bluuebunny/crossref_metadata_2025 huggingface dataset:
Towards Household Blood Glucose Meter in a Sample of Older People
Authors: Liu Hao , Li Xu , Lu Honglei , Lu Peng
Published: April 2023

This paper constructed a new model by integrating the product design factors into the Technology Acceptance Model (TAM), which aimed to investigate the relationship between the design elements of the household blood glucose meter and the use intention of the elderly users. 184 valid samples were collected and the software of SPSS 23.0 and SPSSAU online were used to test the model and hypotheses. The results are shown as below: (1) Older people's perceived usefulness (PU) and perceived ease of use (PEOU) toward household blood glucose meter has a significantly positive effect on their use intention (UT); Older people's perceived ease of use (PEOU) toward household blood glucose meter has a significantly positive effect on their perceived usefulness(PU); (2) The functional design(FD) factors of household blood glucose meter has a significant positive effect both on older people's perceived usefulness(PU) and on their perceived ease of use (PEOU), and it also has a positive effect on older people’s use intention (UT) directly; The appearance design (AD) factors of household blood glucose meter has a significant positive effect both on older people's perceived ease of use (PEOU) and on their perceived usefulness (PU); And the interaction design (ID) factors of household blood glucose meter has a weakly negative effect on older people's perceived ease of use (PEOU) and has a weakly positive effect on their perceived usefulness (PU); (3) The past-experience (UX) of older people has no moderating effect between use perception and use intention (UT) of household blood glucose meter. Finally, some reasonable suggestions are given from product design based on the quantitative analysis to make the design of the home blood glucose meter more consistent with the cognition of the elderly users, so as to improve the interest of blood sugar self monitoring in elderly diabetes group, shape their healthy living and lifestyle.
Research on the System Dynamics of Service-oriented Manufacturing Level
Authors: Chen Jianbiao , Gu Aiqin , Zhong Jiezhi
Published: April 2023

Service-oriented manufacturing is the product of China's industrial transformation, and is suitable for the new form of business of China's industrial upgrading. Starting from the value chain theory, the system dynamics theory is applied to build the three subsystems of service-oriented industry, analyze the factors affecting the service-oriented manufacturing level, establish the causal relationship diagram of service-oriented manufacturing level, construct the system dynamics flow chart of service-oriented manufacturing level, and provide a new theoretical model for the research of service-oriented manufacturing level.
Demand Grading of Emergency Medical Materials Based on Factor Analysis
Authors: Xin Yue , Wang Shimin
Published: April 2023

Reasonable and scientific classification and urgency classification of emergency materials is the premise and basis of emergency management, which affects the effect and efficiency of emergency rescue. Emergency medical materials are related to people's life, health, and safety. In this paper, based on the early stage of COVID-19, the demand for emergency medical materials is combined to determine the demand grading evaluation indicator system, and factor analysis is used to reduce the dimensionality of data and to determine the weights of each indicator. Therefore, a comprehensive evaluation model is established and the demand for emergency medical materials is graded by clustering.
Research on Water Resources Development and Utilization Based on Linear Regression and Multiple Nonlinear Regression
Authors: Chen Yijing , Zhang Genhua , Xie Siyan
Published: April 2023

With the further development of industrialization and urbanization, China's water resources will be more severe. In order to study the synergy of the three red line targets, we predicted the total water consumption in 2030 by establishing the total water consumption model and using the linear regression prediction method. It is assumed that the water consumption of 10,000 yuan of industrial added value and the effective utilization coefficient of agricultural irrigation water all reached the red line value in 2030. Next, a multivariate nonlinear regression model of total water consumption is established, and the indirect substitution method is used to obtain the function of the internal relationship among the water consumption of 10,000 yuan GDP, the actual water consumption per mu of cultivated land for irrigation, and the water consumption of 10,000 yuan industrial added value, which includes time variables, and then the sensitivity analysis of the above functions are carried out. The following conclusions are drawn: China's overall water resources development and utilization should adopt the policy of improving the effective utilization coefficient of farmland irrigation water and reducing the industrial added value water consumption of 10,000 yuan as a supplement.
Research on properties of Bitcoin Based on GARCH model
Authors: Yuan Jiacong
Published: April 2023

