bluuebunny/crossref_metadata_2025 huggingface dataset:
Developing an
in situ
, hydromechanical coupling, true triaxial rock compression tester and investigating the deformation patterns of reservoir bank slopes
Authors: Fan Lei , Yu Meiwan , Wu Aiqing , Zhang Yihu
Published: December 2021

Interactions between water and rocks are the main factors affecting the deformation of rock masses on sloped banks by reservoir impoundment. The technology used in laboratory tests of water–rock interaction mechanisms cannot simulate the coupling of water, the rock structure and the initial stress environment. In this work, we develop an
in situ
, hydromechanical (HM), true triaxial rock compression tester and apply it to investigate the coupling response of reservoir bank rocks to changing groundwater levels. The tester is composed of a sealed chamber, loader, reactor and device for measuring deformation, which are all capable of withstanding high water pressures, and a high-precision servo controller. The maximum axial load, lateral load and water pressure are 12 000 kN, 3000 kN and 3 MPa, respectively. The dimensions of the test specimens are 310 × 310 × 620 mm. The test specimens are grey-black basalts with well-developed cracks from the Xiluodu reservoir area. The results show that increasing water pressure promotes axial compression and lateral expansion, while decreasing water pressure causes axial expansion and lateral compression. A water pressure coefficient,
K
, is introduced as a measure of the HM coupling effect (expansion or compression) with changing groundwater level. A mechanical tester can be used to perform accurate field tests of the response of wet rocks to HM coupling. The test results provide new information about the deformation patterns of rock slopes in areas surrounding high dams and reservoirs.

Thematic collection:
This article is part of the Role of water in destabilizing slopes collection available at:
https://www.lyellcollection.org/cc/Role-of-water-in-destabilizing-slopes
Locally-iterative Distributed (Δ + 1)-coloring and Applications
Authors: Barenboim Leonid , Elkin Michael , Goldenberg Uri
Published: December 2021

We consider graph coloring and related problems in the distributed message-passing model.Locally-iterative algorithmsare especially important in this setting. These are algorithms in which each vertex decides about its next color only as a function of the current colors in its1-hop-neighborhood. In STOC’93 Szegedy and Vishwanathan showed that any locally-iterative Δ + 1-coloring algorithm requires Ω (Δ log Δ + log*n) rounds, unless there exists “a very special type of coloring that can be very efficiently reduced” [44]. No such special coloring has been found since then. This led researchers to believe that Szegedy-Vishwanathan barrier is an inherent limitation for locally-iterative algorithms and to explore other approaches to the coloring problem [2,3,19,32]. The latter gave rise to faster algorithms, but their heavy machinery that is of non-locally-iterative nature made them far less suitable to various settings. In this article, we obtain the aforementioned special type of coloring. Specifically, we devise a locally-iterative Δ + 1-coloring algorithm with running timeO(Δ + log*n), i.e.,belowSzegedy-Vishwanathan barrier. This demonstrates that this barrier is not an inherent limitation for locally-iterative algorithms. As a result, we also achieve significant improvements for dynamic, self-stabilizing, and bandwidth-restricted settings. This includes the following results:

We obtain self-stabilizing distributed algorithms for Δ + 1-vertex-coloring, (2Δ - 1)-edge-coloring, maximal independent set, and maximal matching withO(Δ + log*n) time. This significantly improves previously known results that haveO(n)or larger running times [23].

We devise a (2Δ - 1)-edge-coloring algorithm in the CONGEST model withO(Δ + log*n) time andO(Δ)-edge-coloring in the Bit-Round model withO(Δ + logn) time. The factors of log*nand lognare unavoidable in the CONGEST and Bit-Round models, respectively. Previously known algorithms had superlinear dependency on Δ for (2Δ - 1)-edge-coloring in these models.

We obtain an arbdefective coloring algorithm with running timeO(√ Δ + log*n). Such a coloring is not necessarily proper, but has certain helpful properties. We employ it to compute a proper (1 + ε)Δ-coloring withinO(√ Δ + log*n) time and Δ + 1-coloring withinO(√ Δ log Δ log*Δ + log*n) time. This improves the recent state-of-the-art bounds of Barenboim from PODC’15 [2] and Fraigniaud et al. from FOCS’16 [19] by polylogarithmic factors.

Our algorithms are applicable to the SET-LOCAL model [25] (also known as the weak LOCAL model). In this model a relatively strong lower bound of Ω (Δ1/3) is known for Δ + 1-coloring. However, most of the coloring algorithms do not work in this model. (In Reference [25] only Linial’sO(Δ2)-time algorithm and Kuhn-WattenhoferO(Δ log Δ)-time algorithms are shown to work in it.) We obtain the first linear-in-Δ Δ + 1-coloring algorithms that work also in this model.
Lamboozling Attackers
Authors: Shortridge Kelly , Petrich Ryan
Published: December 2021

Deception is a powerful resilience tactic that provides observability into attack operations, deflects impact from production systems, and advises resilient system design. A lucid understanding of the goals, constraints, and design trade-offs of deception systems could give leaders and engineers in software development, architecture, and operations a new tactic for building more resilient systems?and for bamboozling attackers.
Synthesis of Refractory Metal Carbides on Carbon Fibers in Molten Salts and Their Electrocatalytic Properties
Authors: Dolmatov V. S. , Kuznetsov S. A.
Published: December 2021

