bluuebunny/crossref_metadata_2025 huggingface dataset:
Solution Existence Theory for Artificial Neural Networks
Authors: Liu G. R.
Published: August 2022

Artificial neural networks (NNs) have been widely used in creation of various machine learning (ML) models. Training an NN for a given dataset is essentially finding a set of weights and biases, known as learning (or training) parameters. An NN uses the affine transformations to encode the features in the dataset in the form of learning parameters. One may naturally ask fundamental questions: (1) can the NN be trained, meaning that can a solution for a set of learning parameters can be found? and (2) is the solution unique? This paper addresses these questions. First, detailed formulation is presented for a simple NN with just one basic affine transformation unit (ATU) for linear regression problems. Conditions for solution existence and uniqueness will be examined, leading to the Solution Existence Theory. A discussion will be presented when this Solution Existence Theory is extended to general NNs for complex problems, in addition to a discussion on predictability of NNs.
A note about the non-commutative three-sphere with torsion and non-metricity
Authors: Hurley D. J. , Vandyck M. A.
Published: August 2022

The Levi-Civita connection usually adopted on the non-commutative three-sphere is generalized to a connection possessing torsion and a non-metricity of the Weyl kind. This leads to geometrical properties that are qualitatively different from the ordinary ones and, in particular, provides an example of non-commutative “teleparallelism”. The comparison is made with the analogous case in classical (i.e. commutative) differential geometry. A general framework is developed, from which the unique connection having a given metric, torsion and non-metricity can be determined.
Creation field cosmological models for dust distribution and time-dependent cosmological term (Λ) in Bianchi type II space-time
Authors: Bali Raj
Published: August 2022

In this paper, we present solution of Einstein field equations which admit dust distribution and negative energy massless scalar field as a source with cosmological term ([Formula: see text]) in the frame work of Bianchi type II space-time. The models satisfy conservation equation and creation field increases with time satisfying the result as investigated by Hoyle and Narlikar [A new theory of gravitation, Proc. Roy. Soc. A 282 (1964) 191]. The deceleration parameter ([Formula: see text]) for the model (22) shows a transition from decelerating to accelerating regime with creation. A comparison with other cosmological models shows a transition from decelerating to accelerating regime with and without creation is mentioned. The present model is free from singularity, particle horizon and provides a natural explanation for inflationary scenario and isotropization. These features make the creation field cosmological models theoretically superior to the Big Bang models. Creation field and Einstein field equation are derived using principle of least action and the Lagrangian formulation of variable cosmological term is derived as mentioned by Moffat [Lagrangian formulation of a solution to the cosmological constant problem (1996), arXiv:astro-ph/9608202v1]. The current creation rate with other physical consequences is also discussed. For illustrative purposes, evolutionary behaviors of some cosmological parameters are shown graphically. In the figures, the cosmic time [Formula: see text] is given in gravitational units assuming the velocity of light [Formula: see text]. This [Formula: see text] and [Formula: see text]. Therefore, by multiplying cosmic time [Formula: see text] by (light years)−1, we obtain the coordinate time in years.
Coastal Scenery Quality: A Management Tool for Sandy Beaches
Authors: Diniz Lorrana Lopes , Machado Phillipe Mota , Lima Juliano Silva , Costa Leonardo Lopes , Da Costa Igor David , Zalmon Ilana Rosental
Published: August 2022

Beaches are multidimensional environments, and their management must include the ecological, sociocultural and economic aspects. The continuous occupation of this ecosystem combined with the scarcity of adequate management plans has reduced the quality of coastal sceneries. Therefore, strategies are needed to ensure the perpetuity of resources and delivery of ecosystem services. The objective of this study was to assess the coastal scenery quality at three sandy beaches of Rio de Janeiro, Brazil. A quali-quantitative approach was applied using measurable aspects, considering eight categories as accessibility, water quality, scenic quality, infrastructure, safety and environmental education, based on 67 indicators. The beaches commonly presented higher values for water quality, while environmental education had the lowest ranks, indicating that this category should be prioritised in management strategies. In addition to the low cost of this effective tool for beach management, it is quick to apply, easy to analyse and represents an advancement in important issues about the use of integrative indicators to evaluate coastal sceneries, providing a scientific base that can offer evidence about the main management priorities in areas where coastal tourism has a significant role.
Finite-Dimensional Fuzzy Strong ϕ-b-Normed Linear Spaces
Authors: Das Abhishikta , Bag T.
Published: August 2022

Following the concept of l-fuzzy convergent sequence, l-fuzzy closed, l-fuzzy complete, l-fuzzy compact sets in fuzzy normed linear spaces, in this paper, we study some results in finite-dimensional fuzzy strong [Formula: see text]-b-normed linear spaces and extend the most momentous Riesz Lemma.
Phase conversion during MnC2O4 pyrolysis and the application on high photothermal catalytic degradation of toluene
Authors: Yu Xiao , Chen Zhenglin , Wei Zhihui , Chen Kai , Fan Yixuan , Zou Moliang , Si Xueliu , Deng Banghong , Yang Lixia , Zhang Jie
Published: August 2022