Cryptocurrencies have become a world-class phenomenon, with governments, companies and investors facing huge challenges and opportunities. Bitcoin is the one of most widely known cryptocurrencies. People prefer to use Bitcoin as an asset to invest for profit and hedge risk than for its payment function. This is the reason for the study of bitcoin market is so important. Many scholars had used daily data on bitcoin to construct different GARCH models to analyse the volatility of its returns. This research builds a GARCH model for the logarithmic return series of the bitcoin price to understand the volatility of the bitcoin price over the experimental time horizon. The experimental results show that the price of bitcoin is more volatile and vulnerable to external shocks. The analysis suggests that Bitcoin is more clearly a speculative financial instrument and that the price of Bitcoin is highly frothy.
The Unique Aesthetic Experience of VR Technology
Authors: Fu Xiaoqi , Zhou Zherui , Zhu Xinrui
Published: April 2023

VR as an emerging medium holds potential as a new visual form that has applications in diverse fields including but not limited to educational, artistic, or entertainment. New elements of presence, immersion, and interactivity characterize a completely new aesthetic experience for its users, which will be explored in this paper. Aesthetic experience is defined to be the experience that differs from everyday life, in which psychological focuses are completely on the subject at hand. Different aspects of the aesthetic experience include: fascination, or the user’s attention analyzed through lenses of physical and psychological; appraisal, or the cognition of the narrative story and compositional elements within VR works; and creativity, or the user’s ability to interact and create within virtual worlds. Through research and cumulation, this paper will conclude and create a holistic view of the future of VR and the aesthetic experience.
The Applications of Interface Design and User Experience in Virtual Reality
Authors: Xie Hanqing
Published: April 2023

With the rapid development of science and technology, the application of Virtual Reality (VR) technology is becoming more and more widespread. With its immersion, interactivity and expandability, VR technology has become a promising technology with broad application prospects. Therefore, this paper aims to investigate the factors that influence user experience in the design of user interface in VR environment, and to summarize the key points of VR user interface design in different application areas. The article will take interface design and user experience as the starting point to compare different user interface modes and their impact on user experience in VR environment; meanwhile, the design points of VR user interface in education field and game field and the impact factors on user experience in different scenarios are compared and summarized respectively. The final part of the article summarizes the user interface in VR environment in education and game field, and provides an outlook on the future improvement and enhancement of user experience in VR scenario.
The Role and Impact of VR during the Epidemic
Authors: Ruan Bolun , Qian Yiyi , Zhang Entong
Published: April 2023

Since the outbreak began in the world, people have been so frantic that they can't go about their normal lives. But virtual reality is an almost perfect solution to this problem. This paper from virtual reality technology to office and learning help; The influence of virtual reality technology on economic market and the influence of virtual reality technology on medical treatment are discussed in three parts respectively. First of all, people's feelings about the integration of virtual reality technology into daily life under the epidemic and the acceptance of virtual reality technology to realize remote working and remote teaching. Secondly, virtual reality technology combined with all social strata and applied to all walks of life, the only virtual reality technology cannot solve the tourism industry suffered a heavy blow. Finally, during the epidemic period, virtual reality technology can also be used if offline training or rehabilitation training with patients is not available. These technologies are also applicable even in the future when there is no epidemic.
Application of Virtual Reality in Different Fields
Authors: Feng Chuxuan , Shao Jiawei
Published: April 2023

Virtual reality technology is a rapid development of technology in recent years, has a vital role in the development of different fields. Using image display, human-computer interaction and other technologies to generate three-dimensional environment. Enable participants to interact and manipulate virtual environments and objects in real time. This paper analyses and summarizes the development of VR from three areas. Firstly, it analyses the immersive experience brought by VR in games and discusses the influence of VR on games. Then it summarizes the application of VR in medical care and other fields, bringing more effective means to the treatment of diseases. Doctors can use VR headsets to practice more surgeries and train the younger generation. Finally, the differences between VR films and traditional films are analysed from the perspective of films. At the end of this paper, the development of VR in the above three fields are summarized and prospected.
Global Temperature Prediction based on Time Series and Global Climate
Authors: Chen Yujia , Jiang Ting , Li Siben
Published: April 2023

Global warming is one of the topics of the highest public concern in recent years. This paper mainly analyzes and forecasts the global temperature. This paper have established three models to describe the past and predict the future global temperature level. The first model is the integrated model of ARIMA and BP neural network, which can flexibly mine the linear and nonlinear relationships behind the data. The second model is the Full Convolution Network (FCN) model, which can predict end-to-end time series. The third model is the SVR-QM model based on climate indicators. The three models are established at different angles, and all have good fitting effects.
Composition analysis and identification of ancient glass products based on K-Means clustering analysis algorithm
Authors: Zhong Yijing , Pei Yuhang
Published: April 2023

