressure, bending moment, torque, axial force, and their combinations, and the empirical limit-load equations of straight pipes with local wall-thinning defects under single and complex loads were fitted. Based on the allowable load on the equipment nozzles, the influences of torque and axial force on the load-bearing capacity of straight pipes with local wall-thinning defects were quantitatively analyzed. For medium and low-pressure equipment, the load-bearing capacity was reduced by 0.59~1.44% under the influence of torque, and by 0.83~1.80% under the influence of axial force. For high-pressure equipment, the load-bearing capacity was reduced by 10.07~20.90% under the influence of torque, and by 2.01~12.40% under the influence of axial force.
Applications of Decision Tree and Random Forest as Tree-Based Machine Learning Techniques for Analyzing the Ultimate Strain of Spliced and Non-Spliced Reinforcement Bars
Authors: Dabiri Hamed , Farhangi Visar , Moradi Mohammad Javad , Zadehmohamad Mehdi , Karakouzian Moses
Published: May 2022

The performance of both non-spliced and spliced steel bars significantly affects the overall performance of structural reinforced concrete elements. In this context, the mechanical properties of reinforcement bars (i.e., their ultimate strength and strain) should be determined in order to evaluate their reliability prior to the construction procedure. In this study, the application of Tree-Based machine learning techniques is implemented to analyze the ultimate strain of non-spliced and spliced steel reinforcements. In this regard, a database containing the results of 225 experimental tests was collected based on the research investigations available in peer-reviewed international publications. The database included the mechanical properties of both non-spliced and mechanically spliced bars. For better accuracy, the databases of other splicing methods such as lap and welded-spliced methods were excluded from this research. The database was categorized as two sub-databases: training (85%) and testing (15%) of the developed models. Various effective parameters such as splice technique, steel grade of the bar, diameter of the steel bar, coupler geometry—including length and outer diameter along with the testing temperatures—were defined as the input variables for analyzing the ultimate strain using tree-based approaches including Decision Trees and Random Forest. The predicted outcomes were compared to the actual values and the precision of the prediction models was assessed via performance metrics, along with a Taylor diagram. Based on the reported results, the reliability of the proposed ML-based methods was acceptable (with an R2 ≥ 85%) and they were time-saving and cost-effective compared to more complicated, time-consuming, and expensive experimental examinations. More importantly, the models proposed in this study can be further considered as a part of a comprehensive prediction model for estimating the stress-strain behavior of steel bars.
Numerical Analysis of Tube Heat Exchanger with Trimmed Star-Shaped Fins
Authors: Bošnjaković Mladen , Muhič Simon
Published: May 2022

In some engineering applications, it is very desirable that the heat exchanger is as light as possible while maintaining the heat transfer rate at an acceptable level. In this context, the possibility of reducing the weight of the heat exchanger with the star-shaped fins by cutting off the thermally least efficient part of the fin was investigated. For this purpose, the rear part of the fins was trimmed to Ø28, Ø31 and Ø34 mm. Numerical analysis was used to determine the influence of each variant on the flow characteristics in the air–water heat exchanger and on heat transfer for the range of 2300 < Re < 16,000. The best results were obtained by trimming the rear part of the fin to Ø28 mm. With a 5.53% reduction in fin weight, heat transfer can be increased by up to 8.12% compared to the star-shaped fins without trimming. The pressure drop can be reduced by up to 0.92%. The trimmed fins were also compared with perforated star-shaped fins (perforation Ø2). At approximately the same weight, the trimmed fins increase the heat transfer coefficient by up to 5.75% with a reduction in pressure drop of up to 0.76% compared to the perforated fins.
Time-Varying Pilot’s Intention Identification Based on ESAX-CSA-ELM Classification Method in Complex Environment
Authors: Wang Haibo , Pan Ting , Si Haiqing , Zhang Hongjia , Shang Lei , Liu Haibo
Published: May 2022

Dynamic and accurate identification of pilot intention is an important prerequisite for more accurate identification of control behavior, automatic flight early warning, and human–aircraft shared autonomy. Meanwhile, it is also the basic requirement of microscopic research on flight safety. In response to these demands, the airfield traffic pattern flight simulation experiment was carried out to obtain the pilot’s physiological data, such as electrocardiogram, respiration, and skin electricity, under different intentions. The extended symbol aggregation approximation theory (ESAX) and the intelligent icon method were utilized to analyze and extract the characteristics of the pilot’s intention. Furthermore, combined with the crow search algorithm (CSA) and extreme learning machine (ELM), a CSA-ELM pilot intention identification model was constructed and it is applied to climb, descend, level flight, and other situations in airfield traffic pattern missions to effectively identify whether the pilot has an intention. The rationality and validity of the identification model were verified through experiments with interactive computer simulations. In addition, compared with the traditional machine learning method, the accuracy of the identification method proposed in this paper is improved by about 10%. The above shows that the research results in this paper can provide support for improving the flight safety early-warning system and the pilot’s micro-behavior evaluation system.
Current Approaches and Applications in Natural Language Processing
Authors: Montejo-Ráez Arturo , Jiménez-Zafra Salud María
Published: May 2022

