bluuebunny/crossref_metadata_2025 huggingface dataset:
The Empirical Analysis of Bitcoin Price Prediction Based on Deep Learning Integration Method
Authors: Zhang Shengao , Li Mengze , Yan Chunxiao
Published: June 2022

As a new type of electronic currency, bitcoin is more and more recognized and sought after by people, but its price fluctuation is more intense, the market has certain risks, and the price is difficult to be accurately predicted. The main purpose of this study is to use a deep learning integration method (SDAE-B) to predict the price of bitcoin. This method combines two technologies: one is an advanced deep neural network model, which is called stacking denoising autoencoders (SDAE). The SDAE method is used to simulate the nonlinear complex relationship between the bitcoin price and its influencing factors. The other is a powerful integration method called bootstrap aggregation (Bagging), which generates multiple datasets for training a set of basic models (SDAES). In the empirical study, this study compares the price sequence of bitcoin and selects the block size, hash rate, mining difficulty, number of transactions, market capitalization, Baidu and Google search volume, gold price, dollar index, and relevant major events as exogenous variables uses SDAE-B method to compare the price of bitcoin for prediction and uses the traditional machine learning method LSSVM and BP to compare the price of bitcoin for prediction. The prediction results are as follows: the MAPE of the SDAE-B prediction price is 0.016, the RMSE is 131.643, and the DA is 0.817. Compared with the other two methods, it has higher accuracy and lower error, and can well track the randomness and nonlinear characteristics of bitcoin price.
Design of Cloud Storage-Oriented Sports Physical Fitness Monitoring System
Authors: Zheng Zhou , Liu Yang
Published: June 2022

In order to improve the accuracy and response speed of sports fitness monitoring results and make the monitoring results more comprehensive, a new cloud storage-oriented sports fitness monitoring system is designed. Based on cloud storage technology, the overall framework of the sports fitness monitoring system is established; the function of the hardware module of the monitoring system is analyzed, and distributed database is established. The ray-casting image feature scanning method was used to collect the physical condition monitoring image and generate a high-quality human body target frame to realize the physical condition monitoring. Based on the monitoring data, the fitness method recommendation method is designed according to the user’s physical condition. The experimental results show that the monitoring results of the proposed system have higher accuracy, faster system response speed, and higher comprehensiveness of the monitoring results, which verifies the application value of the proposed system.
Research on the Policy Effect of Property Tax Reform: Take the Pilot Reforms in Chongqing and Shanghai as Examples
Authors: Dong Wei , Fu Xinqi , Zhang Yang , Qin Guowei
Published: June 2022

It has been ten years since the implementation of property tax reform in Shanghai and Chongqing. With the continuous promotion of tax reform, the central government clearly put forward the decision to accelerate the pilot real estate tax reform in 2021. Every piece of news about the pilot and promotion of property tax reform attracts close attention from people in related fields and becomes a hot topic on the Internet and media. Reform policies are carefully formulated and improved, and the relationship between reform policies, market demand, and people’s livelihood is properly handled so that the real estate market will develop in a healthy and stable manner and have a significant impact on the economy and society. This article mainly starts with the history of property tax development, reform priorities, and comparison with property tax policies of other countries. It takes Chongqing and Shanghai as the research objects, selects several typical factors, and uses multiple linear regression models for analysis. This article studies the impact of China’s property tax pilot on the real estate industry and its effects from both theoretical and empirical aspects and discusses the policy effects of the property tax policy pilot. The levy of real estate tax has a certain effect in a short period of time, but it is not ideal in the long run. Studying the economic effects of Shanghai‐Chongqing property tax is conducive to perfecting China’s property tax reform and promoting the healthy development of real estate market and economic and social development.
[Retracted] Nutrigenomic Interventions to Address Metabolic Stress and Related Disorders in Transition Cows
Authors: Hassan Faiz-ul , Nadeem Asif , Javed Maryam , Saif-ur-Rehman Muhammad , Shahzad Muhammad Aasif , Azhar Jahanzaib , Shokrollahi Borhan
Published: June 2022

For dairy cattle, the period involving a shift from late pregnancy to early lactation termed transition or periparturient is an excruciating phase. Health‐related disorders are likely to happen in this time frame. Timely postpartum and metabolic adjustments to this new physical state demands correct management strategies to fulfill the cow’s needs for a successful transition to this phase. Among the management strategies, one of the most researched methods for managing transition‐related stress is nutritional supplementation. Dietary components directly or indirectly affect the expression of various genes that are believed to be involved in various stress‐related responses during this phase. Nutrigenomics, an interdisciplinary approach that combines nutritional science with omics technologies, opens new avenues for studying the genome’s complicated interactions with food. This revolutionary technique emphasizes the importance of food‐gene interactions on various physiological and metabolic mechanisms. In animal sciences, nutrigenomics aims to promote the welfare of livestock animals and enhance their commercially important qualities through nutritional interventions. To this end, an increasing volume of research shows that nutritional supplementation can be effectively used to manage the metabolic stress dairy cows undergo during the transition period. These nutritional supplements, including polyunsaturated fatty acids, vitamins, dietary amino acids, and phytochemicals, have been shown to modulate energy homeostasis through different pathways, leading to addressing metabolic issues in transition cows.
Effects of Aerobic Exercise on the Serum Leptin Level and Heart Rate Variability in the Obese Girl Children
Authors: Li Cuihan , Lyu Shaojun , Zhang Jianwei
Published: June 2022

