bluuebunny/crossref_metadata_2025 huggingface dataset:
EVALUATION OF MONETARY POLICY IN EMU THROUGH CREDIT CHANNELS INTERCONNECTEDNESS: EVIDENCE USING BLS DATA
Authors: PETSALAKIS MICHAIL E. , KHALID AHMED M. , PREMARATNE GAMINI
Published: September 2021

Credit channel(s) of the monetary policy transmission has not been debated much in the literature especially in the context of the European monetary union (EMU) and the apparent rising fragmentation of the previously much integrated European banking system. This discussion is even more important in the aftermath of the global financial crisis (GFC) and the decade-long European debt crisis (EDC), a number of European countries have been experiencing. This paper attempts to investigate the interconnectedness of credit channels in policy transmission in the context of EMU using bank lending survey (BLS) data for a sample of eight European countries. One of the main contributions of this paper is to use BLS data for the entire 11 credit channels. We use principal component analysis (PCA) to investigate the impact of monetary policy on the interconnectedness structure of credit channels. PCA is conducted both for EMU across channels and sample countries. EFA-orthogonal vector rotation indicates a core versus periphery interconnectedness pattern. The results suggest that the household balance sheet channel, borrower cash flow channel and interest rate channel are the most divergent channels in EMU.
Killing vector fields of Bianchi type I spacetimes via Rif tree approach
Authors: Bokhari Ashfaque H. , Hussain Tahir , Hussain Wajid , Khan Fawad
Published: September 2021

In this paper, we have adopted a new approach to study the Killing vector fields of locally rotationally symmetric and general Bianchi type I spacetimes. Instead of directly integrating the set of Killing’s equations, an algorithm is developed in Maple which converts these equations to the reduced involutive form (Rif) and consequently it imposes some restrictions on the metric functions in the form of a tree, known as Rif tree. The set of Killing’s equations is then solved for each branch of the Rif tree, giving the explicit form of the Killing vector fields. The structure of Lie algebra is presented for each set of the obtained Killing vector fields and some physical implications of the obtained metrics are discussed.
Magnetic properties and phase diagrams of the mixed spin-(1 2, 3 2) Ising–Heisenberg model in the mean field approximation
Authors: Seto G. , Yessoufou R. A. A. , Kpadonou A. , Albayrak E. , Hontinfinde F.
Published: September 2021

In this paper, the effects of the longitudinal [Formula: see text] and the transverse [Formula: see text] crystal fields on the mixed spin-[Formula: see text] Ising–Heisenberg model have been studied. The thermodynamic properties of the model are obtained by using a new approach of the mean field approximation (MFA). The thermal variations of the order-parameters and the total magnetic susceptibility of the model are carefully investigated to obtain the phase diagrams on the [Formula: see text] planes for [Formula: see text] and on the [Formula: see text] planes for [Formula: see text] and 6. The existence of compensation temperatures between the sublattice magnetizations, [Formula: see text], and the two components of the quadrupole moments, [Formula: see text], are observed. Our results are compared with other existing works in the literature and reliable agreements are found.
Improving Sub-Pixel Estimation of Laser Stripe Reflection Center by Autoconvolution on FPGA
Authors: Marković Bogdan R. , Ćertić Jelena D.
Published: September 2021

Modern laser scanners perform high-speed real-time image processing algorithms while operating in harsh industrial environments. Their performance goal is to extract the central position of the laser line reflection with Gaussian distribution. Traditional algorithms for sub-pixel estimation, such as the Center of Gravity (CG) or Parabolic Fit (PF), show poor performances under low SNR or if the pixels are saturated. Data pre-processing usually has a key role in suppressing the effects of various noise sources and dynamic environment, especially when the images are overexposed and the top of Gaussian pulse is flattened. Both in simulation and in experiment, this study explains a method that improves the accuracy of estimation of the laser stripe reflection center, by using an autoconvolution for extending the bit-width of pixel intensity. Autoconvolution of the image line is an efficient real-time pre-processing filtering method for improving the accuracy of CG calculation. The proposed algorithm is implemented on Field-Programmable Gate Arrays (FPGAs) and experimentally validated at real operational environment. It is shown that this method can reduce the error of CG laser reflection center estimation for more than one pixel in size when the image is highly affected by external noise sources and ambient light.
EVALUATION OF THE EFFECTS OF DRILLING PARAMETERS, TOOL GEOMETRY AND CORE MATERIAL THICKNESS ON THRUST FORCE AND DELAMINATION IN THE DRILLING OF SANDWICH COMPOSITES
Authors: EKİCİ ERGÜN , UZUN GÜLTEKİN , ALTAŞ SEDAT
Published: September 2021

