bluuebunny/crossref_metadata_2025 huggingface dataset:
Terrain surveillance system with drone and applied machine vision
Authors: Viswanath Shreya , Krishnamurthy Rohith Jayaraman , Suresh Sunil
Published: November 2021

Road accidents are a major contribution to the Annual death rates all over the world. India, ranks first globally in the number of fatalities from road accidents. According to the Ministry of Roads & Transportation, India saw over 440,000 road accidents in 2019. As a result, over 150,000 lives were lost. Poor road conditions contribute to these directly and indirectly. In India, safety standards and conditions of roads are maintained by local bodies in a given area of jurisdiction. While there have been several attempts at improving the quality of roads, weren’t instrumental in giving proper results [42]. A recent study suggested that Artificial Intelligence (AI) might help achieve the goals. Some of the AI applications have had better results when powered with Computer Vision. While computer vision has been previously used to identify faults in roads, it is not widely implemented or made available for public use. Road inspection still largely remains a time-consuming manual task, hindering the maintenance process in most cities. Moreover, being unaware of unattended faults on roads is often the cause of road accidents, especially in rough weather conditions that make it impossible for drivers to visually gauge any dangers on their route. The proposed model uses a transfer-learning approach; using Mask R-CNN in identifying the defects at an instance level segmentation. As adding this, it requires less labelling and an additional mask helps in blocking out extra noise around the images. This paper trains a Mask R-CNN architecture-based model to identify potholes, discontinuous roads, blind spots, speed bumps, and the type of road--gravel, concrete, asphalt, tar, or mud--with a dataset of images obtained from a drone. The model is further trained to create depth maps and friction estimates of the roads being surveyed. Once trained, the model is tested on a drone-captured live feed of roads in Chennai, India. The results, once sufficiently accurate, will be implemented in a practical application to help users assess road conditions on their path.
Unmanned aerial systems in search and rescue applications with their path planning: a review
Authors: Ajith V S , Jolly KG
Published: November 2021

In recent days, the Unmanned Aerial Systems (UAS) is an emerging technology rapidly across many warfare’s and enable new civilian domains which include real-time monitoring, security, border surveillance, wildlife surveys, providing wireless coverage, weather monitoring, smart farming, surveying, search and rescue, products delivery, farming, and civil structure inspection. Initially, there were many challenges in the design and control of UAS as it lacks an onboard pilot for navigation. Now the condition is improved with the implementation of artificial intelligence techniques in path planning and their coordination. Unmanned Aerial vehicles (UAV) in UAS technology open up new potentials in a variety of fields. This paper presents a review of recent literature, starting with the introduction about the UAS and its types, components, developments, potential applications of UAV in search and rescue and the paper completes with a summary of the different path planning methods used in UAS.
Ocean Surface Cleaning Autonomous Robot (OSCAR) using Object Classification Technique and Path Planning Algorithm
Authors: Adarsh JK , Anush OS , Shrivarshan R , Mithulesh Krishnaan S , Akash JK , Arul R , Angalaeswari S
Published: November 2021

Increasing water pollution is one of the biggest concerns in today’s world. It leads to a variety of problems including an increase in the level of toxic concentration in the water. This paper aims to introduce a concept of an ocean/water body cleaning robot that attempts to classify the wastes using a camera with a custom machine learning model and segregate accordingly using separators while collecting them on the basket attached, that can be recycled on the base station. The robot can be deployed on any water surface thus making it more effective than a largescale ocean pollution cleaning technique. It can be used to clean up oil spills from shipwreck and pipeline leakage and can monitor the water quality of the particular location and send a distress signal to the base station if the readings are abnormal. The water quality data and the information about the type of pollutants from the machine learning model can be used to formulate local laws to reduce pollution and create awareness about the type of material that ends up at the ocean/water body.
Drowsiness Detection and Rest Stop Suggestion
Authors: Sabari Mathavan R B , Rohitram V , Ashhwath C , Sasikumar P
Published: November 2021

In recent years, driving accidents have been increasing gradually, with most of them due to drowsiness. To tackle this problem, various methods and systems were developed to alert the driver behind the wheels, and to prevent accidents. A few approaches include heartbeat monitoring, pulse rate check, blink, and yawn detector. This paper discusses a driver mechanism, which is capable of detecting fatigue in real-time, using the Eye Aspect Ratio – EAR – parameter, and also provides a database with an interface for managers to track drivers. When the driver is tired, an email will also be sent to the manager. On the drivers’ side, there will be a buzzer noise to wake the driver up and nearby resting locations will be shown to the driver. Further, mapping to the nearby resting location of the driver’s choice is shown, if the driver feels too drowsy and feels the need for rest. It is essential to fabricate and construct this complete system via IoT and OpenCV methods to address this issue.
Modelling and Simulation of Nonlinear Jump Phenomena of a Non-ideal Rotor Involving Fractional Order PD Controller
Authors: Ghosh Gaurav , Jha Abhishek Kumar , Dasgupta Sovan Sundar
Published: November 2021