Objective. The present study examined the effects of a 16-week aerobic exercise (AE) on the serum leptin level and heart rate variability (time domain and frequency domain) in the obese girl children and correlation coefficients of changes between the serum leptin level and heart rate variability after a 16-week AE intervention. Methods. 36 participants were randomly assigned to either aerobic exercise (AE, n = 18) or obese group (n = 18). The obese girl children in the AE group conducted a 16-week (4 times per week and 60 min per time) exercise protocols, and the obese group did not perform regular physical training during 16 weeks of study. Then, the serum leptin level and HRV (time domain and frequency domain) were measured in all subjects before and after AE intervention. Results. (1) After 16-week AE intervention, compared with pre-exercise, LF/HF decreased

P
<
0.05

, HF, SDNN, and RMSSD significantly increased (

P
<
0.05

and

P
<
0.01

), and there was no significant difference in LF

P
>
0.05

in the AE group. Nevertheless, there was no significant change before and after the test in the serum leptin level and HRV of the obese group (

P
>
0.05

, respectively). (2) After 16-week AE intervention, compared with the obese group, SDNN and HF significantly increased (

P
<
0.05

, respectively), LF/HF significantly decreased

P
<
0.05

in the AE group, but there was no significant difference in RMSSD and LF between the obese group and AE group. (3) The reduction variables of the serum leptin level before and after the AE intervention are positively correlated with the reduction in the LF/HF (r = 0.478,

P
<
0.05

) and negatively correlated with the increasing in the RMSSD (r = −0.482,

P
<
0.05

). But there is no significant association between the reduction in the serum leptin level and the change of LF, HF, and SDNN (

P
>
0.05

, respectively). Conclusion. 16-week AE significantly reduced the serum leptin level and improved cardiac autonomic function in the obese girl children. Moreover, the reduction in the serum leptin level was associated with the increase in parasympathetic activation and improved sympathetic-vagus balance after AE intervention. More research is needed to see whether the effect of exercise on leptin levels in obese girl children can reduce the risk of cardiovascular disease in adulthood.
Exploration of Potential Targets and Mechanisms of Fisetin in the Treatment of Non-Small-Cell Lung Carcinoma via Network Pharmacology and In Vitro Validation
Authors: Ling Junjun , Wang Yuhong , Ma Lihai , Chang Aoshuang , Meng Lingzhan , Zhang Liang
Published: June 2022

Purpose. The morbidity and fatality rates of non-small-cell lung cancer (NSCLC) were high, although a combination of multiple treatments was used. Fisetin, a small flavonoid compound, had shown anticancer activities. Thus, we aimed at exploring the mechanisms of Fisetin in the treatment of NSCLC. Methods. TCMSP and Swiss target tools were used to screen the targets of Fisetin, and GeneCards was used to collect the genes related to NSCLC. The genes common to Fisetin and NSCLC were obtained by Venn analysis, whose possible functions were further annotated. A “Compound-Target-Disease” network was then constructed and hub genes were filtered. Also, molecular docking was performed to predict the binding abilities between Fisetin and the hub genes. Then, the effects of Fisetin on the expression of hub genes in lung adenocarcinoma cells were preliminarily evaluated in vitro. Results. A total of 131 genes common to Fisetin and NSCLC were filtered out, which might be enriched in several biological processes including antioxidation, cell proliferation, and various signaling pathways, such as PI3K-Akt and IL-17 signaling pathways. Among them, PIK3R1, CTNNB1, JUN, EGFR, and APP might be the hub genes. Molecular docking indicated the close bond between Fisetin and them. Experiments implied a possible effect of Fisetin on the expression of hub genes in A549 cells. Conclusion. The present study found a series of novel targets and pathways for Fisetin treating NSCLC. Multiple angles, targets, and pathways were involved in the biological processes, which need to be verified in further experiments.
Synergistic Impacts of Alpinia oxyphylla Seed Extract and Allopurinol against Experimental Hyperuricemia
Authors: Sung Yoon-Young , Kim Dong-Seon
Published: June 2022

