bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploration of Landscape Lighting Design Based on Interactive Genetic Algorithm
Authors: Shi Haixiao , Zheng Jie
Published: August 2022

There are many problems in the practical application of landscape lighting design. In order to solve these problems more specifically, based on the relevant theories of interactive genetic algorithm, radial basis function and hesitation degree are introduced into genetic algorithm. Through the analysis and processing of the data to get the optimized interactive genetic algorithm, the algorithm can analyze and optimize the landscape lighting design. Based on this model, the lighting design can be predicted and analyzed, and the prediction result is relatively good. Relevant studies show that the interactive genetic algorithm can be divided into three typical change stages according to the different results of intensity calculation, of which the first stage mainly presents the trend of gradual decline. The fluctuation phenomenon is obvious in the second paragraph. The third paragraph shows a gradual increasing trend of change. The corresponding relationship between the two fitness functions is obvious. With the increase of experts in independent variables, the corresponding fitness values show a trend of gradual decline on the whole. Through the calculation and analysis of five different indicators of landscape lighting by using interactive genetic algorithm, it can be seen that electrification has a relatively small impact on landscape lighting. The results of intelligent and environmental protection calculation are relatively high, and the corresponding range of change is relatively large, which shows that these two indicators are very important for improving the lighting design level of landscape. Finally, the model is verified by comparing data and model curves. Interactive genetic algorithm is very important to improve the lighting design of landscape, and the optimization model can be widely used in other fields.
CT-IGFBP-4 as a Predictive Novel Biomarker of Ischemic Cardiovascular Events and Mortality: A Systematic Review
Authors: Bhattarai Abhinav , Singh Sunar Pritam , Shah Sangam , Chamlagain Rajan , Babu Pokhrel Nishan , Khanal Pitambar , Kumar Sah Sanjit , Poudel Sujan , Belbase Kapil , Chand Swati , Khanal Rajaram , Bhattarai Anil
Published: August 2022

Background and objective. Numerous novel biomarkers have been proposed for the early diagnosis of cardiovascular diseases. Measurement of the carboxyl-terminal (CT) fragment of IGFBP-4, the CT-IGFBP-4, has shown promising efficacy in cardiac risk assessment in various studies. We performed a systematic review of studies that accessed the utility and predictability of CT-IGFBP-4 in different ischemic cardiovascular events. Methods. The electronic databases PubMed, medRxiv, ScienceDirect, and Google Scholar were searched for relevant literature from inception to the 10th of December, 2021. Thus, retrieved literature was screened by title and abstract, followed by full-text screening based on the eligibility criteria. The risk of bias was accessed using the quality in prognostic studies (QUIPSs) tool. The data on cardiovascular outcomes about CT-IGFBP-4 levels were studied and the results were synthesized. Results. Five studies with a total of 1,417 participants were included in our study. The studies reported a low risk of bias. The mean age of the participants was 66.14 and more than 65% were males. Elevated CT-IGFBP-4 levels were associated with poor cardiovascular outcomes and increased mortality in severely ill patients. In contrast, there were no significant findings in the case of stable patients. Sandwich ELISA using lithium-heparin plasma provided a better detection limit of 0.15 ng/ml, low cross-reactivity (<2%), and generated linear results between 12 and 500 ng/ml. Conclusion. CT-IGFBP-4 is an efficient biomarker for the prediction of MACE and mortality in patients with severe ischemic cardiovascular events.
Research on Soybean Disease Identification Method Based on Deep Learning
Authors: Miao E. , Zhou Guixia , Zhao Shengxue
Published: August 2022

With the continuous integration of computer technology into agricultural production, it also reduces personnel costs while improving agricultural production efficiency and quality. Crop disease control is an important part of agricultural production, and the use of computer vision technology to quickly and accurately identify crop diseases is an important means of ensuring a good harvest of agricultural products and promoting agricultural modernization. In this paper, a recognition method based on deep learning is proposed based on soybean brown spot. The method is divided into image pretreatment and disease identification. Based on traditional threshold segmentation, the preprocessing process first uses the HSI color space to filter the information of the normal area of the leaf, adopts OTSU to set the threshold to segment the original image under the Lab color space, and then merges the segmented images. The final spot segmentation image is obtained. Compared with the renderings of several other commonly used methods of segmentation, this method can better separate the lesions from the leaves. In terms of disease identification, in order to adapt to the working conditions of large samples of farmland operations, a convolutional neural network (CNN) of continuous convolutional layers was constructed with the help of Caffe to extract more advanced features of the image. In the selection of activation functions, this paper selects the Maxout unit with stronger fitting ability, and in order to reduce the parameters in the network and prevent the network from overfitting, the sparse Maxout unit is used, which effectively improves the performance of the Maxout convolutional neural network. The experimental results show that the algorithm is superior to the algorithm based on ordinary convolutional neural network in identifying large sample crop diseases.
miR-381 Inhibits Proliferation and Invasion of Non-Small-Cell Cancer Cells by Targeting USP39
Authors: Cui Fang , Luo Peng , Wu Rui , Meng Jiangping
Published: August 2022

