bluuebunny/crossref_metadata_2025 huggingface dataset:
Wavelet Transform-Based 3D Landscape Design and Optimization for Digital Cities
Authors: Chen Yang , Wang Xiaolin , Zhang Chang
Published: September 2022

As a hot concept, the digital city has developed rapidly in recent years. The digital city uses information technology to realize all the contents of the past, present, and future of the city on the network, and can build a three-dimensional visual landscape. However, the traditional information fusion model has the problems of noise susceptibility and low efficiency in landscape design. In order to solve the above problems, this article proposes a wavelet transform-based 3D landscape design and optimization method for digital cities, which removes the noise influenced by wavelet change and builds an information fusion model based on neural network to complete the design optimization of the three-dimensional landscape of the digital city. Firstly, for the wavelet change denoising problem, an effective denoising algorithm for natural noise and abnormal noise is proposed by combining convolutional neural network and wavelet transform. The algorithm extracts mixed feature information of local long path and local short path based on the information retention module, and decomposes the information by combining wavelet transform, inputs the different components obtained from the decomposition into the network for training, and removes the noise by subsequent feature screening of the network structure. Then, aiming at the optimization of 3D landscape design, an information fusion model based on long-short time memory network and radial basis backpropagation network is proposed for fusing multiple sources of information in the digital city to evaluate the landscape. The method collects digital city feature information at the information layer and preprocesses the feature information by a rate detection algorithm. Then, LSTM and RBF-BP neural networks in deep learning are used in the feature layer for adaptive learning of multiple feature signals, and finally, fuzzy logic is used to control the system decision output to improve the efficiency of 3D landscape design. Finally, the simulation experimental results show that the proposed denoising method in this article can better retain the texture details in the images and the denoised images have better visual effects; the proposed information fusion model has higher accuracy compared with the traditional methods. Combining this method to design and optimize 3D landscapes in digital cities can improve the efficiency of landscape design.
[Retracted] Impact of Alendronate Sodium plus Elcatonin on Postoperative Bone Pain in Patients with Osteoporotic Fractures
Authors: Wang Baohui , Sun Yindi , Shi Da , Han Xiuwei , Liu Na , Wang Bo
Published: September 2022

Objective. This research aims to investigate and analyze the impact of alendronate sodium (ALN) plus elcatonin (EC) in treating postoperative bone pain (BP) in patients with osteoporotic fractures (OPFs). Methods. One hundred and thirty‐eight cases of OPFs admitted between July 2018 and July 2021 were selected, of which 68 cases receiving ALN were set as the control group and 70 cases receiving ALN plus EC were set as the research group. Intercomparisons were performed in terms of BP, curative effect, complication rate, and serum bone metabolism indexes such as bone Gla protein (BGP), parathyroid hormone (PTH), and bone alkaline phosphatase (BALP). Results. Better postoperative BP relief, higher overall response rate, and lower complication rate were identified in the research group versus the control group. On the other hand, the research group presented with increased BGP and BALP after treatment, higher than those in the control group, while the posttreament PTH decreased obviously and was lower versus the control group.Conclusions. For OPF patients, ALN plus EC contributes to significantly reduced postoperative BP, improved clinical efficacy, higher treatment safety, and better bone metabolism, which has high clinical application value.
Special Physical Characteristic and Training Strategy of Badminton Based on Machine Learning Algorithm
Authors: Guan Xiangwei , Li Yang , Bai Yinhui
Published: September 2022

Machine learning algorithms involve many fields such as statistics and probability theory. It is mainly aimed at computer simulation or execution of human learning behaviors to acquire new knowledge and skills. And the existing knowledge is to be integrated and then continue to be improved. This study aims to introduce a machine learning algorithm to establish a corresponding training effect evaluation model, to use the model to research and analyze the special physical fitness training strategy of badminton, and to discuss the appropriate badminton physical fitness training method. At the same time, the Markov model is used to compare the effect of the machine learning algorithm model. The experimental results show that the combination of four kinds of training of phosphate energy supply capacity, speed, sensitivity, and core strength can improve the training performance of badminton players by 10 points and the training efficiency by 4%. Therefore, it is necessary to comprehensively and reasonably arrange the four physical training methods to achieve better training effects. The average evaluation and prediction accuracies of the machine learning algorithm model were 86% and 87%, respectively, and the computing time was 26.7 ms and 13.6 ms. The average evaluation and prediction accuracies of the Markov model were 79% and 82%, respectively, and the computing time was 19.5 ms and 11.8 ms. It can be seen that the model based on the machine learning algorithm is more accurate than the Markov model.
An Approach to Processing More Bioavailable Chickpea Milk by Combining Enzymolysis and Probiotics Fermentation
Authors: Zhang Xue , Liu Shuangbo , Xie Bijun , Sun Zhida
Published: September 2022

