Prospective observational study to evaluate the efficacy of labetalol versus nifedipine in the management of preeclampsia

Background: Hypertensive disorders of pregnancy are the common medical disorders in pregnancy. It has effects both on expectant mother and fetus. Pre-eclampsia is a pregnancy specific multisystem disorder of unknown etiology, and accounts for 12-18% of maternal mortality. There is general consensus that maternal risk is decreased by antihypertensive treatment that lowers very high blood pressure. Objective of this study was to study the efficacy of oral labetalol versus oral Nifedipine in the management of preeclampsia in the antepartum and intrapartum period.Methods: The present study was conducted in a tertiary care centre, Chennai from October 2013 to September 2014. It was a prospective observational study done in antenatal ward and labor ward. All antenatal women diagnosed to have pre-eclampsia, irrespective of gestation are included in this study.Results: Age distribution of PIH patients and the maximum number of patients were 20-25 years of age. maximum patients of severe preeclampsia were primigravida. Both systolic and diastolic BP in the two groups (oral labetalol and oral Nifedipine groups) were not statistically significant as the p value is >0.005.Conclusions: From this study, authors found that both oral labetalol and oral nifedipine are effective and well tolerated when used for rapid control of blood pressure in severe hypertension of pregnancy

Comparative study on Functional Machine learning and Statistical Methods in Disease detection and Weed Removal for Enhanced Agricultural Yield

Agriculture is one of the essential sources of occupation and revenue in India. Conferring to existing statistics, most agriculturalists are facing severe losses due to poor farming yield. Farming activities are challenged by various environmental factors that affect agricultural productivity to a greater extent. The present farming situation is above the average of the process involves more biochemical bases for managing the diseases and other destructing facts. The foremost problems they are facing in day-to-day farming tasks are crop or plant diseases affecting productivity. Also, the growth of weeds along with field crops has been another challenge.  The technology has developed to rectify the problems using some machine learning algorithms like Random Forest algorithms, Decision trees, Naïve Bayes, KNN, K-Means clustering, Support vector machines. The result has been evaluated and observed through the performance evaluation metrics using confusion matrix, accuracy, precision, Sensitivity, specificity with the observations, research, and studies. The statistics have expressed the overall accuracy of 98% by achieving the detection of diseases in plants and by removing the weeds that ruin the growth of plants

End to End Encrypted Smart Lock Using RSA based on Opinion from Social Media Review Comments

In the modern era, from big apartments to small houses, startups to corporate buildings, protecting assets or preventing unauthorized persons are crucial problems. Often traditional locks like padlocks are prone to security risks since they can be easily bypassed. Existing smart lock systems are prone to Man in middle Attacks where digital keys can easily be duplicated. The review comments about prevailing smart locks technologies have been collected from various sources such as blogs and microblogs.  The data set is analyzed to discover the opinion of the people about the smartlock product. In this proposed system, an innovative smartlock system prototype is designed using current technologies. A smart lock system has been proposed which is encrypted end-to-end using the RSA algorithm. This system uses a one-time password sent to registered users combined with the master code to unlock the door. This system is designed as such only the users who are connected to a wireless local area network are able to access the smart lock system, this adds an additional layer of security. It is connected to the cloud and logs all the activity from booting to shutting down. The breach detection system along with image capture is also included to detect forced intrusions. The client functionality can be easily ported to any platform which supports HTTP protocol which tends to be the major advantage of the proposed work

Privacy-Preserving Image Storage on Cloud Using An Unified Cryptographic Authentication Scheme

With the proliferation of several cutting-edge technologies such as the Artificial Intelligence (AI), and Machine Learning (ML), Internet of Things (IoT), cloud technology is gaining colossal popularity in recent years. Despite the general publicity on the theme across the digital world, defending user data kept in the cloud database is the most decisive problem. Recent potential cyber attacks reveal that storing private images entails more unique care related to other types of information on the cloud. As the cloud customer who has kept their images has no control over their data the cloud service provider has to ensure better security against cyber threats. Cryptography algorithms are the best choice to secure pictorial data in the cloud. These techniques transform images into an inarticulate form to keep confidentiality over undependable and vulnerable social media .In this paper, we aim to propose an approach for improving image security on the cloud using cryptography algorithms. We developed a cohesive approach, called Unified Cryptographic Image Authentication (UCIA) to protect user images on a cloud platform. The proposed UCIA approach includes two phases: (i)UCIA engenders a cipher text through a Data Encryption Standard (DES) by providing a key and a message as input, and (ii)UCIA implements a Twofish algorithm to encipher the pictures by applying cipher text. The enciphered picture data is then stored in the cloud database and can be recovered when the customer requests it. The effectiveness of both enciphering and deciphering procedures are analyzed using the evaluation metrics including time for enciphering, deciphering, cloud storage, and enciphering throughput. Experimental results reveal the better performance and strength of the UCIA approac

Antioxidant and Cytotoxic Activities of A Novel Isomeric Molecule (PF5) Obtained from Methanolic Extract of Pleurotus Florida Mushroom