Coatings of TaC and NbC and Mo2C crystals on carbon fibers were obtained by currentless transfer in molten salts. Investigation of electrocatalytic properties of these compositions in the reaction of the hydrogen peroxide decomposition was carried out. It was determined that the hydrogen peroxide decomposition reaction has a zero order for all refractory metal carbides. Using the values of the rate constants at different temperatures the activation energies for the reaction of the hydrogen peroxide decomposition on refractory metal carbides were calculated using the Arrhenius equation. It has been established that coating of NbC on carbon fibers has a higher electrocatalytical properties in comparison with other carbides. The electrocatalytic properties of NbC/C, TaC/C and Mo2C/C composites were studied also by cyclic voltammetry.
Comparison between Accelerated Tests and Natural Exposures for Organic Coating Protective Systems Based on EIS Parameters
Authors: Yong Xingyue , Ji Haotian , Chen Zhenning , Ruan Xin
Published: December 2021

The equivalent relationship between accelerated tests and natural exposures has been extensively studied over the past several years to estimate the service life of a barrier organic coating protective system. Herein, based on the probability density function (PDF) theory, a mathematical expression that describes the limit value of the low-frequency impedance (R

L
) of a barrier organic coating protective system as a function of the elapsed time is proposed in form of Arrhenius formula under certain assumptions, and the degradation coefficient is defined. This expression was consistent with the results of the accelerated tests. The equivalent relationship between accelerated tests and natural exposures, established based on the equivalence principle, was utilized to predict the service life of the coated Al alloy in an ocean atmospheric environment.
Electrochemical Study of Butyl-Pyrene Nitrobenzoate Derivatives Trapped on MWCNT Nanostructured Electrodes
Authors: Barrientos C. , Moscoso R. , Moris S. , Squella J. A.
Published: December 2021

In the scope of our studies tending to find new nanostructured electrodic platforms containing nitroaromatic compounds (NACs) capable of generating in situ electrocatalytic redox couples, we synthesized and electrochemically studied three related 4-(pyren-1-yl)-butyl-substituted nitrobenzoates (2-NBPy, 3-NBPy and 4-NBPy). The design of the compounds is based on a combination of a) an adsorptive tail (-butyl-pyrene) capable of interacting via π–π stacking with the MWCNT nanostructured electrodes and b) nitroaromatic compounds (NACs) capable of electrochemically activating to form a RNHOH/NO redox couple trapped on the nanostructured electrodic platform. Morphological and structural analyses of the nanostructured interfaces were performed by SEM and WAXS/SAXS analysis. All of the NBPy compounds trapped on the nanostructured electrodic platform were susceptible to reduction, generating the corresponding hydroxylamine derivative. The order of ease of reduction for the nitrocompounds is 4-NBPy > 2-NBPy > 3-NBPy. After electrochemical activation, all compounds generated an RNHOH/NO redox mediator couple with the following order of stability of the mediator couple: 2-NBPy > 3-NBPy > 4-NBPy. For the 2-NBPy and 3-NBPy derivatives, excellent stability of the couple was observed, and a decrease in the peak current of 6% was observed after 60 min.
Role of Pr-Vacancies and O-Interstitials on the Activity and Stability of (Pr1−xLnx)2NiO4 (Ln = La, Nd, Pm, Sm, Gd, Tb, Dy, and Ho) towards Oxygen Reduction Reactions: A DFT Study
Authors: Zhang Yanxing , Wang Wei , Wang Yudong , Xu Nengneng , Tian Guang , Karsili Tolga N. V. , Yang Jinbo , Zhou Xiao Dong
Published: December 2021

Praseodymium nickelate, Pr2NiO4 (PNO), is a promising electrode to promote oxygen reduction reaction (ORR) in a solid oxide fuel cell, but it exhibits phase transformation during electrochemical operation. The origin of the simultaneous phase transformation and high electrochemical performance remains obscure. We carried out a systematic density functional theory study to elucidate the mechanism for this conjugated phenomenon. Charge, electronic structure, and normal-mode analysis suggest the presence of peroxide. Our study shows that the formation of peroxide (O2
2−) is attributed to both oxygen interstitials and Pr vacancies. The peroxide species limits the oxygen ion migration due to the additional energy required to break its O–O bond, which leads to a decrease in ORR activity. Subsequently, we investigate the diffusion paths of Pr-ions while comparing them with those of other Ln3+ ions (La, Nd, Pm, Sm, Gd, Tb, Dy, and Ho) in PNO. The formation energies for various Ln3+ cation occupancies are calculated, as well as segregation energies in CeO2(111) surfaces. Finally, criteria for effective Ln3+ dopants are developed. La, Nd, and Pm are proposed as potential substituents in PNO to obtain a stable structure.
Measuring Parasitic Heat Flow in LiFePO4/Graphite Cells Using Isothermal Microcalorimetry
Authors: Logan E. R. , Dahn J. R.
Published: December 2021

