bluuebunny/crossref_metadata_2025 huggingface dataset:
Intrinsic Dipole Moments and Electron Transfer at the MIEC-Gas Interfaces
Authors: Williams Nicholas , Seymour Ieuan , Leah Robert , Mukerjee Subhasish , Selby Mark , Skinner Stephen
Published: July 2021

The magnitude of the electrostatic potential at the surface of a mixed ionic-electronic conducting (MIEC) solid-oxide cell (SOC) electrode is dependent on the intrinsic dipole moment of adsorbed gas species. Using density functional theory, we have investigated the electrostatic nature of hydroxyl adsorbates and the kinetics of electron transfer in the water electrolysis reaction at the pristine ceria-gas interface. First principles data ware used in a generalised kinetic model to predict reaction kinetics near equilibrium and under an applied overpotential. The mechanistic understanding gained from this model is widely applicable to a range of MIEC systems and provides a basis upon which the operating conditions can be tailored.
Effect of Fuel Depletion on Ni-YSZ Anode Supported Membrane Fuel Cell Under Different Discharge Modes
Authors: Lv Zhe , Huang Xiaoying , Liu Xin
Published: July 2021

In this work, button single cells with Ni-YSZ (anode support) | YSZ (electrolyte membrane) | Gd0.1Ce0.9O1.95 (barrier layer) | La0.6Sr0.4Co0.2Fe0.8O3-δ (cathode) structure produced by mass-producing under industrial conditions were operated with dry hydrogen as fuel. In order to simulate single cell unit failure in series stack and local region failure of one cell, fuel gas depletion experiments were carried out in constant current and constant voltage discharge modes, respectively. During the discharging processes, the hydrogen fuel was fed and cut off alternatively for several times with different cut-off time, the output performances were measured to evaluate the stability and healthy of the single cell. The results show that the long time fuel depletion of the cell discharging in constant current mode can directly destroy the cell, it means a cell unit’s life in series stack can be affected when suffered fuel depletion. However, the cell discharging in constant voltage mode can keep stable status under fuel depletion condition, it means that the local fuel depletion in a certain cell will not destroy it.
Investigating Effects of Operational Parameters on the Rate of Electrochemical Cleaning of Chromium Deposits on Strontium-Doped Lanthanum Manganite Cathodes in Solid Oxide Fuel Cells
Authors: Sugimoto Michelle , Zhu Zhikuan , Gopalan Srikanth , Basu Soumendra , Pal Uday
Published: July 2021

Chromium poisoning of the cathode remains a significant obstacle to the stable long-term performance of solid oxide fuel cells. This study reports, a quick, in-situ mitigation method, called electrochemical cleaning. By applying a mild anodic bias, the electrochemical deposition reactions of chromium-containing species are reversed. Chromium vapor species are formed, freeing active electrochemical sites in the air electrode. An LSM/YSZ-based cell was exposed to Cr vapors at 800ºC and then subjected to electrochemical cleaning. Cell performance recovery was evidenced by current-voltage and EIS measurements. Chromium removal was verified using SEM and EDS analyses. The cyclability of the electrochemical cleaning was tested by repeated poisoning and cleaning of another cell. Investigation into the effect of cell operating parameters (current density and cell temperature) on the rate of cleaning is discussed.
Galvanodynamic Electrochemical Impedance Spectroscopy on a Solid Oxide Cell Stack for In-Operando Diagnostics
Authors: Mastropasqua Luca , Saeedmanesh Alireza , Le Giang Tra , Adler Stuart B. , Brouwer Jack
Published: July 2021

In this study, we propose a new experimental setup and methodology that can perform in-situ diagnostic of a solid oxide cell stack without interfering with its normal steady state operation. We establish a floating ground galvanodynamic electrochemical impedance spectroscopy measurement setup connected to a 6-cell short stack. The diagnostic setup is electrically connected in parallel to the electronic load of the stack, so that the respective AC and DC current signals overlap. We demonstrate that this methodology is effective in detecting degradation and assessing the state-of-health of a specific cell or stack without disrupting its operation.
The 3D Reconstruction and Simulation of Solid Oxide Fuel Cell Anode
Authors: Liu Shixue , Liu Zhijing , Yang Ying , Zhang Lin , Huang Rui , Zhu Jiang , Zhang Shuxing
Published: July 2021

The 3D Focused Ion Beam - Scanning Electron Microscopy (FIB-SEM) technique has been used to study the ceramic microstructures with the accuracy of tens of nanometers. Samples taken from commercial size, 10×10 cm2, solid oxide fuel cell (SOFC) single cells were reconstructed with the FIB-SEM tomography. Three samples were chosen from the same production batch, including a cell without reduction, a cell with 5 hours reduction, and a cell with 80 hours high temperature test with humidified hydrogen, respectively. The triple-phase-boundary length and volume fractions were identified for the samples. The lattice Boltzmann method (LBM) was used to simulate the physical processed in the reconstructed porous electrode. The parameters in the exchange current density equation were fitted to the polarization curves.
La-doped Ba0.5Sr0.5Co0.8Fe0.2O3-
d as Cathode for Protonic-Conducting Solid Oxide Fuel Cells with Enhanced Structure Stability
Authors: Xie Yun , Hu Xueyu , Shi Nai , Peng Ranran , Chen Ming , Xia Changrong
Published: July 2021

