Results 51 to 60 of about 7,569,463 (308)
Unsupervised clustering of series using dynamic programming
CoRR, 2021 We are interested in clustering parts of a given single multi-variate series in an unsupervised manner. We would like to segment and cluster the series such that the resulting blocks present in each cluster are coherent with respect to a known model (e.g. physics model). Data points are said to be coherent if they can be described using this model with
Karthigan Sinnathamby +4 more
openaire +3 more sources
FEBS Letters, EarlyView.Animals must match their growth rate to available nutrients. We show that in Drosophila larvae, the nutrient‐sensing TOR kinase controls growth by regulating levels of TFAM, a key regulator of mitochondrial function, in the adipose tissue. When nutrients are abundant, high TOR activity suppresses TFAM, lowering mitochondrial bioenergetic activity and ...
Shrivani Sriskanthadevan‐Pirahas +4 more
wiley +1 more source
Dynamic time series binary choice [PDF]
, 2007 This paper considers dynamic time series binary choice models. It proves near epoch dependence and strong mixing for the dynamic binary choice model with correlated errors.
de Jong, Robert M., Woutersen, Tiemen
core
Simulating Hamiltonian Dynamics with a Truncated Taylor Series
Physical Review Letters, 2015 We describe a simple, efficient method for simulating Hamiltonian dynamics on a quantum computer by approximating the truncated Taylor series of the evolution operator. Our method can simulate the time evolution of a wide variety of physical systems. As in another recent algorithm, the cost of our method depends only logarithmically on the inverse of ...
Berry, Dominic W. +4 more
openaire +6 more sources
Engineering peptides into antibodies—opportunities and strategies for therapeutic innovation
FEBS Letters, EarlyView.Peptides and antibodies occupy complementary therapeutic niches. Peptides recognize difficult targets in a compact format, while antibodies add specificity, long half‐life, and effector functions. This review examines strategies that merge both modalities—peptide grafting into loops, terminal and Fc fusions, and bioconjugation—highlighting how ...
Jinling Wang +2 more
wiley +1 more source
Liver organoids: modelling complexity in homeostasis and disease
FEBS Letters, EarlyView.Studying liver in vitro has been challenging because simple 2D cell cultures fail to capture liver's cellular and architectural complexity. To bridge this gap, scientists increasingly use organoids, 3D liver models which better mimic liver composition and function. This review examines recent advances in liver organoid complexity and realism, discusses
Anna M. Dowbaj, Meritxell Huch
wiley +1 more source
Novel Method for Estimating Time-Varying COVID-19 Transmission Rate
Mathematics, 2023 The transmission rate is an important indicator for characterizing a virus and estimating the risk of its outbreak in a certain area, but it is hard to measure. COVID-19, for instance, has greatly affected the world for more than 3 years since early 2020,
Hongfei Xiao, Deqin Lin, Shiyu Li
doaj +1 more source
Structural and biochemical analysis of a B12 superbinder
FEBS Letters, EarlyView.BtuG proteins are vitamin B12 scavengers in Bacteroides thetaiotaomicron, a dominant human gut bacterium. We present crystal structures of three BtuG homologs bound to cobalamin and its precursor cobinamide, revealing picomolar binding affinities, among the highest known for any natural protein.
Jose M. Martinez Felices +3 more
wiley +1 more source
Dynamic prediction of gas concentration based on time series
Gong-kuang zidonghua, 2018 Existing gas concentration prediction methods could only achieve static gas concentration prediction, could not update with accumulation of gas data, as a result, the prediction results were not timeliness.
GUO Siwen, TAO Yufan, LI Chao
doaj +1 more source
Dynamic Multi-Scale Convolutional Neural Network for Time Series Classification
IEEE Access, 2020 Time series classification is an essential task in many real-world application domains. As a popular deep learning network, convolutional neural networks have achieved excellent performance in time series classification tasks.
Bin Qian +6 more
doaj +1 more source