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&ndash;2021 and 2021&ndash;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