On Transformation Methods and the Induced Parallel Properties for the Temporal Domain

2010 ◽  
pp. 45-70 ◽  
Author(s):  
C.-H. Lai
Keyword(s):  
Temporal Domain ◽  
Transformation Methods

Imputation Via Copula and Transformation Methods, With Applications to Financial and Economic Data

2010 ◽  
Author(s):  
Yangyong Zhang ◽  
Craig A. Friedman ◽  
Jinggang Huang ◽  
Wenbo Cao
Keyword(s):  
Economic Data ◽  
Transformation Methods

Microbial Bioconversion: A Regio-specific Method for Novel Drug Design and Toxicological Study of Metabolites

2019 ◽  
Vol 20 (14) ◽  
pp. 1156-1162
Author(s):  
Maria Yousuf ◽  
Waqas Jamil ◽  
Khayala Mammadova
Keyword(s):  
Microbial Transformation ◽  
Specific Method ◽  
Reaction Conditions ◽  
Small Organic Molecules ◽  
Toxicological Studies ◽  
Drug Designing ◽  
Transformation Methods ◽  
Novel Drug

The methods of chemical structural alteration of small organic molecules by using microbes (fungi, bacteria, yeast, etc.) are gaining tremendous attention to obtain structurally novel and therapeutically potential leads. The regiospecific mild environmental friendly reaction conditions with the ability of novel chemical structural modification in compounds categorize this technique; a distinguished and unique way to obtain medicinally important drugs and their in vivo mimic metabolites with costeffective and timely manner. This review article shortly addresses the immense pharmaceutical importance of microbial transformation methods in drug designing and development as well as the role of CYP450 enzymes in fungi to obtain in vivo drug metabolites for toxicological studies.

Aspect and space

2017 ◽  
Author(s):  
Lucas Champollion
Keyword(s):  
Spatial Domain ◽  
The Other ◽  
Alternative View ◽  
Temporal Domain ◽  
Spatial Aspect ◽  
Temporal Aspect ◽  
The Way

This chapter models the relation between temporal aspect (run for an hour vs. *run all the way to the store for an hour) and spatial aspect (meander for a mile vs. *end for a mile) previously discussed by Gawron (2009). The chapter shows that for-adverbials impose analogous conditions on the spatial domain and on the temporal domain, and that an event may satisfy stratified reference with respect to one of the domains without satisfying it with respect to the other one as well. This provides the means to extend the telic-atelic opposition to the spatial domain. The chapter argues in some detail that stratified reference is in this respect empirically superior to an alternative view of telicity based on divisive reference (Krifka 1998).

POLARON IN A QUANTUM DOT UNDER AN ELECTRIC FIELD

2007 ◽  
Vol 21 (24) ◽  
pp. 1635-1642
Author(s):  
MIAN LIU ◽  
WENDONG MA ◽  
ZIJUN LI
Keyword(s):  
Quantum Dot ◽  
Electric Field ◽  
Field Intensity ◽  
Ground State Energy ◽  
Ground State ◽  
Electric Field Intensity ◽  
State Energy ◽  
Theoretical Study ◽  
The Moment ◽  
Transformation Methods

We conducted a theoretical study on the properties of a polaron with electron-LO phonon strong-coupling in a cylindrical quantum dot under an electric field using linear combination operator and unitary transformation methods. The changing relations between the ground state energy of the polaron in the quantum dot and the electric field intensity, restricted intensity, and cylindrical height were derived. The numerical results show that the polar of the quantum dot is enlarged with increasing restricted intensity and decreasing cylindrical height, and with cylindrical height at 0 ~ 5 nm , the polar of the quantum dot is strongest. The ground state energy decreases with increasing electric field intensity, and at the moment of just adding electric field, quantum polarization is strongest.

scholarly journals Interconversion of Plasma Free Thyroxine Values from Assay Platforms with Different Reference Intervals Using Linear Transformation Methods