Monoclinic Mn5O8, spinel Mn3O4, and perovskite Mn 2O3were prepared by thermal decomposition of MnC2O4. The formation of different MnOx species observed by thermogravimetric analysis (TGA) and X-ray diffraction (XRD) measurements showed temperature-dependent phase transformation following the path of MnC2O 4[Formula: see text]Mn5O8[Formula: see text]Mn3O4[Formula: see text]Mn2O 3occurring during the heat treatment process. Among these manganese oxides, the MO-1 (Mn5O8 ) showed the best light-driven photothermal catalytic performance reaching up to 99% of toluene degradation and 75% of mineralization efficiencies reached within 30 min. Besides, it is found that structural defects decrease with the increase of the calcinated temperature, and the Mn[Formula: see text]/Mn[Formula: see text]active sites and oxygen vacancies play an important role in improving the light-driven photothermal catalytic performance.
Nonlinear free vibration and flexural analysis of hyperelastic beam utilizing a meshless method based on radial basis function
Authors: Hosseini Shahram , Rahimi Gholamhossein , Gazor Mohammad Sajjad
Published: August 2022

This paper investigates nonlinear free and flexural analysis of hyperelastic beams. The constitutive relations of the hyperelastic beam were derived using the neo-Hookean strain energy function and Timoshenko beam theory. Also, the nonlinear governing equations and nonlinear natural boundary conditions were derived using Hamilton’s principle. The meshless collocation method based on the multiquadric radial basis function (MQ-RBF) was utilized to discretize the nonlinear governing equations. Also, the arc-length algorithm was used to solve the nonlinear system of equations. To validate the results of the meshless method, different boundary conditions (clamped–clamped, simply supported–simply supported, clamped–simply supported, and clamped-free) were examined, and the results obtained from the meshless method were compared with those of the finite element method in Abaqus finite element software. The results show that the maximum and minimum differences between meshless and finite element methods occur in clamped and free-boundary conditions, respectively. The results also show that the meshless method based on the MQ-RBF has good accuracy compared to the finite element method for bending and free vibration analysis of hyperelastic beams.
Personalized Travel Recommendation System Using Average Cumulative Rating Matrix Factorization Technique: Concept and Framework
Authors: Kumar Niranjan , Pallavi K. V. , Hanji Bhagyashri R.
Published: August 2022

Recommendation systems in travel applications have a purpose to provide custom-made results to travelers while making a travel plan. These recommendation systems should be adaptable if user preferences change dynamically. To get custom-made results, the recommendation systems should be provided with traveler’s interests such as traveler’s specifications, preferences concerning destinations, type of activities they are very much interested to do in their travel plan. However, current recommendation systems are unable to fetch required features from travelers and destination places. Moreover, current systems are lacking to recommend destination places by considering social interest and their experience (i.e. recommendations by considering many traveler’s interests, for example, when two travelers interest matches the places visit by the first traveler can be suggested to the second traveler or vice-versa and travelers experience concerning particular destination place). To address the issues and problems of the current system, we propose and implement a tourist recommendation system which is termed as Average Cumulative Rating (ACR) that supports the extraction of rating and experience which is in the form of text description. The overall score is computed based on rating and traveler experience and feed to the traditional Matrix Factorization (MF) technique for providing custom results for travelers.
When SDN and blockchain shake hands
Authors: Latah Majd , Kalkan Kubra
Published: August 2022

A survey of recent efforts to combine SDN and BC shows promising results and points to directions for future research.
Polymorphic wireless receivers
Authors: Restuccia Francesco , Melodia Tommaso
Published: August 2022

Today's wireless technologies are largely based on inflexible designs, which make them inefficient and prone to a variety of wireless attacks. To address this key issue, wireless receivers will need to (i) infer on-the-fly the physical layer parameters currently used by transmitters; and if needed, (ii) change their hardware and software structures to demodulate the incoming waveform. In this paper, we introduce
PolymoRF
, a deep learning-based polymorphic receiver able to reconfigure itself in real time based on the inferred waveform parameters. Our key technical innovations are (i) a novel embedded deep learning architecture, called
RFNet
, which enables the solution of key waveform inference problems, and (ii) a generalized hardware/software architecture that integrates
RFNet
with radio components and signal processing. We prototype
PolymoRF
on a custom software-defined radio platform and show through extensive over-the-air experiments that
PolymoRF
achieves throughput within 87% of a perfect-knowledge
Oracle
system, thus demonstrating for the first time that polymorphic receivers are feasible.
The Atlas milestone
Authors: Denning Peter , Ibbett Roland
Published: August 2022

Celebrating virtual memory, which has made such a difference in how we approach programming, memory management, and secure computing.
A metacognitive confidence calibration (MCC) tool to help medical students scaffold diagnostic reasoning in decision-making during high-fidelity patient simulations
Authors: Garbayo Luciana S. , Harris David M. , Fiore Stephen M. , Robinson Matthew , Kibble Jonathan D.
Published: August 2022

