Zobrazeno 1 - 10
of 34
pro vyhledávání: '"K., Arpitha"'
Publikováno v:
National Journal of Laboratory Medicine, Vol 11, Iss 02, Pp 24-27 (2022)
Introduction: Most common carcinomas of lower urinary tract are of urothelial type in which, majority of them occur in the bladder. The demonstration of exfoliated neoplastic cells in urine sediment cytology is one of the choices of investigation.
Externí odkaz:
https://doaj.org/article/e3fb24b6f5224b3fbd2dd749db21f37a
Autor:
Pasha, Adil, C. M., Amulya, D., Anupriya, H. K., Arpitha, Jogin, Bhoomika, G., Pavithra, Manjunath, T. C.
Publikováno v:
Grenze International Journal of Engineering & Technology (GIJET); Jun2024, Vol. 10 Issue 2,Part1, p370-376, 7p
Publikováno v:
National Journal of Laboratory Medicine, Vol 10, Iss 3, Pp PO26-PO29 (2021)
Introduction: The Extra-Pulmonary Tuberculosis (EPTB) is challenging due to the pauci-bacillary nature of the disease and limited tests available for early diagnosis. It is the most common extrapulmonary manifestation of tuberculosis. The samples
Externí odkaz:
https://doaj.org/article/9491940e6d984b15b39ed7cda358a1e9
Publikováno v:
International Journal for Research in Applied Science and Engineering Technology. 10:448-453
Endophytic fungi are those living inside the host plant without causing any apparent negative effect on the host plant. 117 isolates of endophytic fungi were isolated from the leaves, stem and flower of Clerodendrum thomsoniae. Collected from differe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9c6ad0194679b2c943d320bb0f4a9362
https://doi.org/10.22214/ijraset.2022.47353
https://doi.org/10.22214/ijraset.2022.47353
Autor:
Sirasagi, Anilkumar1, K., Arpitha2, Neeha, Saara3, Pattar, Pratima Manohar4 pratimapattar@gmail.com
Publikováno v:
Asian Journal of Medical Sciences. Aug2021, Vol. 12 Issue 8, p144-148. 5p.
Publikováno v:
Journal of Computational and Theoretical Nanoscience. 17:4294-4298
This paper intends to use distinct machine learning algorithms and exploring its multi-features. The primary advantage of machine learning is, a machine learning algorithm can predict its work automatically by learning what to do with information. Th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4a28498c0e168cdda680585bbe0e3300
https://doi.org/10.1166/jctn.2020.9064
https://doi.org/10.1166/jctn.2020.9064
Autor:
Eguru Sreenivasa Rao, K. Arpitha, G. M. Sandeepkumar, Muttanna Revadi, Sourav Mahapatra, K. N. Avinash, Siddharood Maragal
Publikováno v:
Indian Phytopathology. 73:361-365
Vine decline or sudden wilt caused by a complex of pathogens with unknown etiology is emerging as most destructive disease of watermelon in the southern part of India. In this direction ICAR-IIHR, has identified a prebred line derived from Citrullus
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::06723ee095d5eb4e142db6cea241c63b
https://doi.org/10.1007/s42360-020-00197-z
https://doi.org/10.1007/s42360-020-00197-z
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
NATIONAL JOURNAL OF LABORATORY MEDICINE.
Introduction: The Extrapulmonary Tuberculosis (EPTB) is challenging due to the pauci-bacillary nature of the disease and limited tests available for early diagnosis. It is the most common extrapulmonary manifestation of tuberculosis. The samples from
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3ee2a595d705c03b49d5dfd862415ad5
https://doi.org/10.7860/njlm/2021/47991.2498
https://doi.org/10.7860/njlm/2021/47991.2498
Autor:
K. Arpitha Nagesh, D. R. Shilpa
Publikováno v:
Lecture Notes in Electrical Engineering ISBN: 9789811602740
There has always been a need to transmit data since the computer’s inception. When data is sent out of the network, it will require cable sizes to carry the data. To ease the data transmission protocols, cabling scheme, and serial communication was
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9c350505ff29b647d0594a15f7e373fd
https://doi.org/10.1007/978-981-16-0275-7_49
https://doi.org/10.1007/978-981-16-0275-7_49