As a highly efficient energy conversion device, proton-conducting solid oxide fuel cells (PCFCs) have attracted intensive attention. Unfortunately, its practical application is limited by the catalytic activity and stability of the cathode. Here, we report a novel electrochemical catalyst of 10 mol.% La modified Ba0.5Sr0.5Co0.8Fe0.2O3-
d cathode, showing much improved stability under typical PCFCs working conditions. XRD patterns confirm that La0.1Ba0.4Sr0.5Co0.8Fe0.2O3-
d maintains cubic structure after treated in humid air or 10% H2O - 90% N2. In addition, La0.1Ba0.4Sr0.5Co0.8Fe0.2O3-
d also demonstrates outstanding oxygen transport properties with a chemical surface exchange coefficient of 2.3*10-3 cm s-1 at 700oC, and the assembled single cells using this novel material present a minimal polarization resistance of 0.05 W cm2 at 700oC. The high stability and great electrochemical performance of La0.1Ba0.4Sr0.5Co0.8Fe0.2O3-
d may result from the stronger interaction in the La-O bond than in Ba-O. This work provides a strategy to modify materials properties via optimizing the interaction between metal and oxygen ions in the oxide lattice.
Examine Operando Generated Ni-Based Alloy Nanomaterials as Fuel Electrode in Solid Oxide Cells
Authors: Pukhova Alice , He Shuai , Zhang Nuoxi , Yue Xiangling
Published: July 2021

In this work, we focus on investigating the titanate perovskites with exsolved Ni-Co alloy nanocatalysts as fuel electrode of solid oxide cells (SOCs), particularly on operando generating these nanomaterials via applying a potential bias in CO2 electrolysis operating conditions. Three compositions of titanate perovskite were examined, including La0.43Ca0.37Ti0.94Ni0.06O3-δ (LCT-Ni6), La0.43Ca0.37Ti0.94Ni0.03Co0.03O3-δ (LCT-Ni3Co3), and La0.43Ca0.37Ti0.90Ni0.05Co0.05O3-δ (LCT-Ni5Co5). Various techniques, including X-ray diffraction, thermogravimetric analysis, DC conductivity measurement etc., were applied to study the crystal structure, reduction behavior, conductivity property, and microstructure of these materials. SOCs with these titanate fuel electrodes were fabricated and evaluated, with emphasis placed on operando generation of active nanomaterials through electrochemical switching in pure CO2 atmosphere, and on understanding the materials properties linking to their microstructure and performance towards CO2 electrolysis and H2 fuel cell.
Tunable Electrode Architectures for La0.8Sr0.2Fe1-XTixO3-
δ Based Symmetrical Solid Oxide Fuel Cells
Authors: Zamudio Javier , Porras-Vázquez Jose Manuel , Ramirez Enrique , Marrero-Lopez David
Published: July 2021

New strategies are necessary to enhance the efficiency of the electrodes for solid oxide fuel cells (SOFC) applications. Most of the preparation techniques require high sintering temperatures that drastically increases the grain size, leading to a very poor electrochemical activity. On this way, titanium doped ferrites have demonstrated to be promising electrodes, showing high redox stability and acceptable performance. In this study, spray-pyrolysis has been used to prepare nanostructured electrodes of La0.8Sr0.2Fe1-
xTixO3-δ (x= 0.2 and 0.4) in a single deposition step. An infiltrated electrode architecture was obtained by depositing the electrodes directly on a porous Ce0.9Gd0.1O1.95 (CGO) backbone previously screen-printed onto a Zr0.84Y0.16O1.92 (YSZ) electrolyte. The properties of this electrode, in comparison with the traditional electrode, are investigated in both oxidizing and reducing conditions for the implementation of these electrodes in Symmetrical Solid Oxide Fuel Cells (SSOFC).
Aerosol Deposition of Thin-Film Single- and Bi-layered Solid Electrolytes for Intermediate Temperature Planar Solid Oxide Fuel Cells
Authors: Erilin Ivan Sergeevich , Burmistrov Ilya Nikolaevich , Agarkov Dmitrii Aleksandrovich , Pukha Vladimir Egorovich , Yalovenko Dimitriy Vladimirovich , Lyskov Nikolay Viktorovich , Levin Mark Nikolaevich , Bredikhin Sergey Ivanovich
Published: July 2021

The aerosol deposition (AD) method is a technique for the formation of thin and thick, gas-tight, and porous layers by deposition of microscopic powder particles. In the present work, the AD was used to deposit thin-film electrolyte and protective buffer layers for planar anode-supported solid oxide fuel cells (SOFCs). The high quality of deposited layers was confirmed by scanning electron microscopy, as well as electrochemical measurements, including the measurements of current-voltage characteristics and impedance spectroscopy. At working temperature of 800°C the anode-supported cell with bi-layered electrolyte deposited by AD demonstrated the open-circuit voltage of more than 1.04 V, as well as specific power of more than 780 mW/cm2. The difficulties, advantages, and peculiarities associated with the formation of thin-film electrolyte and buffer layers of SOFCs by the AD method have been discussed.
Stability of Nickel/Scandia-Doped-Stabilized-Zirconia Composite Anode Under High Fuel Utilization Conditions
Authors: Taniguchi Shunsuke , Miyara Kengo , Kawabata Tsutomu , Uryu Chie , Inoue Yuko , Chou Jyh-Tyng , Sasaki Kazunari
Published: July 2021

