A comparative study of oral iron and intravenous iron in iron deficient antenatal mothers

Background: The aim of the study is to compare the efficacy, tolerance and compliance between oral iron and intravenous infusion of iron in iron deficient antenatal mother.Methods: This is a prospective randomised clinical and interventional study in the department of Obstetrics and Gynaecology in Vinayaka Mission Kirupananda Variyar Medical College and Hospital. The antenatal women attending the antenatal op were screened for Hb status. Those antenatal women of gestational age 16-34 weeks with Hb level between 7-10g% and diagnosed to have iron deficiency anemia by peripheral smear and serum ferritin were included in this study after getting informed consent. The total numbers of 100 mothers were allotted into two major groups, group A and group B of 50 subjects each. Group A: 50 pregnant women given oral iron supplementation (carbonyl iron 100 mg twice a day). Group B: 50 pregnant women given intravenous iron sucrose therapy after calculating the total iron requirement. The rise in hemoglobin in both the groups were comparedResults: In this study the mean rise of hemoglobin in carbonyl iron was 0.914±0.20 gm% whereas in iron sucrose group was 2.43±0.20gm%. This showed that iron sucrose (i.v) had better rise in Hb than carbonyl iron (oral).Conclusions: The present study revealed that intravenous iron sucrose therapy was bettertolerated with higher increase in mean haemoglobin compared to oral iron therapy. There were no serious side effects with intravenous iron sucrose therapy. Intravenous iron sucrose is a good substitute to oral iron therapy in moderate anaemia

Performance Evaluation of Face Recognition Algorithms

Biometric - based techniques have emerged for recognizing individuals instead of using passwords, PINs, smart cards, plastic cards, tokens etc fo r authenticating people . Automated face recognition has become a major field of interest. In this field several facial recognition algorithms have been explored in the past few decades . A face recognition system is expected to identify faces present in images and videos automatically. The input to the facial recognition system is a two dimensional image, while the system distinguishes the input image as a users face from a pre - determined library of faces. Finally, the output is a discerned face image. This paper deals wi th the comparison of two popular dimensionality reduction algorithms such as PCA and LDA. Here, our main goal is to evaluate the performance of Principal Component Analysis and Linear Discriminant Analysis for large training data set. Finally, we concluded that LDA outperforms PCA for the large samples of training set

Automatic Bleeding Frame and Region Detection for GLCM Using Artificial Neural Network

 Wireless capsule endoscopy is a device that inspects the direct visualization of patient’s gastrointestinal tract without invasiveness. Analyzing the WCE video is a time- consuming task hence computer aided technique is used to reduce the burden of medical clinicians. This paper proposes a novel color feature extraction method to detect the bleeding frame. First, we perform word based histogram for rapid bleeding detection in WCE images. Classification of bleeding WCE frame is performed by applying for glcm using  Artificial Neural Network and K-nearest neighbour method. Second we propose a two-stage saliency map extraction method. In first stage saliency, we inspect the bleeding images under different color components to highlight the bleeding regions. From second stage saliency red color in the bleeding frame reveals that the region is affected. Then, by using algorithm we fuse the two-stage of saliency to detect the bleeding area. Experimental results show that the proposed method is very efficient in detecting the bleeding frames and the region

Pharmacognostic, Phytochemical and Pharmacological Evaluation of the Leaves of Phyllanthus Acidus(L.)Skeels(Euphorbiaceae).

Herbal medicine are being used by about 80% of the world population primarily in the developing countries for primary health care. They have stood the test for their safety, efficacy, cultural acceptability and lesser side effects. The chemical constituents present in them are a part of physiological functions of living flora and hence they are believed to have better compatibility with the human body. Ancient literature also mentions herbal medicines for age-related disease namely memory loss, osteoporosis, diabetic wounds, immune and liver disorders. The active principles responsible for liver cancer may be isolated and evaluated for this activity cancer studies using different animal model.This extract and the isolated active principles may be formulated in suitable dosage form and they may be launched in the market. These herbal formulations will be beneficial to the liver cancer patients those who are not affordable to treat with allopathic chemotherapeutic agents. Sorafenib is the only drug which is used for the chemotherapy of liver cancer

A Study on ‘hs C Reactive Protein’ as Predictive Marker of Cardiovascular Events in Diabetic Renal Disease Patients

INTRODUCTION : A decade ago, the treatment of hypercholesterolemia and Hypertension was expected to eliminate CAD by the end of the 20th century. Lately, however, that optimistic prediction has needed revision. Cardiovascular diseases are expected to be the main cause of death globally Within the next 15 years owing to a rapidly increasing prevalence in Developing countries and Eastern Europe and the rising incidence of obesity, Diabetes and Diabetes related complication like chronic kidney disease (CKD) in both the developing world and the Western world. Cardiovascular diseases cause 38 percent of all deaths in North America and are the most common cause of death in European men under 65 Years of age and the second most common cause in women. These facts force us to revisit cardiovascular disease and consider new strategies for prediction, prevention, and treatment. AIM : We set out to investigate the hypothesis that elevated C-reactive protein (CRP) levels a marker of an (altered immune response) inflammation, would correlate with coronary artery disease in patients with diabetic chronic renal disease. MATERIAL AND METHODS : This study is of Observational Study Design. Inclusive of a total 50 patients. Between 2004 – 2006 at P.S.G. Institute of Medical Sciences and Research. Inclusion Criteria: Patients with Stage 1 to stage 3 chronic kidney disease (according to NKF- DOQI Guidelines)of Diabetic etiology. Diabetes mellitus both type 1 and type 2. Exclusion Criteria: • Advanced stages of renal disease. • Congestive cardiac failure. • Hypoproteinemia. • Inter current infection in the past 3 weeks. • Connective tissue disorder. RESULTS : Characteristics of the Cases and their Relationship with Cardiovascular Events. There is no statistically significant between the mean age of patients with cardiovascular events and normal cases. DISSCUSSION : 1. Our data suggest that the elevated C-reactive protein level is a predictor of cardiovascular events in Diabetic Renal Disease population. Unlike other markers of inflammation (ICAM, IL-6etc), C-reactive protein levels are stable over long periods, have no diurnal variation, can be measured inexpensively with available high-sensitivity assays, and have shown specificity in terms of predicting the risk of cardiovascular disease. 2. C-reactive protein is a stronger predicter of cardiovascular events than the LDL cholesterol level. The same was suggested by Paul M Ridker and Co-workers and several other workers also and our study demonstrates the same observation(33).THE addition of crp to standard cholesterol evaluation may thus provide a effective and inexpensive and non invasive method to improve clobal risk prediction and compliance with approaches. 3. Tighter glycemic controls are associated with better cardiovascular outcomes. CONCLUSION : CRP level is independently associated with Coronary artery disease in our study group of Diabetic CKD patients and is useful predictive marker for Cardiovascular events (IHD)in the study population

