bluuebunny/crossref_metadata_2025 huggingface dataset:
Small strain stiffness for granite residual soil: effect of stress ratio
Authors: Zhang Xianwei , Liu Xinyu , Kong Lingwei , Wang Gang , Chen Cheng
Published: December 2021

Most previous studies have focused on the small strain stiffness of sedimentary soil, while little attention has been given to residual soils with different properties. Most studies also neglected the effects of the deviator stress, which is extensively involved in civil engineering. This note considers the effects of the deviator stress on the small strain stiffness of natural granite residual soil as established from resonant column tests performed under various stress ratios. Although increasing the stress ratio results in a greater maximum shear modulus for both natural and remolded residual soils, remolded soil is more sensitive to changes in the stress ratio, which highlights the effects of soil cementation. The data herein offers new insights to understand the stiffness of residual soil and other weathered geomaterials.
Fast flow algorithm prioritizing the most time-consuming source point by using a multi-source evacuation model
Authors: Yang Jianfang , Lin Hao , Guan Junbiao
Published: December 2021

In many public spaces (e.g. colleges and shopping malls), people are frequently distributed discretely, and thus, single-source evacuation, which means there’s only one point of origin, is not always a feasible solution. Hence, this paper discusses a multi-source evacuation model and algorithm, which are intended to evacuate all the people that are trapped within the minimum possible time. This study presents a fast flow algorithm to prioritize the most time-consuming source point under the constraint of route and exit capacity to reduce the evacuation time. This fast flow algorithm overcomes the deficiencies in the existing global optimization fast flow algorithm and capacity constrained route planner (CCRP) algorithm. For the fast flow algorithm, the first step is to determine the optimal solution to single-source evacuation and use the evacuation time of the most time-consuming source and exit gate set as the initial solution. The second step is to determine a multi-source evacuation solution by updating the lower limit of the current evacuation time and the exit gate set continually. The final step is to verify the effectiveness and feasibility of the algorithm through comparison.
Conserved laws and dynamical structure of axions coupled to photons
Authors: Rodríguez-Tzompantzi Omar
Published: December 2021

In this work, we carry out a study of the conserved quantities and dynamical structure of the four-dimensional modified axion electrodynamics theory described by the axion-photon coupling. In the first part of the analysis, we employ the covariant phase space method to construct the conserved currents and to derive the Noether charges associated with the gauge symmetry of the theory. We further derive the improved energy–momentum tensor using the Belinfante–Rosenfeld procedure, which leads us to the expressions for the energy, momentum, and energy flux densities. Thereafter, with the help of Faddeev–Jackiw’s Hamiltonian reduction formalism, we obtain the relevant fundamental brackets structure for the dynamic variables and the functional measure for determining the quantum transition amplitude. We also confirm that modified axion electrodynamics has three physical degrees of freedom per space point. Moreover, using this symplectic framework, we yield the gauge transformations and the structure of the constraints directly from the zero-modes of the corresponding pre-symplectic matrix.
Deeper properties of the nonlinear Phi-four and Gross-Pitaevskii equations arising mathematical physics
Authors: Yan Li , Kumar Ajay , Guirao Juan Luis García , Baskonus Haci Mehmet , Gao Wei
Published: December 2021

In this paper, the rational sine–cosine and rational sinh–cosh methods are applied in extracting some properties of nonlinear Phi-four and Gross–Pitaevskii equations. The singular periodic wave solutions, dark soliton solutions and hyperbolic function solutions are reported. The solitary waves are observed from the traveling waves under the values of the parameters. Modulation instability analysis is also observed in various simulations. We also plot to observe the wave distributions of parameters of stability in 2D and 3D visuals via package program.
Possible manifestations of transitions within the dark matter structure
Authors: Beylin Vitaly , Bezuglov Maxim
Published: December 2021

In this paper, vector hyperquark extension of the Standard Model with multicomponent dark matter scenario is analyzed. Due to the splitting of dark matter candidates masses, transitions between these components accompanied with final state photons radiation are possible. For these processes, we calculate cross-sections and expected gamma-ray fluxes from regions with an increased density of dark matter. Effect of possible luminescence induced by complex structure of dark matter sector is discussed.
COMPARISON OF PSYCHOLOGICAL DIMENSIONS IN RURAL POPULATION WITH VARIOUS JOINT DEGENERATIVE ARTHRITIS
Authors: Kumar Sunil , Kumar Suraj , Yadav Ramakant , Potturi Gowrishankar , Prerna
Published: December 2021

Background and Purpose: Osteoarthritis patients often suffer from anxiety which can affect the disease prognosis. This study is aimed at assessing the various psychological dimensions in different joint arthritic subjects of the rural population and finding the most common joint arthritis that can lead to anxiety in the rural population. Materials & methods: A total of 252 subjects satisfied the inclusion criteria and were recruited for the study after written informed consent and were asked to fill in the GPS online through Google forms. The “feelings” subscale assesses the patient’s psychological stress due to pain and disease. The psychological dimensions of sub-section feelings of GPS were analyzed by one-way ANOVA to assess whether there is a difference on average in the scores among the three groups at a p < 0.05 significant level. Tukey HSD was used for post hoc pairwise comparisons. Results: One-way ANOVA results showed that there was no statistically significant difference between the groups for fear, level of anxiety, depression, stress, and fatigue. Tukey HSD post hoc comparison revealed that the results were statistically significant for fear (Q = 3.35, p = 0.04) and fatigue levels (Q = 3.69, p = 0.02). The Tukey HSD post hoc comparison for levels of anxiety, depression, and stress was not statistically significant. Conclusion: From this study, we conclude that anxiety, fatigue, and fear are highly prevalent in hip osteoarthritis. Anxiety is associated with all joint osteoarthritis and can result in poor quality of living. We recommend physicians to emphasize psychological dimensions and address them at an early stage in order to achieve a better prognosis in degenerative joint diseases.
Residual Stress Around the Fatigue Crack Front in a Rectangular Sample Cut from CT Specimen
Authors: Materna Aleš , Lauschmann Hynek , Ondráček Jan
Published: December 2021

