bluuebunny/crossref_metadata_2025 huggingface dataset:
Intramolecular cyclization of 15-carboxy-13-amide derivatives of chlorin e6 under the action of 2-Chloro-1-methylpyridinium iodide
Authors: Mal’shakova Marina V , Belykh Dmitriy V.
Published: June 2022

We have shown the possibility of intramolecular cyclization with the participation of the carboxyl group at position 15 of the chlorin macrocycle with a primary or secondary amide group at position 13 through the formation of an imide bond under the action of 2-Chloro-1-methylpyridinium iodide; the imide bond can be used to form a seven-membered exocycle. Using this reaction, we synthesized a number of cycloimide derivatives of chlorophyll a. The proposed synthetic route can be carried out if the substituent at the amide nitrogen atom has a hydroxyl, dimethylaminomethyl or vinyl group, which opens up possibilities for further chemical modification of the obtained derivatives.
Food, Mood, Context: Examining College Students’ Eating Context and Mental Well-being
Authors: Morshed Mehrab Bin , Kulkarni Samruddhi Shreeram , Saha Koustuv , Li Richard , Roper Leah G. , Nachman Lama , Lu Hong , Mirabella Lucia , Srivastava Sanjeev , de Barbaro Kaya , de Choudhury Munmun , Plötz Thomas , Abowd Gregory
Published: June 2022

Deviant eating behavior such as skipping meals and consuming unhealthy meals has a significant association with mental well-being in college students. However, there is more to what an individual eats. While eating patterns form a critical component of their mental well-being, insights and assessments related to the interplay of eating patterns and mental well-being remain under-explored in theory and practice. To bridge this gap, we use an existing real-time eating detection system that captures context during meals to examine how college students’ eating context associates with their mental well-being, particularly their affect, anxiety, depression, and stress. Our findings suggest that students’ irregularity or skipping meals negatively correlates with their mental well-being, whereas eating with family and friends positively correlates with improved mental well-being. We discuss the implications of our study in designing dietary intervention technologies and guiding student-centric well-being technologies.
Deep Genetic Programming Trees Are Robust
Authors: Langdon William B.
Published: June 2022

We sample the genetic programming tree search space and show it is smooth, since many mutations on many test cases have little or no fitness impact. We generate uniformly at random high-order polynomials composed of 12,500 and 750,000 additions and multiplications and follow the impact of small changes to them. From information theory, 32 bit floating point arithmetic is dissipative, and even with 1,501 test cases, deep mutations seldom have any impact on fitness. Absolute difference between parent and child evaluation can grow as well as fall further from the code change location, but the number of disrupted fitness tests falls monotonically. In many cases, deeply nested expressions are robust to crossover syntax changes, bugs, errors, run time glitches, perturbations, and so on, because their disruption falls to zero, and so it fails to propagate beyond the program.
A Study on the Performance of Recurrent Neural Network based Models in Maithili Part of Speech Tagging
Authors: Priyadarshi Ankur , Saha Sujan Kumar
Published: June 2022

This article presents our effort in developing a Maithili Part of Speech (POS) tagger. Substantial effort has been devoted to developing POS taggers in several Indian languages, including Hindi, Bengali, Tamil, Telugu, Kannada, Punjabi, and Marathi; but Maithili did not achieve much attention from the research community. Maithili is one of the official languages of India, with around 50 million native speakers. So, we worked on developing a POS tagger in Maithili. For the development, we use a manually annotated in-house Maithili corpus containing 56,126 tokens. The tagset contains 27 tags. We train a conditional random fields (CRF) classifier to prepare a baseline system that achieves an accuracy of 82.67%. Then, we employ several recurrent neural networks (RNN)-based models, including Long-short Term Memory (LSTM), Gated Recurrent Unit (GRU), LSTM with a CRF layer (LSTM-CRF), and GRU with a CRF layer (GRU-CRF) and perform a comparative study. We also study the effect of both word embedding and character embedding in the task. The highest accuracy of the system is 91.53%.
TURL
Authors: Deng Xiang , Sun Huan , Lees Alyssa , Wu You , Yu Cong
Published: June 2022

Relational tables on the Web store a vast amount of knowledge. Owing to the wealth of such tables, there has been tremendous progress on a variety of tasks in the area of table understanding. However, existing work generally relies on heavily-engineered task-specific features and model architectures. In this paper, we present TURL, a novel framework that introduces the pre-training/fine-tuning paradigm to relational Web tables. During pre-training, our framework learns deep contextualized representations on relational tables in a self-supervised manner. Its universal model design with pre-trained representations can be applied to a wide range of tasks with minimal task-specific fine-tuning.
Numerical Simulation and Modeling of Hydrogen Gas Evolution on Planar and Microwire Array Electrodes
Authors: Chen Yikai , Lewis Nathan S.
Published: June 2022

