Pretrained DcAlexnet Cardiac Diseases Classification on Cognitive Multi-Lead Ultrasound Dataset

The DcAlexNet CNN deep learning classifier can easily track patterns in medical images (brain, heart, spinal cord and etc.) precisely. According to WHO (world health organization) every year 5 billion people are affecting heart diseases and heart-attacks. Heart abnormalities sometimes tends to death; therefore, an efficient medical image pre-processor and deep learning classifier is needed for diagnosis. So that in this research work multi-class DcAlexNet classifier, RRS-HSB segment-filter has been implemented. The RRS (Restrictive Random segmentation) and GHSB (Gaussian Hue saturation brightness filtration) modules are fused to get multi-level feature. The training process has been incorporated to EchoNet dataset and testing process can be verified to real time samples. The segmented features as well as filtered feature are loaded into weighted .CSV file. The following features are classified tends to get predicting abnormalities in heart ultra sound image. The pretrained DcAlexNet CNN model is loading to EchoNet 1 lakh samples using 165 layers such as normalized layer, dense layer, flatten layer, max pooling layer and ReLu layer. The computer aided design with corresponding CNN layers has been finding hidden sample over to get heart abnormality location. The experimental results in terms of Dice score 98.89%, Accuracy 99.455, precision 99.23%, recall 98.34%, F-1 score 98.92%, CC 99.27%, and sensitivity 99.34% had been attained. The attained performance metrics are competed with present technologies and outperformance the application accuracy on heart diagnosis

Characterization of Kuttiyadi ecotype of coconut (Cocos nucifera L.) using morphological and microsatellite markers

West Coast Tall (WCT) is the most popular coconut cultivar grown by the farmers in Kerala, which occupies over 95 per cent of the area under coconut. The long history of coconut cultivation throughout Kerala state has resulted in the development of many ecotypes of WCT. The present work compares the similarity/diversity of the morphological and molecular characteristics of the Kuttiyadi ecotype growing in the hilly, midland region of Kozhikode District, Kerala with those of the WCT cultivar of the coastal region of Kasaragod District, Kerala, using vegetative, reproductive and fruit component characters and microsatellite markers. Geographically, these two locations show a wide range of variation for soil and climactic factors. The vegetative, reproductive and fruit component characteristics and microsatellite markers showed wide variations between selected WCT palms from Kasaragod and Kuttiyadi. The similarity index based on Dice’s coefficient, obtained after pair-wise comparison of Kuttiyadi and WCT samples with 15 SSR markers, revealed that the percentage similarity varied from the coefficient range 0.20 to 0.97 between the WCT and Kuttiyadi palms. UPGMA clustering clearly distinguished the two populations with WCT and Kuttiyadi forming separate clusters. STRUCTURE analysis was also carried out, which also showed that the two populations studied were distinct

Pretrained DcAlexnet Cardiac Diseases Classification on Cognitive Multi-Lead Ultrasound Dataset

The DcAlexNet CNN deep learning classifier can easily track patterns in medical images (brain, heart, spinal cord and etc.) precisely. According to WHO (world health organization) every year 5 billion people are affecting heart diseases and heart-attacks. Heart abnormalities sometimes tends to death; therefore, an efficient medical image pre-processor and deep learning classifier is needed for diagnosis. So that in this research work multi-class DcAlexNet classifier, RRS-HSB segment-filter has been implemented. The RRS (Restrictive Random segmentation) and GHSB (Gaussian Hue saturation brightness filtration) modules are fused to get multi-level feature. The training process has been incorporated to EchoNet dataset and testing process can be verified to real time samples. The segmented features as well as filtered feature are loaded into weighted .CSV file. The following features are classified tends to get predicting abnormalities in heart ultra sound image. The pretrained DcAlexNet CNN model is loading to EchoNet 1 lakh samples using 165 layers such as normalized layer, dense layer, flatten layer, max pooling layer and ReLu layer. The computer aided design with corresponding CNN layers has been finding hidden sample over to get heart abnormality location. The experimental results in terms of Dice score 98.89%, Accuracy 99.455, precision 99.23%, recall 98.34%, F-1 score 98.92%, CC 99.27%, and sensitivity 99.34% had been attained. The attained performance metrics are competed with present technologies and outperformance the application accuracy on heart diagnosis

