6 research outputs found
Reporting ethical processes in two Indian journals
Background: In biomedical journals, authors are expected to report if
the study was carried out in accordance with international and national
ethical guidelines and inform readers if approval from ethics committee
was obtained and if written informed consent was taken from the
participant or legal guardian. Aims: To determine the proportion of
research manuscripts in two pediatric journals published from India
reporting on ethical clearance, obtaining of informed consent and/or
assent. Settings and Design: Retrospective study for analysis of
research articles published. Materials and Methods : Research articles
published in the issues of Indian Pediatrics and Indian Journal of
Pediatrics in 2006 were reviewed for reporting regarding ethical
clearance, obtaining written informed consent from guardians or
parents, and obtaining assent from research participants. Statistical
Analysis Used: Descriptive statistics was used. The number of articles
according to their types; the number of research designs employed
according to their types; and the number of research studies mentioning
ethical clearance, consent, and assent were expressed as percentages
mentioning ethical clearance, consent and assent were expressed as
percentages. Results: Of the 132 manuscripts reporting biomedical
research, 39 (29.53%) reported having obtained approval from the ethics
committee. Forty-six of the 98 (46.94%) manuscripts reporting on
prospective studies indicated that informed consent was obtained from
parents or lawful guardians. Neither ethical approval nor informed
consent was mentioned in 45 (34.10%) published articles reporting
prospective studies. A total of 54/98 (55.1%) studies enrolled children
aged 7 years or more and hence were assessed for reporting of assent;
eight (14.81%) reported that children′s assent was obtained. Only
four (7.41%) eligible studies reported ethics committee′s
approval, informed consent, as well as assent. Conclusions: A
significant proportion of research articles published in the two
pediatric journals did not provide information regarding ethical
approval, written informed consent, and obtaining of assent
Synthesis and characterization of polyimides and co-polyimides having pendant benzoic acid moiety
A novel diamine monomer, 2,4-diamino-4'-carboxy diphenyl ether had been synthesized. Several polyimides were prepared by reacting this diamine with commercially available dianhydrides, such as benzophenone tetracarboxylic acid dianhydride (BTDA), 4,4'-bis{hexafluoroisopropylidene bis (phthalic anhydride)}(6-FDA), oxydiphthalic anhydride (ODPA) and 3,3',4,4'-biphenyltetracarboxylic acid dianhydride (BPDA). Furthermore, copolymers from the resulting diamine and oxydianiline (ODA) with 6 FDA were also synthesized. The inherent viscosities of the polymers were 0.42-0.67 dl g<SUP>−1</SUP>. The polymers have good solubility in polar aprotic solvents, high thermal stability up to 410 °C in nitrogen and high glass transition temperatures (T<SUB>g</SUB>) ranging from 260-330 ° C. These polymers formed tough flexible films by solution casting
Operational Probabilistic Fog Prediction Based on Ensemble Forecast System: A Decision Support System for Fog
One of the well-known challenges of fog forecasting is the high spatio-temporal variability of fog. An ensemble forecast aims to capture this variability by representing the uncertainty in the initial/lateral boundary conditions (ICs/BCs) and model physics. The present study highlights a new operational Ensemble Forecast System (EFS) developed by the Indian Institute of Tropical Meteorology (IITM), Pune, to predict the fog over the Indo-Gangetic Plain (IGP) region using the visibility (Vis) diagnostic algorithm. The EFS framework comprises the WRF model with a 4 km horizontal resolution, initialized by 21 ICs/BCs. The advantages of probabilistic fog forecasting have been demonstrated by comparing control (CNTL) and ensemble-based fog forecasts. The forecast is verified using fog observations from the Indira Gandhi International (IGI) airport during the winter months of 2020–2021 and 2021–2022. The results show that with a probability threshold of 50%, the ensemble forecasts perform better than the CNTL forecasts. The skill scores of EFS are relatively promising, with a Hit Rate of 0.95 and a Critical Success Index of 0.55; additionally, the False Alarm Rate and Missing Rate are low, with values of 0.43 and 0.04, respectively. The EFS could correctly predict more fog events (37 out of 39) compared with the CNTL forecast (31 out of 39) and shows the potential skill. Furthermore, EFS has a substantially reduced error in predicting fog onset and dissipation (mean onset and dissipation error of 1 h each) compared to the CNTL forecasts
Operational Probabilistic Fog Prediction Based on Ensemble Forecast System: A Decision Support System for Fog
One of the well-known challenges of fog forecasting is the high spatio-temporal variability of fog. An ensemble forecast aims to capture this variability by representing the uncertainty in the initial/lateral boundary conditions (ICs/BCs) and model physics. The present study highlights a new operational Ensemble Forecast System (EFS) developed by the Indian Institute of Tropical Meteorology (IITM), Pune, to predict the fog over the Indo-Gangetic Plain (IGP) region using the visibility (Vis) diagnostic algorithm. The EFS framework comprises the WRF model with a 4 km horizontal resolution, initialized by 21 ICs/BCs. The advantages of probabilistic fog forecasting have been demonstrated by comparing control (CNTL) and ensemble-based fog forecasts. The forecast is verified using fog observations from the Indira Gandhi International (IGI) airport during the winter months of 2020–2021 and 2021–2022. The results show that with a probability threshold of 50%, the ensemble forecasts perform better than the CNTL forecasts. The skill scores of EFS are relatively promising, with a Hit Rate of 0.95 and a Critical Success Index of 0.55; additionally, the False Alarm Rate and Missing Rate are low, with values of 0.43 and 0.04, respectively. The EFS could correctly predict more fog events (37 out of 39) compared with the CNTL forecast (31 out of 39) and shows the potential skill. Furthermore, EFS has a substantially reduced error in predicting fog onset and dissipation (mean onset and dissipation error of 1 h each) compared to the CNTL forecasts