bluuebunny/crossref_metadata_2025 huggingface dataset:
Imperative or Functional Control Flow Handling
Authors: Gévay Gábor E. , Rabl Tilmann , Breß Sebastian , Madai-Tahy Loránd , Quiané-Ruiz Jorge-Arnulfo , Markl Volker
Published: June 2022

Modern data analysis tasks often involve control flow statements, such as the iterations in PageRank and K-means. To achieve scalability, developers usually implement these tasks in distributed dataflow systems, such as Spark and Flink. Designers of such systems have to choose between providing imperative or functional control flow constructs to users. Imperative constructs are easier to use, but functional constructs are easier to compile to an efficient dataflow job. We propose Mitos, a system where control flow is both easy to use and efficient. Mitos relies on an intermediate representation based on the static single assignment form. This allows us to abstract away from specific control flow constructs and treat any imperative control flow uniformly both when building the dataflow job and when coordinating the distributed execution.
Structure and Complexity of Bag Consistency
Authors: Atserias Albert , Kolaitis Phokion G.
Published: June 2022

Since the early days of relational databases, it was realized that acyclic hypergraphs give rise to database schemas with desirable structural and algorithmic properties. In a bynow classical paper, Beeri, Fagin, Maier, and Yannakakis established several different equivalent characterizations of acyclicity; in particular, they showed that the sets of attributes of a schema form an acyclic hypergraph if and only if the local-to-global consistency property for relations over that schema holds, which means that every collection of pairwise consistent relations over the schema is globally consistent. Even though real-life databases consist of bags (multisets), there has not been a study of the interplay between local consistency and global consistency for bags. We embark on such a study here and we first show that the sets of attributes of a schema form an acyclic hypergraph if and only if the local-to-global consistency property for bags over that schema holds. After this, we explore algorithmic aspects of global consistency for bags by analyzing the computational complexity of the global consistency problem for bags: given a collection of bags, are these bags globally consistent? We show that this problem is in NP, even when the schema is part of the input. We then establish the following dichotomy theorem for fixed schemas: if the schema is acyclic, then the global consistency problem for bags is solvable in polynomial time, while if the schema is cyclic, then the global consistency problem for bags is NP-complete. The latter result contrasts sharply with the state of affairs for relations, where, for each fixed schema, the global consistency problem for relations is solvable in polynomial time.
Corrigendum: Effects of Foreign Elements Added Oxide-Based Electrocatalyst for Oxygen Reduction Reaction as Non-Precious Metel Cathodes [ECS Trans. 108 (7) 181-188 (2022)]
Authors: Matsuzawa K , Obata M , Takeuchi Y , Ohgi Y , Ikegami K , Nagai T , Monden R , Ishihara A
Published: June 2022

The authors would like to inform the readers that there are several errors in the Abstract, Results and discussion, and Conclusion in our published paper. Here, we have therefore provided the correct version of the Abstract, Results and discussion, and Conclusion in this corrigendum.
Intra- and inter-regional dynamics in cortical-striatal-tegmental networks
Authors: Dede Adam J. O. , Mishra Ashutosh , Marzban Nader , Reichert Robert , Anderson Paul M. , Cohen Michael X.
Published: June 2022

We applied novel clustering techniques to discover functional subregional anatomical patches that changed with behavioral conditions but were frequency specific and stable across days. By taking into account these changes in intraregional signal generator location and extent, we were able to reveal a richer picture of inter-regional functional connectivity than would otherwise have been possible. These findings reveal that the brain’s functional organization changes with state at multiple levels of scale.
New Variant of SARS‐CoV‐2 Dynamics with Imperfect Vaccine
Authors: Faniran Taye Samuel , Ali Aatif , Al-Hazmi Nawal E. , Asamoah Joshua Kiddy K. , Nofal Taher A. , Adewole Matthew O.
Published: June 2022

The occurrence of a new strain of SARS‐CoV‐2 cannot be ruled out. Therefore, this study seeks to investigate the possible effects of a hypothetical imperfect anti‐COVID‐19 vaccine on the control of not only the first variant of SARS‐CoV‐2 but also the second (new) variant of SARS‐CoV‐2. We further examine the rates r and a, escape of quarantined infectious individuals from isolation centers. The control Rc and basic reproduction numbers R0 are computed which gives assess to obtain asymptotic stability of disease‐free equilibrium point globally and the existence of a unique persistent equilibrium solution. Numerical results reveal that people infected with the second strain who are vaccinated with an imperfect vaccine are under control but the prevalence of the second variant enhances the prevalence of the first variant. Thus, discovering a vaccine that is effective (to a good extent) for the prevention of variant 2 (new variant) is necessary for the control of COVID‐19. Numerical results also reveal that increase in the rate at which individuals infected with the first variant escape the isolation center gives rise to the population infected with the first variant and lowers the peak of the population infected with the second variant. This is probably because individuals infected with the second variant appear to be more careful with their lives and get vaccinated more than individuals infected with the first variant.
Effect of Secreted Frizzled-Related Protein 5 in Mice with Heart Failure
Authors: Hong Pan , Wang Lijie , Wang Hongchao , Shi Min , Guo Bingyan
Published: June 2022

