bluuebunny/crossref_metadata_2025 huggingface dataset:
Hadronic molecules composed of a doubly charmed tetraquark state and a charmed meson
Authors: Pan Ya-Wen , Wu Tian-Wei , Liu Ming-Zhu , Geng Li-Sheng
Published: October 2022

The three pentaquark states, $$P_c(4312)$$

P
c

(
4312
)

, $$P_c(4440)$$

P
c

(
4440
)

and $$P_c(4457)$$

P
c

(
4457
)

, discovered by the LHCb Collaboration in 2019, can be arranged into a complete heavy quark spin symmetry multiplet of hadronic molecules of $$\bar{D}^{(*)}\Sigma _{c}^{(*)}$$

D

¯

(

∗
)

Σ

c

(

∗
)

. In the heavy quark mass limit, the $$\Sigma _{c}^{(*)}$$

Σ

c

(

∗
)

baryons can be related to the doubly charmed tetraquark states of isospin 1, i.e., $$T_{\bar{c}\bar{c}}^{(*)}$$

T

c

¯

c

¯

(

∗
)

( $$T_{\bar{c}\bar{c}}^{0}$$

T

c

¯

c

¯

0

, $$T_{\bar{c}\bar{c}}^{1}$$

T

c

¯

c

¯

1

, $$T_{\bar{c}\bar{c}}^{2}$$

T

c

¯

c

¯

2

), via heavy antiquark diquark symmetry, which dictates that the $$\bar{D}^{(*)}\Sigma _{c}^{(*)}$$

D

¯

(

∗
)

Σ

c

(

∗
)

interactions are the same as the $$\bar{D}^{(*)}T_{\bar{c}\bar{c}}^{(*)}$$

D

¯

(

∗
)

T

c

¯

c

¯

(

∗
)

interactions up to heavy antiquark diquark symmetry breakings. In this work, we employ the contact-range effective field theory to systematically study the $$\bar{D}^{(*)}T_{\bar{c}\bar{c}}^{(*)}$$

D

¯

(

∗
)

T

c

¯

c

¯

(

∗
)

systems, and we show the existence of a complete heavy quark spin symmetry multiplet of hadronic molecules composed of a doubly charmed tetraquark state and a charmed meson. These are a new kind of hadronic molecules and, if discovered, can lead to a better understanding of the many exotic hadrons discovered so far. In addition, we summarise the triply charmed hexaquark states formed by different combinations of hadrons. In particular, we show that $$\bar{\Omega }_{ccc}{p}$$

Ω

¯

ccc

p

system can bind by the Coulomb force, which is analogous to a hydrogenlike atom.
Temporally Stochastic Cellular Automata: Classes and Dynamics
Authors: Roy Souvik , Paul Subrata , Das Sukanta
Published: October 2022

This article introduces temporally stochastic cellular automata where a cell of the cellular system can be updated using one of the two elementary cellular automata rules, say [Formula: see text] and [Formula: see text]. The [Formula: see text] is the default rule and [Formula: see text] is temporally applied to the overall system with some probability that acts as noise to the system. As the mathematical analysis of such system is a difficult task, we use qualitative and quantitative simulations to study the dynamics of these temporally stochastic cellular automata. We are specially interested to exploring if it is possible that two periodic (resp. chaotic) rules together depict chaotic (resp. periodic) dynamics. To answer these questions, we fully classify temporally stochastic cellular automata. The study further observes phase transition and various types of class transition in the temporally stochastic cellular automata.
Complex Dynamics and Sliding Bifurcations of the Filippov Lorenz–Chen System
Authors: Zhou Hao , Tang Sanyi
Published: October 2022

In this paper, we propose a Filippov switching model which is composed of the Lorenz and Chen systems. By employing the qualitative analysis techniques of nonsmooth dynamical systems, we show that the new Filippov system not only inherits the properties of the Lorenz and Chen systems but also presents new dynamics including new chaotic attractors such as four-wing butterfly attractor, Lorenz attractor with sliding segments, etc. In particular, we find that different new attractors can coexist such as the coexistence of two-point attractors and chaotic attractor, the coexistence of two-point attractors and quasi-periodic solution, the coexistence of transient transition chaos and quasi-periodic solution. Furthermore, nonsmooth bifurcations and numerical analyses reveal that the proposed Filippov system has a series of new sliding bifurcations including a symmetric pair of sliding mode bifurcations, a symmetric pair of sliding Hopf bifurcations, and a symmetric pair of Hopf-like boundary equilibrium bifurcations.
Hyperchaotic Oscillation and Multistability in a Fourth Order Smooth Chua System with Implementation Using No Analog Multipliers
Authors: Zhu Lei , Pan Minghai
Published: October 2022

