bluuebunny/crossref_metadata_2025 huggingface dataset:
Microbial Proteins in Stomach Biopsies Associated with Gastritis, Ulcer, and Gastric Cancer
Authors: Aziz Shahid , Rasheed Faisal , Akhter Tayyab Saeed , Zahra Rabaab , König Simone
Published: August 2022

(1) Background: Gastric cancer (GC) is the fourth leading cause of cancer-related deaths worldwide. Helicobacter pylori infection is a major risk factor, but other microbial species may also be involved. In the context of an earlier proteomics study of serum and biopsies of patients with gastroduodenal diseases, we explored here a simplified microbiome in these biopsies (H. pylori, Acinetobacter baumannii, Escherichia coli, Fusobacterium nucleatum, Bacteroides fragilis) on the protein level. (2) Methods: A cohort of 75 patients was divided into groups with respect to the findings of the normal gastric mucosa (NGM) and gastroduodenal disorders such as gastritis, ulcer, and gastric cancer (GC). The H. pylori infection status was determined. The protein expression analysis of the biopsy samples was carried out using high-definition mass spectrometry of the tryptic digest (label-free data-independent quantification and statistical analysis). (3) Results: The total of 304 bacterial protein matches were detected based on two or more peptide hits. Significantly regulated microbial proteins like virulence factor type IV secretion system protein CagE from H. pylori were found with more abundance in gastritis than in GC or NGM. This finding could reflect the increased microbial involvement in mucosa inflammation in line with current hypotheses. Abundant proteins across species were heat shock proteins and elongation factors. (4) Conclusions: Next to the bulk of human proteins, a number of species-specific bacterial proteins were detected in stomach biopsies of patients with gastroduodenal diseases, some of which, like those expressed by the cag pathogenicity island, may provide gateways to disease prevention without antibacterial intervention in order to reduce antibiotic resistance.
Can We Merge the Weak and Strong Tetrel Bonds? Electronic Features of Tetrahedral Molecules Interacted with Halide Anions
Authors: Bartashevich Ekaterina V. , Mukhitdinova Svetlana E. , Klyuev Iliya V. , Tsirelson Vladimir G.
Published: August 2022

Using the orbital-free quantum crystallography approach, we have disclosed the quantitative trends in electronic features for bonds of different strengths formed by tetrel (Tt) atoms in stable molecular complexes consisting of electrically neutral tetrahedral molecules and halide anions. We have revealed the role of the electrostatic and exchange-correlation components of the total one-electron static potential that are determined by the equilibrium atomic structure and by kinetic Pauli potential, which reflects the spin-dependent electron motion features of the weak and strong bonds. The gap between the extreme positions in the electrostatic and total static potentials along the line linking the Tt atom and halide anion is wide for weak bonds and narrow for strong ones. It is in very good agreement with the number of minima in the Pauli potential between the bounded atoms. This gap exponentially correlates with the exchange-correlation potential in various series with a fixed nucleophilic fragment. A criterion for categorizing the noncovalent tetrel bonds (TtB) based on the potential features is suggested.
Assessment of a Computational Approach to Predict Drug Resistance Mutations for HIV, HBV and SARS-CoV-2
Authors: Patel Dharmeshkumar , Ono Suzane K. , Bassit Leda , Verma Kiran , Amblard Franck , Schinazi Raymond F.
Published: August 2022

Viral resistance is a worldwide problem mitigating the effectiveness of antiviral drugs. Mutations in the drug-targeting proteins are the primary mechanism for the emergence of drug resistance. It is essential to identify the drug resistance mutations to elucidate the mechanism of resistance and to suggest promising treatment strategies to counter the drug resistance. However, experimental identification of drug resistance mutations is challenging, laborious and time-consuming. Hence, effective and time-saving computational structure-based approaches for predicting drug resistance mutations are essential and are of high interest in drug discovery research. However, these approaches are dependent on accurate estimation of binding free energies which indirectly correlate to the computational cost. Towards this goal, we developed a computational workflow to predict drug resistance mutations for any viral proteins where the structure is known. This approach can qualitatively predict the change in binding free energies due to mutations through residue scanning and Prime MM-GBSA calculations. To test the approach, we predicted resistance mutations in HIV-RT selected by (-)-FTC and demonstrated accurate identification of the clinical mutations. Furthermore, we predicted resistance mutations in HBV core protein for GLP-26 and in SARS-CoV-2 3CLpro for nirmatrelvir. Mutagenesis experiments were performed on two predicted resistance and three predicted sensitivity mutations in HBV core protein for GLP-26, corroborating the accuracy of the predictions.
mTORC2 Is the Major Second Layer Kinase Negatively Regulating FOXO3 Activity
Authors: Jimenez Lucia , Amenabar Carlos , Mayoral-Varo Victor , Mackenzie Thomas A. , Ramos Maria C. , Silva Andreia , Calissi Giampaolo , Grenho Inês , Blanco-Aparicio Carmen , Pastor Joaquin , Megías Diego , Ferreira Bibiana I. , Link Wolfgang
Published: August 2022