The impact of gas evolution on the electrochemical characteristics of planar electrodes and microwire array electrodes has been analyzed using modeling and simulation. The impacts can mainly be broken into three phenomena: a) a shift in the local reversible hydrogen electrode potential; b) hyperpolarization; and c) an increase in the solution resistance of the electrolyte. The local reversible hydrogen electrode potential shift was found to play the most important role, constituting >40% of the total potential drop between the cathode and reference electrode, following correction for cell resistance. Compared to planar electrodes, a microwire array structure reduces the impact of bubbles on the solution conductance, but the shift in the local reversible hydrogen electrode potential varies with distance from the actual electrode surface.
Mechanisms of Exclusive Scale Formation in the High Temperature Oxidation of Alloys
Authors: Blades William H. , Opila Elizabeth J. , Sieradzki Karl
Published: June 2022

The high temperature oxidation of alloys is most often considered within the continuum framework developed by C. Wagner. We argue that in order to make progress in understanding exclusive scale formation, one needs to examine the atomic-scale kinetic processes that today are amenable to a variety of experimental, computational and theoretical approaches. In our discussion, we suggest that there is an analogy between the kinetic processes required for exclusive scale formation and thin film layer-by-layer growth. In both cases, the magnitude of the Ehrlich-Schwoebel barrier sets an effective length scale for growth, that if too large, results in three-dimensional rather than lateral island or oxide growth. In this event, exclusive scale formation can only occur if there is a sufficiently large density of oxide nucleation events at the surface of the alloy. We suggest that a suitably identified, dilute alloy component, could serve as a “surfactant” that segregates to the surface and is capable of enhancing the nucleation density.
Defining the versican interactome in lung health and disease
Authors: Tang Fengying , Brune Jourdan E. , Chang Mary Y. , Reeves Stephen R. , Altemeier William A. , Frevert Charles W.
Published: June 2022

The extracellular matrix (ECM) imparts critical mechanical and biochemical information to cells in the lungs. Proteoglycans are essential constituents of the ECM and play a crucial role in controlling numerous biological processes, including regulating cellular phenotype and function. Versican, a chondroitin sulfate proteoglycan required for embryonic development, is almost absent from mature, healthy lungs and is reexpressed and accumulates in acute and chronic lung disease. Studies using genetically engineered mice show that the versican-enriched matrix can be pro- or anti-inflammatory depending on the cellular source or disease process studied. The mechanisms whereby versican develops a contextual ECM remain largely unknown. The primary goal of this review is to provide an overview of the interaction of versican with its many binding partners, the “versican interactome,” and how through these interactions, versican is an integrator of complex extracellular information. Hopefully, the information provided in this review will be used to develop future studies to determine how versican and its binding partners can develop contextual ECMs that control select biological processes. Although this review focuses on versican and the lungs, what is described can be extended to other proteoglycans, tissues, and organs.
Urokinase-type plasminogen activator negatively regulates α-smooth muscle actin expression via Endo180 and the uPA receptor in corneal fibroblasts
Authors: Sugioka Koji , Nishida Teruo , Kodama-Takahashi Aya , Murakami Junko , Mano Fukutaro , Okada Kiyotaka , Fukuda Masahiko , Kusaka Shunji
Published: June 2022

Corneal fibroblasts are embedded within an extracellular matrix composed largely of collagen type 1, proteoglycans, and other proteins in the corneal stroma, and their morphology and function are subject to continuous regulation by collagen. During wound healing and in various pathological conditions, corneal fibroblasts differentiate into myofibroblasts characterized by the expression of α-smooth muscle actin (α-SMA). Endo180, also known as urokinase-type plasminogen activator (uPA) receptor-associated protein (uPARAP), is a collagen receptor. Here we investigated whether targeting of Endo180 and the uPA receptor (uPAR) by uPA might play a role in the regulation of α-SMA expression by culturing corneal fibroblasts derived from uPA-deficient ( uPA−/−) or wild-type ( uPA+/+) mice in a collagen gel or on plastic. The expression of α-SMA was upregulated, the amounts of full-length Endo180 and uPAR were increased, and the levels of both transforming growth factor-β (TGF-β) expression and Smad3 phosphorylation were higher in uPA−/− corneal fibroblasts compared with uPA+/+ cells under the collagen gel culture condition. Antibodies to Endo180 inhibited these effects of uPA deficiency on α-SMA and TGF-β expression, whereas a TGF-β signaling inhibitor blocked the effects on Smad3 phosphorylation and α-SMA expression. Our results suggest that uPA deficiency might promote the interaction between collagen and Endo180 and thereby increase α-SMA expression in a manner dependent on TGF-β signaling. Expression of α-SMA is thus negatively regulated by uPA through targeting of Endo180 and uPAR.
The dissociable effects of reward on sequential motor behavior
Authors: Sporn Sebastian , Chen Xiuli , Galea Joseph M.
Published: June 2022

