Modelling of Hybrid Meta heuristic Based Parameter Optimizers with Deep Convolutional Neural Network for Mammogram Cancer Detection

Breast cancer (BC) is the common type of cancer among females. Mortality from BC could be decreased by identifying and diagnosing it atan earlierphase. Different imaging modalities are used to detect BC, like mammography. Even withproven records as a BC screening tool, mammography istime-consuming and hasconstraints, namely lower sensitivity in women with dense breast tissue. Computer-Aided Diagnosis or Detection (CAD) system assistsaproficient radiologist to identifyBC at an earlier stage. Recently, the advancementin deep learning (DL)methodsareemployed to mammography assist radiologists to increase accuracy and efficiency. Therefore, this study presents a metaheuristic-based hyperparameter optimization with deep learning-based breast cancer detection on mammogram images (MHODL-BCDMI) technique. The presented MHODL-BCDMI technique mainly focused on the recognition and classification of breast cancer on digital mammograms. To achieve this, the MHODL-BCDMI technique employs pre-processing in two stages: Wiener Filter (WF) based noise elimination and contrast enhancement. Besides, the MHODL-BCDMI technique exploits densely connected networks (DenseNet201) model for feature extraction purposes. For BC classification and detection, a hybrid convolutional neural network with a gated recurrent unit (HCNN-GRU) model is used. Furthermore, three hyperparameter optimizers are employed namely cat swarm optimization (CSO), harmony search algorithm (HSA), and hybrid grey wolf whale optimization algorithm (HGWWOA). Finally, the U2Net segmentation approach is used for the classification of benign and malignant types of cancer. The experimental analysis of the MHODL-BCDMI method is tested on a digital mammogram image dataset and the outcomes are assessed in terms of diverse metrics. The simulation results highlighted the enhanced cancer detection performance of the MHODL-BCDMI technique over other recent algorithms

VALIDATED SPECTROPHOTOMETRIC METHOD FOR THE DETERMINATION OF CHLORAMPHENICOL IN PURE AND IN ITS DOSAGE FORM

Objective: A simple, economic, selective, precise, and accurate UV-Visible spectrophotometric method for the analysis of Chloramphenicol in bulk drug and pharmaceutical formulations was developed and validated in the present study. Methods: Based on oxidative coupling reaction with MBTH reagent at PH-4.5 which is extractable at 620 nm. The Beer's law is obeyed in the concentration range 1-6 ml (10-60 µg ml-1). Results: The RSD was found to be 0.0194% and recovery is 99.73%. The method was completely validated and proven to be rugged. The interferences of the ingredients and recipients were not observed. The repeatability and the performance of the proved method were established by point and internal hypothesis and through recovery studies. Conclusion: The method was found to be accurate and precise, as indicated by recovery studies close to 100 and % RSD is not more than 2. The summery of validation parameters of proposed UV-Visible method is given

VALIDATED SPECTROPHOTOMETRIC METHOD FOR THE DETERMINATION OF CHLORAMPHENICOL IN PURE AND IN ITS DOSAGE FORM

A simple, précis, rapid sensitive and accurate spectrophotometric methods have been developed for the estimation of Chloramphenicol UV in pure form and its pharmaceutical formulations based on oxidative coupling reaction UV with MBTH reagent at P H-4 which is extractable at 620 nm. Beer's law is obeyed in the concentration range 1-6 ml (10-60 µgml-1). The developed method was applied directly and easily for the analysis of the pharmaceutical formulations. RSD was found to be 0.0194 % and recovery 99.73%. The method was completely validated and proven to be rugged. The interferences of the ingredients and excipients were not observed. The repeatability and the performance of the proved method were established by point and internal hypothesis and through recovery studies.Keywords: Spectrophotometry, Chloramphenicol, MBTH, Oxidative coupling