This research aimed to investigate an approach to processing more bioavailable chickpea milk by combining enzymolysis and probiotic bacterial fermentation. The regression model of three factors was established using Box–Behnken design (BBD), and the optimum technology of enzymolysis of isoflavone in specimens was determined. Moreover, the variations in isoflavone concentrations in chickpea milk processed with different enzymolysis conditions were explored during fermentation. The isoflavone content was the highest (246.18 mg/kg) when the doses of papain, α-amylase, and β-glucosidase were 75.0 U/g protein, 69.0 U/g starch, and 11.0 U/g chickpea flour. In addition, the contents of isoflavone glucosides decreased and aglycones increased with the prolongation of fermentation. Compared with group C0 (unhydrolyzed specimens), the isoflavone aglycone contents in groups treated with enzymolysis increased to varying degree. Particularly, the isoflavone aglycone contents in group C6 (hydrolyzed with three compound enzymes) were the highest after 24 h fermentation, reaching 56.93 ± 1.61 mg/kg (genistein), 92.37 ± 3.21 mg/kg (formononetin), and 246.18 ± 2.98 mg/kg (biochanin A). The data above indicated that compound enzymolysis coupled probiotic bacterial fermentation could promote the biotransformation of chickpea isoflavone glucosides into aglycones, which might be used as an effective approach to enhance the bioactivity and nutraceutical properties of chickpea milk.
Application of Multi-Measurement Vector Based on the Wireless Sensor Network in Mechanical Fault Diagnosis
Authors: Kang Wei
Published: September 2022

In order to solve the problem of low positioning accuracy of mechanical fault diagnosis, a polarization GPR imaging reconstruction algorithm based on the MMV model was proposed. The algorithm was mainly based on the joint processing of the measured data of multiple polarization channels to achieve the reconstruction of the reflectance of the detection scene corresponding to each polarization channel. The simulation data processing results based on FDTD showed that compared with the traditional SMV model polarization imaging algorithm, the proposed imaging algorithm could improve the accuracy of target location reconstruction and the ability of background clutter suppression significantly. Compared with the SMV model, TCR obtained by the MMV model increased by 30%. As for the imaging results at different noise ratios, TCR obtained by the MMV model was 10% higher than that obtained by the SMV model. And when the ratio of available real data samples decreased to 25%, the sample data generation based on the adversarial generation network could greatly improve the classification accuracy of the fault diagnosis model. It could realize the detection of the target better, so as to locate faults accurately.
Research on Collaborative Innovation of Supply-Side Reform of University Ideological and Political Education Based on Intelligent Big Data Information Fusion
Authors: Li Xiaomin , Li Ziyue , Xia Xuecang
Published: September 2022

The times are changing with each passing day, and the traditional ideological and political education cannot adapt to the information age. Schools overemphasize theory, weaken the implementation of practice, ignore the needs of students, and lack electronic equipment to assist learning. All these factors make ideological and political education in colleges and universities stay in a superficial form and do not really lead students to study deeply. Innovation introduces supply-side vision, reforms educational theory structurally, and accelerates the transformation of classroom style. Let teachers and students leave the shackles of the classroom, learn from various sources of knowledge, and carry out personalized learning from their own areas of interest. The results show that (1) after data fusion, the credibility of ideological and political knowledge is 91%, which is better than other methods. (2) The knowledge base constructed by the laboratory meets the standards of colleges and universities, and its quality passes the standard, but its timeliness is slightly poor, and the test result is about 85%. (3) Learning interest model can push personalized knowledge according to students’ characteristics. (4) In the actual scene, students’ ideological and political education shows a benign development trend. The results of this study are quite satisfactory, which verifies the practicability and effectiveness of the proposed method and obtains feasible results.
A Classification Technique for English Teaching Resources and Merging Using Swarm Intelligence Algorithm
Authors: Yang Yan , Huang Huaye
Published: September 2022

The evolution of social education has necessitated the optimization of various teaching approaches, and the classification of English teaching resources is one of the crucial factors. With the development of electronic computers and Big Data technologies, the classification of teaching resources that could not be realized before has become possible now. However, the traditional classification methods cannot meet the requirements of modern computing due to the limitations of implementation. The emergence of swarm intelligence algorithms makes the classification of teaching resources possible. Swarm intelligence algorithm is a swarm-based multipoint random search algorithm, which includes evolutionary algorithm, immune algorithm, particle swarm procedure (PSO), ant colony process, artificial fish swarm mechanism, and other typical intelligent techniques. The swarm intelligence algorithm has strong robustness and strong global and local search capabilities, as well as, implicit parallelism. Furthermore, it has no special requirements for objective functions and constraint functions. It has the function of “black box” and can overcome problems where traditional optimization methods are insufficient. The swarm intelligence algorithm has a large space for development and rich forms of expression, and there is an essential connection between them, so that they can be well integrated. The key goal of this study is to implement the swarm intelligence algorithm to the task of classifying English teaching resources and to provide a reference for optimizing the English teaching model. The experimental findings demonstrate that the suggested classification model for English teaching resources has excellent performance, is favorable to enhancing the utilization rate of teaching resources, and is applicable to other disciplines.
An Information-Entropy-Based Hierarchical Serialization Allocation Method for UAV Tracking in 6G Networks
Authors: Zhong Yuhao , Yang Zhihao , Li Ting , Zhang Yuting
Published: September 2022