Our work provides a mechanistic framework for how reward influences motor behavior. Specifically, we show that rapid improvements in speed and accuracy are driven by reward presented in the form of money, whereas knowledge of performance through performance feedback leads to training-based improvements. Importantly, combining both maximized performance gains and led to improvements in movement quality through fusion, which describes an optimization process during which sequential movements blend into a single action.
Distribution of cardiomyocyte-selective adeno-associated virus serotype 9 vectors in swine following intracoronary and intravenous infusion
Authors: Li Jinliang , Kelly Shannon C. , Ivey Jan R. , Thorne Pamela K. , Yamada Kelly P. , Aikawa Tadao , Mazurek Renata , Turk James R. , Silva Kleiton Augusto Santos , Amin Amira R. , Tharp Darla L. , Mueller Christina M. , Thakur Hrishikesh , Leary Emily V. , Domeier Timothy L. , Rector R. Scott , Fish Kenneth , Cividini Federico , Ishikawa Kiyotake , Emter Craig A. , Kapiloff Michael S.
Published: June 2022

Limited reports exist regarding adeno-associated virus (AAV) biodistribution in swine. This study assessed biodistribution following antegrade intracoronary and intravenous delivery of two self-complementary serotype 9 AAV (AAV9sc) biologics designed to target signaling in the cardiomyocyte considered important for the development of heart failure. Under the control of a cardiomyocyte-specific promoter, AAV9sc.shmAKAP and AAV9sc.RBD express a small hairpin RNA for the perinuclear scaffold protein muscle A-kinase anchoring protein β (mAKAPβ) and an anchoring disruptor peptide for p90 ribosomal S6 kinase type 3 (RSK3), respectively. Quantitative PCR was used to assess viral genome (vg) delivery and transcript expression in Ossabaw and Yorkshire swine tissues. Myocardial viral delivery was 2–5 × 105 vg/µg genomic DNA (gDNA) for both infusion techniques at a dose ∼1013 vg/kg body wt, demonstrating delivery of ∼1–3 viral particles per cardiac diploid genome. Myocardial RNA levels for each expressed transgene were generally proportional to dose and genomic delivery, and comparable with levels for moderately expressed endogenous genes. Despite significant AAV9sc delivery to other tissues, including the liver, neither biologic induced toxic effects as assessed using functional, structural, and circulating cardiac and systemic markers. These results indicate successful targeted delivery of cardiomyocyte-selective viral vectors in swine without negative side effects, an important step in establishing efficacy in a preclinical experimental setting.
Supervised Machine Learning Empowered Multifactorial Genetic Inheritance Disorder Prediction
Authors: Ghazal Taher M. , Al Hamadi Hussam , Umar Nasir Muhammad , Atta-ur-Rahman  , Gollapalli Mohammed , Zubair Muhammad , Adnan Khan Muhammad , Yeob Yeun Chan
Published: June 2022

Fatal diseases like cancer, dementia, and diabetes are very dangerous. This leads to fear of death if these are not diagnosed at early stages. Computer science uses biomedical studies to diagnose cancer, dementia, and diabetes. With the advancement of machine learning, there are various techniques which are accessible to predict and prognosis these diseases based on different datasets. These datasets varied (image datasets and CSV datasets) around the world. So, there is a need for some machine learning classifiers to predict cancer, dementia, and diabetes in a human. In this paper, we used a multifactorial genetic inheritance disorder dataset to predict cancer, dementia, and diabetes. Several studies used different machine learning classifiers to predict cancer, dementia, and diabetes separately with the help of different types of datasets. So, in this paper, multiclass classification proposed methodology used support vector machine (SVM) and K-nearest neighbor (KNN) machine learning techniques to predict three diseases and compared these techniques based on accuracy. Simulation results have shown that the proposed model of SVM and KNN for prediction of dementia, cancer, and diabetes from multifactorial genetic inheritance disorder achieved 92.8% and 92.5%, 92.8% and 91.2% accuracy during training and testing, respectively. So, it is observed that proposed SVM-based dementia, cancer, and diabetes from multifactorial genetic inheritance disorder prediction (MGIDP) give attractive results as compared with the proposed model of KNN. The application of the proposed model helps to prognosis and prediction of cancer, dementia, and diabetes before time and plays a vital role to minimize the death ratio around the world.
[Retracted] Efficacy of Self‐Made Hewei Decoction for Chronic Atrophic Gastritis and Its Effect on Gastrin and Pepsinogen Expression Levels
Authors: Ou Jianyun , Wang Lin
Published: June 2022

