bluuebunny/crossref_metadata_2025 huggingface dataset:
Oscillatory Dynamics in Complex Recurrent Neural Networks
Authors: Sengupta Rakesh , Raja Shekar P. V.
Published: August 2022

Spontaneous oscillations measured by local field potentials (LFPs), electroencephalograms and magnetoencephalograms exhibit a variety of oscillations spanning the frequency band of 1–100[Formula: see text]Hz in animals and humans. Both instantaneous power and phase of these ongoing oscillations have commonly been observed to correlate with pre-stimulus processing in animals and humans. However, despite numerous attempts it is not fully clear whether the same mechanisms can give rise to a range of oscillations as observed in vivo during resting-state spontaneous oscillatory activity of the brain. In this paper, we show how oscillatory activity can arise out of general recurrent on-center off-surround neural network. This work shows that (a) a complex-valued input to a class of biologically inspired recurrent neural networks can be shown to be mathematically equivalent to a combination of real-valued recurrent networks with real-valued feed-forward network, and (b) such a network can give rise to oscillatory signatures. We also validate the conjecture with results of simulation of complex-valued additive recurrent neural network.
Pharmacological Induction of Granulocyte Cell Death as Therapeutic Strategy
Authors: Kaufmann Thomas , Simon Hans-Uwe
Published: August 2022

Apoptosis is central for the maintenance of health. In the immune system, apoptosis guarantees proper development of immune cells and shutdown of immune reactions by the coordinated elimination of activated immune cells. Limitation of the life span of granulocytes is important, as overactivation of these cells is associated with chronic inflammation and collateral tissue damage. Consequently, targeted induction of granulocyte apoptosis may be beneficial in the course of respective immune disorders. Anti-inflammatory drugs such as glucocorticoids and monoclonal antibodies against IL-5Rα exert their function in part by triggering eosinophil apoptosis. Agonistic antibodies targeting Siglec-8 or death receptors are tested (pre)clinically. Moreover, a new class of inhibitors targeting antiapoptotic BCL-2 proteins shows great promise for anticancer treatments. Because of their specificity and tolerable side effects, these so-called BH3 mimetics may be worthwhile to evaluate in inflammatory disorders. Here, we review past and recent data on pharmacological apoptosis induction of granulocytes and highlight respective therapeutic potential.
Deglutition and the Regulation of the Swallow Motor Pattern
Authors: Pitts Teresa , Iceman Kimberly E.
Published: August 2022

Despite centuries of investigation, questions and controversies remain regarding the fundamental genesis and motor pattern of swallow. Two significant topics include inspiratory muscle activity during swallow (Schluckatmung, i.e., “swallow-breath”) and anatomical boundaries of the swallow pattern generator. We discuss the long history of reports regarding the presence or absence of Schluckatmung and the possible advantages of and neural basis for such activity, leading to current theories and novel experimental directions.
Point Cloud Key Point Extraction Algorithm Based on Feature Space Value Filtering
Authors: Chen Guowei
Published: August 2022

With the rapid development of 3-dimensional (3D) acquisition technology, point clouds have a wide range of application prospects in the fields of computer vision, autonomous driving, and robotics. Point cloud data is widely used in many 3D scenes, and deep learning has become a mainstream research method for classification with the advantages of automatic feature extraction and strong generalization ability. In this paper, a hierarchical key point extraction framework is proposed to solve the problem of modeling the local geometric structure between points. Various point cloud models such as PointNet, PointNet++, and DGCNN are analyzed and their features in local key point are extracted. Based on these analyses, an indexed edge geometric feature spatial value screening neural network (IEGCNN) is proposed. This network extracts features from each point and its neighborhood, calculates the distance between the center point and the points within its neighborhood, and adds the point orientation information to the edge feature spatial value screening network. The relationship between points in the edge network architecture is projected onto a 3D coordinate system and decomposed into three orthogonal bases. The geometric structure between two points is modeled by feature aggregation based on the angle between the edge vector and the base vector and the distance between the center point and the neighboring points. The proposed method has the capability of fast processing of point cloud data by significantly reducing the training and recognition time. The experimental results show that this method achieved high classification accuracy value. This work also provides an idea to solve the problem of real-time target detection network, which has a broad applications prospect in the deployment of movable devices and real-time processing.
Construction of a Humanized PBMC-PDX Model to Study the Efficacy of a Bacterial Marker in Lung Cancer Immunotherapy
Authors: Wu Chengwei , Wang Xinning , Shang Haitao , Wei Hong
Published: August 2022