Unmanned aerial vehicles (UAVs) play an important role in future 6G networks, which can be used to assist cellular networks in setting up temporary networks to provide communication services when network access demand is intense. It is critical to design a UAV tracking method with high efficiency and high precision under active sensor radiation control to build a reliable network of UAVs. Multisensor cooperative multitarget tracking for UAVs with high accuracy is an alternative solution to meet the performance requirements of 6G. In this paper, an information-entropy-based multisensor to multitarget allocation method under low-radiation control is proposed for UAV tracking. Specifically, the knowledge-map-based demand assessment of integrated track detection is first present; and then, fuzzy-decision-tree-based generation of sensor management plan is given; the next, the basic linear programming model for multitarget to multi-UAV allocation is utilized based on cooperative tracking under radiation control; finally, extensive experiments are conduct, and the experimental results show that the proposed method has a good performance.
Renal Histologic Findings in Necropsies of Type 2 Diabetes Mellitus Patients
Authors: D’Marco Luis , Puchades María Jesús , Escudero-Saiz Victor , Giménez-Civera Elena , Terradez Liria , Moscardó Anais , Carbonell-Asins Juan Antonio , Pérez-Bernat Elisa , Torregrosa Isidro , Moncho Francesc , Navarro Jorge , Górriz José Luis
Published: September 2022

Background. Very few studies have analyzed early histologic lesions of diabetic nephropathy (DN) in patients without signs of clinical involvement (microalbuminuria). In this study, we analyzed renal histologic lesions in necropsies of diabetic patients with or without previous signs of DN. Methods. Histological material was analyzed from 21 autopsies of type 2 diabetes mellitus (T2DM) patients (9 with albuminuria and 12 without albuminuria) and 4 controls. Histologic lesions were evaluated according to the Tervaert classification. Results. Kidneys of diabetic patients presented significantly higher scores in most histologic indices analyzed (glomerular basal membrane thickening, mild and severe mesangial expansion, nodular sclerosis, interstitial fibrosis, and tubular atrophy) than in nondiabetic controls (

p
<
0.01

in all cases). In contrast, no significant differences were detected between histologic scores when comparing the 21 diabetic patients with and without albuminuria. A significant percentage of cases without albuminuria showed moderate to severe histologic lesions, particularly severe mesangial expansion and severe glomerular vascular lesions. No significant differences were found in age, blood pressure, diabetes vintage, BMI, HbA1c, cholesterol, triglycerides, or treatments between the two (albuminuric vs. nonalbuminuric) T2DM patient groups. Conclusions. Our data suggest that histologic lesions of DN are present in the early stages of the disease, even without albuminuria presence. More precise and earlier metabolic control is recommended in T2DM, and monitoring of risk factors can play a role in DN development.
Seasonal Dynamics of Sand Flies (Diptera, Pshycodidae), Vectors of Cutaneous Leishmaniasis, in the City of Fez, Northern Morocco
Authors: Darkaoui Najoua , Janati Idrissi Abdellatif , Talbi Fatima Zahra , El Fattouhi Youness , El Omari Hajar , Najy Mohamed , Taam Abdelkarim , Alami Abdellatif , El-Akhal Fouad , El Ouali Lalami Abdelhakim
Published: September 2022

The infections transmitted by sand flies (Diptera, Psychodidae) pose always a real health problem due to the increasing number of cases detected each year and the annual emergence of new leishmaniasis outbreaks. This study evaluated the temporal evolution of six species of sand flies in five stations inventoried between May 2017 and April 2018, in order to determine for the first time the extent of cutaneous leishmaniasis (CL) transmission in the city of Fez. The monthly impact of Fez sand fly density has been studied using all multivariate statistical analyses, including multiple factor correspondence analysis (MCA), which were performed using XLSTAT and the version of SPSS 20.0 test. Differences between concentrations were considered significant if

