bluuebunny/crossref_metadata_2025 huggingface dataset:
Soft Landing Parameter Measurements for Candidate Navigation Trajectories Using Deep Learning and AI-Enabled Planetary Descent
Authors: Borse Janhavi H. , Patil Dipti D. , Kumar Vinod , Kumar Sudhir
Published: August 2022

Smart instruments, sensors, and AI technologies are playing an important role in many fields such as medical science, Earth science, astronomy physics, and space study. This article attempts to study the role of sensors, instruments, and AI (artificial intelligence) based smart technologies in lunar missions during navigation of trajectories. Lunar landing missions usually divide the power descent phase into three to four sub-phases. Each sub-phase has its own set of initial and final constraints for the desired system state. The landing systems depend on human competencies for making the most crucial landing decisions. Trajectory planning and designing are very significant in lunar missions, and it requires inputs with precision. The manual systems may be prone to errors. In contrast, AI and smart sensor-based measurements give an accurate idea about the trajectory paths and make appropriate decisions where manual systems may turn into disasters. The manual systems are either pre-fed or have manual controls to guide the trajectory. For autonomous landing problems, trajectory design is a very crucial task. The automated trajectories play a vital role in the measurement and prediction of landing state parameters of the space rocket. Nowadays, sensors, intelligent instruments, and the latest technologies go hand in hand to devise measurement methods for accurate calculations and make appropriate decisions during landing space rockets at the designated destination. Space missions are very expensive and require huge efforts to design smart systems for navigation trajectories. This paper attempts to design all possible candidates of reference navigation trajectories for autonomous lunar descent by employing 3D non-linear system dynamics with randomly chosen initial state conditions. The generated candidates do not rely on multiple hops and thus exhibit an ability to serve autonomous missions. This research work makes use of smart sensors and AI federated techniques for smartly training the system to serve the ultimate purpose. The trajectories are simulated in an automated simulating environment to perform exhaustive analyses. The results accurately approximate the trajectories analogous to their numerical counterparts and converge to their measured final state estimates. The generation rate of feasible trajectories measures the accuracy of the algorithm. The algorithm’s accuracy is near 0.87 for 100 sec flight time, which is reasonable.
Research on Optimization of Cross-Border e-Commerce Logistics Distribution Network in the Context of Artificial Intelligence
Authors: Shi Jihua
Published: August 2022

The continuous innovation of artificial intelligence technology has led to industrial upgrading and industry transformation in various industries, and e-commerce logistics has borne the brunt. Artificial intelligence relies on the intelligence of a large number of operations and decisions in the process of logistics operations, as well as the integration of transport, storage, distribution, packaging, loading and unloading, and other aspects of the production process and the hierarchy of the system, which has become an important engine to promote the upgrading of logistics equipment and technology, the innovation of production links and processes, the change in the structure of supply and demand of traditional logistics jobs, and the renewal of the traditional form of logistics. The application of artificial intelligence and the development of a new generation of information technology, including big data, has opened the era of intelligent logistics. And the continuous deepening of China’s foreign trade makes the demand for cross-border e-commerce logistics surge, and the importance of cross-border e-commerce logistics has been rapidly highlighted. Hence, it becomes urgent to construct a cross-line Internet business coordinated operations improvement model by consolidating man-made consciousness innovation. In view of investigating the activity techniques of cross-line online business coordinated factors, this paper advances the improvement methodology of cross-line web-based business operations advancement way with regard to man-made reasoning. By concentrating on the ongoing circumstance and issues of cross-line web-based business coordinated factor circulation module and consolidating the idea of wise strategies, the appropriation stage, the way transportation stage, and freight conveyance phase of Internet business coordinated factor dissemination activity are advanced, in order to accomplish the motivation behind lessening the expense of end dispersion, working on the effectiveness of dissemination, and expanding consumer loyalty.
Mechanism and Numerical Simulation of Vertical Fracture Propagation in Composite Coal Rock
Authors: Zhang Fan , Wan Hanjin , Liu Yan , Li Shuwei , Li Zijiang
Published: August 2022

Vertical fracture propagation mechanism is important to understand the effect of hydraulic fracturing on the roof of outburst coal seams. In this paper, the differences in physical parameters and in situ stress between an outburst coal seam and its roof strata were compared, and influencing factors of roof-fracturing fractures connecting coal seams were vertically analyzed. The impact of different fracturing strata and injection rates on fracture propagation was studied by numerical models. Results show that the horizontal principal stress of an outburst coal seam is less than that of roof strata, and the fracture length of roof fracturing is larger than that of an outburst coal seam. Roof-fracturing fracture of an outburst coal seam has the material conditions to communicate downward with the coal seam. The downward propagation height of roof-fracturing fracture is positively correlated with the minimum horizontal stress difference between an outburst coal seam and its roof strata. Soft coal fracturing cannot form a long fracture dominated by tensile failure, so the coal seam can be communicated by transforming the roof strata of soft coal to form vertical fractures. The injection rate affects the failure location, fracture width, and fracture-propagation path of the numerical model. Construction parameters should be reasonably designed in accordance with the physical parameters of coal and rock, construction displacement, and in situ stress. These research results can provide a theoretical basis and data support for the design, and optimization of construction parameters of roof fracturing in outburst coal seams.
Improving Image Quality and Reducing Scan Time for Synthetic MRI of Breast by Using Deep Learning Reconstruction
Authors: Li Jian , Wu Lin-Hua , Xu Meng-Ying , Ren Jia-Liang , Li Zhihao , Liu Jin-Rui , Wang Ai Jun , Chen Bing
Published: August 2022