Ancient glass is a valuable physical evidence of early trade exchanges, and it is very susceptible to weathering caused by the environmental impact of burial. Therefore, the establishment of a glass cultural relics identification model and the analysis of the chemical composition of glass cultural relics are extremely important for the classification and protection of cultural relics in our country. In this paper, we first use differential analysis to find out the chemical composition with significant differences before and after weathering, and obtain the classification laws of high potassium glass and lead-barium glass. Then the 14 chemical components of high potassium glass and lead-barium glass were analyzed by K-Means clustering, and finally 8 subclasses were divided. After testing, the model has low sensitivity, strong stability and good robustness. On this basis, the improved PYH-Topsis solution distance method is used to construct a judgment matrix, analyze the chemical composition of glass cultural relics of unknown categories, and identify the types to which they belong.
An analytical identification model for ancient glass based on support vector machine and cluster analysis
Authors: Zhang Yexi , Cheng Rongkai , Li Jinglei
Published: April 2023

Glass artifacts are easily weathered by environmental influences during burial, and the internal chemical composition is exchanged with the external environment, resulting in changes in its composition ratio. For archaeological interrogation, it is of great significance to study the chemical composition of glass before and after weathering and related issues. In this paper, a support vector machine model is used to reasonably separate the data points of high potassium glass and lead-barium glass, and a linear classification function is derived, i.e., the classification law of the two types of glass is obtained. Then, this paper performs R-type cluster analysis on the chemical composition indexes first, and reduces the dimensionality of several indexes; then performs Q-type cluster analysis on the sample detection points, and performs a one-way ANOVA test on the classification scheme of different numbers of subclasses obtained, and finally divides them into four subclasses. On this basis, the data of the unknown class of glass artifacts are substituted into the trained support vector machine model, and the type to which they belong can be determined by calculating the value of the judgment linear classification function.
Summary of the methods of composition analysis and identification of ancient glass objects
Authors: Tang Ziyang , Zhao Jiayi
Published: April 2023

The analysis and identification of the composition of ancient glass objects is a major topic in archaeological research today, and its main task is to restore the true appearance of ancient artifacts as completely as possible by examining various characteristics (surface weathering, color, chemical composition, etc.). The analysis of the indicators before and after weathering at the sampling points is a very important research method that should be continuously improved and rationalized. In this thesis, the characteristics of various types of glass products before and after weathering and the indicators of chemical composition are analyzed qualitatively and quantitatively through various methods (modeling, data analysis, etc.), and the patterns among the indicators of various types of glass are identified, and then the composition of various types of glass before weathering is predicted and the type of glass of unknown glass artifacts is judged. The ideas and research methods embodied therein are of certain significance for the analysis and identification of ancient glass objects in the future.
Nuclear weapon quantity prediction based on the lasso regression model
Authors: He Jinlin , Chen Liyun , Xu Hao , Huang Lihua
Published: April 2023

Once a nuclear weapon explodes, its power will be devastating. In this paper, we analyze the current situation of nuclear weapons in the world, and firstly, we analyze the relationship between the number of nuclear-armed countries and the year using linear regression to find out the prediction model, from which we get that in 2123, the number of nuclear-armed countries in the world will reach 9. Then, this paper analyzes the Pearson correlation between the number of nuclear weapons of each country and the year and uses lasso regression to model the change in the number of nuclear weapons of each country with the year. Special attention is paid to the fact that the number of nuclear weapons in South Africa in the next 100 years is 0, indicating that the number of nuclear-armed countries will be reduced to 9 in 2123, which is consistent with the prediction of the number of nuclear-armed countries through linear regression. In 2123, the total number of nuclear weapons in the world will reach 29,293. To derive a limited total number of nuclear weapons in the world, a nuclear bomb detonation location destructive force model is developed in this paper to derive the maximum destructive range of nuclear bombs. Combined with the current number of nuclear bombs in the world, the calculation results show that the current number of nuclear bombs in the world is not enough to destroy the earth, and the total number of nuclear bombs in the world should be limited to 44,563.
Design and Development of Map Vertical Social Platform Based on LBS
Authors: Mi Le , Chen Yuantian , Li Zongyu , Li Weide , Wu Yuling
Published: April 2023

In recent years, vertical social communication among strangers characterized by anonymization and personalization is becoming a new approach to social communication in  mobile Internet era. This paper developed a map vertical social platform based on LBS technology and Retrofit network framework in an attempt to solve such problems as the slow shift from online to offline social activities and barriers to communication between strangers . The platform implements real-time map display by connecting to the Golden Map SDK, uses C/S three-tier structure as the system architecture, SQL Server database to store and manage data, MVVM as the backend framework, and constructs four modules of map social, social activities and recommendation, group chat and user center based on the social needs of young people, which effectively meets the anonymous social needs of strangers.
Forest management based on the TOPSIS model
Authors: Bai Yunfeng
Published: April 2023

