bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect Evaluation of Norepinephrine on Cardiac Function in Patients with Sepsis by Cardiac Ultrasound Imaging
Authors: Zhou Wei , Li Yuyu , Yang Baocheng , Wang Xianjun
Published: June 2022

In order to investigate the therapeutic effect of norepinephrine on patients with sepsis and the effect of echocardiography on the diagnosis of cardiac function in patients with sepsis, 86 patients with sepsis were selected as research objects and randomly divided into two groups. Patients in the control group (

N
=
43

cases) received conventional treatment (1~15 μg/

kg
∗
min

dopamine), and those in the experimental group (

N
=
43

cases) received conventional treatment+norepinephrine therapy (0.05~0.5 

μ
g
∗
kg

-1/min). The clinical efficacy, cardiac ultrasonography results, and hemodynamic indexes of patients between the two groups were analyzed and compared. The results showed that the total effective rate of treatment in the experimental group (97.7%) was significantly higher than that in the control group (81.4%) (

P
<
0.05

). The maximum, minimum, and average values of mitral valve E peak flow velocity (VEpeak) and left ventricular outflow tract peak flow velocity (Vpeak), respiratory variability of mitral valve E peak flow velocity (ΔVEpeak), and respiratory variability of peak flow velocity (ΔVpeak) were all significantly greater than those of the control group (

P
<
0.05

). The area under the receiver operating characteristic curve (AUC) of ΔVEpeak and ΔVpeak for predicting positive volume response in patients with sepsis was 0.934 and 0.913, respectively; the sensitivity was 0.828 and 0.827; the specificity was 0.936 and 0.893; and the Youden indices were 0.765 and 0.712, respectively. In short, norepinephrine had a high total response rate in patients with sepsis, and echocardiography can well evaluate the effect of norepinephrine on cardiac function in patients with sepsis, which is worthy of further promotion.
Simulation Model on Network Public Opinion Communication Model of Major Public Health Emergency and Management System Design
Authors: Li Lei , Wan Yujue , Plewczynski D. , Zhi Mei
Published: June 2022

In order to identify the communication law of network public opinion in major public health emergency, a multifactor communication model based on multiagent modeling is proposed. Based on the SEIR model and NetLogo simulation analysis, the model integrates a variety of network public opinion communication characteristics and extends the existing single network public opinion communication model. Based on these studies, a network public opinion communication management system is designed and developed with Python tools. Case analysis and simulation results show that this model can better simulate the evolution trend of network public opinion communication in major public health emergency; the key communication channels of public opinion play an important role in the evolution of network public opinion, which can control and guide the network public opinion of major public health emergency from the three communication influencing factors of total number, initial number, and communication cycle. Communication cycle refers to the number of days in the process of network public opinion dissemination of major public health emergencies.
[Retracted] Innovating a Practical Teaching Base of Landscape Architecture Major Based on the Campus Environment: A Case Study of Xuzhou University of Technology (China)
Authors: Tan Xuehong , Liu Pin , Nan Nan , Peng Yunle
Published: June 2022

Xuzhou University of Technology is a local newly established applied undergraduate university. The construction of a practical teaching base of landscape architecture majors was faced with the problems of short construction time and lack of funds. The feasibility, necessity, process, and achievements of the construction of the practical teaching base of landscape architecture majors based on the campus environment were studied. The guiding ideology of the campus practical teaching base for landscape architecture majors in applied undergraduate universities was put forward and the construction mode of “four in one” of practical teaching bases was discussed. The campus practical teaching base for landscape architecture majors was built and “four‐stage” progressive training and teaching activities were carried out in Xuzhou University of Technology. The effective combination of the landscape architecture professional practical teaching base and the logistics resources was realized. The combination of the logistics resources and professional construction of the university was carried out as a beneficial exploration in this paper. The achievements of practical teaching base construction were mainly reflected in the improvement of the quality of talent cultivation, the beautification of campus environment, and the enhancement of teachers practical ability.
Rapid Identification of Fupenzi (Rubus chingii Hu) and Its Adulteration by AuNP Visualization
Authors: Li Yuan , Suo Yixin , Wei Liuna , Zhang Yue , Wang Youyou , Deng Jiaxin , Chen Hengye , Yang Jian , Nan Tiegui , Fu Haiyan , Guo Lanping
Published: June 2022

Fupenzi (Rubus chingii Hu) is a dried and immature fruit in East China, which has effects of nourishing kidneys, solidifying essence, and otherwise. Because Fupenzi was often adulterated and replaced with inferior things, this paper had researched Fupenzi and its adulterant raspberry. A new type of visible sensor was constructed by using Au nanoparticles (AuNPs), which was modified by the surface-active agent and combined with the ultraviolet-visible (UV-vis) spectrum technology. It was found that the change in particle size after the interaction of AuNPs and adulterants will lead to color change. In this paper, the RGB (red, green, and blue) values of the solution were extracted to correlate the color with the concentration of adulterants, and the relationship between the absorption peak intensity and the concentration of adulterants was established. The results showed that the intensity of an absorption peak is related to adulteration concentration, and the color of the solution changed from red to gray as the particle size changed. The visual sensor constructed based on the above principle is a fast and precise method to detect adulteration with different concentrations, which has a potential application value in real-time and rapid detection of Fupenzi’s quality.
Hepatoprotective Effect of Mitochondria-Targeted Antioxidant Mito-TEMPO against Lipopolysaccharide-Induced Liver Injury in Mouse
Authors: Wang Peng-Fei , Xie Ke , Cao Yun-Xing , Zhang An
Published: June 2022