Objectives. To investigate a deep learning reconstruction algorithm to reduce the time of synthetic MRI (SynMRI) scanning on the breast and improve the image quality. Materials and Methods. A total of 192 healthy female volunteers (mean age: 48.1 years) underwent the breast MR examination at 3.0 T from September 2020 to June 2021. Standard SynMRI and fast SynMRI scans were collected simultaneously on the same volunteer. Deep learning technology with a generative adversarial network (GAN) was used to generate high‐quality fast SynMRI images by end‐to‐end training. Peak signal‐to‐noise ratio (PSNR), mean squared error (MSE), and structural similarity index measure (SSIM) were used to compare the image quality of generated images from fast SynMRI by deep learning algorithms. Results. Fast SynMRI acquisition time is half of the standard SynMRI scan, and the generated images of the GAN model show that PSNR and SSIM are improved and MSE is reduced. Conclusion. The application of deep learning algorithms with GAN model in breast MAGiC MRI improves the image quality and reduces the scanning time.
Analysis of the Impact of Artificial Intelligence Technology‐Assisted Environmental Protection on the Integrity of Chinese Painting
Authors: Hu Zhen-jiang
Published: August 2022

Han painting is an important art display form in Chinese history; it has a history of hundreds of years. It is the embodiment of a higher level of Chinese painting. Han paintings can also show the development of China’s political economy and culture. However, with the continuous progress of time, the patterns of Han paintings and the color characteristics of Han paintings will be greatly damaged. This limits people’s research on the civilization displayed by Han paintings. At the same time, changes in the environment also have a great relationship with the integrity of Chinese painting. Therefore, the study of the impact of environmental protection on the integrity of Han paintings is crucial to the study of Chinese civilization. It is difficult for traditional research methods to discover the quantitative relationship between environmental protection and the integrity of Han paintings. In this study, the atrous convolutional neural network (ACNN) in the artificial intelligence method and the GRU method were used to explore the relationship between environmental protection and the patterns, colors, and shapes of Chinese paintings. The research results show that the ACNN method and the GRU method can better predict the patterns, shapes, and color characteristics of Chinese paintings. Through research, it can also be found that the color and pattern features of Chinese paintings contain obvious time characteristics, which requires the GRU method for feature extraction. The prediction errors of ACNN and GRU in predicting the integrity of Chinese paintings are all within 2.5%, and the largest prediction error is only 2.45%.
Histone Deacetylase Inhibitor I3 Induces the Differentiation of Acute Myeloid Leukemia Cells with t (8; 21) or MLL Gene Translocation and Leukemic Stem-Like Cells
Authors: Zhao Mengjie , Duan Yu , Wang Jiangyun , Liu Yong , Zhao Yao , Wang Haihua , Zhang Lei , Chen Zhe-Sheng , Hu Zhenbo , Wei Liuya
Published: August 2022

Acute myeloid leukemia (AML) is a heterogeneous disorder characterized by the clonal expansion and differentiation arrest of leukemic cells in peripheral blood and bone marrow. Though the treatment using cytarabine-based protocol for AML patients with t (8; 21) translocation has improved the 5-year overall survival rate, drug resistance continues to be the principal limiting factor for the cure of the disease. In addition, very few AML patients with mixed lineage leukemia gene rearrangements (MLLr) have a desirable outcome. This study evaluated the cell differentiation effect of a potent HDAC (histone deacetylase) inhibitor, I3, and its possible mechanism on the AML cells with t (8; 21) translocation or MLLr and leukemic stem-like cells (Kasumi-1, KG-1, MOLM-13, and THP-1). I3 exhibited efficient anti-proliferative activity on these cells via promoting cell differentiation, accompanied by the cell cycle exit at G0/G1. Importantly, I3 showed the properties of HDAC inhibition, as assessed by the acetylation of histones H3 and H4, which resulted in blocking the activation of the VEGF (vascular endothelial growth factor)-MAPK (mitogen-activated protein kinase) signaling pathway in the Kasumi-1 cell line. These data demonstrate that I3 could be a potent chromatin-remodeling agent to surmount the differentiation block in AML patients, including those with t (8; 21) translocation or MLLr, and could be a potent and selective agent for AML treatment.
Research on Knowledge Management of Intangible Cultural Heritage Based on Linked Data
Authors: Huang Zhaoyan , Xu Tao
Published: August 2022