Forkhead box O (FOXO) proteins are transcription factors involved in cancer and aging and their pharmacological manipulation could be beneficial for the treatment of cancer and healthy aging. FOXO proteins are mainly regulated by post-translational modifications including phosphorylation, acetylation and ubiquitination. As these modifications are reversible, activation and inactivation of FOXO factors is attainable through pharmacological treatment. One major regulatory input of FOXO signaling is mediated by protein kinases. Here, we use specific inhibitors against different kinases including PI3K, mTOR, MEK and ALK, and other receptor tyrosine kinases (RTKs) to determine their effect on FOXO3 activity. While we show that inhibition of PI3K efficiently drives FOXO3 into the cell nucleus, the dual PI3K/mTOR inhibitors dactolisib and PI-103 induce nuclear FOXO translocation more potently than the PI3Kδ inhibitor idelalisib. Furthermore, specific inhibition of mTOR kinase activity affecting both mTORC1 and mTORC2 potently induced nuclear translocation of FOXO3, while rapamycin, which specifically inhibits the mTORC1, failed to affect FOXO3. Interestingly, inhibition of the MAPK pathway had no effect on the localization of FOXO3 and upstream RTK inhibition only weakly induced nuclear FOXO3. We also measured the effect of the test compounds on the phosphorylation status of AKT, FOXO3 and ERK, on FOXO-dependent transcriptional activity and on the subcellular localization of other FOXO isoforms. We conclude that mTORC2 is the most important second layer kinase negatively regulating FOXO activity.
New Strategies on Green Synthesis of Dimethyl Carbonate from Carbon Dioxide and Methanol over Oxide Composites
Authors: Zhang Yifei , Khalid Muhammad Shoaib , Wang Meng , Li Gao
Published: August 2022

Dimethyl carbonate is a generally used chemical substance which is environmentally sustainable in nature and used in a range of industrial applications as intermediate. Although various methods, including methanol phosgenation, transesterification and oxidative carbonylation of methanol, have been developed for large-scale industrial production of DMC, they are expensive, unsafe and use noxious raw materials. Green production of DMC from CO2 and methanol is the most appropriate and eco-friendly method. Numerous catalysts were studied and tested in this regard. The issues of low yield and difficulty in tests have not been resolved fundamentally, which is caused by the inherent problems of the synthetic pathway and limitations imposed by thermodynamics. Electron-assisted activation of CO2 and membrane reactors which can separate products in real-time giving a maximum yield of DMC are also being used in the quest to find more effective production method. In this review paper, we deeply addressed green production methods of DMC using Zr/Ce/Cu-based nanocomposites as catalysts. Moreover, the relationship between the structure and activity of catalysts, catalytic mechanisms, molecular activation and active sites identification of catalysts are also discussed.
Sulforaphane Regulates eNOS Activation and NO Production via Src-Mediated PI3K/Akt Signaling in Human Endothelial EA.hy926 Cells
Authors: Zhang Ying , Khoi Pham Ngoc , Cai Bangrong , Sah Dhiraj Kumar , Jung Young-Do
Published: August 2022

Sulforaphane (SFN) is a naturally occurring isothiocyanate that is abundant in many cruciferous vegetables, such as broccoli and cauliflower, and it has been observed to exert numerous biological activities. In the present study, we investigate the effect of SFN on eNOS, a key regulatory enzyme of vascular homeostasis and underlying intracellular pathways, in human endothelial EA.hy926 cells. The results indicate that SFN treatment significantly increases NO production and eNOS phosphorylation in a time- and dose-dependent fashion and also augments Akt phosphorylation in a time- and dose-dependent manner. Meanwhile, pretreatment with LY294002 (a specific PI3K inhibitor) suppresses the phosphorylation of eNOS and NO production. Furthermore, SFN time- and dose-dependently induces the phosphorylation of Src kinase, a further upstream regulator of PI3K, while PP2 pretreatment (a specific Src inhibitor) eliminates the increase in phosphorylated Akt, eNOS and the production of NO derived from eNOS. Overall, the present study uncovers a novel effect of SFN to stimulate eNOS activity in EA.hy926 cells by regulating NO bioavailability. These findings provide clear evidence that SFN regulates eNOS activity and NO bioavailability, suggesting a promising therapeutic candidate to prevent endothelial dysfunction, atherosclerosis and other cardiovascular diseases.
Natural Convection within Inversed T-Shaped Enclosure Filled by Nano-Enhanced Phase Change Material: Numerical Investigation
Authors: Abderrahmane Aissa , Al-Khaleel Mohammad , Mourad Abed , Laidoudi Houssem , Driss Zied , Younis Obai , Guedri Kamel , Marzouki Riad
Published: August 2022

Energy saving has always been a topic of great interest. The usage of nano-enhanced phase change material NePCM is one of the energy-saving methods that has gained increasing interest. In the current report, we intend to simulate the natural convection flow of NePCM inside an inverse T-shaped enclosure. The complex nature of the flow results from the following factors: the enclosure contains a hot trapezoidal fin on the bottom wall, the enclosure is saturated with pours media, and it is exposed to a magnetic field. The governing equations of the studied system are numerically addressed by the higher order Galerkin finite element method (GFEM). The impacts of the Darcy number (Da = 10−2–10−5), Rayleigh number (Ra = 103–106), nanoparticle volume fraction (φ = 0–0.08), and Hartmann number (Ha = 0–100) are analyzed. The results indicate that both local and average Nusselt numbers were considerably affected by Ra and Da values, while the influence of other parameters was negligible. Increasing Ra (increasing buoyancy force) from 103 to 106 enhanced the maximum average Nusselt number by 740%, while increasing Da (increasing the permeability) from 10−5 to 10−2 enhanced both the maximum average Nusselt number and the maximum local Nusselt number by the same rate (360%).
Metabologenomic Approach Reveals Intestinal Environmental Features Associated with Barley-Induced Glucose Tolerance Improvements in Japanese: A Randomized Controlled Trial
Authors: Goto Yuka , Nishimoto Yuichiro , Murakami Shinnosuke , Nomaguchi Tatsuhiro , Mori Yuka , Ito Masaki , Nakaguro Ryohei , Kudo Toru , Matsuoka Tsubasa , Yamada Takuji , Kobayashi Toshiki , Fukuda Shinji
Published: August 2022