Commensal microbiome is a key factor of lung cancer immunotherapy efficacy. Elucidating the role of specific strains as bacterial markers in immunotherapy has drawn great attention from the academia. At present, most preclinical studies about the relationship between bacterial markers and immunotherapy rely on the syngeneic mouse models. However, mice differ greatly from humans in immune system and tumor characteristics. In this study, humanized mouse models based on peripheral blood mononuclear cells (PBMCs) immune reconstitution and lung cancer cell line-derived xenograft (CDX) or patient-derived xenograft (PDX) were constructed. The PBMC-PDX model was shown to be superior to the PBMC-CDX model in preserving tumor heterogeneity and construction time-saving. Through optimizing the experimental process, the time it took for humanized models to evaluate the effect of cancer treatment was reduced to 42 days. Next, by utilizing PBMC-PDX mice treated with antibiotics (ATB), the role of Bifidobacterium longum in lung cancer immunotherapy was studied. It was found that although both Bifidobacterium longum and immunotherapy drug pembrolizumab alone showed suppressing tumor growth, the efficacy of pembrolizumab was attenuated when administrated to mice colonized with Bifidobacterium longum. Further exploration revealed that Bifidobacterium longum caused significant changes in the proportion of human CD45+ cells in the PBMC-PDX model. The PBMC-PDX model has the potential to be applied as an efficient platform to support evaluation of bacterial markers in immunotherapy research and facilitate development of precision medicine targeting human commensal bacteria.
A Review on Machine Learning Strategies for Real-World Engineering Applications
Authors: Jhaveri Rutvij H. , Revathi A. , Ramana Kadiyala , Raut Roshani , Dhanaraj Rajesh Kumar
Published: August 2022

Huge amounts of data are circulating in the digital world in the era of the Industry 5.0 revolution. Machine learning is experiencing success in several sectors such as intelligent control, decision making, speech recognition, natural language processing, computer graphics, and computer vision, despite the requirement to analyze and interpret data. Due to their amazing performance, Deep Learning and Machine Learning Techniques have recently become extensively recognized and implemented by a variety of real-time engineering applications. Knowledge of machine learning is essential for designing automated and intelligent applications that can handle data in fields such as health, cyber-security, and intelligent transportation systems. There are a range of strategies in the field of machine learning, including reinforcement learning, semi-supervised, unsupervised, and supervised algorithms. This study provides a complete study of managing real-time engineering applications using machine learning, which will improve an application's capabilities and intelligence. This work adds to the understanding of the applicability of various machine learning approaches in real-world applications such as cyber security, healthcare, and intelligent transportation systems. This study highlights the research objectives and obstacles that Machine Learning approaches encounter while managing real-world applications. This study will act as a reference point for both industry professionals and academics, and from a technical standpoint, it will serve as a benchmark for decision-makers on a range of application domains and real-world scenarios.
Application of Image Color Gamut Boundary Judgment Algorithm in Digital Media
Authors: Li Xuewei
Published: August 2022

Image chromatic aberration evaluation is one of the research hotspots and academic difficulties in the field of color science and imaging technology. Based on the algorithm theory of image color gamut boundary judgment, this paper constructs its application model in digital media. The model uses the threshold color difference image as a reference and applies it to the evaluation experiment of color difference above the threshold based on the quantitative estimation method. During the simulation process, the improved HAD dual-color image digital boundary judgment algorithm is programmed. For small color difference data at the threshold level, the calculated color difference of the boundary judgment algorithm framework is smaller than the visual perception color difference; for the large color difference data above the threshold, the boundary judgment algorithm framework is given. The research results of the threshold color difference experiment show that the perceptible color difference threshold and acceptable color difference threshold of image color gamut observers for image color difference are 1.85 AE and 3.63 AE, respectively, which are basically twice the relationship. The visually perceptible chromatic aberration threshold and acceptable chromatic aberration threshold for lightness parameters are higher than those of chroma and hue, which shows that the boundary judgment algorithm framework has certain advantages for the evaluation performance of color digital image threshold chromatic aberration and effectively improves the algorithm robustness.
The In Vitro Effect of Psoralen on Glioma Based on Network Pharmacology and Potential Target Research
Authors: Wu Yang , Zhang Yong-Zheng , Li Meng-Jia , Yang Wen-qing , Cheng Lu-feng
Published: August 2022

Glioma is an aggressive tumor, currently there is no satisfactory management available. Psoralen, as a natural product, has been found to have an effect of treating cancer in recent years, but its effect on glioma has not been explored. In this study, we investigated the in vitro inhibition effect and potential targets of psoralen on glioma through network pharmacology and in vitro glioma treatment experiments. First, we used network pharmacology to preliminarily predict the 21 core genes of psoralen in the treatment of glioma, including PIK3CA, PIK3CB, PIK3CG, and JAK2. The CCK-8 method was used to detect the effect of psoralen on the proliferation of glioma U87 and U251 cells, and the results showed that psoralen could significantly inhibit the proliferation of U87 and U251 cells. The flow cytometry was used to detect the apoptosis and cell cycle changes, and it was found that psoralen could significantly promote the early apoptosis of U87 and U251 cells and had a significant cycle arrest effect on the two cells. The cell scratch test showed that psoralen could significantly inhibit the migration of U87 and U251 cells. The relative expression levels of PIK3CA, PIK3CB, PIK3CG, and JAK2 were analyzed by Real-time Quantitative polymerase chain reaction (QT-PCR), and the results showed that psoralen could inhibit the gene expression of PIK3CA, PIK3CB, PIK3CG, and JAK2. Later, Western blotting (WB) experiments showed that psoralen could inhibit the protein expressions of PI3K and JAK2. This study has preliminarily explored and verified the antiglioma effect of psoralen in the form of inhibiting cell proliferation and migration, promoting cell apoptosis and organizing cell cycle in vitro. And may play a role by inhibiting the expression of PIK3CA, PIK3CB, PIK3CG, JAK2 gene and PI3K, JAK2 protein, psoralen has become a potential antiglioma drug.
Scaling Method Application for Seismic Design along the Central Anatolian Fault Zone
Authors: Gumus Erhan , Ozturk Baki , Mohamed Nazri Fadzli
Published: August 2022