Stability of nickel/scandia-doped-stabilized-zirconia (Ni/ScSZ) composite anode under high pH2O condition was investigated. Electrolyte supported cell with ScSZ electrolyte and Ni/ScSZ anode was operated at 700oC for 500 h by feeding mixture of H2/H2O/N2 as a fuel. Under 10%H2-40%H2O-50%N2, Sc diffused out of the ScSZ grain and dissolved into the adjacent Ni phase. Condensation of Sc in the Ni grain was enhanced by the application of current density of 0.5 A/cm2.
Enhancing the Catalytic Activity of Lanthanum-Ceria Fluorite for Methane Conversion in SOFC
Authors: Vilela Vanessa Bezerra , Thyssen Vivian Vazquez , Rodrigues Lays Nunes , Fonseca Fabio Coral
Published: July 2021

A2B2O7 compounds with tailored compositions exhibit catalytic properties in a variety of high-temperature reactions, such as oxidative coupling of methane (OCM). La2Ce2O7 performs well in OCM due to selective mobile oxygen species, and suitable alkaline sites. Doping with Ca2+ increases the alkalinity, which can considerably increase selectivity for C2 products in OCM. We have explored the combustion synthesis to obtain homogeneous Ca2+-doped La2Ce2O7 materials to use as a catalytic layer in SOFC reactors for methane direct conversion to C2. The addition of Ca2+ in the A site of La2Ce2O7 resulted in the disordered fluorite-type crystalline structure. The formation of superficial oxygen vacancies related to the active oxygen species, which may benefit the OCM reaction, was detected. Electrochemical characterization showed no significant dependence of the conductivity with Ca2+-doping.
Correlation Between Microstructure and Macroscopic Properties of Solid Oxide Fuel Cell Composite Anode: Mesoscale Modeling and Deep Learning with Convolutional Neural Network
Authors: Liu Xuhao , Zhou Shihao , Yan Zilin , Zhong Zheng , Shikazono Naoki , Hara Shotaro
Published: July 2021

In this paper, we propose a framework for studying the linkage between microstructures and macroscopic properties of Ni-YSZ anode in solid oxide fuel cells (SOFCs) by using meso-scale modeling and deep learning. The discrete element method and the mesoscale kinetic Monte Carlo method were used to generate Ni-YSZ anodes with various microstructures. Then, effective mechanical properties of the representative anodes were evaluated using finite element modeling and the homogenization theory. The triple phase boundary length density (L
TPB) was also calculated. The convolutional neural network (CNN) based deep learning model was trained to obtain the functional relationship between the microstructures and the mechanical properties and L
TPB. The deep learning model was finally well validated against new samples with excellent predictive performances. This indicates that the CNN model can be used as a surrogate model for rapid direct access to macroscopic properties of composite anodes and for macroscale continuum modeling of SOFCs.
Degradation Analysis of SOFC Performance for Long-Term Operation with High Fuel Utilization
Authors: Ido Akifumi , Imabayashi Takumi , Asano Koichi , Yamamoto Tohru , Morita Hiroshi , Mugikura Yoshihiro
Published: July 2021

In a NEDO’s project from FY2020 to FY2024, Central Research Institute of Electric Power Industry (CRIEPI) has operated three types of SOFC stacks, which are developed by KYOCERA, MORIMURA SOFC TECHNOLOGY (MST), and DENSO in order to clarify the technical issues for high efficiency and toughness of SOFC stacks and establish the method for degradation diagnosis of SOFC stacks. Each SOFC stack has been operated with the high fuel utilization (Uf = 80 and 85%) as a severe condition for high-efficiency and degradation factors for SOFC durability have been analyzed by using the electrode polarization model which we have developed. Analysis results until now showed that dominant degradation factor was increase of cathode overvoltage or IR loss as same as that in the previous term. Moreover, thermal property testing has been conducted to apply the effect of temperature to our polarization model. It was clarified that internal resistance and electrode resistance coefficients can be expressed by Arrhenius equation.
Investigation on B-Site Exsolved Titanates and its Structure-Property Relationship as Fuel Electrode in Solid Oxide Cells
Authors: He Shuai , Yue Xiangling
Published: July 2021

Titanates capable of exsolving B-site metals have shown great potential as fuel electrode in solid oxide cells (SOCs). The well-anchored nano-particles are found to exhibit superior electrocatalytic activity and resistance towards carbon deposition. Here, in order to investigate the intrinsic properties of exsolved particles under redox conditions, we selected La0.43Ca0.37Ni0.06Ti0.94O3-δ (LCNT), La0.43Ca0.37Ni0.03Fe0.03Ti0.94O3-δ (LCNFT), and La0.8Ce0.1Ni0.4Ti0.6O3 (LCeNT) as model electrode materials to exsolve Ni, Ni-Fe alloy, and Ni-CeO2, respectively. The influence of co-doping, doping level, and A-site deficiency on the exsolution process and the behavior of the exsolved particles upon oxidation were studied and characterized. The results suggest that all three materials exsolved nano-particles after reduction with different size and population, yet they tend to follow a similar trend upon oxidation.
Super-Resolved in-Operando Observation of SOFC Pattern Electrodes
Authors: Yamagishi Rena , Sciazko Anna , Ouyang Zhufeng , Komatsu Yosuke , Katsuhiko Nishimura , Shikazono Naoki
Published: July 2021