This study demonstrates the feasibility of a metacognitive confidence calibration tool (MCC) to assess and promote novices in the learning of diagnostic reasoning and treatment decisions on patient care in real time during high-fidelity patient simulations while comparing confidence and accuracy data and identifying students’ scientific misconceptions. Results revealed the presence of overconfidence bias, overtreatment, and the misconception of metabolic acidosis as the cause of the patient’s problems rather than a consequence of untreated diabetes mellitus.
Age and sex hormones modulate left ventricle regional response to angiotensin II in male and female mice
Authors: Walsh-Wilkinson Élisabeth , Aidara Mohamed Lamine , Morin-Grandmont Audrey , Thibodeau Sara-Ève , Gagnon Juliette , Genest Mathieu , Arsenault Marie , Couet Jacques
Published: August 2022

We propose a new method for the study of regional strain data by analyzing individually the software-generated 48 regions of interest (ROI) from an LV wall tracing in B-mode. This helps obtain a more comprehensive profile of strain data. Using these new tools, we studied in mice how sex, sex hormones, age, or a pathological stress influenced strain parameters. We show that for similar cardiac hypertrophy, regional strain shows important differences related to sex, sex hormones, and age.
Sex differences in human running performance: smaller gaps at shorter distances?
Authors: McClelland Emily L. , Weyand Peter G.
Published: August 2022

Sex performance differences for sprint running bursts are small (<6%), but widen as the distance sprinted increases (range: 5.6%–14.2%). The distance dependency identified here for sprinting differs from the prevailing literature view of between-sex performance differences for the human running of 10%–12% regardless of distance. The variable sprint margins observed reflect the relative performance benefits shorter females have for brief, acceleration-dependent efforts versus those taller males have for longer steadier-speed sprint efforts.
Educational Evaluation Information System Model of Political Ideological Big Data in Colleges and Universities
Authors: Cao Chang
Published: August 2022

This study presents the fundamental guidelines for developing an evaluation index system for political thought education in light of the shortcomings of the current system, including its limited evaluation objectives, singular evaluation methods, lack of pertinence of evaluation indexes, and subjectivity of evaluation standards. In parallel, big data-related technologies are being used to determine the indicators and index weight coefficients of the evaluation system of political thought teaching in institutions of higher learning. This is done on the basis of earlier research on big data and teaching evaluation. The decision tree method is used in this study to create a prediction model for teaching evaluation, which is then pruned based on “relative support” to categorize the sample data. The decision tree method is aimed at a large number of teachers’ information databases. The model is validated at the end. According to the experimental findings, this educational evaluation system is stable to a degree of 94.6 percent, and its evaluation accuracy can reach a level of 95.33 percent. The validity and reliability of the educational evaluation system developed in this study are confirmed by this result. Big data can therefore be used to evaluate political thought instruction in higher education institutions, which offers some fresh perspectives for related research.
Construction and Research of Converged Media Random Matrix Model and Multivariate Evaluation System
Authors: Wei Xiang , Zhang Yujuan , Feng Shuo
Published: August 2022

According to the indicators, the evaluation index system of convergent media communication efficiency is constructed, and its corresponding hierarchical structure model is constructed. According to the nine-level scale in the analytic hierarchy process, the indicators are scored by designing an expert questionnaire with weights of relevant indicators, and a pairwise comparison judgment matrix is constructed from the questionnaire data obtained through the expert consultation questionnaire. This paper uses the YAAHP analytic hierarchy process software to calculate the matrix results and test the final results. If the obtained results are within the consistency test range, it will pass; otherwise it will not pass. The fine-tuning matrix is processed, and the weight vector is calculated to obtain the final indicator weight result. After studying a class of using matrix factorization to enhance the independence of random matrix column vectors, a Gram-Schmidt orthogonalization of random matrices is proposed to minimize the intrinsic correlation of the matrix. After analyzing the reconstruction characteristics of the orthogonal matching pursuit algorithm, a new signal reconstruction algorithm is given by combining the new optimization method with the reconstruction algorithm. Referring to the relevant theories of physics and molecular dynamics, this paper draws on the relevant description of the information fusion theory, introduces the basic concepts of “energy” and “collision,” and constructs the energy description model before data object fusion and the collision model when data objects are fused. By combining the practice of the radio mobile client log access and record data resources that have completed situation assessment and state transition, it effectively handles many low-efficiency regional data object processing problems generated in the process of data object fusion and deepens data object fusion.
Clinical Value Screening, Prognostic Significance, and Key Gene Identification of TrkB in Laryngeal Carcinoma
Authors: Zhang Jing , Hu Xiaoyan , Liu Shuang , He Yuxiao , Lyu Liangge , Jiang Liang
Published: August 2022