Abundant dynamical behaviors and succinct realization forms are of great significance for nonlinear circuits and systems. Hyperchaos represents more complex oscillation mode compared with chaos, while multistability means more complex essential features compared with robustness. And the coexistence of the two is rare but interesting. Based on the classic Chua model, a fourth order smooth Chua system is constructed through utilizing linear feedback control method in this article. The introduction of hyperbolic sine nonlinearity remarkably simplifies the physical realization form for the new system. The two interesting nonlinear phenomena of hyperchaotic oscillation and multistability are discovered by adjusting system parameters. Dynamic analyses including bifurcation diagrams and Lyapunov exponent spectra comprehensively reveal the evolution of oscillatory behaviors brought by the variation of system parameters, whereupon more attractors such as periodic attractors, chaotic attractors in different oscillation scales, coexisting quasi-periodic attractors, coexisting multiple attractors and coexisting periodic attractors are found. And the attractor morphologies of this system are rare and significantly different from those in the reported Chua circuits and systems. Hardware circuit experiments without using analog multipliers are performed from a four-layer printed circuit board, which efficiently verify the simulated dynamical behaviors within the acceptable deviation.
A Chaotic Image Encryption Scheme Based on Genetic Central Dogma and KMP Method
Authors: Sha Yuwen , Bo Sun , Yang Chenxiao , Mou Jun , Jahanshahi Hadi
Published: October 2022

In this paper, an image cryptosystem based on genetic central dogma (GCD), Knuth–Morria–Pratt (KMP) algorithm and a chaotic system is developed. The KMP algorithm is firstly used to bind DNA strings to obtain the next array, which participates in the design of the chaotic initial condition, and then the secure chaotic sequences are produced by employing the sliding idea in pattern string matching. In the present procedure, a DNA-level two-way pixel’s shuffle is achieved by a shared stack push operation and it is adopted in the permutation module for the purpose of accelerating the overall pixel’s shuffle. Subsequently, the pixel values are substituted by simulating the process of protein synthesis in GCD, in which the DNA replication and RNA replication form the basis of the DNA-triploid mutation and new RNA mutation rules, respectively. Experimental simulations and extensive cryptanalysis fully vindicate that superior security effects in addition to satisfactory low time complexity can be simultaneously obtained by the proposed confusion-substitution scheme.
Limit Cycles of a Class of Discontinuous Piecewise Differential Systems Separated by the Curve y = xn Via Averaging Theory
Authors: Guo Zhifei , Llibre Jaume
Published: October 2022

Recently there is increasing interest in studying the limit cycles of the piecewise differential systems due to their many applications. In this paper we prove that the linear system [Formula: see text], [Formula: see text], can produce at most seven crossing limit cycles for [Formula: see text] using the averaging theory of first order, where the bounds [Formula: see text] for [Formula: see text] even and the bounds [Formula: see text] for [Formula: see text] odd are reachable, when it is perturbed by discontinuous piecewise polynomials formed by two pieces separated by the curve [Formula: see text] ([Formula: see text]), and having in each piece a quadratic polynomial differential system. Using the averaging theory of second order the perturbed system can be chosen in such way that it has [Formula: see text] or [Formula: see text] crossing limit cycles for [Formula: see text] even and, furthermore, under a particular condition we prove that the number of crossing limit cycles does not exceed [Formula: see text] (resp., [Formula: see text]) for [Formula: see text] even (resp., [Formula: see text] even). The averaging theory of second order produces the same number of crossing limit cycles as the averaging theory of first order if [Formula: see text] is odd. The main tools for proving our results are the new averaging theory developed for studying the crossing limit cycles of the discontinuous piecewise differential systems, and the theory for studying the zeros of a function using the extended Chebyshev systems.
HOW COMPANIES INNOVATE BUSINESS MODELS AND SUPPLY CHAINS FOR A CIRCULAR ECONOMY: A MULTIPLE-CASE STUDY AND FRAMEWORK
Authors: KAIPAINEN JENNI , URBINATI ANDREA , CHIARONI DAVIDE , AARIKKA-STENROOS LEENA
Published: October 2022

To implement a circular economy (CE), companies are pushed to innovate, respectively, their business models, from a micro-perspective, and their supply chains, from a meso-perspective. Despite the increasing research on both these perspectives, there is still a knowledge gap on how companies innovate business models and supply chains for circularity. In this study, we build on innovation management, circular business model (CBM), and circular supply chain (CSC) literatures and develop a theory-based framework where circularity leads to product/process/service innovation from a micro-perspective, and to possible innovation in companies’ supply chains (retaining existing chains/renewing them) from a meso-perspective. Through a multiple-case study of Finnish and Italian CE pioneer companies, we validate this framework, find evidence on interplay between CBM and CSC innovation, and identify innovation strategy variants. The framework contributes to innovation management, CBM, and CSC literature works, and encourages managers willing to adopt circularity to consider innovating simultaneously both their business models and supply chains.
Multiterminal Pathfinding in Practical VLSI Systems with Deep Neural Networks
Authors: Utyamishev Dmitry , Partin-Vaisband Inna
Published: October 2022

A multiterminal obstacle-avoiding pathfinding approach is proposed. The approach is inspired by deep image learning. The key idea is based on training a conditional generative adversarial network (cGAN) to interpret a pathfinding task as a graphical bitmap and consequently map a pathfinding task onto a pathfinding solution represented by another bitmap. To enable the proposed cGAN pathfinding, a methodology for generating synthetic dataset is also proposed. The cGAN model is implemented in Python/Keras, trained on synthetically generated data, evaluated on practical VLSI benchmarks, and compared with state-of-the-art. Due to effective parallelization on GPU hardware, the proposed approach yields a state-of-the-art-like wirelength and a better runtime and throughput for moderately complex pathfinding tasks. However, the runtime and throughput with the proposed approach remain constant with an increasing task complexity, promising orders of magnitude improvement over state-of-the-art in complex pathfinding tasks. The cGAN pathfinder can be exploited in numerous high throughput applications, such as, navigation, tracking, and routing in complex VLSI systems. The last is of particular interest to this work.
Toward Intelligent Fashion Design: A Texture and Shape Disentangled Generative Adversarial Network
Authors: Yan Han , Zhang Haijun , Shi Jianyang , Ma Jianghong , Xu Xiaofei
Published: October 2022