In this paper, an elastic–plastic finite element model was built to simulate the stress field around a fatigue crack in a standard CT specimen before and after splitting to obtain a rectangular specimen for further investigation. Plane stress and plane strain, as well as 3D simulations, were performed and compared. The simulations consist of two steps: (i) The standard CT-specimen undergoes cyclic loading until the fatigue crack tip achieves the middle of the specimen, and (ii) A rectangular sample with the crack to one half of its width was cut from the CT-specimen. A parametric plane strain study was carried out to determine the location of the cutting plane relative to the edge of the plastic zone, where the impact on the residual stress due to stress relief after cutting is negligible. It was also found that in the peripheral parts of the front close to the free surface, the stress is strongly influenced by the curvature of the crack front.
Radio Antenna Design for Sky-Averaged 21cm Cosmology Experiments: The REACH Case
Authors: Cumner J. , de Lera Acedo E. , de Villiers D. I. L. , Anstey D. , Kolitsidas C. I. , Gurdon B. , Fagnoni N. , Alexander P. , Bernardi G. , Bevins H. T. J. , Carey S. , Cavillot J. , Chiello R. , Craeye C. , Croukamp W. , Ely J. A. , Fialkov A. , Gessey-Jones T. , Gueuning Q. , Handley W. , Hills R. , Josaitis A. T. , Kulkarni G. , Magro A. , Maiolino R. , Meerburg P. D. , Mittal S. , Pritchard J. R. , Puchwein E. , Razavi-Ghods N. , Roque I. L. V. , Saxena A. , Scheutwinkel K. H. , Shen E. , Sims P. H. , Smirnov O. , Spinelli M. , Zarb-Adami K.
Published: December 2021

Following the reported detection of an absorption profile associated with the 21[Formula: see text]cm sky-averaged signal from the Cosmic Dawn by the EDGES experiment in 2018, a number of experiments have been set up to verify this result. This paper discusses the design process used for global 21[Formula: see text]cm experiments, focusing specifically on the Radio Experiment for the Analysis of Cosmic Hydrogen (REACH). This experiment will seek to understand and compensate for systematic errors present using detailed modeling and characterization of the instrumentation. Detailed quantitative figures of merit and numerical modeling are used to assist the design process of the REACH dipole antenna (one of the two antenna designs for REACH Phase I). This design process produced a 2.5:1 frequency bandwidth dipole. The aim of this design was to balance spectral smoothness and low impedance reflections with the ability to describe and understand the antenna response to the sky signal to inform the critically important calibration during observation and data analysis.
TWIST-GAN: Towards Wavelet Transform and Transferred GAN for Spatio-Temporal Single Image Super Resolution
Authors: Dharejo Fayaz Ali , Deeba Farah , Zhou Yuanchun , Das Bhagwan , Jatoi Munsif Ali , Zawish Muhammad , Du Yi , Wang Xuezhi
Published: December 2021

Single Image Super-resolution (SISR)
produces high-resolution images with fine spatial resolutions from a remotely sensed image with low spatial resolution. Recently, deep learning and
generative adversarial networks (GANs)
have made breakthroughs for the challenging task of
single image super-resolution (SISR)
. However, the generated image still suffers from undesirable artifacts such as the absence of texture-feature representation and high-frequency information. We propose a frequency domain-based spatio-temporal remote sensing single image super-resolution technique to reconstruct the HR image combined with generative adversarial networks (GANs) on various frequency bands (TWIST-GAN). We have introduced a new method incorporating
Wavelet Transform (WT)
characteristics and transferred generative adversarial network. The LR image has been split into various frequency bands by using the WT, whereas the transfer generative adversarial network predicts high-frequency components via a proposed architecture. Finally, the inverse transfer of wavelets produces a reconstructed image with super-resolution. The model is first trained on an external DIV2 K dataset and validated with the UC Merced Landsat remote sensing dataset and Set14 with each image size of 256 × 256. Following that, transferred GANs are used to process spatio-temporal remote sensing images in order to minimize computation cost differences and improve texture information. The findings are compared qualitatively and qualitatively with the current state-of-art approaches. In addition, we saved about 43% of the GPU memory during training and accelerated the execution of our simplified version by eliminating batch normalization layers.
OpenQL: A Portable Quantum Programming Framework for Quantum Accelerators
Authors: Khammassi N. , Ashraf I. , Someren J. V. , Nane R. , Krol A. M. , Rol M. A. , Lao L. , Bertels K. , Almudever C. G.
Published: December 2021