Purpose. Using human gene chip expression profiling technology to screen out downstream genes related to TrkB regulation in laryngeal cancer cells. Methods. Using the Hep-2 TrkB shRNA cell line, divide it into an experimental group (shNTRK2) and a control group (PLKO1), and use the human gene expression microarray to screen out the differential genes. Then, select 10 upregulated genes and 10 downregulated genes from the differential genes, and use RT-PCR to verify whether the screening results of human gene expression microarray profiles are reliable. Use GO, KEGG, and miRNA enrichment analyses, PPI network diagram, etc., to analyze the differential genes and further screen out the key genes. Results. A total of 318 differential genes (87 upregulated genes and 231 downregulated genes) were screened in laryngeal cancer cells. Use RT-PCR for the 10 upregulated differential genes (DMKN, FHL1, FOXN4, GGNBP1, HOXB9, ABCB1, TNFAI, RGS2, LINC01133, and FGG) and 10 downregulated differential genes (CHI3L1, FMOD, IGFBP1, IRF5, SPARC, NPAS4, TRPS1, TRAP, COL8A1, and DNER), and the results are consistent with the chip results, confirming the accuracy of the chip results; GO analysis results show that the downstream differential genes (DEGs) regulated by TrkB are mainly involved in biological processes such as retinol metabolic process, diterpenoid metabolic process, and regulation of cell-substrate adhesion. DEGs mainly affect cytoskeletal protein binding, serotonin-activated cation-selective channel activity, and sphingosine molecular functions. DEGs are mainly enriched in the cell periphery, secretory granule, cytoplasmic membrane-bounded vesicle lumen, blood microparticle, and other molecular components. The results of disease enrichment analysis show that the downstream differential genes regulated by TrkB are mainly involved in atypical hemolytic uremic syndrome, hematologic disease, meningococcal disease, lung cancer, susceptibility, asthma, and other diseases. The PPI network diagram results showed 7 hub genes, and then, we used GO analysis and KEGG enrichment analysis to see the biological process, cell component, molecular functions, and biological pathways. Conclusion. Gene chip technology was used to screen out the differential genes of TrkB epigenetic modification in the Hep-2 cell line, and seven key genes (ALDH1A1, SDR16C5, PIK3R1, PLCG2, IL2RG, PIK3CD, and SPARC) were further screened using bioinformatics technology.
MYC Promotes LDHA Expression through MicroRNA-122-5p to Potentiate Glycolysis in Hepatocellular Carcinoma
Authors: Wang Xiaofei , Zhang Penghua , Deng Ke
Published: August 2022

MYC is a notorious oncogene in a vast network of malignancies, whereas liver-specific microRNA- (miR-) 122-5p is downregulated in hepatocellular cancer (HCC). Here, we studied the possible correlation between these two and their involvement in glycolysis in HCC. MYC was overexpressed in HCC tissues and cells compared to normal liver tissues and normal hepatocytes NHC, which predicted a poor survival of HCC sufferers. Functional assays demonstrated that silencing of MYC inhibited the glycolysis in HCC cells, as evidenced by significantly weaker glucose consumption, lactate production, adenosine triphosphate (ATP) levels, and downregulated HK1 and HK2 protein expression. Moreover, MYC bound to the miR-122-5p promoter and repressed the miR-122-5p expression. Rescue experiments showed that miR-122-5p inhibitor rescued the diminished glycolysis after MYC silencing. In addition, lactate dehydrogenase (LDHA) was identified as a downstream target of miR-122-5p. The overexpression of LDHA mitigated the effects of si-MYC and miR-122-5p mimic on glycolysis of HCC cells, respectively. In conclusion, the MYC/miR-122-5p/LDHA axis modulates glycolysis in HCC cells and possibly affects HCC progression.
Novel Type I Half Logistic Burr-Weibull Distribution: Application to COVID-19 Data
Authors: Alshanbari Huda M. , Odhah Omalsad Hamood , Almetwally Ehab M. , Hussam Eslam , Kilai Mutua , El-Bagoury Abdal-Aziz H.
Published: August 2022

In this work, we presented the type I half logistic Burr-Weibull distribution, which is a unique continuous distribution. It offers several superior benefits in fitting various sorts of data. Estimates of the model parameters based on classical and nonclassical approaches are offered. Also, the Bayesian estimates of the model parameters were examined. The Bayesian estimate method employs the Monte Carlo Markov chain approach for the posterior function since the posterior function came from an uncertain distribution. The use of Monte Carlo simulation is to assess the parameters. We established the superiority of the proposed distribution by utilising real COVID-19 data from varied countries such as Saudi Arabia and Italy to highlight the relevance and flexibility of the provided technique. We proved our superiority using both real data.
Lingual Raynaud’s Phenomenon after Surgical and Radiotherapeutic Intervention for Oral Squamous Cell Carcinoma
Authors: Murphy Nicholas J. , Kabbani Loay S. , Shepard Alexander D. , Siddiqui Farzan
Published: August 2022

Raynaud’s phenomenon of the tongue after radiation therapy with or without chemotherapy is an exceedingly rare complication. Symptoms are similar to Raynaud’s disease of other sites and involve pallor and discomfort on exposure to cold temperatures that resolve with rewarming. Presentation occurs approximately 18-24 months after radiotherapy on average and can usually be managed effectively with lifestyle modification and pharmacotherapy. Here, we present a case of lingual Raynaud’s following surgery and adjuvant radiation therapy in a patient with squamous cell carcinoma of the oral cavity.
Classification and Interpretability of Mild Cognitive Impairment Based on Resting-State Functional Magnetic Resonance and Ensemble Learning
Authors: Hu Mengjie , Yu Yang , He Fangping , Su Yujie , Zhang Kan , Liu Xiaoyan , Liu Ping , Liu Ying , Peng Guoping , Luo Benyan
Published: August 2022

