bluuebunny/crossref_metadata_2025 huggingface dataset:
The Power of D-hops in Matching Power-Law Graphs
Authors: Yu Liren , Xu Jiaming , Lin Xiaojun
Published: June 2021

This paper studies seeded graph matching for power-law graphs. Assume that two edge-correlated graphs are independently edge-sampled from a common parent graph with a power-law degree distribution. A set of correctly matched vertex-pairs is chosen at random and revealed as initial seeds. Our goal is to use the seeds to recover the remaining latent vertex correspondence between the two graphs. Departing from the existing approaches that focus on the use of high-degree seeds in $1$-hop neighborhoods, we develop an efficient algorithm that exploits the low-degree seeds in suitably-defined D-hop neighborhoods. Specifically, we first match a set of vertex-pairs with appropriate degrees (which we refer to as the first slice) based on the number of low-degree seeds in their D-hop neighborhoods. This approach significantly reduces the number of initial seeds needed to trigger a cascading process to match the rest of graphs. Under the Chung-Lu random graph model with n vertices, max degree Θ(√n), and the power-law exponent 2<β<3, we show that as soon as D> 4-β/3-β, by optimally choosing the first slice, with high probability our algorithm can correctly match a constant fraction of the true pairs without any error, provided with only Ω((log n)4-β) initial seeds. Our result achieves an exponential reduction in the seed size requirement, as the best previously known result requires n1/2+ε seeds (for any small constant ε>0). Performance evaluation with synthetic and real data further corroborates the improved performance of our algorithm.
Review—High-Pressure Carbon Dioxide Separation Using Ionic Liquids: A CO2-Electrocatalysis Perspective
Authors: Mota-Lima Andressa , Alcantara Murilo Leite , Pérez-Sanz Fernando J. , Bazito Reinaldo C. , Vidinha Pedro , Alves Rita M. B. , Oller Nascimento Claudio A.
Published: June 2021

The use of methane as the energy vector in our current energy matrix has challenged scientists to solve problems, which are now related to the exploration of oil wells but tomorrow will be the foundation for a carbon-neutral industry. Subsea exploration challenges engineers to find new solutions to separate CO2 from CH4 at the extremely high pressure of ca. 400 bar, to which all mature separation technologies are unsuitable. In this review, we highlight possible ways to employ ionic liquid (IL) as a highly selective absorbent to CO2 for extremely high pressure. Besides revising the high-pressure physical-chemical properties of ILs, the IL designing principles, and finally, the current employment of IL for preparing membranes, we prospect possible solutions for the sluggish, disfavored IL-regeneration at high pressure. We prospect—CO2 electro-reduction reaction (CO2RR) as a promising disruption for separation processes, being CO2RR-based technologies viable not only for IL-regeneration after the IL-based CO2 capture but also for CO2 conversion into valuable fuels/chemicals. As a prelude to CO2RR-based technologies, this review highlights key aspects concerning the use of IL as the electrolyte in an electrochemical cell performing CO2RR.
An Improved Image Segmentation Algorithm CT Superpixel Grid Using Active Contour
Authors: Wei Yuntao , Wang Xiaojuan
Published: June 2021

The traditional CT image segmentation algorithm is easy to ignore image contour initialization, which leads to the problem of long time consuming and low accuracy. A superpixel mesh CT image improved segmentation algorithm using active contour was proposed. CT image superpixel gridding was carried out first; secondly, on the basis of gridding, the region growth criterion was improved by superpixel processing, the region growth graph was established, the image edge salient graph was calculated based on the growth graph, and the target edge was obtained as the initial contour; finally, the Mumford‐Shah model in the active contour model was improved; the energy functional was constructed based on the improved model and transformed into the symbol distance function. The results show that the proposed algorithm takes less time to mesh superpixels, the accuracy of image edge calculation is high, the correct classification coefficient is as high as 0.9, and the accuracy of CT image segmentation is always higher than 90%, which has superiority.
Analytical and Experimental Investigations on Mechanical Properties of Weak Plane Bedding in Mudstone
Authors: Zeng Yijin , Jiang Hailong , Ding Shidong , Chen Junhai , Wang Yi , Zheng Jie
Published: June 2021

Wellbore instabilities frequently occur in mudstone formation with weak plane bedding because of strong anisotropies. The mechanics parameters of weak plane bedding are of vital significance to the wellbore stability analysis for mudstone formations. The conventional method for determining the mechanics parameters is to fit lots of triaxial test data due to the blindness of coring. In this paper, an evaluation method of the mechanics parameters of weak plane bedding is proposed to improve the accuracy of weak plane bedding mechanical properties. The mechanics parameters of weak plane bedding are obtained by combing the single-weak plane failure criterion with the compressive strength of rock obtained by the triaxial test of cores with different coring angles. It is seen that the new evaluation method is simple and convenient. On the other hand, a validation method of the mechanics parameters of weak plane bedding is proposed to ensure their accuracy. The compressive strength obtained from the core with the special coring angle is compared with the theoretical compressive strength for verifying the accuracy of weak plane bedding mechanical properties. It is observed that the proposed evaluation and validation methods can be used to measure the value of weak plane bedding mechanical properties precisely. The proposed methods are general and can be used for measuring the mechanical properties of fracture weak-plane and joint weak-plane.
Handcrafted and Deep Learning-Based Radiomic Models Can Distinguish GBM from Brain Metastasis
Authors: Liu Zhiyuan , Jiang Zekun , Meng Li , Yang Jun , Liu Ying , Zhang Yingying , Peng Haiqin , Li Jiahui , Xiao Gang , Zhang Zijian , Zhou Rongrong
Published: June 2021

