bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of TCM Diagnosis and Treatment of Thyroid Diseases Based on Data Mining
Authors: She Kankan , Dai Caiyan 
Published: April 2021

Abstract
Thyroid disease is the most common and frequently occurring endocrine disease. In recent years, the incidence rate of thyroid diseases has increased in recent years due to the gradual change of the ecological environment and the gradual popularization of iodine supplements for iodine deficiency disorders. At present, the prevalence of hyperthyroidism is 1.3%, hypothyroidism is 6.5%, thyroid nodules are 18.6%, and 2%-5% of thyroid nodules are thyroid cancer. Thyroid disease has become a high incidence and common disease in modern society. The number of thyroid disease patients in China has become the second largest disease after hypertension. Thyroid disease belongs to gall disease of traditional Chinese medicine. Compared with western medicine, traditional Chinese medicine has certain advantages in the treatment of gall disease. Compared with western medicine, traditional Chinese medicine can better improve clinical symptoms and reduce toxicity.
In this paper, Stata and python were used to analyze and clean the data of TCM diagnosis thyroid medical records. Principal component analysis and factor analysis were used to analyze and clean the symptoms and pathogenesis of the medical record data. The data in the prescription were quantified. The feature selection of the data set was performed by principal component analysis to reduce the data dimension. In the process of treatment, different kinds of prescriptions will be used. Association analysis algorithm in data mining is used to mine the association rules of prescription medication and complications of thyroid disease, which provides a reference for clinical treatment drug selection and disease prevention of traditional Chinese medicine. Logistic regression was used to establish the prediction model of traditional Chinese medicine diagnosis prescription of thyroid by using the clinical data of traditional Chinese medicine.
Application of Deep Learning in Photovoltaic Array Fault Identification
Authors: Han Yuchen , Yao Xiaodong 
Published: April 2021

Abstract
If a photovoltaic power station needs to operate normally, it cannot do without the blessing of the photovoltaic array, which also takes up about half of the cost of the photovoltaic system. The failure and low efficiency of photovoltaic power plants are the main two reasons for the loss of energy. Among them, the failure of photovoltaic arrays is undoubtedly one of the important reasons. In this article, the author uses the superiority of deep neural network in fault identification technology to complete the fault identification model of photovoltaic array.
Research and Application of Application System Architecture Based on Big Data
Authors: Li Hongyu , Gao Ling , Yang Xiaojun 
Published: April 2021

Abstract
With the advent of the era of big data, traditional application systems have been unable to meet the actual needs of the development of various industries. Building an application system architecture based on big data has become a top priority for many enterprises and organizations. In this context, based on the previous research, this paper proposes an application system architecture model based on big data and based on the application system design principle. The model is divided into data source layer, data storage layer, data acquisition and processing layer, data analysis layer, and data application layer. After a detailed description of the functions and characteristics of each layer, an application example is given for further analysis, hoping to provide some reference for each industry in building a big data application system architecture.
Algorithm Design of Translation Accuracy Correction for English Translation Softwares
Authors: Qu Weiwei 
Published: April 2021

Abstract
With the development of economic globalization, English is needed in more and more different cases in people’s daily life, and so is English translation. Traditional English software translation mainly depends on machine, which on the one hand facilitates people’s life, while on the other hand it also has some disadvantages. For example, translation errors are characterized by iterative transmission, weak logic and low accuracy. Traditional machine translation has been unable to meet people’s demand for both speed and quality, so it can no longer meet people’s needs. Therefore, this paper puts forward the design of translation accuracy correction algorithm for English translation softwares. First of all, an in-depth research on the traditional English translation methods, such as lexical semantic translation and phrase translation, are conducted with the method of documentation. Then, a dependency tree to string model and log linear model are established. Finally, the BLEU value and NIST value of the three translation softwares as well as the translation accuracy before and after algorithm correction is compared and analyzed. The conclusion shows that the highest accuracy of English translation before correction is only 75.6%, while the lowest accuracy is as high as 98.7% after the algorithm is adopted in this paper. The difference of accuracy between the two shows that the effectiveness of the correction system in this paper makes an outstanding contribution.
Application of Computer Information Processing Technology in Teaching Management Information System of Colleges and Universities
Authors: Zhang Ying 
Published: April 2021

Abstract
Human beings have entered a new era — information age, with the rapid development of information technology with network communication technology and multimedia technology as the core, which has caused various profound changes in many fields and accelerated the progress of human beings to the information society. At the same time, with the acceleration of the pace of global economic integration, the level of informatization has become an important symbol to measure the international competitiveness, modernization, comprehensive national strength and economic growth ability of a country and a region. The demand of social development for informatization is becoming more and more intense, and the development of informatization has received unprecedented attention in all countries of the world. As the front position of educational informatization, the process of higher education informatization has had an unprecedented impact on college teaching. Campus, classroom, library and other traditional teaching environment and space-time concept has been adopted and quietly changed. Statistics from the Science and Technology Development Center of the Ministry of Education show that some schools in colleges and universities have built their own campus network, and other schools are under construction, and 98.4% of the colleges and universities with campus network have realized office automation and scientific research networking.
Product Appearance Design and Concept Innovation Based on Neural Network
Authors: Liu Beili 
Published: April 2021