(1) Background: Consumption of barley has been known to exert beneficial effects on glucose tolerance; however, it has also been reported that there are inter-individual differences in these responses. Recent evidence has suggested that these individual differences are mediated by the gut microbiota. (2) Methods: In the present study, we aimed to understand the relationship between the intestinal environment, including intestinal microbiome and their metabolome, and glucose tolerance. A randomized controlled trial with a 4-week consumption of barley or control food was conducted. We conducted an integrated analysis of the intestinal microbiome and metabolome and analyzed the relationship with improvement of glucose tolerance. (3) Results: We found that metabolites such as azelate were significantly increased after barley consumption. Furthermore, the subjects whose glucose tolerance was slightly impaired showed improvement in their glucose tolerance index following the barley consumption. Additionally, the analysis showed that the increase in the abundance of the Anaerostipes was correlated with the improvement in the glucose tolerance index. (4) Conclusions: Our findings indicate that the effects of barley consumption for glucose tolerance are partly defined by the intestinal environment of consumers, providing a quantitative measurement of the dietary effect based on the intestinal environment.
Influence of CLOCK Gene Variants on Weight Response after Bariatric Surgery
Authors: Torrego-Ellacuría Macarena , Barabash Ana , Matía-Martín Pilar , Sánchez-Pernaute Andrés , Torres Antonio J. , Calle-Pascual Alfonso L. , Rubio-Herrera Miguel A.
Published: August 2022

The Circadian Locomotor Output Cycles Kaput (CLOCK) gene has been linked to metabolic dysfunction and obesity. The purpose of this study was to analyze the association between single nucleotide polymorphisms (SNPs) of CLOCK gene with obesity and with long-term weight response after different bariatric surgery (BS) techniques. The cohort includes 375 patients with morbid obesity (MO) and 230 controls. In the association study of SNPs with weight response we combined several variables as phenotype at 6 years after surgery. The study protocol was registered in ISRCTN (ID80961259). The analysis of the selected SNPs was performed by allelic discrimination using Taqman® probes. The genotype association study was performed using the SNPStats program, with comparisons adjusted for sex, age, initial Body Mass Index, type 2 diabetes and hypertension diagnosis, and type of surgery. In the case-control study two of three SNPs were significantly associated with MO. The variant rs1801260 had a protective effect for MO whereas the TT genotype of rs3749474 variant had the strongest association with MO (OR = 2.25 (1.39–3.66); p = 0.0006). In the linear regression analysis both variants showed significant association with long-term weight loss and weight regain after BS, independently of the pre-surgery patient profile.
Potential Coronaviral Inhibitors of the Nucleocapsid Protein Identified In Silico and In Vitro from a Large Natural Product Library
Authors: Pohler Alexandra , Abdelfatah Sara , Riedl Max , Meesters Christian , Hildebrandt Andreas , Efferth Thomas
Published: August 2022

The nucleocapsid protein (NP) is one of the main proteins out of four structural proteins of coronaviruses including the severe acute respiratory syndrome coronavirus 2, SARS-CoV-2, discovered in 2019. NP packages the viral RNA during virus assembly and is, therefore, indispensable for virus reproduction. NP consists of two domains, i.e., the N- and C-terminal domains. RNA-binding is mainly performed by a binding pocket within the N-terminal domain (NTD). NP represents an important target for drug discovery to treat COVID-19. In this project, we used the Vina LC virtual drug screening software and a ZINC-based database with 210,541 natural and naturally derived compounds that specifically target the binding pocket of NTD of NP. Our aim was to identify coronaviral inhibitors that target NP not only of SARS-CoV-2 but also of other diverse human pathogenic coronaviruses. Virtual drug screening and molecular docking procedures resulted in 73 candidate compounds with a binding affinity below −9 kcal/mol with NP NTD of SARS-CoV-1, SARS-CoV-2, MERS-CoV, HCoV-OC43, HCoV-NL63, HoC-229E, and HCoV-HKU1. The top five compounds that met the applied drug-likeness criteria were then tested for their binding in vitro to the NTD of the full-length recombinant NP proteins using microscale thermophoresis. Compounds (1), (2), and (4), which belong to the same scaffold family of 4-oxo-substituted-6-[2-(4a-hydroxy-decahydroisoquinolin-2-yl)2H-chromen-2-ones and which are derivates of coumarin, were bound with good affinity to NP. Compounds (1) and (4) were bound to the full-length NP of SARS-CoV-2 (aa 1–419) with Kd values of 0.798 (±0.02) µM and 8.07 (±0.36) µM, respectively. Then, these coumarin derivatives were tested with the SARS-CoV-2 NP NTD (aa 48–174). Compounds (1) and (4) revealed Kd-values of 0.95 (±0.32) µM and 7.77 (±6.39) µM, respectively. Compounds (1) and (4) caused low toxicity in human A549 and MRC-5 cell lines. These compounds may represent possible drug candidates, which need further optimization to be used against COVID-19 and other coronaviral infections.
Effects of Zinc, Copper and Iron Oxide Nanoparticles on Induced DNA Methylation, Genomic Instability and LTR Retrotransposon Polymorphism in Wheat (Triticum aestivum L.)
Authors: Haliloğlu Kamil , Türkoğlu Aras , Balpınar Özge , Nadaroğlu Hayrunnisa , Alaylı Azize , Poczai Peter
Published: August 2022

