Comparison of neonatal birthweights and fetomaternal outcomes in gestational diabetes-on diet, metformin and insulin

Background: Review suggested that neonatal birthweight in insulin group was higher than in metformin and diet and metformin had overall better fetomaternal outcomes. We wanted to understand the trend in the patients visiting our hospital.Methods: This is an observational comparative study conducted in Department of Obstetrics and Gynaecology, AIMS Kochi from 2019-2021. All antenatal patients were screened and total of 153 patients meeting inclusion and exclusion criteria were studied. The data was collected and analysed using SPSS 20 software.Results: The neonatal birthweight the three groups were comparable, with no significant difference (3.05±0.42 kgs in diet; 2.92±0.37 kgs in metformin; 3.11±0.41 kgs in insulin; p=0.092) and maternal pre-pregnancy weight was associated with birthweight. Insulin group had higher age (31.17±5.54 years versus 27.59±4.62 years in OHA and 29.43±4.56 years in diet; p<0.001). Insulin group delivered at an earlier gestation (37 weeks versus 38 weeks; p<0.001) and most common mode of delivery was cesearean section (74.6% in insulin; 54.2% in diet and 49.8% in OHA). NICU admission (45.8% versus 10.8% in diet and 15.4% in OHA; p<0.001) and need for phototherapy (1.5% in metformin versus 5.4% in diet and 11.8% in insulin; p=0.067) was lesser in metformin group.Conclusions: Strict glycemic control is important in preventing macrosomia Metformin overall has good fetomaternal outcomes compared to diet or insulin

Support Vector Machine based Image Classification for Deaf and Mute People

A hand gesture recognition system provides a natural, innovative and modern way of nonverbal communication. It has a wide area of application in human computer interaction and sign language. The whole system consists of three components: hand detection, gesture recognition and human-computer interaction (HCI) based on recognition; in the existing technique, ANFIS(adaptive neuro-fuzzy interface system) to recognize gestures and makes it attainable to identify relatively complex gestures were used. But the complexity is high and performance is low. To achieve high accuracy and high performance with less complexity, a gray illumination technique is introduced in the proposed Hand gesture recognition. Here, live video is converted into frames and resize the frame, then apply gray illumination algorithm for color balancing in order to separate the skin separately. Then morphological feature extraction operation is carried out. After that support vector machine (SVM) train and testing process are carried out for gesture recognition. Finally, the character sound is played as audio output

CHEMICAL CHARACTERIZATION OF HERBO - MINERAL SIDDHA FORMULATION KARA SOODA SATHU PARPAM BY USING MODERN TECHNIQUES

Kara Sooda Sathu Parpam (KSSP) is a traditional Siddha Herbo- mineral drug. The aim of the present study was to standardize the physico-chemical traits of the Siddha herbo mineral formulation KSSP. Efforts have been made to lay down the analytical standards for Kara Sooda Sathu Parpam which were not found reported to till date. This paper appraises a detail study of physico-chemical properties, phytochemical constituents and heavy metal contents of the selected drug (KSSP) were analyzed. The total ash value was found to be 9.3 %w/w, acid insoluble ash value is 0.94%w/w, water soluble ash value is 5.5 %w/w, and loss of drying at 105 º c is  7.3 % w/w. The water soluble extractives and alcohol soluble extractives were found to be 8.67 % w/w and 5.0 % w/w. The ICP-OES reveals that the heavy metals such as Mercury, Lead, Arsenic, cadmium are present in the drug are below detected limit. HR-SEM analysis has been used to study particle size shape and distribution. The study highlights the appropriate application of modern scientific methods for developing the new insights into metal based Siddha drugs

NON INVASIVE COST EFFECTIVE SIDDHA DIAGNOSTIC TOOLS FOR SIDDHA AILMENTS

The medication of normal procedure shall be extra legitimate if the ailment is identified by using it’s possess viewpoint. So the be taught was once aimed to determine the sensitivity and specificity of the Siddha diagnostic methodology. Siddha strongly advocacies every physician to seem into “what type of person is suffering from an ailment is most important than what variety of health problem he has”. This holistic standpoint devises the protocol of each medication in Siddha. This distinctive primary is the delicate force and motive in the back of the existence of this method considering antiquity.Having the above mentioned unique standards in intellect, this paper tried to fully grasp the complexity and core basics of Siddha diagnostics which indeed pave solution to unique therapeutics. The medication of normal system shall be more legitimate if the disorder is diagnosed via its own point of view. So the learn was once aimed to check the sensitivity and specificity of the Siddha diagnostic ways. Eight fold examinations displays particularly pulse studying, tongue, complexion, voice, eyes, physique examination, stool and urine. These instruments provide the framework in phrases of immediate and individualized prognosis and medication to the patient and support to recover from diseases in a timely fashion without leaving any hazardous impact on the physique

Synergistic Effects of Climate Change and Grazing on Net Primary Production of Mongolian Grasslands