Cities located along the Central Anatolian Fault Zone (CAFZ), such as Kayseri and Mersin, have become metropolitan cities in Turkey since the 1950s and have been attracting big investments, such as the Akkuyu Nuclear Power Plant (Mersin), which is planned to be built close to the CAFZ. In this study, the ground motion records of earthquakes occurring along the CAFZ are scaled for single‐degree‐of‐freedom (SDOF) systems conforming to the current design response spectra. This is a pioneering study on the analysis of seismic behavior using SDOF systems subjected to ground motions that were recorded in relation to earthquakes occurring on the CAFZ in Turkey. It defines the importance of selecting suitable records with certain features that can be used with the scaling method to ensure that real ground motion records match the design acceleration spectra defined in the earthquake codes and will provide a perspective on future destructive earthquakes that may occur on the CAFZ.
Green Power Generation by Microbial Fuel Cells Using Pharmaceutical Wastewater as Substrate and Electroactive Biofilms (Bacteria/Biocarbon)
Authors: Alonso-Lemus Ivonne L. , Cobos-Reyes Carlos , Figueroa-Torres Mayra , Escobar-Morales Beatriz , Aruna K. Kunhiraman , Akash Prabhu , Fernández-Luqueño Fabian , Rodríguez-Varela Javier
Published: August 2022

In this work, electroactive biofilms of Bacillus subtilis (B. subtilis) or Escherichia coli (E. coli) were supported on functionalized biocarbon (AB7-F), which was synthesized from waste leather and was used as catalysts to develop bioanodes for microbial fuel cells (MFCs). This way, bioanodes were fabricated and further evaluated in a three-electrode cell using pharmaceutical wastewater (PWW) as substrate. The electrochemical measurements showed a higher performance of the bioanode based on AB7-f+ B. subtilis to oxidize organic matter from PWW. The polarization curves in the dual-chamber MFC showed that AB7-f+ B. subtilis bioanode can generate an open circuit voltage of 602 mV and a power density of 77 mW m−2. During long-term tests of the MFC, a variation in performance was observed, with a maximum of 96.3 mW m−2 on day 7. Such variation was attributed to the development of more stable biofilm as well as consumption of some compounds metabolized by bacteria grown on the bioanode. The results showed that AB7-f+ B. subtilis can be used as bioanode for MFCs with PWW as substrate removing around 45% of the chemical oxygen demand (COD).
Collagen Modulates the Biological Characteristics of WJ-MSCs in Basal and Osteoinduced Conditions
Authors: Hiew Vun Vun , Teoh Peik Lin
Published: August 2022

Transcriptomic analysis revealed mesenchymal stem/stromal cells (MSCs) from various origins exhibited distinct gene and protein expression profiles dictating their biological properties. Although collagen type 1 (COL) has been widely studied in bone marrow MSCs, its role in regulating cell fate of Wharton jelly- (WJ-) MSCs is not well understood. In this study, we investigated the effects of collagen on the characteristics of WJ-MSCs associated with proliferation, surface markers, adhesion, migration, self-renewal, and differentiation capabilities through gene expression studies. The isolated WJ-MSCs expressed positive surface markers but not negative markers. Gene expression profiles showed that COL not only maintained the pluripotency, self-renewal, and immunophenotype of WJ-MSCs but also primed cells toward lineage differentiations by upregulating BMP2 and TGFB1 genes. Upon osteoinduction, WJ-MSC-COL underwent osteogenesis by switching on the transcription of BMP6/7 and TGFB3 followed by activation of downstream target genes such as INS, IGF1, RUNX2, and VEGFR2 through p38 signalling. This molecular event was also accompanied by hypomethylation at the OCT4 promoter and increase of H3K9 acetylation. In conclusion, COL provides a conducive cellular environment in priming WJ-MSCs that undergo a lineage specification upon receiving an appropriate signal from extrinsic factor. These findings would contribute to better control of fate determination of MSCs for therapeutic applications related to bone disease.
From “Social Integration” to “Class Integration”: Applying Durkheim’s Sociological Thought to Hidden Dropout of Junior Middle School Students
Authors: Jia Limin , Ji Liangfei , Zhou Wenjing
Published: August 2022

