bluuebunny/crossref_metadata_2025 huggingface dataset:
Trends in the development of agricultural enterprises in Ukraine as precondition for the formation of differentiated measures of agricultural policy
Authors: Voskobiinyk Solomiia
Published: March 2021

The purpose of the article – is to determine of tends of agricultural enterprises development in Ukraine based on their seg-mentation on typical for the aims of the research groups and the establishment of the author’s assessment toolkit as one of the preconditions for the formation of differentiated measures of agricultural policy. Research methods. The dialectical method of cognition and systemic method of research of tendencies of agricultural enter-prises development as prerequisites for more substantiated formation of differentiated measures of agricultural policy are the theoretical basis of the article. The results of the research are obtained based on using such main methods as generalization and compare. Three the most significant groups of agricultural enterprises and component of the tools research have been determined based on generalization method. Using the comparison method, the analysis of the performance indicators of the subjects of these groups was carried out. Research results. Trends in the development of agricultural enterprises in Ukraine are considered, three characteristic groups of enterprises are distinguished: farms, conditionally medium agricultural enterprises, with a land use area of 10,000 hectares and large agricultural enterprises with a land use area of more than 10,000 hectares. Scientific novelty. The authors toolkit of research has been formed. It includes the next indicators: number enterprises in groups, the size of agricultural area, the number of employees in plant production and animal husbandry, land supply per employee, average monthly salary, gross output, income (revenue), income per 100 hectares of agricultural land and per employee, level of profitability in plant production and animal husbandry. Practical significance. The results of the article can be used for the elaboration of the differentiated measures of agricultural policy. Tabl.: 4. Refs.: 17.
Prospects for the use of electricity saving systems by rural households and agricultural business
Authors: Zhemoida Oleksandr , Skrypnyk Andrii , Namiasenko Yurii
Published: March 2021

The purpose of the article is to analysis of the effectiveness of existing methods of electricity storage to improve the welfare of rural households and the efficiency of agribusiness. Research methods. As a methodic of research the reduced cost of stored electricity (LCOS) was used based on the discount cost of purchasing and storing a unit of electricity throughout the life of the equipment. Research results. The main factor determining the efficiency of storage systems was the number of recharges, which together with the current night tariff allows to bring the cost of stored energy closer to the daily grid cost. Scientific novelty. To minimize the economic, informational and moral risks from the instability of the electricity supply, it is proposed to use power storage system.. Practical significance. Installation of own capacities of renewable energy in addition to energy saving systems will significantly increase the efficiency and standard of living of the rural population. Tabl.: 3. Figs.: 5. Refs.: 26.
Digitalization and digital platform in the economic development of the agricultural sector
Authors: Vodianka Liubov , Yurii Tetiana
Published: March 2021

The purpose of the article is to reveal the modern significance of digitalization and digital platforms for the economic development of the subjects of the agricultural sector of the economy. Research methods. The following methods were used in the research process, in particular: abstract-logical method (when studying the theoretical foundations of digitalization of the economy), monographic (to clarify the essence of the relevant categories), comparative analysis (when studying the level of digitalization of agricultural holdings «Dream» and «Svarog West Group») economic-statistical (in identifying trends and patterns of development of the state economy), illustrative (for a visual representation of the digital platform of agriculture), as well as methods of systematic approach, grouping and generalization, other methods in the field of economic research. Research results. The need to use a digital platform, especially for small and medium-sized agricultural enterprises, has been identified. In particular, this system will allow: public authorities (to make a plan of visits and yields; to report on the allocation of subsidies, as well as their use; to conduct a financial audit for each enterprise; to assess the competitive advantages of each enterprise; enterprises (to analyze data from weather stations; to study information on the condition of soils; choose crops for sowing; assess the risks of crop loss; obtain data on climatic risks). Scientific novelty. Theoretical provisions on the impact of digitalization of the economy on agricultural production and the need for digitalization of production and economic processes have been further developed. Practical significance. As a result of the implementation of the proposed digital platform in agriculture, the following benefits will be obtained: increased crop yields; the field planning system will improve; reduce production costs based on efficient use of resources and science-based approaches Figs.: 1. Refs.: 17.
Organizational and institutional support for sustainable development of entrepreneurship in agriculture
Authors: Ivanchenko Vitalii
Published: March 2021