In arid and semi-arid regions, grassland degradation has become a major environmental and economic problem, but little information is available on the response of grassland productivity to both climate change and grazing intensity. By developing a grazing module in a process-based ecosystem model, the dynamic land ecosystem model (DLEM), we explore the roles of climate change, elevated CO2, and varying grazing intensities in affecting aboveground net primary productivity (ANPP) across different grassland sites in Mongolia. Our results show that both growing season precipitation totals and average temperature exert important controls on annual ANPP across six sites over a precipitation gradient, explaining 65% and 45% of the interannual variations, respectively. Interannual variation in ANPP, measured as the ratio of standard deviation among years to long-term mean, increased from 9.5 to 18.9% to 23.9–32.5% along a gradient of high to low precipitation. Historical grazing resulted in a net reduction in ANPP across all sites ranging from 2% to 15.4%. Our results further show that grassland ANPP can be maintained at a grazing intensity of 1.0 and 0.5 sheep/ha at wet and dry sites, respectively, indicating that dry sites are more vulnerable to grazing compared to wet sites. In addition, precipitation use efficiency (PUE) decreased while nitrogen use efficiency (NUE) increased across a gradient of low to high precipitation. However, grazing resulted in a net reduction in both PUE and NUE by 47% and 67% across all sites. Our results indicate that seasonal precipitation totals, average temperatures and grazing are important regulators of grassland ANPP in Mongolia. These results have important implications for grassland productivity in semi-arid regions in Central Asia and beyond

Nitrogen effect on carbon-water coupling in forests, grasslands, and shrublands in the arid western United States

Author Posting. © American Geophysical Union, 2011. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 116 (2011): G03023, doi:10.1029/2010JG001621.As greenhouse gases, including CO2, accumulate in the atmosphere, the western United States is predicted to undergo large-scale climate warming and reduced summer precipitation in the coming decades. In this study we explore the role of these climate changes with elevated CO2 to determine the plant physiological response on primary productivity and associated feedbacks on evapotranspiration (ET) and runoff using a biogeochemistry model, TEM-Hydro, with downscaled climate data for the western United States from the NCAR CCSM3 A2 scenario. Net primary productivity increases by 32% in forests due to feedbacks between warmer temperatures and enhanced nitrogen mineralization but decreases in shrublands by 24% due to excessive drying and reduced nitrogen mineralization. Warming directly increases nitrogen mineralization rates but indirectly decreases them by reducing soil moisture, so the net effect is highly dependent on climatic conditions within each biome. Increased soil moisture resulting from larger water use efficiency from the elevated CO2 leads to more net nitrogen mineralization in forests, which reduces N-limiting conditions. The effect of CO2 on stomatal conductance is therefore enhanced because of its effect on reducing nitrogen limiting conditions. Runoff decreases over the 21st century by 22% in forests, 58% in grasslands, and 67% in shrublands due to the reduced precipitation in each region but is modulated by the plant-induced changes in ET. The role of moisture limitation is therefore a crucial regulator of nitrogen limitation, which determines the future productivity and water availability in the West.This study was funded by the Department of Energy, Basic Research and Modeling to Support Integrated Assessment, DE‐FG02‐08ERG64648

IDENTIFICATION OF ANTIULCER ACTIVITY BY INSILICO METHOD IN SELECTED MEDICINAL PLANTS

Ulcer occurs when stomach acid damages the lining of the digestive tract caused by the bacteria Helicobacter pylori. Many pharmacological activities such as antiulcer activity can act against ulcer. Medicinal plants like Mimosa pudica and Vachellia nilotica has the antiulcer activity in a wide range. To study the antiulcer activity in medicinal plants using insilco studies by comparing the phytocompounds of plants with histamine 2 receptor as a binding protein, which is present in the stomach lining of homosapiens. Histamine 2 receptor was modelled using Swiss model and the ligand structures are obtained from PUB-CHEM, viewed easily via PYMOL. All the phytocompounds showed good binding energy with modelled protein on the docking methodology. Specifically ascorbic acid exhibited the lower binding energy of value -3.24 kcal/mol, indole and catechin shows highest binding energy of value -4.99 kcal/mol and -4.98 kacl/mol respectively. The results can be useful for the design and development of phytocompounds having better inhibitory activity against several types of ulcer

Modeling and Monitoring Terrestrial Primary Production in a Changing Global Environment: Toward a Multiscale Synthesis of Observation and Simulation

There is a critical need to monitor and predict terrestrial primary production, the key indicator of ecosystem functioning, in a changing global environment. Here we provide a brief review of three major approaches to monitoring and predicting terrestrial primary production: (1) ground-based field measurements, (2) satellite-based observations, and (3) process-based ecosystem modelling. Much uncertainty exists in the multi-approach estimations of terrestrial gross primary production (GPP) and net primary production (NPP). To improve the capacity of model simulation and prediction, it is essential to evaluate ecosystem models against ground and satellite-based measurements and observations. As a case, we have shown the performance of the dynamic land ecosystem model (DLEM) at various scales from site to region to global. We also discuss how terrestrial primary production might respond to climate change and increasing atmospheric CO2 and uncertainties associated with model and data. Further progress in monitoring and predicting terrestrial primary production requires a multiscale synthesis of observations and model simulations. In the Anthropocene era in which human activity has indeed changed the Earth’s biosphere, therefore, it is essential to incorporate the socioeconomic component into terrestrial ecosystem models for accurately estimating and predicting terrestrial primary production in a changing global environment

Deep learning-based image captioning for visually impaired people

Vision loss can affect people of all ages. Severe or complete vision loss may occur when the eye or brain parts that need to process images are damaged. In this paper, in order to facilitate the blind, deep learning algorithms are used to caption the image for the blind person in which the blind can know about the object, distance and position of object. Whenever an image is captured via the camera, the scenes are recognized and predicted by the machine. After the prediction, it will be sent as an audio output to the user. Thus, with the help of this paper an artificial vision to the blind, can be achieved and help them to gain confidence while travelling alone