Boron-Mediated Regioselective Aromatic C−H Functionalization via an Aryl BF2 Complex

An efficient regioselective functionalization of 2-aryl-heteroarenes and aryl aldehydes via an azaaryl BF2 complex has been developed. Mechanistically the reaction comprises fluoride to bromide ligand exchange on an aryl boron species and consecutive C−B bond cleavage to deliver a broad range of functionalized products. The reaction is high yielding, has a broad substrate scope where several different heteroarenes can be functionalized with chloro, bromo, iodo, hydroxyl, amine and BF2 in a highly regioselective fashion. The method can be applied for late-stage functionalization or for rapid skeleton remodeling with for instance cross-couplings

Prospective study of ovarian function in hysterectomised females

Background: Hysterectomy is one of the most common operations performed in the world. The aim of this study was to determine prospectively the influence of hysterectomy on ovarian function by measuring gonadotrophin levels and studying ovarian doppler over a two-year period.Methods: Authors conducted a prospective cohort study at the department of obstetrics and gynecology in study tertiary care center. The study was carried out over a period of two years November 2012-November 2014. Serum FSH, ovarian PI and questionnaire data were obtained at baseline and at 6 and 12 months postoperatively.Results: There was significant difference in the mean FSH and mean PI at follow-up visits of 6 and 12 months. Patient characteristics did not contribute to the changes that were observed during the follow-up.Conclusions: Authors conclude that hysterectomy affects ovarian function by affecting blood supply (reducing blood supply). This is reflected by increased FSH levels and increased PI values on ovarian Doppler

Analysis of causes of maternal mortality in tertiary care center, 11 years study

Background: Objectives to study the causes of maternal mortality and the complications leading to maternal death.Methods: A retrospective study of hospital records and death summaries of all maternal death over a period of 11 years from January 2008 to December 2018 was carried out at tertiary care hospital, Mumbai.Results: There were a total of 459 maternal death out of 36930 live birth giving maternal mortality rate mean maternal mortality ratio (MMR) of 1242 per 100000 live births. Unregistered and late referral account for maternal death. The majority of women were in 21-30 years age group in 20 to less than 37 weeks of pregnancy. The commonest cause of death was due to hepatitis infection 129 (28.1%), sepsis 52 (11.32%), PIH including eclampsia 46 (10.02%), cardiovascular diseases 33 (7.18%), haemorrhage 31 (6.75%), Kochs 31 (6.75%) and respiratory diseases 22 (4.79%).Conclusions: Maternal mortality can be reduced by identifying causes which are preventable and giving timely treatment

Structural, optical and gas sensing properties of barium titanate surface modified by nano silver

Paper represents the results of SO2 sensing performance of BaTiO3 surface modified by nano silver. Surface modification was performed by dipping of BaTiO3 thick films in the synthesized nano silver. The main objective was to investigate the effect of nano silver on gas sensing performance of BaTiO3 perovskite. Different intervals of dipping time were used to find the optimum dipping amount on the surface of perovskite oxide. Synthesized silver was characterized by UV-visible spectroscopy and transmission electron microscopy. Surface modified thick films were analyzed for structural, morphological, electrical and gas sensing properties by XRD, SEM with EDX, static gas sensing unit respectively. Selectivity of surface modified BaTiO3 thick films was also investigated

Factors affecting stillbirth: prospective study

Background: Stillbirth is defined by WHO as the birth of a baby with a birth weight of 500 gm or more, 22 or more completed weeks of gestation or a body length of 25 cm or more, who died before or during labour and birth.Methods: This was prospective observational study of factors affecting stillbirth was conducted in tertiary hospital for a period of 1 year from 1st June 2014 to 31st May 2015. During the study period, 200 parturient of gestational age 28 weeks or more and fetal weight 1000 gm or more with or without medical disorders were included.Results: The total number of births during study period was 11,951. Stillbirth rate in the present study was 16.73 per 1000 births. Most of stillbirths were seen in the antepartum period (76%) when compared to intrapartum period (24%). Maximum stillbirths occurred in gestational age of 36 weeks and above (52%) and fetal weight between 2001-2500 gm (27.50%). Patients with inadequate antenatal care, less than three visits had 86% stillbirths.Conclusions: Proper antenatal care, prompt referral services and availability of emergency obstetric care will provide a pivotal role for reduction of stillbirths

COTTON CROP CLASSIFICATION METHOD USING LEVENBERG-MARQUARDT NEURAL NETWORK AND ITS PERFORMANCE ANALYSIS ON VEGETATION AND GREEN LEAF INDICES

numerous implications related with food, economic and environmental concerns are looking for cotton crop identification using timely information. However, the accuracy of cotton crop detection remains a challenging task, despite supervised classifier play significant roles. Moreover, the obtained results are not at expected remarkable level, when such direct application of classifiers is done on the images. Hence, vegetation indices are brought into the picture, but challenge persists on identifying suitable vegetation indices among numerous indices in the literature.  This work studies the performance of such six renowned vegetation indices like Simple Ratio (SR), Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Normalised IR, Wide-Dynamic Range Vegetation Index (WDRVI) and GreenNDVI (GNDVI). For this study, fuzzy c – means (FCM) clustering algorithm is unified with neural network, which is trained using Levenberg – Marquardt (LM) algorithm. The experimental results are investigated through which it is found that Green normalised difference Vegetation Index performs well than any other vegetation indices by accomplishing 91.63% accuracy on average