The liver is vulnerable to sepsis, and sepsis-induced liver injury is closely associated with poor survival of sepsis patients. Studies have found that the overproduction of reactive oxygen species (ROS) is the major cause of oxidative stress, which is the main pathogenic factor for the progression of septic liver injury. The mitochondria are a major source of ROS. Mito-TEMPO is a mitochondria-specific superoxide scavenger. The aim of this study was to investigate the effect of Mito-TEMPO on lipopolysaccharide- (LPS-) induced sepsis mice. We found that Mito-TEMPO pretreatment inhibited inflammation, attenuated LPS-induced liver injury, and enhanced the antioxidative capability in septic mice, as evidenced by the decreased MDA content and the increased SOD activity. In addition, Mito-TEMPO restored mitochondrial size and improved mitochondrial function. Finally, we found that the levels of pyroptosis-related proteins in the liver of LPS-treated mice were lower after pretreatment with Mito-TEMPO. The mechanisms could be related to Mito-TEMPO enhanced antioxidative capability and improved mitochondrial function, which reflects the ability to neutralize ROS.
[Retracted] Spatial Pattern Evolution and Influencing Factors on Industrial Agglomeration: Evidence from Pearl River Delta Urban Agglomeration
Authors: Huang Yan , Wu Xiaoxia , Li Yong’e
Published: June 2022

In order to clarify the spatial pattern and influencing factors on industrial agglomeration in urban agglomerations, based on the data of prefecture‐level cities from 2006 to 2018, this paper uses spatial standard deviation ellipse to analyze the spatial pattern evolution of manufacturing, producer services, consumer services, and foreign‐invested industries and takes a dynamic spatial Durbin model to empirically test the influencing factors of industrial agglomeration in Pearl River Delta (PRD) urban agglomeration. The main conclusions are as follows: 1) the degree of industrial agglomeration is at a low level and the difference in the industrial agglomeration level between cities is mainly manifested in the service industries; 2) manufacturing and foreign‐invested industries have entered the stage of industrial diffusion, and all types of industries show an east (by south)‐to‐west (by north) pattern, with a trend of expansion to the south and north; 3) the agglomeration level of service industries and foreign‐invested industries on the east bank of the Pearl River is higher than that on the west; and 4) from the empirical results, there is a general inertia effect in the industrial agglomeration and a siphon effect in the manufacturing agglomeration. Economic scale, transportation infrastructure, government intervention, opening up, and urban environment can all positively influence the agglomeration in some industries, with the apparent spatial spillover effects of each influencing factor. In addition, from the long‐term factors of industrial agglomeration, the coordinated development of urban agglomeration is beneficial to the agglomeration of manufacturing and producer services. The research significance of this paper is that it can practically provide a more comprehensive reference for the impact mechanism of industrial agglomeration in urban agglomerations of China.
Correlation Analysis between Tourism and Economic Growth Based on Computable General Equilibrium Model (CGE)
Authors: Wang Shiyu
Published: June 2022

The current tourism industry has the problems of low service efficiency, poor coordinated development, and slow economic growth in terms of service volume and economic growth. This paper is based on computable general equilibrium (CGE) model. Firstly, a CGE data analysis model based on bee colony intensive breakthrough algorithm is established to store and analyze the data in the whole chain of tourism. Then, combined with the comparative analysis of tourism economic data over the years, it is fed back to the CGE model for error analysis. Finally, relevant experiments are designed to analyze the relationship between tourism and economic growth. The correlation degree of local economic growth is analyzed. The results show that, compared with the traditional research method of tourism economic growth based on module data analysis, this CGE model can realize the correlation analysis of the data involved in the process of tourism economic growth and analyze the factors affecting the speed of economic growth, which has the advantages of good reliability and strong pertinence.
A Load Forecasting Algorithm for Power Internet of Things Using Training Data Dimension Expansion and Ensemble Learning Technique
Authors: Liu Chang , Rao Wei , Wang Jin , Tang Zeyang , Liu Chang , Wang Jie , Tian Li , Zhou Liang , Xu Jiangpei
Published: June 2022

With the development of the power internet of things (IOT), load forecasting will play an important role the power system. It can optimize the power generation planning and improve the economical operation of power IOT. In this paper, a new loading forecasting algorithm for power IOT is proposed using training data dimension expansion and ensemble learning. In the offline phase, the obtained meteorological data and time information is normalized to remove the unit effect at first. Then, the Hampel filter is used to cope with the outliers of the meteorological data from sensors. Through the preprocessing, the fingerprint of the training data is constructed. Next, the matrix multiplication method is proposed to expand the dimension of training data fingerprint information. Finally, the ensemble learning combining multiple long short-term memory (LSTM) networks are proposed to obtain multiple power load forecasting models and corresponding weight coefficients. In the online phase, the obtained meteorological data and time information are preprocessed to form the input of and power load forecasting models. The final power load forecasting is obtained by linear weighted sum method with intermediate forecasting result. In the proposed algorithm, more features of training data can be obtained by the data dimension expansion. Moreover, the ensemble learning using LSTM can make fully use of the timing sequence of training and improve the generalization performance of offline training. Experiment results illustrate that the proposed algorithm has better forecasting performance than existing methods.
The Combination Clinical Value of Plasma Brain Natriuretic Peptide and Serum HbAlc in the Diagnosis of Chronic Pulmonary Heart Disease
Authors: Jia Enxia
Published: June 2022