Texture and shape in fashion, constituting essential elements of garments, characterize the body and surface of the fabric and outline the silhouette of clothing, respectively. The selection of texture and shape plays a critical role in the design process, as they largely determine the success of a new design for fashion items. In this research, we propose a texture and shape disentangled generative adversarial network (TSD-GAN) to perform “intelligent” design with the transformation of texture and shape in fashion items. Our TSD-GAN aims to learn how to disentangle the features of texture and shape of different fashion items in an unsupervised manner. Specifically, a fashion attribute encoder is developed to decompose the input fashion items into independent representations of texture and shape. Then, to learn the coarse or fine styles hidden in the features of texture and shape, a texture mapping network and a shape mapping network are proposed to disentangle the features into different hierarchical representations. The different hierarchical representations of texture and shape are then fed into a multi-factor-based generator to generate mixed-style fashion items. In addition, a multi-discriminator framework is developed to distinguish the authenticity and texture similarity between the generated images and the real images. Experimental results on different fashion categories demonstrate that our proposed TSD-GAN may be useful for assisting designers to accomplish the design process by transforming the texture and shape of fashion items.
The Fluid Mechanics of Deep-Sea Mining
Authors: Peacock Thomas , Ouillon Raphael
Published: October 2022

Fluid mechanics lies at the heart of many of the physical processes associated with the nascent deep-sea mining industry. The evolution and fate of sediment plumes that would be produced by seabed mining activities, which are central to the assessment of the environmental impact, are entirely determined by transport processes. These processes, which include advection, turbulent mixing, buoyancy, differential particle settling, and flocculation, operate at a multitude of spatiotemporal scales. A combination of historical and recent efforts that combine theory, numerical modeling, laboratory experiments, and field trials has yielded significant progress, including assessing the role of environmental and operational parameters in setting the extent of sediment plumes, but more fundamental and applied fluid mechanics research is needed before models can accurately predict commercial-scale scenarios. Furthermore, fluid mechanics underpins the design and operation of proposed mining technologies, for which there are currently no established best practices.
Gas-Liquid Foam Dynamics: From Structural Elements to Continuum Descriptions
Authors: Stewart Peter S. , Hilgenfeldt Sascha
Published: October 2022

Gas-liquid foams are important in applications ranging from oil recovery and mineral flotation to food science and microfluidics. Beyond their practical use, they represent an intriguing prototype of a soft material with a complex, viscoelastic rheological response. Crucially, foams allow detailed access to fluid-dynamical processes on the mesoscale of bubbles underlying the large-scale material behavior. This review emphasizes the importance of the geometry and interaction of mesoscale structural elements for the description of the dynamics of entire foams. Using examples including bulk flow of foam under steady shear, interfacial instabilities, and foam fracture through bubble rupture, this article highlights the wide variety of available theoretical descriptions, ranging from network modeling approaches coupling structural element equations of motion to full continuum models with elastoviscoplastic constitutive relations. Foams offer the opportunity to develop rigorous links between such disparate descriptions, providing a blueprint for physical modeling of dynamical multiscale systems with complex structure.
The Actuation Problem
Authors: Yu Alan C.L.
Published: October 2022

The actuation problem asks why a linguistic change occurs in a particular language at a particular time and space. Responses to this problem are multifaceted. This review approaches the problem of actuation through the lens of sound change, examining it from both individual and population perspectives. Linguistic changes ultimately actuate in the form of idiolectal differences. An understanding of language change actuation at the idiolectal level requires an understanding of ( a) how individual speaker-listeners’ different past linguistic experiences and physical, perceptual, cognitive, and social makeups affect the way they process and analyze the primary learning data and ( b) how these factors lead to divergent representations and grammars across speakers-listeners. Population-level incrementation and propagation of linguistic innovation depend not only on the nature of contact between speakers with unique idiolects but also on individuals who have the wherewithal to take advantage of the linguistic innovations they encountered to achieve particular ideological projects at any given moment. Because of the vast number of contingencies that need to be aligned properly, the incrementation and propagation of linguistic innovation are predicted to be rare. Agent-based modeling promises to provide a controlled way to investigate the stochastic nature of language change propagation, but a comprehensive model of linguistic change actuation at the individual level remains elusive.
Intracellular Ion Control of WNK Signaling
Authors: Goldsmith Elizabeth J. , Rodan Aylin R.
Published: October 2022