In traditional medicine, Alpinia oxyphylla Miquel seed has been used to treat gout and hyperuricemia‐related symptoms by enhancing kidney functions. Allopurinol is the most commonly used drug to treat hyperuricemia; however, the drug has many adverse effects. Combining allopurinol with another compound could reduce the need for high doses and result in improved safety. We investigated the possible synergistic effects of Alpinia oxyphylla seed extract (AE) and allopurinol in decreasing urate concentrations in rats with potassium oxonate‐induced hyperuricemia. This study evaluated the effects of allopurinol combined with AE on levels of serum urate, blood urea nitrogen (BUN), and creatinine in a hyperuricemic rat model. The effects of allopurinol plus AE on xanthine oxidase (XOD) activity and urate uptake were measured. The concomitant administration of allopurinol and AE normalized serum urate and reduced BUN and creatinine. The attenuation of hyperuricemia‐induced impaired kidney function was related to downregulation of renal urate transporter 1 and upregulation of renal organic anion transporter 1, with inhibition of serum and hepatic XOD activities. The antihyperuricemic effects of allopurinol were enhanced when combined with AE. These results suggested that the combined use of allopurinol and AE may have clinical efficacy in treating hyperuricemia.
Attitude Monitoring Algorithm for Volleyball Sports Training Based on Machine Learning in the Context of Artificial Intelligence
Authors: Sun Zhe , Sun Peng
Published: June 2022

With the development of artificial intelligence technology and information technology, the posture of volleyball training is becoming increasingly strict. By analyzing the dynamic training posture monitoring algorithm, the posture information of the human body can be directly obtained, which enables more efficient management of volleyball sports training. This paper aims to study how to monitor volleyball training posture and give suggestions based on machine learning in the context of artificial intelligence. The traditional method of manually detecting volleyball training postures is too subjective and cannot be used to judge the movements. Therefore, this paper proposes an algorithm for human posture monitoring and studies human posture recognition. Human gesture recognition has been widely used in many fields. The experimental results in this paper show that the corrected serve deviation rate of five volleyball players is 13.1% at the highest and 11.3% at the lowest after the traditional manual visual monitoring. The highest error is 0.70 m and the lowest is 0.63 m. The overall error is high. The corrected service deviation rate of the machine learning-based attitude monitoring algorithm is 3.5% at the highest and 2.7% at the lowest. The highest error is 0.24 m and the lowest is 0.19 m. The overall error is much lower than the former. This also shows that the posture monitoring algorithm based on machine learning can effectively detect the movement of volleyball players. This enables athletes to correct their mistakes in a timely manner, improve training efficiency, and improve their own strength.
Modified Q-Learning Method for Automatic Voltage Regulation in Wide-Area Multigeneration Systems
Authors: Abegaz Brook W. , Zarrabian Sina
Published: June 2022

The state-estimation and optimal control of multigeneration systems are challenging for wide-area systems having numerous distributed automatic voltage regulators (AVR). This paper proposes a modified Q-learning method and algorithm that aim to improve the convergence of the approach and enhance the dynamic response and stability of the terminal voltage of multiple generators in the experimental Western System Coordinating Council (WSCC) and large-scale IEEE 39-bus test systems. The large-scale experimental testbed consists of a six-area, 39-bus system having ten generators that are connected to ten AVRs. The implementation shows promising results in providing stable terminal voltage profiles and other system parameters across a wide range of AVR systems under different test scenarios including N-1 contingency and fault conditions. The approach could provide significant stability improvement for wide-area systems as compared to the implementation of conventional methods such as using standalone AVR and/or power system stabilizers (PSS) for the wide-area control of power systems.
Application of the Maximum Sensitivity Principle in the Optimization of Measuring Point Arrangement in Transversely Isotropic Rock Mass Engineering
Authors: Li Yongtao , Zhang Zhizeng
Published: June 2022

The inverse analysis method based on in situ measurement information provides a new approach to determine the mechanical parameters of rock mass. The accurate on-site monitoring data is the prerequisite and basis for the success of displacement back analysis. To improve the accuracy of requirement parameters, a reasonable layout program should be developed to optimize the layout of the measuring position. In order to study the optimal arrangement of measuring points in anisotropic rock mass, the layout optimization of measuring points around a tunnel in the transversely isotropic rock mass is studied according to the maximum sensitivity criteria. The influence of the spatial location of the measuring points on the measurement of the tunnel deformation is obtained. The results indicate that the measuring point should be arranged close to the extreme point in the direction of the larger principal stress.
The Latest Technology of Polycrystalline Ferroelectric Composite Materials in the Design of the Shovel Frame Structure of the Vibratory Excavating Shovel of the Harvester
Authors: Hao Lei , Jie Yanliang
Published: June 2022

China is a large agricultural country. With the development of industrial production, mechanized harvesting has become an inevitable development trend of agricultural material harvesting. In this paper, based on the latest technology of polycrystalline ferroelectric composite materials in the design of the shovel frame of the harvester’s vibrating excavating shovel, the relevant theories of the polycrystalline ferroelectric composite material and the shovel frame of the harvester’s vibrating excavating shovel are based on the literature. After understanding, the shovel frame structure of the vibrating excavating shovel of the harvester was designed, and the latest technology of polycrystalline ferroelectric composite material was introduced in the design of the shovel frame of the vibrating excavating shovel of the harvester to make the vibration system have better performance. The designed shovel frame structure is tested, and the test results show that the horizontal output force received by the shovel designed in this paper increases with the increase of speed and is minimized at 0.26 m/s. The vertical output force decreases first and then increases with the increase of speed. It is the smallest when the running speed is 0.39 m/s. The horizontal working resistance is always greater than the vertical working resistance, and it can be seen that the design of the shovel frame structure can be realized in actual work.
Influence of Moisture Content on Creep Mechanical Characteristic and Mic-Fracture Behavior of Water-Bearing Coal Specimen
Authors: Zhao Zhong , Wu Peng , Wang Lan , Li Ming , Mao Xianbiao , Chen Liang
Published: June 2022