At present, China’s academic circles have made some research results on the hidden dropout of junior middle school students, but they have not formed a relatively mature theory. Based on Durkheim’s “social integration” theory, this paper studies hidden dropout from the perspective of class sociology and puts forward the influencing mechanism of “class integration” of junior middle school students’ hidden dropout behavior. By class observation, this paper obtains the hidden dropout theoretical model of the interaction between individuals and class organization.
Three-Dimensional Reconstruction and Protection of Mining Heritage Based on Lidar Remote Sensing and Deep Learning
Authors: Shang Liqiang , Wang Changming
Published: August 2022

In the past, the traditional small-scale 3D reconstruction technology developed maturely and mainly relied on manual handheld devices for data acquisition. Due to multiple factors, inaccuracy, and other problems, data will be omitted, and sometimes staff will face risks directly. Nowadays, with the development of computer science and technology, three-dimensional reconstruction technology has been innovated continuously, and it has also made a breakthrough in the application of large-scale reconstruction of dangerous areas. In this paper, the expensive sensors in the past are abandoned, and the cheaper and more efficient lidar is used instead. The laser point cloud and image are combined to describe the mining heritage scene in depth, and the academic achievements are transformed into productivity. The results show that (1) comparing the performance of the algorithm, the overall error of the proposed method is 5.86, and the average time consumption is about 10.23 ms. This filtering algorithm can restore the landscape of mining heritage to a great extent and optimize the problems of noise and outliers. (2) Our designed model has a very low loss value, and the point cloud accuracy is as high as 92.9%. Compared with other model methods, the model has excellent performance. (3) After the completion of the model, the overall satisfaction effect is above 70%, which can well restore the mining heritage style. Finally, the experimental effect of 3D reconstruction is good, which is more conducive to the research of reconstruction protection. There are still some work details and performance problems that need to be optimized and solved.
Research on the Innovation of Procurement Mode of Nanomaterials Based on E-Commerce
Authors: Song Baorui , Wang Xiaozhi
Published: August 2022

With the rapid development of science and technology, the proportion of nanomaterials is increasing. With the advantages of height, strength, high density, and lightweight, nanomaterials have become the preferred manufacturing materials in many industries. In the procurement business of e-commerce, the utilization rate of nanomaterials is getting higher and higher. However, due to the long manufacturing cycle, high consumption loss, and high transportation damage rate of nanomaterials, there are often many problems in the procurement process. In this paper, we use the methods of case investigation and experimental research to study the innovation of procurement mode of nanomaterials in e-commerce. The data show that the use of nanomaterials has become the first choice of many manufacturers and suppliers and has a more and more frequent trend in the use process. Nanomaterials are suitable for industrial application due to their low transportation and storage costs and high procurement efficiency. However, at present, nanomaterials need further innovation to achieve more applications. In this paper, the procurement model and marketing model are innovated to make the e-commerce procurement business of nanomaterials more convenient. From these studies, this paper concludes that the most important thing for the procurement of nanomaterials is to find out the customers’ needs, and then according to the user specifications of nanomaterials, achieve the best logistics and distribution methods in the transportation process. The innovation of the e-commerce procurement mode of nanomaterials can greatly facilitate the development of business. Under the innovative mode, the transportation cost and procurement efficiency have been greatly improved, about 2 points higher than before, and the procurement value has also increased by 3 points to more than 6 points. At the same time, the innovation of e-commerce procurement mode of nanomaterials can make the related upstream and downstream industrial chain reach a very saturated state and make the scientific and technological innovation and procurement salesman in the industry more smooth and reliable.
Clinical Study of Progesterone Combined with Vitamin B6 in the Treatment of Amenorrhea Endocrine Disorders Caused by Antipsychotics
Authors: Zhao Yijing , Hu Shuangling , Zhai Wenhui , Wang Meijiao , Ran Lin
Published: August 2022

Background. Endocrine disorders such as amenorrhea, lactation, and irregular menstruation caused by antipsychotics are common in female patients. How to reduce or eliminate these adverse reactions is a matter of concern. Objective. To evaluate the therapeutic effect of progesterone in combination with vitamin B6 in the treatment of antipsychotic-induced amenorrhea. Methods. In our hospital, from May 2019 to May 2021, 120 patients with amenorrhea caused by antipsychotics who underwent surgery were selected for this prospective study. The random residue grouping method divided them into a progesterone group (60 cases) and a vitamin B6 group (60 cases). Among them, the progesterone group was treated only with progesterone, while the vitamin B6 group was given progesterone in combination with vitamin B6. The differences in endocrine index, prolactin, uterine size, and endometrial thickness, effectiveness, and safety analysis of the progesterone and vitamin B6 groups of patients were observed and compared. Results. Before treatment, there was no change in the comparison of endocrine indexes between the progesterone and vitamin B6 groups (

