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Pneumonia disease is caused by viruses and bacteria which affect one or both lungs. It is the most dangerous disease that causes huge cancer death worldwide. Early detection of Pneumonia is the only way to improve a patient’s chance for survival. We can detect this disease from X-ray or Computed Tomography (CT) lung images using Deep Learning Techniques. This research paper provides a solution to medical practitioners in predicting the impact of virus as high-risk, low-risk and medium-risk among the population being tested through various Deep Learning techniques such as Convolutional Neural Networks (CNN), Artificial Neural Network (ANN) and Recurrent Neural Networks (RNN) using Long Short Term Memory (LSTM) cells. We observed 3000 CT images of Pneumonia confirmed patients and achieved the accuracy resulting 98–99%. The performance of the classifiers are evaluated using parameters such as confusion matrix, accuracy, F-measure, precision and Recall. The results proves that deep learning afford a fitting tool for fast screening of Pneumonia and discovering high-risk patients and preventing them by providing suitable medical remedies.

One of the most often utilized signals for assessing the electrical activities of the brain is the Electroencephalograph (EEG) signal. The manual approach of determining epileptic irregularities is time-consuming, and the outcome may vary depending on the reader's level of expertise. In order to identify seizures from EEG signals, this research introduces a unique computer-aided approach that uses hybrid machine learning techniques. Discrete Wavelet Transform is used to extract features from the signals (DWT). A classifier is utilized to distinguish between the normal and seizure classes using a mix of the Self Organizing Neural Network (SONN) and Multilayer Perceptron (MLP) method. The performance of the suggested strategy produced a 99.8 % accuracy.

Twenty surface soil samples were collected from different paddy fields of thoubal district, Manipur to determine status and different forms of zinc in the soils. All the soil samples were acidic in nature with mean value of pH 5.49. The mean value of electrical conductivity was 0.07 dSm-1. The mean value of organic carbon was 2.13%. The mean cation exchange capacity, available nitrogen, available phosphorus and available potassium were 17.37 [cmol(p+)kg-1], 315.16 kg ha-1, 26.39 kg ha-1 and 240.11 kg ha-1 respectively. The studied soils were fine-textured that is clay in the textural class. The mean value of available (DTPA extractable) zinc was 0.82 mg kg-1. The DTPA extractable zinc show positive and significant correlation with CEC. A negative and significant correlation was observed with pH. On the basis of average concentration, the distribution of zinc in the soil order was: WSEX-Zn (0.38 mg kg-1) < CRYOX-Zn (1.31 mg kg-1) < MnOX-Zn (1.95 mg kg-1) < AMOX-Zn (3.04 mg kg-1) < OCx-Zn (3.16 mg kg-1) < Res-Zn (82.79 mg kg-1). All the zinc fractions showed positive correlation with EC, OC, CEC, available nitrogen, available potassium, clay; and negative correlation with pH and available phosphorus. WSEX-Zn and Res-Zn showed the lowest and highest concentration among the all zinc fractions, respectively. Different zinc fractions were found to be correlated to eachother, suggesting the dynamic nature of the equilibrium existing between them. The highest correlation among zinc fractions was found between residual and total zinc indicating the dependence of these forms on each other.

A field investigation was carried out during kharif seasons of 2016 and 2017 at research farm of College of Agriculture, Central Agricultural University, Imphal, to study the influence of integrated nutrient management on dry matter production, yield and NPK content of transplanted rice. The treatments were laid out in a randomized block design and replicated thrice using the rice variety (CAU-R1). Among the different treatments, higher dry matter production and N content in rice were found significantly in T8 (100% RDN from urea + 10 tonnes Azolla ha-1) on 30th, 60th and 90th DAT. At harvest, significantly higher content of N in grain was observed in T10 (75% RDN from urea + 25% RDN from FYM + 10 tonnes Azolla ha-1) while treatments T8 and T10 showed the similar effect in straw N content. However, statistically higher P concentration was recorded in T11 (50% RDN from urea + 50% RDN from FYM + 10 tonnes Azolla ha-1) throughout the growing period and also in grain and straw at harvest time. T12 (25% RDN from urea + 75% RDN from FYM + 10 tonnes Azolla ha-1) noted the highest K concentration in grain followed by T11 while K content in straw was highest in both the treatments T11 andT12. In contrary to P content, the K content recorded in grain was low under different treatments. Critical analysis of the pooled data showed that soil treated with 75% RDN from urea + 25% RDN from FYM + 10 tonnes Azolla ha-1(T10) yielded significantly higher grain and straw yield of rice.