Isothermal microcalorimetry has previously been used to probe parasitic reactions in Li-ion batteries, primarily studying Li[NixMnyCo1-x-y]O2 (NMC) positive electrode materials. Here, isothermal microcalorimetry techniques are adopted to study parasitic reactions in LiFePO4 (LFP)/graphite cells. Features in the heat flow from graphite staging transitions were identified, and the associated heat flow was calculated using simple lattice-gas mean-field theory arguments, finding good agreement with experimentally measured values. Parasitic heat flow was measured in LFP/graphite pouch cells with different electrolyte additives. In an electrolyte without additives, a massive parasitic heat flow was measured suggesting a shuttle reaction unique to the LFP/graphite system. In cells containing electrolyte additives, parasitic heat flow agreed well with long-term cycling results, confirming the value of this technique to rank the lifetime of LFP/graphite cells with different electrolyte additives. Finally, comparing cells with and without unwanted water contamination, it was found that the parasitic heat flow was similar or slightly higher in cells where water was intentionally removed before cycling, seemingly contradicting long-term cycling results. It is concluded that the presence of water (at the 500 ppm level) may slightly reduce parasitic reactions, but at the expense of a more resistive SEI layer.
Atomic Scale Insight into Corrosion Inhibition: DFT Study of 2-Mercaptobenzimidazole on Locally De-Passivated Copper Surfaces
Authors: Chiter Fatah , Costa Dominique , Maurice Vincent , Marcus Philippe
Published: December 2021

A key factor for effective inhibition by organic molecules of the initiation of localized corrosion by pitting is their ability to form a protective organic film in locally de-passivated zones exposing the bare metal next to the oxide-covered surface. Herein, based on quantum chemical DFT calculations, we study the chemistry of the interface between 2-mercaptobenzimidazole (MBI) and a copper surface partially covered by a Cu2O passive oxide film. The results show the adaptability of the molecule to adsorb strongly on the different zones, oxide or metal, of a locally de-passivated surface. However, differences in the local adsorption configurations, involving covalent bonding with H-bonding depending on oxide or metal and on conformer, thione or thiolate, lead to the formation of an inhomogeneous organic film. Increasing order of local adsorption strength is oxide walls < metal surface < oxide surface < oxide edges for the thione species, whereas there is no significant difference of local adsorption strength for the thiolate species. Our results suggest that both species of MBI can heal the oxygen and copper low coordinated sites as well as can protect the exposed metal surface, thus enhancing the barrier properties of the passivated surface even when locally defective.
An Improved Cycling Performance of Different Types of Composite Sulfur-Carbon Cathodes with the Use of Lithium Polysulfides Containing Electrolyte Solutions
Authors: Markevich E. , Salitra G. , Yoshida H. , Sawada S. , Aurbach D.
Published: December 2021

We report on stabilization of Li–S cells with different types of composite sulfur cathodes using ethereal LiTFSI/LiNO3/DOL/DME electrolyte solutions containing a-priori 0.1 M Li2S8. These electrolyte solutions enable an improved cycling behavior for Li–S cells compared to Li2S8-free electrolyte solutions, thanks to the presence of LiSx species from the beginning of operation. We show that Li anodes cycled in Li∣S cells with solutions containing Li2S8 possess flatter and more uniform surface, higher dimensions of the surface structures in average and, as a result, a lower surface area. This surface morphology ensures a low rate of parasitic surface reactions of the electrolyte components on the Li anodes’ surface, slower depletion of the electrolyte solution in the cells and stabilization of the cells cycling. Besides, the presence of Li2S8 maintains a better integrity of composite sulfur/carbon/PVdF cathodes, ensuring a better electronic contact between the particles in the composite cathodes. We believe that we outline herein a logical approach for practical Li–S batteries, emphasizing high energy density, cost effectiveness and relatively simple production procedures.
A Network That Balances Accuracy and Efficiency for Lane Detection
Authors: Zhang Ce , Han Yu , Wang Dan , Qiao Wei , Lin Yier
Published: December 2021

In the automatic lane-keeping system (ALKS), the vehicle must stably and accurately detect the boundary of its current lane for precise positioning. At present, the detection accuracy of the lane algorithm based on deep learning has a greater leap than that of the traditional algorithm, and it can achieve better recognition results for corners and occlusion situations. However, mainstream algorithms are difficult to balance between accuracy and efficiency. In response to this situation, we propose a single-step method that directly outputs lane shape model parameters. This method uses MobileNet v2 and spatial CNN (SCNN) to construct a network to quickly extract lane features and learn global context information. Then, through depth polynomial regression, a polynomial representing each lane mark in the image is output. Finally, the proposed method was verified in the TuSimple dataset. Compared with existing algorithms, it achieves a balance between accuracy and efficiency. Experiments show that the recognition accuracy and detection speed of our method in the same environment have reached the level of mainstream algorithms, and an effective balance has been achieved between the two.
Study on Adjuvant Medication for Patients with Mild Cognitive Impairment Based on VR Technology and Health Education
Authors: Liu Huiling , Yang Xiaona , Wang Xinkun , Yang Xiaoyu , Zhang Xusheng , Li Qi
Published: December 2021

