Analysis of the Significance of Key Points of Patient Interventional Psychological Care and Pain Care

Interventional therapy has become increasingly popular in clinical practice due to advancements in medical technology.However,patients often experience psychological and physiological pressure due to its invasive nature.The management of patient discomfort and tension is crucial to ensure effective treatment.Psychological and pain management are essential components of interventional therapy,as they significantly impact patient recovery and prognosis.This article discussed the importance of interventional psychological and pain care for patients,starting with the development and spread of interventional therapy.The significance of providing high-quality nursing services to patients and improving their quality of life was also discussed.

Identification of the key thermal points on machine tools by grouping and optimizing variables

The grouping and optimization approach to identify the key thermal points on machine tools is studied.To solve the difficulty in grouping because of the high correlated variables from distinct groups,the variables grouping technique is improved.Temperature variables are sorted according to their relativities with the thermal errors.The representative temperature variables are determined by analyzing the variable correlation in sort order and removing the other variables in the same group.Considering the diverse effect of importing the different variables on thermal error model,the method of variable combination optimization is improved.Regression models made up of different combination of representative temperature variables are evaluated by the index of both the determined coefficient and the average residual squares to select the combination of the temperature variables.For the machine tools with complicated structures which need more initial temperature measuring points the improvement is demanded.The improved approach is applied to a precision horizontal machining center to identify the key thermal points.Experimental results show that the proposed approach is capable of avoiding the high correlation among the different groups' variables,effectively reducing the number of the key thermal points without depressing the prediction accuracy of the thermal error model for machine tools.

DM Code Key Point Detection Algorithm Based on CenterNet

Data Matrix(DM)codes have been widely used in industrial production.The reading of DM code usually includes positioning and decoding.Accurate positioning is a prerequisite for successful decoding.Traditional image processing methods have poor adaptability to pollution and complex backgrounds.Although deep learning-based methods can automatically extract features,the bounding boxes cannot entirely fit the contour of the code.Further image processing methods are required for precise positioning,which will reduce efficiency.Because of the above problems,a CenterNet-based DM code key point detection network is proposed,which can directly obtain the four key points of the DM code.Compared with the existing methods,the degree of fitness is higher,which is conducive to direct decoding.To further improve the positioning accuracy,an enhanced loss function is designed,including DM code key point heatmap loss,standard DM code projection loss,and polygon Intersection-over-Union(IoU)loss,which is beneficial for the network to learn the spatial geometric characteristics of DM code.The experiment is carried out on the self-made DM code key point detection dataset,including pollution,complex background,small objects,etc.,which uses the Average Precision(AP)of the common object detection metric as the evaluation metric.AP reaches 95.80%,and Frames Per Second(FPS)gets 88.12 on the test set of the proposed dataset,which can achieve real-time performance in practical applications.

Contrast Enhancement Based Image Detection Using Edge Preserved Key Pixel Point Filtering

In existing methods for segmented images,either edge point extraction or preservation of edges,compromising contrast images is so sensitive to noise.The Degeneration Threshold Image Detection(DTID)framework has been proposed to improve the contrast of edge filtered images.Initially,DTID uses a Rapid Bilateral Filtering process for filtering edges of contrast images.This filter decomposes input images into base layers in the DTID framework.With minimal filtering time,Rapid Bilateral Filtering handles high dynamic contrast images for smoothening edge preservation.In the DTID framework,Rapid Bilateral Filtering with Shift-Invariant Base Pass Domain Filter is insensitive to noise.This Shift-Invariant Filtering estimates value across edges for removing outliers(i.e.,noise preserving base layers of the contrast image).The intensity values are calculated in the base layer of the contrast image for accurately detecting nearby spatial locations using Shift-Invariant base Pass Domain Filter(SIDF).At last,Affine Planar Transformation is applied to detect edge filtered contrast images in the DTID framework for attaining a high quality of the image.It normalizes the translation and rotation of images.With this,Degeneration Threshold Image Detection maximizes average contrast enhancement quality and performs an experimental evaluation of factors such as detection accuracy,rate,and filtering time on contrast images.Experimental analysis shows that the DTID framework reduces the filtering time taken on contrast images by 54%and improves average contrast enhancement quality by 27%compared to GUMA,HMRF,SWT,and EHS.It provides better performance on the enhancement of average contrast enhancement quality by 28%,detection accuracy rate by 26%,and reduction in filtering time taken on contrast images by 30%compared to state-of-art methods.