The purpose of the article is to reveal the main theoretical and methodological aspects of organizational and institutional support for sustainable development of entrepreneurship in agriculture. Research methods. During the research, dialectical methods of scientific knowledge of the process of sustainable development of entrepreneurship in agriculture were used, primarily analysis and synthesis as well as induction and deduction to characterize the organizational and institutional parts of the provision. Research results. It has been established that the system of organizational and institutional support for sustainable development of entrepreneurship in agriculture combines various interdisciplinary aspects of the economic, social and environmental components for organizing activities in the sustainable development system and forming the rules and systems by which these components function. The institutional component of ensuring the activities of the enterprise makes it possible to combine various organizational processes and form various directions in production to ensure the implementation of the goals of the social, environmental or economic components of sustainable development of entrepreneurship in agriculture. Scientific novelty. The main points of organizational and institutional support for sustainable development of entrepreneurship in agriculture are described and the main components of this process are revealed. Practical significance. The main features of organizational and institutional support of sustainable development should be used as a basis for further research into the nature of institutions and the process of organizing production for the system of sustainable development of entrepreneurship. Tabl.: 1. Figs.: 2. Refs.: 12.
Fever and breast cancer: A critical review of the literature and possible underlying mechanisms
Authors: Mehran Shiva , Taravati Afshin , Baljani Esfandiar , Rasmi Yousef , Gholinejad Zafar
Published: March 2021

Fever is a common feature in various pathological conditions that manifests a series of molecular events in the internal milieu. Much less attention has been paid to the clinical importance and the management of fever in breast cancer patients. However, several studies have reported an association between postoperative fever and poor treatment outcomes in breast cancer patients. The fever is a side effect of chemotherapy and a manifestation of cancer recurrence. The postmenopausal breast cancer patients experience another body temperature disturbance that is known as a hot flashes. Here, we reviewed the literature regarding postoperative fever and the possible underlying molecular and cellular mechanisms. Then the efficacy of non-steroidal anti-inflammatory drugs was discussed as a therapeutic option to control postoperative fever. Finally, we reviewed the chemotherapy-induced neutropenic fever and cancer vaccination-induced fever.
Upgrade rates and outcomes of screen-detected atypical intraductal epithelial proliferation (AIDEP) diagnosed on core needle biopsy
Authors: Dunne Emma C. , Quinn Edel M. , Stokes Maurice , Barry John M. , Kell Malcolm , Flanagan Fidelma , Kennedy Margaret M. , Walsh Siun M.
Published: March 2021

INTRODUCTION: Atypical intraductal epithelial proliferation (AIDEP) is a breast lesion categorised as “indeterminate” if identified on core needle biopsy (CNB). The rate at which these lesions are upgraded following diagnostic excision varies in the literature. Women diagnosed with AIDEP are thought to be at increased risk of breast cancer. Our aim was to identify the rate of upgrade to invasive or in situ carcinoma in a group of patients diagnosed with AIDEP on screening mammography and to quantify their risk of subsequent breast cancer. METHODS: We conducted a retrospective review of a prospectively maintained database containing all patients diagnosed with AIDEP on CNB between 2005 and 2012 in an Irish breast screening centre. Basic demographic data was collected along with details of the original CNB result, rate of upgrade to carcinoma and details of any subsequent cancer diagnoses. RESULTS: In total 113 patients were diagnosed with AIDEP on CNB during the study period. The upgrade rate on diagnostic excision was 28.3% (n = 32). 6.2% (n = 7) were upgraded to invasive cancer and 22.1% (n = 25) to DCIS. 81 patients were not upgraded on diagnostic excision and were offered 5 years of annual mammographic surveillance. 9.88% (8/81) of these patients went on to receive a subsequent diagnosis of malignancy. The mean time to diagnosis of these subsequent cancers was 65.41 months (range 20.18–145.21). CONCLUSION: Our data showing an upgrade rate of 28% to carcinoma reflects recently published data and we believe it supports the continued practice of excising AIDEP to exclude co-existing carcinoma.
UNGA as the Anchor: Global Environmental Conferencing
Authors: Matz-Lück Nele , Christiansen Liv
Published: March 2021

The global environmental conferences convened by the United Nations General Assembly (UNGA) during the last fifty years have contributed to the development of international environmental law and institution-building. Yet, given the deteriorating state of the global environment they are but one element of international environmental governance. While they were important to bring environmental issues to the attention of states, the time for agenda-setting seems over. Rather the international community must move on to the implementation of existing binding and non-binding rules and principles. While the UNGA continues to play an important role in the context of sustainable development and the Agenda 2030 process and is, indeed a stable platform for international cooperation on environmental issues, it seems that the time for comprehensive global environmental conferences may have come to an end, unless more innovative mechanisms for the implementation of international environmental law and policy are brought forward.
Peristaltic flow of Herschel Bulkley nanofluid through a non-Darcy porous medium with heat transfer under slip condition
Authors: El-dabe Nabil T. , Abou-zeid Mohamed Y. , Mohamed Mona A. , Maged Mohamed
Published: March 2021

