bluuebunny/crossref_metadata_2025 huggingface dataset:
Innovation Scheme Design of Personal Income Tax Collection and Administration Based on Blockchain Technology
Authors: Wang Jiaqi
Published: April 2023

This paper sorts out the application status and technical characteristics of blockchain, and aiming at the problems of long and complicated tax payment process, lack of sufficient verification mechanism and serious loss of personal income tax in China's personal income tax collection and management, puts forward the idea of personal income tax collection and management combined with blockchain technology. Then, this paper designs a personal income tax collection and administration scheme based on alliance chain and intelligent contract to assist the tax authorities to conduct efficient, safe and automated tax collection.
Optimization of Consumer Satisfaction Towards Tourism Attractions through Text Mining
Authors: Wen Xin , Li Yijie
Published: April 2023

With the ascension of tourism e-commerce, a growing number of consumers are placing greater emphasis on consumer satisfaction and posting their travel experiences on tourism e-commerce platform. Processing the online information generated by consumers through text mining has also become a key technology applied in E-commerce. In order to identify the factors that impact consumer satisfaction and find the method to optimize consumer satisfaction, this study collected data from Ctrip.com and applied topic modeling and regressions to online reviews of tourism attractions. The results show that: (1) consumers with higher involvement in tourism websites are more likely to have lower satisfaction with tourism attractions. (2) online reviews that focus more on Price, Entrance and tickets tend to have lower satisfaction, while online reviews that contain more about Scenery, History and culture, Entertainment and Service are more likely to be higher on consumer satisfaction. These findings show that text mining can be instrumental for E-commerce to optimize management strategies.
Basic Pricing Models and Some New Relevant Derivatives
Authors: Guo Jiayi
Published: April 2023

Assets pricing model theories have developed for long period from CAPM to five factor model. Since Sharp proposed CAPM, some scholars performed empirical tests for it. There were many anomalies that CAPM could not explain. So many scholars challenged the application of CAPM and they tried to modified it from many perspectives. Then the researches of asset pricing model focused on multiple factors ranging from some conventional field, to unconventional factors including factors related to human, like humans behaviors, to describe the return of assets in the market.
Is ESG a Novel Pricing Risk Factor for the Chinese Stock Markets during COVID-19?
Authors: Zhou Weitao
Published: April 2023

This paper examines the potential of ESG as a novel risk factor, explaining different industry portfolio returns from 2018 to 2021 (including two years of the unique COVID-19 window). The ESG factor(SMU) is designed as the spread between the top 30% high-ESG(Sustainable) group and the bottom 30% low-ESG(Unsustainable) group. Based on empirical evidence from the Chinese stock markets, this paper finds: 1) The ESG factor significantly explains industry returns along with Fama-French three factors; 2) Sustainable portfolios consistently outperform unsustainable groups, particularly during the pandemic period; 3) Modified models with ESG factors slightly outperform the classic FF-3 model according to the GRS F-test; and 4) Industry portfolio returns during COVID-19 are surprisingly higher than in normal times, most likely due to the central bank and governments Quantitative Easing(QE) policies.
Should we focus more on the offline retail when constructing financial portfolios?
Authors: Cai Haoyu , Liu Anqi
Published: April 2023

Modern portfolio theory has been researched and applied widely. This paper shows an application of the modern portfolio theory to choose optimal weights for a composite stock s portfolio. It could help optimize investors portfolio by increasing returns and decreasing volatility. Considering returns and volatility at the same time, Sharpe ration is a good indicator. To research portfolio optimization, this article uses Monte Carlo methods to acquire the weights of securities in portfolio that has the highest Sharpe ratio. Current studies about portfolio theory do not take safe securities into consideration. Therefore, this paper first concludes risk-free asset with other risky assets in portfolio. The portfolio in this study includes five stocks (Walmart, Amazon, Dexcom, Warner Bros., T. Rowe) in different sectors and risk-free asset (one-year U.S. Treasury Securities). The result shows that the weight of offline retail increases as the proportion of risk-free asset rises. This has implication that risk-averse investor might prefer offline retail stocks compared with other stocks in portfolio.
Research on Compensation Incentive Mechanism of State-Owned Enterprises - A Case Study of Chinese Enterprises
Authors: Lyu Kejia
Published: April 2023

The sudden change in the global economic situation has brought about changes in internal and external market conditions. In this context, China's state-owned enterprises continue to use the traditional salary management model in the salary system, which has many shortcomings in the degree of market openness, distribution mechanism and supervision, which is not conducive to our economic development. It is very important to establish and improve the salary incentive mechanism of state-owned enterprises. A scientific and perfect incentive mechanism can effectively stimulate the enthusiasm and creativity of employees and play a vital role in the healthy and sustainable development of public enterprises. However, with the progress and development of the times, the traditional wage incentive mechanism has exposed some problems that cannot fully function. To this end, this paper analyzes the problems in the current salary management model of state-owned enterprises and finds that performance-based salary incentives actually reflect the wealth created by employees for their work. The consistency of goals among employees, managers and shareholders. Finally, from the existing problems, measures are proposed to improve the current wage management model of SOEs in order to enhance their economic development.
Research on Embedded Technology Import and the Growth of TFP in China's Manufacturing Industry Based on the Panel Data from 1992 to 2020
Authors: Lu Yunsheng , Sheng Hao
Published: April 2023