It is known that miR-381 plays a therapeutic role in a variety of cancers, but the regulatory mechanism of miR-381 in the treatment of lung cancer remains unclear. This study is aimed at exploring the expression level and mechanism of miR-381 in lung cancer. In this experiment, quantitative real-time PCR (qRT-PCR), western blot, and other methods were used to detect the expression of miR-381 and ubiquitin-specific protease 39 (USP39) in lung cancer tissues. The target genes of miR-381 were predicted by bioinformatics techniques, and the targeting relationship between miR-381 and USP39 was verified by the dual-luciferase reporting method. The expression levels of miR-381 and USP39 were adjusted to verify the effect of miR-381 on the expression of USP39 gene. The effect of miR-381 expression on proliferation of lung cancer cells was verified by cell proliferation and invasion experiments. miR-381 was downregulated in non-small-cell lung cancer tissues and cell lines, while USP39 was upregulated. The dual-luciferase reporter gene assay showed that miR-381 and USP39 had targeted binding sites. After transfection with miR-381 mimics, USP39 expression was significantly decreased, cell proliferation decreased, and apoptosis increased. After transfection with miR-381 inhibitor, USP39 expression was significantly increased, cell proliferation increased, and cell apoptosis decreased. Overexpression of USP39 significantly increased the invasion ability and cell survival curve (

p
<
0.05

). In conclusion, overexpression of miR-381 can regulate the expression of USP39, inhibit the proliferation and invasion of cancer cells, and induce apoptosis of cancer cells. This may provide a new perspective and strategy for targeted therapy of non-small-cell lung cancer.
A Design Thinking Technique of Letting Problems Solved by Self
Authors: Zhao Yulin , Luh Dingbang , Sun Yue , Sun Fei
Published: August 2022

This paper puts forward the thinking mode of problems solved by self, which can turn complaints into wishes that resembles needs beyond user’s expectation and imagination. Inferring the framework for solving problems from existing problem materials, the proposed technique employs literal logic to manipulate mathematical strategies, so that rational thinking can guide the development of affectional contexts, and automatically generate solution concepts, systematically and systemically. Through the demonstration of a design case study and comparative analysis of the effectiveness of related creative techniques the feasibility, novelty, advancement, and practicality of the proposed model are verified. The proposed tool can assist its users to think outside the black box and create “needs that adopters yet to aware.”
Far-Contralateral Oblique (FCO) Sacroiliac Joint Injection: Description of a Novel Technique
Authors: Lee David W. , Buchanan Patrick , Vodapally Shashank , James Christopher , Diep Jack
Published: August 2022

Sacroiliac (SI) joint arthropathy is the primary pain generator in approximately 15–25% of patients with axial low back pain and traditionally diagnosed with >50% pain reduction following an intra-articular injection localized to the inferior 1/3 of the SI joint. The conventional technique for accessing the SI joint encompasses a posterior approach with fluoroscopic guidance at 10–20⁰ contralateral oblique angulation, and minor adjustments to this approach have been implemented with varying degrees of success. The authors present a novel technique for SI joint injection, infiltrating the middle third of the joint through an alternative far-contralateral oblique (FCO) approach, angulation between 20–40⁰. This approach theoretically endows easier access to the SI joint and at the very least provides another option for interventionalists in the diagnosis and treatment of sacroiliac joint pain. It can also be utilized to determine if a patient is a candidate for posterior percutaneous SI joint fusion. The authors sought to document this approach to ensure that it was both reproducible and safe, while recognizing the need for future studies.
Degradation of Methylene Blue Using Hydrothermally Synthesized α‐Manganese Oxide Nanostructures as a Heterogeneous Fenton Catalyst
Authors: Dawadi Sonika , Gyawali Kabita , Katuwal Saurav , Gupta Aakash , Lamichhane Ganesh , Khadka Sujan , Koirala Agni Raj , Parajuli Niranjan
Published: August 2022

Lately, the upsurge in the liberation of synthetic dyes into the environment, primarily by the textile industries, is a threat to the natural habitat and existing ecosystem. Various methods such as adsorption and degradation with nanoparticles are currently being used to degrade those hazardous materials, but still, the yearning for novel methods continues. In this study, hydrothermal reactions were performed at 160°C to synthesize manganese dioxide nanostructures (MnNSs) under different incubation periods that facilitated the comparison of the size, morphology, and crystallinity of MnNSs. The study revealed the change in crystallinity over the incubation period; MnNSs prepared at 24 hrs were highly crystalline among others. Additionally, the size and morphology of MnNSs changed from the sea‐urchin or flower‐like structure, predominantly sheet/layer form, to nanorods as the reaction proceeded for 24 hrs. Characterization of MnNSs was followed by heterogeneous Fenton’s reaction, using α‐manganese dioxide nanostructures, for the degradation of methylene blue (MB). To further understand the catalytic activity of MnNSs, the synthesized nanostructures were subjected to degrade MB at varied time intervals, both with and without hydrogen peroxide (H2O2). Catalytically, MnNSs evinced good potential for degrading MB dye in the presence of H2O2; MnNSs prepared at 24 hrs degraded MB up to 73% within 110 minutes.
A Distribution-Free THWMA Control Chart under Ranked Set Sampling
Authors: Zhang Hongying , Rasheed Zahid , Khan Majid , Namangale Jimmy Joseph , Anwar Syed Masroor , Hamid Aamir
Published: August 2022