In this work, we focused on the peristaltic unsteady flow of non-Newtonian nanofluid with heat transfer through a non-uniform vertical duct. The flow obeys Herschel Bulkley model through a non-Darcy porous medium under the effects of mixed convection and thermal diffusion. Moreover, the effects of thermal radiation, heat generation, Ohmic dissipation, chemical reaction and uniform external magnetic field are investigated. The derived equations that describe the velocity, temperature and nanoparticles concentration are simplified under the assumptions of long wave length and low Reynolds number. These equations have been solved by using a numerical technique with the help of shooting method. The obtained solutions are functions of the physical parameters entering the problem. The effects of these parameters and the obtained solutions are explained and discussed through a set of graphs. It is found that the increment in Prandtl number or Thermophoresis parameter reduces the spread of the nanoparticles (concentration increased) within the fluid along with the thermal diffusivity through the fluid layers. Also the non-Darcy effect supports the inertial forces, and in order to maintain Reynolds number, the viscous forces are motivated and the axial velocity is damped. Moreover, for the validation of the current methodology, this model is reduced to power law model (no yield stress) and compared with the work of Eldabe et al. [ 16 ].
A fuzzy-based approach for resource management in SDN-VANETs: Effect of trustworthiness on assessment of available edge computing resources
Authors: Qafzezi Ermioni , Bylykbashi Kevin , Ampririt Phudit , Ikeda Makoto , Matsuo Keita , Barolli Leonard
Published: March 2021

Vehicular Ad hoc Networks (VANETs) aim to improve the efficiency and safety of transportation systems by enabling communication between vehicles and roadside units, without relying on a central infrastructure. However, since there is a tremendous amount of data and significant number of resources to be dealt with, data and resource management become their major issues. Cloud, Fog and Edge computing, together with Software Defined Networking (SDN) are anticipated to provide flexibility, scalability and intelligence in VANETs while leveraging distributed processing environment. In this paper, we consider this architecture and implement and compare two Fuzzy-based Systems for Assessment of Neighboring Vehicles Processing Capability (FS-ANVPC1 and FS-ANVPC2) to determine the processing capability of neighboring vehicles in Software Defined Vehicular Ad hoc Networks (SDN-VANETs). The computational, networking and storage resources of vehicles comprise the Edge Computing resources in a layered Cloud-Fog-Edge architecture. A vehicle which needs additional resources to complete certain tasks and process various data can use the resources of the neighboring vehicles if the requirements to realize such operations are fulfilled. The proposed systems are used to assess the processing capability of each neighboring vehicle and based on the final value, it can be determined whether the edge layer can be used by the vehicles in need. FS-ANVPC1 takes into consideration the available resources of the neighboring vehicles and the predicted contact duration between them and the present vehicle, while FS-ANVPC2 includes in addition the vehicles trustworthiness value. Our systems take also into account the neighboring vehicles’ willingness to share their resources and determine the processing capability for each neighbor. We evaluate the proposed systems by computer simulations. The evaluation results show that FS-ANVPC1 decides that helpful neighboring vehicles are the ones that are predicted to be within the vehicle communication range for a while and have medium/large amount of available resources. FS-ANVPC2 considers the same neighboring vehicles as helpful neighbors only if they have at least a moderate trustworthiness value ( VT = 0.5). When VT is higher, FS-ANVPC2 takes into consideration also neighbors with less available resources.
A fuel sales forecast method based on variational Bayesian structural time series
Authors: Lian Huiqiang , Liu Bing , Li Pengyuan
Published: March 2021

Fuel prices, which are of broad concern to the general public, are always seen as a challenging research topic. This paper proposes a variational Bayesian structural time-series model (STM) to effectively process complex fuel sales data online and provide real-time forecasting of fuel sales. While a traditional STM normally uses a probability model and the Markov chain Monte Carlo (MCMC) method to process change points, using the MCMC method to train the online model can be difficult given a relatively heavy computing load and time consumption. We thus consider the variational Bayesian STM, which uses variational Bayesian inference to make a reliable judgment of the trend change points without relying on artificial prior information, for our prediction method. With the inferences being driven by the data, our model passes the quantitative uncertainties to the forecast stage of the time series, which improves the robustness and reliability of the model. After conducting several experiments by using a self-collected dataset, we show that compared with a traditional STM, the proposed model has significantly shorter computing times for approximate forecast precision. Moreover, our model improves the forecast efficiency for fuel sales and the synergy of the distributed forecast platform based on an architecture of network.
Renewable energy power system transient stability analysis and assessment
Authors: Cui Chongyu , Li Zhaoxia , Zang Kun , Quan Xuezheng
Published: March 2021

