@article{bhandari_shaktawat_tak_shukla_gupta_patel_kakkar_dube_dia_dia_et al._2021, title={Evaluating interactions between hyperglycemia and clotting factors in patients suffering with SARS-CoV-2 infection}, volume={10}, ISSN={["2450-8187"]}, DOI={10.5603/DK.a2021.0022}, abstractNote={Background. With coronavirus disease-19 (COVID-19), patients with diabetes mellitus are dealing with two pandemics and are at a higher risk of mortality. The present study was undertaken to evaluate interactions between hyperglycemia and clotting factors in COVID-19 patients. Methods. In this retrospective observational study,  53 real-time RT-PCR SARS-CoV-2 positive cases in 40 to 70 years of age, representing both sexes, were enrolled in the study from SMS Medical College, Jaipur (Rajasthan, India). Based on their history of diabetes mellitus and exclusion criterion, patients were divided into diabetics (N = 11) and non-diabetics (N = 17) groups. The data on clinical profile and coagulation profile was recorded along with the markers of inflammation and infection. The two groups were compared using the Mann-Whitney test and the Fisher’s exact test. Correlation coefficients between clotting factors were compared between two groups using Student t test. Results. There was no significant difference in age  (p = 0.25) or gender (p = 0.12) between the two groups. The coagulation indicators FDP (p = 0.79), D-dimer  (p = 0.30), APPT (p = 0.96), PT (p = 0.79), INR (p = 1.00)  PLT (p = 0.17) and the markers of inflammation and infection did not differ significantly between the two groups. There was no significant difference in correlation coefficients among coagulation indicators between the two groups (p > 0.05). Conclusion. The study concludes that pathogenesis in clotting system is not significantly different in stud-ied groups. Further research is needed to explain the higher mortality in diabetic patients suffering from COVID-19.}, number={1}, journal={CLINICAL DIABETOLOGY}, author={Bhandari, Sudhir and Shaktawat, Ajit Singh and Tak, Amit and Shukla, Jyotsna and Gupta, Jitendra and Patel, Bhoopendra and Kakkar, Shivankan and Dube, Amitabh and Dia, Sunita and Dia, Mahendra and et al.}, year={2021}, pages={114–122} }
 @article{bhandari_tak_singhal_shukla_shaktawat_gupta_patel_kakkar_dube_dia_et al._2020, title={Patient Flow Dynamics in Hospital Systems During Times of COVID-19: Cox Proportional Hazard Regression Analysis}, volume={8}, ISSN={["2296-2565"]}, DOI={10.3389/fpubh.2020.585850}, abstractNote={Objectives: The present study is aimed at estimating patient flow dynamic parameters and requirement for hospital beds. Second, the effects of age and gender on parameters were evaluated.}, journal={FRONTIERS IN PUBLIC HEALTH}, author={Bhandari, Sudhir and Tak, Amit and Singhal, Sanjay and Shukla, Jyotsna and Shaktawat, Ajit Singh and Gupta, Jitendra and Patel, Bhoopendra and Kakkar, Shivankan and Dube, Amitabh and Dia, Sunita and et al.}, year={2020}, month={Dec} }
 @article{mohan_silva_klauberg_jat_catts_cardil_hudak_dia_2017, title={Individual Tree Detection from Unmanned Aerial Vehicle (UAV) Derived Canopy Height Model in an Open Canopy Mixed Conifer Forest}, volume={8}, ISSN={["1999-4907"]}, DOI={10.3390/f8090340}, abstractNote={Advances in Unmanned Aerial Vehicle (UAV) technology and data processing capabilities have made it feasible to obtain high-resolution imagery and three dimensional (3D) data which can be used for forest monitoring and assessing tree attributes. This study evaluates the applicability of low consumer grade cameras attached to UAVs and structure-from-motion (SfM) algorithm for automatic individual tree detection (ITD) using a local-maxima based algorithm on UAV-derived Canopy Height Models (CHMs). This study was conducted in a private forest at Cache Creek located east of Jackson city, Wyoming. Based on the UAV-imagery, we allocated 30 field plots of 20 m × 20 m. For each plot, the number of trees was counted manually using the UAV-derived orthomosaic for reference. A total of 367 reference trees were counted as part of this study and the algorithm detected 312 trees resulting in an accuracy higher than 85% (F-score of 0.86). Overall, the algorithm missed 55 trees (omission errors), and falsely detected 46 trees (commission errors) resulting in a total count of 358 trees. We further determined the impact of fixed tree window sizes (FWS) and fixed smoothing window sizes (SWS) on the ITD accuracy, and detected an inverse relationship between tree density and FWS. From our results, it can be concluded that ITD can be performed with an acceptable accuracy (F > 0.80) from UAV-derived CHMs in an open canopy forest, and has the potential to supplement future research directed towards estimation of above ground biomass and stem volume from UAV-imagery.}, number={9}, journal={FORESTS}, author={Mohan, Midhun and Silva, Carlos Alberto and Klauberg, Carine and Jat, Prahlad and Catts, Glenn and Cardil, Adrian and Hudak, Andrew Thomas and Dia, Mahendra}, year={2017}, month={Sep} }