P
>
0.05

). After 1 month of treatment, there were significant differences in estradiol, prolactin, and follicle-stimulating hormone between the progesterone and vitamin B6 groups of patients (

P
<
0.05

). After 1 month of treatment, there were significant differences in prolactin, uterine size, and endometrial thickness, and the vitamin B6 group was significantly lower than the progesterone group (

P
<
0.05

). The clinical efficiency of 95.00% in the vitamin B6 group was significantly higher than 83.33% in the progesterone group (

P
<
0.05

). There were no adverse reactions in the progesterone and vitamin B6 groups. Conclusion. The effectiveness of progesterone combined with vitamin B6 in treating amenorrhea caused by antipsychotics is significantly better than simple progesterone, which can effectively improve the endocrine condition of patients and provide a reference for the clinical treatment of amenorrhea caused by antipsychotics.
Recycling Performance of the Tire Remanufacturing with Production Capacity Constraints considering Carbon Tax and Technology Subsidy
Authors: Hu Ruiqi
Published: August 2022

After considering the manufacturer’s production capacity constraints and market preference, this paper presents a closed-loop supply chain of automotive tires which consists of a remanufacturer, a retailer, and a recycler, where used tires are collected and reused. Based on the features of the closed-loop tire remanufacturing supply chain, four Stackelberg models are developed to investigate the influences of the carbon tax and the technology subsidy on recycling performance. The result shows that the carbon tax is conducive to improving the remanufacturing technology level and reducing emissions, but it reduces the profit of the manufacturer and the retailer. A subsidy can make up for their loss by the carbon tax. Moreover, an allied decision of the chain’s members can help them gain economic benefits, while an independent decision can improve environmental benefits.
Failure Mechanism of Anchored Rock under Constant Resistance Values of Cable Based on Particle Flow Code
Authors: Sun Xiaoming , Cui Li , Zhang Yong , Jiang Zuoxun , Wang Lei
Published: August 2022

Focusing on a constant resistance (CR) cable, using particle flow code (PFC) software, the constant resistance characteristics of the cable are replaced by the servo control of the pallet, and the compressive mechanical properties of rock anchored on the free surface of a tunnel under different constant resistance values (CRVs) are studied. The results show that (1) during the compression failure process of the anchored rock, the stress-strain curve has a “double peak” feature, and the number of cracks has a “step” feature. The mutation point of the number of cracks corresponds to the two peak points of the stress-strain curve. (2) When the constant resistance value of the pallet is approximately 70%-80% of the absolute rigid support strength, the anchored rock has the maximum compressive strength, most stable deformation, maximum pallet energy absorption effect, and minimum number ratio of tensile-shear cracks. The mechanical properties of the CR-anchored rock are the best. (3) According to the different failure forms, the failure types of anchored rock under different CRVs are divided into the overall single-arch collapse type, connected double-arch collapse type, nonconnected double-arch collapse type, and local single-arch collapse type. The research results provide a reference for the design of a CRV and collapse prediction of the anchored surrounding rock.
A Plain Bayesian Algorithm-Based Method for Predicting the Mental Health Status and Biomedical Diagnosis of University Students
Authors: Wang Jiao
Published: August 2022

The purpose of this study was to assess e-learning during Corona epidemic regarding advantages, limitations, and their recommendations for managing learning during the epidemic. Based on a case study, this study used qualitative research. Sixteen students from King Saud University’s College of Education were invited to take part. These students receive their online lectures via the “Zoom” application. A 20-minute WhatsApp one-on-one semiorganized interview was likewise utilized. To guarantee the reliability, iCloud was utilized to record gatherings and meetings for direct record (adaptability, constancy, confirmability, and validity). Results were presented in three themes: advantages of employing distance education, limitations of usages, and recommendations for improvements. Analyzing the feedbacks collected from students by the four interviewers, important characteristics of distance education emerged. They were student-centered learning, which included: comfortable, self-directed learning, asynchronous learning, and flexibility. The most common limitations associated with distance education, in general, included inefficiency, that is, lack of student feedback, and lack of attentiveness. As for recommendations for improvements the most obvious characteristics that became evident in students’ responses were teaching and assessment and quality enhancement.
DEERE: Document-Level Event Extraction as Relation Extraction
Authors: Li Jian , Hu Ruijuan , Zhang Keliang , Liu Haiyan , Ma Yanzhou
Published: August 2022