The most challenging aspect of constructing an underground reservoir is ensuring that the safety coal pillar has long-term stability. It is of great significance to study the creep mechanical behavior of coal pillars under water-rock interaction for the construction of underground reservoirs. Five kinds of coal specimens with different moisture contents (dry, 2.42%, 5.53%, 7.55%, and saturated) were prepared. The effect of moisture content on the creep mechanical behavior of coal specimens was studied by graded loading, and the acoustic emission signals during the creep loading of coal specimens were monitored. The results showed that with the increase in moisture content, the instantaneous strain and creep strain of coal specimens gradually increase, and the total time of the creep test, creep failure stress, and long-term strength generally decreases. The creep failure stress to peak strength and the ratio of long-term strength to peak strength were 73%~85% and 57%~65%, respectively, which are basically independent of water content. As the water content of the coal increased, the cumulative acoustic emission energy decreased, and the failure form of the coal specimen gradually shifted from tension failure (

ω
=
0
%

and 2.42%), tension shear composite failure (

ω
=
5.53
%

) to shear failure (

ω
=
7.55
%

and 10.08%). The research results can be used as a reference for the design and strength evaluation of coal pillars for underground reservoirs in coal mines.
Analytical Solution of Slow Squeeze Flow of Slightly Viscoelastic Fluid Film between Two Circular Disks Using Recursive Approach
Authors: Memon Muhammad , Shaikh Asif Ali , Siddiqui Abdul Majeed , Kumar Laveet
Published: June 2022

This research investigates an analytical solution for the slow squeeze flow of the slightly viscoelastic fluid film between two circular disks in which the upper disk approaches the lower disk with a constant velocity, and the lower disk is kept stationary. The determination of the study is to identify the behavior of the differential type fluid on the steady squeezing flow using Langlois recursive approach. The governing equations for the axisymmetric flow are expressed in cylindrical coordinates and yield the nonlinear system of partial differential equations. The analytical solution of the resulting equations with nonhomogeneous boundary conditions is obtained by the Langlois recursive approach. Flow variables such as stream function, velocity profiles, pressure distribution, shear, normal stresses, and normal force acting on the disk are determined. These flow variables are nondimensionalized by using suitable dimensional quantities. The influence of slightly viscoelastic parameter

β

, radial distance

r

, and aspect ratio on velocity components, pressure distribution, and normal squeeze force is examined mathematically and portrayed graphically. The results illustrate that the axial and radial velocities increase at the higher values of the slightly viscoelastic parameter

β

, which confirms the shear thickening behavior. The obtained solutions of the flow variables satisfied the existing solutions on squeeze flow of viscous fluid upon vanishing the slightly viscoelastic parameters. This solution could elucidate the classical lubrication problems, particularly in load and thrust bearing characteristics of the human body joints, the compression molding process of materials, etc.
Design of a Lens System Reduces Chromatic Aberration for Proton
Radiography
Authors: Jia Qinggang , Wang Wenyuan , Xu Haibo , Lu Liang , Batani Dimitri
Published: June 2022

Multi-GeV proton radiography is an important tool for diagnosing density
distribution of thick objects. The magnetic lens system called Zumbro lens
is widely employed because it compensates for the image distortion induced
by small angle multiple Coulomb scattering (MCS) that occurs when the
charged protons passing through the object. However, radiography is still
suffering from chromatic aberration induced blurring, if the momentum of
transmitted proton is different from the reference value of Zumbro lens. In
this paper, two methods are employed to reduce chromatic aberration. The
first is based on magnetic lens optimization. In addition, a new lens system
is first proposed locating the downstream of Zumbro. It is named “auxiliary”
lens, which can correct the chromatic aberration for certain protons with
momentum far away from the reference of Zumbro lens. Monte Carlo simulation
shows that this proposed lens can decrease chromatic aberration and improve
the radiography image evidently.
DSM and Optimization of Multihop Smart Grid Based on Genetic Algorithm
Authors: Zhu Qi , Li Yingliang , Song Jiuxu
Published: June 2022

