bluuebunny/crossref_metadata_2025 huggingface dataset:
The Validity of Visual Communication Design of Online Advertisement Based on Interactivity
Authors: Zu Ruizhi
Published: July 2022

Today’s society is a society of Internet information, especially the rapid development of new media that is the most distinctive project today. New media has changed the way traditional media are disseminated, and the advertising industry has made new developments with the rapid development of new media, especially with the rise of online advertising, making the dissemination of advertising more influential. In modern advertising information, online advertising has become very influential. This study aims at how to achieve user-matching push and set the right price is the two major problems of Internet advertising push, through the analysis of the emergence and development of network advertising and visual elements in network advertising, starting from the problems appearing in modern online advertisements, and studying the visual communication design in online advertisements. In this paper, a neural network model and a fuzzy comprehensive evaluation decision model are designed; so as to make our online advertisements rich in national characteristics and really cause online users’ active clicks. The experimental results show that the proposed method achieves good results and verifies the effectiveness of the model.
Research on Location of Logistics Distribution Center Based on K-Means Clustering Algorithm
Authors: Wang Ping , Chen Xianjun , Zhang Xuebin
Published: July 2022

The basic task of the logistics distribution center is to achieve the storage and distribution of materials, and to plan, implement, and manage the effective flow of materials from the supplying place to the consumption place. Scientific location of logistics distribution center can effectively reduce logistics cost, improve the speed of circulation, increase the profits of enterprises, and enhance the core competitiveness of enterprises. Combining the advantages of K-means clustering algorithm, this paper applies it to the location problem of logistics distribution center and proposes a logistics distribution center location method combining K-means clustering theory and D-S reasoning, which provides a better solution for the location problem of logistics distribution center. Through case analysis, K-means clustering algorithm can obtain reasonable location of logistics distribution center, which can be applied to the location of multilevel logistics distribution network, and has certain practical application value.
E-Sports Training System Based on Intelligent Gesture Recognition
Authors: Li Hui , Lu Yao , Yan Hongqiao
Published: July 2022

In order to improve the effect of e-sports training, this paper combines the intelligent gesture recognition technology to construct an e-sports training system and judges the training effect of players through the recognition of players’ gestures. Moreover, this paper studies the commonly used feature extraction algorithms and proposes an improved SLC-Harris feature extraction algorithm, and the feasibility of this algorithm is verified by the experimental results on the EUROC data set. In addition, this paper uses the KLT optical flow algorithm to track the extracted feature points and calculates the pure visual pose through epipolar geometry, triangulation, and PnP algorithms. The experimental research results show that the electronic economic training system based on intelligent gesture recognition proposed in this paper has certain effects.
Realization of English Instructional Resources Clusters Reconstruction System Using the Machine Learning Model
Authors: Li Xiaohui
Published: July 2022

Based on ML algorithm, this paper puts forward a method that can search instructional resources through keyword indexing technology, and then cluster and recombine the related results and present them centrally. In this paper, the semantic processing of user query based on the subject index of educational resources is adopted to make up for the deficiency of query semantics, solve the problem of mismatch between query words and document words, and improve the recall and precision of resource retrieval. It is proposed to select the category feature items manually and establish the category feature model. In the environment of small sample set, the weight of category feature items is trained by ML method. The research shows that the user rating of this system is ideal, reaching 93.21% at the highest. In addition, the stability of the system can still reach 89.31% under the condition of relatively large usage, and its performance is excellent. This system can effectively solve the problem of scattered distribution of English instructional resources and make the presentation of knowledge more in line with the needs of users, thereby further improving the utilization rate of English instructional resources and users’ satisfaction.
Rating-Based Recommender System Based on Textual Reviews Using IoT Smart Devices
Authors: Ahmed Muqeem , Ansari Mohd Dilshad , Singh Ninni , Gunjan Vinit Kumar , B. V. Santhosh Krishna , Khan Mudassir
Published: July 2022

Recommender system (RS) is a unique type of information clarification system that anticipates the user's evaluation of items from a large pool based on the expectations of a single stakeholder. The proposed system is highly useful for getting expected meaning suggestions and guidance for choosing the proper product using artificial intelligence and IoT (Internet of Things) such as chatbot. The current proposed technique makes it easier for stakeholders to make context-based decisions that are optimal rather than reactive, such as which product to buy, news classification based on high filtering views, highly recommended wanted music to choose, and desired product to choose. Recommendation systems are a critical tool for obtaining verified information and making accurate decisions. As a result, operational efficiency would skyrocket, and the risk to the company that uses a recommender system would plummet. This proposed solution can be used in a variety of applications such as commercial hotels OYO and other hotels, hospitals (GYAN), public administrative applications banks HDFC, and ICICI to address potential questions on the spot using intelligence computing as a recommendation system. The existing RS is considering a few factors such as buying records, classification or clustering items, and user's geographic location. Collaborative filtering algorithms (CFAs) are much more common approaches for cooperating to mesh the respective documents they retrieved from the historical data. CFAs are distinguished in plenty of features that are uncommon from other algorithms. In this existing system classification, precision and efficiency and error rate are statistical measurements that need to be enhanced according to the current need to fit for global requirements. The proposed work deals with enhancing accuracy levels of text reviews with the recommender system while interacting by the numerous users for their domains. The authors implemented the recommender system using a user-based CF method and presented the significance of collaborative filtering on the movie domain with a recommender system. This whole experiment has been implanted using the RapidMiner Java-based tool. Results have been compared with existing algorithms to differentiate the efficiency of the current proposed approach.
Improvements of Physical Activity Performance and Motivation in Adult Men through Augmented Reality Approach: A Randomized Controlled Trial
Authors: Nekar Daekook M. , Kang Hye Yun , Yu Jae Ho
Published: July 2022