Artificial Intelligence has gained a lot of popularity in recent years thanks to the advent of, mainly, Deep Learning techniques [...]
Thermodynamics and Magnetism of SmFe12 Compound Doped with Co and Ni: An Ab Initio Study
Authors: Landa Alexander , Söderlind Per , Moore Emily E. , Perron Aurélien
Published: May 2022

Ni-doped Sm(Fe1−xCox)12 alloys are investigated for their magnetic properties. The Sm(Fe,Co)11M1 compound (M acts as a stabilizer) with the smallest (7.7 at.%) rare-earth-metal content has been recognized as a possible contender for highly efficient permanent magnets thanks to its significant anisotropy field and Curie temperature. The early transition metals (Ti-Mn) as well as Al, Si, and Ga stabilize the SmFe12 compound but significantly decrease its saturation magnetization. To keep the saturation magnetization in the range of 1.4–1.6 T, we suggest replacing a certain amount of Fe and Co in the Sm(Fe1−xCox)12 alloys with Ni. Ni plays the role of a thermodynamic stabilizer, and contrary to the above-listed elements, has the spin moment aligned parallel to the spin moment of the SmFe12 compound, thereby boosting its saturation magnetization without affecting the anisotropy field or Curie temperature.
COVID-19 Chest X-ray Classification and Severity Assessment Using Convolutional and Transformer Neural Networks
Authors: Le Dinh Tuan , Lee Suk-Hwan , Kwon Seong-Geun , Kwon Ki-Ryong
Published: May 2022

The coronavirus pandemic started in Wuhan, China in December 2019, and put millions of people in a difficult situation. This fatal virus spread to over 227 countries and the number of infected patients increased to over 400 million cases, causing over 6 million deaths worldwide. Due to the serious consequence of this virus, it is necessary to develop a detection method that can respond quickly to prevent the spreading of COVID-19. Using chest X-ray images to detect COVID-19 is one of the promising techniques; however, with a large number of COVID-19 infected cases every day, the number of radiologists available to diagnose the chest X-ray images is not sufficient. We must have a computer aid system that helps doctors instantly and automatically determine COVID-19 cases. Recently, with the emergence of deep learning methods applied for medical and biomedical uses, using convolutional neural net and transformer applications for chest X-ray images can be a supplement for COVID-19 testing. In this paper, we attempt to classify three types of chest X-ray, which are normal, pneumonia, and COVID-19 using deep learning methods on a customized dataset. We also carry out an experiment on the COVID-19 severity assessment task using a tailored dataset. Five deep learning models were obtained to conduct our experiments: DenseNet121, ResNet50, InceptionNet, Swin Transformer, and Hybrid EfficientNet-DOLG neural networks. The results indicated that chest X-ray and deep learning could be reliable methods for supporting doctors in COVID-19 identification and severity assessment tasks.
Design of Fairway Width Based on a Grounding and Collision Risk Model in the South Coast of Korean Waterways
Authors: Kang Won-Sik , Park Young-Soo , Lee Myoung-Ki , Park Sangwon
Published: May 2022

As a method of reviewing the design of new fairways and the redesign of existing fairways, we proposed a fairway design plan based on the collision and grounding probability, considering vessel traffic. A case study was conducted on the four traffic separation schemes (TSS) on the southern coast, which is the most complex coast among Korean coastal waters. The evaluation items of Korea’s Maritime Traffic Safety Assessment Scheme, the PIANC Guide, and the Port and Fishing Port Design Standards were all satisfied; however, some fairways had very high ship congestion at specific times, exceeding the fairway capacity. For each target fairway, the collision risk using the environmental stress (ES) model and the grounding risk using the IWRAP Mk II Model were analyzed. The grounding risk was found to be equally good, but the aggregation environmental stress (ESA) value, according to the ES model, was high in three fairways. The widths of the three fairways with high risk were partially expanded, and, thus, were re-evaluated. The overall ESA was reduced, and the psychological burden of operators due to the marine environment, such as the fairways, was significantly eased. Based on the results of this study, it would be beneficial to apply a design scheme using collision and stranded risk models when designing new fairways or reviewing existing fairways. An appropriate fairway design plan is prepared that, through further research using various evaluation models and techniques, could be useful in coastal waters in the future.
Advanced Analysis Techniques of Food Contaminants and Risk Assessment—Editorial
Authors: Iammarino Marco , Palermo Carmen , Tomasevic Igor
Published: May 2022

No one wants to eat food that is unsafe and that can put their health at risk in any way or form [...]
Positron Emission Tomography Image Segmentation Based on Atanassov’s Intuitionistic Fuzzy Sets
Authors: Couto Pedro , Bento Telmo , Bustince Humberto , Melo-Pinto Pedro
Published: May 2022