Multihop smart grid is built on the basis of an integrated and high-speed communication network. Through the application of advanced sensing and measurement technology, equipment technology, control method, and advanced decision support system technology, the goal of reliable, safe, economic, efficient, environment-friendly, and safe use of the power grid is realized. In order to solve the problem of excessive demand for power supply, new energy power generation and demand response are proposed. According to the above background, the demand side economic scheduling problem is a complex optimization problem, which is difficult to be solved by ordinary algorithms. The adaptive global search algorithm based on a genetic algorithm can better solve complex optimization problems. The genetic algorithm proposed in this paper can effectively manage a large number of controllable loads in the selected area. The algorithm minimizes the cost and peak to the average ratio by changing the load. Home users can arrange their maximum load when the price is low. The peak load of residential buildings decreased from 98.5 kw/h to 90 kw/h, and the peak load decreased by about 7.53%. Through appropriate load dispatching, users minimize the daily electricity charge, which is reduced from 1352 yuan to 1245 yuan per day, and the daily electricity charge is reduced by about 7.25%. In addition, the advanced measurement, communication, and control means under the framework of the smart grid also play a key role in promoting all aspects of demand side management (DSM).
Occurrence of Total Aflatoxins, Aflatoxin B1, and Ochratoxin A in Chicken and Eggs in Some Cameroon Urban Areas and Population Dietary Exposure
Authors: Tatfo Keutchatang Fabrice De Paul , Tchuenchieu Alex K. , Nguegwouo Evelyne , Mouafo Hippolyte Tene , Bouelet Ntsama Isabelle Sandrine , Kansci Germain , Medoua Gabriel Nama
Published: June 2022

Consumption of chicken and eggs contaminated by mycotoxins could lead to a public health concern. This study was conducted to evaluate the dietary exposure of populations to aflatoxins (AFs) and ochratoxin A (OTA) through these poultry products in the three most urbanized regions of Cameroon (Centre, Littoral, and West). A survey was firstly carried out to know about the consumption frequency by the different population age groups as well as their awareness about mycotoxins. Chicken feed, broiler, and eggs were collected from modern poultry farms. AFs and OTA were analysed using the enzyme‐linked immunosorbent assay (ELISA), and dietary exposure was evaluated using a deterministic approach. From the 900 households questioned, a daily consumption frequency of chicken and eggs was the most reported (41% and 69%, respectively), with populations having a very weak knowledge of mycotoxins and their associated health risk (18%). Mean concentrations of AFs, AFB1, and OTA in poultry tissues were below the established regulated limits (20 μg/kg for AFs, 10 μg/kg for AFB1, and 5 μg/kg for OTA) in feeds. These toxins were detected at average concentrations of 1800 and 966.7 ƞg/kg for AFs in chicken muscle and egg, respectively, and 1400 and 1933.3 ƞg/kg for OTA in muscle and egg, respectively. Based on the survey, their estimated daily intakes through these poultry products tended to be lower than the limits 1 and 100 ƞg/kg bw/day for AFB1 and OTA, respectively). The margins of exposure (MOE) of the different population age groups to AFB1 and OTA obtained suggest that the public health concern associated with the presence of mycotoxins in poultry products shall not be underestimated.
Paricalcitol Attenuates Metabolic Syndrome-Associated Heart Failure through Enhanced Mitochondrial Fusion
Authors: Nizami Hina L. , Katare Parmeshwar B. , Prabhakar Pankaj , Adela Ramu , Sarkar Soumalya , Arava Sudheer , Chakraborty Praloy , Maulik Subir K. , Banerjee Sanjay K.
Published: June 2022

Objectives. Transition from cardiac hypertrophy to failure involves adverse metabolic reprogramming involving mitochondrial dysfunction. We have earlier shown that vitamin D deficiency induces heart failure, at least in part, through insulin resistance. However, whether activation of vitamin D receptor (VDR) can attenuate heart failure and underlying metabolic phenotype requires investigation. Thus, we aimed to assess the cardioprotective potential of paricalcitol, a vitamin D receptor-activator, against cardiac hypertrophy and failure in high-fat high-fructose-fed rats. Methods. Male Sprague Dawley rats were fed control (Con) or high-fat high-fructose (HFHFrD) diet for 20 weeks. After 12 weeks, rats from HFHFrD group were divided into the following: HFHFrD, HFHFrD+P (paricalcitol i.p. 0.08 μg/kg/day) and HFHFrD+E (enalapril maleate i.p. 10 mg/kg/day). Intraperitoneal glucose tolerance test, blood pressure measurement, and 2D echocardiography were performed. Cardiac fibrosis was assessed by Masson’s trichrome staining of paraffin-embedded heart sections. Mitochondrial DNA and proteins, and citrate synthase activity were measured in rat hearts. VDR was silenced in H9c2 cardiomyoblasts, and immunoblotting was performed. Results. Paricalcitol improved glucose tolerance, serum lipid profile, and blood pressure in high-fat high-fructose-fed rats. Paricalcitol reduced cardiac wall thickness and increased ejection fraction in high-fat high-fructose-fed rats but had no effect on perivascular fibrosis. PGC1-α was upregulated in the HFHFrD+P group compared to the HFHFrD group, but there was no significant difference in mitochondrial content. Citrate synthase activity was significantly higher in the HFHFrD+P group compared to the HFHFrD group. Rat hearts of the HFHFrD+P group had significantly higher expression of mitofusins. H9c2 cells with VDR knockdown showed significantly lower expression of Mfn2. Improvement in the HFHFrD+P group was comparable with that in the HFHFrD+E group. Conclusions. Paricalcitol reverses cardiac dysfunction in rats with metabolic syndrome by enhancing mitochondrial fusion. We demonstrate repurposing potential of the drug currently used in end-stage kidney disease.
Construction of Tourism E-Commerce Platform Based on Artificial Intelligence Algorithm
Authors: Yin Xiaoyin , He Jiangnan
Published: June 2022