In order to improve the efficiency of auxiliary medication for patients with mild cognitive impairment, this paper proposes a method based on VR technology and health education. Sixty elderly patients with COPD and MCI admitted to a hospital from January 2019 to February 2020 were randomly divided into a control group and study group, with 50 cases in each group. On the basis of conventional drug therapy, health education, and respiratory muscle training, patients in the control group received routine lung rehabilitation training, while patients in the study group received lung rehabilitation training using the BioMaster virtual scene interactive rehabilitation training system. Both groups continued training for 12 weeks. Lung function indexes, 6-minute walking distance, COPD assessment test (CAT) score, and Montreal Cognitive Function Assessment Scale (MoCA) score were compared between the 2 groups before training and 4, 8, and 12 weeks after training. The experimental results show that, in the study group, the percentage of FEV1 in the predicted value at 8 weeks after training, the percentage of FEV1 in the predicted value at 12 weeks after training, and FEV1/FVC were higher than those in the control group (

P
<
0.05

). There was no significant difference in 6-minute walking distance, CAT score, and MoCA score between the two groups before training (

P
>
0.05

). Twelve weeks after training, patients in the study group had a longer 6-minute walking distance, a lower CAT score, and a higher MoCA score than those in the control group (

P
<
0.05

). It is proved that the application of virtual reality technology in lung rehabilitation training of elderly COPD patients with MCI is effective, which can effectively improve the lung function, cognitive function, and exercise tolerance of the patients and reduce the symptoms of dyspnea and the efficiency of medication.
Folic Acid Protects Melanocytes from Oxidative Stress via Activation of Nrf2 and Inhibition of HMGB1
Authors: Du Pengran , Zhang Shaolong , Li Shuli , Yang Yuqi , Kang Pan , Chen Jiaxi , Gao Tianwen , Li Chunying , Zhang Qian , Zhang Weigang
Published: December 2021

Vitiligo is a cutaneous depigmentation disease due to loss of epidermal melanocytes. Accumulating evidence has indicated that oxidative stress plays a vital role in vitiligo via directly destructing melanocytes and triggering inflammatory response that ultimately undermines melanocytes. Folic acid (FA), an oxidized form of folate with high bioavailability, exhibits potent antioxidant properties and shows therapeutic potential in multiple oxidative stress‐related diseases. However, whether FA safeguards melanocytes from oxidative damages remains unknown. In this study, we first found that FA relieved melanocytes from H2O2‐induced abnormal growth and apoptosis. Furthermore, FA enhanced the activity of antioxidative enzymes and remarkably reduced intracellular ROS levels in melanocytes. Subsequently, FA effectively activated nuclear factor E2‐related factor 2 (Nrf2) pathway, and Nrf2 knockdown blocked the protective effects of FA on H2O2‐treated melanocytes. Additionally, FA inhibited the production of proinflammatory HMGB1 in melanocytes under oxidative stress. Taken together, our findings support the protective effects of FA on human melanocytes against oxidative injury via the activation of Nrf2 and the inhibition of HMGB1, thus indicating FA as a potential therapeutic agent for the treatment of vitiligo.
Community Detection Based on Density Peak Clustering Model and Multiple Attribute Decision‐Making Strategy TOPSIS
Authors: Cheng Jianjun , Wang Xu , Gong Wenshuang , Li Jun , Chen Nuo , Chen Xiaoyun
Published: December 2021

Community detection is one of the key research directions in complex network studies. We propose a community detection algorithm based on a density peak clustering model and multiple attribute decision‐making strategy, TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution). First, the two‐dimensional dataset, which is transformed from the network by taking the density and distance as the attributes of nodes, is clustered by using the DBSCAN algorithm, and outliers are determined and taken as the key nodes. Then, the initial community frameworks are formed and expanded by adding the most similar node of the community as its new member. In this process, we use TOPSIS to cohesively integrate four kinds of similarities to calculate an index, and use it as a criterion to select the most similar node. Then, we allocate the nonkey nodes that are not covered in the expanded communities. Finally, some communities are merged to obtain a stable partition in two ways. This paper designs some experiments for the algorithm on some real networks and some synthetic networks, and the proposed method is compared with some popular algorithms. The experimental results testify for the effectiveness and show the accuracy of our algorithm.
New Topological Approaches to Generalized Soft Rough Approximations with Medical Applications
Authors: El-Bably Mostafa K. , Ali Muhammad I. , Abo-Tabl El-Sayed A.
Published: December 2021

There are many approaches to deal with vagueness and ambiguity including soft sets and rough sets. Feng et al. initiated the concept of possible hybridization of soft sets and rough sets. They introduced the concept of soft rough sets, in which parameterized subsets of a universe set serve as the building blocks for lower and upper approximations of a subset. Topological notions play a vital role in rough sets and soft rough sets. So, the basic objectives of the current work are as follows: first, we find answers to some very important questions, such as how to determine the probability that a subset of the universe is definable. Some more similar questions are answered in rough sets and their extensions. Secondly, we enhance soft rough sets from topological perspective and introduce topological soft rough sets. We explore some of their properties to improve existing techniques. A comparison has been made with some existing studies to show that accuracy measure of proposed technique shows an improvement. Proposed technique has been employed in decision-making problem for diagnosing heart failure. For this two algorithms have been given.
Circular RNA mmu_circ_0001598 Contributes to IL-1β-Induced Osteoarthritis Progression by Regulating miR-127-3p
Authors: Apizi Xierenguli , Talifujiang Dilibaier , Kasimu Aziguli , Zhang Xue , Yiming Aibibula , Ma Xin , Song Qingshan , Wang Dequan
Published: December 2021