The combination and integration of multimodal imaging and clinical markers have introduced numerous classifiers to improve diagnostic accuracy in detecting and predicting AD; however, many studies cannot ensure the homogeneity of data sets and consistency of results. In our study, the XGBoost algorithm was used to classify mild cognitive impairment (MCI) and normal control (NC) populations through five rs-fMRI analysis datasets. Shapley Additive exPlanations (SHAP) is used to analyze the interpretability of the model. The highest accuracy for diagnosing MCI was 65.14% (using the mPerAF dataset). The characteristics of the left insula, right middle frontal gyrus, and right cuneus correlated positively with the output value using DC datasets. The characteristics of left cerebellum 6, right inferior frontal gyrus, opercular part, and vermis 6 correlated positively with the output value using fALFF datasets. The characteristics of the right middle temporal gyrus, left middle temporal gyrus, left temporal pole, and middle temporal gyrus correlated positively with the output value using mPerAF datasets. The characteristics of the right middle temporal gyrus, left middle temporal gyrus, and left hippocampus correlated positively with the output value using PerAF datasets. The characteristics of left cerebellum 9, vermis 9, and right precentral gyrus, right amygdala, and left middle occipital gyrus correlated positively with the output value using Wavelet-ALFF datasets. We found that the XGBoost algorithm constructed from rs-fMRI data is effective for the diagnosis and classification of MCI. The accuracy rates obtained by different rs-fMRI data analysis methods are similar, but the important features are different and involve multiple brain regions, which suggests that MCI may have a negative impact on brain function.
A Systematic Review with Meta-Analysis of Comparative Efficacy and Safety of Risankizumab and Ustekinumab for Psoriasis Treatment
Authors: Yu Qianying , Ge Xiaopei , Jing Mingyi , Mi Xiongfei , Guo Jing , Xiao Min , Lei Qing , Chen Mingling
Published: August 2022

Biological targeted therapy serves as a new alternative treatment for psoriasis due to its minimal side effects. This study is aimed at examining the drug effectiveness and safety of risankizumab and ustekinumab for psoriasis treatment, so as to provide a reference for clinical decision-making. Databases from Embase, Web of Science, PubMed, and Cochrane Library were gathered, starting from inception to March 1, 2022, for randomized controlled trials regarding risankizumab and ustekinumab for psoriasis treatment. All retrieved articles were carefully selected in strict accordance with a set of inclusion and exclusion criteria. Stata 15.0 and RevMan 5.4 were applied to perform meta-analysis and risk of bias assessment. A total of two trials with three NCTs were selected, with 384 participants in the risankizumab group and 140 participants in ustekinumab. Meta-analysis showed that in the long-term and short-term PASI100, risankizumab was more effective than ustekinumab (

RR
=
2.27

, 95% CI (1.77, 2.90),

p
<
0.05

;

RR
=
2.33

, 95% CI (1.75, 3.08),

p
<
0.05

). In PASI90,

RR
=
1.77

, 95% CI (1.54, 2.03), and

p
<
0.05

and

RR
=
1.72

, 95% CI (1.48, 2.00), and

p
<
0.05

. In short-term PASI75,

RR
=
1.23

, 95% CI (1.13, 1.34), and

p
<
0.05

. In sPGA of 0, the results at week-16 and week-52 showed that risankizumab was significantly more effective than ustekinumab (

RR
=
2.24

, 95% CI (1.67, 3.01),

p
<
0.05

;

RR
=
2.30

, 95% CI (1.80, 2.95),

p
<
0.05

). Risankizumab was significantly more effective than ustekinumab in improving the quality of life and PSS scores (

RR
=
1.48

, 95% CI (1.26, 1.75),

p
<
0.05

;

RR
=
2.01

, 95% CI (1.41, 2.85),

p
<
0.05

). Nevertheless, risankizumab and ustekinumab did not show significant difference in the incidence of adverse responses (

RR
=
1.02

, 95% CI (0.75, 1.39),

p
>
0.05

). Risankizumab was more effective than ustekinumab for the treatment of psoriasis. The adverse reactions of both risankizumab and ustekinumab were similar and could be tolerated. Risankizumab might be a better alternative option for their treatment.
Creation Characteristics of Music Piano Arrangement Based on Distributed Sensors
Authors: Cao Chuan
Published: August 2022

Music piano arrangement is a popular creation method among the public at present, which can play a role in the promotion of traditional culture and the combination of popular culture. However, the traditional method of analyzing the creative characteristics of musical piano arrangements has limitations, and it is not suitable for today’s public review era. In this paper, to address the limitations, distributed sensor technology is employed. It utilizes the Top-k query method, KNN (one of the most basic approaches in data mining classification technology is the proximity algorithm, often known as the K closest neighbor classification algorithm) algorithm, and fused balance algorithm to classify the creative features of musical piano arrangements. It collects 50 classic piano arrangements and studies its compositional style, melody, and tone. The data results showed that, for the style characteristics, each algorithm has a high recognition rate for passion songs, and the three errors are small; for the melody characteristics, because the KNN algorithm has a delay in determining the rising tempo, the overall melody is not grasped correctly, and the Top-k query method is not sensitive to the descending tempo, and the recognition rate is low; for the tonal characteristics, the Top-k query method has a larger range of low-key judgments, so that the number of identifications is larger. As for the energy consumption of the system, as the number of nodes increases, the energy consumption of the three algorithms also increases gradually. Among them, the Top-k query method has the largest energy consumption, exceeding 400 W at 180 nodes, and its energy consumption growth rate continues to increase. The fusion algorithm fluctuates greatly, while the KNN algorithm is stable. This shows that KNN algorithm is more stable in terms of system performance, and its characteristics can be better summarized in the creation and research of piano adaptation.
Tooth CT Image Segmentation Method Based on the U-Net Network and Attention Module
Authors: Tao Sha , Wang Zhenfeng
Published: August 2022