The Pleurotus florida is recognized as a medicinal and edible mushroom and the present study intends to reveal the active isomeric molecules from this mushroom. The P. florida was cultivated using different nutrient supplements: groundnut husk, maize powder, horse gram powder and coconut oil-cake powder. Horse gram supplement showed the higher mushroom yield and henceit was used for the cultivation of P. florida. Methanolic extract of P. florida was found to be efficient in antioxidant activity among ethanol, aqueous, ethyl acetate and hexane extracts. The bioactive fraction 3-methoxy-4-hydroxy cinnamic acid (PF5) was isolated and purified from the methanolic extract of P. florida by column chromatography, thin layer chromatography (TLC) and gas chromatography-mass spectrum (GC-MS) and further it was characterized by Nuclear magnetic resonance (NMR). The PF5 was tested for its DPPH and reducing power assays, and the IC50 values were found to be 21.7 µg/mL and 105 µg/mL, respectively. We found that the cytotoxic effect of 3-methoxy-4-hydroxy cinnamic acid was tested against the lung cancer cell line using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT), sulphorodamine B (SRB) and trypan blue assays which exhibited a higher cytotoxic effect (CTC50, 645 µg/mL). These results suggested that 3-methoxy-4-hydroxy cinnamic acid from P. florida could be explored as a novel and potent natural antioxidant and cancer preventive agent, alternative to existing synthetic molecules

Glyceral Trinitrate: As Potential Corrosion Protector for Mild Steel in Acid Medium Along with Paint-coated Steel in a Saline Environment

The importance of mild steel lies in its industrial applications, and the fight against corrosion is very important from an ecological, economic, technical, and aesthetic view. The current study involves the use of pharmaceutical drugs namely GTN towards corrosion inhibiting reaction was examined by gravimetric and electrochemical approaches. From weight loss studies, maximum I.E (%) 94.04% reached for 60 mg/L concentration of GTN for 6 hrs immersion time. The Polarization measurements showed that the behaviour of GTN as mixed nature and surface assimilation of GTN at the superficial, such that water molecules are substituted at the solution-metal boundary. The corrosion resistance property of the studied inhibitor as coating was also evaluated in NaCl which shows better progress corrosion retardation property of coating in the saline medium. Theoretical calculations were employed using DFT to correlate with the experimental observations.</jats:p

Performance comparison for grid connected photovoltaic system using sliding mode control

Three sliding mode controllers are designed for the control of a photo-voltaic system connected to grid on the nonlinear behavior of the dc-link capacitor and inverter switching input signals. In this proposed system, a nonlinear state space model is used after abc-dq reference frame transformation to design sliding mode control inputs to ensure the maximum power point extraction from the photo-voltaic system and unity power factor in the grid with different sliding manifolds. The performance of three sliding mode controller is compared and it is concluded that the controller based on the power balanced perform better compared to separate current and voltage tracking. Performance of these controller under nominal conditions, parameter variations and load disturbances is validated by the numerical simulation

AN EMPIRICAL STUDY OF CANCER CLASSIFICATION TECHNIQUES BASED ON THE NEURAL NETWORKS

Cancer is one of the most common dreadful diseases prevailing worldwide, and patients with cancer are rescued only when the cancer is detected at a very early stage. Early detection of cancer is appropriate as in the fourth stage, but the chance of survival is limited. The symptoms of cancers are rigorous, and therefore, all the symptoms should be studied properly before the diagnosis. Thus, an automatic prediction system is necessary for classifying the tumor, i.e. malignant or benign tumor. Over the past few years, cancer classification is increased rapidly, but there is no general technique to find novel cancer classes (class discovery) or to assign tumors to known classes. Accordingly, this survey analyzes distinct cancer classification techniques. Thus, this review article provides a detailed review of 50 research papers presenting the suggested cancer classification techniques, like Deep learning-based techniques, Neural network-based techniques, and Hybrid techniques. Moreover, an elaborative analysis and discussion are made based on the year of publication, utilized datasets, accuracy range, evaluation metrics, implementation tool, and adopted classification methods. Eventually, the research gaps and issues of various cancer classification schemes are presented for extending the researchers towards a better future scope. </jats:p

Prospective observational study to evaluate the efficacy of labetalol versus nifedipine in the management of preeclampsia

Background: Hypertensive disorders of pregnancy are the common medical disorders in pregnancy. It has effects both on expectant mother and fetus. Pre-eclampsia is a pregnancy specific multisystem disorder of unknown etiology, and accounts for 12-18% of maternal mortality. There is general consensus that maternal risk is decreased by antihypertensive treatment that lowers very high blood pressure. Objective of this study was to study the efficacy of oral labetalol versus oral Nifedipine in the management of preeclampsia in the antepartum and intrapartum period.Methods: The present study was conducted in a tertiary care centre, Chennai from October 2013 to September 2014. It was a prospective observational study done in antenatal ward and labor ward. All antenatal women diagnosed to have pre-eclampsia, irrespective of gestation are included in this study.Results: Age distribution of PIH patients and the maximum number of patients were 20-25 years of age. maximum patients of severe preeclampsia were primigravida. Both systolic and diastolic BP in the two groups (oral labetalol and oral Nifedipine groups) were not statistically significant as the p value is &gt;0.005.Conclusions: From this study, authors found that both oral labetalol and oral nifedipine are effective and well tolerated when used for rapid control of blood pressure in severe hypertension of pregnancy.</jats:p