Osteoarthritis (OA), a chronic disease characterized by articular cartilage degeneration, is a leading cause of disability and pain worldwide. Accumulating evidence indicates that circular RNAs (circRNAs) play a critical role in various diseases, but the function of circRNAs in OA remains largely unknown. In this study, we found that circ_0001598 was significantly upregulated in chondrocytes treated with IL-1β and in cartilage tissue from mice with severed anterior cruciate ligament surgery (ACLT) induced OA models. Interference with circ_0001598 in vitro restored IL-1β-induced chondrocyte proliferation and apoptosis. Silencing circ_0001598 significantly alleviated ACLT-induced OA in mice. Mechanistically, knockdown of circ_0001598 affected chondrocyte proliferation, apoptosis, and matrix degradation by regulating miR-127-3p. Taken together, our results demonstrate the fundamental role of circ_0001598 and provide new ideas for the prevention and treatment of osteoarthritis.
Meta-Analysis of the Effectiveness and Safety of Intravenous Thrombolysis in Patients with Acute Cerebral Infarction
Authors: Wu Huili , Gong Weiping , Tang Yanyan , Xu Wuhua , Zhou Ying , Liu Xianjun
Published: December 2021

In this paper, a meta-analysis of the effectiveness and safety of intravenous thrombolysis in patients with acute cerebral infarction was carried out, the original literature inclusion criteria and retrieval strategies were developed, and the collection deadline was about new oral anticoagulants and other methods for the antithrombotic intravenous thrombolytic treatment of patients with acute cerebral infarction for the relevant literature on the safety and effectiveness comparison. First, the quality of the literature is evaluated according to whether the included studies are randomized controlled trials, whether there is randomized concealment, whether blinding is used, and whether they are withdrawn or lost to follow-up, and the RevMan 5.2 software is used for meta-analysis. At the same time, grey literature databases such as dissertations were experimentally searched, and all randomized controlled studies (RCT), nonrandomized controlled studies, case-controlled studies, cohort studies, case series reports, etc. of Wingspan in the treatment of intracranial atherosclerotic stenosis were collected. In the prevention of myocardial infarction in patients with acute cerebral infarction, the difference between the two was not statistically significant (

RR
=
0.82

, 95% CI (0.57, 1.17),

P
=
0.27

). Compared with other methods, it can significantly reduce the all-cause mortality of patients with nonvalvular venous thrombolysis, and the difference is statistically significant (

RR
=
0.90

, 95% CI (0.85, 0.96),

P
=
0.001

). Experimental results show that in terms of safety, the new oral anticoagulant is better than other methods in reducing minor bleeding in patients with acute cerebral infarction, and the difference is statistically significant (

RR
=
0.87

, 95% CI (0.76, 0 99),

P
=
0.03

); the effect is better than other methods in reducing the incidence of serious bleeding events, and the difference is statistically significant (

RR
=
0.79

, 95% CI (0.74, 0.85),

P
<
0.00001

).
Investigation on the Displacement Ductility Coefficient of Reinforced Concrete Columns Strengthened with Textile‐Reinforced Concrete
Authors: Wang Boxue , Yin Shiping , Liu Ming
Published: December 2021

To evaluate the seismic performance of reinforced concrete (RC) columns strengthened with textile‐reinforced concrete (TRC), based on the ABAQUS numerical analysis results of 15 TRC‐strengthened RC columns, the grey correlation theory was used to determine the input variables of the model, and the accuracy of the numerical simulation results is verified by some experiments. Then, according to FEM data, a neural network prediction model was established for the displacement ductility coefficients of TRC‐strengthened columns, and a formula was proposed for calculating the displacement ductility coefficient. The results showed that the BP (backpropagation) neural network model had good rationality and accuracy and that the ductility coefficients of the strengthened columns calculated by the model agreed well with the experimental values. Therefore, the model can be applied for predicting the displacement ductility coefficients of TRC‐strengthened columns and can be used as a reference for engineering design.
Entropy‐Driven Global Best Selection in Particle Swarm Optimization for Many‐Objective Software Package Restructuring
Authors: Prajapati Amarjeet , Parashar Anshu , Sunita  , Mishra Alok
Published: December 2021

Many real‐world optimization problems usually require a large number of conflicting objectives to be optimized simultaneously to obtain solution. It has been observed that these kinds of many‐objective optimization problems (MaOPs) often pose several performance challenges to the traditional multi‐objective optimization algorithms. To address the performance issue caused by the different types of MaOPs, recently, a variety of many‐objective particle swarm optimization (MaOPSO) has been proposed. However, external archive maintenance and selection of leaders for designing the MaOPSO to real‐world MaOPs are still challenging issues. This work presents a MaOPSO based on entropy‐driven global best selection strategy (called EMPSO) to solve the many‐objective software package restructuring (MaOSPR) problem. EMPSO makes use of the entropy and quality indicator for the selection of global best particle. To evaluate the performance of the proposed approach, we applied it over the five MaOSPR problems. We compared it with eight variants of MaOPSO, which are based on eight different global best selection strategies. The results indicate that the proposed EMPSO is competitive with respect to the existing global best selection strategies based on variants of MaOPSO approaches.
The Value of Iterative Reconstruction of Algorithm-Based Coronary Artery Computed Tomography Imaging in the Diagnosis of Old Myocardial Infarction
Authors: Guo Liang , Ren Lu , Shao Yajun , Li Wei , Yu Shangxian
Published: December 2021