Rotating machinery with high speed powered by industrial motors frequently suffers from instability by exhibiting non-linear jump phenomena, formally known as Sommerfeld effect. The drives whose excitation is a function of the system responses, referred to as non-ideal. The system dynamics of such systems exhibit a couple of complex and interesting features when the input power exceeds a critical value. The present research suggests a novel approach to study the efficacy of active magnetic bearing with fractional PD controller to suppress the instability caused by the Sommerfeld effect. The steady-state results obtained by solving the system characteristic equation numerically is compared with the transient analysis. Finally, root locus method is introduced to obtain the bifurcation points at which this kind of instability completely disappears.
Harnessing Energy from Everyday Life
Authors: Roy Madhusree Sankar , Mirunalini A R , Krishna Pavan Sai , Ghosh Ritama , Akash Saravanan B , Manna Shubham , Shwetha S , Sri S Varsha , Augusta Sophy Beulet P
Published: November 2021

Renewable energy will drive the future. The applications of mobile phone is no longer limited to communication between each other but can also be used on an everyday basis starting from grocery shopping to watching series for entertainment. Thus our mobile phones require constant charging of power. It is almost impossible to increase the mAh capacity of the battery indefinitely; therefore the need of a battery re-charging source is inevitable. The objective of this research work is to design a sustainable, portable charger in which power is generated with the help of piezoelectric sensors embedded into the shoes of an individual. The underlying principle is to transduce the pressure applied on the piezoelectric sensors to power. This power can be used to charge mobile phones using a USB cable at any convenient time. The light weight compatibility of the device makes it easily portable. In the proposed system, a grid of piezoelectric sensors of suitable size is incorporated in the shoes and an Android application is developed to monitor the power generated as well as to suggest the optimal walking pace for the user to increase power generation. The key highlight of this prototype is that it is user friendly and is paired with an Android application to facilitate maximum power generation.
Personalized Drug-Disease prediction using Multiple Linear Regression with ReLU
Authors: Vijaya S.
Published: November 2021

Predicting models for personalized Drugs related to specific disease are essential, as traditional methods are expensive and time consuming. The most challenging task in personalized medicine is predicting the status of disease from high dimensionality data. In the biomedical domain the association between drugs and disease plays a vital role as the same drug may treat similar diseases. For the good adaptability to complex and nonlinear behaviour data, Multiple Linear Regression method with ReLU Activation function is used for calculation and to fit the model with Drug –Disease dataset. Based on the results the drug or combination of drugs that treat a specific disease is predicted efficiently.
Ambulance detection using image processing and neural networks
Authors: Agrawal K , Nigam M K , Bhattacharya S , Sumathi G
Published: November 2021

Ambulance Detection using Image Processing and Neural Network is a vehicle detection and tracking system, which recognizes the vehicle (i.e., Ambulance in this case) amidst the traffic congestion. Due to the fact from past few years, the range of vehicles usage of the road is growing each day that results in traffic congestion, for better management of this traffic this system is useful. Traffic Congestion, as mentioned above, can be observed at an ever-growing pace in countries like India and Thailand, where the roads’ width and length make it impossible to make a separate lane for the emergency vehicle (like that of ambulance); Hence making it hard for the vehicle to pass through the traffic at the earliest possible time. The Ambulance tracking system is activated at the mapped junctions and that program detects the ambulance coming close to it and turns the traffic light to Green for the next 15 seconds. Geocoding is the practice of transforming addresses (like a physical address) to location information (like longitude and latitude) that can be used to locate a label on a map or to mark a grid. They plan to provide ambulances with this software to make it easy to transform addresses into a programmable format for review and retrieval. This data is converted to a system that shows all the crossings it must pass to meet the endpoint.
Intelligent Healthcare System for Recuperation and Inoculation of Communicable Diseases
Authors: Jay Sarika , Prabhakar Rao B V A N S S
Published: November 2021

Human life gets interrupted a lot when a communicable disease starts in a society. People are alerted a lot on a different basis and eventually, it leads to difficulty for continuing their normal life. This paper is focused on a communicable disease, the COVID-19, which gave an outbreak for all world counties into a state where their fellow human had to stop their daily job and stay back at home. Common people find it difficult to get treatment when they are identified as positive and also most of them lack the awareness of post covid recovery. The idea of this work is to create a healthcare system that initiates right from the covid test, appropriate treatment according to severity, post-recovery, and vaccination awareness and jabs. These units will have less human interaction and they will be fully automated till in need of pure doctor consultation. The automated system is programmed to identify the infection, its severity and prescribe the treatment accordingly, and follow up recovery needs. On-side, automated vaccination system will allow direct walk-in, identify the customer and do the needful.
Web Based COVID Detection System using Deep Learning
Authors: Srivarshan S , Seshadri Prithvi , Kaarthikand E , Vijayalakshmi A
Published: November 2021