The basic assumption of the parametric control charts is that the underlying process follows the specific distribution. The appropriateness of parametric control charts is questionable when different industrial applications do not support this desired assumption. Recently, nonparametric control charts have been introduced to overcome this deficiency of parametric control charts. Nonparametric control charts have the same in-control run-length characteristics for all continuous distributions and are in-control robust. On the other hand, the ranked set sampling technique is preferred over the simple random sampling technique with control charts because it reduces variability and improves the control chart’s performance. So, this study aims to propose a nonparametric triple homogenously weighted moving average control chart under Wilcoxon signed-rank test with a ranked set sampling technique (regarded as

NPTHWMA

RSS

) to further enhance the process location monitoring. Monte Carlo simulations are used for computational purposes. The proposed control chart’s run-length performance is compared with competing control charts, like TEWMA-SR, TEWMA-

X
¯

, TEWMA-SN, TEWMA-

SR

RSS

, and

NPDHWMA

RSS

control charts. The comparison revealed that the proposed

NPTHWMA

RSS

control chart outperformed the other competing control charts, particularly for small to moderate shifts in process location. Finally, a real-life application is presented for quality practitioners to illustrate the effectiveness of the proposed control chart.
Experimental Study on the Influence of Hydromechanical Boundary Conditions on Shear-Flow Coupling Characteristics of Granite Joints
Authors: Cao Yangbing , Wu Yang , Zhang Xiangxiang , Liu Zhi , Gong Weiguo , Huang Zhenping
Published: August 2022

The instability of jointed rock mass is usually the shear process of the rock mass along discontinuities under the influence of groundwater flow. By conducting laboratory tests and numerical experiments on the shear-flow coupling of rock joints under constant normal stiffness (CNS) and constant normal stress (CNL) boundary conditions, the influence of normal boundary conditions and seepage pressure on the shear mechanical and flow characteristics of joints were investigated. The test results were as follows: The joint shear stiffness, peak, and residual shear strength under the CNS boundary condition were predominantly larger than those under the CNL boundary condition. Overall, these parameters were positively correlated with the initial normal stress

σ

n
0

. When

σ

n
0

>
2

 MPa, the postpeak shear stress of the CNS boundary condition showed a sharp decrease, whereas that of the CNL boundary condition changed from a slowly decreasing type (

σ

n
0

=
4

 MPa, 6 MPa) to a sharply decreasing type at

σ

n
0

=
8

 MPa. The peak dilation rate under the CNS boundary condition at all levels of normal stress was lower than that of CNL, and the strain softening in postpeak of the latter was more remarkable. In the process of joint shear, the hydraulic aperture displayed a four-stage variation law of “steady-sudden increase-slow increase-basically stable.” Moreover, the hydraulic aperture under the CNS boundary condition was always lower than that under the CNL boundary condition. The seepage pressure increased from 0.5 MPa to 1.5 MPa, and the average hydraulic aperture in the stable stage under normal stress at all levels increased from 0.146 mm to 0.187 mm. In addition, the average peak shear stress and average shear stiffness decreased by 0.9 MPa and 0.83 GPa/m, respectively. We also established a numerical model of a real rough three-dimensional joint, compiled a calculation program for the shear-flow process of a joint under CNS boundary conditions, and visualized the flow channel inside the joint. The seepage flow bypassed the area where the joints contacted each other, forming obvious flow channels. The flow rate increased at the intersection of the flow channels.
Correspondence Model of Human Resource Management and Marketing Based on Genetic Algorithm
Authors: Bi Yulin , Tang Ming
Published: August 2022

In order to realize the optimal allocation of human resources and avoid the waste or relative shortage of human resources, human resources and marketing based on the genetic algorithm are combined together and a combined evaluation management model is established in this study. By constructing a weight vector to represent the evaluation performance of different evaluation models for talent evaluation, the combination problem of multiple evaluation models is transformed into an optimization problem of weights. Based on the evaluation accuracy, the fitness function is designed, the weight vector is optimized by the genetic algorithm, and the individual selection strategy is designed to avoid falling into local optimization. The validity of the model and algorithm is verified by a numerical example, and the calculation results show that the proposed method can gradually improve the average working ability of employed employees by reasonably controlling the number of employment at different periods and the number of dismissals, and the average working ability of employees can be improved by 41%, thus realizing the optimization of human resources for the project.
Data Analysis of Building Microrenovation Based on City Information Modeling and Smart Sensor Networks
Authors: Zhang Dongfang , Li Zhennan , Sun Wei , Zhu Xuehua , Ge Hui
Published: August 2022

