Impact of Training on Awareness of COVID-19 among The Health Care Workers in A Tertiary Care Hospital of Dehradun

Background: Novel Corona virus infection (Covid-19) was declared global pandemic by WHO infecting more than 118,000 cases in 114 countries and the number of deaths counting to 4291. WHO recommends the only strategy to limit the spread of Corona virus is only by prevention itself. Aim and Objective: To assess the awareness among Health Care Workers on covid-19 infection. To compare the level of knowledge among the study participants and To assess the impact of training about the knowledge on covid-19 control. Material and methods: The study was conducted by the Research team of Community Medicine Department, SGRRIM&HS, Dehradun between 1st October to 31st December 2020. Self-administered, pre-tested questionnaire was used to assess the knowledge and awareness among health care workers. Data collected and analysed using SPSS software for different parameters. Result: A total of 421 health care workers participated in the present study. Majority of the study participants were female with 346 (82.2%) while 75 (17.8%) of them were male. Independent t-test was used to compare pre and post test values with Socio-demographic profile, designation, and work place of the respondents. Conclusion: Improvement in the knowledge and awareness among health care workers was observed post training

Diversity analysis of sesame germplasm using DIVA-GIS

Sesame (Sesamum indicum L.) was studied for its distribution and diversity in India using DIVAGIS. Grid maps were generated for diversity analysis of the eight quantitative traits viz., plant height, inter-node length, leaves per plant, number of flowers per plant, number of capsules per plant, number of seeds per capsule, seed weight and seed yield. The results indicated that diverse accessions for all these traits can be sourced from Maharashtra, Gujarat and Madhya Pradesh (partly covering Chattisgarh) states and these states are diversity rich pockets for sesame germplasm in India. &nbsp

Diversity analysis of sesame germplasm using DIVA-GIS

Sesame (Sesamum indicum L.) was studied for its distribution and diversity in India using DIVAGIS. Grid maps were generated for diversity analysis of the eight quantitative traits viz., plant height, inter-node length, leaves per plant, number of flowers per plant, number of capsules per plant, number of seeds per capsule, seed weight and seed yield. The results indicated that diverse accessions for all these traits can be sourced from Maharashtra, Gujarat and Madhya Pradesh (partly covering Chattisgarh) states and these states are diversity rich pockets for sesame germplasm in India. &nbsp

Diversity analysis of sesame germplasm using DIVA-GIS

Sesame (Sesamum indicum L.) was studied for its distribution and diversity in India using DIVAGIS. Grid maps were generated for diversity analysis of the eight quantitative traits viz., plant height, inter-node length, leaves per plant, number of flowers per plant, number of capsules per plant, number of seeds per capsule, seed weight and seed yield. The results indicated that diverse accessions for all these traits can be sourced from Maharashtra, Gujarat and Madhya Pradesh (partly covering Chattisgarh) states and these states are diversity rich pockets for sesame germplasm in India. &nbsp

Prospective Observational Study of Mean Platelet Volume and Other Platelet Indices in Preeclampsia and Effects on Maternal and Perinatal Outcome in a Tertiary Care Referral Centre

Background and Objectives: Preeclampsia is an obstetric disorder that affects 6-8% pregnancies worldwide. Thrombocytopenia is the common hematological abnormaliz̄ty seen in Preeclampsia & Eclampsia. The tests like PT, APTT, TT and fibronectin level are more sensitive but are expensive and time consuming. Platelet indices like MPV, PC and PDW are inexpensive and derived from routine blood investigations and widespread availability of testsMaterials and Methods: This is a Prospective comparative study conducted on 120 pregnant women who were meeting inclusion and exclusion criteria.from 20 to 28 weeks of gestation. Out of 120 patients 60 patients with Preeclampsia of different severity were matched with 60 patients of healthy normotensive pregnant women who served as case(n=60) and control(n=60) respectively. At each scheduled antenatal visit subsequently 20-28 weeks (visit 1), 29-32 weeks (visit 2), 33-36 weeks (visit 3), and 37-delivery (visit 4) samples were drawn for platelet indices (MPV, PC, PDW) in EDTA vial and the serial record of these indices was maintained. Effect of deranged platelet indices on foeto-maternal outcome was another aim of the study. Feto-maternal outcome was noted and compiled.Results: In case group majority were Primigravida 37 patients accounting for 61.7%. All platelet indices were found deranged in the PE group. Platelet count decreased significantly from 2.4 + 0.3 lakhs/cumm on first visit to 1.5 + 0.4 lakhs/cumm before delivery while platelet distribution width (PDW) and mean platelet volume (MPV) increased from 13.2fl to 16.9fl and 9.5 fl to 12.2 fl respectively. MPV increased significantly with increasing PE severity (P ˂0.05), it was significantly higher in cases with poor foetal or maternal outcome.Conclusion: Our study proves that Platelet indices can play a significant role in earlier identification of PE and signal intervention to prevent future complications. MPV among three indices was found to be more sensitive than others to be linked to feto-maternal outcome