Although some progress has been made in its treatment, heart failure is still one of the most important health problems that endanger public health. This study aims to explore the myocardial protective effect of secreted frizzled-related protein 5 (SFRP5) on mice with heart failure. The mouse model of heart failure was established by using the isoproterenol (ISO) hydrochloride gradient modeling method. The treatment group was injected with 0.02 mg/kg/24 h SFRP5 recombinant protein intraperitoneally 30 minutes after the injection of isoproterenol, and the ISO + phosphate-buffered saline (PBS) group was injected with the same amount of PBS. After intraperitoneal injection of SFRP5 recombinant protein in mice with heart failure, the inflammatory response was reduced, and the left ventricular systolic and diastolic function of heart failure mice and the pathological structure of the myocardial tissue were improved. Compared with the ISO group, the expression level of SFRP5 protein in the ISO + SFRP5 group was increased significantly, the expression levels of Wnt5a and JNK protein were decreased markedly, and the enzyme activities of SOD and GSH-Px in the serum were observably increased, but they were lower than those parameters in the normal group. The SFRP5 recombinant protein has a protective effect on isoproterenol-induced heart failure in mice. The mechanism of action may be related to inhibiting the Wnt5A/JNK signaling pathway and reducing oxidative stress and inflammation. SFRP5 may be one of the therapeutic targets of heart failure.
Computer Simulation Algorithm of Team Gymnastics Formation Change Path under Artificial Intelligence and Network Big Data
Authors: Zhu Anfeng , Cheng Liangliang
Published: June 2022

With the development of economy, all world countries are entering the ranks of competitive sports. The Olympic Games or large-scale gymnastics performances are of great significance to the publicity and implementation of the national health plan. This paper aims to study the computer simulation algorithm of group gymnastics formation change path under artificial intelligence and network big data, so as to find out the path change algorithm of each team member, so that members in group gymnastics can clearly see their own moving route, and finally achieve the purpose of reducing the difficulty and cost of rehearsal. In this paper, the ellipse search algorithm and the traditionalDijkstraalgorithm, the rectangle search algorithm, and the traditionalDijkstraalgorithm are deeply compared and analyzed, and then, the experimental comparison between the ellipse search algorithm and the rectangle search algorithm is carried out. It is concluded that when finding the shortest path and when the straight-line distance between two nodes is 4.0 km, the time used by the rectangle search algorithm is 2.1 s, while the ellipse search algorithm needs 3.98 s. This shows that the rectangle search algorithm greatly saves the operation time and has superior performance.
Final Colour of Ultratranslucent Multilayered Zirconia Veneers, Effect of Thickness, and Resin Cement Shade
Authors: Khosravani Seyed Reza , Kahnamoui Mehdi Abed , Kimyai Soodabeh , Navimipour Elmira Jafari , Mahounak Farzaneh Sadeghi , Azar Fatemeh Pournaghi
Published: June 2022

Background. Aesthetic restorations should be able to mimic the natural colour depth of teeth, affected by several factors including material properties. There is a lack of information regarding the effect of cement shade and material thickness on the final colour of ultratranslucent multilayered zirconia veneers. Objectives. This study evaluated the effect of ceramic thickness and resin cement shade on the final colour of different layers of ultratranslucent multilayered (UTML) zirconia veneers. Methods. This in vitro study produced 90 rectangular‐shaped specimens with nonsintered Katana UTML monolithic zirconia (Kuraray Noritake Dental, Tokyo, Japan), shade A1 blocks. Ceramic samples were prepared in two groups of 0.7 mm and 0.5 mm thicknesses, 45 of each (a: 8 × 11 × 0.5 mm; b: 8 × 11 × 0.7 mm). Specimens of each thickness were further divided into 5 groups: universal, clear, brown, white, and opaque (n = 9). Each adhesive resin cement (Panavia V5) was applied between the ceramic samples and composite substrate. The colour values were measured using a spectrophotometer in baseline and after resin cement application according to the CIELab system. For all samples, ΔE00 values were obtained. Data were evaluated with SPSS 25 using the three‐way ANOVA test (p < 0.05). Results. The factors of cement shade, ceramic thickness, and ceramic layers have statistically significant effect on ΔE00 values (p < 0.001). The results showed lower ΔE00 values with thicker ceramic veneers. Tukey test results showed that the opaque and brown shade had a significantly greater ΔE00 values comparing to universal (p = 0.004), clear, and white shades (p < 0.001). Conclusion. The colour change was greater in lower ceramic thickness. Different shades of resin cement and layers of UTML zirconia differently affected the final colour.
Stacking Ensemble Learning Process to Predict Rural Road Traffic Flow
Authors: Rasaizadi Arash , Seyedabrishami Seyedehsan
Published: June 2022