This study examined the effects of drilling parameters, tool geometry, and core material thickness (CMT) on thrust force and the delamination factor in the drilling of sandwich composites. Aluminum honeycomb (10 and 15[Formula: see text]mm in thickness) was used as the core material, with carbon fiber-reinforced polymer (CFRP) as the top and bottom surfaces. In the drilling experiments, three different cutting speeds (60, 78 and 100[Formula: see text]m/min) and two different feed rates (0.05 and 0.075[Formula: see text]mm/rev) were used. Drills having a diameter of 6.35[Formula: see text]mm and three different geometries (candlestick drills, twist drills and dagger drills) were used in the experiments. At the end of the experiments, thrust force was seen to increase with increased feed rate and CMT. Increased cutting speed generally decreased the thrust forces and the minimum thrust force was achieved with the 10 mm thick core material, 0.05[Formula: see text]mm/rev feed rate and 100[Formula: see text]m/min cutting speed using the dagger drill. The delamination factor at the entrance area was very low when drilling the sandwich composites and there was no significant difference based on drilling parameters, tool geometry, or CMT. Tool geometry was the main effective factor on exit delamination, and the highest delamination occurred with the use of the candlestick drill. Although increased feed rate increased delamination with all tools, with the dagger drill, increased cutting speed led to a severe increase. Delamination, tearing, and uncut fiber formation were observed when images of the exit areas of the drilled holes were examined.
Strong and uniform boundedness of groups
Authors: Kędra Jarek , Libman Assaf , Martin Ben
Published: September 2021

A group [Formula: see text] is called bounded if every conjugation-invariant norm on [Formula: see text] has finite diameter. We introduce various strengthenings of this property and investigate them in several classes of groups including semisimple Lie groups, arithmetic groups and linear algebraic groups. We provide applications to Hamiltonian dynamics.
Combination of multi-focus Raman spectroscopy and compressive sensing for parallel monitoring of single-cell dynamics
Authors: Li Zhenzhen , Zhang Xiujuan , Xiao Chengui , Chen Da , Huang Shushi , Zhang Pengfei , Wang Guiwen
Published: September 2021

To overcome the low efficiency of conventional confocal Raman spectroscopy, many efforts have been devoted to parallelizing the Raman excitation and acquisition, in which the scattering from multiple foci is projected onto different locations on a spectrometer’s CCD, along either its vertical, horizontal dimension, or even both. While the latter projection scheme relieves the limitation on the row numbers of the CCD, the spectra of multiple foci are recorded in one spectral channel, resulting in spectral overlapping. Here, we developed a method under a compressive sensing framework to demultiplex the superimposed spectra of multiple cells during their dynamic processes. Unlike the previous methods which ignore the information connection between the spectra of the cells recorded at different time, the proposed method utilizes a prior that a cell’s spectra acquired at different time have the same sparsity structure in their principal components. Rather than independently demultiplexing the mixed spectra at the individual time intervals, the method demultiplexes the whole spectral sequence acquired continuously during the dynamic process. By penalizing the sparsity combined from all time intervals, the collaborative optimization of the inversion problem gave more accurate recovery results. The performances of the method were substantiated by a 1D Raman tweezers array, which monitored the germination of multiple bacterial spores. The method can be extended to the monitoring of many living cells randomly scattering on a coverslip, and has a potential to improve the throughput by a few orders.
Asset Prices and Pandemics: The Effects of Lockdowns
Authors: Detemple Jerome
Published: September 2021

We examine the impact of pandemics on equilibrium in an integrated epidemic-economy model with production. Two types of technologies are considered: a neo-classical technology and one capturing the notion of time-to-produce. The impact of a shelter-in-place policy with and without layoffs is studied. The paper documents adjustments in interest rate, market price of risk, stock market and real wage as the epidemic propagates. It shows the qualitative effects of a shelter-in-place policy in the model are consistent with the patterns displayed by the stock market and real wage during the COVID-19 outbreak. Puzzles emerging from the analysis are outlined.
Efficacy and Safety of Endoscopic Esophageal Dilatation in Pediatric Patients with Esophageal Strictures
Authors: Isa Hasan M. A. , Hasan Khadija A. , Ahmed Husain Y. , Mohamed Afaf M.
Published: September 2021

Background and Objectives. Benign strictures are the main cause of esophageal strictures in children. They can be managed by different modalities but endoscopic dilatation is the standard therapy. This study is aimed at reviewing the efficacy and safety of endoscopic dilatations in children with esophageal strictures. Materials and Methods. In this retrospective cross-sectional single center study, records of patients with esophageal strictures presented to the pediatric department, Salmaniya Medical Complex, Bahrain, in the period between 1995 and 2019 were reviewed. Demographic data, indications of endoscopic dilatations, the procedure success rate, and possible complications were assessed. Results. Forty-six children were found to have esophageal strictures. Twenty-five (54.3%) patients were males. Most patients presented during infancy (86.5%, 32/37 patients). Twenty-six (56.5%) patients required 88 dilatation sessions, while the remaining 20 (43.5%) patients did not require dilatations. The median number of dilatation sessions per patient was three (interquartile

range
=
2

–5). Savary-Gilliard bougienages were the main dilators used (80.8%, 21/26 patients). Anastomotic stricture (post esophageal atresia/tracheoesophageal fistula repair) was the main cause of esophageal strictures and was found in 35 (76.1%) patients. Patients with nonanastomotic strictures had more frequent dilatations compared to those with anastomotic strictures (