We aim to investigate the therapeutic effect of self‐made Hewei decoction based on the differences‐in‐differences (DID) model for treating chronic atrophic gastritis and its effect on the gastrin and pepsinogen expression. A total of 166 chronic atrophic gastritis patients treated in our hospital from January 2019 to September 2020 were recruited and randomly assigned to a treatment group and a control group (n = 83 per group). In the control group, patients were given conventional western medicine. In the treatment group, patients were administered self‐made Hewei decoction besides conventional western medicine. The general data, total effective rate, and histological changes before and after treatment were compared between the two groups. The DID model was utilized to compare the changes in three items of gastric function and traditional Chinese medicine (TCM) syndrome scores at various time points (before treatment and 1, 3, 6, and 12 months after treatment) between the two groups. In the treatment group, 5 cases were lost to follow‐up, and 78 cases remained. In the control group, 4 cases were lost to follow‐up, and 79 cases remained. The total effective rate in the treatment group (93.59%) was significantly higher than that in the control group (82.28%) (P < 0.05). The histological score was not significantly different between the two groups before treatment (P > 0.05). The histological score at 12 months after treatment was lower than those before treatment in the two groups (P < 0.05). The histological score was lower in the treatment group than that in the control group (P < 0.05). After treatment, the TCM syndrome score and PGR17 level were lower in the treatment group than those in the control group at each time point (P < 0.05). PGI and PGII levels were higher in the treatment group than those in the control group at each time point (P < 0.05). DID regression model showed that TCM syndrome score and PGR17 level decreased by 106.2% and 65.8%, respectively, after treatment in patients with chronic atrophic gastritis (P < 0.05), but the treatment mode was opposite to the overall therapeutic effect in terms of time. The PGI and PGII levels increased by 102.9% and 97.8%, respectively, in patients with chronic atrophic gastritis (P < 0.05), and the treatment mode was the same as the overall therapeutic effect in terms of time. There was no significant difference in the therapeutic effect between the two groups at 1 month after treatment. A significant difference in the therapeutic effect was detected between the two groups at 3 months after treatment, and the difference showed a decreasing trend after 6 months after treatment. Self‐made Hewei decoction can improve the histological alterations in chronic atrophic gastritis, relieve clinical symptoms, and ameliorate the expression levels of three items of gastric function.
Industrial Robot Vibration Anomaly Detection Based on Sliding Window One-Dimensional Convolution Autoencoder
Authors: Zhong ZhiDan , Zhao Yao , Yang AoYu , Zhang HaoBo , Qiao DongHao , Zhang ZhiHui
Published: June 2022

Model-based methods can be used to detect anomalies in industrial robots, but they require a high level of expertise and are therefore difficult to implement. The lack of sufficient data on the anomalous operation of industrial robots limits data-driven anomaly detection methods. This study proposes Sliding Window One-Dimensional Convolutional Autoencoder (SW1DCAE), an unsupervised vibration anomaly detection algorithm for industrial robots, that can directly act on the original vibration signal and effectively improve detection accuracy. First, the convolutional neural network and the autoencoder model are effectively integrated to construct a one-dimensional convolutional autoencoder model. Secondly, the sliding window algorithm is used for data enhancement, and the dropout technique is introduced to improve the generalization ability of the model. Finally, the reconstruction error of the input sample is calculated and compared with the error threshold to determine whether the operation state of the industrial robot is normal or not. This study discusses the effect of different convolution kernel widths, sliding window sizes, dropout ratios, and other parameters on model performance. Validation with vibration signals collected from an industrial robot test bench shows that this unsupervised anomaly detection algorithm has good accuracy and F1 score.
Classification and Pathological Diagnosis of Idiopathic Interstitial Pneumonia
Authors: Chen Zhihua , Huang Wenqiang , Song Yibo
Published: June 2022

Idiopathic interstitial pneumonia (IIP) is a group of progressive lower respiratory tract diseases of unknown origin characterized by diffuse alveolitis and alveolar structural disorders leading to pulmonary fibrillation and hypertension, pulmonary heart disease, and right heart failure due to pulmonary fibrosis, and more than half of them die from respiratory failure. To address these problems of overly complex prediction methods and large data sets involved in the prediction process of interstitial pneumonia, this paper proposes a prediction model for interstitial pneumonia which is based on the Gaussian Parsimonious Bayes algorithm. Three usual tests of pneumonia, specifically from various patients, were collected as the sample set. These samples are divided into training and testing sets. Additionally, a cross-validation strategy was used to avoid the overfitting problem. The results showed that the prediction model based on the Gaussian Parsimonious Bayes algorithm predicted 92% accuracy on the test set, and the Parsimonious Bayes method could directly predict the final detection of interstitial pneumonia based on the usual pneumonia test pneumonia. In addition, it was found that the closer the data distribution of the sample set was to a normal distribution, the higher the prediction accuracy was, and then, after excluding pneumonia from the test below 60 points, the prediction accuracy reached 96%.
On System of Mixed Fractional Hybrid Differential Equations
Authors: Awadalla Muath , Mahmudov Nazim I.
Published: June 2022

In this article, we find the necessary conditions for the existence and uniqueness of solutions to a system of hybrid equations that contain mixed fractional derivatives (Caputo and Riemann-Liouville). We also verify the stability of these solutions using the Ulam-Hyers (U-H) technique. Finally, this study ends with applied examples that show how to proceed and verify the conditions of our theoretical results.
A Synergistic Effect of Moringa oleifera-Based Coagulant and Ultrafiltration for the Wastewater Treatment Collected from Final ETP
Authors: Rai Ashita , Amari Abdelfattah , Yadav Virendra Kumar , Ismail Mohamed A. , Elboughdiri Noureddine , Fulekar M. H. , Basnet Anup
Published: June 2022