By predicting and informing the future of traffic through intelligent transportation systems, there is more readiness to avoid traffic congestion. In this study, an ensemble learning process is proposed to predict the hourly traffic flow. First, three base models, including K-nearest neighbors, random forest, and recurrent neural network, are trained. Predictions of base models are given to the XGBoost stacking model and bagged average to determine the final prediction. Two groups of models predict traffic flow of short-term and mid-term future. In mid-term models, predictor features are cyclical temporal features, holidays, and weather conditions. In short-term models, in addition to the mentioned features, the observed traffic flow in the past 3 to 8 hours has been used. The results show that for both short-term and mid-term models, the least prediction error is obtained by the XGBoost model. In mid-term models, the root mean square error of the XGBoost for the Saveh to Tehran direction and Tehran to Saveh direction is 521 and 607 (veh/hr), respectively. For short-term models, these values are decreased to 453 and 386 (veh/hr). This model also brings less prediction error for predicting the first and fourth quartiles of the observed traffic flow as rare events.
Construction of English Translation Model Based on Improved Fuzzy Semantic Optimal Control of GLR Algorithm
Authors: Li Xi
Published: June 2022

Data point overlap exists in the model translation recognition results of generalized maximum likelihood ratio detection (GLR) algorithm. A fuzzy semantic optimal control intelligent recognition model for English translation based on improved GLR algorithm is proposed. This algorithm is used to create a phrase corpus for marking tens of thousands of English and Chinese words, so that phrases can be searched automatically. The algorithm builds a phrase corpus of about 710,000 Chinese and English words. Phrase structure is constructed through phrase centers. Partial speech recognition results can be obtained. According to the syntactic function of analytic linear list, the ambiguity of Chinese and English structures in part of speech recognition results is corrected. Finally get the content of the identifier on the basis of comprehensive evaluation. The recognition accuracy based on the improved algorithm is more than 95%. The overall score was 92.3. This algorithm overcomes the disadvantages of GLR. Compared with statistical algorithm and dynamic memory algorithm, the algorithm improves the operation speed and processing performance and is more suitable for machine translation tasks. It provides a new idea in the field of machine translation.
Digital Teaching Management System Based on Deep Learning of Internet of Things
Authors: Feng Peilu , Wu Qi
Published: June 2022

In order to solve a series of problems similar to the repetitive construction of resources and low degree of resource sharing in cruciform teaching, this paper studies the digital disarming management. Based on the in-depth analysis of the actual needs of the digital teaching resource service system and the key problems in the system, taking the resources and business process as the starting point, based on Java Web related technology, combined with the related processes of resources and business processing, this paper designs the digital teaching resource system of colleges and universities. The system has the functions of resource digitization, process management, and interaction with other platforms. The system database platform and operation platform are built; the development environment is configured; and the user login service function, data conversion service function, process management service function, and system management service function are completed. The function is tested by unit test, and the performance is tested and analyzed according to user requirements and design objectives. The system adopts Java web development technology, uses S2SH framework as the development basis, and takes Oracle database as the data storage platform through Tomcat6.0 web server for program publishing. Through system testing and analysis, the software can operate normally and achieve the expected functions and can be put into use.
The Effect of Artificial Liver Support System on Prognosis of HBV-Derived Hepatorenal Syndrome: A Retrospective Cohort Study
Authors: Sheng Xinyu , Zhou Jiaqi , Gu Xiuyu , Wang Hong
Published: June 2022

Hepatorenal syndrome (HRS) could occur when patients get decompensated liver cirrhosis. Meanwhile, hepatitis B virus (HBV) infection raises the risk of mortality of the end-stage liver diseases. As the artificial liver support system (ALSS) has been applied in liver failure, whether ALSS could benefit HBV-derived HRS remains uncertain. We retrospectively enlisted eligible HRS patients and compared the baseline characteristics and prognosis between HBV-derived HRS and non-HBV-derived HRS. Furthermore, propensity score matching (PSM) and Cox regression analyses were used to assess the beneficial effect of ALSS on HBV-derived HRS. In addition, a stratified analysis was carried out according to the degree of acute kidney injury (AKI) and the number of organ failures to observe in which populations ALSS can obtain the most excellent therapeutic effect. 669 patients were diagnosed as HRS, including 298 HBV negative and 371 HBV positive. Baseline characteristics were different between patients with HBV positive and HBV negative. HBV-derived HRS has higher 28-day mortality, though without a statistical difference. After PSM, 50 patients treated with ALSS and 150 patients treated with standard medical treatment (SMT) constituted a new cohort for the following analysis. We found that ALSS could significantly benefit HRS patients (

P
=
0.025

). Moreover, the median survival time of patients treated with ALSS was longer than those treated with SMT. INR, neutrophil percentage, and treatment with ALSS were independent predictive factors for short-term mortality in HBV-derived HRS. The stratified analysis showed that ALSS could reduce the 28-day mortality of patients with HBV-derived HRS, especially those in AKI stage 3 and with organ

failure
≥
2

. Additionally, serum bilirubin was significantly lower after ALSS, and the alteration of INR and creatinine were independent predictive elements for the mortality of HBV-derived HRS. HBV-derived HRS is more severe than non-HBV-derived HRS and has a worse prognosis. ALSS could reduce the short-term mortality of patients with HBV-derived HRS, especially those in AKI stage 3 and with organ

failure
≥
2

. INR and the change of creatinine and INR could predict the prognosis of HBV-derived HRS. ChiCTR2200060123.
Multiagent Culture Algorithm-Based Interactive Design of College English Online Teaching Process
Authors: Peng Nianfan
Published: June 2022