PHP Desk

We use web browser to download HTML, CSS and JS code and execute it. This HTML/CSS/JS code is an output produced by server after processing PHP or JSP pages. So this implies that actual process is completed by server. This is the only disadvantage with this kind of system. We can avoid this problem, if we use our new proposed system called PHP Desk. PHP Desk system does not bring any t ime overhead to load pages as it completes all processes on client side only. In other words it will make application work fas t enough to look like they are real - time projects or desktop applications. As we have said that PHP Desk makes a web script look like it is executing as desktop application. It means a web developer c an become desktop developer. He/she does not need to le arn any special programming language or any technology to develop desktop applications. With their current knowledge they can build good quality desktop applications using PHP Desk system. PHP Desk helps to use Graphic s of Web Standards for desktop applica tions with the same ease of their use in Web Applications. PHP Desk is also useful to utilize CMS technologies for rapid development of new applications. PHP Desk system has to deal with many issues like encryption and decryption to provide security to dat a and code. This code is actually a PHP code which carries critical business logic and data storage information or database connections. This code is not to be d isclosed to clients and other developers. But if we deploy the project to client then the code will be accessible to client. To avoid this we have developed concepts like HK, ECF, SCG, and SCD. We encrypt PHP code using DES algorithm for security purpose. A key of 56 bits is used for encryption which is then processed by SHA algorithm to generate HK (Hashed Key) to be included as Digital Certificate. Code after encryption is called as ECF (Encrypted Code Format) which is generated by SCG (Secure Code Generator).SCG is developers tool. Developer will utilize it to provide security to t he code. SCD is supportive tool to client side Apache, which is responsible for decryption of Apaches decrypted code and it also communicate s with apache server. U sing the above proposed techniques we can overcome the security issues associated earlier

Bioprospecting of Adhatoda vasica for Identification of Novel Compounds using Chromatographic Methods and Screening for Anti-diabetic and Antioxidant Activity

This investigation column eluted fractions of leaf Adhatoda vasica of was assessed for its phytochemical screening, column chromatography, thin layer chromatographic studies, protease activity, anti-inflammatory activity, antidiabetic activity and antioxidant activity. Phytochemical screening reflects the presence of alkaloid, flavonoids, coumarins, terpenoids, steroids, emodin’s, Quinone’s. Column chromatography method was used for purification of bioactive compounds. Thin layer chromatographic study was carried out by using various solvent system of different type of polarity of n- butanol, acetic acid and acetone. TLC profiling shows pure band at 254nm and 366 nm. The strong “proteolytic activity” also pointed out in purified fraction of eluted fraction. In vitro anti-inflammatory activity was evaluated using albumin denaturation fraction 3, showing highest activity 75% followed by fraction 5 (62.73%), membrane stabilization assay fraction 6 (80.23%) followed by fraction 3 (64.65%) and proteinase inhibitory activity of fraction 5(88%) followed by fraction 7 (87.68%) at concentration 500 µg/ml. Aspirin (90.87%) was used as standard drug for the study of anti-inflammatory activity. In vitro antidiabetic activity was performed using Alfa amylase inhibition assay. Highest activity was showed in fraction 4 (79.05 %) and fraction 5 (77.05 %) at concentration 500 µg/ml. Antioxidant activity was performed by reducing power assay fraction number 2 has higher absorbance 1.04 at 500µg/ml followed by reducing power of column eluted fraction was compared with ascorbic acid as standard showing higher absorbance 0.93 at 500µg/ml

Classical View on Bhasma as Chief Formulation of Rasashastra: An Ayurveda Review

Minerals and metals based drugs possess important therapeutic potential and preparation of such medicines described in Rasashastra which deals with minerals and metals based formulations. The processing techniques related to the preparation of these medicines are very specific to make these drugs nontoxic and efficacious. Shodhana means purification and Marana means incineration/calcinations are main procedures associated with the preparation of Rasa- Aushdhis. Bhasmas are important preparation of this category which is considered as herbo-metallic preparation and description of Bhasma Kalpana is found in Ayurveda Samhitas during Arsha Sampradaya. These herbo-mineral/metallic formulations (Bhasma) mainly prepared by various steps of purification, grinding, mixing, heating, incineration and size reduction, etc. These drugs possess advantages of palatability, low dosing frequency, high potency, good bioavailability, optimum absorption and wide range of therapeutic spectrum. Bhasma not only used for therapeutic purpose but also advised for promoting general health and rejuvenating effects. Makshika bhasma, Swarna bhasma, Abhrak bhasma, Louha bhasma and Tamra bhasma, etc. are commonly used Bhasma preparation indicated for many pathological conditions including skin diseases, digestive ailments, sexual disorders, asthma and infections, etc

A Proposed Secured Prediction System for Human Diseases Using a Genetic Algorithm Approach to Data Mining

Many changes are happening in life styles of people in growing countries like India in recent days. Such changes in environment, diet, pollution and stress have led to the scenario that human beings are affected by microorganisms causing fatal diseases. In India, human diseases have become a major reason of deaths. A number of people have worked in this area to detect a particular disease, but it may happen that a person may be suffering from more than one disease at a time. Our attempt therefore is to detect the diseases a patient is suffering from with the use of detail symptoms given by a patient regarding his health status. This detection will enable him to have an appropriate treatment in time.In the health sector Data Mining techniques can be used to play a major role to detect a disease. The aim of the proposed system is to predict human diseases by using Association Rule Mining Algorithm name Apriori and generating optimized association rules using a Genetic Algorithm.