Provision of safe drinking water, devoid of aetiologies, is an all-time challenge due to the usage of unsafe chemicals in most of the water treatment processes. The main objective of the present paper is to evaluate the use of Moringa oleifera (MO) as a natural coagulant in coagulation/flocculation (C/F) followed by the ultrafiltration (UF) of Final Effluent Treatment Plant wastewater treatment which can also be employed as an alternative to the present conventional methods of treatment. Process efficiency was evaluated in terms of chemical oxygen demand (COD), biochemical oxygen demand (BOD), turbidity, total hardness, alkalinity, ammoniacal nitrogen, and zeta potential along with permeability and fouling behaviour of the membrane. A significant improvement in both the physical and chemical characteristics of the effluent quality is showing a clearer colour and a greater reduction in BOD (89.74%) and COD (63.80%) values, while pH was in the acceptable range for effluent disposal. The results indicate a lower membrane fouling rate (49%), an increase in permeate flow, and better quality of the permeate, proving that the C/F-UF treatment is an effective and efficient technique for wastewater treatment. Eventually, the treated wastewater obtained with this process generates better quality water and preserves the aquatic ecosystem.
Hierarchical Lattice Modeling Method with Gradient Functions
Authors: Cheng Cheng , Dai Ning , Gu Weiping , Xu Bai , Xu Jing
Published: June 2022

Lattice structure materials have great application potential in biomedical, aerospace, and other fields. In fact, designing multilevel structure parametrically to achieve excellent mechanical performance is a challenging task. In this paper, a hierarchical lattice modeling method with gradient functions is proposed on the basis of the multilevel structural characteristics of organisms to solve the problem of the coexistence of high hardness, high strength, and high toughness. The multilevel body space is filled with matching lattices in accordance with the given dynamic parameters, and the design is optimized in accordance with the simulation results. Thus, the desired composite functional structure is generated. In fact, the proposed method is divided into two stages, that is, preprocessing and design. In the former stage, the interpolation method is used to establish a lattice unit model family retrieved by parameters, such as elastic modulus and impact toughness. In the latter stage, the multilevel 3D reconstruction model is initially filled with the gradient multilevel lattices through the global optimization technique with an isosurface modeling algorithm. The porosity, rod diameter, and other parameters of the lattice structure are regulated in accordance with the results of finite element analysis through image mapping, meeting the requirements of biomechanical characteristics. Our empirical evaluation and experimental results demonstrate that the proposed method can control the relationship between porous structure porosity, elastic modulus, and impact toughness and design bionic multispace microstructures close to biodental displacement and deformation.
Using Emoji in Response to Customer Reservation Requests and Service Reviews
Authors: Prada Marília , Saraiva Magda , Cruz Sara , Xavier Sílvia , Rodrigues David L.
Published: June 2022

The use of paralinguistic cues—including emoji—in computer-mediated communication has become prevalent in recent years. Brands and service providers have also been using these cues in their communication strategies. And yet, research examining how such emoji use influences customers’ perception and behavior is still scarce. In two experiments (combined

N
=
401

), we tested if using emoji to reply to a customer request (restaurant reservation, Study 1) or online review (hotel experience, Study 2) influenced perceptions of the brands. The emoji used by the brand was always congruent with the valence of the situation. Results from both studies revealed that the presence (vs. absence) of emoji influenced consumers’ perception of the brand/service at several levels. Specifically, the restaurant/hotel was perceived to have a more informal communication style, have a warmer service, and be more modern. In Study 1, we also observed that emoji use had a positive impact on competence perception and reservation intentions. Importantly, these effects of emoji use were not moderated by the valence of the situation. Taken together, our results showed that emoji can influence different perceptions about brands and services and determine how customers relate to brands.
Be Kind to Your Behind: A Systematic Review of the Habitual Use of Bidets in Benign Perianal Disease
Authors: Baig Zarrukh , Abu-Omar Nawaf , Harington Michael , Gill Dilip , Nathan Ginther David
Published: June 2022

Background. Benign perianal disease carries significant morbidity and financial burden on the healthcare system. Given that sitz baths are recommended as a treatment modality, we considered whether using a continuous stream of water, in the form of a bidet, offers a convenient and effective alternative. Bidet use is the predominant form of perianal hygiene in Asia, but its role in perianal disease is unknown. Purpose. To critically analyze and systematically review the current evidence regarding the effect of habitual bidet use on symptoms of benign perianal disease. Data Sources. A database search was conducted on MEDLINE and Epub Ahead of Print, Embase, ClinicalTrials.gov, the Cochrane Library, and ProQuest Dissertations. All studies on bidet use in pruritus ani, hemorrhoids, or anal fissures were included. Data Extraction. The studies were screened and critically analyzed by two independent reviewers in line with PRISMA guidelines. Results. Two prospective trials and 1 cross-sectional study found that habitual use of bidets had no impact on the odds of developing hemorrhoids or hemorrhoidal symptoms. One RCT concluded that using bidets was non-inferior to sitz bath for post-hemorrhoidectomy pain. Two prospective trials and 1 cross-sectional study determined that habitual bidet use may increase the odds of developing pruritus ani. Two case series found that habitual bidet use may cause perianal burns or anterior anal fissures. A meta-analysis was not performed because only a limited number of studies were available, and they were of variable quality. Conclusion. The current evidence does not identify using bidets as a treatment modality for perianal disease, and further research is warranted to study this increasingly utilized technology.
Model Construction of Dance Teaching System for College Students under the Background of Information Technology
Authors: Zhou Li
Published: June 2022