In the past few decades, the import of embodied technologies, mainly the import of capital goods and intermediate goods, has met the needs of industrial structure upgrading and export expansion. This paper uses the DEA-Malmquist method to measure the total factor productivity and its decomposition value of 26 manufacturing industries in China from 1992 to 2020, and uses a fixed effect model to empirically analyze the impact of embedded technology imports on China's manufacturing total factor productivity. The results show that the import of embedded technology has a positive effect on the total factor productivity of the manufacturing industry and technological advancement, while the impact on technical efficiency is not significant. After classifying the manufacturing industry according to the technical level, it is found that the import of embedded technology significantly improves the total factor productivity of low-tech and medium-tech manufacturing, while the impact on resource-based manufactured goods and high-tech manufactured goods is not significant. Finally, this paper gives policy recommendations based on the empirical results.
Research on the impact of corporate social responsibility information disclosure and corporate innovation in China
Authors: Yang Yuchao
Published: April 2023

China started to implement a new system in 2008, asking fractional companies to make public their corporate social responsibility information disclosure. The financial and corporate governance data of Chinese A-share listed businesses from 2007 to 2016 was gathered in order to determine any potential relationships between the mandated corporate social responsibility disclosure system and company patents. According to the two opposite hypotheses of the information hypothesis and reputation hypothesis, the results show that the number of patents of companies surveyed has increased significantly after the implement of the policy of mandatory CSR disclosure. Additionally, after companys patents are separated into invention type patents and utility models, industrial design (non-invention type) patents, invention type patents significantly increase in comparison. This means that the information hypothesis has been supported more. CSR disclosure can effectively alleviate the information asymmetry existed in the internal of the enterprise, increase shareholders confidence, and reduce the problems of corporate financial restrictions. Several robustness tests have proved that the model and conclusions are both steady. This may provide a reference for the government to improve the mandatory disclosure policy further and help improve the capital market development in China.
An Evaluation of the Dividend Discount Model and its Extensions
Authors: Ma Liya , Xie Zhuoling , Zhang Hongyu
Published: April 2023

The valuation of the stock is one of the most fundamental financial concepts, whereas the Dividend Discount Model is the basis of the stock valuation. The model state that the value of the stock is the sum of the present value of the infinite future dividend. It is, however, impossible for Humans to forecast future dividend accurately. Therefore, the assumption of the future dividend and the extension of the dividend discount model are required. In this paper, the assumption, advantages, and limitations of the general Dividend discount model and its extension, including the Fix dividend discount model, Gordon growth model, Two-stage model, Three-phase model, H-model, Geometric and additive model, and the modified Geometric and additive model, are introduced in this paper, which can be used as a reference for the investors for them to make their financial decision or for the scholars for their researches.
The Analysis of Asset-Backed Security Backed by Online Consumer Loan
Authors: Jia Ziyi , Chen Yuwei , Lang Jianing , Li Peidong
Published: April 2023

The "pause button" on Ant Group's dual listing in September 2020 attracted great attention from the fintech companies regarding their use of asset-backed securities (ABS) to lend huge amounts of money to consumers. Chinese regulators responded to this financial practice and introduced a series of regulations to minimize the potential risks of these lending activities and the adverse impacts on consumers. In this paper, the author explains how fintech companies use ABS to conduct their loaning activities, analyzes the risks presented in the industry, and introduces the corresponding policies and regulations.
Why Do So Many People Value the Stock Market
Authors: Li Jiaao
Published: April 2023

In 2020, the impact of the COVID-19 pandemic plunged the world into its worst economic crisis since 2008, and international trade was frustrated by the double whammy of escalating protectionism and the pandemic in recent years. Affected by the epidemic in 2020, many Chinese companies cannot sustain themselves, and the remaining enterprises are only barely maintaining the status quo and waiting for the epidemic to pass. During this period, the overall trend of the stock market fell sharply due to the epidemic, but due to the government's policies, it was still pulled up.
An Analysis of the Involution of Finance College Students
Authors: Xia Yaoyang
Published: April 2023

More and more finance undergraduates cannot find a job, and even some graduate students are facing difficulties in finding a job. Involution which is used to describe any walk of life or everyone who tries desperately to improve himself or herself to increase his or her advantage over others. The industry of finance has a very low threshold for domestic universities, and every university and even the junior college has finance as a major. Therefore, the threshold of financial learning is very low, but the threshold of financial industry is very high, which requires people's professional ability, communication ability and emotional intelligence. As a result, many undergraduates do not meet the requirements of various financial jobs, which leads to the phenomenon of unemployment after graduation. This paper finds out that because of the low threshold of finance and people's limited understanding of finance, they do not know whether they are suitable for this major, so they can make their resume look gorgeous through various ways in the later stage.
Identifying Financial Report Fraud of U.S. Listed Chinese Companies
Authors: Yang Yujing , Wang Xiaoting , Ruan Jiani , Huang Lingfei , Gao Shang
Published: April 2023