Forest management strategies that include appropriate harvesting are beneficial compared to the carbon sequestration benefits of no deforestation at all. To develop a sound forest management plan and thus a forest decision model, the article built a TOPSIS model to comprehensively evaluate each forest to obtain the evaluation index. Then, the article regressed the evaluation index with the forest area to obtain the regression equation, and then performed the extreme value operation to obtain the best forest area. This area is used as the basis for judging whether the forest is deforested or not. Also, considering the differences in geographic location of different forests, the article conducted a multiple linear regression of deforestation in some countries with respect to forest area, latitude, and longitude to determine the effect of geographic lo-cation on the percentage of deforestation.
Optimization design of heat dissipation scheme for submarine data center based on analytic hierarchy process
Authors: Huang Jiawei , Lan Hang , Kun Xiaolong , Tian Guoxiang
Published: April 2023

Aiming at the problem of heat dissipation optimization design of submarine data center, firstly, the placement mode of server is designed, and on this basis, the heat generation power of server is analyzed by Newton cooling method of convective heat transfer to determine its feasibility. Secondly, based on the relationship between fluid velocity and pressure and the relationship between fluid velocity and heat dissipation through the container surface, the container structure design and its placement direction are clarified. Then, the optimal container shell material is determined by using multi-attribute decision-making model and analytic hierarchy process. Finally, the quadratic composite function of shell cost and seawater depth with respect to shell thickness is constructed to calculate the appropriate seawater depth. According to the research, considering the structure, placement method, heat dissipation effect and seawater temperature of the container, on the basis that a single container shell can be placed with up to 609 servers, Maraging 300 Steel is selected as the most suitable container shell material.
Towards Extreme Weather Detection: Dark Channel Priori Enhanced Detection with New Labelled Data
Authors: Li Yijun
Published: April 2023

With more and more cars entering our lives, the number of car accidents is also increasing. To solve this problem, driverless technology has entered our field of vision. An effective way to realize unmanned driving technology is the application of deep learning. At present, the practice of various large companies in this field is mainly to realize the integrated deep learning of image recognition, judgment, and response on automobiles. The model performance is satisfactory in normal condition. However, if the vehicles encounter some extreme weather, e.g., foggy, it is difficult to ensure the safety of deep learning model due to the insufficient accuracy of image recognition. To solve this severe problem, we advance three strategies. Firstly, considering high-capacity backbone will mitigate this situation, Yolov5 with stronger performance was used as the detector in the experiment. Secondly, image pre-process would be benefit to this foggy situation. Thus, we introduce dark channel priori defogging to our detection framework. Thirdly, since deep learning is data hungry, we labelled image collected in heavy fog weather condition and utilize them to train the network. Abundant experiment demonstrates the effectiveness of the proposed strategies. We gain a precision of 0.89734 after training the model 299 times and the safety can be guaranteed with the high accuracy of image recognition.
Stock Price Prediction using LSTM Model
Authors: Zhang Yifei
Published: April 2023

Stock prices represent the development prospects of a company and play an important role in predicting future economic trends. With the development of deep learning, in this paper, our goal is to predict stock prices through deep learning algorithms. The author uses the Long-Short Term Memory (LSTM) network to make predictions by predicting the real stock prices of Google, Amazon, and Apple, and gives the visualization results of the training and testing stages. The results validate the effectiveness of the LSTM model.
Guangzhou Housing Price Prediction Based On Machine Learning Regression Models
Authors: Huang Ziyan , Li Kexin , Wang Chuming , Wang Jiazhi
Published: April 2023

Nowadays, the fluctuation of housing prices is a key concern of homeowners, the real estate market and the government. The researchers found that it was possible to predict house prices accurately by analyzing relevant attributes and using the most effective models. However, due to the impact of the COVID-19 pandemic, there is still a research gap on which model is more suitable for predicting housing prices after the outbreak of COVID-19. Therefore, this study collected the latest real estate data of Guangzhou in China through the web crawler, trained the random forest regression model with collected data, and obtained a model that could predict the housing price by inputting corresponding attributes. The MSE of the trained regression model is 2802, MAE is 534, and the determination coefficient (R²_score) is 0.89, while the MSE of the trained XGBoost regression model is 3108, MAE is 643, and the determination coefficient (R²_score) is 0.87.The random forest regression model has been shown to be more accurate at predicting Guangzhou house prices after the COVID-19 outbreak. Our paper has great potential in house price prediction under the pandemic situation.
Stock Price Prediction using Deep Recurrent Model
Authors: Zhen Liang
Published: April 2023