Currently COVID-19 is a disease that is ravaging the entire globe. Generally, people affected with COVID-19 will come down with a mild to moderate respiratory illness. Detecting COVID-19 has become a major concern in hospitals due to the sheer number of people who claim to have been suffering from the symptoms. This work presents a solution to this problem where the patient can determine whether he/she has COVID-19 or not. This research work tries to identify whether a person is infected with COVID or not by processing the X-Ray scan of the chest area using Deep Learning with the aid of a Neural Network. X-Ray images obtained from a GitHub repository have been used to train the model. Then the model can predict using the X-Ray image obtained from the user. Aweb application has been developed, to make this process seamless and efficient. The trained neural network is used to process the given image. This will be done in the back-end of the web application. If the person is infected with COVID, the application makes use of an advanced AI searching algorithm to find the most suitable physician based on the requirements of the user.
Evolution in diagnosis and detection of brain tumor – review
Authors: Sravanthi Peddinti A , Maloji Suman , Manepalli Kasiprasad
Published: November 2021

Diagnosis of Brain tumor at an early stage has became an important topic of research in recent time. Detection of tumor at an early stage for primary treatment increases the patient’s survival rate. Processing of Magnetic resonance image (MRI) for an early tumor detection face the challenge of high processing overhead due to large volume of image input to the processing system. This result to large delay and decrease in system efficiency. Hence, the need of an enhanced detection system for accurate segmentation and representation for a faster and accurate processing has evolved in recent past. Development of new approaches based on improved learning and processing for brain tumor detection has been proposed in recent literatures. This paper outlines a brief review on the developments made in the area of MRI processing for an early diagnosis and detection of brain tumor for segmentation, representation and applying new machine learning (ML) methods in decision making. The learning ability and fine processing of Machine learning algorithms has shown an improvement in the current automation systems for faster and more accurate processing for brain tumor detection. The current trends in the automation of brain tumor detection, advantages, limitations and the future perspective of existing methods for computer aided diagnosis in brain tumor detection is outlined.
A Tree Based Machine Learning Approach for PTB Diagnostic Dataset
Authors: Premanand S , Narayanan Sathiya
Published: November 2021

The primary objective of this particular paper is to classify the health-related data without feature extraction in Machine Learning, which hinder the performance and reliability. The assumption of our work will be like, can we able to get better result for health-related data with the help of Tree based Machine Learning algorithms without extracting features like in Deep Learning. This study performs better classification with Tree based Machine Learning approach for the health-related medical data. After doing pre-processing, without feature extraction, i.e., from raw data signal with the help of Machine Learning algorithms we are able to get better results. The presented paper which has better result even when compared to some of the advanced Deep Learning architecture models. The results demonstrate that overall classification accuracy of Random Forest, XGBoost, LightGBM and CatBoost, Tree-based Machine Learning algorithms for normal and abnormal condition of the datasets was found to be 97.88%, 98.23%, 98.03% and 95.57% respectively.
Optimization of FSW Process Parameters to Yield Maximum Shear Fracture Load of AA2024 Aluminum Alloy Joints
Authors: Rajesh A , Bhaveshkumar C , Aswin L , Aravind Nachiappan S , Ashwin R
Published: November 2021

AA2024 Aluminum alloy has predominantly been used for making aircraft engine parts and frames. The normal welding process does not apply to join aluminum alloy. Because Al and its alloy have a low melting point and high thermal conductivity, which can easily lead to porosity and partially melting; as a result, Friction Stir Welding (FSW) has been employed to solve these issues. This work focused on the parameter’s optimization to the conceived maximum strength of AA2024 aluminum alloy. Four major parameters viz., tilt angle, shoulder diameter, welding speed, and rotational speed were selected. The formulation of empirical relationship was made using statistical tool design of experiment, and analysis of variance has been used to check the developed model’s adequacy. Furthermore, the response surface graphs were used to identify the maximum strength and its corresponding FSW parameters. The joint obtained the full power from the experimental results at a tilt angle of 1.5 deg., traverse speed of 15 mm/min, speed of tool 1100 rpm, and diameter of shoulder 24 mm.
Concept Design and Analysis of Self Sustainable Triboelectric Pacemaker
Authors: Ackshaya Varshini K S , Maanav Charan K.S. , Shyam Kumar M B
Published: November 2021

The heart is one of the most crucial organs for the functioning of the human body. Due to aging and various other ailments like cardiomyopathy and congestive heart failure, the functioning of the heart tends to drop or stop in serious conditions. In such conditions, a bio-medical device called the cardiac pacemaker is used. The pacemaker is a small device that will be placed in the dysfunctional heart that sends electrical impulses to the heart muscles whenever the functioning decreases or ceases. But the pacemaker existing in the market has a low battery life and has to be replaced every few years which is a painful process for the people using it. Therefore, to overcome this predicament in this study we have designed and developed a self-sustaining pacemaker that can generate its electricity from the pacing of the heart itself thereby increasing its battery life generously. This pacemaker works on the principle of tribe-electricity. The model of this pacemaker is designed using SolidWorks and the electrical circuit for the same is simulated using Simulink.
Estimation of fatigue life parameters of an Alumino Thermic weld on UIC60 rail joint using LEFM
Authors: Sen Prakash Kumar , Bhiwapurkar Mahesh , Harsha S P
Published: November 2021

