Evaluation of abnormal uterine bleeding with transvaginal sonography and hysteroscopy in perimenopausal women

Background: Abnormal uterine bleeding is defined as any deviation from the normal menstrual cycle this include change in regularity, frequency of menses, duration or amount of bleeding during or in between periods. Objective of present study was to evaluate abnormal uterine bleeding with transvaginal sonography and hysteroscopy in perimenopausal women.Methods: This study is conducted on women presenting to the gynecological OPD with complain of abnormal uterine bleeding in perimenopausal age group. A total of 50 patients were subjected to transvaginal sonography and Diagnostic hysteroscopy.Results: On TVS, out of total 50 patients, 50% patient showed normal endometrial finding. 24% Patient showed Endometrial hyperplasia, 14% Endometrial Polyp, 8% Submucosal fibroid, 4% Adenomyosis. On TVS, out of total 50 patient, 50% patient showed normal endometrial finding. 24% Patient showed endometrial hyperplasia, 14% endometrial Polyp, 8% submucosal fibroid, 4% adenomyosis. Out of total 50 patients, 28 (56%) showed normal endometrial finding.20% cases showed endometrial Hyperplasia, 16% showed endometrial Polyp, 8% showed submucosal fibroid. Sensitivity, specificity, PPV, NPV of endometrial hyperplasia – 81.81%, 92.3%, 75%, 94.73% respectively.Conclusions: Transvaginal sonography has a moderate diagnostic accuracy in detecting endometrial hyperplasia and other intrauterine pathology. TVS is safe, acceptable and easily available & is noninvasive. It should be used as 1st line diagnostic tool in patients with AUB in perimenopausal women. Hysteroscopy has important tool in the diagnosis of various endometrial and intrauterine lesions TVS and hysteroscopy should be employed hand in hand in evaluation of AUB

Evaluation of TCSC Power flow control Capability

In an A.C Transmission system power flow can be controlled by injecting a compensating voltage in series with the line. Thyristor Controlled series compensators (TCSC) are utilized as a conventional means for the purpose. This paper utilizes the steady state model of Thyristor controlled series capacitor and a unified power flow controller for series voltage compensation, and evaluating their range of power flow control for simple network. The models are incorporated into the existing Newton Raphson load flow algorithm. The iterative equations of the Newton Raphson load flow algorithm are modified by the device parameters and the combined set of power flow equations and the TCSC control equations are solved for convergence of the formula. Matlab codes are utilized for the implementation of the devices in the Newton-Raphson algorithm. Power flow control ranges are evaluated for standard 5 bus system. Results are reported and studies are presented to illustrate the power flow capabilities of TCSC. Keywords: Converters, Control Strategy, MATLAB, Newton Raphson algorithm, Power flow, TCS

Study of comparison of transvaginal cervical length and Bishop score in predicting successful labour induction- a prospective study from a tertiary care hospital of Rajasthan

Background: Labor induction is one of the common interventions in obstetric practice. Assessment of cervix has been used as a predictor of the successful vaginal delivery. The traditional method of predicting whether an induced labour will result in successful vaginal delivery is based on the pre induction favourability of cervix as assessed by the Bishop score. Now we used transvaginal sonography (TVS) as an objective method of assessment of cervical length to evaluate the role of the pre-induction transvaginal ultrasonographic (TVS) cervical length in predicting labour outcome and comparing it to the Bishop score in patients undergoing induction of labour. Methods: This observational prospective study included 100 pregnant women in which induction of labour was performed at 37-42 weeks of gestation. Cervical length on transvaginal ultrasound and bishop score by digital examination is assessed prior to induction in cases according to standard protocol. Results: In our study though the sensitivity of the Bishop score in predicting the successful labour induction was higher (75.6%) compared with that of cervical length measured trans vaginally (69.35%). The specificity and positive predictive value for the cervical length (2.7 cm) was 77.78% and 91.49% compared with the Bishop score (4) 55.55% and 81.82% respectively. Conclusions: Bishop score and transvaginal cervical length both are good predictors of successful induction of labour. Transvaginal cervical length provides a better prediction of the likelihood of vaginal delivery within 24 hours of induction

Synthesis and characterization of carbamates derivatives from 4-amino-1,2,4-triazole