In this paper, we aim to predict the stock trend using previous stock data. In specific, we perform LSTM training on the stock data of 2017 and 2018 by using the Sandp500 data as the base. The data includes the stock date, opening price, closing price, the highest price of the day, the lowest price of the day, and volume. Through these data we conducted 100 epoch training. After training, our LSTM can correctly predict the learning curve without any delay influence, with a satisfying performance. And we got the visual graph and chart to prove that the result is effective. The MSE value decreased from the original 3.026 to 0.238. This shows that the error of the result is small and the reliability is high. After LSTM training, it can help stock investment companies and related institutions and individuals to better avoid risks and provide individuals with high-credibility investment advice.
Overview of the application of virtual reality in the field of visual arts and video games
Authors: Mao Ziyi , Wong Chunho , Zhang Yunrui
Published: April 2023

Virtual reality (VR) is an important technology applied in the field of visual arts and game in recent years. VR has revolutionized the field of visual arts and video games with its unique immersion, interactivity, and has significantly improved the user experience for oneself. This paper summarizes the application of VR in visual arts and video games, including VR exhibitions, VR performances, VR tourism, VR games, etc. and compares them with traditional ways. The aspects of immersion and socialization of VR game are analyzed. At the same time, the limitation of VR interactive content and the defects of VR technology are indicated, including the problems of the gameplay's deficiency, VR input and output devices. The future development direction of VR technology is prospected.
Thrust distribution algorithm based on supervision and switching and swarm intelligence
Authors: Yang Yichao
Published: April 2023

The ship power positioning control system is the key to maintain the normal operation of the ship, and it is also the basic premise and foundation for the accurate positioning and stable forward movement of the ship, so many ship management and production enterprises attach great importance to the design and construction of the ship power positioning control system. "Thrust distribution" has always been the key technology for designing and constructing ship power positioning control system. When constructing ship power positioning control system by using thrust distribution technology, it is not only necessary to consider the constraint optimization of thrust limit and thrust rate of change limit of propeller, but also the constraint optimization of azimuth rate of change limit, mechanical wear optimization, restricted area limit optimization, etc. It is also necessary to consider the constraint optimization of azimuth rate of change limit, mechanical wear and tear, restricted area limit, etc. The thrust distribution algorithm based on supervision and switching and group intelligence can comprehensively deal with these constraints, which can improve the functions of the ship power positioning control system and solve the convergence problem in the system operation, and improve the operation efficiency, safety and stability of the ship power positioning control system. In this paper, the author discusses the thrust distribution algorithm based on supervision and switching and group intelligence in depth, combining relevant literature and the actual problem of thrust distribution.
Smartcaptor Intelligent Police System Based on Multi-Technology Integration
Authors: Wang Shenghan
Published: April 2023

With the rapid development of China's national economy, urban and rural transportation activities are increasingly frequent. At the same time, road traffic accidents have become a major problem affecting social development and people's lives. This paper is based on the SmartCaptor intelligent police project system, edge computing, 5G, IoT and artificial intelligence and other technologies for integrated innovation, a good solution to the current road monitoring technology bottleneck, to achieve a device multiple functions, equipment cost is low and other core competitive advantages, SmartCaptor intersection intelligent police have full competitive advantage and market prospects.
Power Diagrams and Rules of Cyclists in Road Cycling
Authors: Zheng Yixin
Published: April 2023

Road cycling time trials have a long history in all sports, and the individual time trial is one of the most important events in road cycling time trials. Due to the long distance, complex sections, and uncertain natural environment of road cycling individual time trials, in addition to the performance of the bicycle itself, the rider’s ability and physical ability, the athlete’s planning of the ride during the distance is also an important factor affecting the performance of this sport. Therefore, it is important to create a model that can facilitate cyclists’ planning decisions for cy- cling. In constructing the initial model, we compared the training and competition data of cyclists with other types of athletes by referring to various literature to ﬁnd commonalities and individ- ualities between road cycling time trials and other sports, thereby reﬁning the data, and ﬁnally determined a power curve model related to power functions using knowledge of ordinary differ- ential equations and ﬁtting.The model can infer the instantaneous power from the rider’s riding time, and when combined with the external force data such as wind and gravity, the rider’s kinetic energy can be derived. The model also incorporates the fact that the total energy of the rider is limited, which guarantees the feasibility and reasonableness of the model
Traffic Control Method Review of Signalized Intersection under Connected Vehicles Environment
Authors: Li Yuqing
Published: April 2023