The with no lysine (K) (WNK) kinases are an evolutionarily ancient group of kinases with atypical placement of the catalytic lysine and diverse physiological roles. Recent studies have shown that WNKs are directly regulated by chloride, potassium, and osmotic pressure. Here, we review the discovery of WNKs as chloride-sensitive kinases and discuss physiological contexts in which chloride regulation of WNKs has been demonstrated. These include the kidney, pancreatic duct, neurons, and inflammatory cells. We discuss the interdependent relationship of osmotic pressure and intracellular chloride in cell volume regulation. We review the recent demonstration of potassium regulation of WNKs and speculate on possible physiological roles. Finally, structural and mechanistic aspects of intracellular ion and osmotic pressure regulation of WNKs are discussed.
Modulations in motor unit discharge are related to changes in fascicle length during isometric contractions
Authors: Martinez-Valdes Eduardo , Negro Francesco , Botter Alberto , Pincheira Patricio A. , Cerone Giacinto Luigi , Falla Deborah , Lichtwark Glen A. , Cresswell Andrew G.
Published: October 2022

By employing ultrasound-transparent high-density EMG electrodes, we show that modulations in tibialis anterior muscle motor unit discharge rate were related to both changes in fascicle length and resultant torque. These relationships permitted the quantification of the relative delays between fluctuations in neural drive, muscle contraction, and transfer of torque via the tendon during sustained isometric dorsiflexion contractions, providing information on the conversion of neural activity into muscle force during a contraction.
Efficacy and Safety of Shengxuening Combined with Conventional Iron Supplementation in the Treatment of Anemia during Pregnancy: A Systematic Review and Meta-analysis
Authors: Li Tianhang , Wu Qian , Chen Yonggang , Zou Jili , Zhang Enjing
Published: October 2022

Background. To evaluate the efficacy and safety of Shengxuening combined with conventional iron supplementation in the treatment of anemia during pregnancy. Methods. Electronic searches of Embase, Web of Science, Cochrane Library, China Biomedical Literature Database (CBM), China Knowledge Network (CNKI), Wanfang database (Wanfang), and China Science and Technology Journal Database (VIP) were conducted. A randomized controlled trial of Shengxuening combined with conventional iron supplements for the treatment of anemia in pregnancy was included. The quality of the included trials was assessed using the Cochrane Handbook's Risk of Bias Assessment Tool (version 5.1.0), and data analysis was performed using RevMan 5.4 software and Stata 15.0 statistical software. Results. A total of 150 studies were detected and 17 studies with a total of 1741 cases were finally included. Meta-analysis results showed that the effectiveness of Shengxuening combined with conventional iron supplementation was significantly better than that of conventional iron supplementation alone, and the adverse effects were significantly reduced compared with that of iron supplementation alone, and various anemia indicators such as Hb, RBC, MCV, and MCHC and iron metabolism indicators such as SI and TSAT were also significantly increased. Conclusion. The efficacy of the combination of Shengxuening and conventional iron supplementation in the treatment of anemia in pregnancy is better than that of conventional iron supplementation alone, and the adverse effects in the experimental group are much less than those in the control group, but the quality of the included studies is not high, and more high-quality randomized controlled trials are needed for further validation.
Security Evaluation of Situational Awareness in Cyberspace Based on Artificial Neural Network-Back Propagation
Authors: Han Weihong , Nazir Hafiz Muhammad Jamsheed , Li Shudong
Published: October 2022

Computer network security has become increasingly controversial among many businesses as a result of the rise in cyber threats. Artificial neural network (ANN) is mature research in this field, whereas the traditional algorithm is slower, in feedback error, and has the disadvantage of easy convergence to local extreme value. To guide against these threats, in this paper, ANN-back propagation (BP) algorithm is used to establish the relationship between the level of cyber security situational awareness (CSA) and the perceptual parameters and quantitatively evaluate the situational awareness. This study established the ANN-back propagation (BP) to make the relationship between the level of cyber security situational awareness (CSA) and the perceptual parameters, which evaluates situational awareness. The ANN-BP with variable step size learning strategy and simulated annealing method is used for optimization to build a virtual network environment. The proposed model offers better precision, improved sensitivity, and higher (0.987%) accuracy.
A Meta-Path-Based Evaluation Method for Enterprise Credit Risk
Authors: Du Marui , Ma Yue , Zhang Zuoquan
Published: October 2022

Nowadays, small and medium-sized enterprises (SMEs) have become an essential part of the national economy. With the increasing number of such enterprises, how to evaluate their credit risk becomes a hot issue. Unlike big enterprises with massive data to analyse, it is hard to find enough primary information of SMEs to assess their financial status, which makes the credit risk evaluation result less accurate. Limited by the lack of primary data, how to infer SMEs’ credit risk from secondary data, such as information about their upstream, downstream, parent, and subsidiary enterprises, attracts big attention from industry and academy. Targeting on accurately evaluating the credit risk of the SME, in this study, we exploit the representative power of the information network on various kinds of SME entities and SME relationships to solve the problem. With that, a heterogeneous information network of SMEs is built to mine enterprise’s secondary information. Furthermore, a novel feature named meta-path feature is proposed to measure the credit risk, which makes us able to evaluate the financial status of SMEs from various perspectives. Experiments show that our proposed meta-path feature is effective to identify SMEs with credit risks.
Reservoir Forming Conditions and Enrichment Law of Tight Sandstone Gas in Upper Paleozoic in Ordos Basin
Authors: Zhang Jihua , Zhang Chi
Published: October 2022