The COVID‐19 pandemic had a global impact, increasing the prevalence of physical inactivity, which is mostly due to the lockdown and social distancing measures adopted during the pandemic. Hence, this study aimed to compare the efficacy of augmented reality‐based training on physical activity performance and motivation in healthy adults to mirror visual feedback training and conventional physical therapy. This study used the randomized control trial pretest‐posttest research design. Forty‐eight healthy men aged 18–35 years who were engaged in recreational physical activities were enrolled and randomly divided into four groups: augmented reality‐based training reality (ART), mirror visual feedback training (MVFT), therapist‐based training (TBT), and control group. The total training program was held for four weeks. The isokinetic dynamometer, sit‐and‐reach test, Y balance test, and the intrinsic motivation inventory‐22 were used to measure the outcomes before and after the intervention. Paired sample t‐test was used to compare the changes before and after the intervention within groups, while the one‐way ANOVA was used for the comparison between the groups. Results of the study showed that, after four weeks of intervention, balance, muscle strength, and muscle endurance in all groups significantly improved except for the control group. The ART group showed the highest increase in muscle strength, muscle endurance, and balance compared to the other groups. The motivation level increased in all three feedback groups and was observed in the following order: ART group > MVFT group > TBT group > control group. This study highlighted the most effective method that may be applied for home training during and after this period of the pandemic. The findings revealed that training while receiving real‐time feedback via AR devices improves both physical performance and motivation. Augmented reality‐based training can be used as an effective training option for improving physical activity and motivation and can be suggested for home training programs.
Retrospective Study of the Relationship between Variable Benign Epilepsy of Childhood with Centrotemporal Spikes and the Changes of Zinc, MRS, VEEG, and IQ Test
Authors: Li Zhenhong , Ni Hong , Liu Yueying , Li Fei , Zeng Haijiang
Published: July 2022

Benign epilepsy in childhood with centrotemporal spikes (VBECT) has been associated with electroencephalography (EEG), but the relationship of VBECT with zinc, magnetic resonance spectroscopy (MRS), and intelligence quotient (IQ) tests is unclear. The aim of this study was to investigate the association of VBECT with zinc, MRS, EEG, and IQ tests. In this retrospective study, we selected 58 children with variable benign epilepsy with centrotemporal spikes as the experimental group. A total of 120 children with typical benign childhood epilepsy with centrotemporal spikes were selected as the control group. The zinc, MRS, EEG, and IQ test results of 178 children were measured and analyzed. The results showed that the zinc, MRS, and IQ test results of the patients in the experimental group decreased significantly. The spinal slow wave results in the experimental group showed a significant upward trend. Linear correlation analysis of zinc with MRS, EEG, and IQ tests showed that 13 pairs of indicators were significantly negatively correlated. Our results suggest the importance of zinc, MRS, EEG, and IQ during VBECT.
Role of Posttranslational Modifications of Proteins in Cardiovascular Disease
Authors: Liu Yong-Ping , Zhang Tie-Ning , Wen Ri , Liu Chun-Feng , Yang Ni
Published: July 2022

Cardiovascular disease (CVD) has become a leading cause of mortality and morbidity globally, making it an urgent concern. Although some studies have been performed on CVD, its molecular mechanism remains largely unknown for all types of CVD. However, recent in vivo and in vitro studies have successfully identified the important roles of posttranslational modifications (PTMs) in various diseases, including CVD. Protein modification, also known as PTMs, refers to the chemical modification of specific amino acid residues after protein biosynthesis, which is a key process that can influence the activity or expression level of proteins. Studies on PTMs have contributed directly to improving the therapeutic strategies for CVD. In this review, we examined recent progress on PTMs and highlighted their importance in both physiological and pathological conditions of the cardiovascular system. Overall, the findings of this review contribute to the understanding of PTMs and their potential roles in the treatment of CVD.
Long-Term Effect of Anti-Vascular Endothelial Growth Factor (Anti-VEGF) Injections in Choroidal Neovascularization Secondary to Angioid Streaks
Authors: Torres-Costa Sónia , Bernardes João , Mano Sofia Sousa , Medeiros-Pinto Joana , Abreu Ana Carolina , Furtado Maria João , Silva Rufino , Marques-Neves Carlos , Falcão-Reis Fernando , Carneiro Ângela , Colaço Luísa , Falcão Manuel
Published: July 2022

