Results 191 to 200 of about 780,879 (337)
Unique biological samples, such as site‐specific mutant proteins, are available only in limited quantities. Here, we present a polarization‐resolved transient infrared spectroscopy setup with referencing to improve signal‐to‐noise tailored towards tracing small signals. We provide an overview of characterizing the excitation conditions for polarization‐
Clark Zahn, Karsten Heyne
wiley +1 more source
Hydroelastic waves induced by initial disturbances in ice-covered waters with currents. [PDF]
Prasad IM, Behera H.
europepmc +1 more source
Eigenvalue problem for fractional differential equations with nonlinear integral and disturbance parameter in boundary conditions [PDF]
Wenxia Wang, GUO XIAO-TONG
openalex +1 more source
A tri‐culture of iPSC‐derived neurons, astrocytes, and microglia treated with ferroptosis inducers as an Induced ferroptosis model was characterized by scRNA‐seq, cell survival, and cytokine release assays. This analysis revealed diverse microglial transcriptomic changes, indicating that the system captures key aspects of the complex cellular ...
Hongmei Lisa Li +6 more
wiley +1 more source
Time fractional modeling of MHD natural convection flow between parallel plates via caputo-fabrizio integral. [PDF]
Masood K.
europepmc +1 more source
An integral equation method for the time-harmonic maxwell equations with boundary conditions for the normal components [PDF]
V. Gülzow
openalex +1 more source
Nuclear pore links Fob1‐dependent rDNA damage relocation to lifespan control
Damaged rDNA accumulates at a specific perinuclear interface that couples nucleolar escape with nuclear envelope association. Nuclear pores at this site help inhibit Fob1‐induced rDNA instability. This spatial organization of damage handling supports a functional link between nuclear architecture, rDNA stability, and replicative lifespan in yeast.
Yamato Okada +5 more
wiley +1 more source
WF-PINNs: solving forward and inverse problems of burgers equation with steep gradients using weak-form physics-informed neural networks. [PDF]
Wang X, Yi S, Gu H, Xu J, Xu W.
europepmc +1 more source