Traffic is becoming more and more developed today, and at the same time the problem of intersection congestion is becoming more and more serious. As a key traffic scene in urban network, signalized intersection is much more important and complex than other parts. Vehicles in the connected vehicles environment can carry out data interaction with multiple platforms such as background control center, which can effectively solve the problems of traffic congestion at intersections. Therefore, for signalized intersections in the connected vehicles environment, this paper summarizes the research results of its control methods. The paper first introduces the speed guidance method and optimized signal timing method respectively, then discusses the speed and timing collaborative optimization method combining the two above, and finally introduces a new idea of future intersection zoning control. This paper summarizes the update researches and the future research direction of intersection control in the connected vehicles environment.
Potential landslides risk assessment based on remote sensing technique-a cause study from Dorset, southern England, United Kingdom
Authors: Chen Shumeng
Published: April 2023

This paper presents a method of potential landslide risk assessment from the Dorset Southern England, United Kingdom. It concentrated on potential geological hazards and vulnerability to build a quantitative landslide risk framework in Dorset. In this study, the landslides risk assessment is centered on three components: identification of risks, calculation of risks, and evaluation of risks. Therefore, different natural environmental situations were collected using a large set of optical high-resolution satellite images and remote sensing to determine the probability of landslide occurrence and provide the quantitative model by combining the remote sensing technique. The result shows Dorset area risk level is high. The possibility of landslides mainly comes from natural conditions and human actions. The calculation of the possibility of potential landslides is based on the Bayes’ theorem. Moreover, the limitation of the probability potential risk calculation is insensitivity. The challenge is related to the temporal resolution of precipitation information.
Status and Prospects of Applying Machine Learning for Diagnosis and Treatment in African Healthcare Industry
Authors: Wu Fan
Published: April 2023

There is a big difference on healthcare industry between Africa and advanced countries, which represent in lacking medical equipment and backward skills of treatment. The United Nation are thinking about how to eliminate this variance with not only give medical resources but also apply technology to improve the efficiency of using supplies. To train skilled healthcare workers require long-term and expensive investment, but when the pandemic outbreak, there are few talents who can handle complex and extensive work. Therefore, the scientists start to use computer science to replace with manual work, which is more precise and efficient than human beings. Meanwhile, the information technology has developed to the new stage that using big data and advanced algorithms for predicting future potential results which aim to guide better intervention and treatment work. The United States and other advanced countries have the number of effective cases about using these technologies, but the revolution of healthcare is still processing in Africa. The early stage of applying computer technologies in Africa means that there is a big potential market for both scientists and businessmen to explore more solutions for Africa since the adaptive transformation is the key step in the implement.
Non-Invasive Glucose Detection Based on Biosensors
Authors: Qiu Chenshuo
Published: April 2023

Currently, diabetes is one of the most serious and widespread diseases which has a relatively high mortality rate and needs long-lasting therapy to maintain the blood glucose level. In this case, physicians need to regularly detect patients’ blood glucose levels to adjust their treatments and prescribes. The traditional measuring method for monitoring blood glucose is through pricking fingers, which is a kind of invasive method. Though measurement through blood can ensure the precision of the detection, there are still many disadvantages such as increasing the risk of infection that this noninvasive method can bring. Therefore, many scientists tend to put more effort into studying non-invasive biosensors for frequent blood monitoring. To ensure long-lasting measurements of blood glucose, biosensors are required to have high-quality, efficient, and precise. In this case, this passage will discuss different non-invasive biosensors by introducing their mechanisms, comparing the experiment data, and comparing their advantages and disadvantages.
Clinical Applications of PET-MRI Technique in Alzheimer’s Disease
Authors: Chen Lanhui
Published: April 2023

Alzheimer’s disease (AD), a neurodegenerative disease that afflicts many people as the most common form of dementia, still lacks effective symptomatic treatments. PET-MRI hybrid imaging technology combines Positron emission tomography (PET) and Magnetic resonance imaging (MRI), which is believed to be helpful for the early screening, diagnosis, disease course monitoring and treatment evaluation of AD, and has a very promising technical prospect. This review reviews the roles of PET and MRI in the diagnosis and monitoring of AD, respectively, and analyzes their advantages and disadvantages. Later, based on previous studies, this review discusses the effects of the two technologies when they are used together, and compares them with each other and PET-Computed Tomography (CT) hybrid imaging technology respectively, indicating that PET and MRI can complement each other and give full play to their respective advantages. After this, the review also discusses the problems and challenges still faced by this hybrid imaging technology. This paper presents the current research status and future research direction of PET-MRI for AD diagnosis and monitoring, which is of great value to its research and application
Wearable Electronic Devices for Electrocardiograph Measurement
Authors: Li Yishu
Published: April 2023