Nanomaterials with unique and diverse physico-chemical properties are used in plant science since they improve plant growth and development and offer protection against biotic and abiotic stressors. Previous studies have explored the effects of such nanomaterials on different plant mechanisms, but information about the effects of nanomaterials on induced DNA methylation, genomic instability and LTR retrotransposon polymorphism in wheat is lacking. Therefore, the present study highlights the key role of nanoparticles in DNA methylation and polymorphism in wheat by investigating the effects of ZnO, CuO and γ-Fe3O4 nanoparticles (NPs) on mature embryo cultures of wheat (Triticum aestivum L.). Nanoparticles were supplemented with Murashige and Skoog (MS) basal medium at normal (1X), double (2X) and triple (3X) concentrations. The findings revealed different responses to the polymorphism rate depending on the nanoparticle type and concentration. Genomic template stability (GTS) values were used to compare the changes encountered in iPBS profiles. ZnO, CuO and γ-Fe3O4 NPs increased the polymorphism rate and cytosine methylation compared to the positive control while reducing GTS values. Moreover, non-γ-Fe3O4 NPs treatments and 2X ZnO and CuO NP treatments yielded higher polymorphism percentages in both MspI- and HpaII-digested CRED-iPBS assays and were thus classified as hypermethylation when the average polymorphism percentage for MspI digestion was considered. On the other hand, the 3X concentrations of all nanoparticles decreased HpaII and MspI polymorphism percentages and were thus classified as hypomethylation. The findings revealed that MS medium supplemented with nanoparticles had epigenetic and genotoxic effects.
Research on Casing Deformation Prevention Technology of a Deep Shale Gas Well Based on Cementing Slurry System Optimization
Authors: Cao Jing , Yang Shangyu , Han Lihong , Wang Jianjun , Mou Yisheng , Lu Caihong
Published: August 2022

In the complex fracturing process of shale gas wells, casing is subjected to serious deformation, which can easily to the failure of wellbore integrity and the reduction of well construction productivity. It is particularly important to clarify the casing deformation mechanism and carry out effective control. Based on the logging data of casing deformation from well and full-scale indoor tests, the casing deformation mechanism is mainly considered to be shear and non-uniform extrusion deformation caused by formation slip and displacement control, i.e., the ultimate working conditions. The slip displacement boundary (<40 mm) under complex fracturing conditions is quantified to provide the design and optimization basis. Then, the influence laws of steel grade and wall thickness on the shear and non-uniform extrusion bearing characteristics are studied, using unconventional oil and gas well casing simulation test systems for 110 ksi (φ139.7 × 10.54 mm) and 125 ksi (φ139.7 × 12.7 mm) casings. Furthermore, combined with the full-scale simulation tests and finite-element simulation, the effects of elastic and modified cement slurry with hollow glass beads on casing deformation are compared and studied. The results show that the deformation capacity mitigation of casing is limited by reducing the cement elastic modulus and increasing the elastic cement thickness. By reasonably adding hollow glass beads of modified cement slurry, the maximum geological movement absorption of cement slurry is up to 27 mm. This new method can obviously decrease casing deformation and have an excellent control effect. Combined with the cementing technology of Luzhou blocks, the formula of modified cement slurry is optimized, and the optimization window of the casing deformation control process is formed, which can ensure the smooth progress of engineering fracturing.
Fault Diagnosis of Permanent Magnet Synchronous Motor of Coal Mine Belt Conveyor Based on Digital Twin and ISSA-RF
Authors: Huang Yourui , Yuan Biao , Xu Shanyong , Han Tao
Published: August 2022

Permanent magnet synchronous motors (PMSMs) have been gradually used as the driving equipment of coal mine belt conveyors. To ensure safety and stability, it is necessary to carry out real-time and accurate fault diagnosis of PMSM. Therefore, a fault diagnosis method for PMSM based on digital twin and ISSA-RF (Improved Sparrow Search Algorithm Optimized Random Forest) is proposed. Firstly, the multi-strategy hybrid ISSA is used to solve the problems of uneven population distribution, insufficient population diversity, low convergence speed, etc. In addition, the fault diagnosis model of ISSA-RF permanent magnet synchronous motor is constructed based on the optimization of the number of Random Forest decision trees and that of features of each node by ISSA. Secondly, considering the operation mechanism and physical properties of PMSM, the relevant digital twin model is constructed and the real-time mapping of physical entity and virtual model is realized through data interactive transmission. Finally, the simulation and experimental results show that the fault diagnosis accuracy of ISSA-RF, 98.2%, is higher than those of Random Forest (RF), Sparrow Search Algorithm Optimized Random Forest (SSA-RF), BP neural network (BP) and Support Vector Machine (SVM), which verifies the feasibility and ability of the proposed method to realize fault diagnosis and 3D visual monitoring of PMSM together with the digital twin model.
Development of a Moving Bed Reactor for Thermochemical Heat Storage Based on Granulated Ca(OH)2
Authors: Cosquillo Mejia Aldo , Afflerbach Sandra , Linder Marc , Schmidt Matthias
Published: August 2022