With the potential of quantum algorithms to solve intractable classical problems, quantum computing is rapidly evolving, and more algorithms are being developed and optimized. Expressing these quantum algorithms using a high-level language and making them executable on a quantum processor while abstracting away hardware details is a challenging task. First, a quantum programming language should provide an intuitive programming interface to describe those algorithms. Then a compiler has to transform the program into a quantum circuit, optimize it, and map it to the target quantum processor respecting the hardware constraints such as the supported quantum operations, the qubit connectivity, and the control electronics limitations. In this article, we propose a quantum programming framework named OpenQL, which includes a high-level quantum programming language and its associated quantum compiler. We present the programming interface of OpenQL, we describe the different layers of the compiler and how we can provide portability over different qubit technologies. Our experiments show that OpenQL allows the execution of the same high-level algorithm on two different qubit technologies, namely superconducting qubits and Si-Spin qubits. Besides the executable code, OpenQL also produces an intermediate quantum assembly code, which is technology independent and can be simulated using the QX simulator.
A Comprehensive Survey of Grammatical Error Correction
Authors: Wang Yu , Wang Yuelin , Dang Kai , Liu Jie , Liu Zhuo
Published: December 2021

Grammatical error correction (GEC) is an important application aspect of natural language processing techniques, and GEC system is a kind of very important intelligent system that has long been explored both in academic and industrial communities. The past decade has witnessed significant progress achieved in GEC for the sake of increasing popularity of machine learning and deep learning. However, there is not a survey that untangles the large amount of research works and progress in this field. We present the first survey in GEC for a comprehensive retrospective of the literature in this area. We first give the definition of GEC task and introduce the public datasets and data annotation schema. After that, we discuss six kinds of basic approaches, six commonly applied performance boosting techniques for GEC systems, and three data augmentation methods. Since GEC is typically viewed as a sister task of Machine Translation (MT), we put more emphasis on the statistical machine translation (SMT)-based approaches and neural machine translation (NMT)-based approaches for the sake of their importance. Similarly, some performance-boosting techniques are adapted from MT and are successfully combined with GEC systems for enhancement on the final performance. More importantly, after the introduction of the evaluation in GEC, we make an in-depth analysis based on empirical results in aspects of GEC approaches and GEC systems for a clearer pattern of progress in GEC, where error type analysis and system recapitulation are clearly presented. Finally, we discuss five prospective directions for future GEC researches.
Automatic Parotid Gland Segmentation in MVCT Using Deep Convolutional Neural Networks
Authors: Zhang Junqian , Sun Yingming , Liao Hongen , Zhu Jian , Zhang Yuan
Published: December 2021

Radiation-induced xerostomia, as a major problem in radiation treatment of the head and neck cancer, is mainly due to the overdose irradiation injury to the parotid glands. Helical Tomotherapy-based megavoltage computed tomography (MVCT) imaging during the Tomotherapy treatment can be applied to monitor the successive variations in the parotid glands. While manual segmentation is time consuming, laborious, and subjective, automatic segmentation is quite challenging due to the complicated anatomical environment of head and neck as well as noises in MVCT images. In this article, we propose a localization-refinement scheme to segment the parotid gland in MVCT. After data pre-processing we use mask region convolutional neural network (Mask R-CNN) in the localization stage after data pre-processing, and design a modified U-Net in the following fine segmentation stage. To the best of our knowledge, this study is a pioneering work of deep learning on MVCT segmentation. Comprehensive experiments based on different data distribution of head and neck MVCTs and different segmentation models have demonstrated the superiority of our approach in terms of accuracy, effectiveness, flexibility, and practicability. Our method can be adopted as a powerful tool for radiation-induced injury studies, where accurate organ segmentation is crucial.
Single-Entity Electrocatalysis at Electrode Ensembles Prepared by Template Synthesis
Authors: Siepser Natasha P. , Choi Myung-Hoon , Alden Sasha E. , Baker Lane A.
Published: December 2021

Nanoelectrode ensembles (NEEs), prepared by Au template synthesis, are presented as a proof-of-concept sample platform to study individual electrodeposited materials by scanning electrochemical cell microscopy (SECCM). With this platform, the non-conductive membrane support does not contribute to the electrocatalytic activity recorded at each electrode. Use of low-density template membranes results in electrodes that are isolated because initial membrane pores are typically separated by significant (microscale) distances. Electrodeposition of catalytic nanoparticles onto the electrodes of the array and observation of electrocatalytic activity are demonstrated to be suitable for correlative SECCM voltammetric mapping and electron microscopy. Suitability of NEEs for studies of surface Au oxidation, hydrazine oxidation, and hydrogen evolution (hydrogen evolution reaction, HER), and at Pt particles on NEEs (Pt-NEEs) for HER is demonstrated.
Optimization of the Interface Between Catalyst Layer and Proton Exchange Membrane via Rolled Technique
Authors: Guan Shumeng , Zhou Fen , Du Shaojie , Pan Mu
Published: December 2021