Traditional educational techniques and conceptions no longer match the need of the society for talent training. It is due to the fact that educational reforms are deepening and more open interactive teaching models have begun to be gradually implemented in college English instruction. The method’s innovation and reform can not only fully respect the students’ dominating position but also entice students to devote themselves to the English classroom with greater zeal which is helpful in allowing for deeper knowledge discovery and thinking. This study has the motive to examine the interactive teaching mode’s application tactics in college English classrooms, particularly with the goal of improving the effectiveness of English classroom teaching and promoting the high-quality growth of today’s college students. Furthermore, in order to improve the interactivity of online English teaching in colleges and universities, this research proposes an intelligent conversation system based on multiagents to aid in the improvement of online teaching. Finally, using a public discourse corpus dataset for implementation, the proposed model proves to have better performance than existing state of the art approaches.
Initial Value Problems with Generalized Fractional Derivatives and Their Solutions via Generalized Laplace Decomposition Method
Authors: Elbadri Mohamed
Published: June 2022

In this article, we use thep-Laplace decomposition method to find the solution to the initial value problems that involve generalized fractional derivatives. Thep-Laplace decomposition method is used to get approximate series solutions. The Adomian decomposition is improved with the assistance of thep-Laplace transform to examine the solutions of the given examples to demonstrate the precision of the current technique.
An Integrated Eco-Epidemiological Plant Pest Natural Enemy Differential Equation Model with Various Impulsive Strategies
Authors: Jose Sayooj Aby , Raja R. , Zhu Quanxin , Alzabut J. , Niezabitowski M. , Balas Valentina E.
Published: June 2022

We established a mathematical model based on the sense of biological survey in the field of agriculture and introduced various control methods on how to prevent the crops from destructive pests. Basically, there are two main stages in the life cycle of natural enemies like insects: mature and immature. Here, we construct a food chain model of plant pest natural enemy. In natural enemies, there are two stages of construction. Also, we consider three classes of diseases in the pest population, namely, susceptible, exposed, and infectious in this proposed work. In order to categorize the considered models into the class of Impulsive Differential Equations (IDEs), in our study, we specifically consider two ecosystems, which define the impact of control mechanisms on the impulsive releasing of virus particle natural enemies and infectious pests at particular time. Additionally, the importance of spraying virus particles in pest control is discussed; then, we obtain two types of periodic solutions for the system, namely, plant pest extinction and pest extinction. By utilizing the small amplitude perturbation techniques and Floquet theory of the impulsive equation, we obtain the local stability of both periodic solutions. Moreover, the comparison technique of IDE shows the sufficient conditions for the global attractivity of a pest extinction periodic solution. With the assistance of the comparison results, we draw a numerical calculation for the addressed models. Finally, we extend the study of the two models for pest management models: with and without the existence of virus particle.
Commercial Bank Credit Grading Model Using Genetic Optimization Neural Network and Cluster Analysis
Authors: Bai Yunpu , Zha Dunlin
Published: June 2022

Commercial banks are facing unprecedented credit risk challenges as the financial market becomes more volatile. Based on this, this study proposes and builds a credit risk assessment model for commercial banks based on GANN from the standpoint of commercial banks. In order to provide commercial banks with an effective and dependable credit risk assessment method, the indicators in this study are classified using cluster analysis, and then various representative indicators are chosen using a factor model, which takes into account the comprehensiveness of the information and reduces the complexity of the subsequent empirical analysis. On this basis, the network structure, learning parameters, and learning algorithm of commercial banks’ credit risk assessment models are determined. Furthermore, advancements in data preprocessing and genetic operation have been made. According to simulation results, the highest accuracy rate of this method is 94.17 percent, which is higher than the BPNN algorithm 89.46 percent and the immune algorithm 90.14 percent. The optimization algorithm presented in this study improves the convergence speed and search efficiency of traditional algorithms, and the final experimental results show that the scheme is feasible and effective and can be used for commercial bank credit risk assessment.
Gear Tooth Root Bending Strength Estimation under the Assumption of Fatigue Limit Existence
Authors: Bonaiti Luca , Gorla Carlo
Published: June 2022

Being able to properly predict gear failure is a key aspect to achieve a reliable light-weight gearbox. Among the several gear failures, tooth root bending fatigue is considered as the most dangerous one because it implies the stoppage of the whole gearbox. In order to characterize a gear for this phenomena, Single Tooth Bending Fatigue (STBF) tests are the most performed ones. However, as in STBF test THERE IS no sliding/rolling contact and as the specimens are teeth rather than gears, some differences occur between the test conditions and those of the real case. This paper deals with the statistical ones that is the estimation of the gear SN curve starting from the teeth one. The teeth SN curve has been estimated by means of a statistical model developed considering Murakami’s idea of nonpropagating crack. Then, a methodology based on statistic of extreme is adopted for the purpose of estimating the gear SN curve.
Identification of Novel circRNA-Based ceRNA Network Involved in the Pathogenesis of Gastric Cancer
Authors: Peng Dengfa , Feng Li , Li Huqing
Published: June 2022