In this paper, in-depth analysis, and evaluation of the transient stability of a renewable energy power system are carried out, and a transient stability evaluation method based on stacked autoencoders is proposed. The method breaks through the traditional two-stage evaluation mode. The method proposes a deep network model with a multi-branch structure for different physical natures of different measured data. With the help of different sparse denoising coding networks (branches), features are extracted from each measurement separately and fused on top of the model to finally complete the transient stability assessment. The simulation results show that the method can effectively handle the simultaneous input of multiple measurements, and has the advantages of high accuracy and robustness in noisy environments. To effectively determine the model hyperparameters, the orthogonal test is used for model selection, which can significantly reduce the hyperparameter seeking space and save computational resources. The simulation results show that the method can effectively use multiple measurements to improve the accuracy of wind power prediction. Also, the input variable selection index based on mutual information can provide a good guide for further improvement of model performance.
Prediction model of network security situation based on genetic algorithm and support vector machine
Authors: Xing Jingyu , Zhang Zheng
Published: March 2021

In order to predict the development trend of network security situation more accurately, this paper proposes an improved vector machine model by simulated annealing optimization to improve network security situation prediction. In the process of prediction, the sample data of phase space reconstruction network security status is first formed to form training sample set, and then the simulated annealing method is improved. The correlation vector machine is the optimization of correlation vector machine with simulated degradation algorithm embedded in the calculation process of objective function. The network security situation prediction model is obtained through super parameters to improve the learning ability and prediction accuracy. The simulation results show that this method has higher prediction accuracy better than the correlation vector machine model optimized by Elman and simulated annealing. This method can describe the change of network security well.
Task schedule algorithm based on double-objective particle swarm optimization under cloud computing
Authors: Guang Hui Wei
Published: March 2021

In cloud computing environment, how to reasonably carry out the resource scheduling and reduce the task execution time and task execution energy consumption has become a hot issue in the researches. In this paper, the task processing time and energy consumption were used as the optimization objectives, and a Double-Objective Particle Swarm Optimization (DOPSO) was used to perform the optimal scheduling of task completion time and energy consumption. Finally, the results obtained in DOPSO were simulated in CloudSim, and results showed that compared with existing scheduling algorithms, the proposed algorithm (DOPSO) had obvious advantages in the integrated scheduling performance.
Fuzzy target detection algorithm based on improved SSD and transfer learning
Authors: Wang Peng , Wu Jiao , Li Xiaoyan , Cai Mengyao , Qiao Mengyu , Fu Huitong
Published: March 2021

Fuzzy target detection as an important task to reflect the detection ability of underwater robot, the artificial target recognition based on the image taken by underwater robot has been widely concerned. However, there is no open standard fuzzy underwater image data set, and in the harsh deep-water fuzzy environment, it is difficult to collect large-scale marked underwater fuzzy optical images. At the same time, it is also hoped that the detection model has the ability to learn quickly from small samples in the case of as few samples as possible. Therefore, combining depth learning and transfer learning, a new method based on improved SSD and transfer learning is proposed. Firstly, we design a more accurate SSD network (underwater SSD) which is suitable for fuzzy underwater target detection. The features extracted from the detection network are highly representative. Secondly, we use the Transfer learning method to train the underwater SSD network, which can only use the tags in the air to identify fuzzy underwater objects, and have strong robustness in both the air and fuzzy underwater imaging modes. Finally, soft NMS is used to detect the target. The experimental results of the simulation data show that the algorithm not only overcomes the difficulties of the known data set of underwater target, but also effectively improves the accuracy of underwater target detection compared with the traditional deep learning method, reaching 82.31%, showing better detection performance.
Research and implementation of e-commerce intelligent recommendation system based on fuzzy clustering algorithm
Authors: Hu Jinjuan , Xie Chao
Published: March 2021

After entering the 21st century, the electronic commerce system has affected all aspects of our lives. Whether we read news on our mobile phones or computers or purchase items on our online websites, it greatly facilitates our lives. With the rapid development of short videos, many people like to watch small videos that interest them. The rapid development of e-commerce has facilitated our lives, so that we no longer have to go to many shopping malls to buy our favorite items, and we also no need to change TV stations one by one after watching a program to find our favorite programs. However, due to the rapid development of electronic commerce, there has been a lot of information overload. When users browse the website, items they are not interested in will appear, and even information about online fraud appears. How to filter this information and how to intelligently recommend to users more favorite items is the main research direction of this article. The research of this article is mainly divided into four parts. The first part analyzes the current situation of intelligent recommendation technology research and puts forward the idea of this article. The second part introduces the commonly used collaborative filtering algorithm and the principle and process of the fuzzy clustering algorithm used in this experiment, analyzes the shortcomings of the traditional collaborative filtering algorithm and illustrates the adaptability of the fuzzy clustering algorithm in practical applications. The third part introduces an intelligent recommendation system based on fuzzy clustering, which comprehensively analyzes the characteristics of users and products, makes full use of users’ evaluation information of products, and realizes intelligent recommendations based on content and collaborative filtering. At the end of the article, the comparative analysis experiment with the intelligent recommendation system of collaborative recommendation algorithm further proves the superiority of the intelligent recommendation system of electronic commerce based on fuzzy clustering algorithm in this paper and improves the accuracy of intelligent recommendation.
Fuzzy control based on genetic algorithm in intelligent psychology teaching system
Authors: Pang Xiaojia , Ning Yuwen
Published: March 2021