Optimization of the interface between the catalyst layer (CL) and the proton exchange membrane (PEM) plays an important role in performance enhancement in proton exchange membrane fuel cells (PEMFCs). Here, a rolled technique was used to optimize the PEM∣CL interface to obtain a smooth CL surface with decreased roughness from 0.347 to 0.266 μm due to the reduction of protrusions after the rolled process. Advantages of the optimized PEM∣CL interface formed after decal transfer method were carefully evaluated. First, the internal resistance of the rolled CL is significantly reduced from 61.5 to 47.5 mΩ cm2@2000 mA cm−2, which is ascribed to the higher contact area between CL and PEM. Meanwhile, owning to the alleviation of liquid water accumulation at the interface, the oxygen transport resistance at no back pressure of CL dropped from 0.21 to 0.15 s cm−1. The relieved ohm polarization and mass transfer polarization promote a 28.5% increase of performance. Rolled technique with proper calendrer roll space could result in an optimized interface with well-maintained internal structural integrity of CL. However, a lower calendrer roll gap will damage the structure of CL and have a negative effect on the interface optimization.
Design of Hybrid Schottky-Ohmic Gate in Normally-Off p-GaN Gate AlGaN/GaN HEMTs
Authors: Tsai Wen-Shiuan , Qin Zhen-Wei , Hsin Yue-Ming
Published: December 2021

This study proposes three hybrid Schottky-ohmic gate structures for normally-off p-GaN gate AlGaN/GaN HEMTs. One has a Schottky-gate cover on the ohmic-gate and has part of the area contact to the p-GaN surface at the left and right sides of ohmic-gate (Structure A). The two others only have the Schottky-gate contact to the p-GaN surface at the left side (Structure B) or right side (Structure C) of the ohmic-gate. Different gate metal designs change the hole injection from p-GaN to GaN channel and show various gate leakages. The optimized contact length of Schottky-gate can suppress on-state gate leakage current over two orders of magnitude compared to conventional ohmic p-GaN gate HEMT. The improved on-state maximum drain current is over 60 mA mm−1 compared to Schottky p-GaN gate HEMT. Optimal performance in Structure B with Schottky-gate contact length ranges from 0.8 to 1.8 μm in a 2 μm gate geometry.
Effect of Yttrium Oxide in Hydroxyapatite Biocomposite Materials: Electrical and Antimicrobial Evaluation
Authors: El-Bassyouni Gehan T. , Turky Gamal M. , Kenawy Sayed H. , Abd El-Aty Abeer A. , Hamzawy Esmat M.A.
Published: December 2021

Synthesis and characterization of biocomposite materials of hydroxyapatite (HA) and yttrium oxide (Y2O3) were investigated. HA nanoparticles powder was obtained from mussel shells via a wet chemical precipitation routine. HA powder was doped with 1 and 2 wt% of Y2O3. For microstructural examination, X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), and scanning electron microscopy (SEM) coupled with energy dispersive X-rays (EDX) were used. In addition, the dielectric and electrical properties and antimicrobial activities were investigated. XRD patterns reveal the crystallization of the oxyapatite. The peak intensities of pristine HA are inferior compared to the yttrium containing HA composites, thus suggesting that the addition of yttrium promotes the crystallization of HA due to the variance in their ionic radii. FT-IR shows a variation in the phosphate wavenumber, indicating the integration of yttrium into the HA matrix. SEM reveals nanorod- or worm-like crystals arose in clusters. With increasing Y2O3, from 1 to 2 wt%, the DC conductivity reduces from 16 to 9.3 nS/cm, which confirms that high amounts of Y3+ substitute Ca2+ in the HA matrix. In the high-frequency range, the AC conductivity linearly increases with increasing frequency following the universal power law. Further, antimicrobial activity results showed that the addition of yttrium in HA improves the antimicrobial effects against pathogenic bacteria and fungi. Additional research is needed to investigate the doping concentration of yttrium ions, and an anticipated property could be comprehended for several forthcoming biomedical applications.
The Potential Mechanism of Exercise Combined with Natural Extracts to Prevent and Treat Postmenopausal Osteoporosis
Authors: Zhou Tongxi , Gai Zhuo , Gao Xing , Li Li
Published: December 2021

Postmenopausal osteoporosis (PMOP) is a systemic chronic bone metabolic disease caused by the imbalance between bone formation and bone resorption mediated by estrogen deficiency. Both exercise and natural extracts are safe and effective means to prevent and control PMOP. The additive effect of exercise synergy extract against PMOP may be no less than that of traditional medicine. However, the mechanism of action of this method has not been clarified in detail. A large number of studies have shown that the pathogenesis of PMOP mainly involves the OPG-RANKL-RANK system, inflammation, and oxidative stress. Based on the abovementioned approaches, the present study reviews the anti-PMOP effects and mechanisms of exercise and natural extracts. Finally, it aims to explore the possibility of the target of the two combined anti-PMOP through this approach, thereby providing a new perspective for joint intervention research and providing a new direction for the treatment strategy of PMOP.
A Solution of Subgrade Modulus for Response Displacement Method of Circular Underground Structures
Authors: Wang Wei , Feng Kun , Wang Yunchao , He Chuan , Zhu Guojin , Ning Yu , Zhao Lixiang
Published: December 2021

In the seismic analysis and design of the underground structure, the response displacement method, as a pseudostatic method, has been widely adopted for its solid theoretical background, clear physical concept, and ease of implementation. The subgrade modulus is an essential parameter to the response displacement method, and a few approaches are available to determine its value. However, the existing methods neglect the interaction between the radial and tangential subgrade modulus and the influence of actual ground deformation, resulting in an inaccurate estimation. This study presents a solution to overcome these defects for the response displacement method adopted in the transverse seismic analysis of the shield tunnel with a circular cross section. First, the analytical solutions of subgrade modulus for ground deformation modes described by the Fourier series are derived based on the theory of elasticity. The ratio of the radial displacement to tangential displacement is introduced to create a link between the radial and tangential subgrade modulus. Based on the solutions of subgrade modulus for different ground deformation modes, the displacement fitting method is proposed to derive the subgrade modulus corresponding to the actual ground deformation. With this method, the subgrade modulus would adjust according to the ground displacement. Finally, a case study is conducted to illustrate the validity of the displacement fitting method.
Assignments of the
X