Objective. Evidence increasingly shows that circular RNAs (circRNAs) are closely associated with tumorigenesis and cancer progression. However, the roles of circRNAs and the underlying mechanism behind these circRNAs in gastric cancer (GC) remain to be elucidated. This study is aimed at conferring a better understanding of GC pathogenesis with a specific focus on circRNA-based ceRNA action. Methods. circRNA expression profiles were downloaded from two Gene Expression Omnibus (GEO) microarray datasets, GSE152309 and GSE121445. Expression profiles of miRNAs and mRNAs were collected from The Cancer Genome Atlas (TCGA) database. The ceRNA network was constructed based on circRNA-miRNA pairs and miRNA-mRNA pairs. Functional and pathway enrichment analyses were performed to evaluate functional pathways of differentially expressed mRNAs (DEmRNAs). The PPI network was constructed by mapping DEmRNAs into the STRING database to identify hub genes, and then the DEcircRNA-DEmiRNA-hub gene subnetwork was constructed. The expression levels of candidate differentially expressed circRNAs (DEcircRNAs) in cancerous and matched noncancerous gastric tissues surgically resected from 52 GC patients were determined by the RT-qPCR analysis. Results. Differential expression analysis with Venn diagram analysis showed 11 overlapped DEcircRNAs (7 upregulated circRNAs and 4 downregulated ones) between cancerous tissues and noncancerous gastric tissues. The DEcircRNA-DEmiRNA-DEmRNA network was constructed, consisting of 2 DEcircRNAs, 7 DEmiRNAs, and 104 DEmRNAs. GO and KEGG pathway analyses revealed that 104 DEmRNAs might be associated with GC development and progression. The PPI network was constructed, yielding 16 hub genes, TFDP1, KRAS, LMNB1, MET, MYBL2, CDC25A, E2F5, HMGA1, HMGA2, CBFB, CBX3, CDC7, IGF2BP3, KIF11, PDGFB, and SMC1A, which were all upregulated in GC tissues compared with adjacent tumor-free gastric tissues. Based on the above hub genes in GC, the DEcircRNA-DEmiRNA-hub gene subnetwork was reconstructed based on hsa_circ_0000384 and hsa_circ_0000043, including 22 pairs of the upcircRNA-downmiRNA-upmRNA network. The expression levels of hsa_circ_0000384 and hsa_circ_0000043 were remarkably higher in GC tissues than those in matched adjacent tumor-free gastric tissues (

p
<
0.001

), concurring with the bioinformatics results. Conclusion. Our study offers a better understanding of circRNA-related ceRNA regulatory mechanism in the pathogenesis of GC, highlighting two ceRNA networks based on hsa_circ_0000384 and hsa_circ_0000043.
Temperature Control Algorithm of Underground Air Conditioning in Station
Authors: Zheng Lei , Zhao Yucai , Hu Xinchao , Li Wenlong , Zhou Wei , Fang Yuyue
Published: June 2022

Aiming at the air-conditioning temperature control of underground station, the air-conditioning temperature controller of underground station is designed based on proportional-integral-differential neural network, the bat algorithm is used to select the initial weights, the radial basis function neural network prediction model is used to optimize the design of the predictor, and the designed control system is simulated on the MATLAB simulation platform. The simulation results show that the dynamic characteristics and steady-state characteristics of the PID controller optimized by bat algorithm are better than those of the PID controller tuned by conventional methods. After optimization by radial basis function neural network prediction model, the rapidity and stability of controller are effectively improved.
Digital-Media-Based Interaction and Dissemination of Traditional Culture Integrating Using Social Media Data Analytics
Authors: Hong Na
Published: June 2022

This paper adopts the approach of the Internet fusion digital media to conduct in-depth research and analysis on the interaction and communication of traditional culture. This structural information can be used to express and describe the Internet requirements. With the increasing demand for the Internet applications, the number of objects in the network and the complexity of the structure are also growing, so we can design suitable clustering algorithms to obtain more reasonable network structure information by using different semantic information in the heterogeneous information network. Firstly, the caching scheme is transformed into a backpack problem, and the storage scheme is obtained recursively by using dynamic programming, after which the computational task is optimized based on this storage scheme by using the whale algorithm to make it the least costly. The exact balance between the connotation essence of traditional culture and the emotional resonance in modern life has not yet been found, and the visual language belonging to cultural aesthetics under the combination of traditional and modern aesthetics needs to be explored for a long time. From an objective point of view, the digital art communication of cultural elements still suffers from five problems: lack of communication cultivation and stratification of target audiences, low quality of transcription of digital artworks, unbalanced economic and cultural values, uneven development of digital art communication forms, and low degree of Internet adaptation. A ranking algorithm based on fusing multiple meta-paths is proposed to better reflect the ranking values of different object distributions of the Internet data in heterogeneous information networks, which can obtain better clustering, while better clustering can be calculated to obtain more reasonable rankings, and finally, the types of the Internet-oriented applications are divided into multiple reasonable clusters. The effects of selecting different meta-paths on the clustering algorithm and the effects of fused meta-paths versus single meta-paths on the clustering results are given in the experimental results section. Also compared with other clustering algorithms, the I-RankClus algorithm can better achieve the data clustering classification for the Internet application scenarios.
Trajectory Control Algorithm of Flexible Joint Manipulator Based on Random Matrix and Screw Theory
Authors: Guo Hao , Zhou Dashuai , He Yao
Published: June 2022

