Time-dependent probability density functions and information geometry in stochastic logistic and Gompertz models [PDF]
Lucille-Marie Tenkès +2 more
openalex +1 more source
Alkyltriphenylphosphonium Binding to Cardiolipin Triggers Oncosis in Cancer Cells
Alkyltriphenylphosphonium, exemplified by TPP+‐C14, preferentially accumulates in mitochondria and selectively binds to cardiolipin, a key phospholipid of the inner mitochondrial membrane, causing loss of mitochondrial membrane potential, severe cellular ATP depletion, and calcium imbalance.
Jin Li +8 more
wiley +1 more source
Dimensioning cellular IoT network using stochastic geometry and machine learning techniques
Tuấn Anh Nguyễn
openalex +1 more source
Precision Editing of NLRS Improves Effector Recognition for Enhanced Disease Resistance
Precision engineering of plant NLR immune receptors enables rational design of enhanced pathogen resistance through mismatched pairing, domain swapping, and targeted mutagenesis. These approaches achieve multi‐fold expansion in recognition breadth while minimizing autoimmunity risks and fitness penalties.
Vinit Kumar +7 more
wiley +1 more source
Termination of Calcium Sparks: An Emergent Property from Stochastic RyR Gating and Dyad Geometry [PDF]
Derek R. Laver +3 more
openalex +1 more source
Transient Antiskyrmion‐Mediated Topological Transitions in Isotropic Magnets
A transient antiskyrmion‐mediated pathway that drives repeated stripe‐to‐skyrmion transitions is revealed, producing a net increase in topological charge in isotropic Dzyaloshinskii–Moriya interaction films. Experiments and simulations identify the antiskyrmion as a metastable excitation, enabling stochastic bitstream generation for probabilistic ...
Bingqian Dai +18 more
wiley +1 more source
Stochastic geometry analysis of UAV-assisted networks with probabilistic UAV activation. [PDF]
Selim MM.
europepmc +1 more source
Stochastic geometry modeling and analysis of cognitive heterogeneous cellular networks [PDF]
Fereidoun H. Panahi, Tomoaki Ohtsuki
openalex +1 more source
Learned Conformational Space and Pharmacophore Into Molecular Foundational Model
The Ouroboros model introduces two orthogonal modules within a unified framework that independently learn molecular representations and generate chemical structures. This design enables flexible optimization strategies for each module and faithful structure reconstruction without prompts or noise.
Lin Wang +8 more
wiley +1 more source