Calcium hydroxide is promising for thermal energy storage due to its low cost and high energy density. Nevertheless, the powdered material is cohesive and has low thermal conductivity which is a major challenge for the operation of moving bed reactors. One approach to facilitate the movement of the reaction bed is the stabilisation of the particles through the coating of Ca(OH)2 granules with Al2O3 particles. In this work, a newly designed reactor concept was specifically developed for testing coated Ca(OH)2 granules. The design allows for the movement of the reaction bed by gravity assistance and direct heating of the particles by a counter current gas flow. The operation was successfully demonstrated and proved to achieve high heat transfer between gas and granules. Furthermore, the movement of the reaction bed was achieved after the discharging phase. Two batches of uncoated and coated Ca(OH)2 granules were subject of 10 thermochemical cycles in this reactor. The cycling stability, structural integrity, mechanical stability, morphology and phase composition of the granules were analysed. Full conversion of both samples was demonstrated for the entire experimental series. It was found that the alumina coating enhances the mechanical stability of the granules under reaction conditions.
Supply Chain Management: A Review and Bibliometric Analysis
Authors: Fang Hui , Fang Fei , Hu Qiang , Wan Yuehua
Published: August 2022

Supply chain management (SCM), which generally refers to horizontal integration management, has steadily become the core competitiveness of company rivalry and an essential approach to developing national comprehensive and national strength since the end of the 20th century due to the numerous needs arising from a competitive international economy. Manufacturers develop a community of interest by forming long-term strategic partnerships with suppliers and vendors throughout the supply chain. This paper defines supply chain management by reviewing the existing literature and discusses the current state of supply chain management research, as well as prospective research directions. Specifically, we conducted a bibliometric analysis of the influential studies of SCM in terms of various aspects, such as research areas, journals, countries/regions, institutions, authors and corresponding authors, most cited publications, and author keywords, based on the 8998 reviews and articles collected from the SCI and SSCI database of the Web of Science (WoS) between 2010 and 2020. The results show that the major research areas were Management (3071, 34.13%), Operations Research & Management Science (2680, 29.78%), and Engineering, Industrial (1854, 20.60%) with TP and TPR%. The most productive journal and institution were J. Clean Prod and Hong Kong Polytech Univ with a TP of 554 and 238, respectively. China, USA, and UK were the top three contributing countries. Furthermore, “sustainability”, “green supply chain (management)”, and “sustainable supply chain (management)” were the most popular author keywords in recent three years and since 2010, apart from the author keywords of SCM. When combined with the most cited articles in recent years, the application of block chain and Industry 4.0 in supply chain management increased rapidly and generated great attention.
Zen Philosophy of Mindfulness: Nen 念 according to Dōgen’s Shōbōgenzō
Authors: Nomura Masaki
Published: August 2022

The purpose of this paper is to holistically comprehend the concept of nen 念 in the Zen philosophy of Dōgen (道元 1200–1253), which is one of the origins of Mindfulness-Based Stress Reduction, in relation to his principal concepts. This article specifically investigates its usages in his masterpiece, Treasury of the True Dharma Eye (Shōbōgenzō 正法眼蔵), according to each step of the threefold wisdom (san-e 三慧); for mindfulness is a common thread among them and he presents the concept of “monshishū-shō 聞思修證”, of which shō 證 stands for “awakening”. It is revealed that Dōgen considers “study” (mon 聞) and “reflection” (shi 思) to be essential on the Buddhist path, as well as “practice” (shū 修), and that nen 念 in Dōgen’s philosophy is the self beyond the sense of body-mind or time, which can be attained after long cultivation. Also, the connections among nen 念 and his critical concepts such as “just sitting” (shikan taza 祇管打坐), “dropping off body-mind” (shinjin datsuraku 身心脱落), and “oneness of practice and awakening” (shūshō ittō 修證一等) are elucidated.
Characteristics of Co-Seismic Surface Rupture of the 2021 Maduo Mw 7.4 Earthquake and Its Tectonic Implications for Northern Qinghai–Tibet Plateau
Authors: Xie Hong , Li Zhimin , Yuan Daoyang , Wang Xianyan , Su Qi , Li Xin , Wang Aiguo , Su Peng
Published: August 2022