Flexible articulated manipulators are often used for the task of tracking reference trajectories in space and have attracted much attention. Aiming at the uncertainty of the robot system, based on random matrix and screw theory, this paper constructs a trajectory control model of a flexible joint manipulator. In order to reduce the steady-state tracking error, a random matrix variable structure control method is introduced into the model, and a nonlinear spinor-like random matrix function is designed to improve the traditional random matrix surface. In the simulation process, the dynamic model of the series robot is firstly obtained according to the screw and random matrix equation, and the dynamic characteristics are analyzed. Combined with dynamic surface control technology, a neural network controller is designed to solve the problem of dimensional explosion and ensure that the tracking error converges to a small neighborhood of zero. The experimental results show that by using the observation value to replace the unmeasurable state of the system, combining it with the random matrix network to identify the unknown dynamics of the system, and designing the random matrix network controller, the tracking control of the system can be realized, and the tracking error can be ensured to converge to a small neighborhood of zero. The control system has a better control effect than traditional PID, the peak time is shortened by 45.83%, the adjustment time is shortened by 46.91%, the maximum overshoot is reduced by 51.35%, and the steady-state error after filtering is only 0.049, which is reduced by 47.31%. Effective interference signal and measurement noise are suppressed, and the quantitative observation performance of the flexible joint manipulator system is improved.
Impact of Typhoons of Different Intensities on Short-Term Precipitation in the Middle and Lower Reaches of the Yangtze River in Summer
Authors: Zhang Zhongwu
Published: June 2022

According to China’s reanalyzed meteorological dataset (CN05.1), a 6-h track intensity typhoon meteorological dataset in the Western Pacific, three types of short-term precipitation are described to study the impact of typhoons on summer rainfall of different intensities in the middle and lower reaches of the Yangtze River: short-term extreme precipitation (95% quantile), short-term heavy precipitation (75% quantile), and normal precipitation (below the lower limit of the 75% quantile threshold). The results show that the amount of short-term extreme precipitation is 1.8 and 3.7 times that of normal precipitation and short-term heavy precipitation, respectively. Considerable interannual and interdecadal fluctuations in the proportion of short-term heavy precipitation and extreme precipitation during summer are affected by typhoons, with a wide range of changes occurring between 1980 and 2000. The areas with high amounts of short-term heavy precipitation and extreme precipitation are distributed mostly in the middle and southern parts of the middle and lower reaches of the Yangtze River, whereas areas with a high amount of normal precipitation are distributed mostly in the southeastern parts of the river. The spatial distribution of the three intensities of rainfall affected by typhoons is consistent, with a gradual decrease from southeast to northwest; in addition, the spatial distribution of the proportion of total summer rainfall has similar characteristics. The three intensities of precipitation are affected by the spatial distribution of the typhoon path frequency, and the distribution of the high-value areas is essentially the same as that of precipitation. This indicates that most of the typhoons that affect summer precipitation pass through the middle and lower reaches of the Yangtze River.
Prevalence of Periodontitis among Patients Diagnosed with Marfan Syndrome: A Cross‐Sectional Study Comparing Samples of Healthy Patients
Authors: Galletti Cosimo , Toledano-Serrabona Jorge , Camps-Font Octavi , Teixido-Tura Gisela , Llobet-Poal Inmaculada , Subirà-Pifarré Carles , Fiorillo Luca , Gay-Escoda Cosme
Published: June 2022

Periodontitis is an inflammatory condition caused by a bacterial plaque and characterized by progressive destruction of the tooth‐supporting apparatus. Patients with Marfan syndrome (MFS) exhibit a connective tissue disorder, which can also affect oral soft and hard tissue. Thus, the aims of this cross‐sectional study were to assess the association between periodontitis and MFS and secondly, to compare periodontal parameters and prevalence of disease with a control group (CG) without MFS. 152 patients (MFS = 76, CG = 76) were recruited to evaluate the following periodontal parameters: probing depth, gingival margin, clinical attachment level, plaque index, and bleeding on probing. The 2017 World Workshop guideline was followed for the diagnosis of the periodontal status. A multivariate analysis was performed using a multinomial logistic regression adjusted for age, gender, and smoking. The level of significance required was p < 0.05. Patients with MFS did not show a higher prevalence of periodontitis compared to the CG. However, patients with MFS did have higher values in probing depth, gingival recession, clinical attachment level, and plaque index compared to the CG patients (p < 0.05). In conclusion, although similar prevalence of periodontitis was found among the studied groups, MFS patients showed worse periodontal parameters.
Differences and Associations between Physical Activity Motives and Types of Physical Activity among Adolescent Boys and Girls
Authors: Frömel Karel , Groffik Dorota , Šafář Michal , Mitáš Josef
Published: June 2022