The early diagnosis of developing cardiac disease requires the steady and ongoing monitoring of electrocardiograph (ECG) signals. Wearable technology will need to advance quickly to support the daily collecting of ECG data for continuous monitoring of ECG signals in daily life. This study evaluates wearable technology's most recent advancements and potential uses for textile electrodes in ECG monitoring. In accordance with the various electrode types, several wearable device applications for monitoring ECG signals will also be shown. Wearable electrodes can be categorized as contact or non-contact electrodes. Contact electrodes can be further subdivided into electrodes with metal integration in the textile, electrodes with carbon coating on the textile, and electrodes that are densely woven from conductive polymers. Textile electrodes with integrated conductive elements, capacitive electrodes, and metal-integrated textile electrodes are the three types of non-contact electrodes. For the daily monitoring and early diagnosis of cardiac disease, these portable wearables are crucial.
Biosensors And Their Applications in The Detection of Cancer Biomarkers
Authors: Guo Xiaoyuan , Pan Hezheng
Published: April 2023

Cancer is a critical disease that seriously affects human health and has a high mortality rate. Therefore, it is very important to effectively improve the survival rate of patients. The low survival rate of cancer is because it can’t be effectively diagnosed in the early stage. When most cancers are in the advanced stage after imaging examination, cancer cells have spread in the body or even metastasized, and the difficulty of treatment will be greatly increased after the metastasis occurs. Therefore, early detection of cancer is one of the key factors to improve the survival rate. However, imaging tests such as computer tomography and nuclear magnetic resonance imagining cannot accurately detect small lesions in the early stage of cancer, which also leads to low detection accuracy. In recent years, the interest in the development of biosensors has become more and more intense. Biosensors have shown excellent detection performance and real-time detection capability. Besides, biosensors can also detect biomarkers with extremely low content in detection samples, which is helpful for early cancer diagnosis. In addition, biosensors have also shown the potential to simultaneously detect multiple biomarkers.
Biosensors And Intelligent Algorithms for Heart Failure Monitoring
Authors: Wu Zhaoqian
Published: April 2023

Heart failure is one of the most common causes of mortality and the final stage of cardiovascular disease. The prognosis of individuals with chronic heart failure has improved to some extent which is thanks to our increased understanding of heart failure. Both invasive and non-invasive biosensors have advanced significantly during the previous ten years. It has been demonstrated that biosensors can identify heart failure early and lower the need for hospitalization. In the past, biosensors mainly detected the general condition of patients' vital signs, but now they have been developed into invasive biosensors for monitoring pressure changes such as a pulmonary artery pressure, right ventricle pressure, left atrium pressure and so on. It allows clinicians to observe the function of the heart more intuitively. Non-invasive biosensors can monitor electrocardiograms, heart sounds, pleural effusion and so on, and evaluate the risk of recurrent heart failure by observing the risk factors of heart failure deterioration. Although this kind of sensor cannot cause harm to patients, often not as accurate and timely as invasive sensors. There are intelligent algorithms based on biosensors, which belongs to machine learning, which can greatly improve the specificity of patient diagnosis. These biosensors and intelligent algorithms can further improve the survival rate of patients.
Wearable Electronics for Surface and Needle Electromyography Measurements
Authors: Tang Guojun
Published: April 2023

Because the electromyography (EMG) signal can reflect the potential of muscle contraction controlled by neural activities, it has aroused great interest from researchers. As a result, a number of studies have been conducted around EMG. EMG-based wearable electronics are used not only in the diagnosis of neurogenic or myogenic diseases but also in sports science, rehabilitation, augmented reality, and virtual reality. This article briefly introduces the development history and background of EMG technology, then focuses on the classification of EMG and its technical mechanisms and reviews representative EMG-based wearable electronics. Finally, the challenges and development trends of EMG-based wearable electronics are also discussed. Developing devices with high specificity, adaptability, and robustness remains challenging. It has become a trend to optimize EMG signals' classification, characterization and noise cancellation algorithms for future study by combining multiple technical means. Because of the various applications of wearable electronic devices based on EMG measurements, it will have promising prospects in many fields.
Establishment Of Performance Evaluation System for Public Hospitals - Based on Balanced Scorecard
Authors: Wang Shikun , De Leon Josefine M.
Published: April 2023

The four dimensions of the Balanced Scorecard – financial perspective, customer perspective, internal processes, and learning and growth can help hospitals establish performance evaluation system from an integrated perspective. This can play a significant role in improving the service quality for public hospitals. In this paper, a public hospital in Hebei province is used as an example to establish its performance evaluation system in order to provide a reference for the deepening of its performance management.
Rabies: The Scientific Basis and Its Public Threat
Authors: Gu Yuchen
Published: April 2023