Biology, damage potential and molecular identification of Conogethes punctiferalis Guenee in cocoa

Conogethes punctiferalis is an important polyphagous pest attacking many economically important crops. Recently, C. punctiferalis has been found to be an emerging pest in cocoa and was found to feed and bore into cocoa pods. The larvae feed on the rind of cocoa cherelles/pods, later bore into pods, feed the internal contents of the pods, the granular faecal pellets are seen outside the pods. When pods/cherelles touch each other, it is easy for the larvae to damage more than one pod/cherelle. Pods damaged by Conogethes are exposed to secondary infection by pathogens that lead to pod rot. The larvae sometimes feed on flower buds and flowers cushions. The damaged flower cushions may dry and shed prematurely. The damage of C. punctiferalis on cocoa is observed from December and peak incidence is noticed during March to May. On an average 2 per cent damage was recorded in the Central Plantation Crops Research Institute, Regional Station, Vittal. In order to develop a DNA-based molecular identification system for this species, primers were designed based on two nuclear genes viz., ribosomal protein S5 (RPS5) gene and carbamoyl phosphate synthetase/ aspartate transcarbamylase/dihydroorotase (CAD). PCR-amenable DNA was isolated from C. puntiferalis larva. The designed primers amplified single bands of expected sizes using genomic DNA as template. The amplicons were purified, cloned and sequenced and sequence analysis revealed close homology to the gene of interest from related moths

A Design of Experiments Methodology for Evaluating Configuration for a Generation Next Main Battle Tank

Combat vehicles for generation next main battle tank requires state-of-the-art technologies to counter advanced threats both from conventional and un-conventional sources across various theatres of operation. In addition, they require strategic mobility by road, rail, air and sea. Under such conditions, the trend across the world has been to converge on configurations that are lethal, agile, modular systems and interchangeable mission based turret configurations along with higher survivability which imposes limitations on mobility as mass increases. To achieve all the user objectives as laid down in the qualitative requirements, it is prudent to focus the attention on weight management. The traditional approach of weight management is time consuming, for which an alternate approach using design of experiments is proposed in this paper. To carry out this study, two configurations are selected namely evolutionary and revolutionary design. Keeping the outer boundary as the constraint, a simple linear regression and analysis of variance are carried out with mass and volume data from various systems and sub-systems. Subsequently, the accuracy of the analysis is ascertained using a test of hypothesis using PHStat software. Although this study discusses configuration, the factors responsible for reduced system mass and volume namely technology, materials, intelligence etc have not been discussed. Finally, from the outcome of the study it is observed that the revolutionary design configuration fares better compared to the evolutionary design configuration with a combat mass of only 41 t.

Characterization of gibberellin 2-oxidase isoforms in coconut (Cocos nucifera L.)

Gibberellins (GAs) are plant hormones that are essential for many developmental processes in plants, including seed germination, stem elongation, leaf expansion, trichome development, pollen maturation and the induction of flowering. Gibberellin 2-oxidase (GA2-ox) regulates plant growth by inactivating endogenous bioactive GAs through 2β-hydroxylation. There is no information about GA2-ox encoding genes or their functions in coconut. In this study, we have identified 10 transcripts encoding different isoforms of GA2-ox from coconut leaf transcriptome data. Sequence comparison and phylogenetic analysis revealed that these 10 transcripts represented different types of GA2-ox. The secondary structure, three dimensional structure and active sites of these 10 isoforms were predicted. Docking studies of different active GAs with these isoforms was also carried out