Interventions aimed at motivation for physical activity (PA) are mostly beneficial, but the effects on preventing the decrease in PA are not entirely clear, especially in girls. The main aim of this study was to identify the differences and associations between PA motives and types of PA in boys and girls and between low and high motivated boys and girls. Another aim is to identify the types of motivation and PA that increase the likelihood of achieving PA recommendations and to propose ways of increasing PA among low motivated adolescents. The research carried out before the COVID‐19 pandemic (2010–2019) and involved 2,149 Czech and 1,927 Polish adolescents aged 15–19 years. The International Physical Activity Questionnaire‐Long Form was used to identify the level of PA types, while PA motivation was examined through the Motives for Physical Activities Measure‐Revised. During the ten years, a decline was observed in enjoyment, fitness, and social motives. An increase in appearance motives was observed in girls, while no significant changes were seen in boys. Boys showed a higher motivation for PA than girls in enjoyment, competence, fitness, and social motives, while girls were high motivated in appearance motives. The greatest statistically significant differences between low and high motivated individuals were found in the associations between recreation/vigorous PA and between all types of motivation in boys and girls in both countries. The strongest associations in both genders were observed between enjoyment/competence motives and recreation/vigorous PA. Respecting and using the associations between the types of PA motives and types of PA in low and high motivated boys and girls can support feelings of PA enjoyment, increase PA, support the achievement of PA recommendations, and positively affect adolescents’ healthy lifestyles.
High-Efficiency Mitigation of Nonlinear Distortion in Microwave Photonics Link Assisted by Artificial Neural Network
Authors: Yin Yihui , Yang Wanli , Xie Shifeng , Yun Binfeng
Published: June 2022

A microwave photonics radio over fiber link can deliver the radio frequency (RF) signal to realize the antenna remote. When the signal is a broadband and multicarrier RF signal, there are some linear distortions in the link, such as the crossmodulation distortion (XMD) and third-order intermodulation distortion (IMD3). It will destroy the wide-bandwidth performance of the link. Traditional postdigital compensation methods for XMD and IMD3 mitigation extract the baseband signal and reconstruct the compensation signal with calculated compensation factor. Here, a kind of artificial neural network genetic algorithm (ANN-GA) distortion compensation technique is proposed to seek the compensation factor instead of calculations. The neural network algorithm is used to fit the mapping function between the compensation factor and the distortion and give a set of predicted data as the original individual fitness value for the genetic algorithm. Based on the original value, the minimal distortion, the corresponding optimal compensation factors

γ

and

α

are found with optimization iterations. Taking advantage of the optimal compensation factors, based on the traditional postdigital compensation method, the distortion is mitigated with a suppression ratio of -84.4 dB. In our paper, the mitigation technology of the XMD and IMD3 can be applied for any kinds of link instead of mathematically modelling the link and calculating the compensation factor. The technology can improve the intelligence and flexibility of microwave photonic link linearization design.
Oral Alterations in Heritable Epidermolysis Bullosa: A Clinical Study and Literature Review
Authors: Polizzi Alessandro , Santonocito Simona , Patini Romeo , Quinzi Vincenzo , Mummolo Stefano , Leonardi Rosalia , Bianchi Alberto , Isola Gaetano
Published: June 2022

Epidermolysis bullosa (EB) is a group of skin disorders with skin fragility characterized by blistering from minimal mechanical trauma with rupture at the dermoepidermal junction. There are four major classical heritable EB types, due to mutations in as many as 20 distinct genes: EB simplex (EBS), junctional EB (JEB), dystrophic EB (DEB), and Kindler EB (KEB). This study is aimed at reporting case series on patients (N = 8; males, n = 5 and females, n = 3, age range 12‐68 years) affected by EB and performs a review of the literature on this topic. This group of disorders can affect oral soft and hard tissues in various ways, resulting in various effects including enamel hypoplasia, dental caries, microstomia, ankyloglossia, oral blistering, and ulcerations early‐onset periodontal disease. From the sample results, it can be concluded that the clinical manifestation of EB patients is highly variable and very different in prognosis. Oral health deeply influences the quality of life of EB patients. Dental management is essential to prevent the aggravation of soft tissue damage and tooth loss and to improve the quality of life through prosthetic and restorative therapies. Dentists should consider the oral alterations of EB subtypes to perform a personalized approach to the patients’ needs in a preventive and therapeutic point of view.
Evaluation of Financial Subsidy for Agriculture Based on Combined Algorithm
Authors: Chen Kexin , Wang Zhenyu
Published: June 2022