SIX KEY POINTS FOR ACUPUNCTURE THERAPY

In the present paper, the author puts forward six key points for acupuncture treatment of diseases, namely, (1) careful examination, (2) definite diagnosis, (3) precise and appropriate identification of syndromes, (4) accurate location of the acupoint, (5) flexible application of needling manipulations, and (6) 'Deqi'. The first three aspects are the foundation, accurate location and flexible needling manipulations are also the prerequisite for effective treatment of diseases. In addition, sound theoretical basic knowledge of both traditional Chinese medicine (TCM) and modern medicine, and flexibly applying suitable needling maneuvers, stimulating quantity and duration of needle retaining in accordance with the concrete state of disease and the patient's conditions are also very important in clinical practice of acupuncture.

The Research on the Methods to Confirm the Key Control Points of the Internal Accounting Control

The control points are the key issue of the internal control, and the key control points mean the control joints that play an important part in the process of the operation. If these key control points are not well controlled, the process of the operation disposal will be mistaken and cannot reach the goal. However, for the confirmation of the control points, many studies only do qualitative research from the important aspect instead of quantificational research. They are devoid of a series of scientific methods. This paper advances quantificational methods to confirm the key control points from two aspects of job evaluation and mathematics model.

CPC Central Committee and the State Council Issued the Decision to Specify the “Key Points” of the Universal Two-child Policy

The Decision of CPC Central Committee and the State Council on Full Implementation of the Universal Two-child policy and Innovation and Improvement of Family Planning Service Management（Hereinafterreferred to as the Decision）was announced on January 5,2016.China will implement a birth registration service system.

Difficulty Analysis of HVAC Construction and Key Analysis of Improved Technology

This paper expounds the concept of HVAC construction,specifically analyzes the current situation of HVAC construction in construction engineering,and focuses on the key and difficult points in HVAC construction.In order to provide an effective reference for improving the quality of HVAC construction in the current construction engineering,some suggestions are put forward for improvement of relevant technologies involved in key and difficult points.

Key Points of Supervision of Third-Party Payment Business:A Comparative Analysis of China's Mainland and Macao

China's Mainland has witnessed remarkable achievements in payment innovations based on internet and financial technologies in recent years,whereas Macao has made little progress in financial technologies,especially in payment technologies.Based on the concept and types of third-party payment business in China's Mainland and Macao,as well as to investigate the causes for Macao’s lack of innovation in third-party payment,this study compares their differences from two aspects:business licensing authorities and key points of supervision.By comparison,although the classification and methods of third-party payment businesses are different between China's Mainland and Macao,they are all managed and licensed by a unified supervision department.Moreover,the key points of supervision in both places are similar,but unlike China's Mainland,which takes financial risk prevention as the principle and financial technology as the means to encourage innovation,Macao showed obvious deficiencies.In order to further deepen the connection between the financial markets of China's Mainland and Macao as well as boost financial technologies in Macao,this study aims to provide some suggestions and references for the development of cross-border payment systems.

Multi-Branch High-Dimensional Guided Transformer-Based 3D Human Posture Estimation

The human pose paradigm is estimated using a transformer-based multi-branch multidimensional directed the three-dimensional(3D)method that takes into account self-occlusion,badly posedness,and a lack of depth data in the per-frame 3D posture estimation from two-dimensional(2D)mapping to 3D mapping.Firstly,by examining the relationship between the movements of different bones in the human body,four virtual skeletons are proposed to enhance the cyclic constraints of limb joints.Then,multiple parameters describing the skeleton are fused and projected into a high-dimensional space.Utilizing a multi-branch network,motion features between bones and overall motion features are extracted to mitigate the drift error in the estimation results.Furthermore,the estimated relative depth is projected into 3D space,and the error is calculated against real 3D data,forming a loss function along with the relative depth error.This article adopts the average joint pixel error as the primary performance metric.Compared to the benchmark approach,the estimation findings indicate an increase in average precision of 1.8 mm within the Human3.6M sample.

