bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of “low doses” of multiwall carbon nanotubes when interacting with white mustard seeds and sprouts
Authors: Polischchuk S D , Nazarova A A , Churilov D G , Churilova V V , Churilov G I , Stepanova I A , Arapov I S 
Published: May 2020

Abstract
The paper considers the influence of the sizes of carbon nanotubes (CNT) on the effect of "low doses" (LD) by changing the morphological, physiological and biochemical parameters of seeds and sprouts of white mustard. In the first series of experiments, 20 nm nanoparticles were studied. The second series considered 40-60 nm nanoparticles at concentrations of 0.01 to 1,000 g per ton of seeds. For CNT, the effect of "low doses" with particle sizes of 40-60 nm had its own characteristics. The germination energy and viability were inhibited or did not exceed the control at all concentrations studied with the exception of a concentration of 0.01 g / t when the root length increased by 18.5%. But the analysis of the mass of 7-day-old white mustard sprouts showed that the mass of the experimental sprouts exceeded the control in all cases. The change in the mass of 7-day-old mustard roots was “dome-shaped” and the maximum fell on a CNT dose of 5.0 g / t (+ 42.3% above the control). Carbon nanoparticles up to 20 nm in size showed higher activity in almost all parameters. Energy was higher than the control up to 10 g / t. Concentrations from 100 to 1,000 g / t had a depressing effect on this parameter. Biochemical studies confirmed the results of morpho-physiological studies.
Mathematical models for microbiological processes of rye broth maturation
Authors: Derkanosova N M , Shelamova S A , Uhina E Y , Vasilenko O A 
Published: May 2020

Abstract
One of the factors determining the quality of bakery products made of rye and mixed rye and wheat flour is broth, the parameters of its technology, and process regulation by varying the parameters of its technology. First of all, it is necessary to note the availability of the nutrient substrate and the nature of the interaction of the main microflora of broth cultures - yeast and lactic acid bacteria. The mathematical model of the process of cultivating microorganisms in liquid rye broth was suggested as applied to yeast and lactic acid bacteria based on the adapted equation of N.V. Stepanova and N.D. Jerusalem to describe the growth of lactic streptococci. Based on model systems, the interaction of yeast and lactic acid bacteria in liquid rye broth was studied. The symbiotic nature of this interaction was confirmed. It was justified that Lotka - Voltaire system is the most correct way for its mathematical description. The growth dynamics of the populations of yeast and lactic acid bacteria was described, and the adequacy of the obtained mathematical model was verified.
Designing and maintaining of circuits of distribution networks with voltage of 10-0.38 kV
Authors: Yarosh V A , Efanov A V , Chebanov K A , Zhdanov V G , Logacheva E A 
Published: May 2020

Abstract
The procedure for maintaining circuits in distribution networks with a voltage of 10-0.38 kV is determined in accordance with the Rules of Technical Operation, State Standard. In accordance with these documents, the types of circuits that should be in the subdivisions of electrical networks are determined. All changes in all circuits should be made immediately (after completion of installation work before commissioning), signed by the responsible person. Information on changes in the circuits should be brought to the attention of all employees for whom knowledge of these circuits is required. The need to have the same circuits in production services and subdivisions of electric networks justifies the use of modern information systems such as geographic information systems, which allow working with all types of electric network circuits in multi-user mode. In this case, users will have the most accurate information. The article describes the requirements for supporting circuits designing. The issue of input, preparation and maintenance of data is up to 90% of the cost of a serious project of a geographic information system (according to press). And only 10% is the cost of equipment and software for the geographic information system. A task requiring such costs can be effectively solved only by professional means on professional equipment. The article discusses how to enter electrical network diagrams into geographic information systems and proposes a technique for introducing overhead lines support circuits of 6-10 kV into a geographic information system.
On the substantiation of the technological scheme of the combine harvester with the stationary process of threshing bread mass
Authors: Ovchinnikov A S , Lovchikov A P , Ryadnov A I , Fedorova O A , Konstantinov M M , Fomin S D 
Published: May 2020

Abstract
The article considers the following issue: that further improvement of the grain combine design with the classical threshing-separating device is possible due to the development of its technological scheme based on the principle of modular construction and stationary process of threshing grain mass. To achieve this goal, the problems were solved, by which laws were revealed and a mathematical description of the technological process of the combine harvester was given, as well as patterns characterizing the effect of straw on the process of threshing the grain mass were revealed. It is revealed that the coefficient of straw of grain mass is possible to reduce during combining, grain crops through the application of high-cut stems. Production check has established that the technological resource of this process of direct grain crops harvesting is limited due to the increase of the negative impact of both the ratio of grain and straw by weight and the height of the cut of the stems on the agrotechnical indicators (grain loss) of the combine.
Numerical and experimental analysis of flow and particulate matter dispersion in indoor environment
Authors: Pini A , Musa I , Monti P , Leuzzi G , Bernardino A Di , Cattani G , Di Menno di Bcchianico A , Gherardi M , Pelliccioni A 
Published: May 2020