Objective. The purpose of this study was to investigate the feasibility of applying handcrafted radiomics (HCR) and deep learning-based radiomics (DLR) for the accurate preoperative classification of glioblastoma (GBM) and solitary brain metastasis (BM). Methods. A retrospective analysis of the magnetic resonance imaging (MRI) data of 140 patients (110 in the training dataset and 30 in the test dataset) with GBM and 128 patients (98 in the training dataset and 30 in the test dataset) with BM confirmed by surgical pathology was performed. The regions of interest (ROIs) on T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and contrast-enhanced T1WI (T1CE) were drawn manually, and then, HCR and DLR analyses were performed. On this basis, different machine learning algorithms were implemented and compared to find the optimal modeling method. The final classifiers were identified and validated for different MRI modalities using HCR features and HCR + DLR features. By analyzing the receiver operating characteristic (ROC) curve, the area under the curve (AUC), accuracy, sensitivity, and specificity were calculated to evaluate the predictive efficacy of different methods. Results. In multiclassifier modeling, random forest modeling showed the best distinguishing performance among all MRI modalities. HCR models already showed good results for distinguishing between the two types of brain tumors in the test dataset (T1WI, AUC = 0.86; T2WI, AUC = 0.76; T1CE, AUC = 0.93). By adding DLR features, all AUCs showed significant improvement (T1WI, AUC = 0.87; T2WI, AUC = 0.80; T1CE, AUC = 0.97;

p
<
0.05

). The T1CE-based radiomic model showed the best classification performance (AUC = 0.99 in the training dataset and AUC = 0.97 in the test dataset), surpassing the other MRI modalities (

p
<
0.05

). The multimodality radiomic model also showed robust performance (AUC = 1 in the training dataset and AUC = 0.84 in the test dataset). Conclusion. Machine learning models using MRI radiomic features can help distinguish GBM from BM effectively, especially the combination of HCR and DLR features.
Dynamic Behaviors and Mechanisms of Permanent Magnet Synchronous Motor with Excitation
Authors: Liu Shaohua , Shao Tingting , Wu Hai-dong , Zhang Dong-hui , Han Qing-zhen
Published: June 2021

The aim of this study is to make a general exploration of the dynamic characteristics of the permanent magnet synchronous motor (PMSM) with parametric or external perturbation. The pitchfork, fold, and Hopf bifurcations are derived by using bifurcation theory. Simulation results not only confirm the theoretical analysis results but also show the Bogdanov–Takens bifurcation of the equilibrium. Dynamic behaviors, such as period three and chaotic motion of PMSM, are analyzed by using bifurcation diagram and phase portraits. The symmetric fold/fold bursting oscillation as well as two kinds of delayed pitchfork bursting oscillations is obtained, and different mechanisms are presented.
The Effect of Managerial Ability on Earnings Classification Shifting and Agency Cost of Iranian Listed Companies
Authors: Imeni Mohsen , Fallah Mohammad , Edalatpanah Seyyed Ahmad
Published: June 2021

The objective of this study is to examine the relationship between managerial ability and earnings classification shifting of firms listed in the Tehran Stock Exchange (TSE). The paper consists of a sample of 1,875 firm-year observations after applying systematic elimination sampling method during a period of fifteen years, from 2005 to 2019. This study used the multivariate panel data regression for testing the links between variables. The results of this study provide that there is a positive relationship between managerial ability and earnings classification shifting. The obtained results indicate that there is a negative relationship between managerial ability and real earnings management and no relationship between managerial ability and AEM. In addition, managerial ability mitigates the negative effect of earnings management on future firm performance. Furthermore, managerial ability affects its agency cost positively due to the reduction in earnings management. This paper contributes to developing management literature and financial reporting literature. The study focuses on links managerial ability and earnings classification shifting and agency cost in a developing country like Iran, and the results of the paper can fill distance theory and practice by empirical test. Furthermore, the results of this study indicate in an emerging market, namely, Iran, that has a political business environment among the other countries of the Middle East, managerial ability can release Iranian firms on economic sanctions and financial pressures. This paper is the first study of its type in Iran.
Antibacterial Effect of Dihydromyricetin on Specific Spoilage Organisms of Hybrid Grouper
Authors: Huang Wenbo , Xie Jing
Published: June 2021