In order to investigate Nickel (Ni) movements during operation, in-operando observation of Ni-pattern electrode is conducted with confocal laser microscope. In-operando observations have limitation of quantitative analysis due to the low resolution of the laser microscope. In this study, two machine learning algorithms for super resolving laser microscope images are proposed. Firstly, semantic segmentation algorithm based on convolutional neural network (CNN) is introduced for automatic material identification. U-net architecture is incorporated and compared with simple encoder-decoder network. The phase fractions and triple phase boundary (TPB) density estimated from the automatically segmented image agreed well with the ground truth data. The proposed U-net can detect fine features of the microstructure. Secondly, super-resolution generative adversarial network (GAN) is proposed. The developed network applies pix2pix GAN architecture and aims to synthesize SEM-quality image from low resolution laser image. The generated images achieved very high resolution equivalent to SEM images.
Physical and Electrochemical Characterization of La0.25Sr0.25Ca0.40Ti0.95Ni0.05-xSnxO3–δ (x=0...0.05) Reversible Solid Oxide Cell Fuel Electrode
Authors: Maide Martin , Moeller Prit , Aruväli Jaan , Lust Enn , Nurk Gunnar
Published: July 2021

La0.25Sr0.25Ca0.40Ti0.95Ni0.05-xSnxO3–δ (x=0...0.05) mixed ionic electronic conductor (MIEC) materials were studied as possible fuel electrodes for solid oxide cell. Initial characterization of the materials aimed to understand whether tin occupied the A- or the B-site in the material through precise control of material stoichiometry using thermogravimetric analysis (TGA) and XRD characterization. Thereafter, a set of La0.25Sr0.25Ca0.40Ti0.95Ni0.05-xSnxO3–δ materials were synthesized and characterized to understand the influence of the B-site dopant on the phase purity and time-stability in reducing atmosphere. Finally, initial electrochemical characterization has been conducted for some of the synthesized materials.
Store-operated calcium entry-associated regulatory factor regulates airway inflammation and airway remodeling in asthma mice models
Authors: Wang Yi-Min , Xu Wen-Juan , Xiang Lin-Li , Ding Mei , Zhang Jin-Jin , Lu Jing-Ya , Xie Bao-Juan , Gao Ya-Dong
Published: July 2021

Store-operated calcium entry (SOCE) is involved in the pathogenesis of airway inflammation and remodeling in asthma. Store-operated calcium entry-associated regulatory factor (SARAF) can downregulate SOCE. We sought to investigate the role of SARAF in the regulation of airway inflammation and remodeling in asthma mice models, as well as in the functional regulation of human airway smooth muscle cells (hASMCs). Balb/c mice were sensitized and challenged with ovalbumin to establish the asthma mice models. Mice were transfected with lentivirus, which expressed the SARAF gene + GFP (green fluorescence protein) or the negative control gene + GFP. Airway resistance was measured with the animal pulmonary function system. Airway inflammation and remodeling were evaluated via histological staining. In vitro cultured hASMCs were transfected with scrambled small interfering RNA (siRNA) or SARAF-specific siRNA, respectively. The proliferation, migration rate, hypertrophy, and SOCE activity of hASMCs were examined with Cell Counting Kit-8, wound healing test, bright field imaging, and Ca2+ fluorescence imaging, respectively. SARAF expression was measured by quantitative real-time PCR. Asthma mice models showed decreased SARAF mRNA expression in the lungs. SARAF overexpression attenuated airway inflammation, resistance, and also remodeling. Downregulation of SARAF expression with siRNA promoted the proliferation, migration, hypertrophy, and SOCE activity in hASMCs. SARAF plays a protective role against airway inflammation and remodeling in asthma mice models by blunting SOCE; SARAF may also be a functional regulating factor of hASMCs.
Neurophysiology of slip sensation and grip reaction: insights for hand prosthesis control of slippage
Authors: Zangrandi Andrea , D’Alonzo Marco , Cipriani Christian , Di Pino Giovanni
Published: July 2021

Sensory feedback is pivotal for a proficient dexterity of the hand. By modulating the grip force in function of the quick and not completely predictable change of the load force, grabbed objects are prevented to slip from the hand. Slippage control is an enabling achievement to all manipulation abilities. However, in hand prosthetics, the performance of even the most innovative research solutions proposed so far to control slippage remain distant from the human physiology. Indeed, slippage control involves parallel and compensatory activation of multiple mechanoceptors, spinal and supraspinal reflexes, and higher-order voluntary behavioral adjustments. In this work, we reviewed the literature on physiological correlates of slippage to propose a three-phases model for the slip sensation and reaction. Furthermore, we discuss the main strategies employed so far in the research studies that tried to restore slippage control in amputees. In the light of the proposed three-phase slippage model and from the weaknesses of already implemented solutions, we proposed several physiology-inspired solutions for slippage control to be implemented in the future hand prostheses. Understanding the physiological basis of slip detection and perception and implementing them in novel hand feedback system would make prosthesis manipulation more efficient and would boost its perceived naturalness, fostering the sense of agency for the hand movements.
Anticipation and compensation for somatosensory deficits in object handling: evidence from a patient with large fiber sensory neuropathy
Authors: Parry Ross , Sarlegna Fabrice R. , Jarrassé Nathanaël , Roby-Brami Agnès
Published: July 2021

This study evaluates the effects of sensory neuropathy on the scaling and timing of grip force adjustments across different object handling tasks (i.e., holding, vertical movement, grasping, and placement). In particular, these results illustrate how novel anticipatory and online control processes emerge to compensate for the loss of somatosensory feedback. In addition, we provide new evidence on the role of somatosensory feedback for regulating object orientation during functional prehensile movement.
Electrical epidural stimulation of the cervical spinal cord: implications for spinal respiratory neuroplasticity after spinal cord injury
Authors: Malone Ian G. , Nosacka Rachel L. , Nash Marissa A. , Otto Kevin J. , Dale Erica A.
Published: July 2021