At present, the protection of intangible cultural heritage has received more and more attention from all levels of society. Intangible cultural heritage is a treasure of national culture. It is an indispensable part of Chinese civilization, the crystallization of the wisdom of Chinese civilization, and represents the country’s soft power. The effective organization and management of intangible cultural heritage knowledge is the premise and foundation for the protection, dissemination, and inheritance of intangible cultural heritage. Ontology and linked data technology provide a new method and realization path for the organization and management of intangible cultural heritage knowledge. In this paper, the intangible cultural heritage knowledge is organized reasonably semantically based on the method of linked data, and the purpose is to use the structure of linked data to express the resource data of different structures in a structured manner. This paper first introduces the meaning and background of the research and analyzes the relevant research at home and abroad. Second, it introduces the related knowledge of linked data, analyzes and sorts out the elements and semantic relationship of knowledge in the field of intangible cultural heritage, and designs and constructs the ontology model of intangible cultural heritage knowledge, Finally, based on linked data technology, the process of intangible cultural heritage knowledge organization and linked data set construction is studied, including key steps such as entity to RDF, entity association, linked data storage, and publication. The application of linked data technology in the field of intangible cultural heritage knowledge organization and management can promote the standardization and standardization of intangible cultural heritage knowledge management and is of great significance to the protection and inheritance of my country’s intangible cultural heritage culture.
Built-In Calibration Standard and Decision Support System for Controlling Structured Data Storage Systems Using Soft Computing Techniques
Authors: Chandran George Chellin , Synthia Regis Prabha D. M. Mary , Malathi P. , Kapila Dhiraj , Arunkumar M.S. , Verma Devvret , Teressa Dawit Mamiru
Published: August 2022

Several research that assesses, or assess computer systems has been undertaken in previous decades. Choosing an appropriate DBMS system in a computer application, though, was never completely arbitrary, based on the professional study. Developing a viable answer for such a challenge depending on business goals and needs from judgment necessitates a thorough study on information access as well as comprehensive professional evaluation. The research presents a DSS to help non-kinetics discover their proper DBMS solutions and otherwise information retention types faster. This suggested DSS is unique in that it uses MoSCoW to evaluate criterion weighting or deliberate, as well as assessment frameworks for quantifying overall levels of quasi criterion and ISO/IEC qualitative features to show the link between criterion based upon industry specialists’ expertise. Companies that produce programs have difficulty integrating new innovations, such as Internet computing or information management platforms, into their operations. Because computer engineers and top programmers are usually specialists in their field, users need to consult or train other professionals. Therefore, computer development is an appropriate area for implementing judgment support technologies that can proactively help this prediction to choose the best technologies for their products. We offer a decision support system (DSS) to assist in the selection of the best appropriate information architecture. According to both example reports and specialists, this technique improves visibility into the choice method gives a deeper prioritized choice range than if customers have conducted their study individually, or saves the duration and expense of the judicial procedure.
Influence of Nanosilica Particle Addition on Mechanical and Water Retention Properties of Natural Flax- and Sisal-Based Hybrid Nanocomposites under NaOH Conditions
Authors: Natrayan L. , Veeman Dhinakaran , Baskara Sethupathy S. , Sekar S. , Patil Pravin P. , Velmurugan G. , Mekonnen Hulusew Ferede
Published: August 2022

Organic filament-based lightweight materials are increasingly being used because of their high strength-to-weight ratio, recyclability, and low cost. The application of nanofillers in addition to natural fibres is a fascinating one. The main purpose of the current experimental investigation is to manufacture and estimate the mechanical material of nanocomposites. Natural fibres like flax and sisal are used as reinforcement; nanosilica particles act as fillers, and epoxy resin as a matrix. The composites were created using the Taguchi L9 orthogonal array and a hand lay-up technique. The mechanical and water retention behaviour of the hybrid composites is based on the following three parameters, each with three different levels: (i) adding different weight ratios of nanofiller (1.5, 3, and 4.5 wt%), (ii) weight ratio of reinforcements (20, 30, and 40 wt%), and (iii) duration of NaOCl conditions (2, 4, and 6 hours). Mechanical possessions like tension, bending, and impact were tested as per the ASTM standard. The tested composites show that 30 wt% reinforcement, 3 wt% nanosilica, and 4 hours of alkaline processing provide the best materials and aquatic preoccupation belongings. When compared to nanofiller composites, nanoparticle-filled composites have 17% evolution in tension, 22% upsurge in flexural strength, 13% in impact strength, and 36% increase in impact strength hygroscopic behaviour. Scanning electron microscopes were used to analyze the fractured structure of hybrid composites. Compared to 1.5 and 4.5 wt% of nanofiller, the 3 wt% of filler provides high interfacial adhesion to the hybrid composites. It helps the reinforcement and matrix to contact each other.
Six Genes Associated with Lymphatic Metastasis in Colon Adenocarcinoma Linked to Prognostic Value and Tumor Immune Cell Infiltration
Authors: Wang Baoquan , Yin Changjun , Yang Xu , Shi Huibo , Zhang Zheng , Zhou Jun , Zhang Peitong
Published: August 2022