Purpose. This study aimed to evaluate the long-term effectiveness of intravitreal anti-vascular endothelial growth factor (VEGF) injections in the treatment of choroidal neovascularization (CNV) associated with angioid streaks. Methods. Multicenter retrospective cohort study, including eyes with CNV secondary to angioid streaks treated with anti-VEGF injections, were performed. Best-corrected visual acuity (BCVA) in ETDRS letters; qualitative and quantitative (foveal thickness) OCT parameters; anti-VEGF type; and number of injections were collected at baseline and at 3, 6, 12, 24, 36, 48, 60, and 72 months. Results. Thirty-nine eyes from 29 patients, 17 (58.6%) females, were included. The mean follow-up time was 69.4 ± 34.5 months. BCVA was 59.3 ± 23.3 letters at baseline and 63.7 ± 21.9 letters at 48 months. At 3 months, BCVA improved 6.9 ± 11.7 letters (

P
=
0.003

). Then, BCVA remained stable. The mean foveal thickness decreased from 343.3 ± 120.2 μm at baseline to 268.3 ± 65.4 at 48 months (

P
=
0.021

). The mean number of injections was 4.6 ± 2.1 at 12 months, decreasing to 1.7 ± 2.4 injections between 36 and 48 months (

P
=
0.093

). Conclusion. This real-world study suggests that the functional and morphologic response to anti-VEGF therapy for CNV related to angioid streaks is generally satisfactory and maintained in the long term.
Granger Causality Analysis of Foreign Trade in Cement Products and Ecological Impact in China
Authors: Feng Chen
Published: July 2022

This paper presents an in-depth study and analysis of the impact of foreign trade on cement products and the ecological environment in China through Granger causality analysis. Based on the theoretical basis of foreign trade, ecological environment, and the relationship between them, a general equilibrium model is used to empirically analyze the “three effects” of foreign trade in Chinese cement products on the ecological environment, and the effects of import and export trade on ecological environment and the net effects are calculated, respectively. Then, based on the data of domestic and foreign cement product production and trade, the purpose, scope, and environmental impact factors of the ecological impact of foreign trade of Chinese cement products were determined by the life cycle assessment method, and the inventory analysis was carried out in phases based on the six aspects of nonrenewable resource depletion, global warming, photochemical ozone generation, acidification, eutrophication, and human health damage. The results were characterized and standardized, and the hierarchical analysis method was used to weight the evaluation of each environmental impact type, and finally, the resource consumption coefficient and environmental impact load index values and corresponding ratios were determined based on the green product evaluation method. This paper establishes an index system for the ecological and environmental impacts of foreign trade of cement products, which is a guide for the ecological and environmental impacts of foreign trade of other products in China. The results of the study on the ecological and environmental impacts of foreign trade of Chinese cement products also have important practical significance for the formulation of regulations and standards related to the cement industry, the adjustment of the import and export structure of cement products, and the improvement of production equipment and processes.
Change in Oxidative Stress and Mitochondrial Dynamics in Response to Elevated Cold-Inducible RNA-Binding Protein in Cardiac Surgery-Associated Acute Kidney Injury
Authors: Zheng Xinglong , Fan Yang , Li Jing , Ma Tao , Li Yongxin , Wang Qian , Yan Yang , Liu Wenyan
Published: July 2022

Cardiac surgery-associated acute kidney injury (CSA-AKI) is a common yet serious complication that is closely related to cardiopulmonary bypass (CPB). Extracellular cold-inducible RNA-binding protein (eCIRP) can mediate aseptic inflammation and trigger intracellular oxidative stress. In the present study, expression of serum CIRP was significantly elevated post-CPB (

785.0
±
640.5

 pg/mL vs.

149.5
±
289.1

 pg/mL,

P
<
0.001

) and was positively correlated with CPB duration (

r
=
0.502

,

P
<
0.001

). Patients with high expression of CIRP had higher risks of postoperative AKI than patients with low CIRP expression (OR: 1.67, 95% CI 1.04-2.68). In a rat CPB model, the serum CIRP concentration increased significantly after CPB. Similarly, the levels of Scr and BUN significantly increased 4 hours after CPB. KIM-1 and NGAL mRNA levels in the CPB group were 8.2 and 4.3 times higher than the sham group, respectively. In addition, the levels of inflammatory cell infiltration, oxidative stress, and apoptosis in the renal tissue of the CPB group were significantly higher compared to the sham group. The expression levels of serum inflammatory factors at 4 hours post-CPB were also increased. Administration of recombinant human CIRP protein promoted the expression of NADPH oxidase via the TLR-4/MyD88 pathway, aggravated intracellular oxidative stress, mediated mitochondrial dynamics disorder, and eventually increased apoptosis in HK-2 cells. However, the CIRP inhibitor C23 improved the CIRP-mediated oxidative stress and mitochondrial dysfunction in both rat and cell models. In summary, elevated CIRP could mediate oxidative stress and mitochondrial dynamics in the kidney to promote CSA-AKI.
Study on the Mechanism of circRNA Regulating the miRNA Level in Nephrotic Syndrome
Authors: Li Qianyu , Yin Min , Zhang Zhiping , Yu Yuanzhi , Liu Feng
Published: July 2022