Building microrenovation refers to the building renewal method implemented through partial demolition, repair, preservation, function replacement, renovation, improvement, protection, decoration, and activation under the premise of maintaining the current construction pattern basically unchanged. City information modeling (CIM) technology provides a three-dimensional space floor with all elements for refined city governance and smart city construction; the data layers of smart sensor network (SSN) technology can aggregate multisource data by docking with facility layers and can classify integrated data resources. On the basis of summarizing and analyzing the previous research results, this study expounded the research status and significance of data analysis of building microrenovation, elaborated the development background, current status, and future outlooks of CIM and SSN, introduced the methods and principles of the aggregation and segmentation of information resources and the aggregation and interconnection of multisource data, performed the feature extraction and data storage of the original buildings, conducted the scheme design and information classification of microrenovation, implemented the data extraction and model construction of building microrenovation based on CIM and SSN, performed the data analysis of building appearance improvement, conducted the data analysis of building function replacement, implemented the database establishment and data analysis of building microrenovation based on CIM and SSN, and finally carried out a case application and its result analysis by taking a middle school two-story teaching building as an example. The study results show that the CIM technology can provide buildings’ actual data information such as geometry, physics, structure, and rules for building microrenovation; the SSN technology greatly reduces a lot of work caused by the rewiring of control system in the construction of building microrenovation. The combination of CIM and SSN can effectively connect various entity elements in building microrenovation to form a theme library through various data spatial relationships and spatial coding, realizing the connection of spatial data and nonspatial data in multiple dimensions. The data analysis of building microrenovation based on CIM and SSN includes multiple dimensions of achievements, processes, resources, characteristics, and applications, which is more in line with CIM integration applications and is easier for realistic information exchange and sharing applications.
Stability and Safety of Cooperative Adaptive Cruise Control Vehicular Platoon under Diverse Information Flow Topologies
Authors: Dai Yulu , Yang Yuwei , Zhong Hongming , Zuo Huijun , Zhang Qiang
Published: August 2022

For the cooperative adaptive cruise control (CACC) vehicular platoon, apart from decentralized controllers, the dynamics of a platoon can be affected substantially by the information flow among connected and automated vehicles (CAVs). Existing research studies mainly focus on the stability analysis of platoons where CAVs only adopt the predecessor-following (PF) communication scheme; however, when CAVs “look” further ahead or behind than one vehicle, the stability of platoons might change. To this end, this study seeks to explore the stability and investigate the rear-end collision risk of CACC vehicular platoon under diverse information flow topologies. The research first comprehensively reviews typical information flow topologies for CAV platoons and platoon stability criteria for analyzing local and string stability of platoons. Moreover, the CACC longitudinal dynamic model is derived using the exact feedback linearization technique, which accommodates the inertial delay of powertrain dynamics. Accordingly, sufficient conditions of stability are mathematically derived to guarantee distributed frequency-domain-based control parameters. Simulation experiments are conducted to verify the correctness of derived sufficient stability conditions. The results show that platoons could better maintain stability with more vehicle information taken into consideration. However, when assessing the safety, it is found that the bidirectional type information flow topology would increase rear-end collision risk for CAV platoon. Further, the information flow topology of two-predecessor-leader following is the most recommended to enhance fully CAV platoon stability.
A Neural Network Model for Color Element Data Analysis for Urban Spatial Environment
Authors: Xia Xiaotang , Li Tingyang
Published: August 2022

In this paper, a CNN model for color element data analysis of the urban spatial environment is constructed through an in-depth study of color element data analysis. This paper investigates a high-order structure formed by a few nodes; it proposes a motif-based graph autoencoder MODEL, combining redefined first- and second-order similarities and perfectly integrating motif structure and autoencoder. The algorithm first proposes an efficient graph transformation method to add the influence of central nodes. It then offers a primary awareness mechanism to aggregate the information of noncentral neighbors. Cen GCN_D and Cen GCN_E outperform the latest algorithms in node classification, link prediction, node clustering, and network visualization. As the number of network layers increases, the advantages of these two variants become progressively more prominent. This paper uses a support vector machine to implement classification validation based on CNN. The experimental results show that when 450 images are randomly selected as training data, the classification accuracy obtained by using the features of different CNN output layers is distributed between 91.4% and 95.2%. When the training set of the experiment reaches more than 300, the accuracy can exceed 90%, and the experimental results corresponding to different training sets a more stable trend. Finally, the trained classifier model is obtained in this thesis, which achieves the purpose of fast classification prediction based on CNN for color element data analysis of urban spatial environments.
Urban Disaster Risk Prevention and Mitigation Strategies from the Perspective of Climate Resilience
Authors: Chen Ning , Tang Xiaolin , Liu Weihui
Published: August 2022