4140

,
X

4500

,
X

4630

, and
X

4685

Based on the QCD Sum Rules
Authors: Wang Zhi-Gang
Published: December 2021

In this article, we take into account our previous calculations based on the QCD sum rules, and tentatively assign the

X

4630

as the

D

s

∗

D
¯

s
1

−

D

s
1

D
¯

s

∗

tetraquark molecular state or

c
s

P

c
¯

s
¯

A

+

c
s

A

c
¯

s
¯

P

tetraquark state with the

J

P
C

=

1

−

+

, and assign the

X

3915

and

X

4500

as the 1S and 2S

c
s

A

c
¯

s
¯

A

tetraquark states, respectively, with the

J

P
C

=

0

+

+

. Then, we extend our previous works to investigate the LHCb’s new tetraquark candidate

X

4685

as the first radial excited state of the

X

4140

with the QCD sum rules and obtain the mass

M

X

=
4.70
±
0.12
 
GeV

, which is in very good agreement with the experimental value

4684
±

7

−
16

+
13

 
MeV

. Furthermore, we investigate the two-meson scattering state contributions in details and observe that the two-meson scattering states alone cannot saturate the QCD sum rules, the contributions of the tetraquark states play an unsubstitutable role, and we can saturate the QCD sum rules with or without the two-meson scattering states.
Empirical Analysis on Promoting Industrial Transformation and Upgrading in Zhejiang Province by Enhancing Intellectual Property Protection
Authors: Ye Junjun , Wang Jijian , Zhu Zhiwei
Published: December 2021

This paper aims to reveal the relationship between intellectual property protection (IPP) and industrial transformation and upgrading (T&U) in southeastern China’s Zhejiang Province. Taking five representative industries as objects, the shift-share analysis was adopted to measure the T&U level of each industry, with the total output in 2004–2019 as the basis. The results show that wholesale and retail, lodging and catering, finance, and real estate are the four advantageous industries. Further, the authors calculated Pearson’s correlation coefficients between IPP intensity and the T&U levels of the four industries. By the coefficients, the four industries can be ranked in descending order as lodging and catering (0.8743), real estate (0.6908), wholesale and retail (0.5891), and finance (0.5468). In addition, the IPP was found to be positively correlated with total manufacturing output (0.8027). Hence, the IPP can significantly promote the development of these five industries.
Radar High-Resolution Range Profile Target Recognition by the Dual Parallel Sequence Network Model
Authors: Wu Jizhou , Zhang Hongmin , Gao Xuanhao
Published: December 2021

Using traditional neural network algorithms to adapt to high-resolution range profile (HRRP) target recognition is a complex problem in the current radar target recognition field. Under the premise of in-depth analysis of the long short-term memory (LSTM) network structure and algorithm, this study uses an attention model to extract data from the sequence. We build a dual parallel sequence network model for rapid classification and recognition and to effectively improve the initial LSTM network structure while reducing network layers. Through demonstration by designing control experiments, the target recognition performance of HRRP is demonstrated. The experimental results show that the bidirectional long short-term memory (BiLSTM) algorithm has obvious advantages over the template matching method and initial LSTM networks. The improved BiLSTM algorithm proposed in this study has significantly improved the radar HRRP target recognition accuracy, which enhanced the effectiveness of the improved algorithm.
Lymphocyte and Platelet Counts, as well as Interleukin-6 Levels, Predict Mortality of Coronavirus Disease 2019 (COVID-19): A Systematic Review and Meta-Analysis
Authors: Chen Huiwei , Yang Guang , Long Yunzhu , Li Chaoqian
Published: December 2021

Objective. To systematically evaluate the value of lymphocytes, platelets, and interleukin-6 in predicting the mortality of patients with coronavirus disease 2019 (COVID-19) and to provide medical evidence for the long-term prognosis of patients with COVID-19. Methods. The latest studies published until July 1, 2021, were retrieved from databases including PubMed, Embase, and Cochrane Library to analyze the ability of lymphocyte and platelet counts as well as interleukin-6 levels to predict mortality in patients with COVID-19. Two reviewers independently screened the literature and extracted data, then evaluated the risk of bias of included studies using the Newcastle–Ottawa Scale (NOS), and used Stata 15.0 software for meta-analysis. Results. A total of nine studies were included, involving 4340 patients. There were 1330 patients in the death group and 3010 patients in the survival group. Meta-analysis showed that, compared with the survival group, lymphocyte counts in the death group were significantly lower (SMD = −0.64, 95% CI: −0.86–−0.43,

p
<
0.01

), platelet counts were significantly lower (SMD = −0.47, 95% CI: −0.67–−0.27,

p
<
0.01

), and interleukin-6 levels were significantly higher (SMD = 1.07, 95% CI: 0.62–1.53,

p
<
0.01

). Conclusion. Lymphocyte and platelet counts, as well as interleukin-6 levels, can help predict the mortality of patients with COVID-19. Due to the limitation of the number and quality of the included studies, these conclusions need to be validated by additional high-quality studies.
Existence and Uniqueness of Mild Solution for Fractional-Order Controlled Fuzzy Evolution Equation
Authors: Iqbal Naveed , Niazi Azmat Ullah Khan , Shafqat Ramsha , Zaland Shamsullah
Published: December 2021