Background. Nephrotic syndrome is an enormous public healthy threaten, which causes a variety of complications and secondary disease; however, the molecular mechanism of nephrotic syndrome remains unclear. Methods. In our study, RNA-seq were used to test the transcription level of patients with nephrotic syndrome, in order to investigate the interaction of circRNA-miRNA-mRNA in nephrotic syndrome patients. Results. Consistent with our hypothesis, miRNAs were confirmed to be associated with nephrotic syndrome, majority of their targeting circRNAs downregulated in nephrotic syndrome patients and at the same time, the KEGG pathway analysis found that target genes of the circRNAs bonding miRNAs was highly correlated with the occurrence of kidney diseases. Conclusion. Thus, we can draw a conclusion that downregulated circRNAs cause miRNA expressing aberrant and then affect the expression level of mRNA, finally leading to the generation of nephrotic syndrome.
High-Capacity Data Collection Platform for Smart Cities Using IEEE 802.11ad-Based Millimeter-Wave V2X Communication
Authors: Nakano Kosei , Motozuka Hiroyuki , Wee Gaius Yao Huang , Irie Masataka , Egami Akihiro , Sakamoto Takenori , Takinami Koji , Takahashi Kazuaki
Published: July 2022

The collection and utilization of huge sensor data from vehicles for visualizing the city is expected to realize various enhanced services for smart cities. A next-generation gigabit vehicle-to-everything (V2X) data collection platform based on 60 GHz millimeter-wave (mmWave) small cell radio access has been proposed in the previous work for enabling efficient and high-capacity data upload from vehicles to the cloud. This paper presents further analysis of the initial link setup delay to evaluate the effectiveness of the fast initial V2X link setup method proposed, which is suitable for 60 GHz communication based on IEEE 802.11ad. This paper also presents the application programming interface (API) design based on the hypertext transport protocol (HTTP) to enable the efficient upload of hundreds of files. Combined with the buffering technique at a multiaccess edge computing (MEC) server, the proposed system successfully utilizes very high bandwidth between a vehicle and a MEC server. The proposed methods achieve a 30 times improvement in delay for establishing the initial link and an 11 times higher average throughput. A prototype system installed in Marysville, Ohio, achieved a peak throughput of 2.8 Gbps and successfully demonstrates the effectiveness of city visualization based on high-capacity data collection and analytics.
English Proficiency Evaluation Model of College Students by Using Intuitive Fuzzy Information Theory
Authors: Tang Dongdong
Published: July 2022

English is a required university course in China and is a long-standing and consistent undergraduate-level course in China’s universities. It uses English as the medium and language of instruction to promote general education. As the most important content of undergraduate foreign language education, college English has different characteristics from other courses. It is only when its objectives, content, teaching activities, and assessment system fully reflect its unique requirements that it can truly achieve the ultimate goal of teaching this subject. With the advent of the information age, global economic integration and international exchange are deepening in various industries and fields. It is increasingly common for countries to require professionals to have foreign language skills, especially English as an international language. As a result, the demand for deeper English proficiency has become more prominent. In international communication, the English intercultural communication ability of key personnel directly affects the process of international communication, science and technology exchange, and the smooth transition of cultural conflicts in various fields and even determines the ultimate success of project cooperation. In this context, the effective use of English and cross-cultural communication skills is very important. Therefore, our higher education institutions are mainly responsible for training foreign language talents. However, the core problem facing English teaching in Chinese universities is the teaching value orientation. In particular, it seriously restricts the effectiveness of university English teaching. First, the value orientation of university English teaching deviates from the teaching objectives. It emphasizes the basic knowledge and skills of the English language, which makes teaching mainly stay on the foundation of the language. In other words, it is still limited to learning English for the sake of learning English, and the examination-oriented education is obvious, with a preference for instrumental teaching. Secondly, university English teaching focuses too much on the accumulation of English grammar rules and imitation drills, and the teaching style is dull and the teaching context is empty. This approach deviates from the characteristics of English intercultural communication, which makes the gap between the actual university English teaching and the real intercultural communication more and more obvious. Third, university English teaching lacks integration with other teaching values, especially with the humanistic orientation of university English teaching. Nowadays, a single teaching value orientation dominates university English teaching. As a result, the teaching around various English examinations has become a strange phenomenon in college English teaching.
Research on the Relationship between Beijing-Tianjin-Hebei Airport Group and Regional Coordinated Development
Authors: Li Yafei , Teng Meijun , Feng Yanjin
Published: July 2022