Objective. To analyze the combination clinical value of plasma brain natriuretic peptide and serum glycated hemoglobin (HbAlc) in chronic pulmonary heart disease. Methods. A total of 200 patients with chronic pulmonary heart disease admitted to our hospital from January 2021 to January 2022 were selected as the observation group, and 200 healthy subjects were selected as the control group during the same period. All subjects were examined by an ECG vector map and plasma BNP, and HbAlc levels were detected to analyze the value and clinical significance of each index in single diagnosis and combined diagnosis. Results. Plasma BNP and HbAlc levels in the observation group were significantly higher than those in the control group (

P
<
0.05

). There were 154 BNP positive, 146 HbAlc positive, 164 parallel combined diagnosis positive, and 132 serial combined diagnosis positive. Sensitivity of series combination diagnosis was significantly higher than other indexes (

P
<
0.05

); especially, parallel combination diagnosis was significantly higher than other indexes (

P
<
0.05

). Besides, area under the ROC curve of parallel combination diagnosis and series combination diagnosis was significantly higher than that of each index alone diagnosis (

P
<
0.05

). Conclusion. In the diagnosis of chronic pulmonary heart disease, the combination of plasma BNP and HbAlc can effectively improve the diagnostic specificity and sensitivity, as well as improve the area under the ROC curve.
LncRNA BC083743 Silencing Exacerbated Osteoporosis by Regulating the miR-103-3p/SATB2 Axis to Inhibit Osteogenic Differentiation
Authors: Lu Feng , Tang Ling
Published: June 2022

Objective. The target of the present paper was to reveal the influence of LncRNA BC083743 on osteogenesis in human bone marrow mesenchymal stem cells (hBMSCs). Methods. Serum specimens from osteoporotic patients and normal subjects were collected to isolate hBMSCs from femoral head tissue. The levels of BC083743 and miR-103-3p in serum and hBMSCs were measured by QRT-PCR. Alkaline phosphatase (ALP) activity test and alizarin red dyeing were used to identify ALP activity and mineralization forming ability of hBMSCs after transfection with si-BC083743 (siRNA-targeting BC083743). In addition, QRT-PCR and immunoblotting were conducted to identify the expressing levels of Runt-related transcription factor 2(Runx2), osteoprotegerin (OPG), and bone morphogenetic protein 2 (BMP2) in hBMSCs. Dual-luciferase reporter gene and RNA pull-down assays were employed to substantiate the binding of BC083743 to miR-103-3p and miR-103-3p to SATB2. Results. BC083743 expression was significantly downregulated in sera from patients with osteoporosis, and osteogenic differentiation-related genes and BC083743 expression were obviously upregulated as the time to osteogenic differentiation increased. BC083743 knockdown hindered the osteogenic differentiation of hBMSCs. BC083743 was aimed at miR-103-3p and miR-103-3p inhibitors partially reversed the inhibitory effect of BC083743 downregulation on hBMSCs osteogenesis. BC083743 silencing downregulated SATB2 through uptake of miR-103-3p, thereby inhibiting hBMSCs osteogenesis to exacerbate osteoporosis. Conclusion. BC083743/miR-103-3p/SATB2 axis inhibited osteogenic differentiation and exacerbated osteoporosis, which may offer brand-new molecular aims for the treatment of clinical osteoporosis.
Optimization of Plasma Arc Cutting Parameters on Machining of Inconel 718 Superalloy
Authors: Karthick M. , Anand P. , Meikandan M. , Sekar S. , Natrayan L. , Bobe Ketema
Published: June 2022

Nickel‐based super composites are widely applied in the industry. These alloys withstand high thermal debility conditions and give better strength to machine parts in aviation, biomechanical, marine, and vehicle commerce. Nickel‐based alloys have high quality, corrosion resistance, and high heat refusal. Inconel 718 is one such composite extensively utilized in these loading circumstances because of chemical stability, mechanical friction, high thermal corrosion, and high stability. During the cutting procedure, these qualities will bring a lot of processing issues, for example, surface roughness, machining efficiency, and wear of tool. Plasma arc cutting (PAC) is an upsetting metal‐cutting process to perform slicing of hard to cut materials even for complex profiles. The present work analyzes the impact of PAC process factors, for instance, gas pressure (GP), arc current (AC), cutting speed (CS), and stand-off distance (SOD) on assessing the kerf width (KW), kerf taper (KT), and heat-affected zone (HAZ) of Inconel 718 superalloy. This work deliberates about the cutting parameters required for the machining of Inconel 718 to provide least surface roughness and low instrument wear. The experiments conducted to validate the ingenuity of the process are in accordance with the optimal parameter settings necessary for machining purposes. The divergence from actuality has been extremely minimal with a relative error of 4.45% for kerf width and 4.36% for the extent of heat-affected zone postmachining.
Caries‐Preventive Effect and Retention of Glass‐Ionomer and Resin‐Based Sealants: A Randomized Clinical Comparative Evaluation
Authors: Uzel Ilhan , Gurlek Ceren , Kuter Berna , Ertugrul Fahinur , Eden Ece
Published: June 2022