A magnitude (Mw) 7.4 Maduo earthquake occurred on 22 May 2021 in the northern Qinghai-Tibet Plateau, with predominantly left-lateral strike-slip faulting and a component of normal faulting within the Bayan Har Block. The co-seismic surface rupture extended in a NWW direction for ~160 km with a complicated geometry along a poorly known young fault: the Jiangcuo Fault. The main surface rupture propagated bilaterally from the epicenter and terminated eastward in horsetail splays. The main rupture can be divided into five segments with two rupture gaps. Field surveys and detailed mapping revealed that the co-seismic surface ruptures were characterized by a series of left-lateral offsets, en echelon tensional cracks and fissures, compressional mole tracks, and widespread sand liquefication. The observed co-seismic left-lateral displacements ranged from 0.2 m to ~2.6 m, while the vertical displacements ranged from 0.1 m to ~1.5 m, much lower than the InSAR inverse slip maximum of 2–6 m. Based on the comprehensive analysis of the causative fault geometry and the tectonic structure of the northern Bayan Har Block, this study suggests that the multiple NWW trending sub-faults, including the Jiangcuo Fault, developed from the East Kunlun fault northeast of the Bayan Har Block could be regarded as the sub-faults of the East Kunlun Fault system, constituting a broad and dispersive northern boundary of the Block, controlling the inner strain distribution and deformation.
A Detection Approach for Floating Debris Using Ground Images Based on Deep Learning
Authors: Qiao Guangchao , Yang Mingxiang , Wang Hao
Published: August 2022

Floating debris has a negative impact on the quality of the water as well as the aesthetics of surface waters. Traditional image processing techniques struggle to adapt to the complexity of water due to factors such as complex lighting conditions, significant scale disparities between far and near objects, and the abundance of small-scale floating debris in real existence. This makes the detection of floating debris extremely difficult. This study proposed a brand-new, effective floating debris detection approach based on YOLOv5. Specifically, the coordinate attention module is added into the YOLOv5 backbone network to help the model detect and recognize objects of interest more precisely so that feature information of small-sized and dense floating debris may be efficiently extracted. The previous feature pyramid network, on the other hand, summarizes the input features without taking into account their individual importance when fusing features. To address this issue, the YOLOv5 feature pyramidal network is changed to a bidirectional feature pyramid network with effective bidirectional cross-scale connection and weighted feature fusion, which enhances the model’s performance in terms of feature extraction. The method has been evaluated using a dataset of floating debris that we built ourselves (SWFD). Experiments show that the proposed method detects floating objects more precisely than earlier methods.
Spatial and Temporal Distribution of Cloud Water in the Yellow River Basin, China
Authors: Zhao Kailiang , Zhu Guofeng , Tong Huali , Sang Liyuan , Wang Lei , Liu Yuwei , Xu Yuanxiao , Liu Jiawei , Lin Xinrui , Zhang Wenhao , Ye Linlin
Published: August 2022

The Yellow River Basin is essential to China’s economic and social development and ecological security. In order to assess the temporal and spatial distribution of cloud water in the Yellow River Basin, we analyzed the distribution characteristics of water vapor content and cloud water content using ERA5 monthly averaged data from 1980 to 2019. The results showed that the high-value area of the annual average atmospheric water vapor content distribution was concentrated above the North China Plain in the eastern part of the basin, and the value was mostly between 21 and 24 mm. The low-value areas were mainly centered above the high mountain areas in the western part of the basin, and the value mostly fell between 3 and 6 mm. The seasonal distribution characteristics of the annual average water vapor content were relatively consistent with the annual average distribution characteristics. The high-value cloud ice water content area was in the northeastern part of the Qinghai-Tibet Plateau (4.5 g·m−2), while the low-value area appeared on the Loess Plateau (2 g·m−2). The high-value area of cloud liquid water content was on the north side of the West Qinling Mountains (12 g·m−2). The low-value area appeared on the Loess Plateau and the northern part of the Qinghai-Tibet Plateau (3 g·m−2). The cloud water content was higher in the eastern region than in the western region in the overall spatial distribution, and the content of cloud liquid water was higher than that of cloud ice water. The average annual atmospheric water vapor content was increasing, and the annual average content of cloud ice water and cloud liquid water was declining. The change in the total amount and spatial distribution of cloud water was not obvious in the Yellow River Basin.
Adaptive Lower Limb Pattern Recognition for Multi-Day Control
Authors: Schulte Robert V. , Prinsen Erik C. , Buurke Jaap H. , Poel Mannes
Published: August 2022

Pattern recognition in EMG-based control systems suffer from increase in error rate over time, which could lead to unwanted behavior. This so-called concept drift in myoelectric control systems could be caused by fatigue, sensor replacement and varying skin conditions. To circumvent concept drift, adaptation strategies could be used to retrain a pattern recognition system, which could lead to comparable error rates over multiple days. In this study, we investigated the error rate development over one week and compared three adaptation strategies to reduce the error rate increase. The three adaptation strategies were based on entropy, on backward prediction and a combination of backward prediction and entropy. Ten able-bodied subjects were measured on four measurement days while performing gait-related activities. During the measurement electromyography and kinematics were recorded. The three adaptation strategies were implemented and compared against the baseline error rate and against adaptation using the ground truth labels. It can be concluded that without adaptation the baseline error rate increases significantly from day 1 to 2, but plateaus on day 2, 3 and 7. Of the three tested adaptation strategies, entropy based adaptation showed the smallest increase in error rate over time. It can be concluded that entropy based adaptation is simple to implement and can be considered a feasible adaptation strategy for lower limb pattern recognition.
Agrast-6: Abridged VGG-Based Reflected Lightweight Architecture for Binary Segmentation of Depth Images Captured by Kinect
Authors: Ryselis Karolis , Blažauskas Tomas , Damaševičius Robertas , Maskeliūnas Rytis
Published: August 2022