Traumatic cervical spinal cord injury (cSCI) can lead to damage of bulbospinal pathways to the respiratory motor nuclei and consequent life-threatening respiratory insufficiency due to respiratory muscle paralysis/paresis. Reports of electrical epidural stimulation (EES) of the lumbosacral spinal cord to enable locomotor function after SCI are encouraging, with some evidence of facilitating neural plasticity. Here, we detail the development and success of EES in recovering locomotor function, with consideration of stimulation parameters and safety measures to develop effective EES protocols. EES is just beginning to be applied in other motor, sensory, and autonomic systems; however, there has only been moderate success in preclinical studies aimed at improving breathing function after cSCI. Thus, we explore the rationale for applying EES to the cervical spinal cord, targeting the phrenic motor nucleus for the restoration of breathing. We also suggest cellular/molecular mechanisms by which EES may induce respiratory plasticity, including a brief examination of sex-related differences in these mechanisms. Finally, we suggest that more attention be paid to the effects of specific electrical parameters that have been used in the development of EES protocols and how that can impact the safety and efficacy for those receiving this therapy. Ultimately, we aim to inform readers about the potential benefits of EES in the phrenic motor system and encourage future studies in this area.
[Retracted] Optimization of Intelligent Management and Monitoring System of Sports Training Hall Based on Internet of Things
Authors: Qian Hui
Published: July 2021

This paper provides an indepth analysis and research on the intelligent management and monitoring system of sports training hall through the Internet of Things. Firstly, it introduces the project background of the sports training base stadium service system, analyses the significance of the system development, and describes the related technology and the method of development. The paper then analyses the requirements of the management business of the system and describes the main business processes of the system with activity diagrams; the paper then analyses the functional requirements and data requirements of the system and describes the system with use case diagrams and thumbnail class diagrams, respectively. Based on this, the thesis designs the overall aspect of the system, giving the corresponding total package diagram, and designs all functions one by one, giving the corresponding class diagram, the corresponding sequence diagram, and the corresponding processing flow diagram. The thesis gives the design of database tables by designing entity property diagrams and entity‐to‐entity relationship diagrams according to the data requirements and system functions. Finally, the research of the thesis is summarized accordingly, stating what has been done, what results have been achieved, what problems still exist, and what further work needs to be done to make the outlook of the work.
[Retracted] Gene Position Index Mutation Detection Algorithm Based on Feedback Fast Learning Neural Network
Authors: Zuo Zhike , Tang Chao , Xu Yu , Wang Ying , Wu Yongzhong , Qi Jun , Shi Xiaolong
Published: July 2021

In the detection of genome variation, the research on the internal correlation of reference genome is deepening; the detection of variation in genome sequence has become the focus of research, and it has also become an effective path to find new genes and new functional proteins. The targeted sequencing sequence is used to sequence the exon region of a specific gene in cancer gene detection, and the sequencing depth is relatively large. Traditional alignment algorithms will lose some sequences, which will lead to inaccurate mutation detection. This paper proposes a mutation detection algorithm based on feedback fast learning neural network position index. By establishing a position index relationship for ACGT in the DNA sequence, the subsequence is decomposed into the position relationship of different subsequences corresponding to the main sequence. The positional relationship of the subsequence in the main sequence is determined by the positional relationship. Analyzing SNP and InDel mutations, even structural mutations, through the position correlation of sequences has the advantages of high precision and easy implementation by personal computers. The feedback fast learning neural network is used to verify whether there is a linear relationship between two or more positions. Experimental results show that the mutation points detected by position index are more than those detected by Bcftools, Freebye, Vanscan2, and Gatk.
Temporal-Spatial Characteristics of Ground and Pile Responses to Twin Shield Tunneling in Clays
Authors: Sheng Minghong , Gao Jinjin , Guo Panpan , Cao Rihong , Wang Yixian
Published: July 2021

This paper investigates the temporal-spatial characteristics of ground displacements as well as vertical and horizontal displacements and axial forces in existing piles induced by twin shield tunneling in clays. To that end, a case study and three-dimensional (3D) finite element (FE) analysis were performed. Based on the in situ monitoring data from the presented twin tunneling case history with existing piles beneath, the adopted 3D FE method was validated to be competent to yield reasonable simulation results. The validated 3D FE method was then used to analyze the effects of the distance between the tunnel and the pile, the distance between tunnel faces, and the pile length on the horizontal and vertical displacements and axial stresses in piles. It was found that the horizontal displacement distribution forms along the pile shaft for the front piles are similar to that for the back piles, whereas the magnitudes of the horizontal displacements of the front piles are slightly larger than that of the back piles. The interactions between piles in the pile group provide protection of the middle piles in the pile group against twin tunneling effects. With a reduction in the distance between the tunnel and the pile, the pile displacements and stresses increase nonlinearly. With an increase in the distance between tunnel faces, the maximum positive pile displacements and the maximum and minimum axial pile stresses increase, while the maximum negative pile displacements and the difference between the maximum and minimum axial pile stresses decrease.
Modeling Method of Autonomous Robot Manipulator Based on D-H Algorithm
Authors: Cai Jie , Deng Jinlian , Zhang Wei , Zhao Weisheng
Published: July 2021