The rapid growth of computer network technology has changed the way people communicate and learn. The way of acquiring knowledge is also much more advanced than before. Under the guidance of correct teaching methods and teaching thinking, dance teaching methods must try new methods, adjust teaching contents, and change narrow inertia thinking. Online distance education is a new type of education method that transcends the time and space limitations of traditional education methods, making it easier for more people to learn and share more educational resources. The dance education system for college students proposed in this paper describes the design and related technologies of the B/S-based online education system. The system can provide technical parameters such as composition alignment, movement mechanical rationality, and vocal-dance coordination for sports choreographers and can be used as a competent assistant for sports choreographers. The experiment resulted in interviews with 30 teachers and 50 students, which were recorded and data entered using a form to verify the reliability of the data. The multimedia network environment has undergone significant changes, and 83% of the teachers and students have updated their concepts and agreed with the new teaching model. Therefore, introducing information technology into dance education can optimize resources, enrich the performance context of dance education, broaden the horizons of teachers and students, and use information technology for direct appreciation and design.
A Novel DC-Power Control Method for Cascaded Converter under DC Voltage-Imbalance Condition
Authors: Xia Zhenglong , Wu Qifan , Ye Zongbin , Yu Dongsheng , Zhu Lanqiao , Hu Wenhao
Published: June 2022

This paper proposes an interphase power control algorithm (IPCA) and submodule power control algorithm (SPCA) based on state transition PWM (ST-PWM) for cascaded H-bridge inverter with unbalanced DC sources. In this method, the correction value helps control the interphase power distribution and submodule power distribution by directly modifying the duty cycle of each switching state. In order to achieve linear modulation, an in-depth analysis of ST-PWM is conducted. Combining ST-PWM and IPCA, balanced AC currents and accurate power control on DC side can be achieved with an unbalanced DC source. The proposed strategies are simulated using MATLAB/Simulink and tested on a five-level laboratory prototype. Simulation and experimental results demonstrate the advantage and effectiveness of the proposed algorithm.
Polymyxin B, Cefoperazone Sodium-Sulbactam Sodium, and Tigecycline against Multidrug-Resistant Acinetobacter baumannii Pneumonia
Authors: Hu Guangxue , Liu Wanzong , Wang Mali
Published: June 2022

Purpose. The purpose of this study is to investigate the significance of polymyxin B in combination with cefoperazone sodium-sulbactam sodium (CSSS) and tigecycline for the treatment of multidrug-resistant Acinetobacter baumannii- (MDRAB-) induced pneumonia on the levels of white blood cell (WBC) count, serum C-reactive protein (CRP), and procalcitonin (PCT). Methods. Fifty-six patients with MDRAB pneumonia admitted to the Fifth People’s Hospital of Wuhu from February 2019 to December 2021 were randomized into the observation group (n = 28) and the experimental group (n = 28) by the random table method. The observation group received intravenous infusion of CSSS and tigecycline. The experimental group received intravenous infusion of polymyxin B sulfate plus CSSS and tigecycline. All patients were treated for 14 days. Results. There was no significant difference in the overall response rate between the two groups; the bacterial clearance of the experimental group was significantly higher than that of the observation group; there was no significant difference in the WBC, CRP, and PCT levels between the two groups prior to the treatment; but after treatment, while the WBC, CRP, and PCT levels of the two groups decreased, the WBC count, CRP, and PCT levels of the experimental group were significantly lower than those of the observation group; no significant difference was found in adverse reactions. Conclusion. Polymyxin B-CSSS-tigecycline has good clinical efficacy in the treatment of MDRAB pneumonia. It not only improves the patients’ bacterial clearance rate and effectively reduces the levels of WBC count, serum CRP, and PCT, but also raises no risk of adverse reactions. Therefore, it is worthy of clinical promotion.
Relationship between Enterprise Financing Structure and Business Performance Assisted by Blockchain for Internet of Things Financing Mode
Authors: Li Jing , Feng Hao , Li Mao , Li ManJie , Chen Yuyuan
Published: June 2022