This study aimed to investigate the mechanism of antibacterial activity level inhibition of dihydromyricetin (DMY) against specific spoilage bacteria of grouper. Firstly, the specific spoilage bacteria of grouper in the cold storage process are Pseudomonas antarctica (P. antarctica), which are selected by calculating the spoilage metabolite yield factor. It was determined that the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of DMY against grouper spoilage bacteria were 2.0 mg/mL and 6.4 mg/mL, respectively. DMY was added to the matrix of chitosan and sodium alginate, and DMY emulsions of different concentrations (0 MIC, 1 MIC, 2 MIC, 4 MIC) were prepared and characterized by differential calorimetry methods. Through analyzing cell permeability, enzyme activity, and images of the confocal laser scanning microscope (CLSM), we further studied the antibacterial mechanism of DMY emulsion on specific spoilage bacteria. The results showed that, with the increase of DMY concentration in the treatment group, the leakage of nucleic acid and protein increased significantly, the activity of ATPase and three critical enzymes in the Embden-Meyerhof-Parnas (EMP) pathway decreased significantly, and the activity of AKPase did not decrease significantly, . The metabolic activity and viability are reduced considerably. Analysis of the above results shows that DMY inhibits the growth and reproduction of P. antarctica by interfering with the metabolic activity of bacteria and destroying the function of bacterial cell membranes but has no inhibitory effect on the activity of AKPase. This study proves that DMY could be an effective and natural antibacterial agent against specific spoilage bacteria in aquatic products.
Asphaltene Deposition during CO2 Flooding in Ultralow Permeability Reservoirs: A Case Study from Changqing Oil Field
Authors: Rong-tao Li , Xin-wei Liao , Jian-dong Zou , Chang-wang Gao , Dong-feng Zhao , Yuan-dong Zhang , Xing-ze Zhou
Published: June 2021

Asphaltene deposition is a common phenomenon during CO2 flooding in ultralow permeability reservoirs. The deposited asphaltene occupies the pore volume and decreases permeability, resulting in serious formation damage and pore well productivity. It is urgent to investigate the asphaltene deposition mechanisms, adverse effects, and preventive measures. However, few asphaltene deposition investigations have been systematically conducted by now. In this research, the asphaltene precipitation mechanisms and adverse effects were comprehensively investigated by using experimental and numerical methods. To study the effects of pressure, asphaltene content, and temperature on asphaltene precipitation qualitatively and quantitatively, the microscope visible detection experiment and the PVT cell static experiment were firstly conducted. The adverse effects on porosity and permeability resulted from asphaltene deposition were also studied by the core flooding experiment. Secondly, simulation models of asphaltene precipitation and deposition were developed and validated by experimental data. Finally, a case study from Changqing oil field was presented to analyze the asphaltene deposition characteristic and preventive measures. The experimental results showed that the asphaltene precipitation increases with the increased pressure before reaching the minimum miscible pressure (MMP) and gets the peak value around the MMP, while decreases slowly. The asphaltene precipitation increases with the increased temperature and asphaltene content. The variation trend of adverse effects on porosity and permeability resulted from asphaltene deposition is similar to that of asphaltene precipitation under the influence of pressure, asphaltene content, and temperature. The case study shows that the water-altering-gas (WAG) with high injection rate suffers more serious asphaltene deposition compared with the WAG with low injection rate, for the asphaltene precipitation increases as the increased pressure before reaching the MMP. The CO2 continuous injection with high injection rate is the worst choice, for low sweep efficiency and the most severe formation damage. Thus, the WAG with optimal injection rate was proposed to maintain well productivity and to reduce formation damage resulted from asphaltene deposition during developing ultralow permeability reservoirs.
Two-Level Multimodal Fusion for Sentiment Analysis in Public Security
Authors: Sun Jianguo , Yin Hanqi , Tian Ye , Wu Junpeng , Shen Linshan , Chen Lei
Published: June 2021

Large amounts of data are widely stored in cyberspace. Not only can they bring much convenience to people’s lives and work, but they can also assist the work in the information security field, such as microexpression recognition and sentiment analysis in the criminal investigation. Thus, it is of great significance to recognize and analyze the sentiment information, which is usually described by different modalities. Due to the correlation among different modalities data, multimodal can provide more comprehensive and robust information than unimodal in data analysis tasks. The complementary information from different modalities can be obtained by multimodal fusion methods. These approaches can process multimodal data through fusion algorithms and ensure the accuracy of the information used for subsequent classification or prediction tasks. In this study, a two-level multimodal fusion (TlMF) method with both data-level and decision-level fusion is proposed to achieve the sentiment analysis task. In the data-level fusion stage, a tensor fusion network is utilized to obtain the text-audio and text-video embeddings by fusing the text with audio and video features, respectively. During the decision-level fusion stage, the soft fusion method is adopted to fuse the classification or prediction results of the upstream classifiers, so that the final classification or prediction results can be as accurate as possible. The proposed method is tested on the CMU-MOSI, CMU-MOSEI, and IEMOCAP datasets, and the empirical results and ablation studies confirm the effectiveness of TlMF in capturing useful information from all the test modalities.
Activation of Hippocampal IR/IRS-1 Signaling Contributes to the Treatment with Zuogui Jiangtang Jieyu Decoction on the Diabetes-Related Depression
Authors: Yang Hui , Ling Jia , Meng Pan , Liu Jian , Lin Xiaoyuan , Li Wei , Wang Yuhong
Published: June 2021