The advancement of science has made computer technology and the education industry more and more closely related, and the development of intelligent teaching systems has also opened a new path for classroom teaching. This paper studies the application of fuzzy control based on genetic algorithms in the intelligent psychology teaching system. Facing the complicated variables in the teaching process, the improved genetic algorithm can better realize dynamic teaching decisions through fuzzy control. This article aims to improve the quality of psychology classroom teaching, and develops an intelligent psychology teaching system based on the fuzzy control theory of genetic algorithm. Combined with the current development of fuzzy control theory, the problems existing in the intelligent teaching system are studied and analyzed, and they have been optimized and improved. This paper proposes a control algorithm based on a teaching management system. The algorithm can implement fuzzy control on student models, knowledge organization structure, intelligent test papers and teaching decision-making. While restoring the real teaching process, it can better realize teaching students in accordance with their aptitude and improve teaching. The intelligence of the system. According to the system test data, the proportions of the difficulty of the system’s automatic test paper are 30.1%, 51.6%, 18.3%, which are in line with the designer’s set expectation of 3 : 5:2, which shows the improved genetic algorithm. It can realize the intelligent volume group function very well.
Tracking algorithm of video echo signal based on big data processing
Authors: Chang Ying , Zhu Qinghua
Published: March 2021

With the rapid development of many storage devices and other science and technology, continuous discussion on the role of video target tracking technology in the practical application of photoelectric weapons, guidance systems and security tracking systems has become the current research direction of computer vision and artificial intelligence. The purpose of this study is to explore the differences and characteristics of different algorithms, and provide theoretical and methodological support for the realization of video echo signal tracking in complex environment. For echo signal tracking algorithm only uses a single feature to track, it is particularly easy to cause tracking failure. Therefore, this study uses a method of multi feature fusion to establish the observation model. From the four aspects of gray, color, shape and texture, these four visual characteristics are very representative. In order to study the tracking accuracy, stability and real-time performance of the algorithm, pedestrian, vehicle and face are used as tracking targets to verify the tracking performance of the algorithm in different environments. Using the technical analysis of big data to find the target data file can improve the search speed of the target data and the operation speed of the tracking algorithm. The experimental results show that, in terms of accuracy, the simplest gray feature is only 0.42, and CN feature is improved by about 14% compared with the gray feature. It takes less time to find the target data file by index file method than by traversing the file name method.
Pose recognition in sports scenes based on deep learning skeleton sequence model
Authors: Li-quan Chen , You Li , Shen Fengjun , Shan Zhaoqimeng , Chen Jiaxuan
Published: March 2021

Human skeleton extraction is a basic problem in the field of computer vision. With the rapid progress of science and technology, it has become a hot issue in the field of target detection such as pedestrian recognition, behavior monitoring, and pedestrian gesture recognition. In recent years, due to the development of deep neural networks, modeling of human joints in acquired images has made progress in skeleton extraction. However, most models have low modeling accuracy, poor real-time performance, and poor model availability. problem. Aiming at the above-mentioned human target detection problem, this paper uses the deep learning skeleton sequence model gesture recognition method in sports scenes to study, aiming to provide a gesture recognition method with strong noise resistance, good real-time performance and accurate model. This article uses motion video frame images to train the VGG16 network. Using the network to extract skeleton information can strengthen the posture feature expression, and use HOG for feature extraction, and use the Adam algorithm to optimize the network to extract more posture features, thereby improving the posture of the network Recognition accuracy. Then adjust the hyperparameters and network structure of the basic network according to the training results, and obtain the key poses in the sports scene through the final classifier.
Remanufacturing system reliability analysis based on the uncertainty of part quality
Authors: Huang Jui-Chan , Shu Ming-Hung , Hsu Bi-Min , Hu Chien-Ming , Kao Meng-Chun , Selim Mahmoud M.
Published: March 2021

