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Analysis is conducted on the non-trivial different integral solution to the quadratic equation

The homogenous biquadratic Diophantine equation with five unknowns non-zero unique integer solutions   4 4 2 2 2 x  y  26 z  w p are found using several techniques. The unusual numbers and the solutions are found to have a few intriguing relationships. The relationships between the solutions’ recurrences are also shown.

The non-homogenous cubic equation with three unknowns represented by the Diophantine equation ૜(࢞ ࢟ + ૛ ૛ ) − ࢠ૛૛૞ = (૚ + ࢟ + ࢞)૛ + (࢟࢞)૝ ૜ is analyzed for its patterns of stringfy integral solutions. A few interesting properties among the solutions and some special polygonal numbers are presented.

In this article, we concentrate on identifying all the non-zero, infinitely many integral solutions to the ternary cubic equation

To identify its different integral non-zero solutions, the ternary cubic equation 2 2 3 5x 3y  z is taken into consideration. Different integral solution patterns to the ternary cubic equation under consideration are obtained in each pattern by using the linear transformation and the method of factorization; interesting relationships between the solutions and some polygonal numbers, such as pyramidal and central pyramidal numbers, are also displayed.

In most countries, agriculture is considered a major primary sector and a principal source of income. It is estimated that by the year 2050, the world’s population is expected to reach 9.1 billion people. According to the United Nations Food and Agriculture Organization (FAO), food production would need to expand by almost 70% to feed the growing population. As a result, the increase in agricultural productivity is critical in ensuring high crop yields and farm profitability. The proposed work aims to design an automated, fast-processing, real-time weather monitoring system for sustainable development in smart farming against climatic action. The proposed weather monitoring system is based on IoT technology designed using proteus simulation tool which collects necessary environmental data by using a Temperature sensor (LM35), Pressure sensor (BMP180), Soil moisture sensor, Rain sensor, and Raspberry Pi (RPI3) and the data are fed to ThingSpeak platform to predict the suitable condition for crop growth and better crop yield.

We Present the sum of the Polygonal numbers of even sides are derived from Stella Octangula number and Pronic number using division algorithm.

In this chapter, the binary quadratic equation x2 - 2xy - y2 + 2x + 14y = 72 represents a hyperbola is analyzed for its non-zero distinct integer solutions. Also, we obtain a sequence of its integral solutions and present a few interesting relations among them. The recurrence relations satisfied by the solutions x and y are obtained.

Wildlife has recently become very common when it comes to inhabited areas. As humans encroach on trees, the habitat for wild animals is diminishing. When wild animals invade communities, it causes a great loss of property and lives. To build a warning system of potential animals exiting the park, this research work utilizes the newest developments in technologies such as the Internet of Things (IoT) and the notification will also be sent to Smartphone users to alert them. To do this, the low cost motion detectors and Passive Infrared sensors are used. In order to take more measures, the proposed system relay on the information about certain movements of a control room. Also, this research work involves in the creation of noisy noise by speakers in which animals are unable to reach the land. IoT's fundamental concept is to link numerous sensors and to create connectivity and to provide services as well. In this post, to build an alarm system, multiple IoT devices are utilized at the periphery of the natural reserve. This device can also be used to identify smugglers and other individuals entering the forest illegally.

"The mind is the attribute of man. When man is born, he comes into existence with only one weapon with him—the reasoning mind". Now considering the current scenario and seriousness of COVID 19, human is ready to get challenged in this crucial situation. The paper presents the proposal is to do analysis of COVID affected patients. Machine learning models help in identifying the severity and decision making. Understanding pandemic will help in implementing proper measures at right time. Implementing these measures prior to the outbreak will help maintaining country’s health and economy. Here we observe and analyze the behavior of data, which helps in providing better results for decision making. The model proposed in this paper is in adjunct with an interactive application that gives updates regarding the pandemic; indicates the different zones of the local area prescribed by the government and also serves a platform for needy.