Objective. The aim of the study is to explore the relationship between lymphatic metastasis genes, prognosis, and immune cell infiltration in patients with colon cancer. Methods. Based on the Cancer Genome Atlas Program (TCGA) database, differentially expressed genes and prognostic genes related to colon adenocarcinoma (COAD) lymphatic metastasis were screened and intersected. We used lasso and univariate Cox regression analysis to screen core genes and establish a preliminary prediction model. GO and KEGG enrichment analysis was used for lymphatic metastasis-related genes, and single GSEA was used for the final screening results. Finally, we evaluated the relationship between identified genes and immune cell infiltration. Results. A total of 1727 genes were differentially expressed between COAD patients with TNM stages of N0 and N1. After further screening, six core genes (RNU4-2, ZNF556, RNVU1-15, NSA2P6, RN7SL767P, and RN7SL473P) were obtained, and a preliminary prediction model was established, in which ZNF556 was a risk factor, and the rest were protective factors. Single GSEA showed that pathways such as systemic lupus erythematosus might play an important role in the initial lymphatic metastasis of COAD. GO and KEGG enrichment analysis of 1727 genes supported this result. Immune infiltration analysis showed that six genes were significantly correlated with T cell and NK cell families. Conclusion. Six core genes may affect COAD initial lymphatic metastasis through the systemic lupus erythematosus pathway and immune cell infiltration.
Construction of Multimedia English Teaching Resource Base Based on K-Means Clustering Algorithm
Authors: Yan Jinyan , Wu Lianfang , Wang Qinghong
Published: August 2022

Because of the explosive development of the Internet today, network education resources are becoming more and more valuable, and so is the rapid development of the information teaching environment. Let us pay more attention to the construction of teaching resources. In order to help schools improve the quality of teaching and promote the reform of basic education in China, the teaching resource bank must be enriched in connotation and perfect in function. However, the current teaching database is still facing some difficulties in the construction process, such as insufficient information, and database content structure relative disorder. In fact, the progress of computer technology is likely to help overcome the above difficulties, but there are still some problems in the construction process of the current teaching resource database, such as the connotation of teaching resources is not full, the organization structure of the content of the education resource database is relatively messy. The development of computer technology is likely to help solve the above problems. Therefore, the research on constructing the service system using computer technology has become a very key and hot topic today. Based on the current situation of resource library construction and the classification and summary of some technical problems, the author of this study puts forward a set of methods and procedures for the construction of a multimedia English teaching resource library. An improved hybrid clustering algorithm ISPO + K-means was proposed to integrate PSO and K-means. Compared with other algorithms, the algorithm clustering results are better. Based on this process, this study can automatically sort and classify the collected learning resources, reduce the consumption of manpower and material resources, and improve the service efficiency of the resource library. The purpose of this study is to find the methods that can use information technology to serve the construction of a multimedia English teaching resource bank, hoping to provide a valuable reference for the related research on the construction of teaching resource bank.
Automatic Cutting System Design of Robot Hand Based on Stereo Vision
Authors: Mei Hongbiao , Li Zhongping , Zou Chunhong
Published: August 2022

At present, the pouring riser of valve castings is mainly removed by manual cutting, polluting the environment and causing harm to the human body with a low efficiency. Therefore, an automatic cutting pouring riser method using the stereo vision system and manipulator is proposed. The relative position of the valve casting and the end of the manipulator is obtained through the position transformation of the valve casting coordinate system, the manipulator end of the coordinate system, and the camera coordinate system. The spatial motion trajectory of the manipulator is planned, implementing automatic pouring riser cutting of the same valve casting with the same pose. The experimental results show that the position deviation and the angle deviation of the repetitive positioning accuracy and the random positioning accuracy of the visual system are within ±1 mm and ±1°; in the pouring riser cutting test, the maximum deviation between the actual cutting trajectory and the theoretical cutting trajectory is 3 mm. In summary, the method shows a good reliability and could meet the requirements of cutting accuracy.
Application of VR Virtual Reality in the Course of Later Stage and Special Effect Production
Authors: Wang Dong
Published: August 2022

