Search

Objective- To evaluate and compare the level of TSH in premenopausal women (reproductive age group) and post-menopausal women. Material And Methods- The study was carried out on 100 premenopausal and 100 post-menopausal women attending Out Patient Departments at RIMS, Ranchi, during the period of January 2018- October 2019. Study Design: - Observational Study. Statistics- Statistical analysis was done using SPSS software. The data were represented by counts, percentage and mean ± standard deviation. Statistical analysis of TSH was done by t-test to compare these parameters in premenopausal and post-menopausal women. A p-value of

The CO2 concentration in the atmosphere is rising and anticipated to be doubled by the end of the current century. Agricultural crop production is one of the key sectors that might be affected by rising atmospheric CO2 through its effect on photosynthetic rates and thus productivity. It was reported that C3 plants respond to elevated CO2 by modification of morpho-physiological traits. The crop selected for the present study was Green gram (Vigna radiate L. Wilczek). Though it is an important crop, the availability of pulses has declined. So, a study of the plant responses to high atmospheric CO2 is important since it regulates productivity and quality. Moreover information about genotypic variation of crops under elevated CO2 is lacking in legumes. The general aim of the study is test whether Green gram can adapt to such a change and to explore mechanisms underlining the adaptive response. Six genotypes of green gram used in the study were SML1827, SML832, SML1831, PM1533, Pusa M-19-31, and Pant M-5. Three different levels of CO2 concentration namely 390ppm, 600 ppm and 750ppm under open top chambers along with an ambient concentration were maintained to assess the response of growth, physiological and yield parameters. The purpose of Open Top Chamber was to study the response of plants in high CO2 environment with precise control and regulation of desired CO2, temperature and humidity. The results obtained for this experiment showed that elevated CO2 has a positive effect on crop growth and development. Results indicated that 600ppm CO2 enhanced some growth parameters viz. leaf area, number of branches per plant, number of effective root nodules and total biomass of plant which ultimately influenced the yield. Under 750 ppm CO2, An opposite trend was recorded where yield was significantly reduced. Genotypes like Pant M-5, Pusa M-19-31 could be considered as better genotypes when grown under elevated levels of CO2 as they have better N acquisition capability because of greater nodule formation in addition to biomass accumulation. Therefore, such genotypes may be utilized as future breeding materials for adaptation to the changed climatic condition.

Skeleton-network reconfiguration is an important task and plays a most important role during power system restoration (PSR) after a blackout. By determining the skeleton network, the power ...

The below model depicted the successful engineering how one can design and implement A.I based Inhaler System for Respiratory precision to maintain saturation of human breathing system, we can even labeled the system as Artificial Intelligence based lungs or Lungs Support System or Oxygen Support System or Breath Support System but purpose remains same.

Aim: The study was carried out to estimate TSH and Cortisol level in preeclamptic women as compare to normotensive women. Material and Methods: The present study has been conducted on 100 preeclampticprimigravidae in their trimester of pregnancy attending O.P.D of janana hospital, J.L.N Medical college Ajmer. 50 healthy primigravidae of similar age group were included in the study, as the control group. Results:In this study we observed that out of 100 patients of preeclampsia in which 82 patients were of mild preeclampsia and 18 patients were of severe preeclampsia. There was significant decrease in level of cortisol in patients of mild and severe preeclampsia. Decrease in level of cortisol was more in severe preeclamptics as compared to mild preeclamptic patients. There was significant increase in level of TSH in mild preeclampsia whereas more increase in severe preeclampsia. Conclusion:In this present study of 100 patients we concluded that from the results all these parameters play an important role in preeclampsia hence the measurement of TSH and cortisol activity may be used in early diagnosis and management of patients of preeclampsia. This can also be useful in assessing the severity of preeclampsia.