Breeding and Cultivation Technique of Forage Foxtail Millet Variety Jicaogu 1

[Objective] This study was conducted to solve the problem of the lacking of special forage foxtail millet varieties. [Method] With wild large-grain foxtail millet as an original material, foxtail millet variety Jicaogu 1 （S724） for forage use was bred. [Result] Jicaogu 1 has following outstanding characteristics： （1） high content of crude protein： quality detection showed that the millet straw had a high content of crude protein up to 9.8%; （2） high yields of fresh grass and hay： in field detection, the average yield of fresh grass was 58 308.15 kg/hm2, which was higher than Sicao 2 （35 763.00 kg/hm2） by 58.29%, and the hay yield was 15 922.65 kg/hm2, which was higher than Sicao 2 （11 548.05 kg/hm2） by 37.88%; and （3） biological characteristics： Jicaogu 1 shows young seedlings with a growth period of 122 d, a plant height of 198.22 cm, an ear length of 23.65 cm, a stem/leaf ratio of 1.43 and a fresh weight/dry weight ratio of 37.86, there are 2-3 tillers generally, and the seed yield is 3 383.40 kg/hm2. [Conclusion] Summer seeding in vacant field in North China or spring seeding in Inner Mongolia could be carried out with Jicaogu 1, which is also adapt to mechanized harvest. The development of forage foxtail millet could be promoted by strengthening the extension of Jicaogu 1.

Analysis of Cold Wave Weather Process in Dalian Area on December 29-30,2009

By using the routine weather data and the numerical value forecast products,applying the weather analysis and diagnostic analysis methods,the cold wave weather which happened in the south area of Dalian was analyzed on December 29-30,2009.The results showed that based on the temperature rise in prior period,the strong cold air accumulated in Mongolia and passed Ulan Bator,Erenhot to invade Dalian area.In the cold wave process,the circulation situations in the middle and high latitudes were the 'one ridge and one trough' pattern in Asia.The dynamic mechanisms were the rotary low-pressure trough in high altitude and the strong frontal zone,and the flow field which induced the cold wave to break out was the 'low trough rotation pattern'.After the cold air broke out,Dalian area was controlled by the strong cold advection.The cold high-pressure on the ground entered into the key zone and reached the intensity of cold wave.However,the circulation of cold wave occurrence was southerly,and the shifts of cold air and influence system were quicker.Therefore,the cold wave appeared in Dalian's south areas which included Lvshun,Dalian and Jinzhou.On this basis,the key point of cold wave weather forecast in Dalian area was summarized.

公共卫生研究的伦理审查要素表构建和审查启示

目的针对公共卫生研究的特点构建伦理审查要素表,为今后相关伦理审查工作提供切实可行的参考依据。方法采用文本分析的方法结合公共卫生学科特点及相关文献资料,将本机构的公共卫生研究项目进行分类。采用文献回顾的方法查阅国内外相关法律法规和回顾既往文献研究的基础上,结合工作实际需求咨询相关伦理专业专家初步构建公共卫生研究的伦理审查要素表。结果将公共卫生研究根据学科特点进行分类:使用现有人体生物样本或信息数据的研究、不涉及干预且采集人体健康信息的前瞻性研究、涉及健康行为干预(饮食、运动等)的研究、不涉及干预且采集人体生物样本的前瞻性研究、临床试验研究(疫苗、化妆品或体外诊断试剂效果检验)。使用现有人体生物样本或信息数据研究的伦理审查主要从研究的设计与实施、研究参与者的隐私保护两方面进行考虑。涉及健康行为干预的前瞻性研究的伦理审查主要从干预研究的设计与实施、知情同意、隐私保护、研究风险与获益评估、研究参与者的补偿和医疗保护、研究参与者的招募、弱势群体的保护等方面进行考虑。不涉及干预且采集人体生物样本或者信息数据的前瞻性研究的审查重点为生物样本及信息数据的采集、储存、使用的过程。结论伦理委员会可以根据不同的公共卫生研究类型特点有针对性地进行伦理审查,提高审查效率和质量,重视对知情同意、隐私保护、弱势群体的保护、权益和风险的评估等方面的考量,保护研究参与者的身心安全和合法权益。