Traditional image segmentation methods often encounter problems of low segmentation accuracy and being time-consuming when processing complex tooth Computed Tomography (CT) images. This paper proposes an improved segmentation method for tooth CT images. Firstly, the U-Net network is used to construct a tooth image segmentation model. A large number of feature maps in downsampling are supplemented to downsampling to reduce information loss. At the same time, the problem of inaccurate image segmentation and positioning is solved. Then, the attention module is introduced into the U-Net network to increase the weight of important information and improve the accuracy of network segmentation. Among them, subregion average pooling is used instead of global average pooling to obtain spatial features. Finally, the U-Net network combined with the improved attention module is used to realize the segmentation of tooth CT images. And based on the image collection provided by West China Hospital for experimental demonstration, compared with other algorithms, our method has better segmentation performance and efficiency. The contours of the teeth obtained are clearer, which is helpful to assist the doctor in the diagnosis.
Network-Based Pharmacological Study on the Mechanism of Action of Buxue Liqi Huatan Decoction in the Treatment of Lung Cancer
Authors: Wei Huabing , Zhou Lihuang , Zhao Xiaojing , Xie Feng
Published: August 2022

Objective. This study aimed to investigate the mechanism of action of Buxue Liqi Huatan decoction against lung cancer through network pharmacology. Methods. The chemical composition and targets of all the drugs in the Buxue Liqi Huatan decoction were obtained through the Database and Systematic Analysis Platform of Traditional Chinese Medicine Pharmacology, the Integrated Database of Traditional Chinese Medicine, and by screening lung cancer targets with the gene map and OMIM database. The targets were then imported into Cytoscape 3.7.2 to build a target network of active ingredients and imported into the STRING database to build a protein-protein interaction network. The BisoGenet plug-in in Cytoscape 3.7.2 was used for network topology analysis. Genetic ontology (GO) enrichment analysis and Kyoto Encyclopedia of Gene and Genomes (KEGG) enrichment analysis were performed on potential targets of the Buxue Liqi Huatan decoction for lung cancer using the R-language Bioconductor platform, and results were imported from Cytoscape 3.7.2 to obtain the KEGG network connection diagram via the Autodock molecular docking software. Results. A total of 238 chemical components and 694 disease targets were obtained, including 133 intersecting targets. The key targets included TP53, AKT1, and MYC, and the GO functional analysis was mainly related to oxidative and cellular oxidative stress, apoptotic signaling, and antibiotic response. The results showed that the key target with the best binding performance was TP53. Conclusion. The treatment of lung cancer with blood-supplementing, qi-transforming, and phlegm-transforming soups works through multiple components and targets. The active ingredients include quercetin, luteolin, naringenin, and baicalein. Among them, the core proteins of PPI protein interaction mainly include TP53, AKT1, MYC, EGRF, CCNB1, and ESR1. The enrichment analysis results show that the TNF signal pathway, PI3K-Akt signal pathway, AGE-RAGE, IL-17, etc., are the main signal pathways of Buxue Liqi Huatan decoction in treating lung cancer. This lays the foundation for further study of its mechanism.
Protection of Ethnic Cultural Value: A Case Study of VR Scene Construction in Basha Village
Authors: Li Meng
Published: August 2022

Digitizing ethnic villages through VR technology is helpful for putting limited resources into the most urgent protection projects at this stage. In this paper, Basha village in western Hunan of China is selected as the carrier, and VR technology is used to simulate its virtual village scene. In this paper, ArcGIS is used to show the distribution of villages, through SketchUp software, 3D modeling of the buildings in the village is carried out, which is imported into Lumion platform and optimized, and finally the VR scene of Basha village is established. Through professional analysis tools, accurate reduction scale, and rational analysis and decision-making, it can not only open up a new situation for the protection of national history and culture, but also better promote the construction and renewal of new countryside.
Edaravone Dexborneol Downregulates Neutrophil Extracellular Trap Expression and Ameliorates Blood-Brain Barrier Permeability in Acute Ischemic Stroke
Authors: Huang Yuanxiang , Zhang Xiangjian , Zhang Cong , Xu Wenting , Li Wenshuo , Feng Zixin , Zhang Xianglan , Zhao Keke
Published: August 2022