The objective of this study was to compare the diagnostic value of computed tomography (CT) based on iterative reconstruction algorithm in old myocardial infarction (OMI), thereby providing theoretical guidance and practical basis for clinical treatment. In this study, in order to provide theoretical guidance and practical basis for the diagnosis and treatment of clinical OMI, 10 patients with OMI were selected and divided into two groups, with 5 patients in each group. In addition, an algebraic iterative reconstruction algorithm is constructed, which starts from the initial estimation value, compares, and corrects the estimation results and the measured results continuously until the error between the two results is less than the predetermined value. The experimental group was optimized by algebraic iterative reconstruction algorithm, and the control group was reconstructed by the hospital original method. The image quality parameters under different iteration times were analyzed and compared to obtain the optimal iteration times. The value of iterative reconstruction algorithm in clinical diagnosis was investigated by analyzing the time of drawing and the accuracy of diagnosis after drawing. Through the analysis and comparison of the image quality parameters of the patients from the experimental group, it was found that the image quality firstly increased with the increase in the number of iterations but decreased with the increase of the number of iterations after a certain number of iterations. The results showed that the optimal number of iterations was 13 times. The drawing time of the experimental group and the control group was 54.27 minutes and 117.87 minutes in turn, so the difference between the two groups was significant (

P
<
0.05

). Besides, there was a statistically marked difference in the accuracy rate of the experimental group (93.33%) and the control group (73.33%) (

P
<
0.05

). In conclusion, the time required for coronary artery CT imaging using algebraic iterative reconstruction algorithm was greatly reduced and the diagnostic accuracy was hugely improved. Therefore, the coronary artery CT imaging based on iterative reconstruction algorithm could make more effective use of medical resources and improve the diagnostic accuracy in the diagnosis of OMI.
Denoising Diffusion MRI via Graph Total Variance in Spatioangular Domain
Authors: Wu Haiyong , Yan Senlin
Published: December 2021

Diffusion MRI (DMRI) plays an essential role in diagnosing brain disorders related to white matter abnormalities. However, it suffers from heavy noise, which restricts its quantitative analysis. The total variance (TV) regularization is an effective noise reduction technique that penalizes noise-induced variances. However, existing TV-based denoising methods only focus on the spatial domain, overlooking that DMRI data lives in a combined spatioangular domain. It eventually results in an unsatisfactory noise reduction effect. To resolve this issue, we propose to remove the noise in DMRI using graph total variance (GTV) in the spatioangular domain. Expressly, we first represent the DMRI data using a graph, which encodes the geometric information of sampling points in the spatioangular domain. We then perform effective noise reduction using the powerful GTV regularization, which penalizes the noise-induced variances on the graph. GTV effectively resolves the limitation in existing methods, which only rely on spatial information for removing the noise. Extensive experiments on synthetic and real DMRI data demonstrate that GTV can remove the noise effectively and outperforms state-of-the-art methods.
Characteristic Parameter Optimization of Wireless Flaw Sensing System Based on Active Interference Suppression Algorithm
Authors: Wu Wenping
Published: December 2021

Based on the active interference suppression algorithm, this study combines the radar working mode and the interference type and realizes the effective detection of the flaw detection signal by successively processing the radar receiving signal and the filtering processing. Firstly, this article builds a simulation platform similar to the actual situation to verify the existing conventional active interference suppression algorithms. Secondly, for the detection of chirp active deception jamming signals entering from the main lobe, a radar active deception jamming detection method based on the characteristic parameter matching of the harmonic components of active deception jamming signals is proposed. After that, the spectral characteristics of the harmonic components of the deception interference signal are analyzed, and the center frequency and the tuning frequency of the real target echo are obtained. Finally, by establishing a frequency modulation parameter library for possible interference harmonic signal components, the acquisition phase of the radar gate by the jammer matched analysis with the preestablished frequency modulation parameter library is implemented to achieve active deception interference detection. This method can effectively detect active deception jamming signals in a complex tunnel environment. The interference suppression algorithms verified by simulation include noise FM interference suppression algorithm based on cancellation and distance false target interference suppression algorithm based on LFM radar summary processing. Through actual measurement data processing and analysis, the effectiveness of the method is verified and the idea of interference suppression is expanded. The construction of the simulation platform is obtained by appropriately modifying the actual parameters, a certain type of suppression jammer, and a certain type of deception jammer used in a certain countermeasure field test at a radar station.
[Retracted] CNN‐GRU‐AM for Shared Bicycles Demand Forecasting
Authors: Peng Yali , Liang Ting , Hao Xiaojiang , Chen Yu , Li Shicheng , Yi Yugen
Published: December 2021