Special Effect Production (SFP) is a picture or sound that is generated in television, radio, or movies to depict something genuine (such as an explosion) or fictional (such as a monster), a movie featuring stunning special effects. It is a moment when the organization or product is nearing its completion of development, referred to as late-stage. Virtual reality (VR) uses computer technology to produce interactive virtual experiences that may be watched via a head-mounted display. The ability to immerse users within a virtual environment has the potential to provide a more immersive experience than what can be achieved with a “conventional” flat screen. Some problems are pyrotechnics, prosthetic makeup, animatronics, and live-action weather elements. All the drawbacks are rectified by the method of SFP-VR computer-generated world in which the user’s activities have a small significant impact on what occurs around them; the virtual reality used to construct or get access to virtual reality. When it comes to showcasing your products, high-quality VR/AR material elevates the experience to new heights. Showing off your goods and services in this manner is a fun approach to engage customers and make purchasing a more enjoyable experience for everyone involved. Customers are able to experience the information in a more immersive and emotional way because of this. Various steps of the manufacturing process, such as original design, fabrication, and testing, were incorporated into a desktop VR demonstration application intended to show how a consumer product is made. Demonstrations of the programmer are given in detail, and user feedback is included. It is incredible how quickly virtual worlds have gained traction as a viable tool for manufacturing and other sectors of the economy. As a result, curriculum implementation refers to the teacher’s translation of the planned or formally designed course of study into syllabuses, schemes of work, and lessons for consumers. The planned adjustments are brought into life as a necessary aspect of curriculum development throughout implementation. Must evaluate and enhance VR’s potential as a specialism-free integrating medium within a concurrent engineering methodology to maximize its industrial applicability. It is possible to train in a safe, yet realistic, setting using virtual reality. In addition to providing real advantages to learners and improving the efficiency of work processes, it contributes to a safer and more productive workplace by facilitating team training.
Digitized Visual Transformation of Grotto Art Using Deep Learning and Virtual Reality Technology
Authors: Xie Hao
Published: August 2022

The purpose is to convert the contents of the grotto murals into a digital vision based on deep learning (DL) and virtual reality (VR) technology to protect the precious grotto murals. The grotto murals are analyzed and modeled by introducing the related concepts of the digital library, using VR technology, and taking the cultural relics data acquisition technology as the basic framework. Then, the cultural relics information collection technology under DL is combined with VR technology, the color and materialization concepts of grotto murals are integrated, and a digital recognition model of grotto mural restoration and simulation is constructed. The color analysis scheme of grotto murals is established. Through the analysis of color and material, the comprehensive recognition rate of this color model can reach 70%, and the material recognition of color painting can also ensure one-to-one restoration. Besides, the model can be applied to the simulation and restoration of grotto murals and provide some help for the protection of grotto murals. This paper has practical application value for the protection and restoration of mural art.
Circulating Tumor-Derived Endothelial Cells: An Effective Biomarker for Breast Cancer Screening and Prognosis Prediction
Authors: Han Tuo , Zhang Juanjuan , Xiao Dong , Yang Binhui , Chen Liang , Zhai Chao , Ding Feifei , Xu Yue , Zhao Xiaoyu , Zhao Jiangman
Published: August 2022

Background. Circulating tumor-derived endothelial cell (CTEC) is a new potential tumor biomarker to be associated with cancer development and treatment efficacy. However, few evidences are available for breast cancer. Methods. Eighty-nine breast cancer patients were recruited, and preoperative and postoperative blood samples were collected. Besides, 20 noncancer persons were enrolled as controls. An improved subtraction enrichment and immunostaining-fluorescence in situ hybridization (SE-iFISH) method was adopted to codetect CD31+ aneuploid CTEC and CD31− aneuploid circulating tumor cell (CTC). Then, the clinical significance of CTCs and CTECs on breast cancer screening and prognosis prediction was evaluated and compared. Results. The positive rate of CTCs and CTECs in newly diagnosed breast cancer patients was 68.75% and 71.88%. Among detected aneuploid circulating rare cells, CTEC accounts for a greater proportion than CTC in breast cancer patients. CTEC-positive rate and level were significantly higher in breast cancer patients with lymph node metastasis (LNM) than those without LNM (

P
=
0.043

), while there was no significant difference in CTC. CTEC (area under the curve, AUC = 0.859) had better performance than CTC (AUC = 0.795) to distinguish breast cancer patients from controls by receiver operator characteristic curve analysis. Preoperative CTEC count ≥ 2 was a significant risk factor for reducing PFS of breast cancer patients. Conclusions. CTECs may function as a reliable supplementary biomarker in breast cancer screening and prognosis prediction.
Kannan Contraction Maps on the Space of Null Variable Exponent Second‐Order Quantum Backward Difference Sequences of Fuzzy Functions and Its Pre‐Quasi Ideal
Authors: Bakery Awad A. , Mohamed OM Kalthum S. K.
Published: August 2022

In this paper, we construct and investigate the space of null variable exponent second‐order quantum backward difference sequences of fuzzy functions, which are crucial additions to the concept of modular spaces. The idealization of the mappings has been achieved through the use of extendeds− fuzzy functions and this sequence space of fuzzy functions. This new space’s topological and geometric properties and the mappings’ ideal that corresponds to them are discussed. We construct the existence of a fixed point of Kannan contraction mapping acting on this space and its associated pre‐quasi ideal. To demonstrate our findings, we give a number of numerical experiments. There are also some significant applications of the existence of solutions to nonlinear difference equations of fuzzy functions.
Dantrolene Administration in the Management of the Prehospital Patient with Methylenedioxymethamphetamine Overdose: A Case Series and Literature Review
Authors: Nikoomanesh Kia , Phan Alexander T. , Choi Julian , Arabian Sarkis , Neeki Michael M.
Published: August 2022