A key feature of publicly listed companies all over the world is that the people who own the company, its investors, do not typically participate in the day-to-day management of the company. This separation of ownership and control can become a problem when investors and management have different objectives. Disclosure is a primary means through which investors can understand what managers are doing and ensure that managers serve the objectives of the companys owners. However, since management is responsible for preparing the companys financial statements, they could misreport the numbers to mislead investors. Previous research showed managers had discretion in manipulating the numbers in the financial report. In this paper, we collected samples of Chinese companies listed in the United States, such as Luckin Coffee, and assessed whether there were any signs that might help investors identify fraud earlier than they were discovered, and what mechanisms prevented managers from doing so.
A Study on the Economic Drivers of the Data Element
Authors: Chen Luyu
Published: April 2023

As the development of information technology has entered a new stage, data has become a novel factor of production in the digital economy. With its unique and fundamental economic characteristics, data participate in the production process and brings an innovative driving force to the economy. Thus, how data factors act on production and contribute to economic growth need further study. This article analyses the economic characteristics unique to the data element from the perspective of its causes. In the following parts, we propose three ways in which the data element can be combined with traditional factors of production to drive productive development: value multiplication, input substitution, and resource optimization. Furthermore, the article extends the Cobb Douglas function to investigate the possible paths of the data element economic growth model, and initially constructs a production function model including the data factor to deepen the understanding of the function of the data factor.
The Portfolio Analysis in Hong Kong Stocks
Authors: Li Sijia , Peng Tai , Si Mingzhe
Published: April 2023

Maximizing returns is always peoples investment goal. Stocks have some hedging capabilities, and their prices also fluctuate widely, making them popular in-vestments for investors. As a result, Stock prices have fluctuated wildly, leading to uncertain investments and uncertain returns. To compute and analyze the maximum returns of stocks in Hong Kong stocks, this paper takes The Hang Seng index, an important indicator of Hong Kong stock market prices as the scene. We calculate the variance of these stocks using the Fama experiment. And We examined the normal distribution and i.i.d. of the data. To test whether the hypothesis of independence and the same distribution in the data is reasonable, and then con-duct an ACF test on the five selected stocks to observe their time-series stability. Then, this paper uses Markowitz's effective frontier decision-making process to simulate stock trading and use the Sharp ratio risk analysis to select mid-risk and high-yield portfolios. The results show that: The weight of the five stocks shows an approximate trend with their average return rate. The larger the average value is, the larger the investment proportion will be. stock investment with low-risk accounts for a relatively high proportion, while stock investment with high-risk accounts for a relatively small proportion. Among the selected several representative stocks, Techtronic Industries and Long for Group have more investment value, while the investment value of bank stocks is on the low side.
The Digital Inclusive Finance and Investment Efficiency of Enterprises: Evidence from Perspective of Financialization
Authors: Feng Zixuan
Published: April 2023

Digital inclusive finance, a byproduct of traditional banking and digital technology, has a substantial effect on the financial standing of businesses. Using information from Chinese A-share listed firms between 2011 and 2018, this paper empirically investigates the connection between the emergence of digital financial inclusion and investment efficiency and financialization of real enterprises, as well as their underlying mechanisms. The results show that digital financial inclusion rises a suppressive effect on the investment efficiency of enterprises. Further, this effect is influenced by other control factors. The mechanism test shows that digital financial inclusion enhances the process of financialization of corporations. Findings of this paper help clarify the mechanism of the role of digital inclusive finance. Based on the empirical findings, this paper recommends controlling the unrestricted promotion of digital inclusive finance but encouraging balanced expand.
Portfolio Optimization for Industries in Chinas A-shares Market
Authors: Liu Dong
Published: April 2023

Portfolio optimization has always been a hot topic in financial research. Rational investors seek to balance risk and return in asset allocation. This article conducts a portfolio analysis of the military, liquor, new energy vehicles, medical service, and real estate industries in Chinese market. We select a representative asset from each industry and construct a large number of portfolios using the mean-variance model. Among the efficient frontier, we mainly focus on two portfolios. One is the minimum variance portfolio, and the other is the tangency portfolio. Finally, we compare these two portfolios to the SCI 300 Index. The results show that the real estate industry has the largest proportion in the minimum variance portfolio and the military industry contributes most to the maximum Sharpe portfolio. These two portfolios perform better than the SCI 300 Index.
How does Financial Informatization Influence the Financial Industry?
Authors: Zhao Wenbo
Published: April 2023

In this modern world, talented people create thousands of new technologies like John von Neumann who invented computers and Martin Lawrence Cooper invented phones, all of these E-Techs are recording every information from a person, an organization, or a nation and transmitting the information to the public website. Newspapers, TV shows, and websites always show people information from everywhere in totally different fields, nations are using those technologies to gather information from every corner of the world to have a Big Data Analysis. But, how do those investors or businessmen make a big profit from information? In this essay, I will use qualitative research like a questionnaire to show the influence of financial informatization on the financial industry. The based result was financial informatization is pushing financial industry creation and development and improving the core competitiveness. In conclusion, financial informatization is showing a positive influence on the financial industry.
Food supply chain risk of community group buying in the post-epidemic era
Authors: Liu Yujing
Published: April 2023

Due to the outbreak of COVID-19 at the beginning of 2020, community group buying is booming again, but at the same time, it will bring new risks. Combining with the characteristics of food quality and community group purchase management, from food procurement, supply, distribution, sales link of food supply chain risk is analyzed, by using analytic hierarchy process (AHP) and fuzzy comprehensive evaluation method in the food supply chain risk factors, the result shows that in the community group to the importance of the food supply chain risk for commodity procurement risk > External environmental risk > Logistics distribution risk > Information Technology Risk >Mission risk, By analyzing these five risks, preventive measures are provided for food supply chain risk management in community group buying.
An error based adaptive learning rate stochastic gradient descent algorithm in convolutional neural network
Authors: Li Qianyi
Published: April 2023