Background. Zuogui Jiangtang Jieyu decoction (ZJJ) is mainly used for the treatment of diabetes-related depression in current clinical applications and research. This study aims to investigate whether the brain IR/IRS-1 signaling pathway is involved in the therapeutic effect of ZJJ on depression-like behavior in diabetic rats. Methods. Sprague–Dawley rats were fed with high-fat diet and subjected to streptozotocin injection to establish the diabetes animal model. After treatment with different doses of ZJJ (20.530 g/kg or 10.265 g/kg) for 4 weeks, the blood glucose level and peripheral insulin resistance were measured. The forced-swimming test (FST) and Morris water maze test (MWMT) were applied for the mood and cognitive function assessment. Then, the Western blot method was used to analyze the protein levels of insulin receptor (IR), insulin receptor substrate-1 (IRS-1), phosphatidylonositol-3-kinase (PI3K), and protein kinase B (PKB, also as known as AKT) in the hippocampus of diabetic rats. Meanwhile, the immunofluorescence method was performed to analyze the above proteins’ expression in the neuron and astrocyte. At last, the levels of glycogen, lactate, and ATP were tested by the ELISA method. Additionally, the insulin-sensitive glucose transporter 4 (GLUT4) and the lactate transporter monocarboxylate transporter 4 (MCT4) were analyzed by the Western blot method. Results. ZJJ administration significantly decreased the level of blood glucose and improved the peripheral insulin resistance in diabetic rats. Besides, ZJJ attenuated the depression-like behavior and the cognitive dysfunction in rats with diabetes. Furthermore, we found the upregulation of protein expression of phospho-IR, phospho-IRS-1, phospho-PI3K, and phospho-AKT in the hippocampus of diabetic rats after being treated with ZJJ. Moreover, the above proteins are increased not only in the neuron but also in the astrocyte after ZJJ administration. In addition, ZJJ increased the content of ATP, glycogen, and lactate, as well as the expression of GLUT4 and MCT4 in the hippocampus of diabetic rats. Conclusions. These findings suggest that ZJJ improves the depression-like behavior of diabetic rats by activating the IR/IRS-1 signaling pathway in both hippocampal neuron and astrocyte. And the brain IR/IRS-1 signaling pathway plays an important role in astrocyte-neuron metabolic coupling, providing a potential mechanism by which the IR/IRS-1 signaling pathway may contribute to the treatment of ZJJ on diabetes-related depression.
The Analysis of bcl-2 in Association with p53 and Ki-67 in Triple Negative Breast Cancer and Other Molecular Subtypes in Ghana
Authors: Ameh-Mensah Charity , Duduyemi Babatunde Moses , Bedu-Addo Kweku , Atta Manu Elijah , Opoku Francis , Titiloye Nicholas
Published: June 2021

Background. Little is known about the role of apoptosis in the tumorigenesis and prognosis of breast cancer in Ghana. Chemotherapeutic drug efficacy partially relates to apoptosis induction, rendering it a vital target in cancer therapy with unique biomarker opportunities that have not been exploited. Aberrations in this pathway are central to tumorigenesis, tumor progression, overall tumor growth, and regression during treatment therapies. Antiapoptotic bcl-2 (gene) and p53 are known to play roles in apoptosis while Ki-67 is a proliferative marker. The aim of our study is to determine the association of bcl-2 (protein) with p53 and Ki-67 in 203 consecutive breast cancer cases over a 10-year period. Method. A retrospective cross-sectional study on archival FFPE tissue blocks over a 9-year period with abstraction of clinicopathologic data. Two hundred and three consecutive and suitable FFPE blocks were selected for tissue microarray (TMA) construction, and IHC (bcl-2 (protein), Ki-67, p53, cyclin D, pan cytokeratins A and E, ER, PR, and HER2/neu) was done. Expressions of bcl-2 (protein), p53, and Ki-67 were related to histological grade, lymphovascular invasion, and molecular subtypes. SPSS version 23 was used to analyze results. Results. Most of our cases were in the fifth decade of life (31%); invasive carcinoma of no special type (NST) was predominant (87%); histological grade III (38%) was the highest; and Luminal A (19.8%), Luminal B (9.9%), HER2 (16%), and TNBC (54.3%) constituted the molecular classes. bcl-2 expression was found in 38% of the cases. Our cases also showed mutation in p53 (36.7%) and ki-67 expression (62.5%). bcl-2 (protein) and p53 significantly correlated with Luminal B and TNBC (

p
<
0.01

). Ki-67 also correlated significantly with Luminal A and B and HER2 overexpression (

p
<
0.01

). Premenopausal age (40–49) and histological grade inversely correlated with bcl-2 (protein) expression. p53 statistically correlated with Ki-67 (

p
<
0.05

). Conclusion. Our results show high expression of bcl-2 (protein) suggesting an important role of apoptosis in Ghanaian breast cancer cases. bcl-2 (protein), p53, and Ki-67 expressions emerged interdependently from this research and can thus be manipulated in prediction and prognosis of breast cancers in our setting.
[Retracted] Accounting Data Encryption Processing Based on Data Encryption Standard Algorithm
Authors: Chen Meixi
Published: June 2021