P
=
0.007

). The procedure success rate was 98.8%. Yet, it was operator dependent (

P
=
0.047

). Complete response to dilatation was found in 18 (69.2%) patients, satisfactory in seven (26.9%), and an inadequate response in one (3.9%). Those with satisfactory responses still require ongoing dilatations based on their symptoms and radiological and endoscopic findings. No perforation or mortality was reported. Patients with dilatations had more recurrent hospitalization (

P
<
0.0001

), more dysphagia (

P
=
0.001

), but shorter hospital stay (

P
=
0.046

) compared to those without dilatations. Surgical intervention was required in one patient with caustic strictures. The median follow-up period was six years (interquartile

range
=
2.25

–9.0). Conclusions. Endoscopic esophageal dilatation in children with esophageal strictures is effective and safe. Yet, it was operator dependent. Nonanastomotic strictures require more dilatations compared to anastomotic strictures. Findings of this study are comparable to those reported worldwide.
Feature Extraction and Recognition of Medical CT Images Based on Mumford-Shah Model
Authors: Fan Lumin , Shen Lingli , Zuo Xinghua
Published: September 2021

In this paper, we propose an improved algorithm based on the active contour model Mumford-Shah model for CT images, which is the subject of this study. After analyzing the classical Mumford-Shah model and related improvement algorithms, we found that most of the improvement algorithms start from the initialization strategy of the model and the minimum value solution of the energy generalization function, so we will also improve the classical Mumford-Shah model from these two perspectives. For the initialization strategy of the Mumford-Shah model, we propose to first reduce the dimensionality of the image data by the PCA principal component analysis method, and for the reduced image feature vector, we use

K

-means, a general clustering method, as the initial position algorithm of the segmentation curve. For the image data that have completed the above two preprocessing processes, we then use the Mumford-Shah model for image segmentation. The Mumford-Shah curve evolution model solves the image segmentation by finding the minimum of the energy generalization of its model to obtain the optimal result of image segmentation, so for solving the minimum of the Mumford-Shah model, we first optimize the discrete problem of the energy generalization of the model by the convex relaxation technique and then use the Chambolle-Pock pairwise algorithm We then use the Chambolle-Pock dual algorithm to solve the optimization problem of the model after convex relaxation and finally obtain the image segmentation results. Finally, a comparison with the existing model through many numerical experiments shows that the model proposed in this paper calculates the texture image segmentation with high accuracy and good edge retention. Although the work in this paper is aimed at two-phase image segmentation, it can be easily extended to multiphase segmentation problems.
Phyllanthus reticulatus Prevents Ethanol-Induced Gastric Ulcer via Downregulation of IL-8 and TNF-α Levels
Authors: Izhar Hafsa , Shabbir Arham , Shahzad Muhammad , Mobashar Aisha , Ahmed Syed Shoaib
Published: September 2021

The current study aimed to determine the protective effect of P. reticulatus on ethanol-induced gastric ulcer. For this purpose, thirty-six Sprague-Dawley rats were divided into six groups. The first group served as normal control, while, in other five groups, absolute ethanol was used to induce gastric ulcer. Group II served as a diseased group, while groups III, IV, and V were treated with methanol extract, ethyl acetate fraction, and n-hexane fraction, respectively, in a dose of 400 mg/kg bodyweight. Group VI was given omeprazole in a dose 20 mg/kg bodyweight. The stomachs were removed, ulcer score was evaluated, and histopathological examination of gastric lumen was conducted. Total acidity and pH values were determined in gastric juice. TNF-α and IL-8 mRNA expressions levels were determined using the reverse transcription real-time PCR method. The data indicated that P. reticulatus protected against gastric ulcer, which was evident by attenuation of ulcer score. The pretreatment with P. reticulatus raised the gastric pH and improved all evaluated histopathological parameters such as ulcer score, erosion score, hemorrhage score, fibrinoid necrosis score, inflammatory infiltrate score, and edema score. P. reticulatus significantly reduced mRNA expression levels of TNF-α and IL-8. In conclusion, P. reticulatus possess antiulcer property which might be attributed to downregulation of TNF-α and IL-8 expression levels.
[Retracted] Construction of the Reverse Resource Recovery System of e‐Waste Based on DLRNN
Authors: Li Changru
Published: September 2021

The research on the reverse resource network of e‐waste at home and abroad is still in its infancy, and most of it is only based on traditional forward logistics. Reverse resources are the process of moving goods from their typical final destination for recycling value or proper disposal. With the intensification of market competition and the strengthening of environmental protection legislation by the government, reverse resources are no longer a neglected corner in the supply chain. The DLRNN model of the e‐waste reverse resource recovery system constructed in this paper can provide an important theoretical and empirical basis for the rational utilization of waste electronic products and fully tap the potential value of waste electronic products, which is of great significance to the recycling of natural resources. In this paper, a hybrid network framework DLRNN based on deep learning (DL) and cyclic neural network (RNN) is designed for problem classification. Experimental results show that the classification accuracy of this framework is improved by 2.4% on TREC and 2.5% on MSQC without additional word vector conversion tools.
Adaptive Recognition of Motion Posture in Sports Video Based on Evolution Equation
Authors: Yuan Rui , Zhang Zhendong , Le Yanyan , Chen Enqing
Published: September 2021