The remanufacturing industry is one of the important means to achieve sustainable development and resource recycling. It is of great significance to study the remanufacturing production system. This paper mainly studies the reliability of remanufacturing production system based on the uncertainty of part quality. In order to rationally arrange workshop production, minimize the maximum completion time and the cost of electricity in the production process, this study established a mixed integer linear programming model for the remanufacturing of flexible workshop based on batch processing of partial stations. In order to solve this mathematical model, the traditional genetic on the basis of the algorithm, the crossover and mutation operators of the genetic algorithm conforming to the model are designed, and finally combined with actual examples, compared with traditional batch scheduling to verify the effectiveness of the system. This research takes the remanufacturing of the Steyr engine crankshaft as the research object. Based on the uncertainty of crankshaft wear, the uncertainty of the crankshaft remanufacturing process is investigated and discussed. From the three dimensions of environment, economy and technology, from the remanufacturing process. The evaluation was carried out at the level of the process chain and the modeling process and method were verified, and the sustainability value of the worn crankshaft remanufacturing process was obtained. The remanufacturing production system experiment can show that the average sustainability values of the three batches of used crankshafts are SR1 = 0.9082, SR2 = 0.8669, SR3 = 0.7803. The system reliability analysis can provide a theoretical basis for the reliability of enterprise remanufacturing systems, and has important application and research value.
A combined model based on feature selection and support vector machine for PM2.5 prediction
Authors: Lai Xiaocong , Li Hua , Pan Ying
Published: March 2021

With the increasing attention to the environment and air quality, PM2.5 has been paid more and more attention. It is expected to excavate useful information in meteorological data to predict air pollution, however, the air quality is greatly affected by meteorological factors, and how to establish an effective air quality prediction model has always been a problem that people urgently need to solve. This paper proposed a combined model based on feature selection and Support Vector Machine (SVM) for PM2.5 prediction. Firstly, aiming at the influence of meteorological factors on PM2.5, a feature selection method based on linear causality is proposed to find out the causality between features and select the features with strong causality, so as to remove the redundant features in air pollution data and reduce the workload of data analysis. Then, a method based on SVM is proposed to analyze and solve the nonlinear problems in the data, for reducing the prediction error, a method of particle swarm optimization is also used to optimize SVM parameters. Finally, the above methods are combined into a prediction model, which is suitable for the current air pollution control. 12 representative data sets on the UCI (University of California, Irvine) website are used to verify the combined model, and the experimental results show that the model is feasible and effective.
COVID-19 and Parkinson’s Disease: What Do We Know So Far?
Authors: Artusi Carlo Alberto , Romagnolo Alberto , Ledda Claudia , Zibetti Maurizio , Rizzone Mario Giorgio , Montanaro Elisa , Bozzali Marco , Lopiano Leonardo
Published: March 2021

Background: Many studies on Parkinson’s disease (PD) patients affected by Coronavirus-disease-2019 (COVID-19) were recently published. However, the small sample size of infected patients enrolled in most studies did not allow to draw robust conclusions on the COVID-19 impact in PD. Objective: We aimed to assess whether the prevalence and outcome of COVID-19 in PD patients are different from those observed in the general population. Methods: We conducted a systematic review of studies reporting data on PD patients with a diagnosis of COVID-19 (PD-COVID+). We extracted prevalence, clinical-demographic data, outcome, and mortality. We also analyzed risk or protective factors based on comparisons between PD-COVID+ and control populations with PD without COVID-19 or without PD with COVID-19. Results: We included 16 studies reporting on a total of 11,325 PD patients, 1,061 with a confirmed diagnosis of COVID-19. The median infection prevalence ranged from 0.6% to 8.5%. PD-COVID+ patients had a median age of 74 and a disease duration of 9.4 years. Pooling all PD-COVID+ patients from included studies, 28.6% required hospitalization, 37.1% required levodopa dose increasing, and 18.9% died. The case fatality was higher in PD-COVID+ patients than the general population, with longer PD duration as a possible risk factor for worse outcome. Amantadine and vitamin D were proposed as potential protective factors. Conclusion: Available studies indicate a higher case fatality in PD patients affected by COVID-19 than the general population. Conversely, current literature does not definitively clarify whether PD patients are more susceptible to get infected. The potential protective role of vitamin D and amantadine is intriguing but deserves further investigation.
Detecção de agentes microbianos das mãos de acadêmicos e docentes de uma instituição de ensino superior em Primavera de Leste – MT
Authors:   Universidade de Cuiabá, Santana Vivian Tallita Pinheiro de , Duarte Phelipe Magalhães ,   Universidade de Cuiabá, Fernandes Uvleique Alves ,   Universidade de Cuiabá, Dalmas Alysson Dias ,   Universidade Federal de Santa Catarina, Ferri Isadora Eduarda Bariviera ,   Universidade de Cuiabá
Published: March 2021