If the learning rate of convolutional neural network (CNN) is set improperly, the efficiency and accuracy of the algorithm will be greatly affected. To solve this problem, a learning rate adaptive algorithm is proposed to improve the traditional SGD: based on parameter prediction, the historical training error is used to update the learning rate. Under the condition of given initial learning rate, experiments on classical data sets prove the effectiveness of the above algorithms, and the adaptive learning rate stochastic gradient descent algorithm can keep the convergence of the network. Training accuracy is relatively stable; Shorter training time; And improve the learning accuracy.
A combined analysis system for network products based on aspect extraction and sentiment classification
Authors: Song Shangzheng
Published: April 2023

With the continuous development of online shopping, more and more online shopping review data has been accumulated. These reviews contain consumers' attitudes and opinions on the products, which are of great value for mining. This research introduces a set of methods to mine review information by using aspect extraction and sentiment analysis. By analyzing the aspects involved in the reviews and the sentiment polarity of the reviewers, the potential opinions on the products can be summarized and presented to the merchants so as to understand consumers' preferences and make reasonable improvements to the products. This research combines and adopts several techniques, such as aspect extraction, paragraph vector and sentiment classification, to build a complete process which can handle review text and get the results of review aspects and sentiment polarity. By taking an Amazon review dataset as an example and applying this process, the relevant aspects and sentiment polarities contained in the reviews are obtained, which reveals that the idea of this research is feasible.
Ground Based-cloud Classification Based on Comparing Different Classification Models
Authors: Zhang Tao , Ding Yantian , Gong Wangjiang , Hou Zeyu
Published: April 2023

Clouds are one of the most common things in our daily life, and different types of clouds will foreshadow different weather conditions. Therefore, accurately identifying and classifying them are important for human forecasting the local weather. However, artificially classifying clouds could possibly cause a minor error. With the helping of machine learning classification model could avoid this situation as much as possible. In this study, our goal is to get sufficiently high accuracy of based-cloud classification. We used LBP as a preprocessing approach, and used KSVM, MLP, Custom Vision, and Resnet to compare each result. The dataset contains around 15 thousand cloud images in 5 types in the same format and pixels. With the implementation of four classification models, experiments showed that ResNet34 came out a great result with a test accuracy 94%. Therefore, this study demonstrates ResNet34 is a good image classification model in based-cloud classification field.
A novel information extraction model integrating multi-granularity global information for medical dialogue
Authors: Song Kehang
Published: April 2023

Electronic medical records (EMRs) are one of the ways to help doctors effectively manage and analyze patient medical records. These EMRs can not only help doctors save a lot of time in analyzing medical records, but also reduce the hospital's demand for doctors and reduce the hospital's expenditure cost. Therefore, we propose a novel information extraction model integrating multi-granularity global information to efficiently extract information about a patient's physical condition in a doctor-patient dialogue. Experimental results show that our model achieves better results compared to the baseline model, indicating the effectiveness of the model.
Exploring The Use of Convolutional Neural Networks in UAV Based Rescue Missions
Authors: Shen Xuande Andrew
Published: April 2023

Multi-rotor based flight platforms, especially quadcopters and unmanned aerial vehicles (UAVs), and their embedded avionics have become emerging technologies in rescue operations. Due to the simplicity of mass production, as well as air superiority, rapid deployment and vertical take-off and landing (VTOL) capabilities, autonomous driving will be the next step in rescue operations. This project aims to explore the application of UAV combined with deep learning algorithm in drowning scenario. With the help of Betaflight, create an autonomous flight program that implements specific drowning rescue functions. Deep learning algorithms are critical to developing neural recognition networks for drowning individuals, with pre-programmed flight parameters eliminating the need for human interaction, human error to be precise. The core goal of the project is to improve the success rate of lifesaving solutions through the availability of this technology, a longer operating range than lifeguards, and shorter response times.
A Comparison on Machine Learning Classifiers related to Traffic Sign Recognition
Authors: Zhang Jiajin
Published: April 2023

With the rapid development of machine learning and the automotive industry, the industry of autonomous driving continues to grow. At the same time, governments have new regulations on autonomous driving, which tells us that reliable systems have become more and more critical while developing autonomous driving. In this paper, I use three different classifiers, which are Logistic Regression (LR), Random Forest (RF), and neural network (Multilayer Perceptron), to do the traffic sign recognition tasks and set the best parameters for every classifier. I train three classifiers with the best parameters and estimate using cross-value methods. Finally, I compared the performance, which indicates Random Forest Classifier has the best result among the three classifiers.
PakParse: Machine Translation from Text to Pakistan Sign Language for Effective Communication with Deaf People
Authors: Mahmood Rana Arsal , Ahmad Haseeb , Ann Qurat-ul , Ashraf Muhammad Usman
Published: April 2023

