PM_(2.5)浓度时空分布特征及驱动因子分析——以华中地区为例

近年来,华中地区极端恶劣天气多发,空气污染程度愈发严重。作为我国重要的经济交通枢纽,针对其空气污染进行研究十分必要。基于多源遥感数据,采用MK检验方法分析2000-2021年华中地区PM_(2.5)浓度时空分布特征,采用地理探测器方法探讨影响该地区PM_(2.5)浓度的因子。结果表明:华中地区PM_(2.5)浓度呈“北高南低,东高西低”分布特征;地区年均PM_(2.5)浓度呈倒“V”形分布特征,2000-2009年PM_(2.5)年均浓度显著上升,2010-2021年显著下降。在所有驱动因子中,相对湿度的驱动力最强(q=0.733),其与碳排放组合为最强交互因子(q=0.84)。交互探测结果显示社会因子和自然因子交互解释效果大于其他因子交互,表明地区PM_(2.5)分布受自然因素和社会因素共同影响。

Effect of sodium hyaluronate combined with rehabilitation training on knee joint injury caused by golf

BACKGROUND In high-intensity sports like golf,knee joints are prone to injury,leading to pain,limited mobility,and decreased quality of life.Traditional treatment methods typically involve rehabilitation exercises,but their effectiveness may be limited.In recent years,sodium hyaluronate has emerged as a widely used biomedical material in the treatment of joint diseases.AIM To explore the effect of sodium hyaluronate combined with rehabilitation training on pain degree,flexion range of motion and motor function of knee joint injured by golf.METHODS Eighty patients with knee joint injury caused by golf were randomly divided into control(group B)and observation group(group A).The group B was treated with rehabilitation training,and the group A was treated with sodium hyaluronate combined with rehabilitation training.The clinical efficacy,range of motion and function of knee joint,quality of life and inflammatory factors were compared.RESULTS The excellent and good rate of rehabilitation in the group A was raised than group B.At 6 weeks and 3 months after treatment,the range of motion of the two groups was raised than that before treatment,and that of the group A was raised than group B.After treatment,the scores of Lysholm and International Knee Documentation Committee(IKDC)in the group A were raised,and those in the group A were raised than group B.The VAS score of the two groups was reduced than that of the group B,and the SF-36 score of the group A was reduced than group B.The interleukin(IL)-1β,IL-8 and tumor necrosis factor-αin the two groups were reduced,and those in the group A were reduced than group B.CONCLUSION Sodium hyaluronate combined with rehabilitation training has a good clinical effect in the treatment of patients with knee joint injury caused by golf,which relieve pain,maintain knee joint function and improve patients'life quality.

An Improved Time Feedforward Connections Recurrent Neural Networks

Recurrent Neural Networks(RNNs)have been widely applied to deal with temporal problems,such as flood forecasting and financial data processing.On the one hand,traditional RNNs models amplify the gradient issue due to the strict time serial dependency,making it difficult to realize a long-term memory function.On the other hand,RNNs cells are highly complex,which will signifi-cantly increase computational complexity and cause waste of computational resources during model training.In this paper,an improved Time Feedforward Connections Recurrent Neural Networks(TFC-RNNs)model was first proposed to address the gradient issue.A parallel branch was introduced for the hidden state at time t−2 to be directly transferred to time t without the nonlinear transforma-tion at time t−1.This is effective in improving the long-term dependence of RNNs.Then,a novel cell structure named Single Gate Recurrent Unit(SGRU)was presented.This cell structure can reduce the number of parameters for RNNs cell,consequently reducing the computational complexity.Next,applying SGRU to TFC-RNNs as a new TFC-SGRU model solves the above two difficulties.Finally,the performance of our proposed TFC-SGRU was verified through sev-eral experiments in terms of long-term memory and anti-interference capabilities.Experimental results demonstrated that our proposed TFC-SGRU model can cap-ture helpful information with time step 1500 and effectively filter out the noise.The TFC-SGRU model accuracy is better than the LSTM and GRU models regarding language processing ability.