In the field of sports, the formulation of existing training plans mainly relies on the manual observation and personal experience of coaches. This method is inevitably subjective. The application of artificial intelligence technology to the training of athletes to recognize athletes’ posture can help coaches assist in decision-making and greatly enhance athletes’ competitive ability. The human body movements embodied in sports are more complicated, and the accurate recognition of sports postures plays an active and important role in sports competitions and training. In this paper, inertial sensor technology is applied to attitude recognition in motion. First, in order to improve the accuracy of attitude calculation and reduce the noise interference in the preparation process, this article uses differential evolution algorithm to apply attitude calculation to realize multisensor data fusion. Secondly, a two-level neural network intelligent motion gesture recognition algorithm is proposed. The two-level neural network intelligent recognition algorithm effectively recognizes similar actions by splitting the traditional single-level neural network into two-level neural networks. Experiments show that the experimental method designed in this article for the posture in motion can obtain the motion information of the examinee in real time, realize the accurate extraction of individual motion data, and complete the recognition of the motion posture. The average accuracy rate can reach 98.85%. There is a certain practical value in gesture recognition.
[Retracted] Landscape Planning and Image Analysis Based on Multipopulation Coevolution Particle Swarm Radial Basis Function Neural Network Algorithm
Authors: Wang Yang
Published: September 2021

Urban landscape planning and design is not only closely related to people’s living environment, but also has an important impact on urban planning and development. However, there are some problems in landscape planning and design, such as excellent cases, low reuse rate of data, discrepancy between design scheme and actual situation, and serious shortage of relevant professionals. The artificial neural network can give corresponding ways to improve and solve these problems. Therefore, this paper proposes a research on garden planning and design based on multipopulation coevolution particle swarm radial basis function neural network algorithm. Based on multipopulation coevolution particle swarm radial basis function neural network algorithm, the error between the predicted evaluation value and the actual evaluation value in the simulation experiment is less than 5%, which shows good accuracy and generalization ability in performance. And in the plant configuration simulation experiment, it can effectively evaluate the urban planning and design and put forward the corresponding adjustment scheme according to the analysis results, which is more in line with the actual needs of urban planning.
Experimental Study on the Negative Skin Friction of the Pile Group Induced by Rising and Lowering the Groundwater Level
Authors: Zhang Yu , Zhou Li-Pei , Wang Ming-Yuan , Ding Xuanming , Wang Chenglong
Published: September 2021

Negative skin friction (NSF) has been one of the important factors in the design of pile foundation; especially, the influence of water level on the pile negative skin friction should be paid attention. In this paper, a series of model tests were carried out to analyze the bearing characteristic of the pile group influenced by groundwater level. The pile axial force and negative skin friction, settlement, and soil pore pressure were investigated. The results showed that both the water level rising and lowering cycle could increase the axial force of the pile along the upper part of the pile, yet reducing it along the lower part of the pile; both the axial force and the negative skin friction of the pile presented a feature of time effect; the value of negative skin friction was positively correlated with that of the pile head load, and the neutral plane ranged from 0.57 L to 0.64 L as the water level changed; the soil featured settling in layers, and the change of pore water pressure was accordant with the water level changing regulation.
Big Data‐Based Boring Indexes and Their Application during TBM Tunneling
Authors: Wang Shuangjing , Wang Yujie , Li Xu , Liu Lipeng , Xing Hai , Zhang Yunpei
Published: September 2021

Tunnel boring machine (TBM) tunneling data have been extensively collected to utilize TBM information technology by analyzing and mining the data for achieving a safe and efficient TBM tunneling. Feature extraction of big data could reduce the complexity for problems, but conventional indexes based on feature extraction, such as field penetration index (FPI), specific penetration (SP), and boreability index (BI), have some disadvantages. Thus, we present novel boring indexes derived from tunneling data in the Yinchao TBM project. Linear thrust‐penetration and torque‐penetration relationships in filtered ascending sections (p ≥ 2 mm/r) are proposed using statistical features and through physical mechanism analysis of parameters in the TBM cyclic tunneling process. Boring indexes, such as normal boring difficulty index, initial rock mass fragmentation difficulty index, and tangential boring difficulty index, are defined using the coefficients of the linear thrust‐penetration and torque‐penetration relationships. Subsequently, the defined boring indexes are verified using performance prediction of 291 cyclic tunneling processes. Finally, a preliminary application of support measure suggestions is conducted using the statistical features of boring indexes, where certain criteria are proposed and verified. The results showed that the criterion of boring indexes for support measure suggestions could achieve a reasonable confirmation, potentially providing quantitative quotas for support measure suggestions in the subsequent construction process.
Experimental Analysis of Fabricated Synthetic Midthoracic Paediatric Spine as Compared to the Porcine Spine Based on Range of Motion (ROM)
Authors: Muhayudin Nor Amalina , Basaruddin Khairul Salleh , Daud Ruslizam , McEvoy Fiona , Tansey
Published: September 2021