The mutual development of airport groups and regions is gradually going global with the economic globalization. There is a contradiction between Beijing-Tianjin-Hebei (Jing-Jin-Ji) Airport Group and regional development, which leads to the unbalanced development of aviation enterprises in the region. Therefore, it is of major theoretical and practical significance to analyze the coordinated development relationship between Jing-Jin-Ji Airport Group and the region. This paper selects representative index system, establishes the adaptability evaluation model of airport group and regional development, and quantitatively analyzes the adaptability level of Jing-Jin-Ji Airport Group and radiation area. Taking New York Airport Group as a reference, the synergy degree between Jing-Jin-Ji Airport Group and the region is evaluated by the synergy evaluation model. Analyze the reasons for the development of New York Airport Group, and put forward the measures for the coordinated development of Jing-Jin-Ji Airport Group and the region in the future. The results show that the synergy index (SD) of Jing-Jin-Ji Airport Group is 0.5381, which is lower than that of New York Airport Group (0.7507), and Jing-Jin-Ji Airport Group is barely synergetic. It is necessary to optimize airspace, allocate flight resources, speed up the development of airport economy, and optimize the structure of airport groups. Jing-Jin-Ji Airport Group will be accelerated to enter a high-quality collaborative stage from the aspects of system and resource integration and government leadership.
Approximate Maximum Likelihood Estimations for the Parameters of the Generalized Gudermannian Distribution and Its Characterizations
Authors: Rasekhi Mahdi , Saber Mohammad Mehdi , Hamedani G. G , El-Raouf M. M.Abd , Aldallal Ramy , Gemeay Ahmed M.
Published: July 2022

Generalized Gudermannian distribution is a symmetric distribution with location and scale parameters as an alternative to the well‐known symmetric distributions such as normal, Laplace, and Cauchy. This distribution has a simple closed form for the probability density function (pdf) and cumulative distribution function (cdf) and is more flexible than normal distribution based on kurtosis criterion. Certain characterizations of this distribution are presented. For this distribution, due to the nonlinear form of the likelihood equations, the maximum likelihood estimations (MLEs) of the location and scale parameters do not have closed forms and need a numerical approximation method with suitable starting values. A simple method of deriving explicit estimators by approximating the likelihood equations is presented. The bias and variance of these estimators are examined numerically and are shown that these estimators are as efficient as the maximum likelihood estimators. Some pivotal quantities are proposed for finding confidence intervals for location and scale parameters based on asymptotic normality. From the coverage probability, the MLEs do not work well especially for the small sample sizes; thus, to improve the coverage probability, simulated percentiles based on the Monte Carlo method are used. Finally, a real data set is presented to illustrate the suggested method and its inference related to this data set.
Extraction and Dyeing Techniques of Traditional Vegetable Dyestuffs
Authors: Li Guanggen
Published: July 2022

In order to explore the influencing factors of the extraction of vegetable dyes, a research method for the extraction and dyeing of traditional vegetable dyes was proposed. In this paper, the effects of extraction temperature, extraction time, and the ratio of solid to liquid on the extraction effect were discussed through orthogonal experiments. The dyeing process of silk extract was used in this study. The silk fabric was directly dyed with natural dye from peach leaves, compared with the three dyeing methods of premordant, same-bath mordant, and postmordant, and the color fastness to soaping of the dyed fabric was tested. The results show that the color fastness to soaping of leaf-dyed fabrics conforms to the national standard of superior grades, which effectively proves the correctness of the algorithm and model nature and superiority.
Application of Health Education Based on Phased Transition Theory Model in Continuous Nursing for Patients with Inflammatory Bowel Disease
Authors: Xiao Hongmei , Ye Jun
Published: July 2022

Objective. To explore the application effect of health education based on phased transition theory model in the continuous nursing for patients with inflammatory bowel disease (IBD). Method. A total of 106 patients with IBD admitted to the hospital were enrolled as the research objects between October 2020 and September 2021. According to random number table method, they were divided into observation group and control group, 53 cases in each group. The control group was given routine nursing, while observation group was additionally given health education based on phased transition theory model. The nutritional status (serum prealbumin (PA), albumin (ALB), body mass index (BMI)), scores of Disease Knowledge Mastery Scale, exercise of self-care agency scale (ESCA), and Inflammatory Bowel Disease Questionnaire (IBDQ) were compared between the two groups before and after intervention. Results. After intervention, PA, ALB, and BMI in observation group were higher than those in control group (

P
<
0.05

), scores of Disease Knowledge Mastery Scale, total mastery rate, scores and total score of ESCA, and scores and total score of IBDQ were significantly higher than those in control group (

P
<
0.05

). Conclusion. The application of health education based on phased transformation theory model in the continuous nursing improves disease knowledge mastery, self-care ability, nutritional status, and quality of life in IBD patients.
Deep Learning Models for Fast Retrieval and Extraction of French Speech Vocabulary Applications
Authors: Xu Man
Published: July 2022

Due to the large French vocabulary, how quickly retrieve and accurately identify the required vocabulary is still a big challenge in French learning. In view of the above problems, we introduce a deep learning algorithm in this study to upgrade and optimize the retrieval system of French words and optimize the acquisition speed of speech words data and the recognition accuracy of speech words, so as to meet the needs of users for word retrieval. The results show that the two training methods of SGD synchronous update network and alternate update network parameters for fast retrieval and extraction of French speech vocabulary reduce from a maximum of 11.65% to 4.25% in the WER criterion, with a maximum reduction of 7.4%; the two training methods of SGD synchronous update network and alternate update network parameters for fast retrieval and extraction of French speech vocabulary reduce from a maximum of 13.52% to 4.4% in the SER criterion. The training methods of fast retrieval and extraction of the SGD synchronous update network and alternate update network parameters in French speech vocabulary reduced from the highest 582 ms to 351 ms in the response time criterion, with a maximum reduction of 8.84%; the maximum reduction of 39.7%. In French speech vocabulary, SGD synchronous updating network and alternating updating network parameter algorithm are used to quickly retrieve and extract French words. When the number of iterations reaches 120, the model fitting accuracy of the training set reaches 90.05%, while the model can reach 94.5% in the test set. The system has a stronger generalization ability and a higher speech vocabulary recognition rate to meet the practical requirements.
Prediction of Retail Price of Sporting Goods Based on LSTM Network
Authors: Ding Hui
Published: July 2022