Parameters Compressing in Deep Learning

With the popularity of deep learning tools in image decomposition and natural language processing,how to support and store a large number of parameters required by deep learning algorithms has become an urgent problem to be solved.These parameters are huge and can be as many as millions.At present,a feasible direction is to use the sparse representation technique to compress the parameter matrix to achieve the purpose of reducing parameters and reducing the storage pressure.These methods include matrix decomposition and tensor decomposition.To let vector take advance of the compressing performance of matrix decomposition and tensor decomposition,we use reshaping and unfolding to let vector be the input and output of Tensor-Factorized Neural Networks.We analyze how reshaping can get the best compress ratio.According to the relationship between the shape of tensor and the number of parameters,we get a lower bound of the number of parameters.We take some data sets to verify the lower bound.

A Study on Classification and Detection of Small Moths Using CNN Model

Currently,there are many limitations to classify images of small objects.In addition,there are limitations such as error detection due to external factors,and there is also a disadvantage that it is difficult to accurately distinguish between various objects.This paper uses a convolutional neural network(CNN)algorithm to recognize and classify object images of very small moths and obtain precise data images.A convolution neural network algorithm is used for image data classification,and the classified image is transformed into image data to learn the topological structure of the image.To improve the accuracy of the image classification and reduce the loss rate,a parameter for finding a fast-optimal point of image classification is set by a convolutional neural network and a pixel image as a preprocessor.As a result of this study,we applied a convolution neural network algorithm to classify the images of very small moths by capturing precise images of the moths.Experimental results showed that the accuracy of classification of very small moths was more than 90%.

A Study on Small Pest Detection Based on a CascadeR-CNN-Swin Model

This study aims to detect and prevent greening disease in citrus trees using a deep neural network.The process of collecting data on citrus greening disease is very difficult because the vector pests are too small.In this paper,since the amount of data collected for deep learning is insufficient,we intend to use the efficient feature extraction function of the neural network based on the Transformer algorithm.We want to use the Cascade Region-based Convolutional Neural Networks(Cascade R-CNN)Swin model,which is a mixture of the transformer model and Cascade R-CNN model to detect greening disease occurring in citrus.In this paper,we try to improve model safety by establishing a linear relationship between samples using Mixup and Cutmix algorithms,which are image processing-based data augmentation techniques.In addition,by using the ImageNet dataset,transfer learning,and stochastic weight averaging(SWA)methods,more accuracy can be obtained.This study compared the Faster Region-based Convolutional Neural Networks Residual Network101(Faster R-CNN ResNet101)model,Cascade Regionbased Convolutional Neural Networks Residual Network101(Cascade RCNN-ResNet101)model,and Cascade R-CNN Swin Model.As a result,the Faster R-CNN ResNet101 model came out as Average Precision(AP)(Intersection over Union(IoU)=0.5):88.2%,AP(IoU=0.75):62.8%,Recall:68.2%,and the Cascade R-CNN ResNet101 model was AP(IoU=0.5):91.5%,AP(IoU=0.75):67.2%,Recall:73.1%.Alternatively,the Cascade R-CNN Swin Model showed AP(IoU=0.5):94.9%,AP(IoU=0.75):79.8%and Recall:76.5%.Thus,the Cascade R-CNN Swin Model showed the best results for detecting citrus greening disease.

A Novel Beam Search to Improve Neural Machine Translation for English-Chinese

Neural Machine Translation(NMT)is an end-to-end learning approach for automated translation,overcoming the weaknesses of conventional phrase-based translation systems.Although NMT based systems have gained their popularity in commercial translation applications,there is still plenty of room for improvement.Being the most popular search algorithm in NMT,beam search is vital to the translation result.However,traditional beam search can produce duplicate or missing translation due to its target sequence selection strategy.Aiming to alleviate this problem,this paper proposed neural machine translation improvements based on a novel beam search evaluation function.And we use reinforcement learning to train a translation evaluation system to select better candidate words for generating translations.In the experiments,we conducted extensive experiments to evaluate our methods.CASIA corpus and the 1,000,000 pairs of bilingual corpora of NiuTrans are used in our experiments.The experiment results prove that the proposed methods can effectively improve the English to Chinese translation quality.