With the application of computer and network technology in the field of accounting, the development of accounting informationization is an inevitable trend, and the construction of accounting statement data into the data warehouse will be the basis of intelligent decision‐making. The complexity of industry accounting statements and the arbitrariness and diversity of users’ needs for obtaining information using statements limit the development, popularization, and application of industry accounting statements. As a block encryption algorithm, the Data Encryption Standard (DES) algorithm uses 64‐bit packet data for encryption and decryption. Each eighth bit of the key is used as a parity bit; that is, the actual key length is 56 bits. Encryption and decryption use the same algorithm structure, but the order in which the subkeys are used is reversed. Under the control of the subkey, inputting 64‐bit plaintext can produce 64‐bit ciphertext output; otherwise, inputting 64‐bit ciphertext can produce 64‐bit plaintext output. The confidentiality of the DES algorithm depends on the key, and only a very small number of keys are considered weak keys, which can be easily avoided in practical applications. The 3DES algorithm is a cascade of the DES algorithm, and its encryption process is based on the DES algorithm principle. This article explains the encryption process of the DES algorithm and introduces the composition of the 3DES algorithm. The experimental results show that the 3DES encryption algorithm still has a better encryption effect and “avalanche effect” than before the improvement. In addition, for the 3DES algorithm, its encryption efficiency has not been greatly affected. The 3DES encryption algorithm achieves one encryption process at a time to some extent, can effectively resist exhaustive search attacks, and enhance the security of the DES algorithm.
On the Spectrum of Laplacian Matrix
Authors: Jahanbani Akbar , Sheikholeslami Seyed Mahmoud , Khoeilar Rana
Published: June 2021

Let

G

be a simple graph of order

n

. The matrix

ℒ

G

=
D

G

−
A

G

is called the Laplacian matrix of

G

, where

D

G

and

A

G

denote the diagonal matrix of vertex degrees and the adjacency matrix of

G

, respectively. Let

l

1

G

,

l

n
−
1

G

be the largest eigenvalue, the second smallest eigenvalue of

ℒ

G

respectively, and

λ

1

G

be the largest eigenvalue of

A

G

. In this paper, we will present sharp upper and lower bounds for

l

1

G

and

l

n
−
1

G

. Moreover, we investigate the relation between

l

1

G

and

λ

1

G

.
Sodium Houttuyfonate Ameliorates β-amyloid1-42-Induced Memory Impairment and Neuroinflammation through Inhibiting the NLRP3/GSDMD Pathway in Alzheimer’s Disease
Authors: Zhao Yuequan , Tian YunPeng , Feng Tao
Published: June 2021

Objective. Our research is designed to explore the function of sodium houttuyfonate (SH) on Alzheimer’s disease (AD) and its potential molecular mechanisms. Methods. In our study, the Morris water maze (MWM) test was used to assess the role of SH on spatial learning and memory deficiency in amyloid-β peptide (Aβ)1-42-induced AD mice. We explored the functions of SH on proinflammatory cytokines, neuron apoptosis, and damage in vivo and in vitro by using an enzyme-linked immunosorbent assay (ELISA), quantitative real-time polymerase chain reaction (qRT-PCR), flow cytometry, western blot, and Nissl staining. Moreover, the effect of SH on oxidative stress in vivo and in vitro was also detected. To explore the underlying molecular mechanisms of SH on AD, the expressions of proteins and mRNA involved in the NOD-like receptor pyrin domain containing-3/gasdermin D (NLRP3/GSDMD) pathway were determined using western blot, immunofluorescence staining, and qRT-PCR. Results. Our data demonstrated that SH ameliorated spatial learning and memory deficiency in Aβ1-42-induced AD mice. Moreover, SH significantly improved hippocampal neuron damage and inhibited oxidative stress, neuroinflammation, and neuron apoptosis in Aβ1-42-induced AD mice and PC12 cells. The results also revealed that SH protected Aβ1-42-induced AD through inhibiting the NLRP3/GSDMD pathway. Conclusion. The present study demonstrated that SH could ameliorate Aβ1-42-induced memory impairment neuroinflammation and pyroptosis through inhibiting the NLRP3/GSDMD pathway in AD, suggesting that SH may be a potential candidate for AD treatment.
Relationship between Memory Load and Listening Demands in Age-Related Hearing Impairment
Authors: Pauquet Julia , Thiel Christiane M. , Mathys Christian , Rosemann Stephanie
Published: June 2021

Age-related hearing loss has been associated with increased recruitment of frontal brain areas during speech perception to compensate for the decline in auditory input. This additional recruitment may bind resources otherwise needed for understanding speech. However, it is unknown how increased demands on listening interact with increasing cognitive demands when processing speech in age-related hearing loss. The current study used a full-sentence working memory task manipulating demands on working memory and listening and studied untreated mild to moderate hard of hearing (n=20) and normal-hearing age-matched participants (n=19) with functional MRI. On the behavioral level, we found a significant interaction of memory load and listening condition; this was, however, similar for both groups. Under low, but not high memory load, listening condition significantly influenced task performance. Similarly, under easy but not difficult listening conditions, memory load had a significant effect on task performance. On the neural level, as measured by the BOLD response, we found increased responses under high compared to low memory load conditions in the left supramarginal gyrus, left middle frontal gyrus, and left supplementary motor cortex regardless of hearing ability. Furthermore, we found increased responses in the bilateral superior temporal gyri under easy compared to difficult listening conditions. We found no group differences nor interactions of group with memory load or listening condition. This suggests that memory load and listening condition interacted on a behavioral level, however, only the increased memory load was reflected in increased BOLD responses in frontal and parietal brain regions. Hence, when evaluating listening abilities in elderly participants, memory load should be considered as it might interfere with the assessed performance. We could not find any further evidence that BOLD responses for the different memory and listening conditions are affected by mild to moderate age-related hearing loss.
Effect of Acupuncture on Neuroplasticity of Stroke Patients with Motor Dysfunction: A Meta-Analysis of fMRI Studies
Authors: Lv Qiuyi , Xu Guixing , Pan Yuxin , Liu Tongtong , Liu Xiaodong , Miao Linqing , Chen Xing , Jiang Lan , Chen Jie , He Yingjia , Zhang Rong , Zou Yihuai
Published: June 2021