Radiation in patients with diseases such as xeroderma pigmentosa (XP), systemic lupus erythematosus, and other connective diseases is a matter of concern because of higher incidence of toxicities. Here with, we are reporting a case of carcinoma esophagus with XP, who tolerated the treatment well with sufficiently prolonged palliation of symptoms, after treatment with external beam radiotherapy. This might be attributed to the different mechanisms of DNA damage and repair mechanisms for ultraviolet (UV) rays and X-rays. UV rays cause DNA damage by dimer formation whereas X-rays will cause single- or double-stranded breaks in DNA. The repair mechanisms for UV rays are nucleotide excision repair and translesion synthesis while for X-rays, they are base excision repair, homologous recombination, and nonhomologous end joining, and these repair mechanisms for X-rays are intact in a XP patient. Hence, they can be been treated with high dose of radiation, and they do tolerate the treatment well.

Reliable mapping of soil organic carbon (SOC) and Soil Inorganic Carbon (SIC) densities and estimates of their pool size are important from global warming perspective to understand the sequestration potential and losses. In this study, first spatially explicit mapping of SOC and SIC at 250 m resolution and an estimate of their pool size in India was undertaken using a large number of remote sensing derived data layers and data mining approach. The SOC and SIC densities up to 100 cm depth or paralithic contact (whichever is shallower) were estimated for 1198 soil samples located across India using a stratified random sampling that integrated land use, soil, topography and agro-ecological regions. Using Random forests (RF) based spatial prediction procedure with climatic, land cover, rock type, soil type, multi-year NDVI, irrigation status as independent input variables, models for predicting carbon density at 250 m spatial resolution were developed. For modelling with RF algorithm, about 898 soil profile observations (75% observations) were used, while the rest of 300 (25% of total observations) were used for validation. It was observed that the data distribution of sample points don't have significant influence on RF model predictions. The relationship between observed and predicted values was characterized by Mean Squared Deviation (MSD) and Root Mean Squared Error (RMSE) parameters. The SOC, SIC and total soil carbon pool size of India has been estimated at 22.72 ± 0.93 Pg,12.83 ± 1.35 Pg and 35.55 ± 1.87 Pg, respectively, which are comparable to previous studies while providing first spatially explicit 250 m map of their distribution. The spatial distribution indicates that majority of the carbon stock resides in the northern part of India. The soil carbon stock of eastern India has contribution from organic carbon, while the western portion has contribution mainly from inorganic carbon.

A paper-based device (PBD) for the detection of chlorpyrifos pesticide at field application was fabricated based on the principles of enzyme inhibition and image processing. Rhizopus niveus lipase, p-nitrophenol palmitate and Whatman No.1 paper were used as an enzyme, substrate and support matrix, respectively. The performance of functionalized PBD was tested for lateral flow assay reaction in pure water (negative control), artificial pesticide water (positive control) and selected fruits and vegetables wash water (test). The digital image of the PBD after the test was captured using an android smartphone and analyzed in MATLAB software. Different colour space models such as, grey, RGB, HSV and YCbCr were studied and the Cb coordinate was chosen for its higher linearity (R2 = 0.988) with pesticide concentration. Experimental variations such as paper length, relative concentration ratio of the substrate and enzyme were investigated to minimize the product cost and analysis time. The developed PBD showed a significant response over wide range of sample solution's pH and operational temperature. Further, a long-term storage stability was measured for developed PBD. The LOD and LOQ were found to be 0.065 mgL−1 and 0.198 mgL−1. The results obtained from newly developed image processing method showed 92.8% accuracy with microtiter plate assay. Higher MRL was determined in the wash water of cauliflower, grapes, coriander leaves, brinjal and bitter guard. Overall, the developed paper biosensor was precise, cost effective and most suitable for field applications.

A study was carried out by collecting soil samples from parts of Gwalior and Shivpuri district, Madhya Pradesh in order to assess the dominant clay mineral of these soils using hyperspectral data, as 0.4 to 2.5 μm spectral range provides abundant and unique information about many important earth-surface minerals. Understanding the spectral response along with the soil chemical properties can provide important clues for retrieval of mineralogical soil properties. The soil samples were collected based on stratified random sampling approach and dominant clay minerals were identified through XRD analysis. The absorption feature parameters like depth, width, area and asymmetry of the absorption peaks were derived from spectral profile of soil samples through DISPEC tool. The derived absorption feature parameters were used as inputs for modelling the dominant soil clay mineral present in the unknown samples using Random forest approach which resulted in kappa accuracy of 0.795. Besides, an attempt was made to classify the Hyperion data using Spectral Angle Mapper (SAM) algorithm with an overall accuracy of 68.43 %. Results showed that kaolinite was the dominant mineral present in the soils followed by montmorillonite in the study area.