Financing structure is an important and very complex issue in the financial theory and the rights and obligations of relevant stakeholders of enterprises are also concentrated in the financing structure. Therefore, the financing structure has a significant impact on the value of enterprises. A reasonable financing structure is conducive to standardizing the behavior of enterprises and improving the value of enterprises. The change of corporate financing structure is often used as a signal to external investors about the company’s future income expectations, especially because the financing structure has a certain impact on the company’s performance, which makes the problem of financing structure more valued by the theoretical and financial circles. For the empirical information about company financing, this paper explores the influencing elements of the company’s running overall performance assisted with the aid of the blockchain, and the net of matters provides a chain model and constructs the operating performance indicators according to the comprehensive score. We select the commercial credit financing rate, short-term loan financing rate, long-term loan financing rate, debt financing rate, equity financing rate, and endogenous financing rate. The control variables are total capital, ownership concentration, and average age of the company. The conclusion is drawn by regression analysis. Commercial savings financing rate, fairness financing fee, and endogenous financing fee are positively correlated with the working performance; short-term loans and average age of the company are negatively correlated with the operating performance; and long-term loan financing rate, bond financing rate, and equity concentration are not significantly correlated with the operating performance.
Computational Intelligence-Based Melanoma Detection and Classification Using Dermoscopic Images
Authors: Vaiyapuri Thavavel , Balaji Prasanalakshmi , S Shridevi. , Alaskar Haya , Sbai Zohra
Published: June 2022

Melanoma is a kind of skin cancer caused by the irregular development of pigment-producing cells. Since melanoma detection efficiency is limited to different factors such as poor contrast among lesions and nearby skin regions, and visual resemblance among melanoma and non-melanoma lesions, intelligent computer-aided diagnosis (CAD) models are essential. Recently, computational intelligence (CI) and deep learning (DL) techniques are utilized for effective decision-making in the biomedical field. In addition, the fast-growing advancements in computer-aided surgeries and recent progress in molecular, cellular, and tissue engineering research have made CI an inevitable part of biomedical applications. In this view, the research work here develops a novel computational intelligence-based melanoma detection and classification technique using dermoscopic images (CIMDC-DIs). The proposed CIMDC-DI model encompasses different subprocesses. Primarily, bilateral filtering with fuzzy k-means (FKM) clustering-based image segmentation is applied as a preprocessing step. Besides, NasNet-based feature extractor with stochastic gradient descent is applied for feature extraction. Finally, the manta ray foraging optimization (MRFO) algorithm with a cascaded neural network (CNN) is exploited for the classification process. To ensure the potential efficiency of the CIMDC-DI technique, we conducted a wide-ranging simulation analysis, and the results reported its effectiveness over the existing recent algorithms with the maximum accuracy of 97.50%.
Application of Image Recognition Based on Wireless Sensors in Dance Teaching System
Authors: Ben Chi
Published: June 2022

With the vigorous development of higher education in China, many universities have made great progress in various indicators in recent years. As the number of college students increases year by year, the effect of instruction in the classroom is especially important. The high quality of teaching directly affects the efficiency of students’ listening to lectures, and more and more universities are receiving attention. However, the traditional dance classroom education and the one-to-many education model cannot adapt to the development trend of higher art education under the changes of the times and cannot effectively guarantee the quality of classroom education. The development of wireless sensor networks provides practical and feasible technical solutions for the development of dance education systems. Compared with general detection methods, image sensors can provide more real-time and more intuitive on-site information and wirelessly send image information to user terminals. This article describes the classic feature extraction algorithm and proposes a new feature extraction algorithm based on chart filling. The effectiveness of each algorithm is verified through several data sets. Image recognition is carried out by computer, including from computer to image processing, through the computer to recognize objects and various different modes of the target technology. The identification process usually includes several steps. First, the preprocessing of the image is required, then the segmentation of the image is performed, and then the feature extraction and matching are performed. In layman’s terms, image recognition hopes to imitate the human heart to read photos. By applying the image recognition technology to the dance education system, changes in the methods and forms of dance education can be stimulated.
Efficacy Evaluation of 64‐Slice Spiral Computed Tomography Images in Laparoscopic‐Assisted Distal Gastrectomy for Gastric Cancer under the Reconstruction Algorithm
Authors: Yu Weiguang , Li Xing , Zhou Hongbo , Zhang Yang , Sun Zhiguo
Published: June 2022

This study was aimed to analyze the application value of the filtered back‐projection (FBP) reconstruction algorithm of computed tomography (CT) images in laparoscopic‐assisted distal gastrectomy. In this study, 56 patients with gastric cancer were selected as research subjects and randomly divided into the control group (CT‐guided laparoscopic radical gastrectomy) and the observation group (CT‐guided laparoscopic radical gastrectomy with the FBP reconstruction algorithm), with 28 patients in each group. Fourier transform and iterative reconstruction were introduced for comparison, and finally, the postoperative curative effect and adverse events were compared between the two groups. The results showed that the CT image quality score processed by the FBP reconstruction algorithm (4.31 ± 0.31) was significantly higher than that of the iterative reconstruction method (3.5 ± 0.29) and the Fourier transform method (3.97 ± 0.38) (P < 0.05). The incidences of postoperative wound infection and gastric motility disorder (5.88% and 8.16%, respectively) in the observation group were significantly lower than those in the control group (8.21% and 10.82%, respectively) (P < 0.05). The levels of serum interleukin‐6 (IL‐6) (280.35 ± 15.08 ng/L) and tumor necrosis factor‐α (TNF‐α) (144.32 ± 10.32 ng/L) in the observation group after the treatment were significantly lower than those in the control group, which were 399.71 ± 14.19 ng/L and 165.33 ± 10.08 ng/L, respectively (P < 0.05). In conclusion, the FBP reconstruction algorithm was better than other algorithms in the processing of gastric cancer CT images. The FBP reconstruction algorithm showed a good reconstruction effect on CT images of gastric cancer; CT images based on this algorithm helped to formulate targeted surgical treatment plans for gastric cancer, showing a high clinical application value.
Optimization of Surface Quality and Power Consumption in Machining Hardened AISI 4340 Steel
Authors: Ochengo Dennis , Liang Li , Wei Zhao , Ning He
Published: June 2022