In the late twentieth century, with the rapid development of the Internet, e-commerce has emerged rapidly, which has changed the way people travel around the world. The greatest advantages of e-commerce are the flow of information and data and the importance of traveling freely to experience the mind and body in different fields. Tourism is an important part of the development of e-commerce, but the development of e-commerce tourism lags behind. To solve the current situation of the backward development of tourism e-commerce, this article studies the construction of a tourism e-commerce platform based on an artificial intelligence algorithm. By introducing modern information technology, based on a cloud computing platform, big data analysis, K-means, and other key technologies, this article solves the current situation of the development of an e-commerce platform. It also analyzes the construction methods of traditional cloud platforms and modern cloud platforms through comparative analysis and solves the construction methods suitable for artificial intelligence tourism. At the same time, combined with the actual situation of tourism, this article selects the appropriate networking method based on the analysis of the advantages and disadvantages of wired and wireless coverage methods and economics to complete the project design. Its purpose is to ensure that the work meets the specific construction needs and build an artificial intelligence-based smart tourism big data analysis model. It promotes the development of tourism e-commerce industry. It saves costs and improves efficiency for travel service providers. Then, according to the actual situation of tourism, it conducts demand analysis from the perspectives of tourists, scenic spots, service providers, tourism administrative agencies, etc. Experiments show that, through the practical application of the artificial intelligence tourism mobile e-commerce platform in this article, it can be seen that the artificial intelligence tourism mobile e-commerce platform designed in this article can meet the needs of customers for shopping-related tourism commodities. Tourists of attractions have increased by 3.54%, and the economy of tourist destinations has increased by 4.2%.
[Retracted] Big Data Analytics Model for Distributed Document Using Hybrid Optimization with K‐Means Clustering
Authors: Sharma Kapil , Saini Satish , Sharma Shailja , Kang Hardeep Singh , Bouye Mohamed , Krah Daniel
Published: June 2022

Clustering, also known as unsupervised learning, is one of the most significant topics of machine learning because it divides data into groups based on similarity with the aim of extracting or summarizing new information. It is one of the most often used machine learning techniques. The most significant problem encountered in this subject is the sheer volume of electronic text documents accessible, which is increasing at an exponential rate, necessitating the development of efficient ways for dealing with these papers. Furthermore, it is not practicable to consolidate all of the papers from numerous locations into a single area for processing. In this study, the primary goal is to enhance the performance of the distributed document clustering approach for clustering big, high‐dimensional distributed document datasets. For distributed storage and analysis, one of the most prominent open‐source implementations of the big data analytic‐based MapReduce model, such as the Hadoop framework, is used in conjunction with a distributed file system and is known as the Hadoop Distributed File System, to achieve the desired results. This necessitates an improvement in the approach of the clustering operation with Elephant Herding Optimization, which will be accomplished by applying a hybridized clustering procedure. In conjunction with the MapReduce framework, this hybridized strategy is able to solve the obstacles associated with the K‐means clustering method, including the initial centroids difficulty and the dimensionality problem. In this paper, we analyze the performance of the whole distributed document clustering technique for big document datasets by using a distributed document clustering framework such as Hadoop and the associated MapReduce methodology. In the end, this decides how quickly computations may be completed.
Albumin Paclitaxel Compared with 5-Penfluorouracil, Lobaplatin, and Albumin Paclitaxel Combined with 5-Penfluorouracil in the Treatment of Human Gastric Cancer Cell AGS Line Autophagy and Apoptosis
Authors: Cheng Xingzhen , Yang Fang , Wang Yang , Nie Wei , Mahendra Upadhyay Adarsha , Zhang Maolin , Wang Qian , Yan Zhiqiang
Published: June 2022