Enhancing urban climate resilience and innovating urban risk governance model are of great significance to promote the security development of cities. This paper discusses urban disaster risk prevention and mitigation strategies from the perspective of climate resilience. The urban climate resilience index system is constructed through text mining. The entropy weight TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method and obstacle degree model are used to measure the climate resilience index and identify the main obstacle factors that affect the improvement of urban climate resilience. This provides a quantitative representation method for the analysis of urban climate resilience and clarifies the contribution of climate resilience to urban disaster risk prevention and mitigation, as well as the key and difficult points of urban disaster risk prevention and mitigation. Therefore, based on the quantitative analysis of climate resilience, this paper puts forward disaster risk prevention and mitigation strategies from five aspects: collaborative governance, urban planning, early warning system, scientific and technological empowerment, and disaster education. It is expected to provide a reference for the urban system to maintain green, low-carbon, and high-quality development under climate change.
Analysis and Exploration on the Integration of Mental Health Education into College Physical Education Practice
Authors: Zhu Wei , Li Jinhong
Published: August 2022

In order to understand the mental health status of contemporary college students, the research team of “College Students’ psychological quality training” conducted mental health examination on nearly 6000 Chinese college students from 23 colleges and universities across the country. The results showed that about 16.51% of Chinese college graduates had serious mental health problems. The results of several recent studies on the mental health status of college graduates across the country show that the accuracy rate of mental behavior examination among college graduates across the country is about 16%, and the rate of people with unsound psychology or in a state of mental sub-health is higher, and there has been a psychological poverty group among college students. A large number of educational facts and scientific research have confirmed that sports are one of the most effective ways to promote students’ physical and mental development, and it can be said that there is a very close relationship between college sports and the physical and mental health of college graduates. In order to promote the organic combination of college mental health education and college physical education, the research results will be based on in-depth investigation and understanding of the current situation of college students’ psychological development under the new situation, and a systematic study of the relationship between college graduates’ physical, sports, mental health knowledge, and psychological level. This paper establishes a theoretical model for the organic combination of mental health education and physical education in colleges and universities, and provides specific countermeasures for integrating psychological teaching into college physical education courses, providing a theoretical basis and reference for developing college physical education courses and improving psychological teaching.
Reduction and Heavy Metal Stabilization of River Sediment by Hydrothermal Treatment
Authors: Sun Suyang , Fang Tinggan , Xue Gang , He Yueling , Wang Xiaonuan , Song Qi , Zang Xueke , Wang Yiwei , Zheng Shanshan
Published: August 2022

In this paper, hydrothermal treatment was used to treat river sediment. The physicochemical properties, chemical speciation, bioavailability, ecotoxicity, and leaching toxicity of heavy metals (Zn, Cu, Cr, Cd, Ni, Pb) in sediment under different hydrothermal treatment conditions were studied, and stabilization mechanisms of heavy metals were explained. The results showed that hydrothermal temperature and time had a huge impact on sediment reduction and heavy metal stabilization. The best reduction and stabilization of sediments were achieved at a hydrothermal temperature of 260°C and a hydrothermal period of 3 h. The hydrothermal treatment caused the sediment to undergo dehydration, dihydroxylation, decarboxylation, deamination, and aromatization with a gradual decrease in its H/C ratio, O/C ratio, and pH; a gradual increase in porosity and surface area; and a decrease in particle size. This facilitates the dehydration, reduction, and stabilization of the sediment. The bioavailable components of heavy metals in sediment were dramatically reduced following hydrothermal treatment, but the fraction of stable components rose significantly. This resulted in a marked decrease in the environmental bioavailability, ecotoxicity, and leaching toxicity of the heavy metals. Therefore, hydrothermal treatment might be an effective ex situ repairment way for reducing, stabilizing, and making river sediment harmless.
The Intervention of Data Mining in the Allocation Efficiency of Multiple Intelligent Devices in Intelligent Pharmacy
Authors: Li Xiaohua , Tan Benren , Zheng Jinkun , Xu Xiaomei , Xiao Jian , Liu Yanlin
Published: August 2022