The present study is aimed at investigating the mechanical behaviour of fabricated synthetic midthoracic paediatric spine based on range of motion (ROM) as compared to porcine spine as the biological specimen. The main interest was to ensure that the fabricated synthetic model could mimic the biological specimen behaviour. The synthetic paediatric spine was designed as a 200% scaled-up model to fit into the Bionix Servohydraulic spine simulator. Biomechanical tests were conducted to measure the ROM and nonlinearity of sigmoidal curves at six degrees of freedom (DOF) with moments at ±4 Nm before the specimens failed. Results were compared with the porcine spine (biological specimen). The differences found between the lateral bending and axial rotation of synthetic paediatric spine as compared to the porcine spine were 18% and 3%, respectively, but was still within the range. Flexion extension of the synthetic spine is a bit stiff in comparison of porcine spine with 45% different. The ROM curves of the synthetic paediatric spine exhibited nonlinearities for all motions as the measurements of neutral zone (NZ) and elastic zone (EZ) stiffness were below “1.” Therefore, it showed that the proposed synthetic paediatric spine behaved similarly to the biological specimen, particularly on ROM.
Study on the Differential Value of Tumor Marker CA724 on Primary Gastric Cancer
Authors: Ding Jieying , Zhang Han , Wu Zixian
Published: September 2021

We investigated the diagnostic value of the tumor marker CA724 in patients with primary gastric cancer. One hundred forty-six patients with primary gastric cancer were selected as the observation group; 89 patients with gastritis treated in the same period were included in the control group 1; 91 patients with healthy physical examination during the same period were included in the control group 2. Electrochemiluminescence immunoassay was used to determine the level of carbohydrate antigen CA724 in each group; the pathological data of the observation group were consulted, and the expression level of tumor marker CA724 under different pathological conditions was analyzed; ROC curve was drawn to evaluate the diagnostic value of CA724 in gastric cancer and gastritis. The level of CA724 in primary gastric cancer patients was significantly correlated with tumor diameter, tumor stage, differentiation type, and lymph node metastasis. The ROC curve was drawn with a CA724 cutoff value of 7.94 U/Ml. The AUC value of CA724 in primary gastric cancer patients was 0.815, with a diagnostic sensitivity of 84.68% and a specificity of 71.95%. In conclusion, CA724 was highly expressed in patients with primary gastric cancer, which can achieve the diagnostic differentiation of gastric cancer and gastritis, and obtain a high diagnostic efficiency, providing a reference basis for clinical diagnosis and treatment.
Leader-Follower Multimotor Speed Coordination via Adaptive Fuzzy Multiagent Consensus Scheme
Authors: Masroor Suhaib , Peng Chen , Alkhammash Eman H.
Published: September 2021

Coordinated speed of interconnected motors has vast application in the industry. Typically, the smooth operation of the system relies on the coordinated speed of the multiple motors such as the conveyer belt system. Thus, the problem to have coordinated speed in a network-connected motor is mostly dealt with wire-connected architectures such as cross coupling. The presented study suggests a unique design to deal with the said problem by proposing a network model consisting of a DC chopper drive, termed as an ith agent of a network, while a leader-follower multiagent consensus algorithm is used, in a supervisory role, to ensure coordinated speed. Moreover, a hybrid controller (Fuzzy MRAC-RST), composed of Fuzzy logic controller, pole placement controller (F-RST), along with model reference adaptive controller (MRAC), is used to control the ith agent. The proposed hybrid controller along with MAS consensus algorithm forms an adaptive tracking performance and ensure coordinated speed. The MATLAB platform is used for simulation purpose, and the obtained results validate the design concept.
Analysis of a Coupled System of Nonlinear Fractional Langevin Equations with Certain Nonlocal and Nonseparated Boundary Conditions
Authors: Laadjal Zaid , Al-Mdallal Qasem M. , Jarad Fahd
Published: September 2021

In this article, we use some fixed point theorems to discuss the existence and uniqueness of solutions to a coupled system of a nonlinear Langevin differential equation which involves Caputo fractional derivatives of different orders and is governed by new type of nonlocal and nonseparated boundary conditions consisting of fractional integrals and derivatives. The considered boundary conditions are totally dissimilar than the ones already handled in the literature. Additionally, we modify the Adams-type predictor-corrector method by implicitly implementing the Gauss–Seidel method in order to solve some specific particular cases of the system.
[Retracted] A Comprehensive Examination of Bandgap Semiconductor Switches
Authors: Siva Subramanian S. , Saravanakumar R. , Ganthia Bibhu Prasad , Kaliappan S. , Beyan Surafel Mustefa , Mallick Maitri , Mohanty Monalisa , Pavithra G.
Published: September 2021