Leverage web analytics for real time website browsing recommendations

Trabalho apresentado no 5th World Conference on Information Systems and Technologies (WorldCIST’17), 11-13 de abril 2017, Porto Santo, Madeira PortugalAs a websites’ structure grow it is paramount to accommodate the alignment of user needs and experience with the overall websites’ purposes. Toward this requirement, the proposed website navigation recommendation system suggests to users, pages that might be of her interest based on past successful navigation patterns of overall site’s usage. Most of existing recommendation systems adopts traditionally one of the web mining branches. We take a different stance, on web mining usage, and alternatively considered the real time enactment of web analytic tools supported analysis given their current maturity and affordances. On this basis we provide a model, its implementation and evaluation for navigation based recommendations generation and delivery. The developed prototype adopted a SaaS orientation to promote the underlying functionalities integration within any website. Preliminary evaluation’s results seem to favor the validation of the present contribution rational.N/

A Machine learning Classification approach for detection of Covid 19 using CT images

Coronavirus disease 2019 popularly known as COVID 19 was first found in Wuhan, China in December 2019. World Health Organization declared Covid 19 as a transmission disease. The symptoms were cough, loss of taste, fever, tiredness, respiratory problem. These symptoms were likely to show within 11 –14 days. The RT-PCR and rapid antigen biochemical tests were done for the detection of COVID 19. In addition to biochemical tests, X-Ray and Computed Tomography (CT) images are used for the minute details of the severity of the disease. To enhance efficiency and accuracy of analysis/detection of COVID images and to reduce of doctors' time for analysis could be addressed through Artificial Intelligence. The dataset from Kaggle was utilized to analyze. The statistical and GLCM features were extracted from CT images for the classification of COVID and NON-COVID instances in this study. CT images were used to extract statistical and GLCM features for categorization. In the proposed/prototype model, we achieved the classification accuracy of 91%, and 94.5% using SVM and Random Forest respectively

OCHRATOXIN A AND CITRININ INDUCED PATHOMORPHOLOGICAL CHANGES IN BROILER CHICKEN

ABSTRACT The study was undertaken to evaluate the effect of feeding ochratoxin A and citrinin either alone or in combination in broiler chicken. Two hundred broiler chicks were divided into four groups of 50 chicks each with the following treatment viz. Control diet, (group I), OA 1 ppm, (group II), CTN 12.5 ppm (group III) and combination 1 ppm OA plus 12.5 ppm CTN (group IV) up to 35 days of the trial. The experimental and the control birds were sequentially sacrificed and examined at 7, 14, 21, 28 and 35 th day of the experiment. On post-mortem examination grossly, the toxin fed birds showed congestion, enlargement, pallor or yellowish discoloration of liver with distended gall bladder, swollen and congested kidneys. In addition, congestion of heart with prominent vasculature, pale, dehydrated and shrunken skeletal muscles, presence of small quantity of semisolid ingesta with slight mucous in crop and proventriculous, dry and shrunken gizzard, congested appearance of intestine with small quantity of mucous and congested pancreas was observed in all the toxin fed groups throughout the period of experimentation. Microscopically degenerative changes in hepatocytes, periportal fibrosis, periductular mononuclear cell infiltration, fatty degeneration, focal necrosis in the liver, degeneration and necrotic changes in the tubular epithelial cells in kidneys, myocardial degeneration, hyaline degeneration of muscle, mucosal hyperplasia of crop, proventriculitis, ventriculitis, catarrhal enteritis, pancreatitis, lymphoid depletion in the spleen, bursa of Fabricius and thymus were the prominent lesions observed when both the toxins were fed to birds from second to fifth week of age. Severity of these lesions was found to be enhanced and suggested the additive or synergistic effect of these toxins in the broiler chicken

Antidiabetic and renoprotective effects of the chloroform extract of Terminalia chebula Retz. seeds in streptozotocin-induced diabetic rats

