POTENTIAL OF BAJRA [PENNISETUM GLAUCUM (L.) R. BR.] IN HEALTH AND DISEASE

Bajra, also known as pearl millet, African millet or spiked millet, originated in Northern-Central Sahel of West Africa, was introduced 2500 years ago into Indian subcontinent. However, it is mentioned in Ayurvedic texts from 14th Century AD onwards as Nali under Truna dhanya or Kudhanya vargas. It is considered as a major source of Gluten free diet and is used in the management of Coeliac disease and other gluten allergy conditions worldwide. Indians are also including millet into their day to day diet in accordance with the global trend.  However the conditions of Gluten allergy and Coeliac disease are not common in Southern India. Hence, the necessity of Gluten free diet in South Indian Population is under question. It is hypothesized that excessive millet usage could be a reason behind thyroid dysfunction and goitre. Regular millet only diet may also lead to a nutrition deprived state in people who are not gluten sensitive. Ayurveda also emphasizes on avoidance of regular use of Kudhanyas. This review comprises different aspects of dietary inclusion of Bajra. The properties and usability of Bajra as a gluten free diet, utility of Bajra in populations which are not gluten allergic and the effects of Bajra on health and disease form the core of this review.

Endometriosis fertility index at laparoscope: a ray of hope and lots of scope

Background: Endometriosis fertility index (EFI) is used to predict the fecundity in women with surgically and histologically confirmed endometriosis. Aim of the study is to evaluate the successful spontaneous pregnancy rates in patients with endometriosis after laparoscopic surgery in relation to EFI score.Methods: Observational cross-sectional study was conducted on 76 patients who desire to conceive with suspected endometriosis related infertility treated by laparoscopic surgery. EFI score was calculated and information on mode of conception (spontaneous or assisted reproductive technology-ART) was collected by contacting the patients.Results: In women who conceived spontaneously, mean age was 31.33+3.29 years. Factors found to be significant were age (pvalue-0.0001), time to achieve spontaneous pregnancy (median-9 months). Patients with higher EFI score (5-10) has good spontaneous conception rate (96.2%) compared to those with lower EFI score (0-4) that conceived better with ART (60%) women with lower least function score has better outcome for spontaneous pregnancy (p<0.001).Conclusions: EFI scoring system is effective in predicting postoperative successful spontaneous pregnancy rates in the patients with endometriosis. In our study patients with higher EFI score achieved successful spontaneous pregnancy

Governing accelerating Universe via newly reconstructed Hubble parameter by employing empirical data simulations

A new parametrization of the phenomenological Hubble parameter is proposed to explore the issue of the cosmological landscape. The constraints on model parameters are derived through the Markov Chain Monte Carlo (MCMC) method by employing a comprehensive union of datasets such as 34 data points from cosmic chronometers (CC), 42 points from baryonic acoustic oscillations (BAO), a recently updated set of 1701 Pantheon$^+$ (P22) data points derived from Type Ia supernovae (SNeIa), and 162 data points from gamma-ray bursts (GRB). The kinematic behavior of the models is also investigated by encompassing the transition from deceleration to acceleration and the evolution of the jerk parameter. From the analysis of the parametric models, it is strongly indicated that the Universe is currently undergoing an accelerated phase. Furthermore, the models are compared by using the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC), so that a comparative assessment of model performance can be available.Comment: 17 pages, 6 figure

Calculating the impact of event using emotion detection.

Regardless of the extraordinary advancements in artificial intelligence, we are still far from having the capacity to normally associate with machines. Feature analysis in emotion recognition is significantly less concentrated than the facial recognition. In events like lectures and meetings, it is common for speakers to request feedback in the form of reviews; however, sometimes people do not have sufficient time to adequately write down all their opinions about the event. We suggest that using an AI system, it would be possible to assess an audience's emotional state over the course of an event without needing to ask them to write down their feedback