P
<
0.05

. To better study the results obtained, different ecological indices have been studied. This study showed that these vectors developed in different sectors of the city of Fez. A total of 816 sand flies were collected from five stations in the city, belonging to three species of the genus Phlebotomus (46.82%) and three species of the genus Sergentomyia (53.18%). The seasonal fluctuation of the average density followed a bimodal evolution for the three stations Dhar Richa, Ain Nokbi, and Boujloud. The stations of Ain Nokbi (0.87 ph/m2) and Dhar Richa (0.467 ph/m2) exposed the sites to a high average density with a maximum peak during August (1.965 ph/m2) and July (1.87 Ph/m2), respectively. S. minuta (44.24%), Ph. sergenti (26.96%), Ph. perniciosus (10.78%), and Ph. papatasi (9.07%) were the most qualified species. The calculated P value is above the 5% significance level, so the relative abundance of these species between study sites shows no significant difference. The period of phlebotomy activity of the genus Phlebotomus in Fez lasts seven months from May to November with a bimodal or trimodal evolution and varies according to the species or the surveyed station. The seasonal fluctuation of sand flies could be conditioned by climatic factors where the period of activity of the species coincides with the hot months (May, June, July, and August). We have observed that the temperature factor favors the prevalence of sand flies, while the difference in the relative abundance of species between the sites is related to the difference in the bioecological conditions of each site.
A Novel Noise Suppression and Artifact Removal Method of Mechanomyography Based on RLS, IGWO-VMD, and CEEMDAN
Authors: Li Zebin , Gao Lifu , Lu Wei , Wang Daqing , Cao Huibin , Zhang Gang
Published: September 2022

Mechanomyography (MMG) signals have extensive applications in muscle function assessment and human intention recognition. However, during signal acquisition, MMG signals are easily contaminated by noise and artifacts, which seriously affects the recognition of their characteristics. To address these issues, a novel noise suppression and artifact removal method based on recursive least square (RLS), improved Gray Wolf Optimizer-optimized variable mode decomposition (IGWO-VMD), and complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is proposed. In this paper, the RLS algorithm is first applied to adaptively filter out the power line interference (PLI). Then, IGWO is designed to select the appropriate VMD parameters and use the VMD to decompose the noisy signal into band-limited intrinsic mode functions (BLIMFs). In addition, the BLIMFs are classified into the low-frequency part and high-frequency part according to the given correlation coefficient (CC) threshold value. The effective components of the low-frequency part are identified by the center frequency. Meanwhile, the high-frequency part is decomposed by CEEMDAN, and its effective components are obtained according to the proposed sample entropy threshold range. Finally, the effective components of the low and high-frequency parts are reconstructed to obtain the denoised signal to realize the extraction of useful signals. Simulation experiment results demonstrate that the proposed method outperforms the classical methods and the designed IGWO-VMD method in terms of denoising performance. The effectiveness of the proposed method is verified through the measured MMG signal experiments. The proposed method not only effectively suppresses noise and artifacts but also overcomes the limitations of VMD and CCEMDAN.
A Personalized Recommendation System for English Teaching Resources Based on Learning Behavior Detection
Authors: Yuanfei Zhang
Published: September 2022

When confronted with a plethora of resources, many students struggle to quickly filter out the content that is relevant to them. Because there are many English teaching resources and it is difficult to accurately recommend suitable teaching resources for students. Therefore, in this paper we suggest a personalized recommendation system for English teaching resources, which is founded on learning behavior detection. To begin with, a spatiotemporal convolutional network is introduced to effectively identify students’ online classroom behavior, and a global attention module is added to increase the model’s ability to learn global feature information. Furthermore, the identified characteristics of student behavior are incorporated into the recommendation module. Similarly, the differential evolution (DE) algorithm is implemented to the smoothing factor and kernel function center of a generalized regression neural network (CRNN) for resource recommendation mode, while taking into account the strong dependence of the GRNN training effect on the smoothing factor and the kernel function center. The smoothing factor and offset factor are optimized and solved, and the optimized smoothing factor and offset factor are used to recommend GRNN resources. Experiments show that the approach described in this work first has a high precision (i.e., 90.98%) in behavior recognition, and second, the recommendation performance is superior to both of the comparison algorithms (i.e., 85.23% and 78.33%), resulting in better resource recommendation accuracy. The fundamental goal of this work is to deliver several important guidelines for the informatization and intelligence of the English educational resources and services.
Boosted Tau Lepton as a Microscope and Macroscope
Authors: Qian Sitian , Guan Zhe , Deng Sen , Song Yunxuan , Mu Tianyu , Xiao Jie , Yang Tianyi , Wang Siguang , Mao Yajun , Li Qiang , Lu Meng , You Zhengyun
Published: September 2022

Anomalies from the LHCb lepton flavour universality and Fermilab muon anomalous magnetic moment show tantalizing hints of possible new physics from the lepton sectors. Due to its large mass and shorter lifetime than muon, the tau lepton is believed to couple more to possible new physics beyond the Standard Model. Traditionally, tau leptons are probed through their decay products due to tau’s short lifetime. On the other hand, at a high energy scale, a large fraction of tau leptons could be boosted to a much longer lifetime and fly a visible distance from several centimetres up to kilometer length scale yet very informative to new physics beyond the standard model or high energy cosmic rays. In this article, we investigate rare, yet promising, tau-physics phenomena, where long-lived taus are exploited either as a microscope (for the measurement of tau’s anomalous magnetic moment to an unprecedented level of accuracy) or as a macroscope (for the detection of 1 TeV to 1 PeV cosmic neutrinos).
The Impact of Standardized Health Education in Patients with Ischemic Stroke on Patient Management Satisfaction and Quality of Clinical Management Services
Authors: Chen Jing , Xiang Lin
Published: September 2022