Assessment of General Circulation Models for Water-Resources Planning Applications

Study to predict possible effects of climate change on Texas water resources

Analysis of Distribution Transformer Physiological and Electrical Fault Detection - A Smart Grid Application

  Power grids transport electricity from the point of generation to the market. Power conversion from HV to LV and vice versa occurs in grids, also known as substations. These substations or power grids can be accessible or situated in remote locations. Transformers are used to convert power; they are an essential part of transmission and distribution networks. The method of grid monitoring and maintenance is essentially a very monotonous one. Monitoring the health of the transformers to maintain an uninterrupted power supply to the customers is difficult in such circumstances. Overvoltage, load currents, oil temperature, transformer oil level, and other parameters are monitored. The condition of the distribution transformer’s is evaluated in this article using real-time data from the transformer and specific sensors connected to Raspberry pi and artificial neural networks, are used to analyse the situation and make decisions regarding the health of the transformer. A model has been proposed for continuous monitoring consistent vigilance and swift actions against any faulty situations

Smart Battery Management System for Electric Vehicles

Electric vehicles are showing some promises in the automotive industry and can be the answer for mitigating carbon footprint. In the process of upgrading electric vehicles to the customer demands, battery performance serves a crucial part in deciding the performance of the electric vehicles. So, Battery Management System becomes the brains behind monitoring and controlling the battery. Real-time sensing of the battery parameters, decision-making capability to choose the type of charging, and which cell to be charged are all the functionalities of BMS. All these criteria can be assessed precisely and efficiently via processors like Raspberry pi, along with IoT and cloud computing technologies. These approaches can be used for remote accessing of the battery’s performance, which will help the customer and the company to analyse the vehicle's condition. They also help prevent battery degradation. Since IoT and cloud computing technologies are being used, if an adverse state occurs in the battery, the customer can be notified directly via their mobile. In this article, a combined technology of locally hosted processor and cloud-based decision making has been discussed to improve the battery intern Electric Vehicle’s performance

A VALIDATED RP-HPLC METHOD FOR SIMULTANEOUS ESTIMATION OF FEBUXOSTAT AND KETOROLAC TROMETHAMINE IN PHARMACEUTICAL FORMULATIONS

A simple, fast, precise, selective and accurate RP-HPLC method was developed and validated for the simultaneous determination of Febuxostat and Ketorolac from bulk and formulations. Chromatographic separation was achieved isocratically on a Waters C18 column (250×4.6 mm, 5 µ particle size) using a mobile phase, Methanol and Ammonium acetate buffer (adjusted to pH 6.0 with 1% orthophosphoric acid) in the ratio of 60:40. The flow rate was 1 ml/min and effluent was detected at 321nm. The retention time of Febuxostat and Ketorolac were 2.62 min and 3.96 min. respectively. Linearity was observed in the concentration range of 5-30µg/ml and 10-60 µg/ml for Febuxostat and Ketorolac respectively with correlation coefficient 0.999 for both the drugs. Percent recoveries obtained for both the drugs were 99.75-100.06% and 98.63-99.93%, respectively. The method was validated according to the ICH guidelines with respect to specificity, linearity, accuracy, precision and robustness. The method developed can be used for the routine analysis of Febuxostat and Ketorolac from their combined dosage for

1,8-Bis(3-chloro­anilino)-N,N′-bis­(3-chloro­phen­yl)octane-1,8-diimine

There are two half-mol­ecules in the asymmetric unit of the title compound, C32H30Cl4N4, in both of which the N—H bonds are syn to the meta-chloro substituents in the adjacent benzene ring. The other two Cl atoms of these two mol­ecules are disordered with occunpancy ratios of 0.79 (2):0.21 (2) and 0.68 (1):0.32 (1). Adjacent chloro­phenyl rings make dihedral angles of 74.3 (2) and 63.0 (2)° in the two mol­ecules. In the crystal, inter­molecular N—H⋯N hydrogen bonds link the mol­ecules into infinite chains