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.

Assessing effects of “source-sink” landscape on non-point source pollution based on cell units of a small agricultural catchment

Ascertaining the relationship between "source-sink" landscape and non-point source(NPS) pollution is crucial for reducing NPS pollution, however, it is not easy to realize this target on cell unit scale. To reveal the relationships between "sourcesink" landscape and NPS pollution based on cell units of a small catchment in the Three Gorges Reservoir Region(TGRR), the runoff and nutrient yields were simulated first by rainfall events on a cell unit scale based on the Annualized AGricultural Non-Point Source Pollution Model(AnnAGNPS). Landscape structure and pattern were quantified with "sourcesink" landscape indicators based on cell units including landscape area indices and locationweighted landscape indices. The results showed that:the study case of small Wangjiagou catchment highlighted a good prediction capability of runoff and nutrient export by the AnnAGNPS model. Throughout the catchment, the spatial distribution trends of four location-weighted landscape indices were similar to the trends of simulated total nitrogen(TN) and total phosphorus(TP), which highlighted the importance of spatial arrangement of "source" and "sink" landscape types in a catchment when estimating pollutant loads. Results by Pearson correlation analysis indicated that the location-weighted landscape index provided a more comprehensive account of multiple factors, and can better reflect NPS-related nutrient loss than other landscape indices applied in single-factor analysis. This study provides new findings for applying the "source-sink" landscape indices based on cell units in small catchments to explain the effect of "source-sink" landscape on nutrient export based on cell unit, and helps improve the understanding of the correlation between "source-sink" landscape and NPS pollution.

Landscape Ecology Researches on the Regulation of Non-point Source Pollution in Agroforestry Watershed

Non-point source(NPS) water pollution generated by agricultural production has become a major environmental issue in agroforestry watersheds such as the Three Gorges. Landscape ecology emphasizes the regulation and effect of landscape pattern on material flow, energy flow in the ecological processes. This paper reviewed landscape ecological approaches of controlling non-point source pollution in agroforestry watershed of the Three Gorges from the patch level and landscape level. Stage I: landscape ecological investigation. The investigation is to fi gure out landscape pattern characteristics of the watershed, major causes and key sections of the non-point source pollution, "source" patches and ecological process of non-point source pollution, and the feedback relationship between landscape pattern and non-point source pollution. Stage II: landscape ecological planning. In the patch level, the best management procedures(BMPs) are selected to judge the application effect. In the landscape level, new landscape elements are introduced, "source" and "sink" landscape patch types adjusted, landscape level regulation effect assessed. Stage III: landscape ecological management. Small-watershed landscape ecological construction is carried out from patch level and landscape level, BMPs implemented gradually, landscape ecological planning and management integrated, landscape heterogeneity enhanced, intensity of non-point source pollution controlled effectively to achieve sustainable development of small watersheds.

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.

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.

Trend surface analysis of forest landscape pattern in Guandishan forest region of Shanxi,China

Landscape pattern is a widely used concept for the demonstration of landscape characteristic features. The integral spatial distribution trend of landscape elements is interested point in the landscape ecological research, especially in those of complex secondary forest regions with confusing mosaics of land cover. Trend surface analysis which used in community and population ecological researches was introduced to reveal the landscape pattern. A reasonable and reliable approach for application of trend surface analysis was provided in detail. As key steps of the approach, uniform grid point sampling method was developed. The efforts were also concentrated at an example of Guandishan forested landscape. Some basic rules of spatial distribution of landscape elements were exclaimed. These will be benefit to the further study in the area to enhance the forest sustainable management and landscape planning.

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.

A novel algorithm for SLAM in dynamic environments using landscape theory of aggregation

To tackle the problem of simultaneous localization and mapping(SLAM) in dynamic environments, a novel algorithm using landscape theory of aggregation is presented. By exploiting the coherent explanation how actors form alignments in a game provided by the landscape theory of aggregation, the algorithm is able to explicitly deal with the ever-changing relationship between the static objects and the moving objects without any prior models of the moving objects. The effectiveness of the method has been validated by experiments in two representative dynamic environments: the campus road and the urban road.

Research on BIM Course System and Ideological and Political Essentials of Cost Engineering Major

The era of information technology has dawned on the construction industry,and Building Information Modeling(BIM)is one of the necessary engineering skills for those engaged in civil engineering professions at present and those who will engage in these professions in the future.Therefore,top universities have begun exploring ways to increase BIM-related teaching content in the curriculum system.In this paper,we discuss the integration of BIM in an in-depth manner with regard to the four course modules offered by cost engineering majors(professional foundation course,professional core course,industry-oriented course,and professional practical course)and analyze the construction of BIM curriculum ideology and politics system,the setting of teaching objectives,and the key points of curriculum ideology and politics.