The People around the world use different languages to communicate with each other. But there are many individuals who cant listen or speak. These people use gesture-based language for their communication which is called Sign Language. There is no universal Sign Language in world so it changes region wise. As Sign language cant be written and sign video approach is also expensive (in terms of create, store and manage), thats why sign animation through 3D avatar is best option. Recently Pakistan got its own Sign Language called Pakistan Sign Language (PSL). As a noteworthy population of deaf people live in country, there is no machine translator for PSL which can facilitate deaf in their communication and education. This work proposed a machine translator for Pakistan Sign Language called PakParse, which takes text (English & Urdu) as input, and animate corresponding signs by 3D avatar.
ResNet50 Based Classification on Mnist and Cifar10
Authors: Chen Boshan
Published: April 2023

Convolutional neural network (CNN) is gradually trending in the past few years due to its learning capacity and great generalization power. CNNs use a different version of regularization, which makes it on lower extreme. In this task, we studied the performance of Residual neural networks (ResNet50) on Mnist and Cifar10 datasets. We built the model mainly based on ResNet50 with cross-entropy loss. Then we trained Mnist and Cifar10 datasets on it separately and evaluated its prediction accuracy. The prediction accuracy of this model on the test set of Mnist and Cifar10 is 35.87% and 95.35% respectively.
The Open Secrets of the Model or Marginalized Minority: Political Campaign Participation of Asian Americans in the 21st Century
Authors: Li Maxwell
Published: April 2023

With Asian American population on the rise, Asian Americans have more power than ever in political elections. While qualitative methods have been used to measure this uptrend in Asian American political participation, a thorough and cohesive quantitative study on the topic has yet to be done. Therefore, we utilize machine learning and dictionary-based matching to identify the most accurate numbers for Asian American political participation, categorized by political affiliations, geography, gender, etc. We find that Asian American political participation tends to the Democratic party, is predominantly male, and is proportional to the population size of the individuals respective state.
Memory Implementation on Navigation Systems
Authors: Yao Qingyuan
Published: April 2023

Nowadays, cases in which people get lost under the guidance of navigation systems still occur. In order to render the situation, the essay seek for ways to improve the navigation system in ways other than enhancing navigational message expression. This paper mainly discusses the feasibility of memory implementation on navigation systems. By memorizing past records and past mistakes, the navigation system will be able to provide a revised route for drivers individually, reducing their possibility of making mistakes, and further increasing their system using experience. Meanwhile, with the support of big data, the navigation system could provide better routes for every user, using their own memories. The main method is to mark every hotspot, that is, a spot where drivers are likely to make mistakes themselves, and provide them with alternative routes that cover as small number of hotspots as possible.
Survey on Click-Through Rate Prediction Based on Deep Learning
Authors: Liu Yafei
Published: April 2023

With regards to computer science, deep learning forms an essential research area. Recently, deep learning has made achievements on image processing, language understanding, data analysis, speech recognition, online advertising and so on. At the same time, display advertising has also become the most popular means of publicity with the rapid development in terms of the Internet, as well as the rapid expansion of the market of online advertising. Accurate advertising recommendation is the guarantee of Internet platform profits. The premise of accurate recommendation is accurate advertising click through rate prediction. Since 2015, the deep learning success has made the estimation of CTR results more accurate. Many CTR models have been used widely on a large amount of online platforms. This paper reviews several deep learning-based click-through rate prediction models for online advertising recently; classifies these prediction algorithms in the aspect of basic structure, complexity and main functions; and analyses the differences, advantages and the application. Finally, the survey is summarized and the future prospects of this field are envisaged.
Automation Techniques for Smart and Sustainable Agriculture and its Challenges
Authors: Misra Tripti , Anwarul Shahina , Srivastava Divya , Cheng Xiaochun
Published: April 2023

In the contemporary scenario, the world is primarily focused on trends and technology that leads to intelligent and accurate results in every field. Automation of everything has come up as a necessary demand due to this reason. Things are automated wherever possible. Agriculture is also one such field where automation has acquired much popularity. With the advent of the Fourth Industrial Revolution, integration of various tools and technologies like IoT, Deep Learning, cloud, etc., has led to the development of several automated agriculture systems, generally termed as "Smart and Sustainable Agriculture". Motivated by this fact, a comparative study of state-of-the-art approaches for Smart and Sustainable Agriculture systems using automated devices is presented in this paper. To build the basics, the paper discusses the Smart and Sustainable agriculture systems techniques for the automation of the agriculture systems. The next section presents the relative performance of different approaches. At last, the upcoming challenges and future work directions in this field are discussed next.
Review on 3D printers
Authors: Kolivand Hoshang , Bailey Luke , Asadianfam Shiva , Rehman Amjad
Published: April 2023

In this paper of the report, it is all the different research in the that has been done to under-stand more about the subject of 3D printers and the health sector. In this paper all the differ-ent research that was done was information that is very closely related to subjects previously stated, although these papers are very professional and informative the focus of this part of the paper is to better show all the different gaps in the information and what it could be miss-ing that could possibly be showed in this paper that they have missed out on.
O uso de sequência didática na formação inicial do professor de Geografia frente à educação inclusiva
Authors: Fonseca Ricardo Lopes
Published: April 2023