Background. Deep fissures are highly unprotected from the development of caries. Resin‐based materials and glass‐ionomer cements for sealing fissures are useful in caries control through physical barrier formation, which prohibits metabolic exchange between fissure microorganisms. Retention is one of the most critical properties of fissure sealants. This in vivo study is aimed at comparing and evaluating the clinical efficacy of resin and glass ionomer‐based fissure sealants on first permanent molars with follow‐ups at 6‐, 12‐, and 18‐month intervals. Methods. A randomized split‐mouth design clinical study was conducted after obtaining the ethical committee approval. A total of 50 patients, aged between 7 and 12 years, were randomized and enrolled in the study to perform a total of 200 sealant placements on all four caries‐free and hypoplasia‐free first permanent molars having deep fissures, which are susceptible to caries, were included in this study. The four permanent molars were divided into the following four groups: group A (control), B (Grandioseal, Voco, Germany), C (Smartseal & Loc, Detax Gmbh & Co, Germany), and D (Fuji triage capsule, GC, Belgium). The sealed molars were clinically evaluated at intervals of 6, 12, and 18 months to assess sealant retention, surface roughness, marginal coloration, and caries status through visual evaluation of the sealant by two evaluators. Results. Concerning retention, there were statistically significant differences between the sealants in terms of the survival of partial and fully retained sealants as well as in the survival of caries‐free teeth. Two resin‐based (Smartseal & Loc) and glass‐ionomer cement (Fuji triage) sealants showed significantly similar performances in permanent molars for up to 18 months. In terms of retention, one of the resin‐based (Grandioseal) sealants performed better as compared to the others and showed better caries prevention in deep fissures. Conclusion. It is concluded that both the sealants had comparable retention and caries‐preventive effects in 7 to 12‐year‐old children and can be considered as suitable sealants for a period of at least 18 months in moderate caries risk patients.
Recovering Latent Data Flow from Business Process Model Automatically
Authors: Ye Sheng , Wang Jing , Ali Sikandar , Khattak Hasan Ali , Guo Chenhong , Yang Zhongguo
Published: June 2022

Process-driven applications evolve rapidly through the interaction between executable BPMN (Business Process Modeling and Notation) models, business tasks, and external services. Given these components operate on some shared process data, it is imperative to recover the latent data by visiting relation, which is known as data flow among these tasks. Data flow will benefit some typical applications including data flow anomaly checking and data privacy protection. However, in most cases, the complete data flow in a business process is not explicitly defined but hidden in model elements such as form declarations, variable declarations, and program code. Some methods to recovering data flow based on process model analysis of source code have some drawbacks; i.e., for security reasons, users do not want to provide source code but only encapsulated methods; therefore, data flows are difficult to analyze. We propose a method to generate running logs that are used to produce a complete data flow picture combined with the static code analysis method. This method combines the simple and easy-to-use characteristics of static code analysis methods and makes up for the shortcomings of static code analysis methods that cannot adapt to complex business processes, and as a result, the analyzed data flow is inaccurate. Moreover, a holistic framework is proposed to generate the data flow graph. The prototype system designed on Camunda and Flowable BPM (business process management) engine proves the applicability of the solution. The effectiveness of our method is validated on the prototype system.
The Comprehensive Analysis of Interferon-Related Prognostic Signature with regard to Immune Features in Ovarian Cancer
Authors: An Yuanyuan , Duan Hua
Published: June 2022

Interferon plays an important role in immune response of ovarian cancer. However, the expression pattern of interferon in ovarian cancer remains unclear. This study is aimed at exploring the expression profile of interferon-relate genes and constructing an interferon-based prognostic signature in ovarian cancer. The ovarian cancer samples collected from TCGA database were viewed as the training set, and ovarian cancer samples collected from GEO datasets were used as the independent validation sets. Univariate Cox regression analysis and multivariate Cox regression analysis were used to construct interferon-related signature, which worked as independent prognostic factor. Bioinformatics based on David software, GSEA, and R software were used to investigate the relationship between immune status and the signature in ovarian cancer. The signature showed close correlation with the status for ovarian cancer immune microenvironment, which might provide the possibility for clinical targeted therapy.
[Retracted] Preparation of an Intelligent pH Film Based on Biodegradable Polymers for Monitoring the Food Quality and Reducing the Microbial Contaminants
Authors: Subramanian Kumaran , Balaraman Deivasigamani , Kaliyaperumal Kumaravel , Devi Rajeswari V. , Balakrishnan K. , Ronald Ross P. , Perumal Elumalai , Sampath Renuga Pugazhvendan , Panangal Mani , Swarnalatha Y. , Velmurugan S.
Published: June 2022

