Results 81 to 90 of about 5,119,475 (357)

Cell geometry and membrane protein crowding constrain Escherichia coli growth rate, overflow metabolism, respiration, and maintenance energy

open access: yesFEBS Letters, EarlyView.
The physical dimensions and shape of bacterial cells define the surface area available to acquire nutrients and the volume available for synthesizing proteins and DNA. Here, we use computational systems biology to decode the importance of cell geometry as a major determinant of prokaryotic phenotype, including growth rate and metabolic efficiency. This
Ross P. Carlson   +6 more
wiley   +1 more source

Oil Price Shocks: Testing for Non-linearity [PDF]

open access: yes
This paper presents evidence of a non-linear relationship between GDP growth and oil price changes in the US economy. We also argue that this non-linearity is not merely due to the use of data from the mid-1980s onwards, as most authors, so far, seem to ...
Rebeca Jiménez-Rodríguez
core  

Development of a Measurement Device for Micro Gas Flowrate Based on Laminar Flow Element with Micro-Curved Surface

open access: yesMicromachines
The laminar flow meter (LFM) boasts several advantages such as no moving parts, a wide range ratio, high measurement accuracy, quick dynamic response, etc., and is a promising technology for micro gas flow measurement.
Zixuan Wang   +4 more
doaj   +1 more source

Salmonella lipopolysaccharide‐containing supported lipid bilayers as platforms to study bacteriophage interactions

open access: yesFEBS Letters, EarlyView.
We present robust protocols for the preparation of supported lipid bilayers (SLBs) incorporating either Salmonella smooth LPS or outer membrane vesicles (OMVs). We use a combination of quartz crystal microbalance with dissipation (QCM‐D) and fluorescence microscopy to both characterize the SLBs of various compositions and to probe their interactions ...
Hudson P. Pace   +6 more
wiley   +1 more source

Comprehensive evaluation of RNA-seq quantification methods for linearity

open access: yesBMC Bioinformatics, 2016
Deconvolution is a mathematical process of resolving an observed function into its constituent elements. In the field of biomedical research, deconvolution analysis is applied to obtain single cell-type or tissue specific signatures from a mixed signal ...
Haijing Jin, Ying-Wooi Wan, Zhandong Liu
semanticscholar   +1 more source

Structural insights and therapeutic targets in Acinetobacter baumannii capsule biosynthesis

open access: yesFEBS Letters, EarlyView.
Hypervirulent KL49 A. baumannii's capsular polysaccharide contains the nonulosonic acid 8‐epi‐Leg5,7Ac2, synthesized by epimerization via ElaA, ElaB, and ElaC. Crystal structures of ElaA, ElaB, and ElaC reveal their role in CMP‐Leg5,7Ac2 synthesis and regioselective C8 epimerization.
Woo Cheol Lee   +7 more
wiley   +1 more source

HACking at Non-linearity: Evidence from Stocks and Bonds [PDF]

open access: yes
The implicit assumption of linearity is an important element in empirical finance. This study presents a hypothesis testing approach which examines the linear behaviour of the conditional mean between stock and bond returns.
Robert J Bianchi   +2 more
core  

Non-linearity analysis of a spectroradiometer

open access: yes
Hyperspectral analysis is an important remote sensing tool. Corresponding spectrometers require accurate calibration in optical laboratories. Non-linearity and temperature dependence are important factors that degrade the calibration quality.
Torgasin, Konstantin   +1 more
core   +1 more source

Validation of the procedure for determination of amino acids composition of glatiramer acetate by C-13 NMR spectroscopy

open access: yesРегуляторные исследования и экспертиза лекарственных средств, 2018
The article describes validation of the procedure for determination of amino acids composition of glatiramer acetate by C-13 NMR spectroscopy. The procedure makes it possible to determine the molar ratio of amino acids present in glatiramer acetate with ...
N. E. Kuz’Mina   +6 more
doaj  

Learning Robust Auto-Encoders With Regularizer for Linearity and Sparsity

open access: yesIEEE Access, 2019
Unsupervised feature learning via auto-encoders results in low-dimensional representations in latent space that capture the patterns of input data. The auto-encoders with robust regularization learn qualified features that are less sensitive to small ...
Yong Shi   +3 more
doaj   +1 more source

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