Muitos obstáculos têm-se mostrado presentes na construção do ideal de inclusão de alunos com Necessidades Educacionais Especiais (NEE), notadamente no ensino de Geografia. Essa situação tem provocado muitos debates, envolvendo, não apenas as instituições escolares, mas também muitos setores da própria sociedade. Diante das dificuldades apresentadas, esse estudo foi desenvolvido visando a uma reflexão intermitente acerca do processo de inclusão de alunos com NEE no ensino de Geografia, objetivando, especialmente, definir a importância da Sequência Didática como sendo um mecanismo de avaliação preliminar na preparação inicial do professor de Geografia especialmente direcionada à Educação Inclusiva. Tendo como referência as informações adquiridas com a análise dos resultados alcançados, possibilitou-se observar que com a adoção das práticas realizadas em grupo, com a participação efetiva do professor no processo de mediação pedagógica durante as fases de construção dos instrumentos de apreciação, destacou-se a preparação na formação inicial do professor de Geografia prioritariamente dirigida à Educação Inclusiva.
Qualidade físico-química e microbiológica de leite cru re-frigerado na Região Sudoeste da Bahia
Authors: Carvalho Alves Camila , Cruz da Silva Carolline , Amaral Figueiredo Lopes Rhaissa , Steffens Ana Paula , Do Val de Assis Fábia Giovana , Lopes Leal Patrícia
Published: April 2023

O objetivo deste trabalho foi avaliar a qualidade de amostras de leite cru refrigerado provenientes de 18 fazendas situadas na região do município de Vitoria da Conquista, Sudoeste da Bahia, Brasil. Avaliações quanto à contagem padrão em placas de bactérias mesófilas, bactérias psicotrópicas seguiram metodologia convencional proposta pela Instrução Normativa nº 62/2003 do MAPA. Os parâmetros físico-químicos (acidez titulável em graus Dornic, estabilidade ao álcool alizarol, índice crioscopico) foram avaliados segundo metodologia convencional recomendada pelo Instituto Adolfo Lutz. As análises de gordura, proteína, extrato seco desengordurado (ESD), densidade a 15 °C, foram realizadas utilizando um analisador de leite ultrassônico. Além das características físico-químicas e microbiológicas avaliadas, foi verificada a presença de resíduos dos antibióticos utilizando kits de detecção de penicilina G, tetraciclina, clortetraciclina e oxitetraciclina. Os resultados apontaram presença de mesofilos em valores acima do estabelecido (3,0 x 105 UFC/mL) em 50% das amostras de leite cru refrigerado e, aproximadamente, 11% das amostras foram positivas para presença de resíduo de antibiótico. Para os parâmetros acidez, crioscopia, extrato seco desengordurado, estabilidade ao álcool alizarol, foram detectadas irregularidades em pelo menos 11,11% das amostras de leite cru refrigerado. Os resultados indicaram a necessidade de tomada de medidas preventivas, como, por exemplo, a instrução e qualificação de profissionais que lidam diretamente com o gado leiteiro para maiores garantias da qualidade do leite cru refrigerado.
Влияние ганглиозидсодержащего препарата на развитие окислительногостресса в головном и спинном мозге крыс при экспериментальном аутоиммунном энцефаломиелите
Authors: Казарян Г. С. , Зангинян А. В. , Овсепян Л. М.
Published: April 2023

Բազմակի սկլերոզը միելինային հիվանդությունների ամբողջ խմբում ամենատարածվածն է: Սովորաբար այն սկսվում է երիտասարդ տարիքից և գրեթե անխուսափելիորեն հանգեցնում է հաշմանդամության։ Մարդու բազմակի սկլերոզի մոդել է առնետների փորձարարական աուտոիմուն էնցեֆալոմիելիտը: Վերջին տարիներին առկա են բազմաթիվ տվյալներ, որոնք ցույց են տալիս օքսիդատիվ սթրեսի զգալի պաթոգենետիկ դերը իմունային բորբոքման հետևանքով առաջացած միելինային բջիջների վնասման մեջ: Դրա հիման վրա առանձնահատուկ նշանակություն ունի դեղամիջոցների օգտագործումը, որոնք նվազեցնում են օքսիդատիվ սթրեսի զարգացումը։ Աշխատանքի նպատակն է ուսումնասիրել գանգլիոզիդ պարունակող պրեպարատի ազդեցությունը լիպիդների ազատռադիկալային օքսիդացման, ուղեղի և ողնուղեղի սպիտակուցների օքսիդատիվ ձևափոխման զարգացման վրա մոդելավորված առնետների մոտ: Որպես թերապևտիկ միջոց՝ մենք օգտագործել ենք քրոնասիալ դեղամիջոցը, որի կառուցվածքը ներառում է մոնո-դի-տրի-սիալգանգլիոզիդներ: Ստացված տվյալները բացահայտում են հետազոտվող քրոնասիալ դեղամիջոցի հակաօքսիդիչ և նյարդապաշտպանիչ ազդեցությունն աուտոիմուն էնցեֆալոմիելիտ ունեցող կենդանիների վրա:
The most common disease of the entire group of myelin diseases is multiple sclerosis. Usually the disease begins at a young age and almost inevitably leads to disability. Experimental autoimmune encephalomyelitis in rats is an experimental model of human multiple sclerosis. In recent years, more and more data have appeared
indicating a significant pathogenetic role of oxidative stress in damage to myelin cells caused by immune inflammation. Based on this, the use of drugs that reduce the development of oxidative stress is of particular importance. The aim of the work was to study the effect of ganglioside-containing drugs on the development of free radical lipid oxidation, protein oxidative modification in the brain and spinal cord in rats with experimentally induced allergic encephalitis. As a therapeutic agent, we used the drug Сronassial, the structure of which includes monodi- tri-sialgangliosides.The data obtained indicate the neuroprotective and antioxidative effect of Cronassial when administered to animals with autoimmune encephalitis.
Оценка внедрения программ профилактики и инфекционного контроля в стационарах Армении в 2020 году
Authors: Палозян Г. О.
Published: April 2023