Abstract
Reducing indoor particulate matter (PM) concentration is an issue of concern from an environmental point of view as the world’s population spend only 4% of their time outdoors. Computational fluid dynamics (CFD) is a fundamental tool for predicting indoor pollutant dispersion and improving knowledge on how indoor and outdoor environments interact in terms of pollutant and momentum exchanges. In this paper, an unsteady CFD simulation has been carried out to investigate the airflow and PM concentration in a classroom of the University of Rome “La Sapienza”. Wind velocity and PM concentration acquired during a field campaign conducted within and outside the building of interest have been used as input for the simulation and to test the model performance as well. The results show a reasonable agreement between measured and simulated concentration within the classroom and emphasize the major role played by the micrometeorology in PM concentration. The importance of the boundary conditions at the room openings has been also discussed.
Analysis of Wind Speed, Humidity and Temperature: Variability and Trend in 2017
Authors: Zakaria Nur Hidayah , Salleh S A , Asmat Arnis , Chan Andy , Isa Nurul Amirah , Hazali Nur Atiqah , Islam M A 
Published: May 2020

Abstract
In recent years, it has been observed that numerous cases of windstorm event. There are many factors that cause windstorms to occur. The factors of meteorology, urban morphology, the topography need to be studied to find out the cause of windstorms. The work analyzed meteorology factors such as: wind speed, humidity and temperature, occurring in 2017. Meteorological data from the Department of Environment Malaysia (DOE) station, allow determining the wind speed, humidity and temperature data daily in 2017. As well as, the pattern of parameter and their relationship between them being determined. The pattern of wind speed monthly was inconsistent. The highest average wind speed in 2017 was 4.72 m/s and the lowest average was 0.56 m/s. While humidity, the highest average was 83.12 % and the lowest average humidity was 72.33 %. For temperature, the maximum average for 2017 was 28.43 °C and the minimum average was 26.26 °C. The correlation of wind speed between humidity and temperature was -0.256 and 0.278, which is low correlate. That must be other active factors that influence the wind speed and contribute to the windstorm event. Wind speed, humidity and temperature during the windstorm event on 11 February 2017 was analyzed. During the windstorm event, the wind speed blows up to 15.7 m/s while the humidity reading decrease to 68.4 % and the temperature was 30.9 °C. When the wind speed reading is high, the temperature reading also increases and the humidity reading will go down and vice versa and has caused the windstorm event to happen.
Identification of air quality redundant stations through a clustering ensemble method
Authors: Stolz T , Huertas M , Mendoza A 
Published: May 2020

Abstract
The main purpose of this study is to assess the performance of three air quality monitoring networks of Mexico. Emphasis is placed on an ensemble method to combine the results of the different clustering techniques: Principle Component Analysis, Hierarchical Clustering and k-means. The specific objectives of this paper are: (i) finding similar and redundant stations using the ensemble method and (ii) giving a physical meaning to groups of similar stations by evaluating additional information like emission sources, meteorology and topography of the area of interest. The study was applied on time series data of particulates that have aerodynamic diameters less than or equal to 10 μm (PM10) and ozone (O3), acquired from the air pollutant monitoring systems in the metropolitan areas of Mexico City (MCMA), Monterrey (MMA) and Guadalajara (GMA). These three conurbations are characterized by diverse meteorological and geographical conditions. The findings show that the GMA has a well distributed air quality network with the fewest number of similar stations. The MMA presents the same clusters of stations for PM10 and O3, while in the MCMA a cluster of possible redundant stations is found. Results confirm that the clustering ensemble method is a confidence tool to identify similar stations.
Innovative low-cost air quality stations as a supporting means for road traffic regulations in urban areas
Authors: Brilli L. , Berton A. , Carotenuto F. , Gioli B. , Gualtieri G. , Martelli F. , Profeti S. , Trombi G. , Dibari C. , Moriondo M. , Vagnoli C. , Zaldei A. 
Published: May 2020