Importance. Acupuncture is an effective treatment for stroke, especially in the aspect of motor deficit. Many brain imaging studies of acupuncture have found significant changes in brain function after acupuncture treatment in order to reveal its underlying mechanisms in regulating neural plasticity. However, no definite consensus has been reached. Objective. To analyze the pattern of intrinsic brain activity variability that is altered by acupuncture compared with conventional treatment in stroke patients with motor dysfunction, thus providing the mechanism of stroke treatment by acupuncture. Methods. Chinese and English articles published up to May 2020 were searched in the PubMed, Web of Science, EMBASE, and Cochrane Library databases, China National Knowledge Infrastructure, Chongqing VIP, and Wanfang Database. We only included randomized controlled trials (RCTs) using resting-state fMRI to observe the effect of acupuncture on stroke patients with motor dysfunction. R software was used to analyze the continuous variables, and Seed-based d Mapping with Permutation of Subject Images (SDM-PSI) was used to perform an analysis of fMRI data. Findings. A total of 7 studies comprising 143 patients in the treatment group and 138 in the control group were included in the meta-analysis. The results suggest that acupuncture treatment helps the healing process of motor dysfunction in stroke patients and exhibits hyperactivation in the bilateral basal ganglia and insula and hypoactivation in motor-related areas (especially bilateral BA6 and left BA4). Conclusion. Acupuncture plays a role in promoting neuroplasticity in subcortical regions that are commonly affected by stroke and cortical motor areas that may compensate for motor deficits, which may provide a possible mechanism underlying the therapeutic effect of acupuncture.
m6A RNA Methylation Regulators Elicit Malignant Progression and Predict Clinical Outcome in Hepatocellular Carcinoma
Authors: Li Wenli , Liu Jun , Ma Zhanzhong , Zhai Xiaofeng , Cheng Binbin , Zhao Hetong
Published: June 2021

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide, and N6-methyladenosine (m6A) is a predominant internal modification of RNA in various cancers. We obtained the expression profiles of m6A-related genes for HCC patients from the International Cancer Genome Consortium and The Cancer Genome Atlas datasets. Most of the m6A RNA methylation regulators were confirmed to be differentially expressed among groups stratified by clinical characteristics and tissues. The clinical factors (including stage, grade, and gender) were correlated with the two subgroups (cluster 1/2). We identified an m6A RNA methylation regulator-based signature (including METTL3, YTHDC2, and YTHDF2) that could effectively stratify a high-risk subset of these patients by univariate and LASSO Cox regression, and receiver operating characteristic (ROC) analysis indicated that the signature had a powerful predictive ability. Immune cell analysis revealed that the genes in the signature were correlated with B cell, CD4 T cell, CD8 T cell, dendritic cell, macrophage, and neutrophil. Functional enrichment analysis suggested that these three genes may be involved in genetic and epigenetic events with known links to HCC. Moreover, the nomogram was established based on the signature integrated with clinicopathological features. The calibration curve and the area under ROC also demonstrated the good performance of the nomogram in predicting 3- and 5-year OS in the ICGC and TCGA cohorts. In summary, we demonstrated the vital role of m6A RNA methylation regulators in the initial presentation and progression of HCC and constructed a nomogram which would predict the clinical outcome and provide a basis for individualized therapy.
Research on the Evaluation Model for Wireless Sensor Network Performance Based on Mixed Multiattribute Decision‐Making
Authors: Song Jiekun , Zhang Yemeng , Zhao Zhihao , Chen Rui
Published: June 2021

Many application fields initiate using wireless sensor network (WSN), and the evaluation for its performance becomes an important topic, which can help the decision‐maker to find the deficiency of the current WSN or seek the best WSN. There exist mixed multiple attributes in the WSN performance evaluation process, for example, some evaluation indicators can be expressed as interval numbers, while others can be expressed as linguistic variables, so it is necessary to explore the evaluation model based on mixed multiattribute decision‐making (MADM). Considering the specific evaluation purpose and requirements for different enterprises, this paper puts forward an indicator selection method and a subjective weighting method based on the rough set theory. After that, based on the transformation of mixed attributes into the unified intuitionistic fuzzy numbers (IFNs), an objective weighting method based on intuitionistic fuzzy entropy is proposed. Meanwhile, the combined weights of indicators are obtained by synthesizing the subjective and objective weights. Subsequently, in order to evaluate WSN performance objectively, an integrated comprehensive evaluation framework is proposed, which includes single evaluation, compatibility test, combination evaluation, and consistency test. The paper gives specific models and calculation steps in detail. Finally, it provides a case study to explain the application of the proposed indicator selection method and the evaluation models, which provide new ideas and references for WSN performance evaluation.
Skin Closure Technique and Postprocedural Pain after Spinal Cord Stimulator Implantation: A Retrospective Review
Authors: Bendel Markus A. , D’Souza Ryan S. , North Taylor J. , Pittelkow Thomas P. , Hagedorn Jonathan M.
Published: June 2021