At wheel track contact point, the high stress concentration, poor weld quality, and heterogeneity of weld material are the main factors that cause fatigue crack on any rail weld. Railway network agencies are concerned about the safety of the railway track when it comes to detecting and fixing weld faults to avoid vehicle derailment and loss of lives. This study analysed a numerical simulation of fatigue crack and its evolution under loaded service condition. A 3-D CAD wheel rail weld assembly model was built to study an AT welded joint under fatigue, and for stress concentration factor (SIF) calculation. The results are found by inserting a semi elliptical crack on the rail weld head surface with ANSYS, and then numerical simulation has been performed to get the different three modes of SIF at rail weld crack. The analysis findings data was recorded with critical fracture parameters of SIFs and its number of cycles to failure using LEFM technique and respective results have been plotted. With ANSYS the stress intensity on a crack will be resulted. By using numerical method, the critical crack size and number of cycle load with fatigue life of rail would be determined. The numbers of rail weld inspection per year has been determine by using the maximum number of cycle. The aim of this paper is to develop an effective inspection and maintenance frequency based on rolling contact surfaces crack propagation analyse. This will help to prevent the occurrence of rail failure by taking the required action at the right time, and extend the rail life expectancy, reduce the rail maintenance work and its cost.
Evaluation of nitrogen loading in the last 80 years in an urbanized Asian coastal catchment through the reconstruction of severe contamination period
Authors: Wang Kunyang , Onodera Shin-ichi , Saito Mitsuyo
Published: November 2021

Most semi-enclosed seas have experienced severe eutrophication owing to high nutrient loading from rivers during rapid population growth periods. In Japan, the coastal areas of some megacities (e.g. Tokyo and Osaka) experienced considerable economic growth during the 1960s–1970s. Therefore, determining the amount of nutrient loading during this period is essential to undertake measures for the conservation of coastal environments. However, determining the nutrient loading that occurred several decades ago is generally difficult owing to lacking water quality records. In this study, the nitrogen loading in the Yamato River catchment, an urbanized coastal catchment in Asia, for 80 years from the 1940s to the 2010s is reconstructed using the Soil and Water Assessment Tool. We considered factors such as population growth, wastewater treatment plant (WWTP) construction, and changes in land and fertilizer usage in different urbanization stages. Results show that the total nitrogen loading in the catchment peaked in the 1970s at 6616 tons yr−1 owing to untreated wastewater discharge and rapid increase in population growth. By reducing 57% of the nitrogen loading in the 2010s from the catchment, WWTPs have been instrumental in improving the water environment. The decrease in and integration of agricultural land has reduced nitrogen loading attributed to nonpoint sources; however, this reduction was not obvious because of the high fertilizer usage before the 2000s. Overall, the findings of this study provide a comprehensive understanding of the impact of rapid urbanization in an Asian coastal catchment on nitrogen loading during the high economic growth period in the past. This study will be useful for the long-term assessment of nutrient loading in other.
Diffusion with stochastic resetting of interacting particles emerging from a model of population genetics
Authors: da Silva Telles Timóteo , Fragoso Marcelo Dutra
Published: November 2021

In this paper, we put forward a connection between diffusion with resetting and a certain extension of Ohta–Kimura model, inspired on what was carried out in Da Silva and Fragoso (2018 J. Phys. A: Math. Theor.
51 505002). The contribution is twofold: (1) we derive a new extension of Ohta–Kimura model, dubbed here new extended version of Ohta–Kimura ladder model (NOKM) which bears a strong liaison with the so-called jump-type Fleming–Viot process. The novelty here, when we compare with the classical Ohta–Kimura model, is that we now have an operator which allows simultaneous interaction among many individuals. It has to do with a generalized branching mechanism i.e. m individual types extinguish and one individual type splits into m copies. The system of evolution equations arising from NOKM can be seen as a system of n-dimensional Kolmogorov forward equations (or Fokker–Planck equations). The analysis requires an amenable armory of concepts and mathematical technique to analyze some relevant issues such as correlation, indistinguishability of individuals and stationarity; (2) nudged by the ideas brought to bear in Da Silva and Fragoso (2018 J. Phys. A: Math. Theor.
51 505002), we advance in this agenda here by making an initial incursion on the connection between diffusion with resetting and the NOKM. The connection which relies on the similarities between the models allows, in some cases, that relevant results obtained for one model can be translated to the other model framework by taking advantage of the technique used to derive a result in one of the models. Through the development of the population genetic model and its reinterpretation in terms of diffusion with stochastic resetting, we show an invariance property of the correlation between two interacting particles that reset at a time-inhomogeneous resetting rate. Pushing forward the ideas we obtain the stationary state of a new model for an n-particle system under an anisotropic diffusion with resetting. Although the results using this approach are of recent vintage, we believe that this avenue of research seems to be very encouraging.
Twisted kink dynamics in multiflavor chiral Gross–Neveu model
Authors: Thies Michael
Published: November 2021

