Some studies on products of Fuzzy soft graphs

In this paper, alpha, beta and gamma product of two fuzzy soft graphs are defined. The degree of a vertex in these product fuzzy soft graphs are determined and its regular properties are studied.

Evaluation of analgesic activity of the methanol extract from the galls of Quercus infectoria alone and as an adjuvant in wistar rats

Background: Non-steroidal anti-inflammatory drugs and opioids are the most preferred drugs for pain relief. Considering the gastrointestinal toxicity, dependence and other side effects, search for better analgesic drug continues. Quercus infectoria (QI) is from the family Fagaceae. The galls of QI are comprised of tannin (36 to 60%), gallic acid, ellagic acid, and syringic acid. They possess antioxidant, anti-inflammatory, antimicrobial, and anti-diabetic properties. In India, galls of QI have been used for the treatment of toothache, diarrhoea, sore throat and inflammatory diseases as a home remedy. This study was conducted to evaluate the analgesic activity of methanolic extract of galls of QI on wistar rats using tail-flick and Eddy’s hot-plate methods. The objective of the study was to evaluate the analgesic activity of methanolic extract of galls of QI alone and as an adjuvant with tramadol on Wistar rats.Methods: Total of 24 wistar rats were included in the study and divided into 4 groups. They received drugs intra-peritoneally as follows. In group 1, normal saline, in group 2, tramadol, in group 3, methanolic extract of galls of QI and in group 4, tramadol with methanolic extract of galls of QI was available.Results: Methanolic extract of galls of QI produced significant maximal possible analgesia (<0.001) at 30 and 60 minutes in tail-flick method whereas it failed to produce analgesia in hot-plate method during all time intervals.Conclusions: Methanolic extract of galls of QI showed analgesic activity in tail-flick method indicating that its possible mechanism of action is spinally mediated

Ensemble Machine Learning Model to Predict Benefaction of an Individual in the Health Sector

Ensemble methodis a machine learning technique that combines several base models in order to produce one optimal predictive model. This work aims to develop blood donor’s prediction model, for the management of the blood bank during emergency situations using ensemble method. The proposed model uses two supervised algorithms including multivariate regression and decision tree algorithms. An automated intelligent system is developed that learns from the data presented to the machine learning model to predict blood donors. The system is integrated with score allocation to the blood donors. A network of available ethical blood donors’ model has been developed which can be used in case of an emergency for an ailing person. Machine Learning techniques are used to find a perfect matched donor with respect to blood group, medical history and other demographics. A prioritized/ranked donor list based on their medical history, habits and other blood related metrics is generated to benefit the receivers. The ensemble methods used in this intelligent system helps in report generation facilitating medical experts and the society in decision making leading to increased number of donors

Effect of ranolazine on HbA1c and blood glucose levels in diabetic patients with chronic angina

Background: Diabetes mellitus is the fifth leading cause of death worldwide and is one of the common co-morbid conditions associated with coronary artery disease (CAD). The overall prevalence of CAD is 7.4% but the prevalence of CAD in diabetics is 9%. Hence treatment of hyperglycemia is a key goal of secondary preventive therapy with a target of reducing HbA1c to <7%. The risk of CAD has been reported to occur 2 to3 decades prior in diabetics compared to non-diabetics. Hence discovery of drugs with potential role in both diabetes and CAD seems to be necessary. Ranolazine is a novel oral anti anginal drug known to reduce HbA1c and fasting blood glucose levels in angina patients with diabetes. The objective of this study is to show the effect of ranolazine (antianginal drug) on HbA1c and fasting blood glucose levels in diabetic patients with chronic angina.Methods: Patients were divided into: Group 1 continued with previous antidiabetic drugs and antianginal drugs. Group 2 were prescribed Tab ranolazine 1000mg b.d (orally) as add on therapy along with previous antidiabetic drugs and antianginal drugs.Results: There was a significant reduction in HbA1c and FBS levels in Group 2 patients who were on ranolazine. Reduction of HbA1c in group1 and Group 2 was 0.21±0.65% and 1.30±1.16% respectively. Reduction of FBS in group1 and group2 was 10.66±27.80mg/dl and 29.97±31.49mg/dl respectively.Conclusions: From the present study we can conclude that ranolazine, an antianginal drug when given at a dose of 1000mg bd in diabetic patients with chronic angina reduces HbA1c and FBS levels.