The critical limit of nitrogen in soil and plant (CAU R-1) was determined through a pot culture experiment with twenty five soils of Imphal West district of Manipur, India for predicting the response of rice to nitrogen application. All the soil samples were clayey in texture and acidic in reaction with the mean pH value of 5.16, electrical conductivity ranged from 0.06 to 0.14 dSm-1 with an average of 0.1 dSm-1, organic carbon content from 1.06 to 2.62 % with mean value of 2.03%, cation exchange capacity of the soils from 12.20 to 20.20 meq/100g with mean value of 16.06 meq/100g. Available nitrogen content in soils varied from 185.00 to 331.06 kg N/ha with an average value of 267.24 kg N/ha. Available nitrogen in the soils was positively and significantly correlated with plant N content (r=0.653**), dry matter yield (r=0.556**), plant N uptake (r=0.726**) in control pots. There was also a positive and significant correlation between available N and bray’s per cent yield (r = 0.519**). The critical limit of available N was established at 257 kg N/ha for soil and 1.04 % for 45 days old rice plants. Soil containing N below this critical limit may respond economically to N fertilization for growing rice.

The genetic variability of ‘Candidatus Liberibacter asiaticus’ (CLas) population associated with huanglongbing (HLB) disease of citrus in North Eastern (NE) region of India, a geographically locked region, and home for the diversity of many citrus species was analyzed on the basis of tandem repeat numbers (TRN) in variable CLIBASIA_01645 genomic loci. Fifty-five CLas strains sampled from different groves of NE Hill (NEH) region of India were in single amplicon group, but there was remarkable genetic variability in TRNs. The TRN in HLB-associated CLas strains varied from 0-21 and two novel repeat motifs were also identified. Among the NE population of CLas, TRN5 and TRN9 were most frequent (total frequency of 36.36%) followed by TRN4 (14.55%) and TRN6, TNR7 with a frequency of 12.73% each. Class II type CLas genotypes (5 < TRN ≤ 10) had highest prevalence (frequency of 60.00%) in the samples characterized in present study. Class I (TRN ≤ 5) genotypes were second highest prevalent (29.09%) in the NEH region. Further analysis of genetic diversity parameters using Nei's measure (H value) indicated wide genetic diversity in the CLas strains of NE India (H value of 0.58-0.86). Manipur CLas strains had highest genetic variability (0.86) as compared to Eastern, Southern and Central India. The R10 values (TRN ≤ 10/TRN > 10) of NE CLas population was 10.43 (73/7), higher from other regions of India. Present study conclusively reported the occurrence of high genetic variability in TRN of CLas population in North East Indian citrus groves which have evolved to adapt to the specific ecological niche.

While conventional cleaning to remove the coating from plasma chamber walls becomes essential to reproduce the desired materials on the target substrate for widespread applications, an attention towards wall-deposited materials is scarce. Recycling those waste materials to value-added product is of great importance for sustainable progress of our modern society. Herein, we investigated the materials deposited on the wall of plasma chamber, explored their promising features and compared them with conventionally grown materials. A mixture of ZnO and α-Fe2O3 (ZF) exposed to high energy plasma was collected from the wall (ZF-W) and also from the substrate (ZF-S) to check the feasibility of providing same quality products. With same lattice constant of hematite, magnetite and zinc ferrites, ZF-W differs from ZF-S in coercivity, saturation magnetization, ferromagnetic stoichiometry and defects. In addition, degradation of Methyl Blue (MB) dye in ZF-W without use of any external light sources are comparable, more stable and durable in comparison to ZF-S. The slight differences obtained in the property-performances between ZF-W and ZF-S are attributed to the cationic arrangement and the oxygen vacancy defects present in the structure. The study reflects the potentiality of ZF-W as a promising active material for wastewater treatment just as one can use ZF-S. These findings clearly depict that the unused products with altered intrinsic properties obtained after plasma treatment has similar or even better potential to its actual targeted product and thus can be utilized properly thereby saving cost and time and, hence generates an unexplored direction for the materials science community.