The Gross–Neveu model with UL(N
f) × UR(N
f) chiral symmetry is reconsidered in the large N
c limit. The known analytical solution for the time dependent interaction of any number of twisted kinks and breathers is cast into a more revealing form. The (x, t)-dependent factors are isolated from constant coefficients and twist matrices. These latter generalize the twist phases of the single flavor model. The crucial tool is an identity for the inverse of a sum of two square matrices, derived from the known formula for the determinant of such a sum.
The inspection paradox in stochastic resetting
Authors: Pal Arnab , Kostinski Sarah , Reuveni Shlomi
Published: November 2021

The remaining travel time of a plane shortens with every minute that passes from its departure, and a flame diminishes a candle with every second it burns. Such everyday occurrences bias us to think that processes which have already begun will end before those which have just started. Yet, the inspection paradox teaches us that the converse can also happen when randomness is at play. The paradox comes from probability theory, where it is often illustrated by measuring how long passengers wait upon arriving at a bus stop at a random time. Interestingly, such passengers may on average wait longer than the mean time between bus arrivals—a counter-intuitive result, since one expects to wait less when coming some time after the previous bus departed. In this viewpoint, we review the inspection paradox and its origins. The insight gained is then used to explain why, and under which conditions, stochastic resetting expedites the completion of random processes. Importantly, this is done with elementary mathematical tools which help develop a probabilistic intuition for stochastic resetting and how it works. This viewpoint can thus be used as an accessible introduction to the subject.
Position-dependent mass Dirac equation and local Fermi velocity
Authors: Ghosh Rahul
Published: November 2021

We present a new approach to study the one-dimensional Dirac equation in the background of a position-dependent mass m. Taking the Fermi velocity v
f to be a local variable, we explore the resulting structure of the coupled equations and arrive at an interesting constraint of m turning out to be the inverse square of v
f. We address several solvable systems that include the free particle, shifted harmonic oscillator, Coulomb and nonpolynomial potentials. In particular, in the supersymmetric quantum mechanics context, the upper partner of the effective potential yields a new form for an inverse quadratic functional choice of the Fermi velocity.
Comparative evaluation of varieties of winter hard wheat by the weight of 1000 grains with different morphotype of the germ
Authors: Kazakova A S , Galayan A G , Samofalova N E , Yu Maiboroda S , Kuleshova L A , Tatyanchenko I S
Published: November 2021

Abstracts. The productivity of plants depends on the weight of 1000 grains (M1000), the density of the productive stalk, the number of grains per ear, cultivation conditions, etc. The aim of the research was to comparatively evaluate M1000 in seeds differing in the morphology of the embryonic part, in varieties of durum winter wheat bred by the Agrarian Scientific Center “Donskoy”. The weight of 1000 grains were determined according to the State Standard 10842-89. The most productive and frequently encountered are the seeds with the main morphotypes 2, 3, 4, and 5, and the seeds with minor morphotypes 1a, 1, 6, and 7 make up 5%. An average positive relationship with M1000 of the entire heap of seeds was shown only for seeds of 2 main morphotypes - embryo morphotypes 2 (r = 0.45) and embryo morphotypes 5 (r = 0.42). Indicator M1000 embryo morphotypes 3 is not associated with M1000 of the whole seed heap, and all other embryo morphotypes for this trait have medium and strong negative correlation. Consequently, obtaining a fully formed grain in the dry spring and summer period is ensured by the stability of the filling of seeds of the main morphotypes 2 and 5.
The indices of sorghum seed quality in dependence on ecological and geographical origin
Authors: Kovtunov V V , Kovtunova N A , Popov A S
Published: November 2021

The current paper presents the study results of protein percentage, content of lysine and starch in the collection samples of grain sorghum of various ecological and geographical origin. It was determined that the seed protein percentage in the grain sorghum samples varied from 9.0 to 13.5%. The highest values were identified in the samples from Russia (KiM, Krymbel, Krusta, Ros’), Ukraine (Pioner 412/Milovskoe 6, No. 13-13, Pioner 878/Genicheskoe brown 129) and China (KX 8, No. 26-14) with 13.0-13.5%. The lysine content in protein of the studied samples was 2.5-4.3%, while the value of the standard variety Zernogradskoe 88 was 3.17% with the standard deviation of 0.24%. The maximum content (3.8-4.3%) was identified in the samples Early Hegari (Peru), Line ExF3 IS12606 (Australia), DN-35f (Ukraine), CS-175 (Philippines), H.S.-21 (Romania), Sorghum k-9553 (Korea). The starch content in seed of the collection samples varied within 70.2-77.5%. The highest intragroup values were showed by the samples from Peru (73.9%), Australia (73.8%), France (73.0%), Senegal (73.4%).
Spring vetch Mega mixed crops productivity at different seeding rates
Authors: Matveenko K A , Goncharov A V , Mednov A V , Volpe A A , Kruk E S , Abramkina L P
Published: November 2021