Spinal cord and dorsal root ganglion stimulation are minimally invasive surgical techniques used to treat an array of chronic pain disorders. There is a paucity of data related to defining best practices in these specific patient populations, and historically, providers have relied on consensus committees to opine on the best techniques for patient safety and experience. The most efficacious mechanism of surgical closure—specifically a running suture closure compared to a surgical staple closure—is debated. A retrospective review of 155 patients implanted with either a spinal cord or dorsal root ganglion stimulator between 2017 and 2019 was undertaken to determine if the type of surgical closure was related to degree of postoperative surgical site discomfort. The primary outcome showed no statistically significant difference on postoperative pain scores between the suture (6.0 (IQR 5.0–8.0)) and staple (7.0 (IQR 5.0–8.0)) cohorts at postoperative day (POD) #1 (adjusted β 0.17 (95% CI −0.61 to 0.95),

P
=
0.670

). This finding held for postoperative pain scores at POD #10 as well (staples (1.0 (IQR 0.0–4.0)) and suture (2.0 (IQR 0.0–5.0), adjusted β −0.39 (95% CI −1.35 to 0.58),

P
=
0.432

)). A regression analysis was performed to identify secondary factors impacting postoperative pain scores. Higher preoperative pain score (β 0.50 (95% CI 0.09 to 0.92),

P
=
0.019

) and female gender (β 1.09 (95% CI 0.15 to 2.02),

P
=
0.023

) were predictive of higher incisional pain scores at POD#10. Increasing age was associated with decreased incisional pain scores at POD#10 (β −0.06 (95% CI −0.09 to −0.03),

P
<
0.001

). These findings are of interest to the pain practitioner and may be valuable in preoperative discussions with prospective patients.
[Retracted] Computer Simulation of Ideological and Political Teaching under Big Data of Complexity
Authors: Zhu Guoping , Zhu Guohua , Zhang Jianhua
Published: June 2021

This study is to discuss the application of computer simulation technology (CST) in ideological and political teaching (I&P teaching) and promote the reform of ideological and political teaching in the era of big data. In this study, a set of computer simulation system for I&P teaching is constructed, and targeted research is launched from this. The main research results are as follows: Firstly, a computer simulation system for ideological and political teaching is designed based on the Apriori algorithm and other theoretical foundations. The system includes a user layer, a business layer, and a data layer. The main modules of the system include the website (WEB) server, Mail server, and user terminal. Secondly, the system is tested accordingly. The performance test and function test results reveal that when the maximum number of concurrent users is 500, the system can run normally with the maximum response time of 6.6 s and the good condition of various functions, so it can meet the actual needs of universities. Finally, in comparison with the conventional I&P courses, the proposed system can effectively improve the attitudes towards I&P courses of students, increase their satisfaction and acceptance of I&P teaching, and contribute to the mastery of knowledge. Therefore, the designed system can realize a good actual teaching effect and show reliable application value. In addition, the results of this study can provide scientific and effective reference materials for subsequent research on I&P teaching.
Neonatal Outcomes in Pregnant Women Infected with COVID-19 in Babol, North of Iran: A Retrospective Study with Short-Term Follow-Up
Authors: Akbarian-Rad Zahra , Mojaveri Mohsen Haghshenas , Bouzari Zinatossadat , Sadeghi Farzin , Yahyapour Yousef , Rad Mojgan Naeimi , Alizadeh Somayeh , Ebrahimpour Soheil , Sepidarkish Mahdi , Javanian Mostafa
Published: June 2021

During the coronavirus disease 2019 (COVID-19) pandemic, the number of pregnant women and neonates suffering from COVID-19 increased. However, there is a lack of evidence on clinical characteristics and neonatal outcomes in pregnant women with COVID-19. We evaluated short-term outcomes (4 weeks postdischarge) and symptoms in neonates born to mothers infected with COVID-19. In this retrospective cohort study, we included all neonates born to pregnant women with COVID-19 admitted to Ayatollah Rohani Hospital, Babol, Iran, from February 10 to May 20, 2020. Clinical features, treatments, and neonatal outcomes were measured. Eight neonates were included in the current study. The mean gestational age and birth weight of newborns were

37
±
3.19

weeks (30₊6-40) and

3077.50
±
697.64

gr (1720-3900), respectively. Apgar score of the first and fifth minutes in all neonates was ≥8 and ≥9 out of 10, respectively. The most clinical presentations in symptomatic neonates were respiratory distress, tachypnea, vomiting, and feeding intolerance. This manifestation and high levels of serum C-reactive protein (CRP) in three infants are common in neonatal sepsis. The blood culture in all of them was negative. They have been successfully treated with our standard treatment. Our pregnant women showed a pattern of clinical characteristics and laboratory results similar to those described for nonpregnant COVID-19 infection. This study found no evidence of intrauterine or peripartum transmission of COVID-19 from mother to her child. Furthermore, the long-term outcomes of neonates need more study.
Identification of CD8+ T Cell-Related Genes: Correlations with Immune Phenotypes and Outcomes of Liver Cancer
Authors: Pan Qi , Cheng Ying , Cheng Donghua
Published: June 2021