The objective of the present study was to identify the microbiota present in the hands of academics and teachers of a Higher Education Institution in the municipality of Primavera do Leste - MT. Samples were collected from 24 volunteers using a swab. Of the samples collected, 19 (79.1%) showed bacterial growth in a nutrient culture medium, being isolated from this: Staphylococcus aureus (31.6%), S. lugdunensis (31.6%), S. epidermidis (15.8%), S. spp. (5.8%) and Escherichia coli (5.2%). The occurrence of bacteria found in the hands of the volunteers makes it possible to infer that the hands can act as a means of transmission and microbiological multiplication. To avoid this transmission, hygiene and antisepsis measures should be adopted regularly.
Toxocariose em bovinos leiteiros no estado de Rio Grande do Sul
Authors:   Universidade Federal do Rio Grande do Sul, Mattos Mary Jane Tweedie de , Pozza Maikel Jones , Opitz Fabiola , Bitencourt Ana Paula Gobbi de , Guedes Fabiane , Merlin Junior Ivandre Antonio , Praetzel Karen
Published: March 2021

Parasitic diseases in cattle represent a worldwide health problem, with emphasis on toxocariosis involved in animal mortality in the first weeks of life. The purpose of this report is to record the prevalence of Toxocara eggs (Neoascaris) in the feces of cattle in RS. Fecal samples were processed using the Willis-Mollay method. In the present study, it was observed that 41.36% (67/162) of fecal samples from cattle (162) had Toxocara (Neoascaris) vitulorum eggs, with 49.25% of calves and 50.75% of cows being positive. The high degree of infection demonstrates that there is a lack of knowledge of parasitosis on the part of producers, requiring further studies in livestock.
PENGEMBANGAN PERANGKAT WIRELESS SENSOR NETWORK UNTUK MENGONTROL TINGKAT VOLUME AIR PADA TURBIN
Authors: Hesti Emilia
Published: March 2021

Wireless Sensor Network technology is a wireless network consisting of several individual sensor nodes that are used to monitor the condition of a place and can interact with its environment by means of sensing, controlling and communication of physical parameters. The application of Wireless Sensor Network Technology to the water turbine as a power plant is used for remote control and monitoring of the water turbine. So that it allows users to get maximum and real time information without having to be in the sensor area, in the sending and receiving of information using the Wireless HC-12 module with a frequency range of 432 MHz. HC12 Wireless Transceiver that can receive information on the Master Controller device and can send requests to the microcontroller on the server device. In this subsystem there is a MAX232 IC as a converter that converts the RS232 level signal from a TTL level signal on the HC12 Wireless module to a data communication that can be displayed on a computer. Keywords: Artificial Inteligent, Embedded System, Microkontroller, Visual Basic, Wireless Sensor Network
The role of Russian and Tatar intelligentsia in the cultural life of Kazakh society
Authors:   L.N. Gumilyov Eurasian National University, Janguzhiyev M.S.
Published: March 2021

The article deals with the organization of library business in the Kazakh region in the midXIX - early XX centuries and the valuable heritage of the Russian and Tatar intelligentsia for the study of Kazakh society. According to the author, in order to optimize education, Kazakh scientists and educators used library resources of publishing houses in Orenburg and Kazan. In addition, the author provides specific facts about the role of the Kazakh intelligentsia in the work of printing houses, including the increase in the number of publications. Although many libraries were disbanded and closed, history knows the works of the Kazakh intelligentsia. As a result of studying the history and culture of the Kazakh society of the mid-XIX - early XX centuries, the facts were confirmed not only about strengthening cultural and economic ties with neighboring countries, but also about the spiritual life of the people.
Reasons for mass revolts against the forceful collectivization of farms in the East Kazakhstan region
Authors:   Kazakh Humanitarian Law Innovative University, Zhylgeldy Zh.S.
Published: March 2021

The article examines the state policy in relation to the collectivization of the Kazakh ASSR in the late 20s and early 30s of the XX century and the reasons for the uprisings in the East Kazakhstan region. In the region of East Kazakhstan historiography of the Soviet period and the Soviet government on the reasons for the peasants‘ revolt against the collectivization policy envisaged in the post-Soviet period. The author’s research assesses the direction of research on the causes of the uprisings of the Soviet period, its reliability and influence on state policy. Currently, the directions and features of modern research are analyzed in detail, and the goals are clearly defined. After analyzing the works published after the 90s of the XX century, they were not published during the Soviet period, used new archival documents, expanded the field of research, and made conclusions of new quality. The study identified the political, social, economic, and cultural causes of the uprisings against mass forced collectivization in the late and early 30s of the twentieth century. The article analyzes the relationship of collectivization policy with uprisings in the modern East Kazakhstan region and in other regions.
Union of naymans and merkits in the 13th century
Authors:   L.N. Gumilyov Eurasian National University, Kayirken T.Z.
Published: March 2021