Spring vetch is the most well-known annual legume forage crop. With the cultivation and application of various methods and terms of harvesting crops, not only for green fodder and hay, but also for haylage, silage, grain-growing, the requirements for the quality of the mown mass were reduced, but the need to create non-growing crops suitable for machine harvesting increased. In the gene pool of spring vetch, there are no forms with a strong, resistant to lodging stem, so the only way to solve the problem is to support the supporting culture. According to the results of research for two years, for the cultivation of vetch for green mass, the best option is vetch mixed with oats with a seeding rate of 1.2 million vetch, oats of 3 million germinating seeds per hectare. For grain cultivation, the best option is a mixture of vetch and oats with a seeding rate of 1.8 million and 3 million germinating seeds, respectively. For obtaining a grain crop for seed-growing purposes, the best option for two years of research is vetch mixed with spring wheat with a seeding rate of 1.8 and 3 million germinating seeds per hectare.
The system of mineral nutrition of tomatoes in the Astrakhan region
Authors: Yu Anishko M , Ovchinnikov A S , Vilkova Zh A
Published: November 2021

The article considers the characteristics of tomato vegetable culture when growing it in the open ground in the soil and climatic conditions of the Astrakhan region. The total demand of tomatoes for macronutrients – nitrogen, phosphorus and potassium in the context of the planned yield from 40 to 100 tons per hectare, taking into account the availability of mobile forms of nutrients in the soil, is shown. The average doses of the main fertilizer application during the preparation of the soil for tomatoes, the timing and doses of fertilizing tomatoes with nitrogen fertilizers when they are applied with fertigation during sprinkling and the fertigation program for drip irrigation of tomatoes for processing are presented.
Role and significance of treatment in modern farming systems
Authors: Belenkov A I , Mazirov M A , Nikolaev V A , Zinchenko S I
Published: November 2021

The article deals with the influence of various methods of basic soil treatment on indicators of soil fertility and productivity of grain crop rotation crops at the experimental field of the Centre for precision farming. This center is based on the field experiment with the total area of about 6 hectares in the comparative study of precision and traditional farming technologies, as well as basic soil treatment techniques in a four-course crop rotation with alternating of crops: vetch and oat mixture for feed-winter wheat with stubble sowing of mustard for green manure-potatoes-barley. Two factors are studied in the experiment, namely technologies of field crops cultivation and methods of basic soil treatment. It is found that for most years, dump treatment was in the lead, primarily on a vetch and oat mixture and potatoes. The overall conclusion is that there are various degrees of manifestation interdependence between crops productivity and individual indicators of soil fertility, depending on treatment. The use of various agricultural methods that improve the rates of agrophysical, biological and agrochemical indicators will prevent the beginning of soil degradation in the field experiment of the center for precision farming and will stabilize soil characteristics at a sufficiently high level.
Development of precision farming technologies
Authors: Mazirov M A , Ragimov A O , Korchagin A A , Shenterova E M , Malakhova S D
Published: November 2021

The research was carried out on the territory of the Vladimir Opolye (Suzdal, Russian Federation). For the experimental site, in the watershed part of the plakor terrain with a slope of < 1°, a soil map was compiled. Field studies were carried out in a long-term stationary field experiment measuring 86 m by 280 m with the total area of 2.41 hectares. Four tillage systems were studied in the experiment: 1. generally accepted dump-annual dump plowing; 2. combined-energy-saving-alternation of small non-fall treatments with dump plowing of perennial grasses; 3. combined-tier-alternation of small non-fall treatments with plowing with a long-line plow of perennial grasses; 4. anti-erosion-alternation of deep non-fall treatments with plowing of perennial grasses. The results showed a different reaction of soil to agrotechnological techniques. Gray forest soils with a second humus horizon have a higher potential fertility, the advantage of which when applying moderate doses of mineral fertilizers was 3.3-4.4 centners per hectare of grain units compared to the background gray forest soils. A further increase in the dose negates these differences. Deep soil loosening by 25-27 cm also shows the advantage of soils with a second humus horizon, the yield increases were 4.4-5.2 centners per hectare.
Fertilizers, plant density and nutritional properties of corn grain
Authors: Syomina S A , Paliychuk A S , Gavryushina I V , Lysenko I A
Published: November 2021

The article presents data on the influence of an increasing plant density of an early-ripening corn hybrid on the biochemical composition and fodder properties of grain, depending on the level of mineral nutrition. It is shown that the highest protein supply was noted for the grain obtained in the variants with nitrogen feeding; the increase in crude protein in comparison with the variants on the natural agrobackground was 1.56%. The use of complete mineral fertilization had no advantages over a single application of nitrogen-phosphorus fertilizers; against these nutritional backgrounds, the increase of 0.97-1.05% was obtained in relation to the unfertilized agricultural background. As the crops crowd, there is a tendency for the crude protein content in the grain to increase. Over the years of testing, the stable influence of the conditions of mineral nutrition and the plants density on the content of crude fiber, crude ash and nitrogen-free extractive substances has not been established. The grain with a higher crude fat content was obtained with the introduction of complete mineral fertilization, and the crowding of the crops led to the decrease in its content in the grain.
Influence of humic preparations on productivity increase of cucurbits in arid farming conditions
Authors: Utaliev A A , Yakovleva L V , Maslova E A
Published: November 2021