The demand forecast of shared bicycles directly determines the utilization rate of vehicles and projects operation benefits. Accurate prediction based on the existing operating data can reduce unnecessary delivery. Since the use of shared bicycles is susceptible to time dependence and external factors, most of the existing works only consider some of the attributes of shared bicycles, resulting in insufficient modeling and unsatisfactory prediction performance. In order to address the aforementioned limitations, this paper establishes a novelty prediction model based on convolutional recurrent neural network with the attention mechanism named as CNN‐GRU‐AM. There are four parts in the proposed CNN‐GRU‐AM model. First, a convolutional neural network (CNN) with two layers is used to extract local features from the multiple sources data. Second, the gated recurrent unit (GRU) is employed to capture the time‐series relationships of the output data of CNN. Third, the attention mechanism (AM) is introduced to mining the potential relationships of the series features, in which different weights will be assigned to the corresponding features according to their importance. At last, a fully connected layer with three layers is added to learn features and output the prediction results. To evaluate the performance of the proposed method, we conducted massive experiments on two datasets including a real mobile bicycle data and a public shared bicycle data. The experimental results show that the prediction performance of the proposed model is better than other prediction models, indicating the significance of the social benefits.
Attenuation in Proinflammatory Factors and Reduction in Neuronal Cell Apoptosis and Cerebral Vasospasm by Minocycline during Early Phase after Subarachnoid Hemorrhage in the Rat
Authors: Chung Chia-Li , Tsai Hung-Pei , Huang Yu-Hua , Wu Shu-Chuan , Chai Chee-Yin , Kwan Aij-Lie
Published: December 2021

Background. Subarachnoid hemorrhage (SAH) is an important subcategory of stroke due to its high mortality rate as well as severe complications such as neurological deficit. It has been suggested that cerebral inflammation is a major factor in advanced brain injury after SAH. Microglia and astrocytes are known supporting cells in the development and maintenance of inflammation in central nervous system. However, the role of microglia and astrocytes in the development of inflammation and neuronal cell apoptosis during the early phase after SAH has not been thoroughly investigated. Materials and Methods. Sprague‐Dawley rats were divided into 4 groups (n = 6/group): sham group, animals subjected to SAH without treatment, SAH animals pretreated with the microglia inhibitor minocycline (50 mg/kg, ip), and SAH animals pretreated with the astrocyte inhibitor fluorocitrate (50 mg/kg, ip). SAH was induced by injecting autologous blood (1 ml/kg) into the cistern magna on day 0. Pretreatment with minocycline or fluorocitrate was given three days prior to the induction of SAH. Rats were sacrificed 6 hr after SAH, and their cerebral spinal fluids were used to measure protein levels of neuroinflammatory cytokines IL‐1β, IL‐6, and TNF‐α by ELISA. In addition, the cerebral cortex was utilized to determine the levels of caspase‐3 by western blot and to evaluate neuronal cell apoptosis by immunohistochemistry staining and detect microglia and astrocyte by immunofluorescence staining for Iba‐1 and GFAP. In this study, all SAH animals were given an injection of autologous blood and SAH rats treated with minocycline or fluorocitrate received ip injections on day 1, 2, and 3 before inducing SAH. Neurological outcome was assessed by ambulation and placing/stepping reflex responses on day 7. Results. Immunofluorescence staining showed that SAH induced proliferation of microglia and astrocyte and minocycline inhibited the proliferation of both microglia and astrocyte. However, fluorocitrate inhibited only the proliferation of astrocyte. ELISA analysis showed that SAH upregulated TNF‐α and IL‐1β, but not IL‐6 at 6 hr after SAH. Minocycline, but not fluorocitrate, attenuated the upregulation of TNF‐α and IL‐1β. Western blot analysis and immunohistochemistry staining showed that SAH induced neuronal cell apoptosis. Pretreatment with minocycline, but not fluorocitrate, decreased SAH‐induced neuronal death and cerebral vasospasm. Furthermore, significant improvements in neurobehavioral outcome were seen in the minocycline treatment group, but not in animals treated with fluorocitrate. Conclusions. Microglia may play an important role to regulate neuronal cell apoptosis and cerebral vasospasm through inhibiting inflammation at an early phase after SAH in the rat.
Small Ruminant Models for Articular Cartilage Regeneration by Scaffold-Based Tissue Engineering
Authors: Peng Liqing , Zhang Bin , Luo Xujiang , Huang Bo , Zhou Jian , Jiang Shuangpeng , Guo Weimin , Tian Guangzhao , Tian Zhuang , Shen Shi , Li Yangyang , Sui Xiang , Liu Shuyun , Guo Quanyi , Li Haibo
Published: December 2021

Animal models play an important role in preclinical studies, especially in tissue engineering scaffolds for cartilage repair, which require large animal models to verify the safety and effectiveness for clinical use. The small ruminant models are most widely used in this field than other large animals because they are cost-effective, easy to raise, not to mention the fact that the aforementioned animal presents similar anatomical features to that of humans. This review discusses the experimental study of tissue engineering scaffolds for knee articular cartilage regeneration in small ruminant models. Firstly, the selection of these scaffold materials and the preparation process in vitro that have been already used in vivo are briefly reviewed. Moreover, the major factors influencing the rational design and the implementation as well as advantages and limitations of small ruminants are also demonstrated. As regards methodology, this paper applies principles and methods followed by most researchers in the process of experimental design and operation of this kind. By summarizing and comparing different therapeutic concepts, this paper offers suggestions aiming to increase the effectiveness of preclinical research using small ruminant models and improve the process of developing corresponding therapies.
Research on the Coordinated Development of Global Urban Economic Competitiveness: Based on a Sample of 1007 Cities
Authors: Liu Xiaonan , Ni Pengfei , Niu Fangqu , Li Bo , Li Qihang
Published: December 2021

