Zobrazeno 1 - 10
of 339
pro vyhledávání: '"P. M. Rao"'
Autor:
Sudhakar M. Rao
Publikováno v:
Discover Civil Engineering, Vol 1, Iss 1, Pp 1-13 (2024)
Abstract Because of their low embodied energy, recyclable nature, abundance of raw materials, and limited environmental impact, unstabilized adobes and earth mortars are preferred as earth building materials (EBMs). An ideal range of clay, sand, and
Externí odkaz:
https://doaj.org/article/d03d4b1ee50e4e2e826c9f423f6d78bf
Autor:
Raj Sahajanandan, A V Varsha, Vinay M. Rao, Ben B. Kurien, Korah Kuruvilla, Roy Thankachen, Madhu A. Philip
Publikováno v:
Annals of Cardiac Anaesthesia, Vol 27, Iss 4, Pp 330-336 (2024)
Objective: The need for reinstitution of intensive care unit (ICU) care (“recidivism”) in post-cardiac surgery patients is associated with increased morbidity, mortality, resource use, and healthcare costs. Recidivism is propounded as a quality i
Externí odkaz:
https://doaj.org/article/a5e05ef3e0f44726928094418a6601a7
Autor:
Peshal Karki, Rajasekhar Bhimireddi, Lokeswararao Dhavala, Anupama A V, Apparao M. Rao, Raja Karreddula, Anees A. Ansari
Publikováno v:
ACS Omega, Vol 9, Iss 43, Pp 43948-43955 (2024)
Externí odkaz:
https://doaj.org/article/762d26b4f4cf4f1b9da38b7e4665e2bf
Publikováno v:
Eurasian Chemico-Technological Journal, Vol 6, Iss 2, Pp 79-90 (2004)
The present investigation comprises of an attempt to investigate the titania supported chromia catalysts using X-ray diffraction measurements (XRD), evolved gas analysis (EGA), FT infrared spectroscopy (FTIR) and FT-Raman spectroscopic techniques wit
Externí odkaz:
https://doaj.org/article/b780bb5956df4b289b8cda1cf469be76
Autor:
Sowmya H. Rajashekar, Seema S. J., Swathi H. K., Prabhu C. Mishra, Praveen N. Somaiya, Yogitha M. Rao
Publikováno v:
Reproductive, Female and Child Health, Vol 3, Iss 3, Pp n/a-n/a (2024)
Abstract Introduction Previable premature rupture of membrane (PV‐PROM) is a complex clinical situation posing considerable risks to the foetus. There is an extreme paucity of management options and clear guidelines in the literature for this disma
Externí odkaz:
https://doaj.org/article/2f3573565e124d02bb84a7731ccecc67
Autor:
Reema M. Rao, Shovan Roy, Arnab Mondal, Jignesh Tate, K Bharath, Siva Kumar Pendyala, Pritee Pandey, Heena D. Tiwari
Publikováno v:
Journal of Pharmacy and Bioallied Sciences, Vol 16, Iss Suppl 3, Pp S2758-S2760 (2024)
Objective: The purpose of this research is to estimate the effectiveness of non-laser surgery and laser surgery in the management of periodontitis. Methods: One hundred participants with a chronic periodontitis diagnosis participated in a randomized
Externí odkaz:
https://doaj.org/article/7971afc7140f41bdad9e3a6533c16dcd
Publikováno v:
ACS Omega, Vol 9, Iss 8, Pp 9137-9146 (2024)
Externí odkaz:
https://doaj.org/article/ed9532a73a974de1a247e54328d7a697
Autor:
Gretchen B. Schober, Unaiza Uzair, Morgan Reel, Vigjna Abbaraju, Herbert Behlow, Apparao M. Rao, Sriparna Bhattacharya, Jeffrey N. Anker
Publikováno v:
Advanced Sensor Research, Vol 3, Iss 6, Pp n/a-n/a (2024)
Abstract A new hybrid ultrasound luminescent chemical imaging technique is described along with a pH sensor to image chemical concentrations at the surface of implanted medical devices. The purpose is to detect and study local biochemistry during inf
Externí odkaz:
https://doaj.org/article/a353d546808b4c25abfad08219587bed
Autor:
Prasanna Reddy Pulakurthi, Mahsa Mozaffari, Sohail A. Dianat, Jamison Heard, Raghuveer M. Rao, Majid Rabbani
Publikováno v:
IEEE Access, Vol 12, Pp 174222-174244 (2024)
Generative Adversarial Networks (GANs) have gained considerable attention owing to their impressive ability to generate high-quality, realistic images from a desired data distribution. This research introduces advancements in GANs by developing an im
Externí odkaz:
https://doaj.org/article/1fb4dd29d4384b6793a37c477452f191
Autor:
Junhao Zhang, Vishwanatha M. Rao, Ye Tian, Yanting Yang, Nicolas Acosta, Zihan Wan, Pin-Yu Lee, Chloe Zhang, Lawrence S. Kegeles, Scott A. Small, Jia Guo
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-10 (2023)
Abstract Schizophrenia is a chronic neuropsychiatric disorder that causes distinct structural alterations within the brain. We hypothesize that deep learning applied to a structural neuroimaging dataset could detect disease-related alteration and imp
Externí odkaz:
https://doaj.org/article/a4b05c2f97d943c087626eb390ea8efd