Abstract
Air pollution is currently one of main issues affecting urbanized areas worldwide. Industrial activities, road traffic and heating systems are main emission sources significantly increasing the levels of atmospheric pollutants as particulate matter, ozone, and nitrogen oxides. Local administrations monitor these harmful gases by means of reference monitoring stations provided by regional/national environmental protection agencies. These stations, however, have limitations due to the little presence over the whole municipality, low time-frequency, and high costs. In this framework, CNR-IBE, University of Florence – Department of Agriculture, food, environment, and forestry (DAGRI), Tuscany Region Environmental Protection Agency (ARPAT) and epidemiologists of the Pisa University agreed an initiative to create an environmental “living lab” aimed at assessing the impacts due to anthropogenic activities on air quality and thus on population exposure. Two study areas located in the Tuscany region (Italy) were chosen: the rural town of Capannori, and the city of Florence. The town of Capannori was selected since it lies within a critical area both affected by a variety of emission sources and winter weather conditions unfavourable to pollutant dispersion. The city of Florence was chosen for assessing air quality in urban areas following a possible traffic reduction due to creation of new urban tramway lines. The air quality analysis was carried out by means of a monitoring network comprising innovative low-cost stations (named AIRQino). PM concentrations were mainly considered for providing indicative air quality measurements. The preliminary results indicated that: i) low-cost stations, after calibration and validation against more than one-year observations from a reference air quality station, confirmed their reliability in measuring air quality data; ii) AIRQino data can supplement air quality information from reference stations and may be used to help traffic regulation actions at urban scale.
A Web-Enabled GIS Platform for Agricultural Land Use
Authors: Acedo Gemma G. 
Published: May 2020

Abstract
One of the important and leading sources of livelihood in Catanduanes is agriculture. Agriculture has been an avenue to help improve the Philippine economy. To further boost the agriculture industry, the researcher aimed to design and develop a web-enabled GIS platform for agricultural land use that contains a database socio-demographic profile and geographic physical information details of agricultural lands of the province. Data collected are subjected to analysis of an approach in the development and implementation of the study and set as bases for government implementation and a possible policy that assist farmers and local communities. The features of the system help the local leaders to strategize activities and easily facilitate the identification, monitoring, forecasting, visualization, and analysis of situations on Agricultural land use. The acceptability rating of the system developed is 4.72 highly acceptable according to system users. The web-enabled GIS serves as an initiative to improve agricultural land use system by integrating GIS in terms of locating, mapping, profiling, and land management in the province. It is expected through this endeavour that an increase in harvest rate will benefit farmers and local communities. Utilization is expected to help combat climate change and preserve the environment and its ecosystem.
Efficacy of virtual reality in reducing fear of public speaking: A systematic review
Authors: Daniels M M , Palaoag T , Daniels M 
Published: May 2020

Abstract
Public speaking is no doubt one of the most feared mode of oral communication. Such anxiety is often treated through cognitive behavior therapy (CBT). An arising alternative to this treatment is virtual reality exposure therapy (VRET) where user confronts feared stimuli in a controlled 3D environment designed for such purpose. Sense of presence in this medium elicits similar feeling when standing in front of a real audience. Because of this, several studies were conducted to test its effect on individuals suffering from PSA. This paper attempts to look into the undertakings of studies within the last 10 years with the objective of gaining enlightenment on the efficacy of virtual reality in reducing public speaking anxiety. From Google Scholar search engine and online libraries PLOS ONE and ScienceDirect, 14 were short-listed for final review based on the set inclusion/exclusion criteria. Findings of these studies reveal that VRET can be as effective as CBT, and more advantageous in terms of cost-efficiency and manageability. The use of virtual reality is then highly recommended as a tool for treating PSA. It is worth noting that the length of time spent in this therapy is a great factor in its efficacy.
Blood Glucose Prediction Model for Type 1 Diabetes based on Extreme Gradient Boosting
Authors: Alfian Ganjar , Syafrudin Muhammad , Rhee Jongtae , Anshari Muhammad , Mustakim M. , Fahrurrozi Imam 
Published: May 2020

Abstract
Predicting future blood glucose (BG) level for diabetic patients will help them to avoid critical conditions in the future. This study proposed Extreme Gradient Boosting (XGBoost), an ensemble learning model to predict the future blood glucose value of diabetic patients. The clinical dataset of Type 1 Diabetes (T1D) patients was utilized and the prediction models were generated to predict future BG of 30 and 60 minutes ahead of time. The prediction models have been tested tofive children who develop T1D and showed that BG prediction model based on XGBoost outperformed other models, with average of Root Mean Square Error (RMSE) are 23.219 mg/dL and 35.800 mg/dL for prediction horizon (PH) 30 and 60 minutes respectively. In addition, the result showed that by utilizing statistical-based features as additional attributes, most of the performance of predictions model were increased.
Orange Fruit Images Classification using Convolutional Neural Networks
Authors: Asriny Dhiya Mahdi , Rani Septia , Hidayatullah Ahmad Fathan 
Published: May 2020