Carbamate derivatives are proved to be an essential class of molecules because of their application as drugs and prodrugs. Their several derivatives also have been used to craft the drug-target interfaces by incorporating the carbamate moiety. Due to the huge demand in pharma-industries these have been extensively explored and synthesized. The synthesis and characterization of carbamate derivatives from 4-amino-1,2,4-triazoles and 3-(methylthio)-4-amino-1,2,4-triazoles are described. Carbamate derivatives of 4-amino-1,2,4-triazoles with phenyl chloroformate in CH3CN using K2CO3 at ca. ~80°C have been synthesized with good to excellent yield (~81 to 97%). The methodology has been subsequently extended for synthesis of carbamate derivatives of 3-(methylthio)-4-amino-1,2,4-triazoles in which bicarbamate derivatives are formed as major products (~39 to 47%) along with mono carbamate derivatives as minor products (~9 to 22%) in the presence of similar solvent and base. On investigating the effect of solvent and base, the reaction in CH3CN in presence of K2CO3 shows the best results

Exploration of Indian traditional recipe “Tarvaani” from the drained rice gruel for nutritional and probiotic potential

Study background: Traditional fermented foods are the source of probiotic bacteria which can be envisaged as formulation ingredients in various food and beverages. Scope and approach: The present research aimed to explore one of the Indian traditional recipes, “Tarvaani,” for nutritional and probiotic potential as a part of its healthy perspectives. Main findings and conclusion: The traditional recipe was found to contain the lactic acid bacteria and isolated. The isolated product showed prominent curdling activity after 48 h, and bacterial growth was seen in all the pH (pH 3–7) tested. The antibiotic susceptibility test found that streptomycin, vancomycin, and kanamycin were resistant to the bacterial culture, and imipenem, gentamycin, rifampicin, and tetracycline were found to be resistant susceptible to the bacterial culture according to zone diameter interpretative criteria given in ICMR SOP 2015. A clear halo zone around the tested colony was obtained in the amylase test, which indicated that starch was degraded and α-amylase was produced. The culture also showed prominent antimicrobial action and inhibited the growth of the pathogenic strains tested by a well-diffusion assay. Moreover, the isolates only showed no haemolysis activity after incubation at 30 ◦C for 24 h under anaerobic conditions. Overall, the present research findings showcase the nutritional and probiotic potential of Lactobacillus sp. of “Tarvaani” as a viable option as a formulation ingredient in traditional-based functional foodsUniversidade de Vigo/CISU

Bayesian parameter inference for shallow subsurface modeling using field data and impacts on geothermal planning

Understanding the subsurface is crucial in building a sustainable future, particularly for urban centers. Importantly, the thermal effects that anthropogenic infrastructure, such as buildings, tunnels, and ground heat exchangers, can have on this shared resource need to be well understood to avoid issues, such as overheating the ground, and to identify opportunities, such as extracting and utilizing excess heat. However, obtaining data for the subsurface can be costly, typically requiring the drilling of boreholes. Bayesian statistical methodologies can be used towards overcoming this, by inferring information about the ground by combining field data and numerical modeling, while quantifying associated uncertainties. This work utilizes data obtained in the city of Cardiff, UK, to evaluate the applicability of a Bayesian calibration (using GP surrogates) approach to measured data and associated challenges (previously not tested) and to obtain insights on the subsurface of the area. The importance of the data set size is analyzed, showing that more data are required in realistic (field data), compared to controlled conditions (numerically-generated data), highlighting the importance of identifying data points that contain the most information. Heterogeneity of the ground (i.e., input parameters), which can be particularly prominent in large-scale subsurface domains, is also investigated, showing that the calibration methodology can still yield reasonably accurate results under heterogeneous conditions. Finally, the impact of considering uncertainty in subsurface properties is demonstrated in an existing shallow geothermal system in the area, showing a higher than utilized ground capacity, and the potential for a larger scale system given sufficient demand

Bayesian parameter inference for shallow subsurface modeling using field data and impacts on geothermal planning