In this article, we investigated the existence and uniqueness of mild solutions for fractional-order controlled fuzzy evolution equations with Caputo derivatives of the controlled fuzzy nonlinear evolution equation of the form

 

0

c

D

I

γ

x

I

=
α
x

I

+
P

I
,
x

I

+
A

I

W

I

,
I
∈

0
,
T

,
x

I

0

=

x

0

, in which

γ
∈

0
,
1

,

E

1

is the fuzzy metric space and

I
=

0
,
T

is a real line interval. With the help of few conditions on functions

P
:
I
×

E

1

×

E

1

⟶

E

1

,

W

I

is control and it belongs to

E

1

,

A
∈
F

I
,
L

E

1

, and

α

stands for the highly continuous fuzzy differential equation generator. Finally, a few instances of fuzzy fractional differential equations are shown.
Transcriptional and Epigenetic Bioinformatic Analysis of Claudin-9 Regulation in Gastric Cancer
Authors: Hernández-Nava Elizabeth , Montaño Luis F. , Rendón-Huerta Erika P.
Published: December 2021

Gastric cancer is a heterogeneous disease that represents 5% to 10% of all new cancer cases worldwide. Advances in histological diagnosis and the discovery of new genes have admitted new genomic classifications. Nevertheless, the bioinformatic analysis of gastric cancer databases has favored the detection of specific differentially expressed genes with biological significance. Claudins, a family of proteins involved in tight junction physiology, have emerged as the key regulators of cellular processes, such as growth, proliferation, and migration, associated with cancer progression. The expression of Claudin-9 in the gastric cancer tissue has been linked to poor prognosis, however, its transcriptional and epigenetic regulations demand a more comprehensive analysis. Using the neural network promoter prediction, TransFact, Uniprot-KB, Expasy-SOPMA, protein data bank, proteomics DB, Interpro, BioGRID, String, and the FASTA protein sequence databases and software, we found the following: (1) the promoter sequence has an unconventional structure, including different transcriptional regulation elements distributed throughout it, (2) GATA 4, GATA 6, and KLF5 are the key regulators of Claudin-9 expression, (3) Oct1, NF-κB, AP-1, c-Ets-1, and HNF-3β have the higher binding affinity to the CLDN9 promoter, (4) Claudin-9 interacts with cell differentiation and development proteins, (5) CLDN9 is highly methylated, and (6) Claudin-9 expression is associated with poor survival. In conclusion, Claudin-9 is a protein that should be considered a diagnostic marker as its gene promoter region binds to the transcription factors associated with the deregulation of cell control, enhanced cell proliferation, and metastasis.
Iteratively Coupled Flow and Geomechanics in Fractured Poroelastic Reservoirs: A Phase Field Fracture Model
Authors: Zhao Jinzhou , Yin Qing , McLennan John , Li Yongming , Peng Yu , Chen Xiyu , Chang Cheng , Xie Weiyang , Zhu Zhongyi
Published: December 2021

Fluid-solid coupling in fractured reservoirs plays a critical role for optimizing and managing in energy and geophysical engineering. Computational difficulties associated with sharp fracture models motivate phase field fracture modeling. However, for geomechanical problems, the fully coupled hydromechanical modeling with the phase field framework is still under development. In this work, we propose a fluid-solid fully coupled model, in which discrete fractures are regularized by the phase field. Specifically, this model takes into account the complex coupled interaction of Darcy-Biot-type fluid flow in poroelastic media, Reynolds lubrication governing flow inside fractures, mass exchange between fractures and matrix, and the subsequent geomechanical response of the solid. An iterative coupling method is developed to solve this multifield problem efficiently. We present numerical studies that demonstrate the performance of our model.
MiR-429 Inhibits the Angiogenesis of Human Brain Microvascular Endothelial Cells through SNAI2-Mediated GSK-3β/β-Catenin Pathway
Authors: Sun Yameng , Ding Shenghao , Fan Yiling , Shen Fei , Dong Qing , Zhao Bing , Pan Yaohua , Wan Jieqing
Published: December 2021

MicroRNA (miRNA) dysfunction has been confirmed as a key event of ischemic stroke appearance. This study is aimed at revealing the role of miR-429 in the angiogenesis of HBMECs. The HBMECs were treated with oxygen and glucose deprivation (OGD) to establish the ischemic cell model. The qRT-PCR was used to measure the expression levels of the miR-429 in the serums of the patients or cells, and CCK-8, wound healing assay, and tube formation assay were used to observe the effects of miR-429 on the phenotype of HBMECs. Moreover, the Targetscan, dual-luciferase reporter assay, and Western blot were used to reveal the downstream target and regulation mechanism of miR-429 in OGD-induced HBMECs. The results showed that miR-429 was significantly upregulated in the serums of the patients, and overexpressed miR-429 could extremely inhibit the viability, migration, and tube formation of OGD-induced HBMECs. Furthermore, it was found that SNAI2 was a downstream factor of miR-429, and SNAI2 could rescue the effects of miR-429 on OGD-induced HBMECs. Besides, the Western blot showed that miR-429 could affect the activity of GSK-3β/β-catenin pathway via inhibiting the expression of SNAI2. In conclusion, this study suggests that miR-429 inhibits the angiogenesis of HBMECs through SNAI2-mediated GSK-3β/β-catenin pathway.
Detection and Genotyping of Francisella tularensis in Animal Hosts and Vectors from Six Different Natural Landscape Areas, Gansu Province, China
Authors: Zhang Fang , Wang Xiaoheng , Yu Guowei , Gao Jiangli , Niu Hongmei , Zhao Jin
Published: December 2021