Human Interaction Recognition in Surveillance Videos Using Hybrid Deep Learning and Machine Learning Models

Human Interaction Recognition(HIR)was one of the challenging issues in computer vision research due to the involvement of multiple individuals and their mutual interactions within video frames generated from their movements.HIR requires more sophisticated analysis than Human Action Recognition(HAR)since HAR focuses solely on individual activities like walking or running,while HIR involves the interactions between people.This research aims to develop a robust system for recognizing five common human interactions,such as hugging,kicking,pushing,pointing,and no interaction,from video sequences using multiple cameras.In this study,a hybrid Deep Learning(DL)and Machine Learning(ML)model was employed to improve classification accuracy and generalizability.The dataset was collected in an indoor environment with four-channel cameras capturing the five types of interactions among 13 participants.The data was processed using a DL model with a fine-tuned ResNet(Residual Networks)architecture based on 2D Convolutional Neural Network(CNN)layers for feature extraction.Subsequently,machine learning models were trained and utilized for interaction classification using six commonly used ML algorithms,including SVM,KNN,RF,DT,NB,and XGBoost.The results demonstrate a high accuracy of 95.45%in classifying human interactions.The hybrid approach enabled effective learning,resulting in highly accurate performance across different interaction types.Future work will explore more complex scenarios involving multiple individuals based on the application of this architecture.

Application of Off-season Cultivation Techniques in Landscape Engineering of Beijing Garden Expo

It is a key and difficult point in landscape engineering to keep higher survival rate of off-season cultivation.This paper takes widely-planted species such as Ginkgo biloba,Metasequoia glyptostroboides and Cedrus deodara in Beijing Garden Expo for example,summarizes key off-season cultivation techniques in urban landscaping,elaborated key technical links such as seedling selection,cultivation techniques,after-cultivation maintenance,and provided useful references for the off-season cultivation in urban landscaping of north China.

Analysis of the Relationship between Landuse and Non-point Source Pollution in Ashi River Basin

Landuse is one of the most influential factors of non-point source pollution. Based on the three-year landuse data( 2000,2005 and 2008),Arc GIS and Fragstat were used to analyze the landuse type and the change of landscape pattern. The relationships between landuse and non-point source-total nitrogen( NPS-TN) and nonpoint source-total phosphorus( NPS-TP) were discussed with the methods of spatially statistical analysis,landscape pattern analysis and principal component analysis. The study results conveyed that agricultural land and forestland,which accounted for over 92% of the study area,were the major landuse type of Ashi River Basin.Meanwhile,the NPS pollution had close connections with landuse type and landscape pattern. When it comes to landuse type,the export risks of NPS-TN and NPS-TP were agricultural land > urban land > grassland > forestland. As for landscape pattern,NPS-TN and NPS-TP were positively related to SHDI and SHEI, while negatively connected with LPI,AI and COHESION. Therefore,the study could reach the conclusion that the more fragmented and complicated the landscape patterns were,the more serious the NPS pollution was.

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.

A voxel-based fine-scale 3D landscape pattern analysis using laser scanner point clouds

The landscape pattern metrics can quantitatively describe the characteristics of landscape pattern and are widely used in various fields of landscape ecology.Due to the lack of vertical information,2D landscape metrics cannot delineate the vertical characteristics of landscape pattern.Based on the point clouds,a high-resolution voxel model and several voxel-based 3D landscape metrics were constructed in this study and 3D metrics calculation results were compared with that of 2D metrics.The results showed that certain quantifying difference exists between 2D and 3D landscape metrics.For landscapes with different components and spatial configurations,significant difference was disclosed between 2D and 3D landscape metrics.3D metrics can better reflect the real spatial structure characteristics of the landscape than 2D metrics.

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.

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.

Real-Time Safety Behavior Detection Technology of Indoors Power Personnel Based on Human Key Points

Safety production is of great significance to the development of enterprises and society.Accidents often cause great losses because of the particularity environment of electric power.Therefore,it is important to improve the safety supervision and protection in the electric power environment.In this paper,we simulate the actual electric power operation scenario by monitoring equipment and propose a real-time detection method of illegal actions based on human body key points to ensure safety behavior in real time.In this method,the human body key points in video frames were first extracted by the high-resolution network,and then classified in real time by spatial-temporal graph convolutional network.Experimental results show that this method can effectively detect illegal actions in the simulated scene.