The descriptions of complex events usually span sentences, so we need to extract complete event information from the whole document. To address the challenges of document-level event extraction, we propose a novel framework named Document-level Event Extraction as Relation Extraction (DEERE), which is suitable for document-level event extraction tasks without trigger-word labelling. By well-designed task transformation, DEERE remodels event extraction as single-stage relation extraction, which can mitigate error propagation. A long text supported encoder is adopted in the relation extraction model to aware the global context effectively. A fault-tolerant event integration algorithm is designed to improve the prediction accuracy. Experimental results show that our approach advances the SOTA for the ChFinAnn dataset by an average F1-score of 3.7. The code and data are available at https://github.com/maomaotfntfn/DEERE.
Clinicopathological Characteristics and Curative Effect of Lymphoma Based on Sampling Theory
Authors: Ding Shuxiang
Published: August 2022

With the continuous development of society, people’s attention to the body is also increasing. This article explains and analyzes the clinicopathological characteristics of a more serious disease, lymphoma, and the effect of treatment. In the previous studies of this type of disease, the collected data was very limited, and the theory for data analysis was also lacking. The direct result was that the analysis of such disease types was not complete, and it was difficult to obtain statistical significance, which made the clinical guidance weak. In order to improve this problem, this paper applies the sampling theory in statistics to the clinicopathological characteristics of lymphoma and the effect of treatment. Through the scientific analysis of such samples, it is hoped to provide some ideas for clinical treatment. In the sampling theory, this paper selects two methods, Bayesian algorithm and adaptive sampling theory, and introduces the corresponding methods for the correlation analysis of the clinicopathological characteristics and curative effect of lymphoma according to the above two methods. These related processing methods start from a large number of samples and provide sufficient computational support for the final experiments. Experiments show that the score of clinical symptoms of lymphoma is not less than 96%, which means that the patient is in a state of recovery. When the evaluation score is between 63% and 96%, the corresponding treatment has a significant effect. These results show that, in the analysis of the clinicopathological characteristics of lymphoma and related treatment effects, by using the Bayesian algorithm in the sampling theory and the adaptive sampling theory, the data results can well correspond to the clinical effects.
Building a Smart City Planning System Integrating Multidimensional Spatiotemporal Features
Authors: Lu Jing
Published: August 2022

With the development of mobile communication technology and the popularization of mobile devices, the connection between people has become increasingly close, the data circulating between them have increased rapidly, and the multidimensional space-time characteristics have gradually entered the stage of the times. The proposal of the basic smart city system is a revolution in the concept of urban construction. A smart city is both an opportunity and a challenge for the urbanization process. By analyzing the multidimensional spatiotemporal feature engineering, this paper studies the development trend of smart cities and discusses how multidimensional spatiotemporal features play a fundamental role in the smart city system.
Digital Modeling System for Dynamic Nonlinear Systems of Power Equipment in Digital Grids and 5G
Authors: Li Siming , Guo Wei , Yan Qing , Wang Guoshi , Liu Ying , Zhang Yingbin , Zeng Zhixiang
Published: August 2022

The digital power grid system is used to maintain stability and to provide a continuous supply of electrical energy to consumers in the event of a power outage or other interruption of service. This is due to their ability to respond quickly in the event of an interruption. However, unpredictable failures and cascading accidents occur regularly, resulting in a blackout that can cause significant disruption to modern life. Furthermore, the rotor angle behavior can indicate the overall synchronism and stability of the complete digital power grid system. The digital dynamic nonlinear system operators can profit economically and technically from implementing protection measures that are appropriately designed and implemented. This study has utilized data transitions over digital power grids, connectivity used in digital power grids, power quality, network congestion, and stability issues as independent variables. However, the digital dynamic nonlinear system has been used as the dependent variable. The data was collected using questionnaires, and the data was collected from various digital power grids and solar system users. The collected data was analyzed by using SEM PLS 3. The reliability of the collected data was tested by Cronbach’s alpha and the values above 0.7. The results indicated that there are significant values between the variables.
Intelligent Decision Making for Constructing Students’ Entrepreneurship System in Colleges and Universities
Authors: Liu Cui
Published: August 2022

In order to test the efficiency of colleges and universities to carry out innovation and entrepreneurship education and cultivate the innovative talent system required by economic and social development and change, this paper proposes to combine the fuzzy comprehensive evaluation method based on the analytic hierarchy process. First, gather the students’ ideas, then create a set of measures for each measure, count the weight and significance of each measure, and create a set of criteria for the assessment of the educational process of innovation and entrepreneurship. Census of colleges and universities’ innovation and business measurement model based on student perceptions and determining the weight of each measurement scale will help students understand what is more important in evaluating college and universities’ innovation and business education. Other metrics include innovation and training market, it needs approach, design industry analysis examines business, opportunities for school-to-business engagement, innovation, business education, training, entrepreneurship, and platform information. Therefore, in order to improve the innovation and business education of colleges and universities, it is necessary to carefully establish school management, faculty, classes, activities, innovation, business platform, business education environment, support, advocacy mechanism, and so on. We will improve the teaching of innovation and entrepreneurship and focus on training faculty of innovation and business education and focus on strengthening the innovation and entrepreneurship information platform, innovation, and entrepreneurship incubation base.
Altered Functional Connectivity in Pain-Related Brain Regions and Its Correlation with Pain Duration in Bone Metastasis with Cancer Pain
Authors: Zhou Xiaoyu , Tan Yong , Chen Jiao , Wang Chengfang , Tang Yu , Liu Jiang , Lan Xiaosong , Yu Hong , Lai Yong , Hu Yixin , Zhang Jing , Cao Ying , Liu Daihong , Zhang Jiuquan
Published: August 2022