Աշխատանքում ներկայացված են հանրապետության տարբեր մակարդակների բժշկական օգնություն տրամադրող հիվանդանոցներում միջազգային IPCAF գործիքով իրականացված վարակի կանխարգելման և հսկողության (ՎԿՀ) ծրագրերի ներդրման գնահատման արդյունքները։ ՀՀ բոլոր հիվանդանոցների համար հաշվարկված ՎԿՀ ծրագրերի միջին գնահատականը 2020 թվականին բնութագրվել է որպես «միջին»։ Բացահայտվել են ՎԿՀ այն հիմնական բաղադրիչները, որոնց ուղղությամբ անհրաժեշտ է աշխատանքներ իրականացնել՝ առկա իրավիճակը բարելավելու համար։
The results of the evaluation of Infection prevention and control (IPC) programs in Armenian hospitals of different levels with the international IPCAF tool are presented. The average total rate of IPC programs calculated for the whole country in 2020 was estimated as "medium". IPC core components in risk were identified. It is necessary to organize and carry out the measures to improve the current situation.
Լեղային բարդությունների առաջացման պատճառները և բուժումը լյարդի մասնահատումների դեպքում
Authors: Բարսեղյան Հ. Ա. , Ոսկանյան Ա. Ա․ , Կուրղինյան Ռ․ Մ․ , Գալումյան Ա․ Ս․ , Հարությունյան Հ․ Վ․ , Պետրոսյան Դ․ Ի․
Published: April 2023

Проведено ретроспективное изучение результатов лечения 185 больных, перенесших резекцию печени. Билиарное осложнение развилось в 24,8% случаев, но они не повлияли на показатель летальности. Нами исследованы 24 пред- и интраоперационных фактора, зарегистрированы факторы риска возникновения желчеистечения: внепеченочное обнажение, перевязка и пересечение долевого желчного протока при правосторонней гемигепатэктомии. Консервативное лечение и малоинвазивные методы (чрескожное дренирование) эффективны при устранении билиарных осложнений, их эффективность составляет 93,5%. Повторная операция требуется в редких случаях.
A retrospective study of the results of treatment of 185 patients who underwent liver resection was carried out. Biliary complications developed in 24,8% of cases, but they did not affect the mortality rate. 24 pre- and intraoperative factors were studied, risk factors for bile leakage were recorded: extra hepatic exposure, ligation and intersection of the lobar bile duct during right-sided hemihepatectomy. Conservative treatment and minimally invasive methods (percutaneous drainage) are effective in eliminating biliary complications, their effectiveness is 93,5%. Reoperation is required in rare cases.
Էնդոսկոպիկ տրանսնազալ վիրաբուժությունը ուղեղ-ողնուղեղային հեղուկի արտահոսքով ուղեկցվող ախտաբանական վիճակների դեպքում
Authors: Կոշտոյան Ա. Ս. , Մովսիսյան Լ. Ս. , Պետրոսյան Լ. Ա. , Ղուկասյան Յ. Օ. , Զարգարյան Հ. Ա. , Մկրտչյան Ա. Հ. , Նահապետյան Ն. Ռ.
Published: April 2023

Истечение цереброспинальной жидкости (ликворея), вызванное дефектом дна передней черепой ямки, считается актуальной проблемой в оториноларингологии и нейрохирургии. Ликворея обусловлена аномальным соотношением между полостью носа, пазух и субарахноидальным пространством. В данной работе описаны клинические проявления, диагностика, доступы и результаты оперативного лечения двух случаев – спонтанной и индуцированной опухолью ликвореи.
Cerebrospinal fluid (CSF) leakage due to anterior skull base defect is considered a topical issue in otorhinolaryngology and neurosurgery. An abnormal relation between the nasal cavity, the sinuses and the subarachnoid space causes CSF leakage. The clinical manifestations, diagnosis, surgical approaches and results of treatments of two cases, spontaneous and tumor-induced CSF leakage, have been described in this work.
Спорные вопросы в онкогинекологии
Authors: Джилавян Г. А. , Джилавян Ар. Г.
Published: April 2023