Aim. Ischemic stroke is a common brain disease, which seriously affects the quality of life of patients. The purpose of this study was to evaluate the impact of the application of standardized health education in ischemic stroke patients on patient management satisfaction and clinical management service quality. Methods. 220 patients with ischemic stroke were chosen for study target. The research objects were randomly divided into control group (

n
=
110

) and education group (

n
=
110

) by odd even number draw lots. The control group conducted conventional treatment; on the basis of the control group, the education group received standardized health education. The impact of the application of standardized health education in patients with ischemic stroke on patient management satisfaction and clinical management service quality was analyzed. Results. The number of health error items in the two groups decreased significantly after 2 months and 3 months of treatment, contrast to before admission, and the number of health error items in the education group was lower than that in the control group, and the difference was statistically significant. After 3 months of treatment, the daily activity score increased and the neurological function score decreased in the two groups, and the daily activity score in the education group was higher than that in the control group, and the neurological function score was lower than that in the control group; the difference was statistically significant. The satisfaction scores of patients in the education group in different aspects such as staff working attitude, health management, diet management, and environmental management were higher than those in the control group, and the disparity was obvious. Conclusion. The application of standardized health education in patients with ischemic stroke has certain clinical value.
Deformation Prediction and Analysis of Soft Rock Roadway with High Altitude and Large Buried Depth Based on Particle Swarm Optimization LSTM Model
Authors: Du Bin , Yi Huahui , Yang Fan
Published: September 2022

Deformation prediction is an important basis for roadway information construction, especially for soft rock roadway at high altitude and large buried depth, whether the deformation of roadway surrounding rock can be effectively and accurately predicted is an important basis for judging the stability of roadway surrounding rock. However, at present, the research on the informatization construction of the roadway is not in-depth, and the intelligent prediction technology for the deformation of the surrounding rock of the roadway is still in its infancy, and the accuracy of deformation prediction is also low. Therefore, based on the research of domestic and foreign researchers, in order to solve the breakthrough of related technology, this paper puts forward the deformation prediction and control technology of high altitude and deep buried soft rock roadway based on a neural network model. This method is based on the traditional prediction model and is replaced by the neural network, so as to improve the problems of low accuracy and large prediction deviation in the related deformation prediction of the traditional prediction model. At the same time, aiming at the problem of poor local weight and network search ability, an improved method using particle swarm optimization algorithm is proposed, which effectively considers the influence of local and global factors on the combined weight. Finally, the improved deformation prediction model of high altitude and deep buried soft rock roadway based on particle swarm optimization LSTM model is applied to an engineering example and compared with the traditional model to explore its feasibility and effectiveness. The results show that the prediction model has higher prediction accuracy than the traditional prediction model, and the relative deviation of the prediction results is controlled within 2%. At the same time, compared with other models (BP neural network model), it has relatively higher accuracy and stability. The research results can provide a new idea for the deformation prediction of soft rock roadway with high altitude and deep burial.
Multiparty Coordinated Logistics Distribution Route Optimization Based on Data Analysis and Intelligent Algorithm
Authors: Li Xinyu
Published: September 2022

Aiming at the shortcomings of traditional genetic algorithms such as premature and insufficient local search ability, a hybrid genetic algorithm combining

k

-means algorithm and cluster analysis to improve genetic algorithm is proposed. Among them, the selection operation adopts the tournament selection strategy of the elite retention model, the crossover operation adopts the double cut-point crossover, and the variation operator introduces the

k

-exchange variation operation to ensure the evolution of individuals from generation to generation. Through the selection, crossover, and variation operations, the objective function is minimized, the vehicle travel distance is greatly reduced, and the distribution route is optimized.
Realization of Single-Phase Grounding Fault Location and Recovery Technology in Distribution Network
Authors: Zhang Di , Tang Haiguo , Zhu Jiran , Zhou Hengyi , Zhang Zhidan , Song Xingrong
Published: September 2022

In order to locate the single-phase-to-ground fault in distribution network, a research method of single-phase-to-ground fault location and recovery technology in distribution network is proposed. According to the characteristics of single-phase-to-ground fault in distribution network, the fault characteristics of zero-sequence current and three-phase current transient records are extracted by generalized S transform of correlation coefficient, and multi-source redundant information is formed. Fuzzy C-means clustering analysis method is used to fuse multiple fault features online location strategy. The simulation results show that the fuzzy clustering based on FCM changes continuously with the accumulation of samples, and the sample center changes with the enrichment of the samples. When the arc suppression coil is grounded with different initial phase angle transition resistance and intermittent fault, the state of each measuring point can be correctly identified, and the accurate energization rate is 97%. The test results show that the system can achieve accurate positioning for all sections.
[Retracted] Analysis of the Correlation between the Level of Posttraumatic Growth and Social Support among Caregivers of Children with Acute Leukemia
Authors: Chen Qiurong , Xiao Xujia , Zhang Yaling , Lin Chao
Published: September 2022