Hydrogel refers to a three‐dimensional cross‐linked polymeric network made of synthetic or natural polymers that can hold water in its porous structure. The inclusion of hydrophilic groups in the polymer chains, such as amino, carboxyl, and hydroxyl groups, contributes to the hydrogel’s water‐holding ability. At physiological temperature and pH, these polymeric materials do not dissolve in water, but they do swell significantly in aqueous media. Hydrogel can be manufactured out of almost any water‐soluble polymer, and it comes in a variety of chemical compositions and bulk physical properties. Hydrogel can also be made in a variety of ways. Hydrogel comes in a variety of physical shapes, including slabs, microparticles, nanoparticles, coatings, and films. Due to its ease of manufacture and self‐application in clinical and fundamental applications, hydrogel has been widely exploited as a drug carrier. Contact lenses, artificial corneas, wound dressing, suture coating, catheters, and electrode sensors are some of the biomedical applications of hydrogels. The pigment color changes were observed from colorless to pale pink followed by dark reddish‐pink. Anthocyanin was produced in large quantities and tested using a UV‐visible spectrophotometer. At 450–550 nm, the largest peak (absorbance) was detected, indicating the presence of anthocyanin. The FTIR analysis of this study shows the different stretches of bonds at different peaks: 2918.309 (‐C‐H alkane stretch), 2812.12 (‐C‐H aldehyde weak intensity), 192320.37/cm (C‐O bend), 21915.50, 2029.08/cm (‐C=C arene group), 1906.94/cm (=C‐H aromatics), 1797.78/cm (=C‐H), 1707.94 (‐C=O ketene), 1579.70, 1382.96 (C‐H alkane strong bend), 889.18/cm (C‐H aromatics plane bend), and 412.77/cm (‐C‐CI strong bond). The spectra of the PVA/chitosan film depict the peak’s formation: 1571.88, 1529.55, 1500.62/cm (C‐H alkene strong bend), 1492.90, 1483.26, 1467.83/cm (C‐H alkene strong bond), 670.48, 443.63, 412.77/cm (‐O‐H carboxylic acids with great intensity), 1708.93 (‐C=O ketone), and 1656.0/cm (alkenyl C=C stretch strong bond).
A Numerical Study of Ground Displacement and Stress Conditions of Small and Medium Circular Diaphragm Wall during Excavation
Authors: Xiao Zun-Qun , Lin Jian , Tang Dong-Sang
Published: June 2022

In the present study, a dimensional total‐stress elasto‐plastic FEM analysis was conducted, which was based on the Mohr‐Coulomb constitutive model. The model was combined with a practical engineering case in order to investigate ground displacements and stress conditions during the installations of a medium‐sized and a small‐sized circular diaphragm wall, as well as the subsequent soil excavations within the walls. The distribution characteristics of the lateral radial displacements and stress conditions in the ground following the wall installations and excavations within the walls were investigated. Also, two different excavation methods, as well as three different soil depths for the walls, were considered. The distributions of the internal forces along the depth directions of the radial sections of the walls were also analyzed in this study. The analysis results showed that the slotting order had made the model nonaxisymmetric, which had further influenced the distribution characteristics of radial stress and displacements. It was found that the distributions of the horizontal radial displacements, along with the stress levels of the soil behind the walls, were only minimally affected by the excavations of the soil in the shaft. The internal force distribution of the wall radial section caused by the direct excavation method and the reverse excavation method is very small, that is, the wall bending moment generated by the reverse excavation process is larger, and the most obvious near the rock‐socketed depth. The distribution pattern of the bending moment depth corresponding to different excavation construction methods is similar. Furthermore, the soil penetration depths of the walls were determined to have had little influence on the internal force distributions of the radial sections of the walls above the foundation pit. However, there was a greater influence observed on the internal force distributions of the radial sections of the walls below the foundation pit.
Intelligent English Translation and Optimization Based on Big Data Model
Authors: Wang Xiao Yan
Published: June 2022

With the development and popularization of communication technology, intelligent analysis using big data front-end in various fields is also skillful. In the study of English literature and short sentence translation, we should realize a fast and intelligent translation approach. Based on the analysis and research of big data, a set of online learning algorithms for English translation learning algorithms is compiled, which will greatly improve the efficiency and accuracy of translation. On the premise of online processing of big data English information, this paper shortens the processing time without affecting the translation accuracy. The radial function algorithm for big data reduces the complexity of big data, improves the computational efficiency of dealing with problems, and realizes the generalization of translation performance. The effective application of big data in the optimization practice of English translation will provide an effective theoretical way for accurate translation and realize intelligent model algorithm. The experimental results are summarized as follows: (1) with the increase of the number of translated texts, the translation time will also increase and the difficulty will increase. (2) The approximation value in radial basis function is used to evaluate the translation effect, and its error in 100 texts will decrease with the increase of literature, and its approximation state is consistent with the real state. (3) Among various translation techniques, conventional literal translation is still the usual method, and its feedback effect is also the best, which is the basic method of thinking according to data. (4) The evaluation of accuracy in intelligent calculation methods is different, from 100% accuracy under heterogeneous functions to 50% accuracy under unified algorithms, which shows that optimization methods need to be updated and improved in time.
A Type‐3 Fuzzy Approach for Stabilization and Synchronization of Chaotic Systems: Applicable for Financial and Physical Chaotic Systems
Authors: Tian Man-Wen , Bouteraa Yassine , Alattas Khalid A. , Yan Shu-Rong , Alanazi Abdullah K. , Mohammadzadeh Ardashir , Mobayen Saleh
Published: June 2022