With the wide application of artificial intelligence and big data technology in the medical field, the problems of high cost and low efficiency of traditional pharmacy management were becoming more and more obvious. Therefore, this paper proposed to use data mining technology to design and develop the dispensing process and equipment of intelligent pharmacy. Firstly, it summarized the existing data mining technology and association rule methods and expounded its application value in the related fields. Secondly, the data standard and integration platform of dispensing in intelligent pharmacy were established. Web service technology was used to design the interactive interface and call it to the intelligent device of pharmacy. Finally, an intelligent pharmacy management system based on association rule mining was constructed through the data mining of intelligent pharmacy equipment, in order to improve the intelligence and informatization of modern pharmacy management. For the emergency dispensing process of intelligent equipment failure, data mining was used to optimize the intelligent pharmacy equipment and dispensing process and change the pharmacy management from traditional prescription to patient drug treatment, so as to improve the dispensing efficiency of intelligent pharmacy equipment. Through the systematic test and analysis, the results showed that through the real-time risk prevention and control, the formula accuracy and operation speed of the intelligent dispensing machine were improved and the dispensing time was shortened. Through intelligent drug delivery, the unreasonable drug use of patients was reduced, the safety and effectiveness of clinical drug use were ensured, and the contradiction between doctors and patients was reduced. This study can not only optimize the medical experience of patients and provide patients with more high-quality and humanized pharmaceutical technical services but also provide some support for the intelligent management of modern hospitals.
Pityriasis Versicolor Resistant to Antifungal Drugs in a Patient in Lomé (Togo)
Authors: Teclessou Julienne , Kombate Koussake , Saka Bayaki , Akakpo Séfako Abla , Pitche Palokinam
Published: August 2022

Background. Pityriasis versicolor (PV) is a ubiquitous superficial skin mycosis that often affects young adults. It is often effectively treated with local or oral antifungal agents. Cases of PV resistance to antifungal agents have been reported rarely. We report a case of antifungal resistant PV. Observation. A 22-year-old patient was followed since the age of 17 years in a dermatology outpatient clinic for hyperpigmented scaly macular lesions of the trunk and upper limbs. The clinical diagnosis of PV was retained. The patient was treated by fluconazole 300 mg/week before being lost to follow-up. He was seen again in 2019 (about 2 years later) for the same symptomatology and treated again by fluconazole and ciclopirox olamine cream without improvement. He was again lost to follow-up and seen again six months later. A mycological sample was taken and Aspergillus niger was isolated. The patient was treated by itraconazole for 6 weeks. The evolution was marked by a clinical status quo. The patient was again put on salicylated petroleum jelly 10% associated with terbinafine cream and then lost to follow-up. Conclusion. The emergence of fungal resistance to antifungal drugs does not spare PV. It can therefore be resistant to several antifungal drugs, leaving clinicians and patients in despair.
Analysis of Mining Subsidence Characteristics and Deformation Prediction considering Size Parameters and Mechanical Parameters
Authors: Liu Shangguo , Li Kaixin , Shi Weiping , Wang Zijun , Zhang Haoran , Li Zhaoying
Published: August 2022

Crushing and caving of roof strata in goaf is an important factor affecting surface subsidence. In order to study the influence law of mining under thick loose layer, overburden size parameters, and initial mechanical parameters of collapse zone on surface subsidence, the law of surface subsidence was analyzed through measured data. On this basis, with the help of FLAC3D numerical simulation software, the surface subsidence was simulated by changing the above factors, and the evolution characteristics of the maximum surface subsidence under the influence of various factors were analyzed. Based on the grey relational analysis, the relational degree between each factor and the maximum surface subsidence value is analyzed, and through multiple nonlinear regression, the prediction model of mining subsidence deformation under thick loose layer considering the influence of seven factors is established. The results show that the mining thickness has the greatest influence on the surface subsidence, and cohesion has the least influence on surface subsidence. The rationality of the subsidence prediction model is verified by an example.
Research on Management and Efficiency Evaluation of Physical Education Course Selection in Colleges Based on Random Matrix Theory
Authors: Zou Jiashu , He Yi
Published: August 2022

The administration of bodily schooling instructing in schools and universities is creating toward informatization and digitalization. The scholar path determination device can noticeably limit the workload of instructional administrators, enhance the provider satisfactory of instructing management, realise the standardization and transparency of college students’ direction decision process, and meet quite a number of teachers, college students, and managers needed. At the same time, it has additionally considerably multiplied the work effectivity of instructional administration personnel, decreased a lot of human funding in academic administration management, and flawlessly elevated the modern state of affairs of heavy duties in faculty management. Physical coaching route decision in colleges and universities is a huge volume of statistics computing behavior that occurs intensively. Its typical overall performance requirements are very quintessential and have grown to be the most quintessential element of its availability. The overall performance optimization of the path decision gadget is the focal point of the data work of the instructional administration system. This paper first analyses the overall performance issues of the authentic path resolution system, places ahead a multilevel overall performance optimization scheme to optimize and enhance the enterprise process, and decreases the attention of facts processing in the course of direction selection. The stress check device was once used for overall performance test, and the overall performance index was once considerably extended to meet the diagram requirements. The route desire machine meets the requirements of 5000 clients online all thru the route choice pinnacle period, the response speed is lowered to plenty much less than 5 seconds, and the software program server runs stably, which properly meets the route dedication requirements of whole universities.
TRIM50 Inhibits Proliferation and Metastasis of Gastric Cancer via Promoting β-Catenin Degradation
Authors: Li Rongzhou , Xu Peng , Jin Xiaosheng , Shi Zhengchao , Zhang Qingqing , Ye Fangpeng , Yu Weilai , Ji Tingting
Published: August 2022