With the popularization of natural gas and the requirement of environmental protection, the development and utilization of natural gas are particularly important. The status of natural gas in China’s oil and gas exploration and development is constantly improving, and the country pays more and more attention to the exploitation and utilization of natural gas. The tight sandstone of Upper Paleozoic in Ordos Basin has the characteristics of low porosity, low permeability, and large area of concealed gas reservoirs. With the increasing demand for natural gas in China, systematic analysis and research on the geological conditions and enrichment law of large area gas reservoirs of tight sandstone of Upper Paleozoic in Ordos Basin to guide exploration and production also pose a great challenge to the current level of natural gas exploration and development in China. In order to solve this problem, this paper takes the Upper Paleozoic tight sandstone in Hangjinqi area in the north of Ordos Basin as the research object, summarizes the natural gas accumulation conditions of tight sandstone according to the geological characteristics of Ordos Basin, determines the main control factors of gas accumulation by superposition method in combination with the distribution characteristics of natural gas, simulates the dynamic process of gas accumulation, establishes the gas accumulation model, analyzes the conditions of gas accumulation and enrichment by statistical methods, summarizes the accumulation and enrichment rules of natural gas, and predicts the favorable exploration areas for natural gas. The results show that the relationship between hydrocarbon source rocks, traps, migration and transportation, and other reservoir-forming conditions and the distribution characteristics of natural gas is summarized, and the main controlling factors of reservoir-forming are determined by superposition method. We simulate the evolution process of faults, strata, oil, gas, and water flows in the study area and establish the dynamic reservoir-forming process of natural gas. By combining the reserve data with the reservoir source distance, reservoir facies type, and gas filling times, the reservoir-forming and enrichment conditions are studied by statistical analysis method, and the reservoir-forming and enrichment rules are summarized by combining the main controlling factors. The enrichment of natural gas is controlled by the development degree of source rocks, favorable tight sandstone combination, confluence channel, and local structure. According to the law of accumulation and enrichment, the division standards of favorable areas in different horizons are established, and the favorable exploration areas in the study area are predicted. The results provide theoretical data support for natural gas exploration in the study area.
Robot Structural Optimization Based on Computer Intelligent Image
Authors: Zhao Junling
Published: October 2022

In order to solve the problems of low degree of automation, difficult identification of picking objects, and large picking damage in traditional fruit and vegetable picking operations, the author proposes a robot structure optimization method based on computer intelligent images. This method introduces the computer imaging technology, examines the principle of imaging the computer imaging technology as the in-depth study of the computer imaging technology, completes the mechanical design of the selected robot, and optimizes all hardware models of choice robot. At the same time, the computer image acquisition system, image acquisition module, and execution module are designed; finally, the computer image information processing flow design of the picking robot is completed, and the simulation experiment of the picking robot is carried out. Experimental results show that in the experiments with 166, 142, and 165 tomato identification numbers, the identification accuracy rates were all over 96%. Conclusion. The picking robot based on computer images has a simple structure, high recognition accuracy of picking targets, less damage to the picking targets, high safety and stability, and great promotion value.
Seven Hub Genes Predict the Prognosis of Hepatocellular Carcinoma and the Corresponding Competitive Endogenous RNA Network
Authors: Han Xueqiong , Lu Jianxun , Chen Chun , Deng Yongran , Pan Mingmei , Li Qigeng , Wu Huayun , Li Zhenlong , Ni Bingqiang
Published: October 2022

Purpose. This study was aimed at identifying hub genes and ceRNA regulatory networks linked to prognosis in hepatocellular carcinoma (HCC) and to identify possible therapeutic targets. Methods. Differential expression analyses were performed to detect the differentially expressed genes (DEGs) in the four datasets (GSE76427, GSE6764, GSE62232, and TCGA). The intersected DEmRNAs were identified to explore biological significance by enrichment analysis. We built a competitive endogenous RNA (ceRNA) network of lncRNA-miRNA-mRNA. The mRNAs of the ceRNA network were used to perform Cox and Kaplan-Meier analyses to obtain prognosis-related genes, followed by the selection of genes with an area under the curve >0.8 to generate the random survival forest model and obtain feature genes. Furthermore, the feature genes were subjected to least absolute shrinkage and selection operator (LASSO) and univariate Cox analyses were used to identify the hub genes. Finally, the infiltration status of immune cells in the HCC samples was determined. Results. A total of 1923 intersected DEmRNAs were identified in four datasets and involved in cell cycle and carbon metabolism. ceRNA network was created using 10 lncRNAs, 67 miRNAs, and 1,923 mRNAs. LASSO regression model was performed to identify seven hub genes, SOCS2, MYOM2, FTCD, ADAMTSL2, TMEM106C, LARS, and KPNA2. Among them, TMEM106C, LARS, and KPNA2 had a poor prognosis. KPNA2 was considered a key gene base on LASSO and Cox analyses and involved in the ceRNA network. T helper 2 cells and T helper cells showed a higher degree of infiltration in HCC. Conclusion. The findings revealed seven hub genes implicated in HCC prognosis and immune infiltration. A corresponding ceRNA network may help reveal their potential regulatory mechanism.
Smart Home-Based Complex Interwoven Activities for Cognitive Health Assessment
Authors: Alsubai Shtwai , Alqahtani Abdullah , Sha Mohemmed , Abbas Sidra , Almadhor Ahmad , Peter Vesely , Mughal Huma
Published: October 2022