Abstract
Design, in essence, is a process in which designers use their own design language to explicitly express the needs of users. It is the collision and coupling of design knowledge and user knowledge. Therefore, the study of design knowledge and the realization of knowledge-based COMPUTER-aided design is of positive significance for improving design quality and efficiency. This paper mainly studies the product appearance design and concept innovation based on neural network. In this paper, the comprehensive application of BP neural network and genetic algorithm in the optimization of product appearance modeling scheme to meet the needs of users is studied. Through MATLAB, a BPN model was built to realize the mapping relationship between the product appearance modeling knowledge and the overall image, and the optimized objective function was obtained by combining the image of user demand, thus improving the usability and reliability of product appearance design.
Risk Management of Community Sports Based on AI Technology
Authors: Zhou Wenyong , Huang Qiong 
Published: April 2021

Abstract
With the progress of the times, China’s economy, politics and culture are developing rapidly. Today’s sports life is rich and colorful. People gradually realize that sports activities play a positive role in people’s health. Therefore, with the development of mass sports healthy lifestyle and AI technology, sports community risk management has become increasingly important. The purpose of this paper is to study the risk management of sports community based on AI technology. This paper uses the related technologies of emergency virtual scene construction, including three-dimensional terrain visualization technology based on terra Vista and global mapper software, and static object simulation modeling technology based on creator software. This paper puts forward the method of list sort, risk matrix, Pareto analysis and mathematical statistics. This paper discusses and deeply analyzes the related concepts of risk management in sports community and puts forward solutions. Finally, it adopts a variety of forms of expression, and presents its trend chart intuitively to users. The experimental study shows that human and site factors account for about 20% of the risk factors, and social factors account for the least, accounting for 6.56%. The severity index of self action completion and management efficiency reached 4.62 and 4.84 respectively. The maximum probability index of the impact of management efficiency on the occurrence of accidents reached 4.57.
Problems and Development Strategies for Art Education in Kindergarten in the New Media Era
Authors: Yang Wudai , Chen Mei 
Published: April 2021

Abstract
The effective combination of education and information technology has developed into a new educational trend, which has also made it a field that has attracted much attention from the education community and is worthy of research. This research uses questionnaire surveys to collect information, analyzes the status quo of art education in kindergartens in the new media era and the current problems in art education, proposes development strategies for art education in kindergartens in the era of new media, further improves the effective integration of new media and traditional art education classes in kindergartens, and promotes the development of kindergarten education.
A Brief Review of Machine Learning Algorithms for Cooperative Spectrum Sensing
Authors: Wang Jingting , Liu Bao 
Published: April 2021

Abstract
With the development of wireless communication services, spectrum resources become more and more scarce. Cognitive radio technology is widely considered as a feasible solution to the problem of spectrum sharing. The introduction of machine learning has greatly promoted the cooperative spectrum sensing of cognitive radio. In particular, this paper brief reviews the cooperative schemes in three machine learning algorithms, including support vector machine, Convolutional Neural Network, and deep reinforcement learning. It is worth summarizing and discussing these machine learning cooperative spectrum sensing algorithms.
Research on Multi-Dimensional Practical Teaching System of Art Design Major in Ming and Qing Dynasty Furniture Design Based on Sample Data Analysis
Authors: Liu Jing 
Published: April 2021

Abstract
Aiming at the problems of weak course and poor teaching effect of furniture design major in Ming and Qing Dynasties, this paper puts forward the idea of constructing multiple practical teaching mode, and reforms the teaching of furniture design specialty in Ming and Qing Dynasties from the implementation of diversified talent training scheme, reform of teaching mode and construction of practical teaching system. This paper analyzes the current situation of Ming and Qing furniture design of art design major, and puts forward the multi-dimensional practice teaching system of art design major in Ming and Qing Dynasty furniture design. In this paper, 260 students of art design major in furniture design were selected as survey samples, and the satisfaction, pertinence and acceptance of multidimensional practice teaching in recent three years were compared and analyzed, and the results were discussed and analyzed. The research on the implementation method of multidimensional practice teaching in furniture design of Art Design Specialty was put forward, which provided a reference for the development of furniture design of art design specialty Security. The research of this paper has important practical significance for the further development of the two.
Implementation of an inexpensive cathodoluminescence and electron beam induced current image generator coupled to a scanning electron microscope
Authors: Benítez-Lara A. , Cisneros H. , Bautista E. , Molina J. , Morales F. , Morales-Narváez E. , Carrillo-López J. , Desirena H. , Lopez O. 
Published: April 2021