Improvements in the material characteristics of bandgap semiconductors allow the use of high‐temperature, high‐voltage, and fast switch rates in power devices. Another good reason for creating new Si power converter devices is that previous models perform poorly. The implementation of novel power electronic converters means high energy efficiency but a more logical use of electricity. At this moment, titanium dioxide and gallium nitride are the most prospective semiconductor materials because of their great features, established technology, and enough supply of raw components. This study is focused on providing an in‐depth look at recent developments in manufacturing Si‐C‐ and high‐powered electronic components and showcasing the whole scope of the newly developing product generation.
Feature Selection and Feature Stability Measurement Method for High‐Dimensional Small Sample Data Based on Big Data Technology
Authors: Huang Chengyuan
Published: September 2021

With the rapid development of artificial intelligence in recent years, the research on image processing, text mining, and genome informatics has gradually deepened, and the mining of large‐scale databases has begun to receive more and more attention. The objects of data mining have also become more complex, and the data dimensions of mining objects have become higher and higher. Compared with the ultra‐high data dimensions, the number of samples available for analysis is too small, resulting in the production of high‐dimensional small sample data. High‐dimensional small sample data will bring serious dimensional disasters to the mining process. Through feature selection, redundancy and noise features in high‐dimensional small sample data can be effectively eliminated, avoiding dimensional disasters and improving the actual efficiency of mining algorithms. However, the existing feature selection methods emphasize the classification or clustering performance of the feature selection results and ignore the stability of the feature selection results, which will lead to unstable feature selection results, and it is difficult to obtain real and understandable features. Based on the traditional feature selection method, this paper proposes an ensemble feature selection method, Random Bits Forest Recursive Clustering Eliminate (RBF‐RCE) feature selection method, combined with multiple sets of basic classifiers to carry out parallel learning and screen out the best feature classification results, optimizes the classification performance of traditional feature selection methods, and can also improve the stability of feature selection. Then, this paper analyzes the reasons for the instability of feature selection and introduces a feature selection stability measurement method, the Intersection Measurement (IM), to evaluate whether the feature selection process is stable. The effectiveness of the proposed method is verified by experiments on several groups of high‐dimensional small sample data sets.
Hippocampus Segmentation Method Based on Subspace Patch-Sparsity Clustering in Noisy Brain MRI
Authors: Ren Xiaogang , Wu Yue , Cao Zhiying
Published: September 2021

Since the hippocampus is of small size, low contrast, and irregular shape, a novel hippocampus segmentation method based on subspace patch-sparsity clustering in brain MRI is proposed to improve the segmentation accuracy, which requires that the representation coefficients in different subspaces should be as sparse as possible, while the representation coefficients in the same subspace should be as average as possible. By restraining the coefficient matrix with the patch-sparse constraint, the coefficient matrix contains a patch-sparse structure, which is helpful to the hippocampus segmentation. The experimental results show that our proposed method is effective in the noisy brain MRI data, which can well deal with hippocampus segmentation problem.
Using Wireless Sensor Network to Remote Real‐Time Monitoring and Tracking of Logistics Status Based on Difference Transmission Algorithm
Authors: Wu Jiang , Ding Xuefeng
Published: September 2021

This paper proposes a logistics tracking information management system based on a wireless sensor network, using wireless sensor nodes to track and manage logistics tracking information, and designs a networked logistics tracking information management system to achieve remote real‐time management of logistics tracking information. The research work in this paper can mention the real‐time and accuracy of logistics tracking information management, which has significant guiding significance to the information security of the logistics industry. This paper first analyzes the business process of logistics enterprises, obtains the demand analysis of logistics tracking management system, divides the whole logistics tracking management system into several functional modules according to the logistics business process of enterprises, analyzes and designs these system functional modules, and gives the model of system functions. After analyzing and designing the system, for the data processing problem in the wireless sensor network, the difference transmission algorithm based on the mean expectation is proposed, which calculates the mean value as the expected value under the specific data model. Then, the data of the difference between the collected value and the expected value is transmitted to reduce the amount of data sent by the nodes, reduce energy consumption, extend the network life cycle, and ensure the stability of the logistics tracking information system. The purpose is to reduce the amount of data sent by nodes, reduce energy consumption, extend the network life cycle, and ensure the stable operation of the logistics tracking information system. In this paper, we describe the logistics tracking system based on a wireless sensor network, which has not only features such as sharing and flexibility but also has high fault tolerance. The system is designed for functional modules such as procurement management, inventory management, and sales management. The JAVA technology platform is selected for design and development, and the SQL Server database is selected for the backend of the system, and a simple and easy‐to‐use WEB interface for the user service side of the system is designed to meet the needs of a user‐friendly environment. The implementation of the system also makes some theoretical and practical contributions to the design and development of similar logistics tracking information management systems based on wireless sensor networks.
The Evaluation Model of College Students’ Mental Health in the Environment of Independent Entrepreneurship Using Neural Network Technology
Authors: Meng Xiangmin , Zhang Jie , Ren Guoyan
Published: September 2021