This article discusses the creation of the alliance in the 13th century between the Naiman Kaganate that lived in the Altai and Khangai mountains and the Merkits who inhabited the southern parts of Lake Baikal, and their opposition to the forces of Genghis Khan, also considers the route of movement after their defeat by the Mongol forces. In the article, the author refutes the point of view of the Chinese historian Su Beihai that after the Merkits and Naimans lost the battle, the Mongols migrated to the Idikut state through the Altai Mountains and the eastern part of the Dzungarian lowland. The fact is that, after the defeat by Genghis Khan’s troops and retreating to Western Altai, the Naimans and Merkits were not able to cross over the Irtysh again and move to the Eastern part of Altai, which remained under Mongol rule. On the same basis, according to historical data, the Naimans and Merkits, after being defeated by the Mongols at the intersection of the Bukhtarma River and the Irtysh River in Western Altai, migrated to the borders of the Idikut state through the mountains of Kalba, Tarbagatai and the Western edge of the Dzungarian lowland. In addition, the history, ethnocultural ties and traditions of statehood of these two ethnic groups are presented before the conquest of Central Asia by Genghis Khan in 1218.
Reflection of historical events in the toponymy of the West Kazakhstan region (based on the materials of the Baiterek, Burly, Terekty districts)
Authors:   L.N. Gumilyov Eurasian National University, Umitkaliev U. U. , Zhanissov A. T. ,   L.N. Gumilyov Eurasian National University, Koshman T. V. ,   L.N. Gumilyov Eurasian National University, Kurmangozhina T. M. ,   L.N. Gumilyov Eurasian National University
Published: March 2021

The article discusses about the main stages of the historical development of Ural regions through the prism of toponymy dates. The article was prepared as part of a joint research project «Research of historical toponymy of some regions of the West Kazakhstan» of L.N. Gumilyov Eurasian National University and Zhangir Khan West Kazakhstan Agrarian-Technical University. In 2019, the team of authors conducted research on the historical toponyms of the Baiterek, Burly, Terekty districts of West Kazakhstan region. The toponymy of area is a kind of primitive knowledge of the surrounding nature, geography, which closely related to the way of economic life. Studying of the toponyms of the region, coupled with historical and ethnographic sources, contributes to understand many past events. In this research authors used field studies conducted in the territories of these regions in 2019, published materials from previous years, written sources of the pre-revolutionary period, and oral history materials
Religious policy of the Soviet authorities during the Second World War
Authors:   L.N. Gumilyov Eurasian National University, Ilyassova K.M. , Zholdassuly T. ,   Selcuk University
Published: March 2021

This article intends the change in the Soviet Religion Politics during the World War II. At first the Soviet Religion Politics and the Soviet opression against religion after the WWII is explained. It reveals how the Soviet Religion Politics changed abruptly, futhermore their appeal to clergy to unite the believers against enemy. The formation of the Russian Orthodox Church and four Spiritual Administrations of Muslims has also been mentioned in this work. Besides, it explains that The Soviets had to give freedom to religion in order to get foreign and local Muslims’ support and did every possible means to raise people’s spirit. The information that all believers, especially Muslims contributed to the victory also that they financially and materially supported the soldiers, families is given with archive documents. This contribution lasted after the war. Accordingly Muslims were praised for it, resulting in Islam and State reconciliation
The Development of gender studies in the World and in Azerbaijan
Authors:   Department of Philosophy and Social Sciences of Azerbaijan State Pedagogical University, Adygezalova S.
Published: March 2021

The large-scale development of gender research in the world took place in the 1960s. These studies in the post-Soviet space made serious changes in the world view, philosophy and social knowledge, which experienced a deep crisis after the collapse of the Marxist-Leninist methodology. In philosophy, a new era of postmodernism began, in which gender studies, along with synergy, ecology, a culture of peace and other non-classical directions, laid the foundations for the newest directions of knowledge. The development of the «second nature» - culture until today permanently carries out the process of segregation of women and men, establishing temporary norms of their behavior, consolidating certain values, in general worldviews of the two sexes, which differ significantly from each other, sometimes reaching a polar opposite. In this regard, gender relationships and roles often fit into the pattern of binary opposition, widely represented in historical types of knowledge, in different social and humanitarian sciences. In this context, it is possible to imagine an initial, somewhat simplified definition of gender, which should be understood as the scientific and philosophical direction of research into the totality and characteristics of the behaviour, roles and values of men and women in each particular society. The paper attempts to reconstruct the nodal moments of history, theory, methodology and practice of gender philosophy development in the world and Azerbaijan. The method of research in the article is selected historical and philosophical analysis. The scientific novelty consists in reconstruction of the stages of transformation of world feminism into gender research, summing up the results of the first stage of gender research development in Azerbaijan and determining the essential features of its second stage. The author believes that the first phase, which was educational and feminist, has now been completed. On the basis of the analysis undertaken, it is stated that the forthcoming second stage in Azerbaijan will involve a shift to a gender approach and a study of men ‘s issues, with a view to determining the necessary procedures for the establishment of true gender equality.