Background. Gastric cancer (GC) is a common malignancy with a poor prognosis. Tripartite motif-containing 50 (TRIM50) belongs to the TRIM family and is reported to be related to numerous cancers. This study aimed to investigate the function of TRIM50 in GC. Methods. Three microarray datasets (GSE13911, GSE79973, and GSE19826) containing GC and adjacent nontumor tissues were used for bioinformatics analysis to screen GC-related genes and assess the associations between GC development and TRIM50 expression. Then, TRIM50 expression in GC cells was detected at mRNA and protein levels. After TRIM50 was knockdown or overexpressed, the effect of TRIM50 on the proliferation and metastasis of GC cells was analyzed using Cell Counting Kit-8 (CCK-8), flow cytometry, scratch, and Transwell assays. The interaction between TRIM50 and β-catenin was analyzed. The expression of cell cycle-, migration-, invasion-, and Wnt/β-catenin signaling pathway-related proteins was detected by Western blot. Furthermore, we measured the role of TRIM50 overexpression on tumor growth as well as the Wnt/β-catenin signaling pathway in vivo. In addition, XAV939 (a WNT/β-catenin signaling pathway inhibitor) was used to clarify the mechanism of TRIM50 on GC. Results. Bioinformatics revealed that TRIM50 expression was decreased in GC samples and associated with GC development. In vitro study revealed that TRIM50 overexpression impeded the GC cell proliferation and metastasis, while TRIM50 knockdown presented the opposite results. In addition, TRIM50 interacted with β-catenin to induce the degradation of β-catenin. In in vivo assay, TRIM50 overexpression inhibited tumor growth and blocked the Wnt/β-catenin signaling pathway. In addition, TRIM50 knockdown-promoted cell proliferation and metastasis in GC cells were inverted by XAV939. Conclusion. TRIM50 overexpression may inhibit cell proliferation and metastasis in GC via β-catenin degradation, indicating that TRIM50 could be a target for the treatment of GC.
Dance Movement Recognition Based on Modified GMM-Based Motion Target Detection Algorithm
Authors: Tian Jing , Yang Xiaoqiang
Published: August 2022

Under the synergistic development of social economy and science and technology, the intelligent teaching of dance has become more and more popular. This teaching method can not only decompose dance movements more specifically, which is easy for students to understand and master, but also get rid of the time and space limitation in traditional dance teaching and provide more independent learning opportunities for students. The problem of low accuracy of dance movement recognition due to complex gesture changes in dance movements is addressed. To this end, this paper proposes a modified motion target detection algorithm based on GMM. The dance movement recognition algorithm first extracts the features of dance movements through a feature pyramid network, then uses a multi-feature fusion module to fuse multiple features to improve the algorithm’s estimation of complex postures, and finally completes the recognition of dance movements. Experiments show that our method can maintain a certain recognition rate in the case where the background and target are easily confused, and can effectively improve the dance action recognition accuracy, thus realizing the action correction function for dancers. This also verifies the effectiveness of the action recognition algorithm for dance movement recognition.
Evaluation Method for Diversifying Dynamic Capabilities of Small- and Medium-Sized Enterprises Using a Hybrid Genetic Algorithm
Authors: Ge Zhenfeng , Zhao Jingfang
Published: August 2022

Focusing on the topic of dynamic capability development and digital transformation of traditional enterprises in the digital economy era, and using traditional manufacturing as an example, this paper examines how small- and medium-sized (SMS) businesses should transform and develop in the digital economy era. Furthermore, in light of the problem that existing models cannot evaluate dynamic nonlinear optimization, a diversified dynamic capability evaluation model of SMS enterprises is developed, and the model is solved using the accelerated genetic value method based on real number coding, while the parameters of the BP network are evaluated using the genetic algorithm. In this study, 100 SMS companies are chosen from a pool of 1000 companies to perform an empirical study. In the empirical study, three different scenarios were employed. The selected dataset is utilized to test BP and GA in the first scenario. In the second scenario, the BP and GA are combined to create a more robust model, which is then evaluated on the specified dataset. This research provides a novel approach that combines the PCA with the acceleration method in the third case. According to the findings of this study, the methodology suggested in this work has an overall evaluation accuracy of 95.6 percent, which is pretty good when compared to other approaches. The model training error and test error, on the other hand, are both lower than those of traditional assessment procedures, according to the data.
RWYI: Reading What You Are Interested in with a Learning-Based Text Interactive System
Authors: Yu Zhenghong , Wang Hao , Yang Hang , Zhou Huabing
Published: August 2022