Formaldehyde tracking in a histopathology laboratory in a medical college

Background: Formalin 10% is a fixative agent used in pathology laboratories. Formaldehyde released from formalin is a strong irritant and a carcinogen. The lab personnel are exposed to 10% formalin preserved surgical and post-mortem tissue samples during the visual examination and grossing. The present study aims to assess the exposure to formaldehyde in a histopathology laboratory unit as well as the effectiveness of existing engineering/ventilation systems. Methods: This is a cross-sectional study. Formalin levels were measured using portable air quality/pollution meter which measures formaldehyde (HCHO) in terms of mg/m3 in the morning, noon, and evening in different areas for one month. Areas of rooms and ventilation were mapped. The level of formalin was noted before, during, and after the grossing procedure and compared with the reference values given in the Occupational Safety and Health Administration (OSHA) and World Health Organisation (WHO). Results: Formaldehyde concentration ranged from 0.005 to 0.48 ppm (parts per million) in the grossing room and 0.002-0.010 ppm in the museum. Formaldehyde levels were highest in the morning and during grossing without using exhaust/ventilation and the levels reached minimum value within 15-20 minutes of switching on the existing control methods (exhaust fan of grossing station and opening of window panes). Conclusions: Formalin from the histology laboratories cannot be removed entirely but can be reduced sufficiently to lessen the risks to health by educating lab personnel and adopting appropriate control techniques

Fostering Proficiency in Cell Identification: A Comparative Analysis of Diagrams and Microscopic Images for Optimal Cytopathology Learning in Competency Based Medical Education Curriculum

Background: Histopathology and Cytopathology are crucial aspects of medical education. With a paradigm shift from traditional to competency-based curriculum, teaching strategies are crucial to enable learning. we undertook a comparative analysis to evaluate the efficacy of two distinct teaching Learning tools—diagrams and microscopic images—in enhancing the observational and cognitive skills of medical students. Material and methods: A mixed method research design was planned to obtain quantitative data followed by qualitative data. These were later integrated for interpretation. A series of thirty microscopic images of cells, from topics already taught and diagrams of the same cells, drawn with Hematoxylin Eosin pencils, were projected to assess cell identification. Students were tasked with identifying and documenting their observations. The microscopic images were sourced from standard textbooks, while the diagrams were prepared by faculty and validated by subject experts. Responses were evaluated and scores analyzed using paired t-test. Focus group discussion was conducted to obtain qualitative data. Results: A group of 74 second-year medical students voluntarily participated in this study. Statistical analysis revealed that the scores for diagram identification were significantly higher than those for microscopic images, with a p-value of less than 0.05. Diagrams had a positive impact. Conclusion: Diagrams were superior to microscopic images in facilitating cell identification. This study underscores the importance of incorporating drawing-based teaching and learning methods in cytology as they encourage a more profound and effective learning process. Continued inclusion of diagrams in medical education to enhance students' cell identification skills is recommended. Keywords: Cytopathology, Curriculum, Medical Education, Drawin

Structure and Magnetic Studies on UNiAlD2.2

Heavy fermion itinerant antiferromagnetic UNiAl is one of the very few U-containing compounds which absorbs H2/D2 without disproportionation. The present neutron diffraction studies on UNiAlDy (y = 2.2) are directed towards resolving controversies with regard to the occupancy of Ni atoms and the associated interstitial sites for (H/D) atoms, as well as the nature of magnetic ordering in the higher hydride phase with y ≥ 2. The fit to the neutron diffraction data is found to improve considerably if the Ni atoms originally lying in the U-atoms\u27 plane in UNiAl get shifted to the Ni-Al atoms\u27 plane in the deuteride. This is in agreement with an earlier neutron diffraction report on a deuteride sample of similar composition [T. Yamamoto et al., J. Alloys Compd. 269, 162 (1998)] and our x-ray structural studies on UNiAlH2.3 [P. Raj et al., Phys. Rev. B 63, 94414 (2001)], but differs from those of Bordallo et al., [H. N. Bordallo et al., Physica B 276-278, 706 (2000)] and of Kolomiets et al. [A. V. Kolomiets et al., J. Appl. Phys. 87, 6815 (2000)]. Our values of the structural parameters including the D-site occupancies are broadly in agreement with the results of Yamamoto et al. The magnetization studies on UNiAlD2.2 show a single antiferromagnetic transition with Néel temperature, TN=95 K. © 2001 American Institute of Physics

Aeroelastic testing of LCA wing models - Model fabrication - Ground testing - Wind tunnel testing and Data analysis

Aeroelastic Testing Programme of Scaled Aeroelastic model of LCA half wing with rigid fuselage

Efficient handling of Big Data Analytics in Densely Distributed Sensor Networks

Abstract The elaboration of wireless sensor networks has reached a point where each specific node of a network may store and convey a massive amount of (sensor-based information at once or terminated time). Hence in the forthcoming future, densely linked, enormously dynamic distributed sensor networks such as vehicle-2-vehicle communication setups may hold even greater knowledge potency. This is often due to the increase in node complexity. Subsequently, data volumes will become a problem for traditional data aggregation strategies traffic-wise as well as with regard to energy efficiency. For that reason, in this paper we suggest to call such scenarios as big data scenarios, they pose similar questions and problems as traditional big data concepts and granting the major focus mostly on business intelligence difficulties. Consequently our scheme would be propose an aggregation strategy tied to technological prerequisites which enable the efficient use of energy and the handling of large data volumes in an open source Hadoop frameworks with single/multi clustered architectures. Together with, we demonstrate the energy conservation potential based on experiments with actual sensor platforms in a distributed context