Understanding the subsurface is crucial in building a sustainable future, particularly for urban centers. Importantly, the thermal effects that anthropogenic infrastructure, such as buildings, tunnels, and ground heat exchangers, can have on this shared resource need to be well understood to avoid issues, such as overheating the ground, and to identify opportunities, such as extracting and utilizing excess heat. However, obtaining data for the subsurface can be costly, typically requiring the drilling of boreholes. Bayesian statistical methodologies can be used towards overcoming this, by inferring information about the ground by combining field data and numerical modeling, while quantifying associated uncertainties. This work utilizes data obtained in the city of Cardiff, UK, to evaluate the applicability of a Bayesian calibration (using GP surrogates) approach to measured data and associated challenges (previously not tested) and to obtain insights on the subsurface of the area. The importance of the data set size is analyzed, showing that more data are required in realistic (field data), compared to controlled conditions (numerically-generated data), highlighting the importance of identifying data points that contain the most information. Heterogeneity of the ground (i.e., input parameters), which can be particularly prominent in large-scale subsurface domains, is also investigated, showing that the calibration methodology can still yield reasonably accurate results under heterogeneous conditions. Finally, the impact of considering uncertainty in subsurface properties is demonstrated in an existing shallow geothermal system in the area, showing a higher than utilized ground capacity, and the potential for a larger scale system given sufficient demand

Associations of clinical, psychological, and sociodemographic characteristics and ecological momentary assessment completion in the 10-week Hypo- METRICS study:Hypoglycaemia MEasurements ThResholds and ImpaCtS

Introduction: Reporting of hypoglycaemia and its impact in clinical studies is often retrospective and subject to recall bias. We developed the Hypo-METRICS app to measure the daily physical, psychological, and social impact of hypoglycaemia in adults with type 1and insulin-treated type 2 diabetes in real-time using ecological momentary assessment(EMA). To help assess its utility, we aimed to determine Hypo-METRICS app completion rates and factors associated with completion.Methods: Adults with diabetes recruited into the Hypo-METRICS study were given validated patient-reported outcome measures (PROMs) at baseline. Over 10 weeks, they wore a blinded continuous glucose monitor (CGM), and were asked to complete three daily EMAs about hypoglycaemia and aspects of daily functioning, and two weekly sleep and productivity PROMs on the bespoke Hypo-METRICS app. We conducted linear regression to determine factors associated with app engagement, assessed by EMA and PROM completion rates and CGM metrics.Results: In 602 participants (55% men; 54% type 2 diabetes; median(IQR) age 56 (45-66)years; diabetes duration 19 (11-27) years; HbA1c 57 (51-65) mmol/mol), median(IQR)overall app completion rate was 91 (84-96)%, ranging from 90 (81-96)%, 89 (80-94)% and94(87-97)% for morning, afternoon and evening check-ins, respectively. Older age, routine CGM use, greater time below 3.0 mmol/L, and active sensor time were positively associated with app completion.Discussion: High app completion across all app domains and participant characteristics indicates the Hypo-METRICS app is an acceptable research tool for collecting detailed data on hypoglycaemia frequency and impact in real-time

Associations of clinical, psychological, and sociodemographic characteristics and ecological momentary assessment completion in the 10-week Hypo- METRICS study:Hypoglycaemia MEasurements ThResholds and ImpaCtS

Introduction: Reporting of hypoglycaemia and its impact in clinical studies is often retrospective and subject to recall bias. We developed the Hypo-METRICS app to measure the daily physical, psychological, and social impact of hypoglycaemia in adults with type 1and insulin-treated type 2 diabetes in real-time using ecological momentary assessment(EMA). To help assess its utility, we aimed to determine Hypo-METRICS app completion rates and factors associated with completion.Methods: Adults with diabetes recruited into the Hypo-METRICS study were given validated patient-reported outcome measures (PROMs) at baseline. Over 10 weeks, they wore a blinded continuous glucose monitor (CGM), and were asked to complete three daily EMAs about hypoglycaemia and aspects of daily functioning, and two weekly sleep and productivity PROMs on the bespoke Hypo-METRICS app. We conducted linear regression to determine factors associated with app engagement, assessed by EMA and PROM completion rates and CGM metrics.Results: In 602 participants (55% men; 54% type 2 diabetes; median(IQR) age 56 (45-66)years; diabetes duration 19 (11-27) years; HbA1c 57 (51-65) mmol/mol), median(IQR)overall app completion rate was 91 (84-96)%, ranging from 90 (81-96)%, 89 (80-94)% and94(87-97)% for morning, afternoon and evening check-ins, respectively. Older age, routine CGM use, greater time below 3.0 mmol/L, and active sensor time were positively associated with app completion.Discussion: High app completion across all app domains and participant characteristics indicates the Hypo-METRICS app is an acceptable research tool for collecting detailed data on hypoglycaemia frequency and impact in real-time