Methylenedioxymethamphetamine (MDMA) is a psychoactive substance that is used commonly as a recreational drug at rave music festivals. MDMA intoxication can cause a myriad of symptoms and side effects including the manifestation of hyperpyrexia in patients. Hyperpyrexia can mimic a heat stroke and ultimately lead to various forms of end-organ damage. The most common methods used in treating MDMA-induced hyperpyrexia focus on the rapid reduction of core body temperature. Various off-label medications have also been used in combating MDMA-induced hyperpyrexia. Dantrolene is one such medication, although its role in the treatment of MDMA intoxication remains uncertain. This case series preliminarily examines the efficacy of dantrolene in mitigating MDMA-induced hyperpyrexia and potentially reducing the risk of end-organ damage in patients suffering from MDMA overdose. This study focuses on nine patients who presented after ingesting various forms of MDMA at “rave” music events. All patients were found to be hyperthermic in the field with a maximum core body temperature of 109 degrees Fahrenheit. All patients were immediately managed by cooling measures, and seven patients additionally received dantrolene in the field before being transferred to Arrowhead Regional Medical Center. Upon arrival to the hospital, nearly every patient was found to have significantly decreased body temperatures when compared to previously measured body temperatures out in the field. However, nearly all patients in the study were also noted to have laboratory abnormalities consistent with various forms of end-organ damage. The degree and severity of end-organ damage observed in MDMA-induced hyperpyrexia seem to be a function of initial core body temperature. Higher core body temperature tends to correlate with more forms of end-organ damage and a higher severity of end-organ damage. Intervention with dantrolene and cooling measures appeared to have no effect on reducing the risk of developing end-organ damage in this patient population.
Application of Genetically Encoded Molecular Imaging Probes in Tumor Imaging
Authors: Du Meng , Wang Ting , Yang Yaozhang , Zeng Fengyi , Li Yue , Chen Zhiyi
Published: August 2022

In recent years, imaging technology has made rapid progress to improve the sensitivity of tumor diagnostic. With the development of genetic engineering and synthetic biology, various genetically encoded molecular imaging probes have also been extensively developed. As a biomedical imaging method with excellent detectable sensitivity and spatial resolution, genetically encoded molecular imaging has great application potential in the visualization of cellular and molecular functions during tumor development. Compared to chemosynthetic dyes and nanoparticles with an imaging function, genetically encoded molecular imaging probes can more easily label specific cells or proteins of interest in tumor tissues and have higher stability and tissue contrast in vivo. Therefore, genetically encoded molecular imaging probes have attracted increasing attention from researchers in engineering and biomedicine. In this review, we aimed to introduce the genetically encoded molecular imaging probes and further explained their applications in tumor imaging.
Study on Energy-Saving Optimization of Urban Rail Transit Train Timetable under Regenerative Braking
Authors: Zheng Yajing , Ma Zihan , Liu Naiyu , Jin Wenzhou
Published: August 2022

Energy-saving driving and regenerative braking energy utilization are two main ways to realize energy-saving optimization of urban rail transit train timetables. On the basis of the more mature energy-saving driving achievements of the predecessors, the absorption utilization rate of regenerative braking energy is improved by adjusting the dwell time of trains in the station so that while a train is braking, other trains in the same electric section are just under traction. In this paper, the overlap time between the traction and braking processes of different trains is used as a measure of the proportion of regenerative braking energy that is absorbed. In order to maximize this overlap time, an energy-saving optimization model of urban rail transit train timetable based on regenerative braking technology was established. To facilitate the solution, the nonlinear constraints are converted to linear at the time of model construction in this paper. In the solution, the spatio-temporal local rolling algorithm and the commercial optimization software ILOG CPLEX are used for the solution. The solution results show that the method in this paper can effectively improve the absorption and utilization of regenerative braking energy.
The Intervention of Music Education on Students’ Mental Health Based on Fuzzy Computing
Authors: Wang Ying
Published: August 2022

Music is an important way for people to express and communicate their thoughts and feelings. It not only has the functions of cultivating sentiment, developing intelligence, and promoting personality development but also has an energetic function on the spiritual fitness of pupils. As an important part of quality education in schools, music education has become a pioneer in the implementation of psychological intervention for students. Music education can cultivate sentiment and lively and optimistic mood by emotional images conveyed through various music and has a special role that cannot be replaced by other disciplines. However, the current music education in schools only focuses on the dissemination of music knowledge and there is no research on which type of music can effectively interfere with students’ mental health. In order to be able to choose music that is effective for students’ mental health intervention in music education, this paper will study the intervention research of music education on students’ mental health based on fuzzy computing. This paper extracts the musical features such as average pitch, average pitch intensity, melody direction, pitch stability value, rhythm intensity, and beat, uses fuzzy computing to classify music, determines which types of music can improve students’ mental health, and uses experiments to verify the validity of this research. The consequences of the research show that choosing effective music to intervene in students’ mental health can greatly improve students’ mental health problems. The scores of students’ psychological status after the intervention are 0.73 times of those before the intervention. It demonstrates the validity of the study.
Construction and Evaluation Method of Key Indicators of Moral Character and Political Concept Education of Undergraduate Pupils Based on CIPP Model
Authors: Wang Wei
Published: August 2022