Բուժումը ծրագրելիս կլինիցիստը բախվում է մի շարք վիճահարույց խնդիրների՝ առանց գինեկոլոգիական պաթոլոգիաներից որևէ մեկի բացառության: Հետազոտության մեջ ներառվել են արգանդի վզիկի, ձվարանների և արգանդի մարմնի մորֆոլոգիապես ապացուցված քաղցկեղով 894 հիվանդների տվյալները, ովքեր բուժվել են Ուռուցքաբանության ազգային կենտրոնում։ Մշակվել են ուղիներ՝ ուռուցքային հիվանդների մոտ փուլերի միգրացիան կանխելու համար: Ցույց է տրվել ձվարանների քաղցկեղի նեոադյուվանտ քիմիաթերապիայի և ախտորոշիչ լապարոսկոպիայի անհրաժեշտությունը: Քննարկվել են արգանդի վզիկի քաղցկեղի քիմիաթերապիայի հարցերը։
When planning treatment, the clinician faces a number of controversial issues for any of the gynecological pathologies without exception. The study included data on 894 patients with morphologically proven cancer of the cervix, ovaries and cancer of the body of the uterus, who were treated at the National Center of Oncology. Measures have been developed to prevent the migration of stages in oncogynecological patients. The need for neoadjuvant chemotherapy and diagnostic laparoscopy in ovarian cancer is shown. Issues of chemotherapy in cervical cancer were discussed.
Türkiye’de Kadın Kooperatifleri: Mevcut Durum Analizi, Kadın Güçlenmesi ve İstihdam Yaratma Potansiyeli
Authors: ŞAHANKAYA ADAR Aslı , DEDEOĞLU Saniye , KURTULUŞ Güneş
Published: April 2023

Türkiye hala toplumsal cinsiyet normlarının çok güçlü olduğu ve kadınların ekonomik yönden birçok dezavantajı yaşadıkları bir ülkedir. Bunun en bariz gözlemlenebildiği alan ise, işgücü piyasasıdır. Türkiye’de kadınların işgücü piyasasına katılımları ve istihdam oranları OECD ve AB ülkeleriyle karşılaştırıldığında oldukça düşüktür. Son dönemde kadın ekonomik ve sosyal hayata katılımlarının artırılması amacıyla alternatif bir güçlenme aracı ve istihdam modeli olarak kadın kooperatifleri öne çıkmaktadır. Nitekim kadın kooperatiflerinin yaygınlaşması amacıyla kamu kurumları, yerel yönetimler, uluslararası kuruluşlar ve STK’lar kadın kooperatiflerini maddi olarak ve kooperatiflerin kuruluş ve işletilmesiyle ilgili eğitimler aracılığıyla teknik açıdan desteklemektedirler. Ancak desteklerle sayıları gün geçtikçe artan kadın kooperatiflerinin mevcut durumunu ortaya koyan çalışmaların sınırlı olmasının yanında aktif kadın kooperatifleri ve bunların ortakları sayıları ile faaliyet alanları gibi bilgilere ulaşmak da oldukça güçtür. Bu alandaki bilgi eksikliği kadın kooperatiflerinin hem nicelik hem de nitelik açısından değerlendirilmesini zorlaştırmakta, kuruluş hedefleri ile faaliyetleri arasındaki ilişkinin analiz edilmesini engellemektedir. Bu çalışmada Türkiye’de kadın kooperatiflerinin mevcut durumu, kadın kooperatiflerinin istatistiki bölge sınıflandırmalarına göre düzey 2’de yer alan 26 bölgedeki dağılımları ve üretim ile hizmet sınıflandırmaları da dikkate alınacak şekilde incelenmiştir. Bunu yaparken Ticaret Bakanlığı’nın resmî sitesindeki verilerden, üst birliklerden elde edilen verilerden ve çalışma süresinde doğrudan iletişime geçilerek ulaşılan kadın kooperatiflerinin verilerinden yararlanılmıştır. Bu çalışma son yıllarda kadın kooperatif sayılarındaki hızlı artışa rağmen, kadın kooperatiflerinin kadın istihdamını arttırmada ve kadın güçlenmesini desteklemekte epey zayıf etkiler yarattığını göstermektedir. Fakat yine de uzun vadede kadın kooperatiflerinin toplumsal yaşamda ve çalışma yaşamında toplumsal cinsiyet eşitsizliklerinin ortadan kaldırılmasında veya azaltılmasında önemli bir güçlenme aracı olduğu söylenebilir.
Türkiye’de Yoksullukla Mücadelede Sosyal Yardım Kurumlarının Etkinliği
Authors: DAL Rabia , TEMİZ Nurcan
Published: April 2023

Yoksulluk, dünya ülkelerini olumsuz olarak etkileyen ve etki alanının genişlemesi nedeniyle mücadele edilmesi gereken büyük bir sorundur. Yoksulluk sorununa müdahalede bulunulmaz ise kronik bir hal alıp toplumun büyük bir çoğunluğu üzerinde etkisini hissettirecektir. Yoksulluk sorunu ile mücadele şekilleri zamanla değişiklik göstermiş olsa da amaç hiç değişmemiştir. Günümüzde yoksullukla mücadelede etkin rol üstlenen devlet aktörleri bulunmaktadır. Bu çalışmada bu aktörler içerisinden sosyal yardım kurumlarına ve bu kurumların yapmış olduğu sosyal yardımlara değinilmiştir. Sosyal yardım harcamalarının yoksulluk oranı üzerindeki etkisini ölçebilmek amacıyla zaman serisi analizi yapılmıştır. Bu analizlerde Gauss 21 ve Eviews 12 paket programları kullanılmıştır. Çalışmada uygulanan zaman serisi analizi ile yoksulluk oranı ve sosyal yardım harcaması, sosyal yardımdan yararlanan hane sayısı, sosyal yardım harcamasının milli gelir içerisindeki payı arasında uzun dönemli tek yönlü bir nedensellik ilişkisi olduğu ortaya konmuştur