Background. Gastric cancer is one of the most common malignant tumors in the world. Albumin paclitaxel (Nab-PTX) is a novel microtubule inhibitor with albumin as the carrier. Several clinical trials are underway in gastric cancer, but the autophagy mechanism of Nab-PTX on gastric cancer is still unclear. The autophagy and apoptosis effects of Nab-PTX compared with 5-pentafluorouracil (5-Fu) and lobaplatin (LBP) in gastric cancer are also unclear. Objective. This article will compare the effects of Nab-PTX, 5-Fu, LBP, and albumin paclitaxel + 5-pentafluorouracil (Nab-PTX + 5-Fu) on AGS cells from the perspective of autophagy and apoptosis, which is to provide new ideas and experimental evidence for gastric cancer. Method. (1) Experimental groups were control (Ctrl), Nab-PTX, 5-Fu, LBP, and Nab-PTX + 5-Fu. (2) CCK-8 assay was used to reflect cell viability and proliferation. (3) The flow cytometry was used to perform the 24-hour apoptosis and cell cycle of each group. (4) Western blot assay was used to investigate autophagy signal proteins LC3I/LC3II, LC3II/LC3I, SQSTM1/p62, Beclin-1, Atg12, Atg5, p-mULK1, p-AMPK, p-mTOR, and apoptosis signal proteins Bax and Bcl-2. Results. Nab-PTX, 5-Fu, LBP, and Nab-PTX + 5-Fu inhibited AGS cells' proliferation and arrested the cell cycle. At the same time, each group increased the apoptosis of AGS cells to various degrees (Nab-PTX + 5-Fu > Nab-PTX > 5-Fu > LBP, respectively). The experimental results showed that Nab-PTX and Nab-PTX + 5-Fu promoted autophagy and apoptosis of AGS cells. The comparison of Nab-PTX, 5-Fu, and LBP between groups revealed that 5-Fu inhibited autophagy and the expression of apoptosis protein Bax. In LBP, abnormal activation of autophagy downstream, blocking of autophagy flow, abnormal increase of ATG12, and increased expression of apoptosis protein Bax occurred. Further study found that the autophagy upstream mechanism is different. Conclusion. Nab-PTX, 5-Fu, LBP, and Nab-PTX + 5-Fu can inhibit cell proliferation, promote cell apoptosis, and induce the difference in autophagy expression. The autophagy difference of this antitumor drug may be related to its inducing apoptosis. Meanwhile, Nab-PTX has a better antitumor effect than 5-Fu and LBP in gastric cancer, and the combination of Nab-PTX + 5-Fu has more antitumor advantages.
Analysis Model of Human Resource Cross-Media Fusion Based on Deep Neural Network
Authors: Ma Shengqing , Xuan Shanwen , Liang Yinjing
Published: June 2022

With the continuous deepening of enterprise system reform and the rapid development of national economy, enterprises are facing the great challenge of market competition. In the new market and social environment, the role of human resource management in enterprises becomes particularly important. To further improve the level of enterprise human resources strategic management has become an urgent problem to be solved. In the process of human resource management, enterprises are faced with complex and changeable environment and other influencing factors. Therefore, in the human resource information retrieval, this paper uses the method of deep learning to screen human resource management indicators and constructs the human resource management index system of power supply enterprises. In this paper, the nonlinear characteristics of neural network are used to establish a deep neural network human resource cross-media fusion model, which provides an operational method for enterprise human resource management. The human resource allocation relationship of enterprises is predicted, and the influencing factors and trends of personnel post-matching are analyzed. The demand forecasting results show that the neural network depth has a good fit with the enterprise staff, and the actual forecasting error is less than 3.0. It can accurately predict the human resource allocation of enterprises, improve the scientificity and effectiveness of human resource strategic decision-making, and make enterprises better adapt to the requirements of market economy. This will be of practical significance to the modernization of enterprise management.
Simulation‐Based Tracking Test and Optimization of Large‐Tonnage Box Girder Transport with Trolley on an Erected Bridge
Authors: Wang Lei , Lv Zhong-da , Xu Ai-min , Wang Fei , Dong Xin-long
Published: June 2022

In the construction of large‐tonnage box girder, the construction load of box girder transport is generally greater than the operating load in highway industry; therefore, it is a crucial task to carry out accurate simulation and optimization on bearing box girder. For this purpose, the refined modeling method of 40 m/1270t box girder is studied first in this paper, followed by detailed stress analysis by considering the impact coefficient of vehicles and the most unfavorable conditions. Tracking tests on dead load, prestressed load, and the transport load have shown that the calculated stress values obtained by the refined models are very close to the measured stress values. Based on dynamic strain test of the vehicles at the speed of 4 km/h, the impact coefficient of four vehicles is estimated to be 1.08 and its value meets the requirements of no more than 1.1 provided by the vehicle manufacturer. Aimed at no tensile stress in the midspan section, the optimized geometry of 40 m box girder is obtained with less concrete and longitudinal prestressed tendons. These results demonstrate the plausibility and validity of the proposed research methods and optimization schemes for large‐tonnage box girder transport.
Footprint Extraction and Sports Dance Action Recognition Method Based on Artificial Intelligence Distributed Edge Computing
Authors: Hu Xiaolin , Xu Xiang
Published: June 2022

Distributed edge computing technology for artificial intelligence refers to an emerging technology that integrates network core processing functions, computing functions, storage functions, etc. into one end source closer to objects or data on the basis of an open platform to optimize service quality. In this paper, distributed edge computing technology is applied to footprint extraction and sports dance action recognition, aimed at improving the recognition efficiency and recognition quality. Firstly, the overview of edge computing theory is introduced; these include edge computing concepts, edge computing characteristics, and edge computing platforms; and then, the classification of action recognition technology is described. Finally, the edge computing recognition technology and traditional recognition technology are compared and tested. The experimental results show that the average accuracy of edge computing technology for footprint extraction can reach 98.98, and the average recognition rate of sports dance movements can reach 80.21%, which verifies its practicability.
Brushless Wound Rotor Synchronous Machine Based on a Consequent-Pole Rotor Structure with Better Torque Attributes
Authors: Hussain Bukhari Syed Sabir , Yu Jaewon , Shah Madad Ali , Bajaj Mohit , Ro Jong-Suk
Published: June 2022