Design Configuration of a Generation Next Main Battle Tank for Future Combat

The future combat scenario will undergo a sea change as compared to the conventional and un-conventional warfare employed by the traditional armies and non-state actors. In such a scenario, the main battle tank which serves as a game changer during these conflicts has to face the dilemma whether its design should be either evolutionary or revolutionary. To determine the basis of selecting the right type of design based on the above, the broad parameters that define the configuration namely number of crew, weight, armament system, survivability, operating range, transportability, tactical mobility, trafficability, intelligence - surveillance - target acquisition - reconnaissance (ISTAR), system modularity and theatre of operation have been considered. Taking these parameters into account, this study evaluates both the evolutionary and revolutionary design configurations for a generation next main battle tank. Finally, from the outcome of this study it is observed that the revolutionary design approach not only fares better compared to the evolutionary approach, but also possess ease of adaptiveness as an universal combat weapon platform

Numerical investigation of critical range for the occurrence of secondary peaks in the Nusselt distribution curve

The study of heat transfer augmentation in micro/nano scale and electronic packaging systems are some of the paramount areas of impending universe. In such systems the cooling of the hot heat sinks is generally achieved through the impingement of air jet. In order to study the characteristic of heat dissipation rate, variation of Nusselt number versus radial distance over the target surface is investigated. The magnitude of Nusselt Number is found to decrease gradually with increase in the radial distance away from the jet. The record of Nusselt magnitude over the radial distance is accomplished through computation using ANSYS CFX 14.5. A 2-D axis-symmetric model consisting of nozzle and target surface with discrete meshing is solved using an appropriate turbulence model, in order to develop the flow regime and record the necessary heat interactions. As far as the transition and intermediacy in flow structure at the target surface due to the un-predicted transport of shear stress is concerned, SST along with Gamma – Theta turbulence model is solved simultaneously in order to incorporate these phenomena.. The occurrence of such secondary peaks increases the heat transfer rate. Looking into the light of research area in determining the exact cause and the intervening range for the occurrence of such peaks, the current research focuses over the determination of the critical range within which the secondary peaks exists. This critical range comprises of multiple of jet to the target spacing and diameter-based Reynolds number and the corresponding critical range is between 2205 and 26, 46, 000. Not only that the velocity contour of the flow regime is mapped for the sets of parameters within the critical range. An empirical correlation for the area averaged Nusselt number terms of Reynolds number and jet to the target spacing being is proposed. This correlation improvises the calculation of the magnitude of area

CD44 mediates stem cell mobilization to damaged lung its novel transcriptional targets, Cortactin and Survivin

Beyond their role in bone and lung homeostasis, mesenchymal stem cells (MSCs) are becoming popular in cell therapy. Various insults may disrupt the repair mechanisms involving MSCs. One such insult is smoking, which is a major risk factor for osteoporosis and respiratory diseases. Upon cigarette smoke-induced damage, a series of reparatory mechanisms ensue; one such mechanism involves Glycosaminoglycans (GAG). One of these GAGs, namely hyaluronic acid (HA), serves as a potential therapeutic target in lung injury. However, much of its mechanisms of action through its major receptor CD44 remains unexplored. Our previous studies have identified and functionally validated that both cortactin (CTTN: marker of motility) and Survivin (BIRC5: required for cell survival) act as novel HA/CD44-downstream transcriptional targets underpinning cell motility. Here, human MSCs were treated with "" smoke to investigate the effects of cigarette smoke condensate (CSC) on these HA-CD44 novel signaling pathways. Our results show that CSC decreased the expression of both CD44 and its downstream targets CTTN and BIRC5 in MSCs, and that HA reversed these effects. Interestingly, CSC inhibited migration and invasion of MSCs upon CD44-targeted RNAi treatment. This shows the importance of CD44-HA/CTTN and CD44-HA/BIRC5 signaling pathways in MSC motility, and further suggests that these signaling pathways may provide a novel mechanism implicated in migration of MSCs during repair of lung tissue injury. These findings suggest that one should use caution before utilizing MSC from donors with history of smoking, and further pave the way towards the development of targeted therapeutic approaches against CD44-associated diseases