Purpose. Treatment outcomes for advanced liver cancer are poor. Immunotherapy is a treatment strategy that has been widely used to treat other cancers. Studies have shown that CD8+ T lymphocytes are essential factors affecting the efficacy of immunotherapy. We used computational biology methods to determine the coexpressed gene network that promotes CD8+ T lymphocyte infiltration. Method. We obtained the liver cancer gene matrix and clinical follow-up information data from TCGA liver hepatocellular carcinoma FPKM. We obtained single nucleotide polymorphism (SNP) data to evaluate the tumor mutation burden. The “estimate” package and the CIBERSORT algorithm were used to evaluate tumor purity and the proportion of CD8+ T lymphocytes in the liver cancer cohort. We used the gene expression matrix of liver cancer and the relative proportion of CD8+ T lymphocytes as input files and performed WGCNA based on this analysis. The weighted coexpression network identified the most CD8+ T lymphocyte-related coexpression modules in liver cancer. Then, we analyzed the biological processes involved in the module. We determined the coexpression module with CD8+ T lymphocyte infiltration in terms of data and function. We then screened the factors in the coexpression module correlated with CD8+ T lymphocyte content greater than 0.4. Finally, the expression levels of these factors were verified at the protein level using immunohistochemistry and single-cell sequencing. Results. We determined the CD8+ T lymphocyte proportions that correlated with coexpression networks. Four coexpressed genes (C1QC, CD3D, GZMA, and PSMB9) were identified as CD8+ T cell coexpression genes that promoted infiltration of CD8+ T cells. Because the factors in the coexpression network often participate in similar biological processes, we found that these factors were most related to antigen processing and presentation of peptide antigen through functional enrichment. In the clinical phenotype analysis, we found that 18 factors can be used as independent prognostic protective factors. We found that these factors were significantly negatively correlated with tumor purity and negatively correlated with M2 macrophages in the immunophenotyping analysis. Using immunohistochemistry and single-cell sequencing analysis, we found that CD3D antibody staining was weaker in tumor tissues than normal tissues and was related to CD8+ T cells. Conclusion. These coexpressed genes were positively related to the high infiltration proportion of CD8+ T lymphocytes in an antigen presentation process. The biological process might provide new directions for patients who are insensitive to immune therapy.
Finite Element Structure Analysis of Automobile Suspension Control Arm Based on Neural Network Control
Authors: Li Yixuan
Published: June 2021

The control arm is an important transmission and guidance device in the Macpherson suspension system, which has an important impact on the ride comfort, operation stability, and safety of the vehicle, so it is necessary to study the structural performance of the control arm. In this paper, based on neural network control model, finite element analysis, and fatigue analysis theory, the strength, stiffness, and dynamic and fatigue performance of the control arm are studied and analyzed. Taking the ground contact force of the tire as the input condition, the static analysis of the front suspension is carried out, and the boundary condition of the load of the control arm is extracted. The finite element strength of the control arm is calculated in the OptiStruct solver under the conditions of uneven road, braking, and turning. At the same time, the longitudinal stiffness and lateral stiffness of the control arm are analyzed. The simulation results show that the control arm has better strength and stiffness performance.
Cellular Signal Transduction Pathways Involved in Acute Lung Injury Induced by Intestinal Ischemia‐Reperfusion
Authors: Li Guangyao , Zhang Yingyi , Fan Zhe
Published: June 2021

Intestinal ischemia‐reperfusion (II/R) injury is a common type of tissue and organ injury, secondary to intestinal and mesenteric vascular diseases. II/R is characterized by a high incidence rate and mortality. In the II/R process, intestinal barrier function is impaired and bacterial translocation leads to excessive reactive oxygen species, inflammatory cytokine release, and even apoptosis. A large number of inflammatory mediators and oxidative factors are released into the circulation, leading to severe systemic inflammation and multiple organ failure of the lung, liver, and kidney. Acute lung injury (ALI) is the most common complication, which gradually develops into acute respiratory distress syndrome and is the main cause of its high mortality. This review summarizes the signal transduction pathways and key molecules in the pathophysiological process of ALI induced by II/R injury and provides a new therapeutic basis for further exploration of the molecular mechanisms of ALI induced by II/R injury. In particular, this article will focus on the biomarkers involved in II/R‐induced ALI.
A Privacy-Preserving Identity Authentication Scheme Based on the Blockchain
Authors: Gao Sheng , Su Qianqian , Zhang Rui , Zhu Jianming , Sui Zhiyuan , Wang Junsheng
Published: June 2021

Traditional identity authentication solutions mostly rely on a trusted central entity, so they cannot handle single points of failure well. In addition, most of these traditional schemes need to store a large amount of identity authentication or public key information, which makes the schemes difficult to expand and use in distributed situations. In addition, the user prefers to protect the privacy of their information during the identity verification process. Due to the open and decentralized nature of the blockchain, the existing identity verification schemes are difficult to apply well in the blockchain. To solve this problem, in this article, we propose a privacy protection identity authentication scheme based on the blockchain. The user independently generates multiple-identity information, and these identities can be used to apply for an identity certificate. Authorities use the ECDSA signature algorithm and the RSA encryption algorithm to complete the distribution of the identity certificate based on the identity information and complete the registration of identity authentication through the smart contract on the blockchain. On the one hand, it can realize the protection of real identity information; on the other hand, it can avoid the storage overhead caused by the need to store a large number of certificates or key pairs. Due to the use of the blockchain, there is no single point of failure in the authentication process, and it can be applied to distributed scenarios. The security and performance analysis show that the proposed scheme can meet security requirements and is feasible.