In this paper, a new approach is presented for stabilizing and synchronizing financial chaotic systems. A new type‐3 (T3) fuzzy‐based system (FLS) with an online optimization scheme is designed to cope with chaotic behavior, high‐level uncertainties, and unknown dynamics. An adaptive compensator also eliminates the effect of approximation errors (AEs) and perturbations. The stability of the dynamics of synchronization errors is guaranteed by the use of the Lyapunov method. Several simulations and comparisons demonstrate the superiority of the suggested control and synchronization scenarios.
Instinctive Recognition of Pathogens in Rice Using Reformed Fractional Differential Segmentation and Innovative Fuzzy Logic-Based Probabilistic Neural Network
Authors: Preetham Anusha , Ahmad Sayed Sayeed , Wattar Ihab , Singh Pooja , Rout Sandeep , Alqahtani Mejdal A. , Tetteh Amoatey Enoch
Published: June 2022

Rice is an essential primary food crop in the world, and it plays a significant part in the country’s economy. It is the most often eaten stable food and is in great demand in the market as the world’s population continues to expand. Rice output should be boosted to fulfil the growing demand. As a result, the yield of plant crops diminishes, creating an environment conducive to the spread of infectious illnesses. To boost the production of agricultural fields, it is necessary to remove plant diseases from the environment. This study presents ways for recognising three types of rice plant diseases, as well as a healthy leaf, in rice plants. This includes image capture, image preprocessing, segmentation, feature extraction, and classification of three rice plant illnesses, as well as classification of a healthy leaf, among other techniques. Following the K-means segmentation, the features are extracted utilising three criteria, which are colour, shape, and texture, to generate a final product. Colour, shape, and texture are the parameters used in the extraction of the features. It is proposed that a novel intensity-based technique is used to retrieve colour features from the infected section, whereas the form parameters of the infected section, such as the area and diameter, and the texture characteristics of the infected section are extracted using a grey-level co-occurrence matrix. The colour features are retrieved depending on the characteristics of the features. All three previous techniques were surpassed by the proposed fuzzy logic-based probabilistic neural network on a range of performance metrics, with the new network obtaining greater accuracy. Finally, the result is validated using the fivefold cross-validation method, with the final accuracy for the diseases such as bacterial leaf blight, brown spot, healthy leaf, and rice blast being 95.20 percent, 97.60 percent, 99.20 percent, and 98.40 percent, respectively, and 95.40 percent for the disease brown spot.
A Prediction Method for Floor Water Inrush Based on Chaotic Fruit Fly Optimization Algorithm–Generalized Regression Neural Network
Authors: Zhu Zhijie , Sun Chen , Gao Xicai , Liang Zhuang
Published: June 2022

The research was aimed at predicting floor water-inrush risk in coal mines and forewarn of such accidents to guide safe production of coal mines in practice. To this end, a prediction method for floor water inrush combining the chaotic fruit fly optimization algorithm (CFOA) and the generalized regression neural network (GRNN) is proposed. Floor water inrush is predicted by virtue of the robust nonlinear mapping capability of the GRNN. However, because the prediction effect of the GRNN is influenced by the smoothing factor, the CFOA is adopted to optimize this factor. In this way, influences of human factors during parameter determination of the GRNN prediction model are decreased, and the prediction accuracy and applicability of the model are improved. Results show that the CFOA–GRNN prediction model has an accuracy of 93.2% for whether floor water inrush will occur or not. Compared with the BPNN, RNN, and GRU network prediction model, the CFOA–GRNN model is superior in the prediction accuracy and generalization, and it can more accurately predict floor water inrush.
PointLAE: A Point Cloud Semantic Segmentation Neural Network via Multifeature Aggregation for Large-Scale Application
Authors: Li Jiang , Liu Jinhao
Published: June 2022

The fast semantic segmentation algorithm of 3D laser point clouds for large scenes is of great significance for mobile information measurement systems, but the point cloud data is complex and generates problems such as disorder, rotational invariance, sparsity, severe occlusion, and unstructured data. We address the above problems by proposing the random sampling feature aggregation module ATSE module, which solves the problem of effective aggregation of features at different scales, and a new semantic segmentation framework PointLAE, which effectively presegments point clouds and obtains good semantic segmentation results by neural network training based on the features aggregated by the above module. We validate the accuracy of the algorithm by training on Semantic3D, a public dataset of large outdoor scenes, with an accuracy of 90.3, while verifying the robustness of the algorithm on Mvf CNN datasets with different sparsity levels, with an accuracy of 86.2, and on Bjfumap data aggregated by our own mobile environmental information collection platform, with an accuracy of 77.4, demonstrating that the algorithm is good for mobile information complex scale data in mobile information collection with great recognition effect.
Value of a Signature of Immune-Related Genes in Predicting the Prognosis of Melanoma and Its Responses to Immune Checkpoint Blocker Therapies
Authors: Yuan Bo , Miao Linlin , Mei Disen , Li Lingzhi , Zhou Qiongyan , Dong Dong , Wang Songting , Zhu Xiaoxia , Xu Suling
Published: June 2022