As computer vision and human-computer interaction technology mature, vision-based auxiliary text reading has become the mainstream method to optimize the learning and reading experience. Most of the existing auxiliary text reading methods use scene text recognition combined with human gesture recognition to complete the task in multiple stages. However, these methods cannot accurately and effectively extract the textual information that readers are interested in complex and varied reading scenarios. To improve the text reading experience, we propose a human-centered fast auxiliary text reading method. It utilizes a hand-text hybrid object detection (HTD) model to instantly locate text of interest to readers, a font-consistent prior text image superresolution network (FCSRN) to recover low-resolution text images to enhance the accuracy of text recognition, and a convolutional recurrent neural network (CRNN) text recognition operator to obtain the content of the text, that is, interesting to readers. To verify the effectiveness of the proposed method, we tested the performance of the text localization module on a homemade HTD dataset and the performance of the FCSRN on the public text image superresolution dataset called TextZoom. Quantitative experiments on the overall performance of the fast auxiliary reading system, called reading what you are interested in (RWYI), were designed. The experiments indicate that the proposed method can meet the needs of human-computer interactive auxiliary reading in text reading scenarios and optimize the reading experience.
5G Wireless Multimedia-Assisted Marketing Strategy Establishment and Effect Evaluation
Authors: Fu Tieyan , Zhang Bei
Published: August 2022

5G wireless networks are attracting attention due to their high data rates and robustness to multimedia options. Based on 5G wireless multimedia technology, this paper constructs an auxiliary marketing strategy for multipath collaboration. Based on the 5G wireless network system, the model solves the optimization problem of effective service energy consumption. The solution of the problem is obtained through a two-step solution and related algorithms, and the numerical simulation proves that the multipath cooperative transmission strategy has the advantages of network delay and effective service performance. In the simulation process, a 5G NR downlink system simulation model is established according to the wireless data transmission theory; in the marketing strategy estimation, the decision feedback marketing strategy estimation algorithm is improved to improve the marketing strategy estimation performance, which can effectively reduce insertion loss of the network. The results show that with the increase of the marketing data center density, the receiving delay decreases and the energy efficiency increases; when the number of video contents in the marketing data center is configured as 264, the effective service performance under the single-path transmission strategy can be achieved. Compared with the minimum value of the effective service energy consumption under the single-path transmission strategy, the minimum value of the effective service energy consumption under the multipath cooperative transmission strategy is reduced by 11.5%, which effectively improves the network throughput of data.
Clinical Value and Treatment Progress of Prenatal Ultrasonography in Twin Pregnancy: A Systematic Review
Authors: Zou Lihua , Yang Jianzheng , Min Aiping , Yin Yang , Li Minxing
Published: August 2022

Assisted reproductive technology has continued to develop in recent years, the technology has become more and more mature, and it has improved the total gestational age of the population. Assisted reproductive technology has improved twin pregnancy rates with the use of ovulation‐inducing drugs. The risk factor of twins is much higher than singletons, and adverse pregnancy outcomes such as stillbirth and premature birth are more likely to occur than singletons, especially the special complications of monochorionic twins (MC), and the neonatal mortality and morbidity are also increased. Prenatal diagnosis and prognosis of twin pregnancy, as well as therapeutic interventions, are of current concern. Ultrasound can realize the understanding of intrauterine growth and development of twin pregnancy fetuses during pregnancy, can more accurately determine gestational age, organ function, and maturity, and timely detect fetal growth and development abnormalities in twin pregnancy, while the prognosis and treatment still need further improvement. The purpose of this study was to investigate the clinical value and treatment progress of prenatal ultrasound monitoring in twin pregnancy.
Powered Toothbrushes: An Opportunity for Biofilm and Gingival Inflammation Control
Authors: Rösing Cassiano Kuchenbecker , Garduño Eduardo , Bussadori Sandra Kalil , Zerón Agustín , Soares Paulo Vinícius , Saadia Marc , Villar Cristina Cunha
Published: August 2022

The present review aimed at a broad investigation on the potential of powered as compared to manual toothbrushes in different aspects of clinical dentistry. Studies evaluating plaque and gingival inflammatory parameters were included, as well as those that investigated adverse effects. Emphasis was given separately to adults, youngsters, special-needs patients, and those under fixed orthodontic therapy. In general, comparisons favored powered toothbrushes. In summary, approximately 68% of the included studies, in terms of plaque/gingival inflammation in adults, presented better results for powered toothbrushes. In children and special-needs populations, approximately 40% of the included studies favored powered toothbrushes for plaque/gingival inflammation, and none favored manual ones. In orthodontic individuals, 50% of the studies also demonstrated a better effect of powered toothbrushes on plaque and gingival inflammation. All included studies that assessed adverse events did not demonstrate a difference in these effects when comparing manual vs. powered toothbrushes. It is concluded that the use of powered toothbrushes is an opportunity to enhance patterns of plaque control and associated gingival inflammation.