Due to environmental issues and smart grid development, distributed energy resources, energy storage systems, and demand response (DR) are gaining attention to reduce the pollution and fossil fuel usage. This paper presents a customer’s preferences based innovative home appliances scheduling framework considering numerous constraints and DR for scheduling household appliances incorporating local energy grid and energy storage systems, including electrical and thermal energy storage. First, the models of household appliances and air conditioning load are built as the shiftable and non-schedulable loads and a flexible thermal load, respectively. Second, an enhanced normalized normal constraint (ENNC) strategy based on game theory (GT) is presented for a novel home appliance scheduling (HAS) framework with the objectives to optimize consumption cost, end-users comfort, and peak to average ratio. Then, the fuzzy compromising (FCP) method is proposed to optimize overall energy cost and gaseous emissions for the novel HAS framework with a residential local energy grid. In addition to this, conditional value at risk (CVaR) has also been incorporated in the objective function to resolve the sudden absence of distributed energy resources and power failures. Finally, case studies on data from Dallas, Texas, USA are performed, and the simulation results show that the proposed strategy is computationally inexpensive and outperforms other approaches in terms of electricity cost, gaseous emissions, and customer’s comfort. The proposed approach gives a significantly lower cost of 104.30 cents and gaseous emissions of about 18.753 kg for an entire day of novel HAS with DR adoption. Thus, it can provide help for DR accomplishment and precise prediction of electricity consumption.

Nowadays, the most notable uncertainty for an electricity utility lies in the electrical demand and generation in power systems. Demand response (DR) accomplishment due to the home appliances energy management has acquired considerable attention for the reliable and cost-optimized power grid. The optimum schedule of home appliances is a challenging task due to uncertain electricity prices and consumption patterns. Given this background, an innovative home appliance scheduling (IHAS) framework is proposed based on the fusion of the grey wolf and crow search optimization (GWCSO) algorithm. Using the proposed technique, the cost of electricity reduction, users-comfort maximization, and peak to average ratio reduction is analyzed for home appliances in the presence of real-time price signals (RTPS). The proposed optimization algorithm is also employed for Air Conditioners (ACs) scheduling and end-users comfort maximization in its usage due to the high percentage of ACs load. Simulation results indicate that the proposed GWCSO approach is robust, computationally efficient, and outperforms conventional ones in terms of electricity cost, peak to average ratio, and it also demonstrate that there is a trade-off between users’ comfort considering appliances waiting time and electricity cost. Thus, it can provide guidance for precise electricity consumption predictions and different DR actions.

Mosquito-borne diseases are rapidly spreading in all regions of the world with an estimation of 2.5 billion people globally are at risk. The recent surge in dengue outbreaks has caused severe affliction to Malaysian society. Hence, the ability to predict a dengue outbreak and mitigate its damage and loss proactively is very critical. In this paper, we study the possibility of applying machine learning (ML) and deep learning (DL) approaches to predict the number of confirmed dengue fever (DF) cases in Kuala Lumpur. We identified several contribution factors correlate to a dengue outbreak. In addition to the two frequently used factors (daily mean temperature and daily rainfall), we also took into account the enhanced vegetation index (EVI), humidity and wind speed as input factors to our prediction engines. We collected and cleansed data on these factors and the daily DF incidents in Kuala Lumpur from 2002 to 2012. We then used these data to train and evaluate our 3 ML/DL models. Among the three models, GA_RNN was the best performer and achieved a MAE of 10.95 for DF incidence prediction.

Typhoid is one of the infectious diseases of human. Outbreaks of typhoid fever caused by S. typhi and S. paratyphi A are still a serious health problem worldwide. There are number of test available now days from molecular to immunological and biochemical to microbiological. In our study we have tried to establish the relevance of widal test in the diagnosis of typhoid fever. Both the tube and slide agglutination widal test were used to investigate the incidence of ty- phoid fever in 80 test individuals comprising 60 typhoid fever patients and 20 apparently healthy individuals comprised of adult and children. The test results were compared with those of standard blood culture tests. We tested different individu- als and were categorized according to their age above 10 years (20), and between 5- 10 years (20), and children under 5 years (20). Results showed that the accuracy of the widal tube and slide agglutination tests as used in the study in terms of sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were 71%, 62%, 91% and 31%, respectively. It is concluded that widal test will remains relevant as a diagnosis tool for typhoid fever, which is more con- venient, cheaper and faster than the other molecular and serological test.