Abstract
In this work, implementation of a novelty cathodoluminescence and electron beam induced current image generator system for do in situ experiments in a scanning electron microscopy (SEM) is presented. The equipment is composed by one mechatronic system (MS) with interchangeable probes and digitalization system programed with Labview. Porous silicon and Eu2(WO4)3 microparticles were characterized in cathodoluminescense mode with luminescence peaks centered at 410 and 613 nm, respectively. For CL imaging, the emission signal is collected through a probe of nine optical fibers and transduced to an electrical signal via a photomultiplier tube (PMT). In other way, the configuration in EBIC mode was tested with commercial silicon monocrystalline solar cell to determine internal defects using a current mapping. However for EBIC imaging, the current is collected by two electrodes connected to a picoammeter synchronized with the electron beam. CL and EBIC images are compared with SE images and chemical elemental mapping images to correlate the emission and defects regions of the sample.
A review of linkage mechanisms in animal joints and related bioinspired designs
Authors: Burgess Stuart 
Published: April 2021

Abstract
This paper presents a review of biological mechanical linkage mechanisms. One purpose is to identify the range of kinematic functions that they are able to perform. A second purpose is to review progress in bioinspired designs. Ten different linkage mechanisms are presented. They are chosen because they cover a wide range of functionality and because they have potential for bioinspired design. Linkage mechanisms enable animal joints to perform highly sophisticated and optimised motions. A key function of animal linkage mechanisms is the optimisation of actuator location and mechanical advantage. This is crucially important for animals where space is highly constrained. Many of the design features used by engineers in linkage mechanisms are seen in nature, such as short coupler links, extended bars, elastic energy storage and latch mechanisms. However, animal joints contain some features rarely seen in engineering such as integrated cam and linkage mechanisms, nonplanar four-bar mechanisms, resonant hinges and highly redundant actuators. The extreme performance of animal joints together with the unusual design features makes them an important area of investigation for bioinspired designs. Whilst there has been significant progress in bioinspiration, there is the potential for more, especially in robotics where compactness is a key design driver.
Indian Ocean warming as a potential trigger for super phytoplankton blooms in the eastern equatorial Pacific from El Niño to La Niña transitions
Authors: Tian Feng , Zhang Rong-Hua , Wang Xiujun 
Published: April 2021

Abstract
During El Niño to La Niña transitions in 1998 and 2010, satellite observations revealed a sharp increase in surface chlorophyll in the eastern equatorial Pacific (EEP), exceeding the interannual amplitude by threefold; however, the causes of such super phytoplankton blooms (SPBs) remain unclear. Here, observational data, climate model simulations, and coupled ocean-biogeochemical modeling experiments are adopted to show that Indian Ocean (IO) warming plays an active role in remotely triggering SPBs in the EEP. During the previous boreal winter in an El Niño year, IO warming generates anomalous easterlies over the western edge of the tropical Pacific, which excite upwelling Kelvin waves propagating into the EEP during the following boreal spring, remotely causing an uplift of the nutricline in the EEP. Seasonally, the mixed layer deepens and the upper ocean warms during the following late spring, and large amounts of nutrient-rich cold subsurface waters entrain into the mixed layer; interannually, the local grazing pressure is low after the peak of El Niño. These remote and local factors jointly promote SPBs in the EEP.
Stable and unstable Dp-branes in p-brane Newton–Cartan background
Authors: Klusoň Josef 
Published: April 2021

Abstract
We formulate Dp-brane Newton–Cartan (NC) background through the limiting procedure from relativistic Dirac–Born–Infeld action and Wess–Zumino term. We also determine action for unstable D(p + 1)-brane in Dp-brane NC background and study its properties.
3D–3D correspondence from Seifert fibering operators
Authors: Fan Yale 
Published: April 2021

Abstract
Using recently developed Seifert fibering operators for 3D

N
=
2

gauge theories, we formulate the necessary ingredients for a state-integral model of the topological quantum field theory dual to a given Seifert manifold under the 3D–3D correspondence, focusing on the case of Seifert homology spheres with positive orbifold Euler characteristic. We further exhibit a set of difference operators that annihilate the wavefunctions of this TQFT on hyperbolic three-manifolds, generalizing similar constructions for lens space partition functions and holomorphic blocks. These properties offer intriguing clues as to the structure of the underlying TQFT.
Semi-classical Lindblad master equation for spin dynamics
Authors: Dubois Jonathan , Saalmann Ulf , Rost Jan M 
Published: April 2021