We investigate the current situation of stress burden and quality of life of primary caregivers of children with leukemia and analyze the correlation between their stress burden and quality of life, using the phenomenological research method in qualitative research. The posttraumatic growth experiences of the parents of children with leukemia included life perceptions (appreciation of life, change in priority of important things in life, and adjustment of self to reality); personal empowerment (increased sense of self‐reliance and increased sense of self‐achievement); and improvement of interpersonal relationships (increased family harmony, valuing parent‐child bonding, benefiting from professional support from other parents and medical staff, and increased sense of empathy and altruism). The posttraumatic growth experiences of parents of children with leukemia are based on their roles (parenting) and responsibilities and can be used as an important basis for future trauma interventions, as well as an entry point for exploring the posttraumatic growth potential of parents of children with leukemia and ultimately improving the posttraumatic growth of parents of children with leukemia.
A Fusion Localization Algorithm with Adaptive Kalman Gain for Port Container Seamless Positioning
Authors: Yue Peng , Xu Yue , Xue Rui , Liang Zedong
Published: September 2022

BeiDou Navigation Satellite System (BDS) has provided high-precision, reliable positioning, navigation, and timing services anywhere in the world since the end of 2020. However, the positioning performance of BDS does not behave well like the other global navigation satellite systems (GNSS) in the transition areas indoor and outdoor, particularly in container ports, because the navigation signals are blocked and reflected by containers. In order to solve the above problem, as the pulse radio ultra-wideband (UWB) has the characteristics of high positioning accuracy, high multipath resolution, large bandwidth, and high communication rate, it is used as the Beidou auxiliary system, and the two are combined. In addition, the positioning algorithm greatly affects BDS/UWB integrated positioning performance. The single Newton iterative least square (LS) positioning algorithm does not take into account the continuity of position in time, leading to disordered positioning results and large positioning errors. For obtaining high positioning accuracy, the Kalman filter (KF) is introduced to process the output results of the LS algorithm, and a fusion localization algorithm of the Newton iterative least square and Kalman filter (LS-KF) with adaptive Kalman gain is proposed in this paper. The fusion algorithm can solve effectively the problem that the Kalman gain approaches a stable state after multiple observation epochs, resulting in a constant ratio between the predicted and the measured states. Besides, the algorithm can be used to assess the confidence of each measurement state, determine the Kalman gain adaptive adjustment factor according to the obtained confidence, and further adjust the Kalman gain through the adaptive factor. Theoretical analysis and simulation results show that the proposed algorithm can improve the overall positioning accuracy and anti-interference ability.
English Language Learning Pattern Matching Based on Distributed Reinforcement Learning
Authors: Zhao Hua
Published: September 2022

The rapid development of a new generation of information technology, the promotion of network technology, and the emergence of complex and diverse requirements for control objects make the structure of language learning models more and more distributed. Distributed learning theory emphasizes the central position of learners in the learning process and the universality of learning scenes. This paper explores the significance and value of various learning modes to improve students’ learning effect. By analyzing the research data and explaining various effective language learning models, this paper aims to establish a theoretical framework of English language learning models and explore more effective language model matching schemes. This paper analyzes the adaptive multiagent, reward function, Markov model, probability function model, etc. and conducts experiments on the basis of the designed model. The linear correlation parameters of the model and the English language pattern matching efficiency are analyzed and judged on several important indicators. Because the algorithm designed in this paper has a good effect on the control of error, the error reduction rate has reached 85.6%.
[Retracted] An Empirical Study on the Relationship between New Energy Vehicle’ Export Sophistication and Industrial Structure Upgrading in China
Authors: Cao Xuwen , Rasiah Rajah , Furuoka Fumitaka
Published: September 2022

Following decades of reducing greenhouse gas emissions in the transportation industry, most car companies will stop producing petrol cars and promote the development of new energy vehicles in the near future, even in China. This study is based on energy vehicle exports using China’s 31 provinces’ panel data from 2010 to 2020. Considering that China mainly engages in processing trade, this study analyzes the domestic energy vehicle’s export sophistication after deleting intermediate goods, measuring the relationship between export sophistication and industrial upgrading with static and dynamic panel models. Then, heterogeneity tests were deployed to examine the domestic export sophistication of three major economic belts partition. The results revealed that improving export sophistication is conducive to realizing China’s industrial upgrading. China’s new energy vehicles industry is positively affected by export sophistication, R&D, foreign direct investment, average GDP growth rate, market factors, and human resources over the long run. Regarding regional stratification, domestic export sophistication in the eastern and western regions has more significant effects on promoting industrial upgrading than in the central region. In particular, in western regions, every increase in export sophistication by one unit will bring a significant industrial upgrading effect. Given this, China’s new energy vehicles should increase export sophistication to help the country’s industrial upgrading.
Stability Analysis of Dump Slope: Taking Zijinshan Open-Pit Mine as an Example
Authors: Lin Boxuan
Published: September 2022