The paper presents the results of studying the influence of liquid humic fertilizer produced from milled lowland peat on biological activity, the dynamics of nutrients in brown semi-desert soils in arid climate conditions with leaf fertilization of cucurbits. In arable farming of the Astrakhan region most of the harvest is formed by mobilizing soil fertility without compensation for the elements of nutrition carried out with the harvest, which leads to a negative balance of humus and nutrients, as a consequence, the soil is depleted, its fertility becomes lower. It is shown, that application of humates promotes increase of the content of humus in soil in arable horizons and reception of higher harvests of an early ripe watermelon that is caused by activization of biochemical processes in soil and increase of nutrients availability that has accelerated development and ripening of fruits of studied crop.
Transformation of immature wheat germ (Triticum aestivum L.) by particle bombardment
Authors: Verbitskaya A A , Ivanova A I , Shulga O A , Schuklina O A , Gaponenko A K
Published: November 2021

The aim of the research was to create an effective method for producing transgenic wheat plants suitable for a wide range of promising varieties, both spring and winter crops. The plant material was cultivated at temperatures ranging from 4 to 25°C, either in the dark or in the light, with a 16-hour photoperiod (16/8 - day / night). Osram L36/77 FLUORA and F36W/33 Cool White lamps were used for lighting. The composition of all nutrient media included macroand micro-salts, vitamins B5, phytohormones and carbohydrates. The pH of the medium was adjusted to 5.8 before autoclaving. The medium was sterilized in an autoclave at pressure of 1.2 atmospheres for 15 minutes. An effective method of regeneration of transgenic wheat plants for ballistic transformation has been developed. Plants obtained by this method are phenotypically normal and fully fertile. The transgenic insertion of the target gene is transmitted to the offspring in accordance with Mendel’s laws. The transformation efficiency was high for all the studied varieties and ranged from 1.4 to 7.8%.
Environmental and hydrological risks in the Lake Baikal basin water resources management
Authors: Bolgov M V , Buber A L , Buber A A , Korobkina E A , Golovinov E E
Published: November 2021

For optimal water resources management of the Angara reservoirs cascade (a complex “Lake Baikal – Irkutsk, Bratsk, Ust-Ilimsk and Boguchansk reservoirs”) and water users provision in the MIKE 11 software a quasi-two-dimensional simulation hydrodynamic model of the Angara hydroelectric power stations (HPS) cascade from Lake Baikal to the Boguchansk HPS downstream, which is a tool for reproducing the features of the water flow hydrodynamic structure, was developed. A hydrodynamic computer model using the built-in module “Regulating structures” module makes it possible to form reasonable operating modes of the Angarsk cascade of reservoirs that meet the most significant requirements of water users: ecology, fisheries and utilities, transport and energy. Hydrodynamic calculations and the flood zones obtained in the GIS project of the territory showed that catastrophic phenomena in the floodplain and coastal zone of Irkutsk occur even when releases into the lower pool of the Irkutsk reservoir exceed 3200 m3/s. The developed hydrodynamic model of the Angarsk cascade of reservoirs makes it possible to determine the objects and floodplain areas most susceptible to flooding in the downstream of the Irkutsk HPS for further development of scientifically based measures to protect them, prevent flooding and develop evacuation plans in an emergency.
Watering of the river delta Volga and Western sub-steppe ilmens based on simulation hydrodynamic modeling
Authors: Borodychev V V , Byber A A , Ratkovich E L
Published: November 2021

To ensure the flooding of the Volga river delta and the Western sub-basin Ilmen and meet the requirements of the fisheries and agriculture, the following tasks were set and completed: to describe the current state and the main environmental, fisheries, agricultural and transport problems of the functioning of the Volga Delta and the Western sub-basin Ilmen; to develop a computer simulation model in the software package MIKE 11 plot of the Volga river from Verkhneye Lebyazhye village before flowing into the Caspian sea, with the specification of cross-sections along the river bed and the floodplain of the Volga river and its branches, spawning grounds, and western sub-steppe ilmen; to perform computer hydrodynamic modeling of the studied section of the Volga river; to develop possible scenarios to solve the problems of flooding of the Volga river delta and the western sub-steppe ilmen, and to meet the requirements of fisheries and agriculture. As the result, the requirements of the main water users for the operating modes of the Volga hydroelectric power station were presented and a hydrodynamic model was described, which allows determining the measures for watering the territory and using simulation modeling to evaluate their effectiveness.
Management of information processes under a radiation emergency
Authors: Voronov O S , Popov E V , Voronov S I , Sednev V A
Published: November 2021