Randomized Controlled Pilot Trial of Truncal Exercises after Stroke to Improve Gait and Muscle Activity

The purpose of the present study was to evaluate the effects of a trunk exercise program on the gait and muscle activity in stroke patients. The participants of this pilot study included six hemiplegic stroke patients. The outcomes were surface electromyography (sEMG) and spatiotemporal gait parameters. In analysis of sEMG, no statistically difference was found between pre- and post-training of Maximal Voluntary Isometric Contraction (MVIC) in rectus abdominis and external abdominal oblique muscle, but it tended to increase. However, the gait parameter significantly increased in walking speed, walking cycle, and affected stride length in stroke patients. These results suggest that the trunk exercise program may in part improve the gait of chronic stroke patients.

刍议网络语言成因的传播学及心理学分析

随着互联网和信息技术的不断发展,网络语言逐渐开始出现于语言表达形式之中,并成为人们网络交流的重要途径。本文主要从传播学和心理学两个方面,对网络语言的成因进行有效分析。

A Study on Cascade R-CNN-Based Dangerous Goods Detection Using X-Ray Image

X-ray inspection equipment is divided into small baggage inspection equipment and large cargo inspection equipment.In the case of inspection using X-ray scanning equipment,it is possible to identify the contents of goods,unauthorized transport,or hidden goods in real-time by-passing cargo through X-rays without opening it.In this paper,we propose a system for detecting dangerous objects in X-ray images using the Cascade Region-based Convolutional Neural Network(Cascade R-CNN)model,and the data used for learning consists of dangerous goods,storage media,firearms,and knives.In addition,to minimize the overfitting problem caused by the lack of data to be used for artificial intelligence(AI)training,data samples are increased by using the CP(copy-paste)algorithm on the existing data.It also solves the data labeling problem by mixing supervised and semi-supervised learning.The four comparative models to be used in this study are Faster Regionbased Convolutional Neural Networks Residual2 Network-101(Faster R-CNN_Res2Net-101)supervised learning,Cascade R-CNN_Res2Net-101_supervised learning,Cascade Region-based Convolutional Neural Networks Composite Backbone Network V2(CBNetV2)Network-101(Cascade R-CNN_CBNetV2Net-101)_supervised learning,and Cascade RCNN_CBNetV2-101_semi-supervised learning which are then compared and evaluated.As a result of comparing the performance of the four models in this paper,in case of Cascade R-CNN_CBNetV2-101_semi-supervised learning,Average Precision(AP)(Intersection over Union(IoU)=0.5):0.7%,AP(IoU=0.75):1.0%than supervised learning,Recall:0.8%higher.

不寻常的祭坛装饰：芙烈达·卡萝的画作《桃乐茜·黑尔的自杀》

作者从芙烈达·卡萝的一幅画《桃乐茜·黑尔的自杀》出发，叙述了其创作的缘由，并描绘了画面整体构图和卡萝运用的超现实主义创作手法。作者认为，正是卡萝自己的观点、现实经历和对生死的接受，促使她生动地描绘出桃乐茜最后一刻对自杀的厌倦，被当时文艺评论家马赛尔推崇为墨西哥“超现实主义派”创作的代表作之一。

Analysis of Skin Parameters of Korean Men According to the Parts of the Body for Integumentary Physiotherapy Research

Studies have demonstrated that some cutaneous biophysical properties vary with the part of the body. The results to date of skin conditions in human skin of multiple parts of the body have not yet been well established. In this study, we assessed the differences in the skin’s sebum, moisture, pores, wrinkles, pigmentation, and elasticity of each body part in Korean men in their 20s. A total of 34 healthy men were enrolled. A Skin Diagnosis Meter was used to measure the skin’s surface sebum, moisture, pores, wrinkles, pigmentation, and elasticity of each body part. The sebum content was significantly higher on the face than at other sites. Moisture was significantly high on the feet. Pores were significantly high on the face. Wrinkles were significantly high on the face. Pigmentation was high on the face and neck, but not significantly. Elasticity was significantly high on the hands. In the correlation analysis results, sebum and pore were positively correlated, but sebum and moisture and wrinkle and elasticity were negatively correlated. For nearly the first time, this study resulted in systematic reference values for standardized biophysical measuring methods and body parts reflecting the skin physiology of healthy South Korean men. The results show that skin’s surface sebum, moisture, pores, wrinkles, pigmentation, and elasticity vary with the part of the body.