Hard turning has become an attractive method of machining for most manufacturers in the last few years due to its low cost and superior surface quality compared to grinding. In this experimental study, the machinability of hardened steel under dry machining on a CNC lathe is undertaken to optimize the cutting parameters for minimum surface roughness and energy consumption with the cutting speed (320, 450, and 575), tool type (coated and uncoated), and feed rate (0.1, 0.18, and 0.26) as the input parameters. The Taguchi method, based on the L18 orthogonal array, the variance analysis, the signal-to-noise ratios, and the response surface methodology have been used to optimize surface roughness (Ra) and cutting power (Cp). Optimum cutting parameters and levels were determined, and the relationship between cutting parameters and output variables was analyzed with the aid of two-dimensional and three-dimensional graphics. The results show that the most effective parameter on the surface roughness was the tool type (78%), while the most effective parameter on energy consumption was the cutting speed (90%). The combination of low feed rate and high cutting speed is necessary for minimizing the surface roughness. Besides, the impact of two-factor interactions of the feed rate-cutting speed and depth of cut-cutting speed appears to be substantial. The linear regression models were validated using confirmation tests. Finally, regression coefficients were determined as a mathematical model, and it was observed that this estimated model yielded results that were very similar to those achieved via real experiment (correlation values: 97.64% for surface roughness and 98.72% for energy consumption).
An Application of English Reading Mobile Teaching Model Based on K-Means Algorithm
Authors: Peng Changhong
Published: June 2022

The rapid development and maturity of emerging technologies such as mobile Internet and artificial intelligence have had a subversive impact on all aspects of teaching, and mobile learning has become the normal learning of students. Educational technology has developed from traditional technology and ordinary media technology to multimedia information network technology. Personal computers and wired networks have been more and more widely used. Wireless communication technology and mobile Internet technology of mobile computing devices will be popularized, and the trend from digital learning to mobility will be more and more obvious. This study uses the k-means algorithm to analyze the English reading performance, finds out the factors affecting the test performance, provides guidance for improving the pass rate of CET-4, and focuses on the rise of mobile learning under this background and its specific application in English teaching. The experimental results show that 39 students (55%) believe that mobile reading learning provides rich and real reading materials, can obtain real and authentic language input, and increase their interest in English reading. 31 students (44%) believed that the learning model was helpful to enhance autonomous learning ability. Therefore, one of the biggest advantages of this clustering algorithm is that it has high scalability and efficiency in the processing of large data sets. The mobile teaching model of English reading based on the k-means algorithm can more effectively promote the interaction of English reading teaching and improve students’ English text reading comprehension ability than the traditional teaching model. In addition, it can promote students’ active learning and cultivate students’ awareness of autonomous learning and cooperation.
Investigation of the Aerodynamic Characteristics of Platoon Vehicles Based on Ahmed Body
Authors: Luo Jianbin , Mi Ke , Tan Dongli , Zhang Zhiqing , Li Mingsen , Qing Jun , Huang Huiqiong
Published: June 2022

In this paper, the aerodynamic characteristics of two vehicles and three vehicles in the platoon under different vehicle spacings have been explored in detail. Firstly, the realizable k-

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model was used to verify the numerical method based on a single 35° Ahmed body. Then, the aerodynamic characteristics such as drag characteristics, surface pressure, wake structure, and turbulent kinetic energy distribution were analyzed for the platoon of two and three 35° Ahmed bodies. Although the RANS (Reynolds-averaged Navier–Stokes) model had got good results for simulating a single 35° Ahmed body, when simulating two 35° Ahmed bodies in the platoon, it was found that there is still a big error compared with the experimental data. In the three 35° Ahmed body, the drag coefficient of the leading body is almost unchanged compared with that of the leading body in the two-vehicle platoon, while the drag coefficients of the middle body and the trailing body are both reduced compared with those of the single body. For x/L = 0.25, the middle body is about 56% of the single-body value, and the trailing car is about 88% of the single-body value. It can be seen that the drag reduction effect of three 35° Ahmed bodies is larger than that of two 35° Ahmed bodies. It is shown that the aerodynamic characteristics are very sensitive to the selected platoon vehicle model. Because model with different geometric shapes will produce different wake structures, different aerodynamic phenomena will occur when they are arranged in the platoon.