The article provides examples of radiation emergencies (ES), emergency response measures aimed at protecting the public and territories, including applicability of a comprehensive monitoring system of the public security conditions. A special attention is paid to scientific approaches and research results aimed at optimization of information processes during the operational use of data from monitoring systems on the conditions status under radiation emergencies. Besides, the expediency and sufficiency of using two data sources producing reports was determined and justified if one of the data sources is a monitoring system. Based on the research results, other provisions concerning the management of information processes under radiation ES conditions related to the requirements for operational public notification were justified. In particular, schemes for constructing such systems under special radiation ES conditions, algorithms for their operation, operating modes, and some parameters that these systems should provide with were justified. The information subsystem as a part of the CSPPCM is a kind of information system for the prompt public notification, and the research results are quite relevant for it.
Advanced technologies for the creation of forest cultures in the southern regions with arid climate
Authors: Kostin M V
Published: November 2021

The article analyzes the of the drip irrigation and biologically active substances fertilization use effectiveness in forestry in arid regions; the main advantages and disadvantages of drip irrigation for protective afforestation in dry steppe and semi-desert are indicated, the conclusion about the possibility of its use in the creation of forest crops with economic feasibility, the availability of infrastructure (a water source with water suitable for irrigation, power lines) is made. The use of drip irrigation is advisable when planting plantations of particular value (forest seed plantations, walnut groves, orchards, landscaping plantings in recreational areas, etc.). However, for an unambiguous answer, it is necessary to lay experimental crops in different soil and hydrological conditions, with different types and mixing schemes, woody and shrub species composition, to develop irrigation and watering norms, to test the latest biological preparations that improve the processes of root formation, growth, and resistance to diseases and environmental stressors.
Efficiency of forest planting in the spring and autumn periods in the conditions of the Republic of Kalmykia
Authors: Kostin M V
Published: November 2021

The Republic of Kalmykia is the driest region in the south of the European part of Russia. The purpose of the study is to find a new approach to reforestation and breeding in the republic, which will ensure the increase in the survival rate of forest crops, and subsequently increase the forest cover of the region. The article analyzes data for a ten-year period in a zonal section on the survival rate of tree and shrub species cultivated in the forestry of the Republic of Kalmykia. It is concluded that carrying out forest cultivation works in the autumn period has no advantages in survival rate over the spring period and they should be carried out either in early spring (in late March and early April) on thawing soil, or in autumn, before the onset of persistent cold weather. The main factor of successful afforestation in the dry steppe and semi-desert is the correct selection of the forest area, the accuracy and quality of forest planting, agrotechnical and forestry care. Special attention should be paid to the control of locust pests, which in the conditions of Kalmykia in some years can cause significant damage to the planting of young forest crops.
Scenario model to forecast behavior of intrusive plant communities in response to control effects in arid agriculture
Authors: Novochadov V V , Ivantsova E A , Shiroky A A , Onistratenko N V
Published: November 2021

The presence of large areas of anthropogenic transformation of plant communities with a potentially negative impact on adjacent territories makes it relevant to develop various methods for automated monitoring and modeling of processes occurring in these ecosystems. Based on the results of previous studies of phytocoenoses, the authors selected four groups of indicators for constructing a scenario model: integral characteristics of intrusive plant communities (IPC), including those obtained by using remote dynamic methods; integral indicators of the negative impact of IPC on the adjacent agro-ecosystem; indicators of the distribution of mobile forms of trace elements in the soil; and indicators of soil microbiota. As the result, a hypothetical formula is obtained that allows, with minimal impact on the biosystem of technogenic IPC, to sufficiently reduce its adverse impact on the adjacent agro-ecosystem. Further refinement and dissemination of the scenario model and its connection to databases on plant communities will automatically change the values of the coefficients in the solving equations, thereby providing the most accurate and reliable forecast of the response of agro-ecosystems to various control actions.
Fuzzy cognitive modeling of agricultural land productivity in the context of food security
Authors: Rogachev A F , Melikhova E V
Published: November 2021

The article deals with the problems of fuzzy cognitive modeling and evaluation of the productivity of reclaimed soils, taking into account the combination of natural-climatic, soil and environmental factors. To construct a fuzzy model, the parameters to be modeled were the coefficient of bioclimatic productivity with a range of variation of 0.5-1.5, and the yield of grain crops, which varied within 10…45 dt/ha for different natural and climatic zones. The theoretical basis for the development of a model of land productivity is the theory of fuzzy inference based on the fuzzy-multiple approach. The main stages of fuzzy modeling using the Mamdani algorithm in interactive mode are presented. An algorithmic representation of the dependence of the integral indicator of the productivity of agricultural land on the value of the yield of grain crops, and the coefficient of bioclimatic productivity is obtained. The constructed fuzzy model allows to obtain estimates of the generalized indicator of agricultural land productivity based on the yield values for the range of values of the bioclimatic coefficient. The constructed model can be used as a part of a system for predicting the level of food security.