It has always been our party’s fine tradition to focus on moral character and political concept education for undergraduate pupils. Since the founding of the Communist Party of China, the moral character and political concept education of undergraduate pupils has been attached great importance, no matter when the moral character and political concept education of undergraduate pupils in the primary position of education. With the development of modernization, the moral character and political concept education system of undergraduate pupils is quite different from the traditional system, so how to evaluate the moral character and political concept education of undergraduate pupils more accurately and fairly requires more suitable evaluation methods and key indicators. Today’s higher education is dominated by a pragmatic view, and one of its main goals is to produce pupils who contribute to society. The importance of which will need to practice, thus combining the domestic and foreign education view, and the specific ideological education present situation, we put forward the practice of the key indicators, based on the CIPP model built which is suitable for the modern undergraduate pupils’ ideological education evaluation system method; the results show that the presented evaluation method and undergraduate pupils’ ideological education level fit are 15% higher than the traditional methods, and it has stronger accuracy and fit degree.
Construction and Validation of a Necroptosis-Related lncRNA Signature in Prognosis and Immune Microenvironment for Glioma
Authors: Jiang Fan , Zhan Zheng , Yang Yanbo , Liu Guangjie , Liu Song , Gu Jingyu , Chen Zhouqing , Wang Zhong , Chen Gang
Published: August 2022

Background. Glioma is the most common primary brain tumor, representing approximately 80.8% of malignant tumors. Necroptosis triggers and enhances antitumor immunity and is expected to be a new target for tumor immunotherapy. The effectiveness of necroptosis-related lncRNAs as potential therapeutic targets for glioma has not been elucidated. Methods. We acquired RNA-seq data sets from LGG and GBM samples, and the corresponding clinical characteristic information is from TCGA. Normal brain tissue data is from GTEX. Based on TCGA and GTEx, we used univariate Cox regression to sort out survival-related lncRNAs. Lasso regression models were then built. Then, we performed a separate Kaplan-Meier analysis of the lncRNAs used for modeling. We validated different risk groups via OS, DFS, enrichment analysis, comprehensive immune analysis, and drug sensitivity. Results. We constructed a 12 prognostic lncRNAs model after bioinformatic analysis. Subsequently, the risk score of every glioma patient was calculated based on correlation coefficients and expression levels, and the patients were split into low- and high-risk groups according to the median value of the risk score. A nomogram was established for every glioma patient to predict prognosis. Besides, we found significant differences in OS, DFS, immune infiltration and checkpoints, and immune therapy between different risk subgroups. Conclusion. Predictive models of 12 necroptosis-related lncRNAs can facilitate the assessment of the prognosis and molecular characteristics of glioma patients and improve treatment modalities.
Real-Time Forestry Pest Detection Method Based on Enhanced Feature Fusion with Deep Learning
Authors: Li Rui , Liu Tong , Ren Yalu
Published: August 2022

The aim of this study is to address the real-time requirements of forestry pest detection and the problem of a low detection rate caused by anchor box redundancy of existing detection methods. This paper proposes a real-time forestry pest detection method based on theanchor-free method that can balance the detection rate and detection accuracy. Based on the TTFNet method, a mobile feature extraction network is introduced, and the effective feature weights are increased by one-dimensional convolution before feature output to suppress invalid features. For pest detection, data are mostly small-scale targets. An enhanced feature fusion method is proposed to introduce an asymmetric convolution module in multi-scale feature fusion to feature-enhance the feature maps extracted by the backbone network and connect across layers to improve the detection accuracy. To address the degradation of the anchor box position regression loss in the original method, DIOULoss is introduced to optimize the position regression loss function of the anchor box. Finally, data augmentation is performed on a relatively small number of samples in the dataset, the accuracy of the model is improved by 1.94%, the FPS is improved to 1.6 times of the original one, and the training time is slightly increased compared with the preinnovation model. Ablation experiments are designed to demonstrate the effectiveness of the proposed algorithm while being more conducive to deployment on edge devices.
Experimental Investigation on the Effect of Three Elemental Nanoparticles on the Performance Characteristics of Ethanol-Diesel Emulsion
Authors: Firew Deresse , Nallamothu Ramesh Babu , Alemayehu Getachew , Gopal Rajandiran
Published: August 2022

The utilization of nanoparticle in ethanol-diesel emulsions combustion catalyst is important. For this study, ethanol and diesel fuels are emulsified varying the ethanol amount as 5, 10, and 15% volume ratio designated as E5, E10, and E15, respectively, by using span 80 and tween 80 emulsifying agents. Nickel Zinc Iron Oxide (NiZnFe2O4) nanoparticle is used in each fuel sample with a dose rate of 25, 50, and 100 ppm. Cetyl Trimethyl Ammonium Bromide (CTAB) surfactant is used to keep the nanoparticle homogeneously suspended in the fuel. Mechanical steering and ultrasonic vibrator are used to prepare the sample fuel. A single-cylinder diesel engine testing rig is used to test the performance. For the ethanol-diesel emulsion, the power and torque output decreased as the ethanol percentage and the BSFC increased. The nanoparticle addition improved power and torque output and reduced BSFC. Ethanol-diesel emulsion fuel performance characteristics could be improved with the utilization of NiZnFe2O4.
Analysis of the Innovation Path of Marxism Popularization Based on Big Data Analysis
Authors: Chu Dongwei , Yu Dahuai
Published: August 2022