Objective. Tularemia, also known as hare fever, is caused by the bacterium Francisella tularensis (F. tularensis) transmitted through diseased wild animals, blood sucking insects, or contaminated water or food, which is distributed worldwide. The purpose of this study was to investigate F. tularensis infection in animal hosts and vectors from six different natural landscape areas in Gansu Province and to identify the genotypes of the detected F. tularensis. Methods. Rodents were captured by snap traps, and ticks were collected by dragging a cloth over the vegetation or from domestic animals. After species identification, DNA was isolated from the captured animals and detected by nested PCR assays targeting the F. tularensis fopA gene. The positive samples were further amplified to discriminate the species, and another two short-sequence tandem repeat regions (SSTR) were amplified to identify their genotypes. All positive fragments were sequenced and analyzed by ClustalX (5.0) and DNAClub software. Results. A total of 407 rodents of 12 species were captured, among which six rodent species were positive for F. tularensis, with an overall prevalence of 3.93%. The geographical difference in infection rate was statistically significant. At the SSTR9 locus, there were 7 genotypes among positive rodent samples. A total of 1864 ticks were tested for evidence of tularemia by nested PCR assays, 69 of which were positive, with an average positive rate of 3.70% for F. tularensis in ticks. The positive rates were significantly different among different regions. Seven genotypes were identified at the SSTR9 locus, one of which seemed dominant in positive tick samples. All positive samples had the same genotype at the SSTR16 locus. Conclusion. There is natural infection of F. tularensis among animal vectors and hosts in Gansu Province, with diverse genotypes.
Colistin-Induced Acute Kidney Injury and the Effect on Survival in Patients with Multidrug-Resistant Gram-Negative Infections: Significance of Drug Doses Adjusted to Ideal Body Weight
Authors: Arrayasillapatorn Nittha , Promsen Palinee , Kritmetapak Kittrawee , Anunnatsiri Siriluck , Chotmongkol Wijittra , Anutrakulchai Sirirat
Published: December 2021

Background. Colistin is a lifesaving treatment for multidrug-resistant Gram-negative bacterial (MDR-GNB) infections along with its well-known nephrotoxicity. The controversy of colistin-induced acute kidney injury (AKI) on mortality is noted. This study aimed to determine the risk factors and impact of AKI on the survival and significance of colistin dosage. Methods. A retrospective cohort study was performed in adult patients who received intravenous colistin for MDR-GNB treatment between June 2015 and June 2017. Factors influencing colistin-induced AKI and survival were evaluated by Cox regression analysis. Cut-off levels of the colistin dose per ideal body weight (IBW) that significantly affected clinical outcomes were assessed with linearity trends and receiver operating characteristic analyses. Results. AKI occurred in 68.5% of 412 enrolled patients with an incidence rate of 10.6 per 100 patients-days and a median time was 6 (3–13) days. Stages I–III of AKI were 38.3, 24.5, and 37.2%. Factors associated with colistin-induced AKI were advanced age, high serum bilirubin, AKI presented before colistin administration, increased daily colistin doses per IBW, and concomitant use of nephrotoxic drugs. Colistin-induced AKI was related to mortality (HR 1.74, 95% CI 1.06–2.86,

p
=
0.028

). In the non-AKI before colistin usage subgroup, the total dose and total dose/IBW were >1,500–2,000 mg and 30–35 mg/kg to benefit mortality reduction but were <2,500–3,000 mg and 45–50 mg/kg for risk reduction of AKI. A daily colistin dose/IBW >4.5 mg/kg/day also increased the risk of AKI. In the AKI developed before colistin subgroup, the cut-off values of total colistin dose >1250–1350 mg and total dose/IBW >23.5–24 mg/kg demonstrated significant risks of AKI. Conclusion. The incidence of AKI after colistin administration was high and impacted mortality. Prevention and early correction of these related factors are mandatory. Careful use of colistin was also both beneficial in mortality and AKI reductions.
Repetitive Transient Extraction Using the Optimized SES Entropy Wavelet for Fault Diagnosis of Rotating Machinery
Authors: Wang Tingzhong , Zhu Lingli , Fu Miaomiao , Zhu Tingting , He Ping
Published: December 2021