In recent years, the employment of college students is becoming more and more prominent; no matter for the society, universities, college students themselves, and their families have formed a huge pressure, in the current situation, the success rate of college students to start their own business is not high; one of the important reasons is that college students generally have defects in entrepreneurial psychology. Therefore, effective evaluation of college students’ mental health under the environment of independent entrepreneurship is conducive to comprehensively improving the quality of talent training in colleges and universities. In this paper, we propose a novel three-channel multifeature fusion network based on neural network technology to identify and predict college students’ mental health problems in the self-entrepreneurship environment. Specifically, we first extract the behavior characteristics, visual characteristics, and social relations as a three-channel network input. Second, in view of the behavior characteristic, we use the length of the memory deep context dependent on network access. In view of visual features, we use the convolution neural network to face emotional characteristics and characteristics of social relations. The feature concat strategy is used for feature fusion. The experimental results on real datasets show that the method in this paper is effective, and it is expected to propose a new solution for college students’ mental health assessment.
A Class of Nonlinear Nonglobal Semi-Jordan Triple Derivable Mappings on Triangular Algebras
Authors: Fei Xiuhai , Zhang Haifang
Published: September 2021

In this paper, we proved that each nonlinear nonglobal semi-Jordan triple derivable mapping on a 2-torsion free triangular algebra is an additive derivation. As its application, we get the similar conclusion on a nest algebra or a 2-torsion free block upper triangular matrix algebra, respectively.
Whole‐Exome Sequencing Identified a Novel Homozygous Frameshift Mutation of HPS3 in a Consanguineous Family with Hermansky‐Pudlak Syndrome
Authors: Wang Zhao-Xia , Liu Yi-Hui , Dong Yi , Li Ya-Li , Tang Tie-Yu , Fan Liang-Liang
Published: September 2021

Hermansky‐Pudlak syndrome (HPS) is a rare genetic disorder with an autosomal recessive inherited pattern. It is mainly characterized by deficiencies in lysosome‐related organelles, such as melanosomes and platelet‐dense granules, and leads to albinism, visual impairment, nystagmus, and bleeding diathesis. A small number of patients will present with granulomatous colitis or fatal pulmonary fibrosis. At present, mutations in ten known genetic loci (HPS1–11) have been identified to be the genetic cause of HPS. In this study, we enrolled a consanguineous family who presented with typical HPS phenotypes, such as albinism, visual impairment, nystagmus, and bleeding diathesis. Whole‐exome sequencing and Sanger sequencing were applied to explore the genetic lesions of the patient. A novel homozygous frameshift mutation (NM_032383.5, c.1231dupG/p.Aps411GlyfsTer32) of HPS3 was identified and cosegregated in the family members. Furthermore, real‐time PCR confirmed that the mutation decreased the expression of HPS3, which has been identified as the disease‐causing gene of HPS type 3. According to ACMG guidelines, the novel mutation, resulting in a premature stop codon at amino acid 442, is a pathogenic variant. In summary, we identified a novel mutation (NM_032383.5, c.1231dupG/p.Aps411GlyfsTer32) of HPS3 in a family with HPS. Our study expanded the variant spectrum of the HPS3 gene and contributed to genetic counseling and prenatal genetic diagnosis of the family.
Primary Ovarian Choriocarcinoma: Rare Entity
Authors: Adow Mequanent Tariku , Gebresilasie Shimelis Fantu , Abebe Natnael Alemayehu
Published: September 2021

Background. Primary pure ovarian choriocarcinoma is a rare aggressive tumor which can be nongestational arising from germ cells or gestational origin. Preoperative diagnosis of extrauterine choriocarcinoma is challenging due to nonspecific clinical presentation. Case Presentation. This article reports primary ovarian choriocarcinoma, likely gestational in a 25-year-old para 2 woman presenting with lower abdominal pain and swelling of two-week duration. Diagnosis was suspected by serum beta-human chorionic gonadotropin and confirmed histologically after surgery. Postoperatively, she was managed with multiple courses of chemotherapy using a bleomycin, etoposide, and cisplatin regimen, and the treatment was effective. Conclusion. In patients with adnexal mass presenting with nonspecific symptoms especially with high Doppler blood flow of the mass on ultrasound evaluation, serum beta-human chorionic gonadotropin determination is recommended before laparotomy. In setups where the genomic test is not available, histological and clinical effort to differentiate gestational versus nongestational choriocarcinoma is useful for specific management decision.
Does Emotional Intelligence of Dental Undergraduates Influence Their Patient Satisfaction?
Authors: Mohan Mandakini , Lin Kah Heng , Parolia Abhishek , Pau Allan
Published: September 2021