With the prevalence of cognitive diseases, the health industry is facing newer challenges since cognitive health deteriorates gradually over time, and clear signs and symptoms appear when it is too late. Smart homes and the IoT (Internet of Things) have given hope to the health industry to monitor and manage the elderly and the less-abled in the comfort of their homes. Smart homes have been most influential in detecting and managing cognitive diseases like dementia. They can give a comprehensive view of the ADL (Activities of Daily Living) of dementia patients. ADLs are categorized as activities of daily life and complex interwoven activities. First signs of cognitive decline appear when a cognitively impaired individual tries to perform complex activities involving planning, analyzing, calculating, and decision making. Therefore, we analyze individuals’ performance while performing complex activities as opposed to Simple ADL. Artificial Intelligence has been one of health-care’s most promising techniques for prediction and diagnosis. When applied to ADL data, machine learning and deep learning algorithms can conveniently and accurately analyze activity patterns and predict the first signs of cognitive decline. Our proposed work uses machine and deep learning classifiers to classify dementia and healthy individuals by analyzing complex interwoven activity data. We use the subset of the CASAS (Centre of Advanced Studies in Adaptive Systems) dataset for eight complex activities performed by 179 individuals in a smart home setting. decision tree, Naive Bayes, support vector, multilayer perceptron classifiers, and deep neural networks have been used for classification. Their results and performances are compared to determine the best classifier. It is observed that deep neural networks and multilayer perceptron show the best results for classifying dementia vs. healthy individuals when evaluating their complex interwoven activities.
Analysis of Maternal and Infant Outcomes and Related Factors of Vaginal Delivery of Second Pregnancy after Cesarean Section
Authors: Pan Xing , Sha Shuhui , Xu Shuxia , Zhan Bingqing , Guan Xue , Ling Fang
Published: October 2022

Objective. To explore the clinical effect of different delivery methods and the safety of vaginal delivery of second pregnancy after cesarean section and analyze the related factors. Methods. A total of 738 eligible pregnant women who underwent cesarean section from September 2018 to August 2020 were randomly selected from our hospital. Among them, 527 pregnant women successfully delivered vaginally were selected as the observation group, and 211 pregnant women who failed vaginal delivery were selected as the control group. To analyze the factors that influence the success of vaginal delivery of second pregnancy after cesarean section and compare the outcomes of mother and infant in two groups. Results. There was no significant difference in age, prenatal body mass index (BMI), and thickness of lower uterine segment between the two groups (

P
>
0.05

). There were significant differences in fetal head orientation, fetal abdominal circumference, fetal biparietal diameter, uterine height, premature rupture of membranes, Bishop score, and epidural anesthesia during labor between the two groups (

P
<
0.05

). Multivariate logistic regression analysis showed that fetal abdominal circumference, fetal head orientation, Bishop score, and epidural anesthesia during labor were independent factors affecting the success of VBAC (

P
<
0.05

). There was no significant difference in the incidence of uterine rupture between the two groups (

P
>
0.05

). The amount of postpartum hemorrhage in the observation group was significantly lower than that in the control group (

P
<
0.05

). There was no significant difference in Apgar score, asphyxia rate, and hospitalization rate between the two groups (

P
>
0.05

). There was no significant difference in the incidence of complications between the two groups (

P
>
0.05

). Conclusion. There are many factors that influence the success of vaginal delivery after cesarean section. Through prenatal comprehensive evaluation of vaginal delivery conditions, we can guide the parturient to choose a reasonable mode of delivery, reduce the incidence of complications, and improve the outcome of mother and baby.
Application of Face Recognition in E-commerce Security Authentication in the Era of Big Data
Authors: Chang Shu , Duan Youtao
Published: October 2022

Although Internet technology brings invaluable benefits to all walks of life, the security of network and information is becoming more and more prominent. The leakage of personnel information caused by Internet security incidents causes irreparable harm and loss to individuals or enterprises. E-commerce is a virtual transaction mode based on Internet technology. Its security requirements for transactions are more stringent than those for traditional transaction modes. Traditional identity authentication technology can no longer meet its security needs. People urgently need a reliable identity authentication system, meaning to ensure the security of e-commerce. According to the actual application scenarios of the algorithm in e-commerce, this paper, based on the research on face recognition technology, focuses on the in-depth research on face detection technology under the background of big data in order to introduce face recognition technology in this paper. This paper proposes a feature-based face matching algorithm. The face image is preprocessed to improve the accuracy of real-time face detection and reduce the false detection rate. Based on the research of traditional facial feature extraction technology, a virtual sample set that can effectively support a traditional facial feature extraction algorithm is constructed to solve the problem of insufficient training samples in practical applications. The experimental results showed that the accuracy of the method in this paper can reach up to 79.5% and that the minimum time consumption is only 0.142 s. Compared with the traditional method, the accuracy rate is higher and the time consumption is shorter.
Stability Analysis and Financial Inclusion of Foreign Trade and Financial Data Based on Panel Data Pairs of Different Countries
Authors: Zhang Yuan
Published: October 2022