Commodity prices play a unique role as a lever to regulate the economy. Price forecasting is an important part of macrodecision-making and micromanagement. Because there are many factors affecting the price of goods, price prediction has become a difficulty in research. According to the characteristics that price data are also affected by other factors except for time series, a multifactor LSTM price prediction method is proposed based on the long-term and short-term memory network (LSTM) deep learning algorithm. This method not only makes use of the memory of LSTM to historical data but also introduces the influence of external factors on price through the full connection layer, which provides a new idea for solving the problem of price prediction. Compared with BP neural network, the experimental results show that this method has higher accuracy and better stability. Analyze the commodity description and commodity price characteristics, find out the commodities similar to the target commodity, complete the commodity price data by using the historical price data of similar commodities, and establish the training set to verify the validity of the proposed method.
Investigating the Mechanisms of Jieduquyuziyin Prescription Improves Lupus Nephritis and Fibrosis via FXR in MRL/lpr Mice
Authors: Liu Jingqun , Ma Qing , Sun Qice , Luo Qihan , Wang Yiheng , Wang Cheng , Zhu Akao , Zhao Lisha , Yin Lu , Lou Jiang , Dong Yu , Qiu Ping
Published: July 2022

Lupus nephritis (LN) is one of the most serious complications of systemic lupus erythematosus (SLE) and one of the leading causes of death. An alternative effective treatment to ameliorate and relieve LN and delay the process of renal tissue fibrosis is urgently needed in the clinical setting. Jieduquyuziyin prescription (JP) has been successfully used to treat SLE, but its potential mechanisms are not sufficiently understood. In this study, we treated MRL/lpr mice with JP for 8 weeks and treated human renal tubular epithelial cells (human kidney 2 (HK-2)) with drug-containing serum to observe the antagonistic effects of JP on inflammation and fibrosis, as well as to investigate the possible mechanisms. Results demonstrated that JP significantly reduced urinary protein and significantly improved pathological abnormalities. Metabolomics combined with ingenuity pathway analysis illustrated that the process of kidney injury in lupus mice may be closely related to farnesoid X receptor (FXR) pathway abnormalities. Microarray biomimetic analysis and LN patients indicated that FXR may play a protective role as an effective therapeutic target for LN and renal fibrosis. JP significantly increased the expression of FXR and inhibited the expression of its downstream targets, namely, nuclear transcription factor κB (NF-κB) and α-smooth muscle actin (α-SMA), in the kidney of MRL/lpr mice and HK-2 cells, as confirmed by in vitro and in vivo experiments. In conclusion, JP may mediate the activation of renal FXR expression and inhibit NF-κB and α-SMA expression to exert anti-inflammatory and antifibrotic effects for LN prevention and treatment.
Chemical Composition and Antibacterial and Antioxidant Activities of Stem Bark Essential Oil and Extracts of Solanecio gigas
Authors: Molla Yitayeh Mequanint , Monie Wassihun Amanu
Published: July 2022

Herbal medication developed from natural resources has to have antibacterial and antioxidant effects. The aim of this research is to look at the chemical makeup of Solanecio gigas (S. gigas) stem bark essential oil (EO), as well as the effectiveness of EO and extracts (chloroform, ethyl acetate, and methanol) against human pathogenic bacteria and their antioxidant activity. The GC-MS analysis identified 23 components, accounting for 98.7% of the total oil containing Methylene chloride (49.2%), sabinene (10.5%), 1-nonene (11.3%), Terpinen-4-ol (6.9%), Camphene (4.3%), γ-terpinene (3.6%), α-phellandrene (2.9%) β-myrcene (2.6%), 1,2,5-Oxadiazol-3-carboxamide, 4,4′-azobis-2,2′-dioxide (2.4%), α-terpinene (1.9%), 1-Octanamine, N-methyl- (1.9%), ρ-cymene (1.6%) as major components. The antibacterial efficacy of the EO and extracts (25, 50, 100, and 200 mg/ml) was demonstrated by the inhibitory zones (8.5 ± 0.47–23.3 ± 0.36 and 7.2 ± 0.25–22.0 ± 0.45 mm), respectively. The MIC values of the extracts and the EO were 120–150 and 240 to <1100 μg/ml, respectively. The EO also demonstrated a significant antibacterial impact. The EO and methanolic extract had free radical scavenging activities with IC50 value, 13.8 ± 0.48 and 4.2 ± 0.04 μg/ml, respectively. In comparison to the other extracts, the methanolic extract had the greatest phenolics (100.2 ± 0.13 μg GAE/mg of dry extract) and flavonoid contents (112.1 ± 0.18 μg CE/mg of dry extract).
Perception of Edentulous Patients and Dental Professionals towards Care and Maintenance of Complete Denture Prostheses
Authors: Nand Meenal , Mohammadnezhad Masoud
Published: July 2022