Bone metastatic pain is thought to be a severe type of cancer pain that has refractory characteristics and a long duration. This study is aimed at exploring the brain functional connectivity (FC) pattern in lung cancer patients with bone metastatic pain. In this study, 27 lung cancer patients with bone metastatic pain (CP+), 27 matched lung cancer patients without pain-related complaints (CP−), and 27 matched healthy controls (HC) were recruited. All participants underwent fMRI data acquisition and clinical assessments. One-way ANOVA or a Mann–Whitney

U

test was applied to compare clinical data according to data distribution. Seventeen hypothesis-driven pain-related brain regions were selected as regions of interest (ROIs). FC values among pain-related brain regions across the three groups were computed by using ROI–ROI functional connectivity analysis. ANCOVA with a post hoc test was applied to compare FC differences among the three groups.

p
<
0.05

indicated statistical significance. Correlation analysis was conducted to explore the potential relationship between the FC values and clinical characteristics. Except for years of education, no significant differences were revealed among the three groups in age, gender, or neuropsychological assessment. In the CP+ group, FC alterations were mainly concentrated in the dorsal lateral prefrontal cortex (DLPFC), anterior cingulate cortex (ACC), secondary somatosensory cortex (SII), and amygdala compared to the CP− group. Among these brain regions with statistical differences, FC between the right DLPFC and the right ACC showed a positive correlation with the duration of cancer pain in the CP+ group. In addition, in the CP− group, altered FC was found in the bilateral SII, ACC, and thalamus compared to the HC group. Altered FC in pain-related brain regions may be a brain pattern of bone metastatic pain and may be associated with the long duration of cancer pain.
Physicochemical Properties and Antibacterial Activity of Gellan Gum Incorporating Zinc Oxide/Carbon Nanotubes Bionanocomposite Film for Wound Healing
Authors: Liu Jichao , Ismail Nur Arifah , Yusoff Mahani , Razali Mohd Hasmizam
Published: August 2022

Wound healing dressing based on a natural polymer of gellan gum incorporating zinc oxide nanoparticles and multiwall carbon nanotubes (GG/ZnONP + MWCNT) bionanocomposite film was fabricated via the solution casting method. The physicochemical properties of the film were characterized using X‐ray diffraction (XRD), Fourier transform infrared (FTIR), and scanning electron microscopy (SEM). Moreover, the antibacterial properties of the bionanocomposite film were investigated for wound healing applications. The characterization results confirmed the reinforcement of the gellan gum (GG) matrix with zinc oxide nanoparticles (ZnONP) and multiwall carbon nanotubes (MWCNT), as an amorphous GG/ZnONP + MWCNT bionanocomposite film was obtained. SEM morphological analysis shows that the addition of ZnONP and MWCNT nanofillers changed the film microstructure into a sponge‐like structure that is more suitable for fluid uptake and thus more useful for wound healing. The GG/ZnONP + MWCNT bionanocomposite film demonstrated good antibacterial activity against all strains tested. Furthermore, macroscopic analysis shows that the wound treated with GG/ZnONP + MWCNT bionanocomposite film recovered completely (100%) in 14 days, compared to pure GG film (90.76%) and negative control (77.40%). As a result, the GG/ZnONP + MWCNT bionanocomposite film could be a promising wound dressing material.
Design of Digital Teaching Platform for Spoken English Based on Virtual Reality
Authors: Bao Shijun
Published: August 2022

In order to improve the effect of digital teaching of spoken English, this paper combines virtual reality technology to design a digital teaching platform for spoken English and combines virtual reality technology to digitally process spoken English. The signal processed by the front-end amplifier circuit is converted into a digital signal through analog-to-digital conversion, and the digital receiving system is realized by means of software radio, which reduces the dependence on the hardware circuit and enhances the portability of the system. In addition, this paper selects filters according to the needs of digital teaching of spoken English and constructs a digital teaching platform for spoken English based on virtual reality. The experiment verifies that the digital teaching platform for spoken English based on virtual reality has a good effect of digital spoken English teaching.
Metagenomics Analysis of Microbial Species and Antibiotic Resistance Genes (ARGs) in Untreated Wastewater from Different Types of Hospitals in Hangzhou
Authors: Chen Song , Zhou Yi , Song Lu , Yang Yanli , He Fuming , Chen Qianming , Cheng Xi
Published: August 2022