With the continuous development of science and technology, robotics is widely used in various fields. In recent years, more and more research studies have been done on the control of autonomous robotic manipulators. How to quickly, accurately, and smoothly grasp objects has always been a difficult point of research. As the robot’s executive mechanism, the robot arm plays an important role in whether the robot can complete a specific task. Therefore, the research on the robot arm is also the main topic in the development of robot technology. The control theory, kinematics, and human-computer interaction of robotic arms are the focus of the research in the field of robotic arms. Based on the above background, the research content of this paper is the research on the modeling method of autonomous robotic manipulator based on D-H algorithm. This paper uses D-H modeling method to model a four-degree-of-freedom robotic arm and gives the forward kinematics equation of the robotic arm. The inverse solution of the manipulator was given by the method and the geometric method, and the joint variable values were calculated. Finally, through experimental simulation, the experimental results show that the inverse solution of the end position of the machine by the geometric method is in the range of 2∼4 mm, and the inverse solution of the end position of the machine by the algebraic method is in the range of 6∼14 mm. It is more accurate to find the inverse solution of the geometrical method of the manipulator than the algebraic method.
Systematic Profiling of mRNA Splicing Reveals the Prognostic Predictor and Potential Therapeutic Target for Glioblastoma Multiforme
Authors: Zhang Botao , Wu Quanyou , Cheng Shujun , Li Wenbin
Published: July 2021

Despite many changes in alternative splicing events (ASEs) are frequently involved in various cancers, prognosis-related ASEs and drug treatment targets in glioblastoma multiforme (GBM) have not been well explored. ASEs participate in many biological behaviors in the initiation and progression of tumors, the aberrant ASE has been considered another hallmark of cancer, and the systematic study of alternative splicing may provide potential biomarkers for malignancies. In this study, we carried out a systematic analysis to characterize the ASE signatures in GBM cohort. Through comparing GBM tissues and nontumor tissues, a total of 48,191 differently expressed ASEs from 10,727 genes were obtained, and these aberrant ASEs play an important role in the oncogenic process. Then, we identified 514 ASEs independently associated with patient survival in GBM by univariate and multivariate Cox regression, including exon skip in CD3D, alternate acceptor site in POLD2, and exon skip in DCN. Those prognostic models built on ASEs of each splice type can accurately predict the outcome of GBM patients, and values for the area under curve were 0.97 in the predictive model based on alternate acceptor site. In addition, the splicing-regulatory network revealed an interesting correlation between survival-associated splicing factors and prognostic ASE corresponding genes. Moreover, these three hub splicing factors in splicing regulation network are the potential targets of some drugs. In conclusion, a systematic analysis of ASE signatures in GBM could serve as an indicator for identifying novel prognostic biomarkers and guiding clinical treatment.
Noise-Induced Hearing Loss: Updates on Molecular Targets and Potential Interventions
Authors: Mao Huanyu , Chen Yan
Published: July 2021

Noise overexposure leads to hair cell loss, synaptic ribbon reduction, and auditory nerve deterioration, resulting in transient or permanent hearing loss depending on the exposure severity. Oxidative stress, inflammation, calcium overload, glutamate excitotoxicity, and energy metabolism disturbance are the main contributors to noise-induced hearing loss (NIHL) up to now. Gene variations are also identified as NIHL related. Glucocorticoid is the only approved medication for NIHL treatment. New pharmaceuticals targeting oxidative stress, inflammation, or noise-induced neuropathy are emerging, highlighted by the nanoparticle-based drug delivery system. Given the complexity of the pathogenesis behind NIHL, deeper and more comprehensive studies still need to be fulfilled.
(m, n)-Ideals in Semigroups Based on Int-Soft Sets
Authors: Muhiuddin G. , Alanazi Abdulaziz M.
Published: July 2021

Algebraic structures play a prominent role in mathematics with wide ranging applications in many disciplines such as theoretical physics, computer sciences, control engineering, information sciences, coding theory, and topological spaces. This provides sufficient motivation to researchers to review various concepts and results from the realm of abstract algebra in the broader framework of fuzzy setting. In this paper, we introduce the notions of int-softm,n-ideals, int-softm,0-ideals, and int-soft0,n-ideals of semigroups by generalizing the concept of int-soft bi-ideals, int-soft right ideals, and int-soft left ideals in semigroups. In addition, some of the properties of int-softm,n-ideal, int-softm,0-ideal, and int-soft0,n-ideal are studied. Also, characterizations of various types of semigroups such asm,n-regular semigroups,m,0-regular semigroups, and0,n-regular semigroups in terms of their int-softm,n-ideals, int-softm,0-ideals, and int-soft0,n-ideals are provided.
Evaluating the Safety Impact of Connected and Autonomous Vehicles with Lane Management on Freeway Crash Hotspots Using the Surrogate Safety Assessment Model
Authors: Zhang Hui , Hou Ninghao , Zhang Jianhua , Li Xuyi , Huang Yan
Published: July 2021