Analysis of Interferential Current Therapy-Induced Skin Changes in Healthy Korean Men

We examined the changes in numerous skin conditions before and after the ap-plication of interferential current therapy to various regions of healthy male bodies. In this study, we assessed the differences in the skin’s sebum, moisture levels, pores, wrinkles, pigmentation, and elasticity on the shoulders, lower back, and the knees of Korean males in their 20s. A total of 30 healthy males were in-cluded in the study. We used a skin diagnosis meter as a device for measuring the state of the skin. A statistical difference was found when comparing the pre- and post-measurement values in regards to the moisture levels, wrinkles, and pig-mentation. In the correlation analysis results, the sebum and pigmentation, moisture levels and wrinkles, moisture levels and pigmentation, and moisture levels and elasticity were all positively correlated, respectively. The results of this study partially suggest that a change in skin condition is associated with ex-ternal stimulation. The study also found that the effects of the application of in-terferential current therapy on the various skin conditions may differ depending on the region of the body that the application is conducted as well.

Characteristic Dermatologic Changes in the Condition of Skin after Ultrasonic Stimulation in Healthy Korean Men

The aim of our study was to recognize different skin conditions of the face and neck using six biophysical parameters and to show the changes after the application of ultrasonic stimulation (US). We assessed the differences in the sebum, moisture, pores, wrinkles, pigmentation, and elasticity of the skin in the face and neck regions. A total of 30 healthy men in their 20s were enrolled. We used a skin diagnosis meter to assess the state of the skin. The sebum and pores of the face were more significant than in the neck. The amount of moisture in the U-zone was significantly higher than in other areas. Statistical differences were found between the pre-and post-measure-ment values in the sebum, moisture, wrinkles and pigmentation. Wrinkles and pigmentation were positively correlated. Our data showed that the changes in skin condition are associated with external stimulants. The effect of US on skin may differ depending on the part of the body, and some biophysical properties of skin vary depending on the location on the body.

Compensation of image noise induced by difference in optical characteristics of array-LED chips of LED print head

There are various applied electro-optical devices, which utilize light emitting didoe(LED) chip array for applications to displays and opto-electronic sensors. In those devices, it is the one of the critical technical issues to minimize uncertain fluctuations including optical power and optical density. Due to variation in operating environment of a device, those are not corrected precisely by controlling parameters based on simple relation between parameters and resultant abovementioned outputs.Therefore, there is essential need to correct outputs in real-time based on correction function generated from the consideration on various operation condition. In this article, we introduce an output correction method through reporting real-time image noise reduction in the application to electro-photography with LED print head. In the technology of LED print head, as differences in optical characteristics between each LED cause vertical image noise, it should be corrected in order to obtain images that are comparable or better in quality compared to those produced by the conventional laser scanning method. Even though it seems that the method used to obtain uniform light power from each LED can solve this problem, it does not work well for high-resolution printing. Therefore, a scan method involving correction by a printed and scanned pattern is introduced through this work. The scan method is composed of correction patterns to minimize printing noise by its shape, the correction algorithm to calculate the optimized value and the printing algorithm to control gray levels in real-time precisely. We believe that the developed correction method upgrades the printing quality of the LPH printer better than commercial printers. The developed correction method can also be applied to various application areas that use an array-type light source such as display systems and lighting systems.

MouseVenue3D:A Markerless Three-Dimension Behavioral Tracking System for Matching Two-Photon Brain Imaging in Free-Moving Mice

Understanding the connection between brain and behavior in animals requires precise monitoring of their behaviors in three-dimensional(3-D)space.However,there is no available three-dimensional behavior capture system that focuses on rodents.Here,we present MouseVenue3D,an automated and low-cost system for the efficient capture of 3-D skeleton trajectories in markerless rodents.We improved the most time-consuming step in 3-D behavior capturing by developing an automatic calibration module.Then,we validated this process in behavior recognition tasks,and showed that 3-D behavioral data achieved higher accuracy than 2-D data.Subsequently,MouseVenue3D was combined with fast high-resolution miniature two-photon microscopy for synchronous neural recording and behavioral tracking in the freely-moving mouse.Finally,we successfully decoded spontaneous neuronal activity from the 3-D behavior of mice.Our findings reveal that subtle,spontaneous behavior modules are strongly correlated with spontaneous neuronal activity patterns.