Antibiotic resistance genes (ARGs) are contaminants that can propagate through a variety of environmental media. They contribute to an increase in the number of antibiotic-resistant microbes and thereby pose a danger to human health. Discharge from hospitals is the most significant contributor of ARGs and antibiotic-resistant bacteria to the natural environment. A comprehensive understanding of the microbiological structure and the distribution of ARGs in hospital wastewater can facilitate appropriate treatment of such wastewater and can improve our understanding of the pathophysiology of several epidemic illnesses. In this work, metagenomics techniques were used to compare the microbial species and ARGs in a control group with those in untreated wastewater from three types of hospitals (a general hospital, a hospital of traditional Chinese medicine, and an oral specialty hospital). The microbiota found in the hospital wastewater represented 6,415 species and 244 phyla. The composition of the bacterial community in the wastewater from the three hospitals was significantly different from that in the control group. The ARGs in the samples were also analyzed using the Antibiotic Resistance Genes Database (ARDB) and Comprehensive Antibiotic Resistance Database (CARD). Finally, the link between abundant species and ARGs in the samples was examined. The findings of this study indicate that a connection exists between the microbial species and the ARG composition found in the wastewater samples. A variety of distinct genera of ARGs, each having their own unique correlations, have been found in wastewater from various hospitals. Consequently, the ARGs and microbial species found in the untreated wastewater from various hospitals have unique characteristics. Therefore, more detailed protocols need to be established to treat wastewater from various types of hospitals. Further studies should examine whether a connection exists between the various microbial species found in the wastewater of various types of hospitals and certain illnesses.
Properties of Meromorphic Spiral-Like Functions Associated with Symmetric Functions
Authors: Breaz Daniel , Cotîrlă Luminița-Ioana , Umadevi Elangho , Karthikeyan Kadhavoor R.
Published: August 2022

To consolidate or adapt to many studies on meromorphic functions, we define a new subclass of meromorphic functions of complex order involving a differential operator. The defined function class combines the concept of spiral-like functions with other studies pertaining to subclasses of multivalent meromorphic functions. Inclusion relations, integral representation, geometrical interpretation, coefficient estimates and solution to the Fekete-Szegö problem of the defined classes are the highlights of this present study. Further to keep up with the present direction of research, we extend the study using quantum calculus. Applications of our main results are given as corollaries.
Intelligent Optimization Method of Resource Recommendation Service of Mobile Library Based on Digital Twin Technology
Authors: Shang Shanshan , Yu Zikai , Geng Aili , Xu Xiuxiu , Ma Huizhen , Wang Guozhong
Published: August 2022

In order to improve the Resource Recommendation and sharing ability of mobile library, an intelligent optimization model of Mobile Library Resource Recommendation Service Based on digital twin technology is proposed. Build the association rule feature distribution set of mobile library resource recommendation service, carry out text information retrieval in the process of Mobile Library Resource Recommendation and sharing, carry out semantic correlation feature registration according to the retrieval preference of mobile library reading user object, establish the association rule data set of mobile library reading user object preference for mobile library Resource Recommendation and sharing, carry out feature block processing, and analyze the library reader preference. Complete the collaborative filtering recommendation of Mobile Library Resource Recommendation sharing. The simulation results show that the collaborative recommendation under the intelligent optimization mode of mobile library resource recommendation service using this method has high accuracy and good confidence level, which improves the intelligent level of Mobile Library Resource Recommendation and user satisfaction.
Generative Adversarial Network Combined with SE-ResNet and Dilated Inception Block for Segmenting Retinal Vessels
Authors: Yue Chen , Ye Mingquan , Wang Peipei , Huang Daobin , Lu Xiaojie
Published: August 2022

This study develops an accurate method based on the generative adversarial network (GAN) that targets the issue of the current discontinuity of micro vessel segmentation in the retinal segmentation images. The processing of images has become increasingly efficient since the advent of deep learning method. We have proposed an improved GAN combined with SE-ResNet and dilated inception block for the segmenting retinal vessels (SAD-GAN). The GAN model has been improved with respect to the following points. (1) In the generator, the original convolution block is replaced with SE-ResNet module. Furthermore, SE-Net can extract the global channel information, while concomitantly strengthening and weakening the key features and invalid features, respectively. The residual structure can alleviate the issue of gradient disappearance. (2) The inception block and dilated convolution are introduced into the discriminator, which enhance the transmission of features and expand the acceptance domain for improved extraction of the deep network features. (3) We have included the attention mechanism in the discriminator for combining the local features with the corresponding global dependencies, and for highlighting the interdependent channel mapping. SAD-GAN performs satisfactorily on public retina datasets. On DRIVE dataset, ROC_AUC and PR_AUC reach 0.9813 and 0.8928, respectively. On CHASE_DB1 dataset, ROC_AUC and PR_AUC reach 0.9839 and 0.9002, respectively. Experimental results demonstrate that the generative adversarial model, combined with deep convolutional neural network, enhances the segmentation accuracy of the retinal vessels far above that of certain state-of-the-art methods.