The stable development of agriculture is related to the national economy, and the fragility and foundation of agricultural production determine the inherent requirements of the government for financial support of agriculture. Based on China’s policy of agricultural subsidy, in this study, the basic characteristics and classification methods of agricultural subsidies are analyzed, and an evaluation model of agricultural subsidies is established based on a combined algorithm, where the attributes of agricultural subsidies are screened by analytic hierarchy process, and the evaluation process of agricultural subsidies is constructed by data envelopment approach. Moreover, the development level of regional financial subsidies for agriculture is measured by relative efficiency value, and the implementation direction of financial subsidies is evaluated, to enhance the administrative benefits of government finance and deepen the supply-side reform of agricultural financial subsidies, which promote the sustainable development of agricultural insurance and agricultural production.
A Novel Analysis of Generalized Perturbed Zakharov–Kuznetsov Equation of Fractional‐Order Arising in Dusty Plasma by Natural Transform Decomposition Method
Authors: Alhazmi Sharifah E. , Abdelmohsen Shaimaa A. M. , Alyami Maryam Ahmed , Ali Aatif , Asamoah Joshua Kiddy K.
Published: June 2022

The natural transform decomposition method (NTDM) is a relatively new transformation method for finding an approximate differential equation solution. In the current study, the NTDM has been used for obtaining an approximate solution of the fractional‐order generalized perturbed Zakharov–Kuznetsov (GPZK) equation. The method has been tested for three nonlinear cases of the fractional‐order GPZK equation. The absolute errors are analyzed by the proposed method and the q‐homotopy analysis transform method (q‐HATM). 3D and 2D graphs have shown the proposed method’s accuracy and effectiveness. NTDM gives a much‐closed solution after a few terms.
Assessment of Antioxidative and Alpha-Amylase Potential of Polyherbal Extract
Authors: Patwekar Mohsina , Patwekar Faheem , Mezni Amine , Sanaullah Syed , Fatema Shaikh Rohin , Almas Ustad , Ahmad Irfan , Tirth Vineet , Mallick Jewel
Published: June 2022

The present study aims to prepare a polyherbal formulation (PHF) of Azadirachta indica (Neem), Aloe barbadensis (Aloe vera), Allium sativum (garlic), Acacia arabica (Babul), and Aegle marmelos (Bel) and evaluation of antidiabetic and antioxidant activity utilizing the in vitro model. Air-dried powder of 5 medicinal plants, which are divided into equal portions, and PHF, is prepared by the soxhlet technique using polar and nonpolar solvents. The PHF is screened for the phytochemical screening, and then the antidiabetic activity is determined by alpha-amylase inhibition. The extracts thus obtained are also subjected to the inhibition assay by the use of (DNS) dinitro salicylic acid. The antioxidant activity was determined by the DPPH radical scavenging assay, H2O2 scavenging assay, and TBARS assay. In in vitro study, the result revealed polyherbal formulation in which hot water extract has the topmost inhibitory effect on alpha-amylase activity, ranging from 20.4% to 79.5% with an IC50 value of 48.98 ± 0.31 μg/ml. This extract clearly showed the effective lowering of postprandial hypertriglyceridemia (PPHG). In the antioxidant activity carried out by using the (DPPH) radical scavenging assay, the highest result was obtained by the concentration of 250 μg/ml, which was around 77.2 ± 0.05 with statistical significance compared with control (a:p<0.01; b:p<0.001), while in the GTA method, the highest result was obtained by the concentration of 250 μg/ml, which was around 78.2 ± 0.05, and in the case of the TBARS assay, the concentration of 250 μg/ml gave around 76.2 ± 0.03 anti-oxidant value. In conclusion, the study shows that polyherbal formulation has superior antidiabetic activity and antioxidant properties.
Severity Prediction over Parkinson’s Disease Prediction by Using the Deep Brooke Inception Net Classifier
Authors: Sarankumar R. , Vinod D. , Anitha K. , Manohar Gunaselvi , Vijayanand Karunanithi Senthamilselvi , Pant Bhaskar , Sundramurthy Venkatesa Prabhu
Published: June 2022

Parkinson’s disease (PD) is a neurodegenerative illness that progresses and is long-lasting. It becomes more difficult to talk, write, walk, and do other basic functions when the brain’s dopamine-generating neurons are injured or killed. There is a gradual rise in the intensity of these symptoms over time. Using Parkinson’s Telemonitoring Voice Data Set from UCI and deep neural networks, we provide a strategy for predicting the severity of Parkinson’s disease in this research. An unprocessed speech recording contains a slew of unintelligible data that makes correct diagnosis difficult. Therefore, the raw signal data must be preprocessed using the signal error drop standardization while the features can be grouped by using the wavelet cleft fuzzy algorithm. Then the abnormal features can be selected by using the firming bacteria foraging algorithm for feature size decomposition process. Then classification was made using the deep brooke inception net classifier. The performances of the classifier are compared where the simulation results show that the proposed strategy accuracy in detecting severity of the Parkinson’s disease is better than other conventional methods. The proposed DBIN model achieved better accuracy compared to other existing techniques. It is also found that the classification based on extracted voice abnormality data achieves better accuracy (99.8%) over PD prediction; hence it can be concluded as a better metric for severity prediction.