Melanoma is becoming increasingly common worldwide, with high rates of transformation into malignancy compared to other skin lesions. The prognosis of patients with melanoma at an advanced stage is highly unsatisfying despite the development of immunotherapy, target therapy, or combinative therapy. The major barrier to exploiting immune checkpoint therapies and achieving the best benefits clinically is resistance that can easily develop if regimens are not selected appropriately. In this study, we investigated the possibility of using immune-related genes to predict patient survival and their responses to immune checkpoint blocker therapies with the expression profiles available at The Cancer Genome Atlas (TCGA) Program plus expression data from the Gene Expression Omnibus (GEO) for validation. A five gene signature that is highly correlated with the local infiltration of cytotoxic lymphocytes in the tumor microenvironment was identified, and a scoring model was developed with stepwise regression after multivariate Cox analyses. The score calculated strongly correlates with Breslow depth, and this model effectively predicts the prognosis of patients with melanoma, whether primary or metastasized. It also depicts the heterogenous immune-related nature of melanoma by revealing different predicted responses to immune checkpoint blocker therapies through its correlation to tumor immune dysfunction and exclusion (TIDE) score.
Conservative Therapy vs. Endovascular Approach for Intracranial Vertebrobasilar Artery Trunk Large Aneurysms: A Prospective Multicenter Cohort Study
Authors: Wu Qiaowei , Li Tianxiao , Jiang Weijian , Hernesniemi Juha Antero , Li Li , He Yingkun
Published: June 2022

Background. Intracranial vertebrobasilar trunk large (≥10 mm) aneurysms (IVBTLAs) are rare and challenging to manage. In this study, we describe the natural prognosis and evaluate the safety and efficacy of endovascular treatment of IVBTLAs compared with conservative therapy. Methods. This prospective multicenter cohort study included patients with IVBTLAs, who chose either endovascular treatment (endovascular group) or conservative therapy (conservative group) after discussion with their doctors. The primary endpoint was the incidence of serious adverse events (SAEs) related to the target vessel, while secondary endpoints included target vessel-related mortality, major stroke, other serious adverse events, and aneurysm occlusion rate. Results. In total, 258 patients were referred to our two centers for the management of vertebrobasilar aneurysms, and 69 patients had IVBTLAs. Among them, 51 patients underwent endovascular treatment, and 18 patients received conservative therapy. The incidence of target vessel-related SAEs was 15.7% (8/51) in the endovascular group and 44.4% (8/18) in the conservative group (

P
=
0.031

). The target vessel-related mortality was 2.0% (1/51) in the endovascular group and 38.9% (7/18) in the conservative group (

P
<
0.001

). The cumulative survival rates in the endovascular group and conservative group within 1-year, 3-year, and 5-year were 98.0% vs. 83.3%,

P
=
0.020

; 98.0% vs. 66.7%,

P
=
0.001

; and 98.0% vs. 35.6%,

P
<
0.001

, respectively. Multivariate analysis revealed conservative therapy, giant aneurysm, and ischemic onset as risks factor for SAEs. Conclusions. Compared with conservative treatment, endovascular treatment of the IVBTLAs may be associated with a lower incidence of SAEs, with higher 1-year, 3-year, and 5-year survival rates. Conservative therapy, giant aneurysm, and ischemic onset were associated with a high risk of SAEs.
Thermal Vibration of Rectangle Plate with Two-Dimensional Circular Thickness Effect
Authors: Sharma Amit , Mani Naveen , Bhardwaj Reeta , Kumar Kamal
Published: June 2022

Frequencies comprising two-dimensional circular thickness impacts are computed for the first time, for clamped rectangle plate under nonhomogeneity and temperature field. The study also comprises the two-dimensional temperature and one-dimensional density effect, on frequencies computation, utilizing the Rayleigh–Ritz technique. The objective of the study is to reduce the frequencies of the plate as well as to provide the effect of various plate parameters on frequencies. Numerical illustration and comparative study of the frequencies with other available results well authenticate the objective of the study. A comparison of frequency modes done for the clamped rectangle and square plate corresponding to tapering and aspect ratio and nonhomogeneity concludes that frequency obtained for the present study is very less in comparison with other studies done. A convergence study of the obtained results is also presented with the help of figures. The convergence study done concludes that rate of convergence in case of circular variation is faster than the other variations.
Moving Target Tracking Algorithm Based on Improved Resampling Particle Filter in UWB Environment
Authors: Li Zhihao , Wu Junkang , Kuang Zhenwu , Zhang Zuqiong , Zhang Shenglan , Dong Luxi , Zhang Lieping
Published: June 2022

In this paper, a moving target tracking (MTT) algorithm based on the improved resampling particle filter (IRPF) was put forward for the reduced accuracy of particle filter (PF) due to the lack of particle diversity resulting from traditional resampling methods. In this algorithm, the influences of the likelihood probability distribution of particles on the PF accuracy were firstly analyzed to stratify the adaptive regions of particles, and a particle diversity measurement index based on stratification was proposed. After that, a threshold was set for the particle diversity after resampling. If the particle diversity failed to reach the set threshold, all new particles would be subjected to a Gaussian random walk in a preset variance matrix to improve the particle diversity. Finally, the performance of related algorithms was tested in both simulation environment and actual indoor ultrawideband (UWB) nonline-of-sight (NLOS) environment. The experimental results revealed that the nonlinear target state estimation accuracy was maximally and minimally improved by 12.83% and 1.97%, respectively, in the simulation environment, and the root mean square error (RMSE) of MTT was reduced from 17.131 cm to 10.471 cm in actual UWB NLOS environment, indicating that the IRPF algorithm can enhance the target estimation accuracy and state tracking capability, manifesting better filter performance.
Receitas e despesas no setor governo no Brasil durante os anos 2000: Elementos para avaliação da efetividade das políticas governamentais
Authors: Biasoto Junior Geraldo
Published: June 2022