Based on the global urban economic competitiveness data in 2017, this study conducts coupling analyses of the competitiveness indicator system. The comprehensive study on the coupling coordination degree among explanatory indexes of urban economic competitiveness concludes that the city with higher economic competitiveness rankings has a higher degree of coupling coordination (DCC); the city ranked lower in the economic competitiveness has a lower DCC. The cities with higher DCC are mainly those global cities or metropolis known for financial and technological innovations, while cities with bare coupling coordination are mainly in underdeveloped countries in Asia, Africa, and Latin America. Based on the findings, the paper employs a model that combines linear regression and quantile regression to identify the specific driving factors that affect the cities’ competitiveness around the world. Therefore, every city should act according to local conditions, focus on the key drivers of urban development, and address the inadequacies to balance the economic development so as to enhance its competitiveness.
Effect of Temperature and Strain Rate on the Brittleness of China Sandstone
Authors: Yang Xiuyuan , Ge Zhenlong , Sun Qiang , Zhang Weiqiang
Published: December 2021

To quantitatively study the influence of temperature and strain rate on the brittleness of sandstone, the mechanical parameters of sandstone under different temperatures and strain rates are collected from the previous literature, and two empirical equations for calculating rock brittleness are used to quantitatively calculate and evaluate the brittleness of sandstone. The results show that both BI1 and BI2 can characterize the brittleness of sandstone, but the applicable conditions are different. The BI1 method is more accurate in calculating the variation in the sandstone brittleness with a strain rate, while the BI2 method is more accurate in calculating its variation with temperature. The brittleness of sandstone increases with the increase in the strain rate, especially when the strain rate exceeds 100 s-1. Under low-temperature conditions, the strength and brittleness of rocks increase due to the strengthening of ice. Under the condition of high temperature, the thermal damage to sandstone is intensified after 400°C, and the quartz phase changes after 600°C, which leads to the increase in microcrack density and the decrease in brittleness of sandstone. The conditions of low temperature and high strain rate are beneficial to the enhancement of sandstone brittleness.
Evaluation of the Safety of High-Salt Wastewater Treatment in Coal Chemical Industry Based on the AHP Fuzzy Method
Authors: Guo Shijun , Sharma Shubham , Issakhov Alibek , Khalilpoor Nima
Published: December 2021

Aim. Epichlorohydrin (ECH) is a widely used chemical product. The production of glycerol has its irreplaceable advantages. With the development of biodiesel industry, it will become the main trend of ECH production in the future. Methods. A vacuum evaporation device is built to investigate the effect of evaporation on the treatment of this kind of high-salt wastewater, and the feasibility of the thermodynamic equation of the simulation process is verified. Process. An AHR fuzzy mathematics evaluation algorithm is used to compare experimental values with simulated numerical values in brine. Results and Conclusions. In the multieffect evaporation process simulation with glycerin-containing brine, the amount of salt precipitated by unit steam energy is arranged in order from more to less than that of seven-effect parallel flow evaporation, is greater than five-effect parallel flow evaporation, and is larger than three-effect parallel flow evaporation, which shows that the increase of validity number is beneficial to the utilization of heat.
Optimization Algorithm for Point Cloud Quality Enhancement Based on Statistical Filtering
Authors: Zhao Qian , Gao Xiaorong , Li Jinlong , Luo Lin
Published: December 2021

In the process of acquiring point cloud data by a 3D laser scanner, some problems, such as outliers, mixed points, and holes, may be caused in the target point cloud due to the external environment, the discreteness of the laser beam, and the occlusion of objects. In this paper, a point cloud quality optimization and enhancement algorithm is designed. A self‐adaptive octree is established to rasterize the point cloud and calculate the density of each grid, combing with the statistical filtering to remove outliers from the point cloud data. Then, a plane projection method is used for removing the confounding points from the point cloud data. Finally, the point cloud is triangulated and a priority value is set, and then, points are preferentially inserted where the priority value is the largest to repair the holes. Experiments show that while removing outliers and confounding points, the detailed features of the point cloud can be maintained, holes are effectively filled, and the quality of the point cloud is effectively improved.
Study on the Influence of Various Rainfall Types on the Stability of High and Steep Slopes
Authors: Qian Jin , Sun Ding , Li Guodong , Wu Yue
Published: December 2021

Taking the high and steep slope of a ski resort as the background, in order to ensure the structural safety of the slope in the subsequent complex rainfall environment, the calculation principle of unsaturated soil slope stability is summarized, and the parameter interaction analysis is proposed. The numerical simulation method is used to study the influence of various rainfall types on slope stability; combined with a multiparameter combination, the slope stability is analyzed. The results show that different types of rainfall have a significant impact on the safety factor of the slope, the safety factor of the slope under the front rainfall type is the smallest, the minimum value is 1.38, and the front rainfall mostly occurs in the late summer, so it is necessary to avoid construction in the late summer or do a good job of safety monitoring in the late summer. Through setting monitoring points, it is found that the pore water pressure of the three positions from small to large is in the order of slope toe<slope middle<slope top, and the pore water pressure at the slope toe is basically 0 kPa. At this time, the matric suction at the slope toe is the minimum, so the protection should be strengthened. In the combination analysis of the four parameters, the direct effect and coupling effect of C15 are at a small level, which indicates that when the four parameters fluctuate together, the mutual coupling is not the effect of a single parameter, which provides a theoretical reference for the follow-up related research.