Zobrazeno 1 - 10
of 16 138
pro vyhledávání: '"PALLAVI P."'
Autor:
Peng Pan, Michael Zoberman, Pengsong Zhang, Sharanja Premachandran, Sanjana Bhatnagar, Pallavi P. Pilaka-Akella, William Sun, Chengyin Li, Charlotte Martin, Pengfei Xu, Zefang Zhang, Ryan Li, Wesley Hung, Hua Tang, Kailynn MacGillivray, Bin Yu, Runze Zuo, Karinna Pe, Zhen Qin, Shaojia Wang, Ang Li, W. Brent Derry, Mei Zhen, Arneet L. Saltzman, John A. Calarco, Xinyu Liu
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-15 (2024)
Abstract The nematode Caenorhabditis elegans is widely employed as a model organism to study basic biological mechanisms. However, transgenic C. elegans are generated by manual injection, which remains low-throughput and labor-intensive, limiting the
Externí odkaz:
https://doaj.org/article/b503551c7f214a86a2d6655e303a67ea
Autor:
Kunzes Dolma, Anu Sumi Issac, Renuka Gupta, Surya Kumari Achanta, Pallavi P. Channe, Oruganti Venkata Ramanand, Anil Managutti
Publikováno v:
Journal of Pharmacy and Bioallied Sciences, Vol 16, Iss Suppl 3, Pp S2443-S2445 (2024)
Background: Salivary gland tumors (SGTs) present a diagnostic challenge due to their diverse histological subtypes and variable clinical behavior. Methods: This research conducted a retrospective analysis of SGT cases diagnosed and managed at a terti
Externí odkaz:
https://doaj.org/article/335ca7a30d1d416385c7b4b3ddf534d7
Publikováno v:
Frontiers in Molecular Neuroscience, Vol 16 (2023)
Liquid–liquid phase separation results in the formation of dynamic biomolecular condensates, also known as membrane-less organelles, that allow for the assembly of functional compartments and higher order structures within cells. Multivalent, rever
Externí odkaz:
https://doaj.org/article/abf44a10f4c84500aad90165c5ae09c1
An analytical study of second harmonic generation due to the interaction of radially polarized laser beam with homogeneous and unmagnetized plasma is presented. The analytical study is based on Lorentz force, continuity and electromagnetic wave equat
Externí odkaz:
http://arxiv.org/abs/2412.15340
Autor:
Jones, Caitlin, Kraus, Nico, Bhardwaj, Pallavi, Adler, Maximilian, Schrödl-Baumann, Michael, Manrique, David Zambrano
Time series forecasting is a valuable tool for many applications, such as stock price predictions, demand forecasting or logistical optimization. There are many well-established statistical and machine learning models that are used for this purpose.
Externí odkaz:
http://arxiv.org/abs/2412.13878
Autor:
Kumar, Vinay, Bhat, Pallavi
Magnetic reconnection, a fundamental plasma process, is pivotal in understanding energy conversion and particle acceleration in astrophysical systems. While extensively studied in two-dimensional (2D) configurations, the dynamics of reconnection in t
Externí odkaz:
http://arxiv.org/abs/2412.10065
Pre-trained vision-language models (VLMs), such as CLIP, demonstrate impressive zero-shot classification capabilities with free-form prompts and even show some generalization in specialized domains. However, their performance on satellite imagery is
Externí odkaz:
http://arxiv.org/abs/2412.08536
We present analytical and simulation study of twisted terahertz (THz) radiation generation via propagation of a circularly polarized Laguerre Gaussian (LG) laser pulse in homogeneous plasma embedded in an axial magnetic field. Analytical formulation
Externí odkaz:
http://arxiv.org/abs/2411.06189
Autor:
Pan, Hongyi, Hong, Ziliang, Durak, Gorkem, Keles, Elif, Aktas, Halil Ertugrul, Taktak, Yavuz, Medetalibeyoglu, Alpay, Zhang, Zheyuan, Velichko, Yury, Spampinato, Concetto, Schoots, Ivo, Bruno, Marco J., Tiwari, Pallavi, Bolan, Candice, Gonda, Tamas, Miller, Frank, Keswani, Rajesh N., Wallace, Michael B., Xu, Ziyue, Bagci, Ulas
Accurate classification of Intraductal Papillary Mucinous Neoplasms (IPMN) is essential for identifying high-risk cases that require timely intervention. In this study, we develop a federated learning framework for multi-center IPMN classification ut
Externí odkaz:
http://arxiv.org/abs/2411.05697
Autor:
Pan, Hongyi, Durak, Gorkem, Zhang, Zheyuan, Taktak, Yavuz, Keles, Elif, Aktas, Halil Ertugrul, Medetalibeyoglu, Alpay, Velichko, Yury, Spampinato, Concetto, Schoots, Ivo, Bruno, Marco J., Keswani, Rajesh N., Tiwari, Pallavi, Bolan, Candice, Gonda, Tamas, Goggins, Michael G., Wallace, Michael B., Xu, Ziyue, Bagci, Ulas
Federated learning (FL) enables collaborative model training across institutions without sharing sensitive data, making it an attractive solution for medical imaging tasks. However, traditional FL methods, such as Federated Averaging (FedAvg), face d
Externí odkaz:
http://arxiv.org/abs/2410.22530