Background: Accurate determination of the working length of root canals is an important factor for the success of endodontic therapy. Aim: Two different apex locators namely Propex Pixi (Dentsply) and Canal Pro (Coltene) are used to determine the working length of root canals and their results are compared to determine their accuracy. Material and Methods: Twenty extracted permanent single-rooted teeth are used for the study. To determine the working length of root canals of each tooth, two different types of electronic apex locators, Propex Pixi (Dentsply) and CanalPro (Coltene) are used and their results are compared. Result: There was a significant difference in accuracy between the two apex locators in determining the working length of root canals (p-value

Manipuri traditional game Kei-Yen, which originates from the ancient Meitei mythological story, is a mind game between two players of different mindsets, one has the mindset of killing (Kei), whereas the other (Yen) has the mindset of protecting itself and block the moves of Kei. We propose and develop an algorithm of this game by incorporating various possible logical tactics and strategies for a possible computer software of this game. Since this game involves various logical mind games, playing this game can improve our way of thinking, strategies, tricks and other skills related to mind game. In this play there is not the case of draw which means one has to win over the other at the end of the game. This game could become one of most interesting indoor national or international game.

In ours paper, we have developed a Mamdani Fuzzy interference system in MATLAB R2014a for mobile robot navigation in static environment. Inputs of the fuzzy inference system are the angle between the robot orientation and the robot target orientation (i.e. robot rotation angle) and the distance measured by the ultrasonic sensor from the obstacle to the orientation. The robot can reach the target with less bending energy, minimum time and shortest path with obstacle avoidance in static environment. The proposed system takes minimum inputs and rules to avoid the clustered obstacles in the static environments. It also calculate the angular velocities of two wheels of the mobile robot. The efficiency of the proposed method is verified by the simulation and experimental results.

Understanding the microscopic origin of physical properties is fundamental to the study of glasses. In the present study, unique trends were observed in structural and dynamical properties in lead-borate [xPbO:(1-x)B2O3] glasses upon increasing the modifier. Properties driven by short-range structural changes like, glass transition temperature (Tg) and elastic modulii exhibit a broad maxima around x = 0.3, in congruence with the average coordination number . Using Raman spectroscopy, this behaviour is attributed to the gradual conversion of three-coordinate (B3) to four-coordinate (B4) boron species. However, dynamic properties like the Boson peak and fragility behave similar to the above structural properties except an anomalous dip at x = 0.3. The corresponding dynamic correlation length, therefore, exhibits a decrease except a peak at x = 0.3 with increasing x. The static correlation lengths estimated from the first sharp diffraction peak (FSDP), did not follow a linear trend with the dynamic correlation lengths, indicating a different spatial origin. The analysis of the Boson peak and FSDP suggests that while the Boson peak arises from intermediate-range ordering within the network units, the FSDP arises due to ordering of voids between such units. Moreover, the Boson peak maximum showed a linear decrease with increasing , while the Boson peak position and fragility were found to vary linearly. These correlations emerge from the evolution of the network packing and connectivity with the addition of modifier and changing role of lead oxide as a glass former at higher concentrations. The anomalous variation in dynamical properties reflects the critical role of Pb2+ in tuning the intermediate-range structure of the vitreous network.

Mycobacterium tuberculosis causes tuberculosis in humans and predominantly infects alveolar macrophages. To survive inside host lesions and to evade immune surveillance, this pathogen has developed many strategies. For example, M. tuberculosis uses host-derived lipids/fatty acids as nutrients for prolonged persistence within hypoxic host microenvironments. M. tuberculosis imports these metabolites through its respective transporters, and in the case of host fatty acids, a pertinent question arises: does M. tuberculosis have the enzyme(s) for cleavage of fatty acids from host lipids? We show herein that a previously uncharacterized membrane-associated M. tuberculosis protein encoded by Rv2672 is conserved exclusively in actinomycetes, exhibits both lipase and protease activities, is secreted into macrophages, and catalyzes host lipid hydrolysis. In light of these functions, we annotated Rv2672 as mycobacterial secreted hydrolase 1 (Msh1). Furthermore, we found that this enzyme is up-regulated both in an in vitro model of hypoxic stress and in a mouse model of M. tuberculosis infection, suggesting that the pathogen requires Msh1 under hypoxic conditions. Silencing Msh1 expression compromised the ability of M. tuberculosis to proliferate inside lipid-rich foamy macrophages but not under regular culture conditions in vitro, underscoring Msh1's importance for M. tuberculosis persistence in lipid-rich microenvironments. Of note, this is the first report providing insight into the mechanism of host lipid catabolism by an M. tuberculosis enzyme, augmenting our current understanding of how M. tuberculosis meets its nutrient requirements under hypoxic conditions.