Revelation of Significant Fake Rhetorical in Wrapping Bygone Utilizing Significant Learning Procedures

The developing computation control has made the profound learning calculations so powerful that making an unclear human synthesized video famously called a profound fake has got to be exceptionally straightforward. Scenarios where these practical confront swapped profound fakes are utilized to form political trouble, fake psychological warfare occasions, vindicate porn, and shakedown people groups are effortlessly imagined. In this work, we depict a modern profound learning-based strategy that can viably recognize AI-generated fake recordings from genuine videos. Our strategy can naturally be recognizing the substitution and reenactment of deep fakes. We are attempting to utilize Manufactured Intelligence (AI) to battle Fake Intelligence(AI). Our framework uses a res-next neural convolution system to extract frame-level highlights and promote the use of these highlights to prepare the long-term memory (LSTM)-based repetitive neural network (RNN) to classify whether the video is subject to art. control or not , i.e whether the video is profoundly fake or genuine. To imitate the genuine time scenarios and make the show perform way better on genuine time information, we assess our strategy on an expansive sum of adjusted and blended data-set arranged by blending the different accessible data-set like Face-Forensic, Deep Fake location challenge, and Celeb-DF. We moreover focus on  how our framework can accomplish competitive results utilizing exceptionally straightforward and strong approaches

Study on the reproductive behavior among women of rural areas of Pondicherry

Background: The fertility rate in India is declining and it is necessary to know the factors responsible for such decline in different states. It was decided to study reproductive behavior of women contributing to decline in fertility in Pondicherry. The aim and objective of this study is known the reproductive behavior of women in the rural areas on Pondicherry.Methods: Sample of 300 married women aged between 30 and 60 years were selected randomly from village belonging to Katerikuppam PHC and the data collected using the pre tested semi open ended questionnaires by interviewing the subjects at their doorsteps during September to November 2014.Results: The mean age of the subjects was 41.5 ± 9.5 years. There were 793 total pregnancies and live births were 701 and abortions accounted for ten percent and still births were 9 in number. The mean number of pregnancies and live births were 2.6 ± 1.1 and 2.3 ± 1.0 per women respectively. The mean age at menarche, marriage and first pregnancy were 14.3 ± 1.4, 19.6 ± 3.1 and 21.1 ± 3.1 years respectively. The mean number of pregnancies were declined from currently older age to the lower age of the subjects and found to be statistically significant.Conclusions: The mean age at marriage and first pregnancy is increasing and the differences in the mean number of pregnancies and live births are showing declining trend.

Naïve Bayesian Classification Based Glioma Brain Tumor Segmentation Using Grey Level Co-occurrence Matrix Method

Brain tumors vary widely in size and form, making detection and diagnosis difficult. This study's main aim is to identify abnormal brain images., classify them from normal brain images, and then segment the tumor areas from the categorised brain images. In this study, we offer a technique based on the Nave Bayesian classification approach that can efficiently identify and segment brain tumors. Noises are identified and filtered out during the preprocessing phase of tumor identification. After preprocessing the brain image, GLCM and probabilistic properties are extracted. Naive Bayesian classifier is then used to train and label the retrieved features. When the tumors in a brain picture have been categorised, the watershed segmentation approach is used to isolate the tumors. This paper's brain pictures are from the BRATS 2015 data collection. The suggested approach has a classification rate of 99.2% for MR pictures of normal brain tissue and a rate of 97.3% for MR images of aberrant Glioma brain tissue. In this study, we provide a strategy for detecting and segmenting tumors that has a 97.54% Probability of Detection (POD), a 92.18% Probability of False Detection (POFD), a 98.17% Critical Success Index (CSI), and a 98.55% Percentage of Corrects (PC). The recommended Glioma brain tumour detection technique outperforms existing state-of-the-art approaches in POD, POFD, CSI, and PC because it can identify tumour locations in abnormal brain images

Electricity Low Tension Analysis Using ETAP

ABSTRACT-One of a utility's core responsibilities is to deliver the voltage to customers within a suitable range. The main aim of our project is to deliver the voltage to consumers within the limit. When the load is increased on the secondary side of the distribution transformer, the fuse will often get tripped, efficiency of the transformer will be reduced and very important is that the consumer will get a reduced voltage below the suitable range. In order to overcome this we are using a parallel operation on distribution transformers because by using parallel operations when the load is increased on the LT side, the additional transformer will supply a required power to consumers for the consumer's satisfaction. Here we are using software called Electrical Transient Analyzer Programming (ETAP) for the purpose of analyzing and monitoring the LT parameters of distribution transformer. By using this software we can analyze and measure the current, voltage and frequency at each and every line