One goal for large-scale deployment of connected and autonomous vehicles is to achieve the traffic safety benefit since connected and autonomous vehicles (CAVs) could reduce the collision risk by enhancing the driver’s situation perception ability. Previous studies have analyzed the safety impact of CAVs involved in traffic, but only few studies examined the safety benefits brought by CAVs when approaching high-collision-risk road segments such as the freeway crash hotspots. This study chooses one freeway crash hotspot in Wuhan, China, as an instance and attempts to estimate the safety benefits for differential penetration rates (PRs) of CAVs using the surrogate safety assessment model (SSAM). First, the freeway crash hotspot is identified with kernel density estimation and simulated by VISSIM. Then, the intelligent driver model (IDM) and Wiedemann 99 (a car-following model) are adopted and calibrated to control the driving behaviors of CAVs and human-driven vehicles (HVs) in this study, respectively. The impact that rather CAVs are constrained with or without managed lanes on traffic safety is also discussed, and the PR of CAVs is set from 10% to 90%. The results of this study show that when the PR of CAVs is lower than 50%, there is no significant improvement on the safety measures such as conflicts, acceleration, and velocity difference, which are extracted from the vehicle trajectory data using SSAM. When the penetration rate is over 70%, the experiment results demonstrate that the traffic flow passing the freeway hotspot is with fewer conflicts, smaller acceleration, and smaller velocity difference in the scenario where CAVs are constrained with managed lane compared with the scenario without managed lane control. The safety benefit that CAVs bring needs to be discussed. The lane management of CAVs will also lead to distinct safety impact.
Intrusion Detection System to Advance Internet of Things Infrastructure‐Based Deep Learning Algorithms
Authors: Alkahtani Hasan , Aldhyani Theyazn H. H.
Published: July 2021

Smart grids, advanced information technology, have become the favored intrusion targets due to the Internet of Things (IoT) using sensor devices to collect data from a smart grid environment. These data are sent to the cloud, which is a huge network of super servers that provides different services to different smart infrastructures, such as smart homes and smart buildings. These can provide a large space for attackers to launch destructive cyberattacks. The novelty of this proposed research is the development of a robust framework system for detecting intrusions based on the IoT environment. An IoTID20 dataset attack was employed to develop the proposed system; it is a newly generated dataset from the IoT infrastructure. In this framework, three advanced deep learning algorithms were applied to classify the intrusion: a convolution neural network (CNN), a long short‐term memory (LSTM), and a hybrid convolution neural network with the long short‐term memory (CNN‐LSTM) model. The complexity of the network dataset was dimensionality reduced, and to improve the proposed system, the particle swarm optimization method (PSO) was used to select relevant features from the network dataset. The obtained features were processed using deep learning algorithms. The experimental results showed that the proposed systems achieved accuracy as follows: CNN = 96.60%, LSTM = 99.82%, and CNN‐LSTM = 98.80%. The proposed framework attained the desired performance on a new variable dataset, and the system will be implemented in our university IoT environment. The results of comparative predictions between the proposed framework and existing systems showed that the proposed system more efficiently and effectively enhanced the security of the IoT environment from attacks. The experimental results confirmed that the proposed framework based on deep learning algorithms for an intrusion detection system can effectively detect real‐world attacks and is capable of enhancing the security of the IoT environment.
Pink1/PARK2/mROS‐Dependent Mitophagy Initiates the Sensitization of Cancer Cells to Radiation
Authors: Yu Lei , Yang Xiangshan , Li Xin , Qin Lijing , Xu Weiqiang , Cui Hongli , Jia Zhen , He Qiang , Wang Zhicheng
Published: July 2021

Autophagy plays a double‐edged sword for cancer; particularly, mitophagy plays important roles in the selective degradation of damaged mitochondria. However, whether mitophagy is involved in killing effects of tumor cells by ionizing radiation (IR) and its underlying mechanism remain elusive. The purpose is to evaluate the effects of mitochondrial ROS (mROS) on autophagy after IR; furthermore, we hypothesized that KillerRed (KR) targeting mitochondria could induce mROS generation, subsequent mitochondrial depolarization, accumulation of Pink1, and recruitment of PARK2 to promote the mitophagy. Thereby, we would achieve a new strategy to enhance mROS accumulation and clarify the roles and mechanisms of radiosensitization by KR and IR. Our data demonstrated that IR might cause autophagy of both MCF‐7 and HeLa cells, which is related to mitochondria and mROS, and the ROS scavenger N‐acetylcysteine (NAC) could reduce the effects. Based on the theory, mitochondrial targeting vector sterile α‐ and HEAT/armadillo motif‐containing protein 1‐ (Sarm1‐) mtKR has been successfully constructed, and we found that ROS levels have significantly increased after light exposure. Furthermore, mitochondrial depolarization of HeLa cells was triggered, such as the decrease of Na+K+ ATPase, Ca2+Mg2+ ATPase, and mitochondrial respiratory complex I and III activities, and mitochondrial membrane potential (MMP) has significantly decreased, and voltage‐dependent anion channel 1 (VDAC1) protein has significantly increased in the mitochondria. Additionally, HeLa cell proliferation was obviously inhibited, and the cell autophagic rates dramatically increased, which referred to the regulation of the Pink1/PARK2 pathway. These results indicated that mitophagy induced by mROS can initiate the sensitization of cancer cells to IR and might be regulated by the Pink1/PARK2 pathway.
Blood Lead Levels and Associated Sociodemographic Factors among Children Aged 3 to 14 Years Living near Zinc and Lead Mines in Two Provinces in Vietnam
Authors: Hoang Thi Giang , Tran Quang Phuc , Lo Van Tung , Doan Ngoc Hai , Nguyen Thu Ha , Pham Minh Khue
Published: July 2021