Every year, more than 55,000 people die from rabies around the world. Most human rabies deaths happen in Africa and Asia, where rabies remains a neglected disease. As soon as symptoms appear, human rabies is usually fatal due to acute, progressive encephalomyelitis. Although humans take precautions against rabies, sporadic outbreaks still occur in wild populations, indicating that factors that govern virus transmission and spread remain unclear. A great deal is unknown about the evolution of rabies viruses and other lyssaviruses. Because lyssaviruses are highly neurotropic, they infect the nervous system by breaking through the skin barrier. The transmission of rabies is largely dependent on domestic dogs. In addition to being part of the daily lives, domestic dogs are also part of our surroundings, which makes them more likely to contract zoonotic diseases. To eliminate rabies from domestic dog populations, which are the most dangerous vectors for humans, a sustained international commitment is important. Preventing clinical disease and death in domesticated and wild animals can be accomplished by vaccination and avoiding behaviors that may trigger exposure. Vaccines for wildlife and monoclonal antibodies are also being investigated as ongoing treatments.
Scarlet Fever: An Exploration Based on Characteristics, History and The Intervention
Authors: Hu Alice
Published: April 2023

Scarlet Fever, a fever that has strong infectious ability, has caused many outbreaks in decades, grabbing people’s attention and awareness in the past ten years. A high density of the population is disturbed by this disease until today’s world. Outbreaks and cases mainly present in cohorts under 13, increasing the burden of infectious diseases on children and adolescents. Potential outbreak places for scarlet fever are intensive working or living places such as school, hospital or neighborhood. Historically, a high proportion of scarlet fever outbreaks take place in school. Understanding the epidemic history of scarlet fever still has important reference value and enlightenment significance for preventing and controlling modern scarlet fever outbreak. This article is aimed to spread awareness and educate the public about scarlet fever based on existing research and publication of the characteristics of scarlet fever, diagnosis, treatment, statistics of past outbreaks and existing interventions to let the public have an objective view of the disease.
Flexible Temperature Sensors and Their Applications
Authors: Yang Yuanqing
Published: April 2023

The most interesting part of the sensor is the flexible sensitive part and irregular curved surface, which is different from the conventional surface structure and provides positive inspiration for many medical devices. These necessary conditions have become welcome items for medical care. Body temperature detection is an indispensable element of flexible temperature sensor, which is a symbol of identity. I think that with its growing popularity, we should better understand its performance and use. The degree of temperature response and the sensitivity of temperature to external stimuli will affect the use of the sensor. In my opinion, its appearance must be able to better help mankind. The following text will explain the current development status of flexible temperature sensors one by one.
The Investigation of LPA Binding Sites on LPA 1 And LPA 4
Authors: Zhang Huyang , Hou Wenjuan
Published: April 2023

Lysophosphatidic acid (LPA) is a class of biologically active lipid molecules with important biological functions. LPA can induce various cellular responses through six LPA receptors (LPA1-6) on cell membranes to achieve its biological functions. This study utilized computer simulation tools such as AutoDock Vina and RosettaFold to investigate the binding sites of LPA1 and LPA4 to LPA molecules. Based on these results, this study could provide new insights for the subsequent development of extracellular antagonists and agonists, and facilitate drug formation for the treatment of cancer invasion.
Application of Polymeric Micelles for Cancer Treatment: A Review
Authors: Guo Kunhao
Published: April 2023

Polymeric micelles have been considered a promising development in chemotherapies to treat cancer diseases in recent decades. Bearing a structure of hydrophilic outer shell and hydrophobic core, these micelles possess many advantages like their nano-size structure, self-assembly synthesis, physical and chemical stability, biocompatibility, prolonged blood circulation time, and high drug loading and release capacity. The increased availability of building block copolymers that produce polymeric micelles also enables researchers to create the ideal drug delivery system. The formation of these polymeric micelles depends on various non-covalent interactions, the used concentration and temperature, block lengths, and methods of preparation. Among these polymeric micelles, stimuli-sensitive micelles have been developed and begun to attract more attention in recent years for their high on-site specificity and enhanced drug release efficacy. To accommodate the complex microenvironment in tumors, such as the internal changes in pH, reductive responses, and enzyme activities, or the external factors like visible lights, UV irradiations, and temperature, the stimuli-sensitive micelles exhibit strong stability, high drug loading, efficient drug delivery, specific site release, and mild side effects in recent studies. This research also discusses dual or multi-stimuli-sensitive polymeric micelles that are under high research nowadays, dictating a more novel and efficient way of cancer treatments and clinical practices.