Abstract
The quality of fruit is important to increase sales in the market. Right now, the quality selection of orange fruit is mostly still complete by humans. Several drawbacks such as inaccuracy and inconsistency in results happened due to the limitation of human perceptions. The development of computer vision, making it possible to train the computer to classify images based on specified characteristics. This paper proposes the classification model to classify orange images using Convolutional Neural Network (CNN). Five classes of orange namely good-orange-grade-1, good-orange-grade-2, immature-orange, rotten-orange, and damaged-orange are classified using deep learning CNN. Total of 1000 orange images is collected using the smartphone camera. Each class consists of 200 images which are divided into 60% as the training data, 20% as the validation data, and 20% as the testing data. K-Fold Cross-Validation method is used to validate the model. In this paper, the hidden layer of CNN consists of 256 nodes. Two activation functions, ReLU and Tanh, are employed for comparing the accuracy of classification with the Softmax classifier. The result shows that the accuracy of ReLU activation function is 96%, which is better than the Tanh activation function that gives only 93,8%.
Forecasting and Pattern Analysis of Philippine Regions’ Palay and Corn Production
Authors: Cortez Michelle M. 
Published: May 2020

Abstract
Inadequate food production has been an immediate concern that the country is trying to address. Where farmers used fertilizers in their farms in the hope of increasing their agricultural production. Though, if fertilizer application is poorly managed, instead of having an increased production it will result in the contrary. Therefore, the efficient use of fertilizer is critical and has a great impact on crop production. Thus this study aims to show the pattern of Philippine’ regions crop production, specifically in rainfed and irrigated palay; white and yellow corn. This will also show which fertilizer will maximize their crop production and to seek for the most applicable association model in forecasting future crop production. Three predictive techniques were used namely, canopy clustering, Apriori association rule mining and time series forecasting models. Results reveal that all regions have a low volume of production for rainfed rice. The canopy clustering shows the pattern leading to the high production of irrigated rice for Region III. Also, Region II, Region X, and Region XII have a high volume of production of yellow corn and lastly clustering results on white corn shows Region VII has a Mid area harvested but shows Low volume of production, while Region X though have a low area harvested managed to have a Mid volume of production. The association of fertilizers to the volume of production shows that low Ammophos leads to a lower volume of production and the low Ammosul is not associated with a low volume of production hence a combination of low Ammosul and low Ammophos leads to a low volume of production. The forecasting methods’ linear regression, Gaussian processes, and SMOreg are all applicable in predicting the regions’ volume of production, whereas the SMOreg has the least MAE of 8.90% for Region VI.
Hybridization of Genetic Algorithm and Artificial Immune System for Assignment Problem
Authors: Farhan La Ode Muhammad , Zukhri Zainudin 
Published: May 2020

Abstract
Genetic Algorithms (GA) have proven its reliability to obtain near optimum for complex problems. However, to optimize solutions and prevent premature convergence, operators on the GA were highly dependent on large population sizes, causing the computational speed to be slower than newer algorithms. Therefore, in this study, we propose a way to cause a significant improvement in GA for a higher quality of solutions and lower computing costs yet easy to implement. Hence, we analyzed the clonal selection algorithm from AIS to inspire genetic processes in GA. We then compared the performance of the proposed algorithm called HGA as with the GA to solve the assignment problem. Simulation results showed that HGA performed better in case of preventing on being stuck with the local optima as it accurately obtains an average of the optimum solution up to 100% for every given dataset while also reducing computational costs as it has less generation.
Populating Databases Automatically with Realistic Data Using Metadata-Driven Methods
Authors: Rebolledo K S , Arroyo J S , Roig JV 
Published: May 2020

Abstract
This research investigated the feasibility and utility of a metadata-driven “fake data“ generator. The researchers created a prototype for a data generator whose job is to be pointed to a database and then generate fake but appropriate and realistic data. Using metadata analysis, the generator was able to make autonomous and smart decisions as to how to populate the various tables and fields it encounters, populating them with realistic data. This promises great utility to programmers, QA testers, and database administrators for various use cases such as testing, debugging, database design validation, load testing, and performance scaling.
Disaster Sentiment Analysis: Addressing the Challenges of Decision-Makers in Visualizing Netizen Tweets
Authors: Baro R A , Palaoag T D 
Published: May 2020

Abstract
Among other crucial aspects of disaster-related initiatives is decision-making. The capacity to carry out efficient holistic management of measures and programs rely greatly upon the decision-makers and the religious participation of all stakeholders. Adopting the sentiments can help government leaders in their decision-making responsibilities towards disaster management when meaningful patterns are easily visualized. The purpose of this research is to analyze disaster-related sentiments from Twitter and presents the results using data visualization easily understood by decision-makers. The study underscores the use of Python programming with NLP techniques to learn from Twitter data, Sentiment Analysis using TextBlob to identify polarity and subjectivity of tweets and Plotly for interactive data visualization. The implementation of the study contributes to the reduction of injury, damage to infrastructures, properties and especially the loss of life. The challenges of both decision-makers and data scientists working in the discipline are highlighted in the study.