A deep architecture for enhancing students’ action recognition is proposed to improve preschool education. This paper seamlessly combines the teaching objectives, teaching scope, teaching ...implementation, and breeding evaluation status of preschool breeding practice theory. We attempt to solve the problem of effective preschool teaching, based on which we propose the simple adaptation strategies. We further evaluate the practice of preschool breeding and its effectiveness. In this way, civilized and high-quality preschool talents will be cultivated, and preschool educational experiences will be promoted. In the method of promoting the preschool culture of weak-aged children, owing to the problem that the traditional action recognition algorithm can indicate the specific students’ actions, an action recognition method based on the combination of deep integration and human skeleton representation is proposed. First, the connected spatial locations and constraints are fed into a long-short-specified recall (LSTM) mode with a spatially and temporally aware algorithm which is designed to obtain spatiotemporal feature and highly separable deep joint features. Afterward, a new mechanism is introduced to resolve keyframes as well as the joints. Finally, based on the two-stream deep architecture, the effective discrimination of similar actions is achieved by integrating the color and shape features into the skeleton features by designing the deep model. Extensive experiments have demonstrated that, compared with the mainstream algorithms, this method can effectively distinguish students’ action types in the classroom of homogeneous preschool children. Thus, we can substantially improve the efficiency of preschool teaching.
In order to improve the quality of English translation teaching, this paper combines the theory of multiple intelligence to classify the English translation teaching process. Moreover, this paper ...adopts Fisher’s discriminant method and Bayesian discriminant method to classify the English translation teaching samples. In order to improve the discrimination accuracy of the extreme learning machine algorithm, this paper applies the particle swarm optimization extreme learning machine algorithm to the research on the classification of English translation teaching samples and proposes an intelligent English classification teaching model based on the actual situation of English translation teaching. In addition, this paper verifies the system model proposed in this paper by evaluating the teaching method. The research shows that the classification model of English translation teaching mode based on the theory of multiple intelligence proposed in this paper has a certain effect, which can promote the effect of English translation teaching.
Over the past two decades, the viewpoint of atherosclerosis has been replaced gradually by a lipiddriven, chronic, low-grade inflammatory disease of the arterial wall. Current treatment of ...atherosclerosis is focused on limiting its risk factors, such as hyperlipidemia or hypertension. However, treatment targeting the inflammatory nature of atherosclerosis is still very limited and deserves further attention to fight atherosclerosis successfully. Here, we review the current development of inflammation and atherosclerosis to discuss novel insights and potential targets in atherosclerosis, and to address drug discovery based on anti-inflammatory strategy in atherosclerotic disease.
The contents of hemicellulose, cellulose and lignin are important for moso bamboo processing in biomass energy industry. The feasibility of using near infrared (NIR) spectroscopy for rapid ...determination of hemicellulose, cellulose and lignin was investigated in this study. Initially, the linear relationship between bamboo components and their NIR spectroscopy was established. Subsequently, successive projections algorithm (SPA) was used to detect characteristic wavelengths for establishing the convenient models. For hemicellulose, cellulose and lignin, 22, 22 and 20 characteristic wavelengths were obtained, respectively. Nonlinear determination models were subsequently built by an artificial neural network (ANN) and a least-squares support vector machine (LS-SVM) based on characteristic wavelengths. The LS-SVM models for predicting hemicellulose, cellulose and lignin all obtained excellent results with high determination coefficients of 0.921, 0.909 and 0.892 respectively. These results demonstrated that NIR spectroscopy combined with SPA-LS-SVM is a useful, nondestructive tool for the determinations of hemicellulose, cellulose and lignin in moso bamboo.
The regulation of iron (Fe) homeostasis is critical for plant survival. Although the systems responsible for the reduction, uptake, and translocation of Fe have been described, the molecular ...mechanism by which plants sense Fe status and coordinate the expression of Fe deficiency-responsive genes is largely unknown. Here, we report that two basic helix-loop-helix-type transcription factors, bHLH34 and bHLH104, positively regulate Fe homeostasis in Arabidopsis (Arabidopsis thaliana). Loss of function of bHLH34 and bHLH104 causes disruption of the Fe deficiency response and the reduction of Fe content, whereas overexpression plants constitutively promote the expression of Fe deficiency-responsive genes and Fe accumulation. Further analysis indicates that bHLH34 and bHLH104 directly activate the transcription of the Ib subgroup bHLH genes, bHLH38/39/100/101. Moreover, overexpression of bHLH101 partially rescues the Fe deficiency phenotypes of bhlh34bhlh104 double mutants. Further investigation suggests that bHLH34, bHLH104, and bHLH105 (IAA-LEUCINE RESISTANT3) function as homodimers or heterodimers to nonredundantly regulate Fe homeostasis. This work reveals that plants have evolved complex molecular mechanisms to regulate Fe deficiency response genes to adapt to Fe deficiency conditions.
Polygonum cuspidatum Sieb. et Zucc. (Polygonum cuspidatum), also known as Reynoutria japonica Houtt and Huzhang in China, is a traditional and popular Chinese medicinal herb. Polygonum cuspidatum ...with a wide spectrum of pharmacological effects has been used for treatment of inflammation, favus, jaundice, scald, and hyperlipemia, etc.
The present paper reviews the traditional applications as well as advances in botany, phytochemistry, pharmacodynamics, pharmacokinetics and toxicology of this plant. Finally, the tendency and perspective for future investigation of this plant are discussed, too.
A systematic review of literature about Polygonum cuspidatum is carried out using resources including classic books about Chinese herbal medicine, and scientific databases including Pubmed, SciFinder, Scopus, the Web of Science and others.
Polygonum cuspidatum is widely distributed in the world and has been used as a traditional medicine for a long history in China. Over 67 compounds including quinones, stilbenes, flavonoids, counmarins and ligans have been isolated and identified from this plant. The root of this plant is used as the effective agent in pre-clinical and clinical practice for regulating lipids, anti-endotoxic shock, anti-infection and anti-inflammation, anti-cancer and other diseases in China and Japan.
As an important traditional Chinese medicine, Polygonum cuspidatum has been used for treatment of hyperlipemia, inflammation, infection and cancer, etc. Because there is no enough systemic data about the chemical constituents and their pharmacological effects or toxicities, it is important to investigate the pharmacological effects and molecular mechanisms of this plant based on modern realization of diseases’ pathophysiology. Drug target-guided and bioactivity-guided isolation and purification of the chemical constituents from this plant and subsequent evaluation of their pharmacologic effects will promote the development of new drug and make sure which chemical constituent or multiple ingredients contributes its pharmacological effects. Additionally, chemicals and their pharmacological effects of the other parts such as the aerial part of this plant should be exploited in order to avoid resource waste and find new chemical constituents.
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