Background. Our previous work has shown that inflammatory processes play a detrimental role in the pathophysiology of acute ischemic stroke (AIS). Neutrophil extracellular traps (NETs) have been recognized as a key contributor to the proinflammatory response in AIS and could aggravate blood-brain barrier (BBB) damage. Recently, experimental and clinical researches showed that Edaravone Dexborneol (Eda.B), which is comprised of two active ingredients, Edaravone and (+)-Borneol, was effective in treatment of AIS. However, it is not clear whether the effects of Eda.B against AIS are related to NETs and BBB permeability. Methods. Experiment 1 was to detect the effects of Eda.B in AIS patients. Serum samples of volunteers and AIS patients were collected before and 3 days after Edaravone Dexborneol treatment. Markers of NETs and occludin were detected by ELISA kit. Experiment 2 was to explore the effects of Eda.B on experimental stroke mice. Male C57BL/6 mice were subjected to distal middle cerebral artery occlusion (MCAO) and treated with vehicle, Eda.B, or DeoxyribonueleaseI (DNase I). After stroke, the neurobehavioral tests, infarct volume, and cerebral blood flow evaluation were determined. Leakage of Evans blue was to assess the integrity of BBB. Western blot, real-time quantitative polymerase chain reaction (RT-qPCR), and immunofluorescence were used to examine the expression of NETs and tight junction- (TJ-) associated proteins. Results. Eda.B significantly improved neurological function and cerebral blood flow but reduced infarct volume after experimental stroke. Eda.B downregulated level of NETs in serum samples of AIS patients and tissue samples of MCAO mouse cortex. Eda.B and DNase I alleviated BBB permeability by upregulating TJ-associated proteins. Conclusion. NETs are related to the early stage of AIS. Eda.B exerted neuroprotective effects and ameliorated BBB permeability after AIS.
5G Edge Computing Access Node Selection Algorithm Based on Energy Efficiency and Delay
Authors: Hu Wenjian , Guo Siyan , He Liping , Wang Lin , Yuan Yubao
Published: August 2022

In order to address the dissipation of energy efficiency in 5G edge computing, and the problem of network delay, better improve the quality of user service, considering the data aggregation delay while improving the network energy efficiency. The author proposes a 5G edge computing access node selection algorithm based on energy efficiency and delay; through the energy efficiency and delay balanced data collection mechanism (EEDBDG), a new dynamic tree is used to organize the network topology, eliminating the hot zone problem; nodes dynamically choose routes and take turns acting as the root of the tree, which collects data and communicates directly with the base station. At the same time, three data collection strategies are proposed for different latency and energy efficiency requirements: delay optimal algorithm (EEDBDG-D), energy efficiency optimal algorithm (EEDBDG-E), and energy efficiency delay balance algorithm (EEDBDG-M). Experimental results show that, when the communication radius of nodes is limited, EEDBDG balances the energy consumption of nodes, prolongs the network life time, and shows outstanding performance in energy saving and time saving. Compared with GSEN, in the best case, the network lifetime of EEDBDG-E is increased by 72%, and the convergence delay of EEDBDG-D is reduced by 74%. Conclusion. The algorithm can effectively reduce the energy dissipation and delay of edge computing.
Effects of Acupuncture on Neuropathic Pain Induced by Spinal Cord Injury: A Systematic Review and Meta-Analysis
Authors: He Kelin , Hu Rong , Huang Yi , Qiu Bei , Chen Qinqin , Ma Ruijie
Published: August 2022

Introduction. Neuropathic pain is a commonly seen symptom and one of the most intractable comorbidities following spinal cord injury (SCI). Acupuncture has been widely used for neuropathic pain after SCI in clinical settings. There is no systematic review or meta‐analysis evaluating the efficacy of acupuncture in the treatment of SCI-induced neuropathic pain. Thus, this study aimed to conduct a systematic review and meta-analysis to assess the efficacy of acupuncture on SCI-induced neuropathic pain. Methods. Seven databases were comprehensively searched, including PubMed, the Cochrane Library, the Web of Science, the China National Knowledge Infrastructure (CNKI), the Chinese Biomedical Literature Service System (SinoMed), the Wanfang Database, and the Chinese Scientific Journals Database (VIP) from their inception to 30 September 2021. Two independent reviewers evaluated the eligibility of the data retrieved based on the pre-established eligibility criteria and assessed the methodological quality of the included studies using the Cochrane Risk of Bias Tool. The outcome indexes in this study included the visual analogue scale, the numeric rating scale, the present pain intensity, and the pain region index. Sensitivity and subgroup analyses were also performed to specifically evaluate the intervention effects. In addition, publication bias was analyzed. Results. Six randomized controlled trials (145 participants in the experimental groups and 141 participants in the control groups) were identified that evaluated the application of acupuncture for neuropathic pain after SCI and were included in this study. The results of our study revealed that acupuncture had a positive effect on the pain severity (standardized mean difference (SMD): −1.40, 95% confidence interval (CI): −2.23; −0.57), the present pain intensity (MD = −0.61, 95% CIs = −0.98; −0.23), and the pain region index (MD = −3.04, 95% CI = −3.98; −2.11). In addition, sensitivity analyses showed that these results were robust and stable. Subgroup analyses indicated that electroacupuncture (EA) had better effects on SCI-induced neuropathic pain. However, a publication bias was observed. Conclusion. Available evidence appears to suggest that acupuncture may have a role in SCI-induced neuropathic pain management, but this remains to be determined.
Noise-Resistant Video Channel Identification
Authors: Wang Mingkai , Xie Zengkun , Tang Xiangdong , Chen Fei
Published: August 2022