Marxist theory points out that practice is the method of understanding the world, and it is also the essential characteristic of human beings. Based on the above theoretical basis and guidance, this paper, from the perspective of ideological and political education evaluation, conducts research on student behavior in Marxist popular classrooms, grasps the characteristics of student behavior in Marxist popular classrooms in the new era, and explores behavioral research. Approaches and methods for ideological and political education evaluation and student evaluation were introduced. This paper analyzes the combination method of AHP and BP neural network in the previous research and points out its limitations. On this basis, it innovatively proposes an inherited combination method of AHP and BP neural network and conducts model training and exact match experiment based on AHP and BP neural network. Finally, by comparing and analyzing the above four sets of experimental results, it is found that the inheritance-type combination method of AHP-BP neural network not only avoids the problem of small AHP capacity but also scientifically integrates hierarchical weights with theoretical basis into the calculation of BP neural network. In addition, the inheritance-type combination of AHP-BP neural network in this study can replace the normalization of data and effectively improve the training speed and matching accuracy of the precise matching model for political classrooms in colleges and universities under the new situation.
Pharmacological Mechanism of Zuojin Pill for Gastroesophageal Reflux Disease: A Network Pharmacology Study
Authors: Lv Mi , Huang Jinke , Hu Jiayan , Yu Wenxi , Liu Ping , Zhang Kunli , Wang Fengyun
Published: August 2022

Background. Although Zuojin Pill (ZJP) is widely used in China as a traditional prescription to treat gastroesophageal reflux disease (GERD), its exact mechanism of action is still unknown. Therefore, we employed network pharmacology (NP), molecular docking (MD), and molecular dynamics simulation (MDS) to investigate the pharmacological mechanisms of ZJP against GERD. Methods. Active compounds and target genes corresponding to ZJP and target genes related to GERD were identified through analysis of publicly available datasets. Subsequently, the obtained data were subjected to further network pharmacological analysis to explore the potential key active compounds, core target genes, and biological processes (BPs) associated with the effect of ZJP against GERD. Finally, the prediction results of NP were validated by MD, and MDS of the optimal core protein-ligand for each component obtained by MD were performed using Gromacs 2020 software. Results. Twelve active components of ZJP were identified to act on 82 target genes associated with GERD, and ZJP might exert an anti-GERD effect through the regulation of BPs such as reactive oxygen species (ROS) metabolism, response to oxidative stress (OS), and ROS, as well as the activation of signaling pathways such as apoptosis, p53 signaling, chemical carcinogenesis-ROS, and HIF-1 signaling pathways. Furthermore, quercetin, kaempferol, and coptisine, the three key components of ZJP were shown to stably bond with the 14 core target genes, including AKT1, MMP2, TP53, EGFR, JUN, CASP3, CXCL8, HIF1α, IL-1β, MYC, PPARG, MMP9, PTGS2, and FOS. Results from MDS showed that PPARG-quercetin and MMP2-quercetin bound more stably. Conclusions. The findings suggest that ZJP alleviates the symptoms of GERD and improves the prognosis by regulating ROS metabolism, thereby reducing the secretion of proinflammatory cytokines like IL-1β, COX-2, CXCL8, and MMPs, regulating the expression of oncogenes such as JUN and FOS, and maintaining the normal expression of tumor suppressor genes such as TP53 and MYC. However, whether the effect of this modulation of ROS metabolism is positive or negative needs to be further verified by pharmacological experiments.
Design of Music Teaching System Based on Internet of Things Multimedia Intelligent Platform
Authors: Xie Bin
Published: August 2022

In order to improve the practical and popularization value of the multimedia vocal music teaching system, the author proposes a teaching system based on the Internet of Things multimedia intelligent platform. Mainly use Visual C++ to realize the acquisition, playback, and display of audio and realize the real-time modification of the sound wave waveform on the computer and also add the function of vocal score. Experimental results show that in the pitch comparison, the standard fundamental frequency average value of the fundamental frequency track of the two pieces of music is obtained by the cepstral method:

avgF
0
=
143.12
HZ

and the average fundamental frequency of the trial singing:

avgF
0
=
142.05
HZ

. The average distance and score of each parameter of the testers are

mindisv
=
726.126

for pitch intensity,

path
 
length
=
144

;

mindisp
=
4.51987

,

path
 
length
=
163

for pitch,

breath
 
smoothness
=
484.20

. Conclusion. This method not only improves the intuitiveness and interaction of vocal music teaching, but also increases the interest of vocal music teaching.