Optimal Deep Convolutional Neural Network with Pose Estimation for Human Activity Recognition

Human Action Recognition(HAR)and pose estimation from videos have gained significant attention among research communities due to its applica-tion in several areas namely intelligent surveillance,human robot interaction,robot vision,etc.Though considerable improvements have been made in recent days,design of an effective and accurate action recognition model is yet a difficult process owing to the existence of different obstacles such as variations in camera angle,occlusion,background,movement speed,and so on.From the literature,it is observed that hard to deal with the temporal dimension in the action recognition process.Convolutional neural network(CNN)models could be used widely to solve this.With this motivation,this study designs a novel key point extraction with deep convolutional neural networks based pose estimation(KPE-DCNN)model for activity recognition.The KPE-DCNN technique initially converts the input video into a sequence of frames followed by a three stage process namely key point extraction,hyperparameter tuning,and pose estimation.In the keypoint extraction process an OpenPose model is designed to compute the accurate key-points in the human pose.Then,an optimal DCNN model is developed to classify the human activities label based on the extracted key points.For improving the training process of the DCNN technique,RMSProp optimizer is used to optimally adjust the hyperparameters such as learning rate,batch size,and epoch count.The experimental results tested using benchmark dataset like UCF sports dataset showed that KPE-DCNN technique is able to achieve good results compared with benchmark algorithms like CNN,DBN,SVM,STAL,T-CNN and so on.

An Intelligent Framework for Recognizing Social Human-Object Interactions

Human object interaction(HOI)recognition plays an important role in the designing of surveillance and monitoring systems for healthcare,sports,education,and public areas.It involves localizing the human and object targets and then identifying the interactions between them.However,it is a challenging task that highly depends on the extraction of robust and distinctive features from the targets and the use of fast and efficient classifiers.Hence,the proposed system offers an automated body-parts-based solution for HOI recognition.This system uses RGB(red,green,blue)images as input and segments the desired parts of the images through a segmentation technique based on the watershed algorithm.Furthermore,a convex hullbased approach for extracting key body parts has also been introduced.After identifying the key body parts,two types of features are extracted.Moreover,the entire feature vector is reduced using a dimensionality reduction technique called t-SNE(t-distributed stochastic neighbor embedding).Finally,a multinomial logistic regression classifier is utilized for identifying class labels.A large publicly available dataset,MPII(Max Planck Institute Informatics)Human Pose,has been used for system evaluation.The results prove the validity of the proposed system as it achieved 87.5%class recognition accuracy.

Existing Problems and Solutions on Rural Primary School Language Education

At present,there are still many problems in language teaching in rural primary schools,which will affect the quality of teaching if we don't pay much attention to them.This article focuses on the existing flaws in current language teaching and provides some solutions.

Suburban Sightseeing Farm Design from the Perspective of Behaviordriven Design

Suburban sightseeing farm has always been restrained by such problems as focusing on form and visual effect, low design level, poor depth, similarity with others, poor sustainability and so on. This paper proposed major characteristics of sightseeing farm design based on core connotations of behavior-driven design from the perspective of cognitive psychology. Cases were taken to analyze the design techniques of sightseeing farm, and it was concluded that sightseeing farm design based on behavior-driven perspective should orient to performancebased, refi ned, individualized and participatory from the four perspectives of highlighting functions, deepening the details, stressing originality, and optimizing experience, in order to provide new thoughts for solving existing problems of current sightseeing farm design.