As the video streaming traffic grows exponentially nowadays, variable bitrate (VBR) encoding has been widely utilized by modern live video streaming service providers, such as YouTube, TikTok, and Twitch. However, video bitrate can be a delicate fingerprint of the video streaming, leading to risks of privacy leakage. There are several studies that attempt to eavesdrop the privacy from encrypted video streaming, but most of them presume strict requirements on the implementation environments and have great limitations when noise interference exists. Actually, the video traffic from the multimedia edge server is distinct from interapplication traffic flows due to device customization and can be identified even if there are noise interferences or the victim in a weak network condition. In this paper, a video traffic identification method is proposed to identify the encrypted video streaming from multimedia edge server under the interference of irrelevant traffic flows. Initially, we use an interapplication filter to identify the traffic from the edge server. Then, a longest-common-subsequence (LCS)-based method is developed for similarity matching to resist the noise interference from unpredictable burst traffic and network environment variations. In order to evaluate the system performance, we setup the prototype system with an AWS EC2 server and a raspberry pi device, then utilize the real-world trace data for pushing movies to victims. The experimental results show that the accuracy of our proposed strategy can reach 89.1% within 140 seconds eavesdropping even mixed with 14% noise interference.
Visual Feature Evaluation of Shenyang Greenway Landscape Based on Deep Learning
Authors: Pan Tianyang , Jiang Min
Published: August 2022

At present, the research on the visual characteristics of greenway landscape is mostly focused on the evaluation of beauty degree, landscape preference, and recreation preference and mainly on the overall macroscopic evaluation of a single greenway or typical spatial research in some areas, while less attention is paid to the overall characteristics of urban greenway landscape and the differences in visual characteristics of different types of greenway landscape. The emergence of new data and new technologies such as street view, Baidu map, and deep learning provides the possibility to study the visual characteristics of greenway landscapes in large scale and full sample. The study of greenway landscape based on large deep learning can effectively refine the overall pattern of visual characteristics of greenway landscape and reveal the differences of visual characteristics of different types of greenways and their key factors, so as to provide support for the planning and design of greenway landscape and landscape appearance enhancement.
Modern Package Design Using Digital 3D Image Processing Technique
Authors: Feng Shengying , Li Dingfang , Wen Chen , Bu Naifeng , Gao Jing
Published: August 2022

In the extensive age, dear designate perplexity and relatively supercilious show charge in the traditive parcel extend project composition, the double discriminator GAN is ply to the bale work indicate composition. On the basis of BicycleGAN, a topic discriminator is added, and the analogous privation sine and external province are reformed. In the proof, the input aim is a likeness suit of “margin idol + source cast,” and the product goal is the copy with the top 10 chance of genuineness. The trial arise are appraised from the three aspects of variegation, PSNR importance, and SSIM appraise. The arise shows that the effigy produced by the double discriminator GAN not only has improved variegation but also better peculiarity of show lowdown. Therefore, it is practicable to devote the double discriminator GAN to the look sketch of parcel products. On the one side, it can stipulate designers with sketch breath, and on the other side, it can also rescue manpower and significant cause and disapprove duty ability.
Intelligent Computing of Levenberg-Marquard Technique Backpropagation Neural Networks for Numerical Treatment of Squeezing Nanofluid Flow between Two Circular Plates
Authors: Ullah Hakeem , Fiza Mehreen , Zahoor Raja Muhammad Asif , Khan Imran , Shoaib Muhammad , Al-Mekhlafi Seham M.
Published: August 2022

This study presents new techniques based on the artificial intelligence neural network with Levenberg-Marquardt Scheme with backpropagation (ANN-LMS). The boundary value problem BVP is obtained from the governing equations of the flow model. Along with ANN-LMS, the semianalytical method namely the optimal homotopy analysis method (OHAM) is used for validating the results. ANN-LMS optimized the absolute error and increased the accuracy of the solution. The effect of physical parameters is discussed with the help of plots and tables.
Gear Fault Diagnosis and Life Prediction of Petroleum Drilling Equipment Based on SOM Neural Network
Authors: Lu Linzhu , Liu Jie , Huang Xin , Fan Yongcai
Published: August 2022

In order to solve the problem that variable working conditions and fault types cannot be diagnosed in gear fault diagnosis of petroleum drilling equipment, four kinds of faults, namely, gear broken tooth, gear crack, gear pitting, and gear wear, are studied in this paper. Based on the SOM neural network algorithm, an intelligent diagnosis model of gear fault is proposed, and the PCA method is used to reduce data dimension and fuse features. The state index of life prediction is determined, and the remaining service life prediction of gear transmission system is predicted based on exponential degradation model. The results show that the accuracy of the SOM model for fault diagnosis is high, and the bearing in gearbox can be replaced or repaired in advance according to the residual life curve, so as to achieve the purpose of predictive maintenance.