Lead poisoning in children is a major public health concern worldwide, especially in developing countries. We conducted a cross‐sectional study on 403 children aged from 3 to 14 years living nearly zinc–lead mining areas in two provinces in Vietnam (Bac Kan and Thai Nguyen) from 06/2016 to 10/2016 to identify risk factors for lead contamination. Results. The proportion of children with blood lead levels (BLLs) ≥ 10 μg/dL was 80.51% in Bac Kan and 50% in Thai Nguyen; the mean blood lead level for children was 14.41 ± 9.42 μg/dL. In linear regression analyses, the body mass index was negatively associated with elevated BLLs with r = −0.404, p < 0.05 (95% CI: ‐0.801, ‐0.006). In multivariable regression analysis, several risk factors were associated with lead contamination including male sex (aOR = 2.44, 95% CI: 1.13‐5.24, p = 0.02), play areas in Bac Kan (aOR = 2.3 (1.02‐5.17), p = 0.04), proximity of children’s home of less than 2 kilometers from the mine (aOR = 2.90 (1.54‐5.44), p = 0.001), and inattentive symptoms in Thai Nguyen (aOR = 7.85, 95% CI 3.49‐17.69, p = 0.001). Environmental factors, including lead concentrations in the soil and ambient air samples in both locations, are many times higher than Vietnamese standards.
Optimization of Correlation Filters Using Extended Particle Swarm Optimization Technique
Authors: Masood Haris , Zafar Amad , Ali Muhammad Umair , Khan Muhammad Attique , Iqbal Kashif , Tariq Usman , Kadry Seifedine
Published: July 2021

In the past few decades, the field of image processing has seen a rapid advancement in the correlation filters, which serves as a very promising tool for object detection and recognition. Mostly, complex filter equations are used for deriving the correlation filters, leading to a filter solution in a closed loop. Selection of optimal tradeoff (OT) parameters is crucial for the effectiveness of correlation filters. This paper proposes extended particle swarm optimization (EPSO) technique for the optimal selection of OT parameters. The optimal solution is proposed based on two cost functions. The best result for each target is obtained by applying the optimization technique separately. The obtained results are compared with the conventional particle swarm optimization method for various test images belonging from different state-of-the-art datasets. The obtained results depict the performance of filters improved significantly using the proposed optimization method.
Assessment and Modeling of Household-Scale Solar Water Heater Application in Zambia: Technical, Environmental, and Energy Analysis
Authors: Jahangiri Mehdi , Akinlabi Esther T. , Sichilalu Sam M.
Published: July 2021

Solar water heaters (SWHs) are one of the most effective plans for general and easy use of solar energy to supply hot water in domestic and industrial sectors. This paper gives the first-ever attempts to assess the optimal localization of SWHs across 22 major cities in Zambia, as well as determine the possibility of hot water generation and model the greenhouse gas (GHG) emission saving. The climate data used is extracted by using the MeteoSyn software which is modeled in TSOL™. Results show the high potential of GHG emission reduction due to nonconsumption of fossil fuels owing to the deployment of SWHs, and three cities Kabwe, Chipata, and Mbala had the highest GHG mitigation by 1552.97 kg/y, 1394.8 kg/y, and 1321.39 kg/y, respectively. On average, SWHs provide 62.47% of space heating and 96.05% of the sanitary hot water requirement of consumers. The findings have shown the potential for the deployment of SWHs in Zambia. The techno-enviro study in this paper can be used by the policymakers of Zambia and countries with similar climates.
Cramming the Specificities in Contemplating Safe Bearing Capacity for the Foundation Assessed from Borehole Samples in a Sandy‐Moorum Zone
Authors: Lohani Tarun Kumar , Ayana Melkamu Teshome , Mohammed Abdella Kemal , Pattanaik Jyotiranjan
Published: July 2021

Borehole samples drilled up to a depth of 10 m provide a clear understanding whether a foundation is safe for any structure. The main objective of the present study reconnoitered the soil bearing capacity and foundation settlement characteristics using the standard penetration test (SPT) data obtained from 3 boreholes at 1 m, 2 m, and 3 m depths to correlate soil properties and deterrents, if any, created by groundwater. The methodology of the research is to collect soil samples, and ensuing subsoil analysis was performed in order to obtain concrete information to optimize the foundation system within the safe bearing capacity of soil and its allowable settlement. The scope of the work encompasses conducting detailed soil investigation from drilling logs, laboratory testing, and conducting and estimating safe bearing capacity. The result of the research aims at providing safety to the foundation from the investigations of conclusive recommendation to be adopted which would be economically feasible and structurally secured.
Damage Identification of Ancient Timber Structure Based on Autocorrelation Function
Authors: Hou Yanfang , Hu Weibing , Wang Xin , Hou Tingting , Sun Congli
Published: July 2021

A damage location method for the autocorrelation peak value change rate based on the vibration response of a random vibration structure is established. To calculate the autocorrelation function of the vibration response of each measurement point, we transformed the maximum values into an autocorrelation peak vector. Under a good condition, the autocorrelation peak vector has a fixed shape; hence, it can be used as a basis for structural damage identification. The two adjacent measurement points with the largest change corresponding to the two nodes of the damage unit and the damage location are determined to calculate the change rate of the autocorrelation peak values between damaged and intact structures. When the degree of damage is 5%, the autocorrelation peak value change rate of the acceleration response on the two nodes of the damage unit is significantly greater than that of the other points, which can accurately determine the damage location, indicating that the damage location index constructed has good damage sensitivity. The damage location index can determine a single damage, as well as a double damage. The antinoise capability of the damage location index gradually improves with an increase in the degree of damage. At 45% degree of damage and signal‐to‐noise ratio (SNR) of 0 dB, the damage location index can still accurately determine the damage location, which has good antinoise interference capability. The Xi’an Bell Tower is used as a case study, and the feasibility of this method is verified, which provides a new method for the study of damage location of ancient timber structures.