Background and objectives. Edentulism is a major public health concern globally relating to extensive loss of teeth. Due to paucity of study, this research aimed to explore the perception of edentulous patients (EDPs) and dental professionals (DPs) towards care and maintenance given to complete denture prostheses (CDP) in Fiji. Methods. A descriptive qualitative study was conducted among 30 EDPs attending dental prosthetic clinics (DPCs) at the four centres in Fiji and 28 DPs at the four DPCs under purposive sampling. Semi‐structured questionnaire with open‐ended questions was used for in‐depth interview (IDI) with EDPs via telephone and focus group discussion (FGD) with DPs virtually via Zoom. Participant responses were recorded and thematic analysis was used to manually analyze the verbatim transcripts. Results. Five themes were identified as perceptions of EDPs towards care and maintenance of CDP in Fiji: patient perceptions towards CDP, CDP care and maintenance, communication between DPs and EDPs, challenges faced in CDP, and management strategies to CDP care and maintenance. Seven themes were identified as perceptions of DPs: CDP guidelines, post‐denture insertion advice, care and maintenance, challenges while treating EDPs, management strategies to challenges faced, communication and teamwork, and recommendations to improving quality of CDP delivery in Fiji. Conclusion. Patients’ perception towards care and maintenance of CDP was low. It is highly recommended for EDPs to adhere to CDP advice given by DPs whilst for DPs, it had been recommended to provide written, oral, and visual forms of CDP care and maintenance advice to EDPs for effectiveness.
Most Effective Sampling Scheme for Prediction of Stationary Stochastic Processes
Authors: Saber Mohammad Mehdi , Shishebor Zohreh , Raouf M. M. Abd El , Hafez E.H. , Aldallal Ramy
Published: July 2022

The problem of finding optimal sampling schemes has been resolved in two models. The novelty of this study lies in its cost efficiency, specifically, for the applied problems with expensive sampling process. In discussed models, we show that some observations counteract other ones in prediction mechanism. The autocovariance function of underlying process causes mentioned result. Our interesting result is that, although removing neutralizing observations convert sampling scheme to nonredundant case, it causes to worse prediction. A simulation study confirms this matter, too.
A Method for Evaluating the Accuracy of Vocal Art Performance of Singers’ Voices Based on Sensor Space Localization Algorithm
Authors: Hongtao Wang , Li Gong
Published: July 2022

Recently, research on singing assessment has focused on analyzing singer characteristics rather than building an automated evaluating approach. Hence, there are many methods for evaluating the accuracy of singer’s singing performance. Traditional methods mostly use quantitative analysis approach for the accuracy analysis of vocal artistic performance, and the results have obvious ambiguity and correlation. Therefore, this paper proposes a method for evaluating the accuracy of vocal art expression of singers’ voices based on a sensor spatial localization algorithm. The adaptive cascade retrieval control approach is used to find and mine the singers’ performance based on their voice characteristics. The sensor spatial location algorithm and huge vocal music resources with high precision are utilized to locate the vocal music sources in the mining results. The vocal music of the singers is received through the vocal music preprocessing platform, which sends and controls musical compositions. The adaptive frequency’s shift filter and the wavelet transform method are used to filter out any noise in the music. Finally, the accurate evaluation of singer vocal artistic performance is realized from the aspects of music beat detection, note boundary accuracy analysis, and voiced segment accuracy detection. The experimental results show that our proposed method can reduce the error of the sound source’s localization and can effectively filter out the noise in the music signal.
A Review of Intraocular Pressure (IOP) and Axial Myopia
Authors: Zhang Dongyan , Wang Liyin , Jin Le , Wen Yingying , Zhang Xuhong , Zhang Liyue , Zhu Hong , Wang Ziyu , Yu Xin , Xie Chen , Tong Jianping , Shen Ye
Published: July 2022

The pathogenesis of myopia is driven by genetic and environmental risk factors. Accommodation not only alters the curvature and shape of the lens but also involves contraction of the ciliary and extraocular muscles, which influences intraocular pressure (IOP). Scleral matrix remodeling has been shown to contribute to the biomechanical susceptibility of the sclera to accommodation-induced IOP fluctuations, resulting in reduced scleral thickness, axial length (AL) elongation, and axial myopia. The rise in IOP can increase the burden of scleral stretching and cause axial lengthening. Although the accommodation and IOP hypotheses were proposed long ago, they have not been validated. This review provides a brief and updated overview on studies investigating the potential role of accommodation and IOP in myopia progression.
Network Pharmacology-Based Strategy to Reveal the Mechanism of Cassiae Semen against Cataracts
Authors: Zhong Ying , Chen Ruo-fu , Fang You-fa
Published: July 2022