This paper mainly analyzes the stability of the waste dump of Zijinshan open-pit mine. ANSYS software was used to establish the numerical model of the slope of the waste dump according to the geological report and the real geographic conditions. The displacement, stress, and plastic deformation of the waste dump in X and Y directions under different number of overburden layers and different strength reduction factor were obtained, so as to obtain the safety factor of the slope stability of the waste dump and give waste dump operation measures.
On-Load Electromagnetic Compatibility Test and Simulation Closed-Loop of the Electric Drive System of New Energy Vehicles
Authors: Luo Xinwen , Liu Weize , Li Jingpu
Published: September 2022

In order to solve the problem of high-amplitude and high-frequency interference generated by the electric drive system of new energy vehicles, the author proposes a closed-loop research method for on-load electromagnetic compatibility testing and simulation for electric drive systems of new energy vehicles. The method includes EMC design of the electric drive system on-load test equipment, establishment of a conducted EMI simulation platform for the electric drive system under load conditions, and optimization of the conducted EMI performance of the electric drive system based on key parameters and PWM control. Experimental results show that if the parasitic inductance of the IGBT gate increases, the conducted emission level in the frequency range of 2∼30 MHz will increase, and there is basically no change at the low frequency, and the position of each resonance point shifts to the relatively low frequency. The experiment was replaced with the DPWM3 modulation mode, and the conducted emission amplitude was reduced by about 2 dBμV in the range of 200 kHz∼2 MHz, and there was basically no change on the whole. Conclusion. It is proved that the electromagnetic compatibility closed-loop development technology of the electric drive system of new energy vehicles under load conditions can meet the development needs of new energy vehicles in the environment where energy problems and air pollution problems are becoming more and more serious.
Symbolic Model of New Media Art Expression Based on Artificial Intelligence Big Data
Authors: Lee Duksoon
Published: September 2022

With the rapid development of China’s economy and the continuous optimization and improvement of Internet information technology, a new thing, new media, has emerged. On this basis, a kind of artistic behavior of creating, carrying, spreading, and appreciating is also called new media art. New media art has developed for a long time in foreign countries, but its development and popularization are relatively late in China, and it is still in a stage of improvement. As far as visual communication design is concerned, the emergence and development of new media have strongly promoted the development of its work and the dissemination of various works. Developing visual communication design based on new media art has become a key issue for all visual communication designers. Nowadays, deep learning is widely used in different fields in different ways, and image art representation is a hot research field in computer vision. Therefore, this paper mainly studies and analyzes the symbolism of new media art expression forms and proposes a new media art symbolism model based on artificial intelligence big data. In order to provide a method of real-time representation of art images, the deep learning method is used to model the artistic expression of images, and spatial reorganization of content features and style features is carried out. This paper designs simulation experiments to verify the effectiveness of the model, which can provide some help for the development and improvement of new media art in China. We compared the results of our model with a number of other models to test its effectiveness. We achieved a matching accuracy of 98.4% which is higher than or equal to the results of the existing models.
Prick‐by‐Prick Test with Pasteurised Cow’s Milk: A Valuable Tool in Paediatric Practice
Authors: Adomaite Ieva , Stirbiene Neringa , Marciukaitiene Vilma , Akuleviciute Laura , Gurevicius Romualdas , Petraitiene Sigita , Rudzeviciene Odilija
Published: September 2022

Background. This study assessed the utility of a prick‐by‐prick test with pasteurised cow’s milk in predicting a pasteurised cow’s milk allergy (CMA) diagnosis. Methods. This was a retrospective study of 86 paediatric patients who had undergone open pasteurised cow’s milk oral food challenges (OFCs). We evaluated the diagnostic performance of a prick‐by‐prick test with pasteurised cow’s milk in predicting a positive OFC result. We calculated the threshold values representing high test specificity and predictive probability in children aged ≤24 and >24 months. Results. A prick‐by‐prick test with pasteurised cow’s milk was a good classifier of a positive cow’s milk OFC outcome. The mean prick − by − prick test wheal diameter ≥ 3 mm yielded 100% sensitivity in both groups of children. Thresholds representing high test specificity and 95% predicted probability were 7 and 11 mm in children ≤ 24 months and 11 and 17 mm in children > 24 months of age, respectively. Conclusion. A prick‐by‐prick test with pasteurised cow’s milk is valuable in paediatric practice when diagnostic thresholds are implemented.
High Efficiency Compound Vacuum Oil Gas Separation Technology Based on Integrated Oil Filter of Ultra-High Voltage Transformer
Authors: Guan Jin , Hu Xuechao , Liu Huan , Yang Yaoguo
Published: September 2022