There is a complex relationship between financial inclusion and financial stability. In order to explore the relationship between them, this paper proposes a mechanism by which foreign trade affects financial inclusion through financial stability and uses fixed effects analysis and time-variant analysis of variance for the results. Four different criteria were used: GNI per capita, GDP per capita, life expectancy, and infant mortality. The experimental results show that to achieve financial inclusion, policymakers should consider improving foreign trade flows, rational allocation of foreign exchange reserves, and improving credit markets to a certain extent.
A Study on the Relationship between Sense of Disease Uncertainty and Family Strength and Mental Resilience in Guardians of Children with Inflammatory Bowel Disease
Authors: Yan Jun , Luo Lin
Published: October 2022

Background. Inflammatory bowel disease is difficult to cure, which seriously affects the physical and mental health of children and brings negative psychological stress to guardians. Uncertainty in illness of guardians reduces the ability of care and is not conducive to the treatment and recovery of children. Therefore, it is of great significance to explore the related factors of uncertainty in illness. Objective. The aim of this study is to explore the relationship between sense of disease uncertainty and family strength and mental resilience in guardians of children with inflammatory bowel disease (IBD). Method. A total of 146 guardians of 88 children with inflammatory bowel disease were investigated. The guardians’ sense of disease uncertainty, family strength, and mental resilience were evaluated by Mishel uncertainty in illness scale-family member (MUIS-FM), family hardiness index (FHI), and Connor–Davidson resilience sca1e (CD-RISC), respectively. Spearman correlation was used for analyzing the correlation between the guardian’s sense of disease uncertainty and family resilience. Results. The guardian’s MUIS-FM score from lowest to highest was complexity, unpredictability, lack of information, and uncertainty. The average scores of FHI and CD-RISC were lower than the average score of CD-RISC of the general community in China 65.4 (t = −4.36,P<0.05). The score of MUIS-FM was significantly correlated with the scores of FHI and CD-RISC (P<0.05). Multiple linear regression analysis showed that the challenge score in the FHI scale and the fortitude score and the strength score in the CD-RISC scale were the main influencing factors of guardians’ sense of disease uncertainty in children with IBD (P<0.05). Conclusion. The guardians of children with IBD had a more serious sense of disease uncertainty, which was related to family strength and mental resilience.
lncRNAs AC156455.1 and AC104532.2 as Biomarkers for Diagnosis and Prognosis in Colorectal Cancer
Authors: Kuang Fei , Luo De , Zhou Mengjia , Du Juan , Yang Jie
Published: October 2022

Background. There have been countless studies to date assessing specific oncogenic pathways in a range of tumor classes, but the role of N6-methyladenosine- (m6A-) related long noncoding RNAs (lncRNAs) in colorectal cancer (CRC) remains to be defined. Methods. We analyzed such m6A-related lncRNAs by conducting analyses of the Pearson correlation with information originating from the databank of The Cancer Genome Atlas (TCGA). The prognostic relevance of these lncRNAs in CRC was then assessed through a series of univariate Cox regression analyses, leading to the identification of two different m6A modification patterns; they are associated with clinical outcomes and have been used to estimate tumor immune microenvironment (TIME) by the CIBERSORT and ESTIMATE algorithms. We tested the expression of m6A-related lncRNAs in twelve pairs of colorectal cancer tissues and adjacent normal tissues from patients by qRT-PCR. Results. We discovered the prognostic risk signature composed of six m6A-related lncRNAs based upon TCGA data. When the overall survival of cases in the dataset of TCGA was investigated, the low-risk cases survived longer than the high-risk CRC cases in both the training and testing cohorts. ROC curves further indicated that m6A-related lncRNA prognostic signature (m6A-LPS) can effectively estimate the survival outcomes of patients in both of these cohorts. We found that lncRNAs AC156455.1 and AC104532.2 were upregulated in twelve colorectal cancer tissues compared with adjacent normal tissues using qRT-PCR. Conclusions. This data highlights that the lncRNAs AC156455.1 and AC104532.2 in CRC can be used as biomarkers for diagnostics and prognosis in CRC, demonstrating their potential as targets when designing novel immunotherapeutic regimens.
Research on Data News Propagation Path Based on the Big Data Algorithm
Authors: Hao Zhoucheng , Liu Yanan , Wang Gang
Published: October 2022

News propagation originates from a person/location, dwelling with an event that grabs significance. News data propagation relies on telecommunication and big data for precise content distribution and mitigation of false news. Considering these factors, the event-dependent data propagation technique (EDPT) was introduced to improve the data precision. These data refer to the news information originating and propagating from digital media. The data analysis considers the external factors for fake information and precise projection medium for preventing multiviewed false circulations. In this technique, the liability of the information is analyzed using a linear pattern support vector classifier. The data modification and propagation changes are classified based on liability information across the circulation time. The SVM classifier identifies these two factors with close liability validation, preventing false data. The data accumulation and analysis rates for the abovementioned classifications are performed in the propagation process using the classifier hyperplane. This plane is updated from the previous propagation point from which the events are identified. The proposed technique’s performance is analyzed using propagation accuracy, precision, false rate, time, and rate.
Traditional Chinese Medicine Compounds Containing Lonicera japonica, Chrysanthemum morifolium, and Siraitia grosvenorii Inhibits the Growth of Streptococcus mutans
Authors: Zhou Xiaomin , Reheman Asimuguli , Kang Zhongjie , Long An , Wang Tingting
Published: October 2022