Cassiae semen (CS) is one of the most well-known herbs used in the treatment of cataracts in China. However, the potential mechanisms of its anticataract effects have not been fully explored. In this study, network pharmacology was used to investigate the potential mechanism underlying the actions of CS against cataracts, and molecular docking was performed to analyze the binding activity of proteins and compounds. qPCR was performed to detect the mRNA level of genes, and the cell apoptotic rate was measured using flow cytometry. We identified 13 active compounds from CS and 105 targets, as well as 238 cataract-related targets. PPI networks were constructed, and fifty key targets were obtained. These key targets were enriched in the regulation of transcription, apoptotic process, and signal transduction pathways. Molecular docking demonstrated that the compounds of CS exhibited good affinity to some critical targets. Furthermore, CS prevented the apoptosis of human lens epithelial cells induced by UVB lights by decreasing the gene expression of CASP3, ESR1, and TP53 and increasing the CRYAB gene expression. The present study attempted to explain the mechanisms for the effects of CS in the prevention and treatment of cataracts and provided an effective strategy to investigate active ingredients from natural medicines. Further studies are required to verify these findings via in vivo and in vitro experiments.
The Comparison of Clinical Efficacy of Minimally Invasive Tarsal Sinus Approach and L-Type Incision Approach Combined with 3D Printing Technology in Calcaneal Fracture
Authors: Du Hao , Li Shiang , Tu Shicheng , Wang Kun , Fang Zhiyu
Published: July 2022

Purpose. To explore the comparison of the reduction of the subtalar articular surface and other postoperative effects of the minimally invasive tarsal sinus approach and lateral L-shaped incision conventional approach for the treatment of calcaneal fracture with 3D printing technology. Methods. Patients who received surgical treatment for calcaneal fractures in the First Affiliated Hospital of Henan University of Science and Technology from June 2019 to December 2020 were collected. 3D printing equipment produced the affected side reduction heel bone fracture model and navigation template model. The tarsal sinus approach was used in the experimental group, and the lateral L-shaped incision approach was used in the control group. Patients were followed up 3 days, 1 month, 3 months, 6 months, and 12 months after the operation. Imaging indicators were measured 12 months after surgery, and scores from American Foot and Ankle Orthopaedic Society (AOFAS) and MSF were performed. Results. Operation time was

70.52
±
13.16

in the control group and

55.24
±
12.25

minutes in the experimental group (

P
<
0.001

). Intraoperative blood loss was

98.77
±
18.65

in the control group and

89.56
+
17.54

in the experimental group (

P
>
0.05

). The duration of antibiotic use was

5.53
±
3.24

days in the control group and

5.48
±
4.18

days in the experimental group (

P
>
0.05

). The frequency of fluoroscopy was

6.56
±
1.72

in the control group and

3.88
±
1.05

in the experimental group (

P
<
0.001

). Fracture healing time was

3.24
±
0.52

months in the control group and

3.08
±
0.58

months in the experimental group (

P
>
0.05

). The postoperative Böhler angle was

28.31
±
3.14

in the control group and

29.24
±
2.76

in the experimental group (

P
>
0.05

). Postoperative subtalar articular displacement (

step
>
2

 mm) was observed in 4 patients in the control group and 1 in the experimental group (

P
<
0.05

). MSF score was

90.12
±
4.85

in the control group and

91.36
±
2.58

in the experimental group (

P
>
0.05

). Conclusion. The study found that the experimental group was significantly better than the control group in terms of the operation time, intraoperative fluoroscopy times, and success rate of reduction of the subtalar articular surface. 3D printing technology can shorten the operation time, accurately reduce the fracture block, and reduce the secondary trauma, which is conducive to the functional recovery of the affected foot.
Human Sports Action and Ideological and PoliticalEvaluation by Lightweight Deep Learning Model
Authors: Li Mingqian , Zhao Jing
Published: July 2022

The purpose is to automatically and quickly analyze whether the rope skipping actions conform to the standards and give correct guidance and training plans. Firstly, aiming at the problem of motion analysis, a deep learning (DL) framework is proposed to obtain the coordinates of key points in rope skipping. The framework is based on the OpenPose method and uses the lightweight MobileNetV2 instead of the Visual Geometry Group (VGG) 19. Secondly, a multi-label classification model is proposed: attention long short-term memory-long short-term memory (ALSTM-LSTM), according to the algorithm adaptive method in the multi-label learning method. Finally, the validity of the model is verified. Through the analysis and comparison of simulation results, the results show that the average accuracy of the improved OpenPose method is 77.8%, an increase of 3.3%. The proposed ALSTM-LSTM model achieves 96.1% accuracy and 96.5% precision. After the feature extraction model VGG19 in the initial stage of OpenPose is replaced by the lightweight MobileNetV2, the pose estimation accuracy is improved, and the number of model parameters is reduced. Additionally, compared with other models, the performance of the ALSTM-LSTM model is improved in all aspects. This work effectively solves the problems of real-time and accurate analysis in human pose estimation (HPE). The simulation results show that the proposed DL model can effectively improve students’ high school entrance examination performance.