This paper presents a subharmonic-based brushless wound rotor synchronous machine (BL-WRSM) topology with permanent magnet-assisted (PMA) and consequent-pole (CP) rotor structures to achieve better torque characteristics as compared to the conventional subharmonic-based brushless WRSM. The proposed topologies use the conventional high-efficient subharmonic field excitation technique to achieve a brushless operation and a lower volume of permanent magnet (PM) to achieve better average, starting, maximum, and minimum torques and lower torque ripple. A four-pole, twenty-four-slot (4-pole/24-slot) machine with conventional, PM-assisted (PMA), and consequent-pole (CP) rotor structures are developed in a JMAG-Designer 20.1 environment to carry out two-dimensional finite element analysis (2D-FEA). The developed machines are used to validate the operation and achieve electromagnetic and electromechanical performances of the proposed subharmonic-based BL-WRSM topologies with better torque attributes.
The Teaching Capacity of Industry Characteristic Counselors Based on Data Fusion and Random Forest Algorithm
Authors: Ji Li , Sun Yingmin , Sun Meimei , Kong Miaomiao
Published: June 2022

The good development of industry-specific universities (hereinafter referred to as characteristic universities) promotes the optimal allocation of national university resources and moreover promotes the development of China’s education, while counselors, as important teaching and research staff, have a very close connection with the development level of the school, directly reflecting the quality and level of education of the school and determining the height of its educational development. Talent is the first productive forces, counselors as teaching talents, and is essential to the construction of industry specialty universities. The evaluation index system of teaching ability of counselors can effectively guide counselors toward the path of specialization, scientifically realize career planning, and maximize the achievement of the general goal of the characteristic school they are in. This article aims to assess the teaching capacity of counselors and targeted training capabilities. The counselor’s ability is reflected in the teaching of teaching, completing teaching objectives and cultivates student’s hobbies. In this paper, through investigating the cultivation methods of different industries, the cultivation of counselor’s ability is to assess consensus and establish multilevel teachers’ teaching capacity cultivation system. The results show that the system can effectively improve the teaching capacity of young teachers and increase 20% of student’s satisfaction; however, it also shows that the professional competence of counselors still needs to be improved.
Species-Specific Enhancer Activity of OCT4 in Porcine Pluripotency: The Porcine OCT4 Reporter System Could Monitor Pluripotency in Porcine Embryo Development and Embryonic Stem Cells
Authors: Kim Seung-Hun , Lee Mingyun , Choi Kwang-Hwan , Jeong Jinsol , Lee Dong-Kyung , Oh Jong-Nam , Choe Gyung Cheol , Lee Chang-Kyu
Published: June 2022

The present study examined the activity and function of the pig OCT4 enhancer in the porcine early embryonic development stage and porcine authentic embryonic stem cells. OCT4 is known as a pluripotent regulator, and its upstream regulatory region-based dual-fluorescence protein reporter system controlled by distal and proximal enhancers is broadly used in studies examining the states and mechanism of pluripotency. We analyzed how this reporter system functions during early embryo development and in stem cells using a previously established porcine-specific reporter system. We demonstrated that the porcine OCT4 distal enhancer and proximal enhancer were activated with different expression patterns simultaneously as the expression of pluripotent marker genes changed during the development of in vitro pathenotes and the establishment of porcine embryonic stem cells (ESCs). This work demonstrates the applicability of the porcine OCT4 upstream region-derived dual-fluorescence reporter system, which may be applied to investigations of species-specific pluripotency in porcine-origin cells. These reporter systems may be useful tools for studies of porcine-specific pluripotency, early embryo development, and embryonic stem cells.
Initial Clustering Based on the Swarm Intelligence Algorithm for Computing a Data Density Parameter
Authors: Xiong Wei
Published: June 2022

To improve the accuracy and efficiency of cluster startup using data density parameters, the author proposes a large data cluster extraction algorithm based on a herd intelligence algorithm. Since clustering to initiate data density parameters is primarily data mining, the author explores data mining clustering based primarily on herd intelligence algorithms. First, the obscure c-key cluster algorithm in the clustering algorithm is analyzed, and then the hybrid jump algorithm in the sub-heuristic herd intelligence optimization technology is optimized in the case of a few parameters by combining the obscure c-means cluster algorithm. The simulation results show that the convergence speed of the fuzzy C-means clustering algorithm and hybrid leapfrog algorithm is slow; the convergence rate of the PSO-FCM algorithm has been improved. Since the fusion algorithm requires fewer adjustment parameters, the cluster centers can be obtained more accurately and quickly with strong robustness and fast convergence. Compared with other algorithms, the fusion algorithm proposed by the author has the best performance in clustering effect, accuracy, convergence rate, and robustness. It is proved that the swarm intelligence algorithm can effectively perform density parameter initialization clustering on computational data.