Binary object segmentation is a sub-area of semantic segmentation that could be used for a variety of applications. Semantic segmentation models could be applied to solve binary segmentation problems by introducing only two classes, but the models to solve this problem are more complex than actually required. This leads to very long training times, since there are usually tens of millions of parameters to learn in this category of convolutional neural networks (CNNs). This article introduces a novel abridged VGG-16 and SegNet-inspired reflected architecture adapted for binary segmentation tasks. The architecture has 27 times fewer parameters than SegNet but yields 86% segmentation cross-intersection accuracy and 93% binary accuracy. The proposed architecture is evaluated on a large dataset of depth images collected using the Kinect device, achieving an accuracy of 99.25% in human body shape segmentation and 87% in gender recognition tasks.
An Improved Crucible Spatial Bubble Detection Based on YOLOv5 Fusion Target Tracking
Authors: Zhao Qian , Zheng Chao , Ma Wenyue
Published: August 2022

A three-dimensional spatial bubble counting method is proposed to solve the problem of the existing crucible bubble detection only being able to perform two-dimensional statistics. First, spatial video images of the transparent layer of the crucible are acquired by a digital microscope, and a quartz crucible bubble dataset is constructed independently. Secondly, to address the problems of poor real-time and the insufficient small-target detection capability of existing methods for quartz crucible bubble detection, rich detailed feature information is retained by reducing the depth of down-sampling in the YOLOv5 network structure. In the neck, the dilated convolution algorithm is used to increase the feature map perceptual field to achieve the extraction of global semantic features; in front of the detection layer, an effective channel attention network (ECA-Net) mechanism is added to improve the capability of expressing significant channel characteristics. Furthermore, a tracking algorithm based on Kalman filtering and Hungarian matching is presented for bubble counting in crucible space. The experimental results demonstrate that the detector algorithm presented in this paper can effectively reduce the missed detection rate of tiny bubbles and increase the average detection precision from 96.27% to 98.76% while reducing weight by half and reaching a speed of 82 FPS. The excellent detector performance improves the tracker’s accuracy significantly, allowing for real-time and high-precision counting of bubbles in quartz crucibles. It is an effective method for detecting crucible spatial bubbles.
Squat Detection of Railway Switches and Crossings Using Wavelets and Isolation Forest
Authors: Zuo Yang , Thiery Florian , Chandran Praneeth , Odelius Johan , Rantatalo Matti
Published: August 2022

Railway switches and crossings (S&Cs) are critical, high-value assets in railway networks. A single failure of such an asset could result in severe network disturbance and considerable economical losses. Squats are common rail surface defects of S&Cs and need to be detected and estimated at an early stage to minimise maintenance costs and increase the reliability of S&Cs. For practicality, installation of wired or wireless sensors along the S&C may not be reliable due to the risk of damages of power and signal cables or sensors. To cope with these issues, this study presents a method for collecting and processing vibration data from an accelerometer installed at the point machine to extract features related to the squat defects of the S&C. An unsupervised anomaly-detection method using the isolation forest algorithm is applied to generate anomaly scores from the features. Important features are ranked and selected. This paper describes the procedure of parameter tuning and presents the achieved anomaly scores. The results show that the proposed method is effective and that the generated anomaly scores indicate the health status of an S&C regarding squat defects.
Comparison of Deep Learning and Deterministic Algorithms for Control Modeling
Authors: Zhai Hanfeng , Sands Timothy
Published: August 2022

Controlling nonlinear dynamics arises in various engineering fields. We present efforts to model the forced van der Pol system control using physics-informed neural networks (PINN) compared to benchmark methods, including idealized nonlinear feedforward (FF) control, linearized feedback control (FB), and feedforward-plus-feedback combined (C). The aim is to implement circular trajectories in the state space of the van der Pol system. A designed benchmark problem is used for testing the behavioral differences of the disparate controllers and then investigating controlled schemes and systems of various extents of nonlinearities. All methods exhibit a short initialization accompanying arbitrary initialization points. The feedforward control successfully converges to the desired trajectory, and PINN executes good controls with higher stochasticity observed for higher-order terms based on the phase portraits. In contrast, linearized feedback control and combined feed-forward plus feedback failed. Varying trajectory amplitudes revealed that feed-forward, linearized feedback control, and combined feed-forward plus feedback control all fail for unity nonlinear damping gain. Traditional control methods display a robust fluctuation for higher-order terms. For some various nonlinearities, PINN failed to implement the desired trajectory instead of becoming “trapped” in the phase of small radius, yet idealized nonlinear feedforward successfully implemented controls. PINN generally exhibits lower relative errors for varying targeted trajectories. However, PINN also shows evidently higher computational burden compared with traditional control theory methods, with at least more than 30 times longer control time compared with benchmark idealized nonlinear feed-forward control. This manuscript proposes a comprehensive comparative study for future controller employment considering deterministic and machine learning approaches.
Study on the Construction of a Time-Space Four-Dimensional Combined Imaging Model and Moving Target Location Prediction Model
Authors: Zhu Junchao , Zeng Qi , Han Fangfang , Cao Huifeng , Bian Yongxin , Wei Chenhong
Published: August 2022