In order to improve the filtering effect of vacuum oil purifier, the author proposes the research and application of high-efficiency compound vacuum oil-gas separation technology based on electric ultra-high voltage transformer integrated oil purifier. The author studies under the condition of constant oil temperature and flow rate, the effect of vacuum degree on the filtering effect of transformer oil vacuum oil filter. Using the research results, a frequency conversion automatic vacuum oil filter is designed, which makes the processing process have the characteristics of simple operation, high degree of automation, and high work efficiency. The test results show that if the transformer oil processed by the variable frequency automatic vacuum oil purifier is new oil, its water content is less than 45 mg/kg and the gas content is less than 12%; when the breakdown voltage is greater than 25 kV, the transformer oil index can meet the following requirements after the equipment is filtered for one cycle: breakdown voltage ≥75 kV; water content ≤5 mg/kg; and gas content ≤0.1% (volume ratio). After one cycle (after 100 min), the variable frequency automatic (three-stage) vacuum oil filter can greatly shorten the time of transformer oil circulating and filtering. Conclusion. The designed frequency conversion automatic vacuum oil purifier is obviously better than other transformer oil vacuum oil purifiers.
A Genomically and Clinically Annotated Patient-Derived Xenograft Resource for Preclinical Research in Non–Small Cell Lung Cancer
Authors: Woo Xing Yi , Srivastava Anuj , Mack Philip C. , Graber Joel H. , Sanderson Brian J. , Lloyd Michael W. , Chen Mandy , Domanskyi Sergii , Gandour-Edwards Regina , Tsai Rebekah A. , Keck James , Cheng Mingshan , Bundy Margaret , Jocoy Emily L. , Riess Jonathan W. , Holland William , Grubb Stephen C. , Peterson James G. , Stafford Grace A. , Paisie Carolyn , Neuhauser Steven B. , Karuturi R. Krishna Murthy , George Joshy , Simons Allen K. , Chavaree Margaret , Tepper Clifford G. , Goodwin Neal , Airhart Susan D. , Lara Primo N. , Openshaw Thomas H. , Liu Edison T. , Gandara David R. , Bult Carol J.
Published: September 2022

Patient-derived xenograft (PDX) models are an effective preclinical in vivo platform for testing the efficacy of novel drugs and drug combinations for cancer therapeutics. Here we describe a repository of 79 genomically and clinically annotated lung cancer PDXs available from The Jackson Laboratory that have been extensively characterized for histopathologic features, mutational profiles, gene expression, and copy-number aberrations. Most of the PDXs are models of non–small cell lung cancer (NSCLC), including 37 lung adenocarcinoma (LUAD) and 33 lung squamous cell carcinoma (LUSC) models. Other lung cancer models in the repository include four small cell carcinomas, two large cell neuroendocrine carcinomas, two adenosquamous carcinomas, and one pleomorphic carcinoma. Models with both de novo and acquired resistance to targeted therapies with tyrosine kinase inhibitors are available in the collection. The genomic profiles of the LUAD and LUSC PDX models are consistent with those observed in patient tumors from The Cancer Genome Atlas and previously characterized gene expression-based molecular subtypes. Clinically relevant mutations identified in the original patient tumors were confirmed in engrafted PDX tumors. Treatment studies performed in a subset of the models recapitulated the responses expected on the basis of the observed genomic profiles. These models therefore serve as a valuable preclinical platform for translational cancer research.

Significance:

Patient-derived xenografts of lung cancer retain key features observed in the originating patient tumors and show expected responses to treatment with standard-of-care agents, providing experimentally tractable and reproducible models for preclinical investigations.
Heterogeneity of Subcellular Diffusion in Bacteria Based on Spatial Segregation of Ribosomes and Nucleoids
Authors: Dersch Simon , Rotter Daniel A.O. , Graumann Peter L.
Published: September 2022

It has long become clear that in spite of generally lacking internal membrane systems, bacteria contain well-structured subcellular structures of usually filamentous proteins, and a preferred 3D arrangement of their chromosome(s). Some of these systems are set up by so-called cytoskeletal elements, or by polar landmark proteins, but the mechanism of specific localization is still unclear in most cases. Intriguingly, apart from such spatially organizing systems, the bacterial cytoplasm has unusual properties in terms of the diffusion of molecules, which varies between different sites within the cell. In many bacteria, chromosomes are compacted into centrally located nucleoids, being orderly folded as opposed to consisting of random coils of DNA. In these bacteria, there is a separation of transcription and translation, such that transcription by RNA polymerase occurs on the nucleoids, and translation takes place mostly at the cell poles and directly underneath the cell membrane, because 70S ribosomes accumulate at sites surrounding the nucleoids. Interestingly, accumulation of ribosomes appears to slow down diffusion of enzymes, noticeable for larger enzyme complexes, while nucleoids provide areas of confined motion for DNA-binding proteins, yet acceleration zones for non-DNA-binding proteins. Crowded regions at the cell poles set up zones of higher concentration of the translation machinery, shortening diffusion distances for rate-limiting translation factor/ribosome interactions, and of metabolic enzymes, possibly speeding up pathways containing low concentrations of metabolites. Thus, heterogeneous diffusion adds another layer of subcellular organization on top of cytoskeletal elements.