Results 91 to 100 of about 19,330,588 (265)

Smaller is better: nanobodies meet NMR

FEBS Letters, EarlyView.
Nanobodies are single‐domain antigen‐binding fragments derived from camelid heavy chain antibodies. Their small size, high stability, and exceptional specificity make nanobodies uniquely useful probes for NMR studies of protein dynamics, transient conformational states, and protein–protein interactions.
Oleg Y. Dmitriev
wiley   +1 more source

Time-varying parameters of glycemic control and glycation in relation to arterial stiffness in patients with type 1 diabetes. [PDF]

Cardiovasc Diabetol, 2022
Helleputte S, Calders P, Rodenbach A, Marlier J, Verroken C, De Backer T, Lapauw B.   +6 more
europepmc   +1 more source

Closed-Form Covariance Matrix for Portfolio Optimization: Theory and Empirical Evidence Under a Multidimensional Black–Scholes Model with Time-Varying Parameters

Mathematics
This paper develops a model-driven analytical framework for portfolio optimization under a multidimensional Black–Scholes model with time-varying parameters, where both the drift and volatility functions evolve linearly over time.
Touch Toem, Sanae Rujivan, Angelo E. Marasigan   +2 more
doaj   +1 more source

Invisible but not inaccessible—Revealing transient oligomers formed by intrinsically disordered proteins with solution NMR and complementary methods

FEBS Letters, EarlyView.
Transient oligomers formed by intrinsically disordered proteins may be ‘invisible’ to direct detection yet remain accessible to solution NMR through equilibrium‐exchange measurements and pressure‐jump experiments. Complementary methods report on mass, stoichiometry, selected distance distributions, morphology, and internal packing.
Martin D. Gelenter, Ad Bax
wiley   +1 more source

A Time-Varying Generalised Minimum Variance Controller

, 2008
:- A generalised minimum variance controller is developed for linear time-varying systems. The plants to be controlled are described using a controlled autoregressive moving average model and are exponentially stable.
Z. Li, Und Prozessinformatik, A Time-varying Generalised, Zheng Li, Lehrstuhl Für Automatisierungstechnik, Chr Schmid, Christian Schmid, Ruhr-universität Bochum   +7 more
core  

Estimation of spatiotemporally varying parameters for grid-based distributed hydrologic models

Journal of Hydrology: Regional Studies
Study region: Xiangjiang and Baihe River basins, China. Study focus: Hydrologic models often use either time-varying or spatially heterogeneous parameter methods to improve runoff simulations.
Xiaojing Zhang, Pan Liu, Kang Xie, Weibo Liu, Lele Deng, Huan Xu, Qian Cheng, Liting Zhou   +7 more
doaj   +1 more source

Membrane composition and thermodynamic identity as boundaries of life for synthetic cell research

FEBS Letters, EarlyView.
What makes a cell a cell? The boundary of a living cell is not just a wall. Read as a Markov blanket, the membrane separates internal from external states, generating identity and non‐equilibrium order. Can this identity be rebuilt from scratch in a synthetic cell?
Caterina Presutti, Bert Poolman
wiley   +1 more source

Time-varying modal parameters identification of large flexible spacecraft using a recursive algorithm

, 2016
In existing identification methods for on-orbit spacecraft, such as eigensystem realization algorithm (ERA) and subspace method identification (SMI), singular value decomposition (SVD) is used frequently to estimate the modal parameters.
Ni ZY(倪智宇), Wu SN(邬树楠), Wu ZG(吴志刚)   +2 more
core  

IMPDH inhibition enhances cytarabine efficacy in SAMHD1‐expressing leukaemia cells via guanine nucleotide depletion

Molecular Oncology, EarlyView.
Cytarabine is a key therapy for acute myeloid leukaemia (AML), but its efficacy is limited by the dNTPase SAMHD1, which hydrolyses its active metabolite. Screening nucleotide biosynthesis inhibitors revealed that IMPDH inhibitors selectively sensitise SAMHD1‐proficient AML cells to cytarabine.
Miriam Yagüe‐Capilla, Christopher Dirks, Caroline Eiden, Sonja K. Fesenmayer, Femke M. Hormann, Yolande Klootsema, Ingrid Lilienthal, Si Min Zhang, Nikolas Herold, Sean G. Rudd   +9 more
wiley   +1 more source

Deep learning forecasting using time-varying parameters of the SIRD model for Covid-19. [PDF]

Sci Rep, 2022
Bousquet A, Conrad WH, Sadat SO, Vardanyan N, Hong Y.   +4 more
europepmc   +1 more source