Abstract
We derive the semi-classical Lindblad master equation in phase space for both canonical and non-canonical Poisson brackets using the Wigner–Moyal formalism and the Moyal star-product. The semi-classical limit for canonical dynamical variables, i.e. canonical Poisson brackets, is the Fokker–Planck equation, as derived before. We generalize this limit and show that it holds also for non-canonical Poisson brackets. Examples are gyro-Poisson brackets, which occur in spin ensembles, systems of recent interest in atomic physics and quantum optics. We show that the equations of motion for the collective spin variables are given by the Bloch equations of nuclear magnetization with relaxation. The Bloch and relaxation vectors are expressed in terms of the microscopic operators: the Hamiltonian and the Lindblad functions in the Wigner–Moyal formalism.
Next generation human brain models: engineered flat brain organoids featuring gyrification
Authors: Rothenbücher Theresa S P , Gürbüz Hakan , Pereira Marta P , Heiskanen Arto , Emneus Jenny , Martinez-Serrano Alberto 
Published: April 2021

Abstract
Brain organoids are considered to be a highly promising in vitro model for the study of the human brain and, despite their various shortcomings, have already been used widely in neurobiological studies. Especially for drug screening applications, a highly reproducible protocol with simple tissue culture steps and consistent output, is required. Here we present an engineering approach that addresses several existing shortcomings of brain organoids. By culturing brain organoids with a polycaprolactone scaffold, we were able to modify their shape into a flat morphology. Engineered flat brain organoids (efBOs) possess advantageous diffusion conditions and thus their tissue is better supplied with oxygen and nutrients, preventing the formation of a necrotic tissue core. Moreover, the efBO protocol is highly simplified and allows to customize the organoid size directly from the start. By seeding cells onto 12 by 12 mm scaffolds, the brain organoid size can be significantly increased. In addition, we were able to observe folding reminiscent of gyrification around day 20, which was self-generated by the tissue. To our knowledge, this is the first study that reports intrinsically caused gyrification of neuronal tissue in vitro. We consider our efBO protocol as a next step towards the generation of a stable and reliable human brain model for drug screening applications and spatial patterning experiments.
Tissue printing for engineering transplantable human parathyroid patch to improve parathyroid engraftment, integration, and hormone secretion in vivo
Authors: Yu Hyeong Won , Kim Byoung Soo , Lee Jae Yeon , Lee Keunchul , Ahn Minjun , Jang Jinah , Cho Dong-Woo , Choi June Young 
Published: April 2021

Abstract
During thyroid surgery, some parathyroid glands fail to maintain their function, therefore, they are unavoidably detached from the patient. For the purpose of re-preservation of the function, they are minced into small segments and transplanted into the fat or muscle layer. Yet, this method of auto-grafting the parathyroid glands is frequently unsuccessful due to its poor interaction and engraftment with the native tissue, eventually leading to the dysfunction of the parathyroid hormone (PTH) secretion. In this study, we suggest a methodology to restore parathyroid activity through the introduction of the ‘tissue printing’ concept. Parathyroid glands of patients with secondary hyperparathyroidism were minced into the fragments smaller than 0.5 × 0.5 mm, which is in common with the traditional surgical method. These parathyroid tissues (PTs) were uniformly mixed with the adipose-derived decellularized extracellular matrix (adECM) bioink that protects the PTs from hostile in vivo environments and promote initial engraftment. PTs-encapsulated adECM bioink (PTs-adECM) was then printed onto the pre-designed polycaprolactone (PCL) mesh to produce patch-type PTs construct, which functions as a mechanical support to further enhance long-term in vivo stability. The engineered patch was transplanted subcutaneously into rats and harvested after 4 weeks. In vivo results showed that the engineered patches were well engrafted and stabilized in their original position for 4 weeks as compared with PTs only. Immunohistochemistry results further revealed that the concentration of PTH was approximately 2.5-fold greater in rats engrafted in the patch. Taken together, we envision that the novel concept ‘tissue printing’ over cell printing could provide a closer step towards clinical applications of 3D bioprinting to solve the unmet need for parathyroid surgery method.
Sustainable application of silvered nickel foam for the highly efficient degradation of rhodamine B
Authors: Meng Yongde 
Published: April 2021

Abstract
The use of organic dyes has led to serious environmental problems resulting from contaminated wastewater; hence, the development of new dye-removal methods is an important objective. Herein, silvered nickel foam (nickel foam loaded with silver nanoparticles) is reported to significantly degrade an organic dye in aqueous solution. 20 mg · l–1 rhodamine B is completely reduced within 20 min with a rate constant of 0.26 min−1 in the presence of nickel foam sparsely loaded with silver. A mechanism for the reduction of rhodamine B is proposed. Moreover, the silvered nickel foam can be recycled at least five times. This research demonstrates that silvered nickel foam is a promising pollution-control candidate material.