BACKGROUND: Terminalia chebula (Combretaceae) has been widely used in Ayurveda for the treatment of diabetes. In the present investigation, the chloroform extract of T. chebula seed powder was investigated for its antidiabetic activity in streptozotocin-induced diabetic rats using short term and long term study protocols. The efficacy of the extract was also evaluated for protection of renal functions in diabetic rats. METHODS: The blood glucose lowering activity of the chloroform extract was determined in streptozotocin-induced (75 mg/kg, i.p.; dissolved in 0.1 M acetate buffer; pH 4.5) diabetic rats, after oral administration at the doses of 100, 200 and 300 mg/kg in short term study. Blood samples were collected from the eye retro-orbital plexus of rats before and also at 0.5, 1, 2, 4, 6, 8 and 12 h after drug administration and the samples were analyzed for blood glucose by using glucose-oxidase/peroxidase method using a visible spectrophotometer. In long term study, the extract (300 mg/kg) was administered to streptozotocin-induced diabetic rats, daily for 8 weeks. Blood glucose was measured at weekly intervals for 4 weeks. Urine samples were collected before the induction of diabetes and at the end of 8 weeks of treatments and analyzed for urinary protein, albumin and creatinine levels. The data was compared statistically using one-way ANOVA with post-hoc Dunnet's t-test. RESULTS: The chloroform extract of T. chebula seeds produced dose-dependent reduction in blood glucose of diabetic rats and comparable with that of standard drug, glibenclamide in short term study. It also produced significant reduction in blood glucose in long term study. Significant renoprotective activity is observed in T. chebula treated rats. The results indicate a prolonged action in reduction of blood glucose by T. chebula and is probably mediated through enhanced secretion of insulin from the β-cells of Langerhans or through extra pancreatic mechanism. The probable mechanism of potent renoprotective actions of T. chebula has to be evaluated. CONCLUSION: The present studies clearly indicated a significant antidiabetic and renoprotective effects with the chloroform extract of T. chebula and lend support for its traditional usage. Further investigations on identification of the active principles and their mode of action are needed to unravel the molecular mechanisms involved in the observed effects

Policy of foreign direct investment liberalisation in India: implications for retail sector

This study has analysed the impact of liberalisation of Indian economy and FDI policy on the retail sector since its implementation in the 1990s. It also further analyses sub-categories by investigating its impact on the unorganised retail sector and the flow of FDI in single-brand retail and multi-brand retail sectors. A comprehensive and critical review of the existing evidence on the subject was carried out, and descriptive statistical analysis of data from 1991 to 2013 was performed which leads to conclude that the policy of FDI liberalisation has proved to provide diversification and sustainable development to the Indian economy and specifically retail sector which is considered to be one of the significant pillars of economy. Furthermore, for continuous growth of the economy, it seems vital to encourage more investment in other sectors by liberalising the restrictive policies

Poly-β-hydroxybutyrate administration during early life: effects on performance, immunity and microbial community of European sea bass yolk-sac larvae

The reliable production of marine fish larvae is one of the major bottlenecks in aquaculture due to high mortalities mainly caused by infectious diseases. To evaluate if the compound poly-β-hydroxybutyrate (PHB) might be a suitable immunoprophylactic measure in fish larviculture, its capacity to improve immunity and performance in European sea bass (Dicentrarchus labrax) yolk-sac larvae was explored. PHB was applied from mouth opening onwards to stimulate the developing larval immune system at the earliest possible point in time. Larval survival, growth, microbiota composition, gene expression profiles and disease resistance were assessed. PHB administration improved larval survival and, furthermore, altered the larva-associated microbiota composition. The bacterial challenge test using pathogenic Vibrio anguillarum revealed that the larval disease resistance was not influenced by PHB. The expression profiles of 26 genes involved e.g. in the immune response showed that PHB affected the expression of the antimicrobial peptides ferritin (fer) and dicentracin (dic), however, the response to PHB was inconsistent and weaker than previously demonstrated for sea bass post-larvae. Hence, the present study highlights the need for more research focusing on the immunostimulation of different early developmental stages for gaining a more comprehensive picture and advancing a sustainable production of high quality fry