Repetitive transients are usually generated in the monitoring data when a fault occurs on the machinery. As a result, many methods such as kurtogram and optimized Morlet wavelet and kurtosis method are proposed to extract the repetitive transients for fault diagnosis. However, one shortcoming of these methods is that they are constructed based on the index of kurtosis and are sensitive to the impulsive noise, leading to failure in accurately diagnosing the fault of the machinery operating under harsh environment. To address this issue, an optimized SES entropy wavelet method is proposed. In the proposed method, the optimized parameters including bandwidth and central frequency of Morlet wavelets are selected. Then, based on the wavelet coefficients decomposed using the optimized Morlet wavelet, the SES entropy is calculated to select the scales of wavelet coefficients. Finally, the repetitive transients are reconstructed based on the denoising wavelet coefficients of the selected scales. One simulation case and vibration data collected from the experimental setup are used to verify the effectiveness of the proposed method. The simulated and experimental analyses showed that the signal‐to‐noise ratio (SNR) of the proposed method has the largest value. Specifically, the SNR in the experimental analysis of the proposed method is 0.6, while that of the other three methods is 0.043, 0.0065, and 0.0045, respectively. Therefore, the result shows that the proposed method is superior to the traditional methods for repetitive transient extraction from the vibration data suffered from impulsive noise.
Parametric Sensitivity Study of Deep Excavation in Singapore Old Alluvium Formation
Authors: Wu Lanting , Sun Jianping , Tong Yuqiang
Published: December 2021

Deep excavation supported by vertical retaining walls together with strutting system is commonly used in Singapore for the construction of underground infrastructure. In this paper, a series of numerical scenarios simulated by PLAXIS software are carried out to study the influence of different design parameters such as pre‐auger loosening effect, the embedded depth of retaining wall into the stiff soil layer, and the elastic modulus of the ground improvement layer on excavation design especially on strut force, retaining wall deflection, and bending moment. The results show that there is high risk if only a single set of parameters are used as input to predict the performance of the retaining system. Sensitivity analysis shall be carried out to evaluate the effects of these parameter variations within a reasonable range on strut force, retaining wall deflection, and bending moment.
Evolutionary Game Analysis of Capital‐Constrained Supplier’s and Manufacturer’s Financing Schemes
Authors: Zhang Suyong , Pardalos Panos. M. , Jiang Xiaodan
Published: December 2021

Purchase order financing (POF) and buyer direct financing (BDF) are both innovative financing schemes aiming to help financial constrained suppliers secure financing for production. In this paper, we investigate the interaction mechanism between suppliers’ financing strategy selection and manufacturers’ loans offering strategy adoption under two innovative financing schemes. We developed an evolutionary game model to effectively investigate the interaction mechanism between suppliers and manufacturers and analyzed the evolutionary stable strategies of the game model. Then we used system dynamics to present the performance of the evolutionary game model and took a sensitivity analysis to verify the theoretical results. The main conclusions are as follows: in the supply chain, to deal with the noncooperation among suppliers and manufacturers on innovative financing schemes, the revenue of manufacturers, the rate of manufacturer loan, and the proper financial risk factor should be relatively high.
To Predict Anti-Inflammatory and Immunomodulatory Targets of Guizhi Decoction in Treating Asthma Based on Network Pharmacology, Molecular Docking, and Experimental Validation
Authors: Sun Rui , Xu Gonghao , Gao Dongyang , Ding Qi , Shi Yuanyuan
Published: December 2021

Asthma, characterized by the continuous inflammatory response caused by a variety of immune cells, is one of the most common chronic respiratory diseases worldwide. Relevant clinical trials proved that the traditional Chinese medicine formula Guizhi Decoction (GZD) had multitarget and multichannel functions, which might be an effective drug for asthma. However, the effective ingredients and mechanisms of GZD against asthma are still unclear. Therefore, network pharmacology, molecular docking, and cell experiments were performed to explore the antiasthma effects and potential mechanisms of GZD. First, we applied the TCMSP database and literature to obtain the bioactivated ingredients in GZD. SwissTargetPrediction, TCMSP, GeneCards, OMIM, PharmGkb, TTD, DrugBank, and STRING database were used to get core genes. In addition, the key pathways were analyzed by the DAVID database. Molecular docking was used to predict whether the important components could act on the core target proteins directly. Finally, qPCR was carried out to verify the network pharmacology results and the possible mechanisms of GZD in the treatment of asthma. We collected 134 active ingredients in GZD, 959 drug targets, and 3223 disease targets. 431 intersection genes were screened for subsequent analysis. Through GO and KEGG analyses, enriched pathways related to inflammation and immune regulation were presented. Through the qPCR method to verify the role of essential genes, we found that GZD had an excellent anti-inflammatory effect. Direct or indirect inhibition of MAPK and NF-κB pathways might be one of the crucial mechanisms of GZD against asthma. GZD might be a promising potential drug for the treatment of asthma. This article provided a reference for the clinical application of GZD.
Systemic Risk Contribution and Contagion of Industrial Sectors in China: From the Global Financial Crisis to the COVID-19 Pandemic
Authors: Liu Jianxu , Cheng Yangnan , Zhou Yefan , Li Xiaoqing , Kang Hongyu , Sriboonchitta Songsak
Published: December 2021

This paper investigates the risk contribution of 29 industrial sectors to the China stock market by using one-factor with Durante generator copulas (FDG) and component expected shortfall (CES) analyses. Risk contagion between the systemically most important sector and other sectors is examined using a copula-based ∆CoVaR approach. The data cover the 2008 global financial crisis and the beginning of the COVID-19 pandemic. The empirical results show that the banking sector contributed most to systemic risk before and during the global financial crisis. Nonbank finance became equally important in 2020, and the COVID-19 pandemic promoted the position of the computer and pharmaceuticals sectors. The spillover effect diminishes over time, but there remains risk contagion between sectors. The risk spillover trend is consistent with that of systemic risk.