Postoperative sore throat (POST) is one of the common complications after endotracheal intubation under general anesthesia. This work attempted to design and screen out the traditional Chinese medicine (TCM) compounds containing Lonicera japonica Thunb., Chrysanthemum morifolium Ramat., and Siraitia grosvenorii (Swingle) C. Jeffrey ex A. M. Lu et Z. Y. Zhang, and further explored its antibacterial effect on POST. The antibacterial activities of Lonicera japonica, Chrysanthemum morifolium, and Siraitia grosvenorii on Streptococcus mutans (S. mutans) UA159 was measured. Lonicera japonica (40 mg/mL), Chrysanthemum morifolium (10 mg/mL), and Siraitia grosvenorii (10 mg/mL) effectively inhibited the growth of S. mutans. Then, 5 different TCM compounds were designed using the U5 (53) uniform design experimentation method. TCM compound C3 (50 mg/mL Lonicera japonica, 10 mg/mL Chrysanthemum morifolium, and 15 mg/mL Siraitia grosvenorii) significantly promoted the inhibition zone and inhibited the biofilm formation of S. mutans. In addition, TCM compound C3 exerted great antibacterial effects on S. mutans and had the least effect on cell viability of primary human pharyngeal epithelial cells. In conclusion, this work demonstrated that TCM compound containing Lonicera japonica, Chrysanthemum morifolium, and Siraitia grosvenorii inhibited the growth of S. mutans. Thus, this study provides a theoretical basis for screening out the optimal compatibility of effective components in TCM mouthwash for relieving POST.
Computational Clues of Immunogenic Hotspots in Plasmodium falciparum Erythrocytic Stage Vaccine Candidate Antigens: In Silico Approach
Authors: Azimi-Resketi Mojtaba , Heydaryan Saeed , Kumar Niloufar , Takalou Azin , Dizaji Reza Esmaeelzadeh , Gorgani Bahman Noroozi , Shams Morteza
Published: October 2022

Malaria is the most pernicious parasitic infection, and Plasmodium falciparum is the most virulent species with substantial morbidity and mortality worldwide. The present in silico investigation was performed to reveal the biophysical characteristics and immunogenic epitopes of the 14 blood‐stage proteins of the P. falciparum using comprehensive immunoinformatics approaches. For this aim, various web servers were employed to predict subcellular localization, antigenicity, allergenicity, solubility, physicochemical properties, posttranslational modification sites (PTMs), the presence of signal peptide, and transmembrane domains. Moreover, structural analysis for secondary and 3D model predictions were performed for all and stable proteins, respectively. Finally, human helper T lymphocyte (HTL) epitopes were predicted using HLA reference set of IEDB server and screened in terms of antigenicity, allergenicity, and IFN‐γ induction as well as population coverage. Also, a multiserver B‐cell epitope prediction was done with subsequent screening for antigenicity, allergenicity, and solubility. Altogether, these proteins showed appropriate antigenicity, abundant PTMs, and many B‐cell and HTL epitopes, which could be directed for future vaccination studies in the context of multiepitope vaccine design.
Pre-Antibiotic Treatment Followed by Prolonged Repeated Faecal Microbiota Transplantation Improves Symptoms and Quality of Life in Patients with Irritable Bowel Syndrome: An Observational Australian Clinical Experience
Authors: Hamblin Harrison , Gunaratne Anoja W. , Clancy Annabel , Pilarinos Denise , LeBusque Antoinette , Dawson Marie Vic M. , Borody Thomas J.
Published: October 2022

Background. The use of faecal microbiota transplantation (FMT) in irritable bowel syndrome (IBS) has frequently failed to induce long-term symptomatic improvement. The use of multiple FMT infusions is one proposed mechanism through which the efficacy of FMT can be amplified. Aims. To evaluate the safety and efficacy of a novel six-month FMT treatment protocol in IBS. Methods. Patients diagnosed with IBS confirmed by Rome IV Criteria were recruited for single-centre, single-arm, prospective clinical observational study. Participants received one colonoscopically delivered FMT followed by 36 rectal enemas across a six-month period. Validated abdominal symptoms and Short-Form (SF-36) Quality of Life (QOL) questionnaires were collected at baseline, week-12, week-24, and week-56, respectively. Wilcoxon matched-pairs signed-rank tests were conducted to compare differences in abdominal symptom and SF-36 QOL scores over the follow-up timepoints. Statistical significance was set at 5%. Results. Sixty participants diagnosed with IBS [IBS-constipation (

n
=
27

), IBS-diarrhoea (

n
=
18

), and IBS-mixed (

n
=
15

)] received the six-month FMT treatment. IBS symptom severity reduction was achieved in up to 61% of respondents at week-12, 64% of respondents at week-24, and maintained in up to 75% of respondents at week-52. Long-term reduction in symptom severity was associated with an increase in QOL, achieved in up to 64% of respondents at week-52 when compared to baseline. Adverse events were experienced in 28% of participants, though they were both transient and mild in nature. Conclusions. Six-month sustained FMT appears to be both safe and effective in the short- and long-term alleviation of IBS associated symptoms as well as improving participant QOL.