Time-space four-dimensional motion target localization is a fundamental and challenging task in the field of intelligent driving, and an important part of achieving the upgrade in existing target localization technologies. In order to solve the problem of the lack of localization of moving targets in a spatio-temporal four-dimensional environment in the existing spatio-temporal data model, this paper proposes an optical imaging model in the four-dimensional time-space system and a mathematical model of the object-image point mapping relationship in the four-dimensional time-space system based on the central perspective projection model, combined with the one-dimensional “time” and three-dimensional “space”. After adding the temporal dimension, the imaging system parameters are extended. In order to solve the nonlinear mapping problem of complex systems, this paper proposes to construct a time-space four-dimensional object-image mapping relationship model based on a BP artificial neural network and demonstrates the feasibility of the joint time-space four-dimensional imaging model theory. In addition, indoor time-space four-dimensional localization prediction experiments verify the performance of the model in this paper. The maximum relative error rates of the predicted motion depth values, time values, and velocity values of this localization method compared with the real values do not exceed 0.23%, 2.03%, and 1.51%, respectively
Modeling of the Influence of Operational Parameters on Tire Lateral Dynamics
Authors: Alcázar Vargas Manuel , Pérez Fernández Javier , Sánchez Andrades Ignacio , Cabrera Carrillo Juan A. , Castillo Aguilar Juan J.
Published: August 2022

Tires play a critical role in vehicle safety. Proper modeling of tire–road interaction is essential for optimal performance of active safety systems. This work studies the influence of temperature, longitudinal vehicle speed, steering frequency, vertical load, and inflation pressure on lateral tire dynamics. To this end, a tire test bench that allows the accurate control of these parameters and the measurement of the variables of interest was used. The obtained results made it possible to propose a simple model that allowed the determination of relaxation length as a function of tire vertical load and vehicle linear speed, and the determination of a representative tread temperature. Additionally, a model has been proposed to determine the lateral friction coefficient from the aforementioned temperature. Finally, results also showed that some variables had little influence on the parameters that characterize lateral dynamics.
Test and Analysis of Vegetation Coverage in Open-Pit Phosphate Mining Area around Dianchi Lake Using UAV–VDVI
Authors: Luo Weidong , Gan Shu , Yuan Xiping , Gao Sha , Bi Rui , Hu Lin
Published: August 2022

This work aimed to detect the vegetation coverage and evaluate the benefits of afforestation and ecological protection. Unmanned aerial vehicle (UAV) aerial survey was adopted to obtain the images of tailings area at Ma’anshan near the Dianchi Lake estuary, so as to construct a high-resolution Digital Orthophoto Map (DOM) and high-density Dense Image Matching (DIM) point cloud. Firstly, the optimal scale was selected for segmentation by considering the terrain. Secondly, the visible-band difference vegetation index (VDVI) of the classified vegetation information of the tail mining area was determined from the index gray histogram, ground class error analysis, and the qualitative and quantitative analysis of the bimodal index. Then, the vegetation information was extracted by combining the random forest (RF) classification algorithm. Finally, the extracted two-dimensional (2D) vegetation information was mapped to the three-dimensional (3D) point cloud, and the redundant data was eliminated. Fractional vegetation cover (FVC) was counted in the way of surface to point and human–machine combination. The experimental results showed that the vegetation information extracted from the 2D image was mapped to the 3D point cloud in the form of surface to point, and the redundant bare ground information was eliminated. The statistical FVC was 36.06%. The field survey suggested that the vegetation information in the turf dam area adjacent to the open phosphate deposit accumulation area research area was sparse. Relevant measures should be taken in the subsequent mining to avoid ecological damage caused by expanded phosphate mining. In general, applying UAV measurement technology and related 2D and 3D products to detect the vegetation coverage in an open phosphate mine area was of practical significance and unique technical advantages.
Assessing Dietary Nutrient Adequacy and the Effect of Season—Long Training on Body Composition and Metabolic Rate in Collegiate Male Basketball Players
Authors: Nishisaka Morgan M. , Zorn Sebastian P. , Kristo Aleksandra S. , Sikalidis Angelos K. , Reaves Scott K.
Published: August 2022

The success of performance in basketball relies on both optimal body composition and nutrient intake. The purpose of this study was to examine seasonal changes in body composition (BC), resting metabolic rate (RMR) and respiratory quotient (RQ), as well as dietary intake of National Collegiate Athletic Association (NCAA) Division I (DI) male basketball players. BC, RMR and RQ were assessed during pre-season, in-season, and post-season (September, December, and March) while dietary assessment data were collected in September and February. Results of this study indicated that players received inadequate energy (p < 0.0001), protein (p < 0.001) and carbohydrate (p < 0.0001) relative to the recommendations for exercising individuals during the September baseline period. However, following diet analysis and consultations and relative to recommendations, athletes received adequate amounts of energy and protein during follow-up, yet intakes of carbohydrate (p = 0.0025) were still significantly different than recommended. Results also indicated that there was a decrease in percent body fat (%BF) during season, an increase in lean body mass (LBM) from pre- to post-season, a peak in RMR during season and an increase in RQ post-season. These findings reveal that significant metabolic and body composition changes occur in players over the season and suggest that nutritional strategies employed concomitantly may be beneficial.