In this paper, we present an approach to fully automate tumor delineation in positron emission tomography (PET) images. PET images play a major role in medicine for in vivo imaging in oncology (PET images are used to evaluate oncology patients, detecting emitted photons from a radiotracer localized in abnormal cells). PET image tumor delineation plays a vital role both in pre- and post-treatment stages. The low spatial resolution and high noise characteristics of PET images increase the challenge in PET image segmentation. Despite the difficulties and known limitations, several image segmentation approaches have been proposed. This paper introduces a new unsupervised approach to perform tumor delineation in PET images using Atanassov’s intuitionistic fuzzy sets (A-IFSs) and restricted dissimilarity functions. Moreover, the implementation of this methodology is presented and tested against other existing methodologies. The proposed algorithm increases the accuracy of tumor delineation in PET images, and the experimental results show that the proposed method outperformed all methods tested.
Study on Performance Evaluation and Prediction of Francis Turbine Units Considering Low-Quality Data and Variable Operating Conditions
Authors: Duan Ran , Liu Jie , Zhou Jianzhong , Liu Yi , Wang Pei , Niu Xinqiang
Published: May 2022

The stable operation of the Francis turbine unit (FTU) determines the safety of the hydropower plant and the energy grid. The traditional FTU performance evaluation methods with a fixed threshold cannot avoid the influence of variable operating conditions. Meanwhile, anomaly samples and missing values in the low-quality on-site data distort the monitoring signals, which greatly affects the evaluation and prediction accuracy of the FTU. Therefore, an approach to the performance evaluation and prediction of the FTU considering low-quality data and variable operating conditions is proposed in this study. First, taking the variable operating conditions into consideration, a FTU on-site data-cleaning method based on DBSCAN is constructed to adaptively identify the anomaly samples. Second, the gate recurrent unit with decay mechanism (GRUD) and the Wasserstein generative adversarial network (WGAN) are combined to propose the GRUD–WGAN model for missing data imputation. Third, to reduce the impact of data randomness, the healthy-state probability model of the FTU is established based on the GPR. Fourth, the prediction model based on the temporal pattern attention–long short-term memory (TPA–LSTM) is constructed for accurate degradation trend forecasting. Ultimately, validity experiments were conducted with the on-site data set of a large FTU in production. The comparison experiments indicate that the proposed GRUD–WGAN has the highest accuracy at each data missing rate. In addition, since the cleaning and imputation improve the data quality, the TPA–LSTM-based performance indicator prediction model has great accuracy and generalization performance.
Advanced Machine Learning Applications to Viscous Oil-Water Multi-Phase Flow
Authors: Rushd Sayeed , Gazder Uneb , Qureshi Hisham Jahangir , Arifuzzaman Md
Published: May 2022

The importance of heavy oil in the world oil market has increased over the past twenty years as light oil reserves have declined steadily. The high viscosity of this kind of unconventional oil results in high energy consumption for its transportation, which significantly increases production costs. A cost-effective solution for the long-distance transport of viscous crudes could be water-lubricated flow technology. A water ring separates the viscous oil-core from the pipe wall in such a pipeline. The main challenge in using this kind of lubricated system is the need for a model that can provide reliable predictions of friction losses. An artificial neural network (ANN) was used in this study to model pressure losses based on 225 data sets from independent sources. The seven input variables used in the current ANN model are pipe diameter, average velocity, oil density, oil viscosity, water density, water viscosity, and water content. The ANN developed using the backpropagation technique with seven processing neurons or nodes in the hidden layer demonstrated to be the optimal architecture. A comparison of ANN with other artificial intelligence and parametric techniques shows the promising precision of the current model. After the model was validated, a sensitivity analysis determined the relative order of significance of the input parameters. Some of the input parameters had linear effects, while other parameters had polynomial effects of varying degrees on the friction losses.
Active Jet Noise Control of Turbofan Engine Based on Explicit Model Predictive Control
Authors: Ji Runmin , Huang Xianghua , Zhao Xiaochun
Published: May 2022

The active jet noise control received significant attention due to the little influence it has on the engine performance. The active jet noise control is a multivariable problem because it needs to achieve the simultaneous closed-loop control of jet noise and engine performance. Model predictive control (MPC) has great application potentials in the field of multivariable control of aero-engines, but the real-time performance of MPC is intractable. This paper proposed an active jet noise controller of a turbofan engine, based on explicit model predictive control (EMPC). An integrated model of turbofan engine and jet noise, which calculates the engine parameters and jet noise in real time, was established. The online computational burden of MPC was transferred to offline computation using multi-parametric quadratic programming (MPQP). To improve the efficiency of the online positioning algorithm, the sequence search method was replaced by a binary search tree. Step simulations were performed to test the effectiveness of the proposed controller. The results show that the proposed EMPC controller not only achieves the simultaneous control of jet noise and the turbofan engine, but also improve the real-time performance greatly.