O objetivo da reflexão exposta é avaliar, ainda que preliminarmente, os elementos centrais das políticas de gasto do setor público brasileiro nos anos recentes. Dois trajetos são realizados no artigo. O primeiro é uma tentativa de compreender os grandes movimentos das contas públicas, com destaque para receitas e gastos reais, assim como sua desagregação. O segundo busca avaliar, qualitativamente, os principais avanços e dificuldades dos mecanismos institucionais que dão suporte à intervenção do Estado no domínio econômico e social, notadamente no que tange aos aparelhos de planejamento e avaliação do gasto público.
Especialista em políticas públicas e gestão governamental: Uma descrição da carreira nos estados da Bahia, Goiás, Mato Grosso, Minas Gerais, Rio de Janeiro e São Paulo
Authors: Mota Maria Martha , Coelho Fernando de Souza , Gomes Thiago Von Zeidler , Teixeira Caio Penko
Published: June 2022

A partir de meados da década de 1980, emergem discussões sobre um novo perfil de burocrata no processo de redemocratização no Brasil. A (re)conquista dos direitos políticos e a ampliação dos direitos sociais, bem como a entrada de novos atores no processo decisório, tornaram clara a necessidade de articulações/negociações no espectro político e profissionalização da alta burocracia para concretização das políticas públicas e modernização da gestão pública. Com base em estudo do embaixador Sérgio Paulo Rouanet, em 1982, a Escola Nacional de Administração Pública (ENAP) foi criada, no ano de 1986, com objetivo de formar gestores públicos aptos à tomada de decisão na alta estrutura do Poder Executivo e, como subproduto, surge, em 1989, a carreira de especialista em políticas públicas e gestão governamental (EPPGG). No início dos anos 1990, houve descontinuidade no projeto da reforma administrativa e provimento da carreira de EPPGG durante os governos de Fernando Collor e Itamar Franco. Os concursos foram retomados tão-somente em 1995, no bojo do processo de Reforma do Aparelho do Estado, apresentado pelo governo Fernando Henrique Cardoso. Percebe-se que a iniciativa de estruturação de uma alta burocracia administrativo-organizacional estável e meritocrática no governo federal refletiu no nível estadual o anseio por profissional similar, resultando na criação da carreira de EPPGG em algumas unidades da federação. O presente trabalho tem como objetivo apresentar uma descrição sinóptica da carreira de especialista em políticas públicas e gestão governamental nos estados da Bahia, Goiás, Mato Grosso, Minas Gerais, Rio de Janeiro e São Paulo. Metodologicamente, a pesquisa baseou-se em coleta de informações a respeito das carreiras nas secretarias e casas legislativas estaduais. Após o levantamento de dados, procedeu-se uma comparação entre as carreiras estaduais, analisando suas convergências e divergências ao modelo adotado pelo governo federal. À guisa de conclusão, observa-se que a carreira de EPPGG nos estados tende à consolidação, demonstrada pela regularidade de recrutamento, número de servidores ocupantes do cargo e papel – reconhecido ou em reconhecimento – como núcleo estratégico de apoio aos mandatários políticos e/ou dirigentes públicos, seja no ciclo das políticas públicas estruturantes, seja nos macroprocessos de gestão governamental.
Cardiovascular and Limb Events Following Endovascular Revascularization Among Patients ≥65 Years Old: An American College of Cardiology PVI Registry Analysis
Authors: Weissler E. Hope , Wang Yongfei , Gales Jordan M. , Feldman Dmitriy N. , Arya Shipra , Secemsky Eric A. , Aronow Herbert D. , Hawkins Beau M. , Gutierrez J. Antonio , Patel Manesh R. , Curtis Jeptha P. , Jones W. Schuyler , Swaminathan Rajesh V.
Published: June 2022

Background

We aimed to characterize the occurrence of major adverse cardiovascular and limb events (MACE and MALE) among patients with peripheral artery disease (PAD) undergoing peripheral vascular intervention (PVI), as well as associated factors in patients with chronic limb threatening ischemia (CLTI).

Methods and Results

Patients undergoing PVI in the American College of Cardiology’s (ACC) National Cardiovascular Data Registry’s PVI Registry who could be linked to Centers for Medicare and Medicaid Services data were included. The primary outcomes were MACE, MALE, and readmission within 1 month and 1 year following index CLTI‐PVI or non‐CLTI‐PVI. Cox proportional hazards regression was used to identify factors associated with the development of the primary outcomes among patients undergoing CLTI‐PVI. There were 1758 (49.7%) patients undergoing CLTI‐PVI and 1779 (50.3%) undergoing non‐CLTI‐PVI. By 1 year, MACE occurred in 29.5% of patients with CLTI (n=519), and MALE occurred in 34.0% of patients with CLTI (n=598). By 1 year, MACE occurred in 8.2% of patients with non‐CLTI (n=146), and MALE occurred in 26.1% of patients with non‐CLTI (n=465). Predictors of MACE at 1 year in CLTI‐PVI included end‐stage renal disease on hemodialysis, congestive heart failure, prior CABG, and severe lung disease. Predictors of MALE at 1 year in CLTI‐PVI included treatment of a prior bypass graft, profunda femoral artery treatment, end‐stage renal disease on hemodialysis, and treatment of a previously treated lesion.

Conclusions

Patients ≥65 years old undergoing PVI experience high rates of MACE and MALE. A range of modifiable and non‐modifiable patient factors, procedural characteristics, and medications are associated with the occurrence of MACE and MALE following CLTI‐PVI.