Objectives. The research aimed to investigate if emotional intelligence (EI) scores of dental undergraduates influenced their patients’ satisfaction with the treatment received. Methods. A 33-item EI questionnaire was completed by 46 dental undergraduates in a cross-sectional study. Responses, measured on a five-point Likert scale, were summed to yield EI scores. Patients treated by the same undergraduates were invited to complete a patient satisfaction (PS) questionnaire. EI and PS scores were calculated and compared by undergraduates’ gender and the patients’ age and education status. The four EI factors (optimism/mood regulation, appraisal of emotions, utilization of emotions, and social skills of students) were correlated with PS using Spearman’s correlation test with a significance level set at

p
<
0.05

. Results. EI scores did not differ significantly between male (N = 23) and female (N = 23) undergraduates

p
=
0.218

. PS was not associated with patients’ gender, but those educated to the secondary school level were more likely to be satisfied compared to those educated to the college/university level

p
=
0.022

. Of the four EI factors, optimism/mood regulation was positively correlated with PS

p
=
0.049

. Conclusion. The results of the study suggest that the EI of the students can influence PS. Practical Implications. Interventions to enhance EI can be developed to improve the patient experience.
Mutation in the SLC2A9 Gene: A New Family with Familial Renal Hypouricemia Type 2
Authors: Maalouli Christian , Dahan Karin , Devresse Arnaud , Gillion Valentine
Published: September 2021

Familial renal hypouricemia is a rare genetic disorder characterized by a defect in renal tubular urate reabsorption. Some patients present with exercise-induced acute kidney injury and nephrolithiasis. Type II is caused by mutations in the SLC2A9 gene. Here, we report the case of a young patient who developed acute kidney injury after exercise secondary to familial renal hypouricemia type II. The same mutation was found in other asymptomatic members of his family. We review the medical literature on this condition. This case highlights the importance of considering uric acid disorders in the work-up of acute kidney injury after exercise.
Open Platform for Intelligent R&D and Technology Innovation Management Service Based on Edge Computing
Authors: Xie Bing
Published: September 2021

The rapid development of mobile Internet and Internet of Things makes the future network face higher speed, lower delay, and higher reliability. Because this edge computing becomes the most likely network architecture to realize the vision of intelligent R&D and technological innovation, it has attracted wide attention. Edge computing can meet the high computing needs of mobile devices with limited resources by using computing‐intensive tasks from the mobile device open platform to nearby edge computing servers. This paper mainly studies the open platform of intelligent R&D and technology innovation management service based on edge computing, which can study the characteristics of edge computing more. The characteristics of edge computing will have a certain impact on the open platform strategy. This paper mainly uses the edge computing algorithm, model, edge computing time‐to‐time optimization open platform policy, platform function investigation experiment, platform module analysis, and other methods to study the open platform of intelligent R&D and technology innovation management service based on edge computing. This can better meet the actual application and improve the effect of the open platform which can better meet the different needs of the open platform. The results show that the number of users in the useful task open platform increases by 27.4% in the open platform of intelligent R&D and technology innovation management services based on edge computing. The platform can also meet the simulation of different scenes well, and the edge algorithm has some advantages in comparison with other algorithms.
Early Failure of Total Ankle Arthroplasty in a Patient with Ipsilateral Varus Knee Deformity
Authors: Kim Taehyeon , Lee Su Chan , Nam Chang Hyun , Ryu Suengryol , Ahn Hye Sun , Baek Ji-Hoon
Published: September 2021

Multiple risk factors such as age, body mass index (BMI), preoperative diagnosis, smoking, diabetes mellitus, malalignment of an implant, and presence of ipsilateral hindfoot fusion have been shown to contribute to failure of total ankle arthroplasty (TAA). However, the exact causes of TAA failure remain uncertain, and various causes can lead to a need for revision surgery. We report a case of early aseptic loosening of the implant following TAA in a patient with severe varus deformity of the ipsilateral knee.
Determination of Carrageenan in Livestock and Poultry Meat by Ultrahigh-Performance Liquid Chromatography-Tandem Mass Spectrometry
Authors: Sun Yanqin , Zhu Xudong , Shen Xixi , Wang Wei
Published: September 2021

Ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) has become the main method for the detection and analysis of food additives because of its good separation, high selectivity, and high sensitivity. The aim of this study was to establish an UHPLC-MS/MS method that can quickly and accurately measure the content of carrageenan in livestock and poultry meat. Chromatographic separation was performed on an ACQUITY UPLC BEH HILIC C18 column (2.1 mm × 50 mm, 1.7 μm) using a gradient elution with methanol and 0.1% (v/v) formic acid in water as a mobile phase. The quantitative analysis was executed using a triple quadrupole mass spectrometer in which electrospray ionization, multiple reaction monitoring, and negative mode were operated. The retention time was about 1.3 min for carrageenan. The carrageenan content showed a good linear relationship from 0.05 to 1.00 g/kg. The limit of detection (LOD) was 0.06 g/kg, and the limit of quantification (LOQ) was 0.18 g/kg. The standards were spiked at three levels (low, medium, and high) and were analyzed in six replicates. The recovery values of carrageenan in pork, beef, lamb, chicken, and duck meat were 82.06–111.55%, 85.43–112.50%, 89.55–116.00%, 83.80–102.15%, and 82.41–110.90%, respectively. The relative standard deviations (RSDs) were all lower than 7.51%. The developed method shows a high recovery rate and good precision and can be used for the rapid detection of carrageenan in livestock and poultry meat.