Results 71 to 80 of about 213,098 (343)

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

Turbulence effects on warm-rain formation in precipitating shallow convection revisited [PDF]

Atmospheric Chemistry and Physics, 2016
Two different collection kernels which include turbulence effects on the collision rate of liquid droplets are used as a basis to develop a parameterization of the warm-rain processes autoconversion, accretion, and self-collection.
A. Seifert, R. Onishi
doaj   +1 more source

Model‐Inversion‐Resistant Physical Unclonable Neural Network Using Vertical NAND Flash Memory

Advanced Science, EarlyView.
Schematic and key features of the proposed forward‐forward physical unclonable neural network (FF‐PUNN), incorporating a concealable physical unclonable function (PUF) layer and forward‐forward (FF) learning. ABSTRACT The growing use of neural networks in privacy‐sensitive applications necessitates architectures that inherently protect both data and ...
Sung‐Ho Park, Ryun‐Han Koo, Jonghyun Ko, Jiseong Im, Yeongheon Yang, Mingyun Oh, Dongbeen Shin, Gyuweon Jung, Jong‐Ho Lee   +8 more
wiley   +1 more source

A Machine‐Learning‐Assisted Stochastic Cloud Population Model as a Parameterization of Cumulus Convection

Journal of Advances in Modeling Earth Systems, 2022
A machine‐learning‐assisted stochastic cloud population model is coupled with the Advanced Research Weather Research and Forecasting (WRF) model to represent fluctuations in the cloud‐base mass flux associated with the life cycles and interactions among ...
Samson Hagos, Jingyi Chen, Katelyn Barber, Koichi Sakaguchi, Robert S. Plant, Zhe Feng, Heng Xiao   +6 more
doaj   +1 more source

Performance of cumulus parameterization schemes in the simulation of Indian Summer Monsoon using RegCM4

, 2017
The Indian Summer Monsoon (ISM) is driven by organized large-scale convection; hence, its simulation is expected to depend on an appropriate representation of cumulus convection in the model.
S. Maity, M. Mandal, S. Nayak, R. Bhatla
semanticscholar   +1 more source

Distinct Biotypes of Visual Perception in Major Depressive Disorder

Advanced Science, EarlyView.
In a discover dataset (272 acute MDD patients), this work identifies a novel depression biotype characterized by impaired visual motion perception, using machine learning clustering. An independent dataset confirms the robustness of this biotype through cross‐validation and demonstrates its generalizability.
Zhuoran Cai, Xi‐Wen Hu, Yuyang Li, Zheng Lin, Yongjie Li, Yong‐Chun Cai, Tao Xu, Ke Jia, Jin‐Fang Han, Zhong‐Lin Tan, Dezhong Yao, Xue Mei Song, Sugai Liang, Georg Northoff   +13 more
wiley   +1 more source

Differences in Sandy forecasts due to cumulus parameterization [PDF]

Eos, Transactions American Geophysical Union, 2014
One reason for Hurricane Sandy's noteworthy impact was a discrepancy in its forecasting. Scientists knew of the hurricane days before it made landfall, but two different models consistently made two different predictions for its track. One week in advance of the actual landfall, the European Centre for Medium‐Range Weather Forecasts (ECMWF) predicted ...
openaire   +1 more source

What determines the distribution of shallow convective mass flux through cloud base?

, 2017
The distribution of cloud-base mass flux is studied using large-eddy simulations (LES) of two reference cases, one representing conditions over the tropical ocean, and another one representing mid-latitude conditions over land.
Hohenegger, Cathy, Sakradzija, Mirjana
core   +1 more source

On the computation of moist-air specific thermal enthalpy [PDF]

, 2014
The specific thermal enthalpy of a moist-air parcel is defined analytically following a method in which specific moist entropy is derived from the Third Law of thermodynamics.
Ambaum, Arakawa, Bannon, Bechtold, Betts, Betts, Betts, Bohren, Bougeault, Bretherton, Bretherton, Businger, Catry, Chase, Cuijpers, De Groot, Derbyshire, Dufour, Emanuel, Emanuel, Fagerstroem, Feistel, Fuehrer, Gerard, Glansdorff, Hauf, Iribarne, Jacobsen, Khairoutdinov, Lipiński, Madden, Manzhelii, Marquet, Marquet, Marquet, Marquet, Nagle, Normand, Pauling, Pauluis, Pauluis, Peterson, Richardson, Saunders, Siebesma, Tripoli, Wisniak, WMO, Zdunkowski   +48 more
core   +3 more sources

Nanocurvature‐Activated Dipolar Polarization in M–N4 Single‐Atom Sites for High‐Performance Electromagnetic Wave Absorption

Advanced Science, EarlyView.
Increasing nanocurvature effectively enriches the local electron density of the M–N4 motif, which facilitates electron transfer from the metal center to nitrogen atoms. This electronic behavior intensifies the localization and asymmetric distribution of charge, thereby significantly amplifying the dipole moment and polarizability.
Daohu Sheng, Siyao Cheng, Mengmeng Zhang, Jinglei Zhang, Xufei Zhu, Weijin Li, Bo Zhang, Aming Xie   +7 more
wiley   +1 more source