Biology ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 45
Author(s):  
Fanwen Meng ◽  
Jacqueline Jonklaas ◽  
Melvin Khee-Shing Leow
Keyword(s):  
Linear Transformation ◽  
Piecewise Linear ◽  
Equilibrium Dialysis ◽  
Accurate Method ◽  
Reference Intervals ◽  
Thyroid Stimulating Hormone ◽  
Free Thyroxine ◽  
Thyroid Function Tests ◽  
Linear Transformations ◽  
Transformation Methods

Clinicians often encounter thyroid function tests (TFT) comprising serum/plasma free thyroxine (FT4) and thyroid stimulating hormone (TSH) measured using different assay platforms during the course of follow-up evaluations which complicates reliable comparison and interpretation of TFT changes. Although interconversion between concentration units is straightforward, the validity of interconversion of FT4/TSH values from one assay platform to another with different reference intervals remains questionable. This study aims to establish an accurate and reliable methodology of interconverting FT4 by any laboratory to an equivalent FT4 value scaled to a reference range of interest via linear transformation methods. As a proof-of-concept, FT4 was simultaneously assayed by direct analog immunoassay, tandem mass spectrometry and equilibrium dialysis. Both linear and piecewise linear transformations proved relatively accurate for FT4 inter-scale conversion. Linear transformation performs better when FT4 are converted from a more accurate to a less accurate assay platform. The converse is true, whereby piecewise linear transformation is superior to linear transformation when converting values from a less accurate method to a more robust assay platform. Such transformations can potentially apply to other biochemical analytes scale conversions, including TSH. This aids interpretation of TFT trends while monitoring the treatment of patients with thyroid disorders.

scholarly journals A new method for identifying the role of marital preferences at shaping marriage patterns

2021 ◽  
pp. 1-27
Author(s):  
Anna Naszodi ◽  
Francisco Mendonca
Keyword(s):  
Contingency Table ◽  
Transformation Method ◽  
New Method ◽  
Marriage Patterns ◽  
The Us ◽  
Analytical Properties ◽  
The Matrix ◽  
Transformation Methods

Abstract We develop a method which assumes that marital preferences are characterized either by the scalar-valued measure proposed by Liu and Lu, or by the matrix-valued generalized Liu–Lu measure. The new method transforms an observed contingency table into a counterfactual table while preserving its (generalized) Liu–Lu value. After exploring some analytical properties of the new method, we illustrate its application by decomposing changes in the prevalence of homogamy in the US between 1980 and 2010. We perform this decomposition with two alternative transformation methods as well where both methods capture preferences differently from Liu and Lu. Finally, we use survey evidence to support our claim that out of the three considered methods, the new transformation method is the most suitable for identifying the role of marital preferences at shaping marriage patterns. These data are also in favor of measuring assortativity in preferences à la Liu and Lu.

scholarly journals Enhancing Wind Turbine Power Forecast via Convolutional Neural Network

Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 261
Author(s):  
Tianyang Liu ◽  
Zunkai Huang ◽  
Li Tian ◽  
Yongxin Zhu ◽  
Hui Wang ◽  
...  
Keyword(s):  
Time Series ◽  
Wind Speed ◽  
Wind Turbine ◽  
Wind Power ◽  
Rapid Development ◽  
Superior Performance ◽  
Learning Platform ◽  
Novel Approach ◽  
Wind Power Forecast ◽  
Transformation Methods

The rapid development in wind power comes with new technical challenges. Reliable and accurate wind power forecast is of considerable significance to the electricity system’s daily dispatching and production. Traditional forecast methods usually utilize wind speed and turbine parameters as the model inputs. However, they are not sufficient to account for complex weather variability and the various wind turbine features in the real world. Inspired by the excellent performance of convolutional neural networks (CNN) in computer vision, we propose a novel approach to predicting short-term wind power by converting time series into images and exploit a CNN to analyze them. In our approach, we first propose two transformation methods to map wind speed and precipitation data time series into image matrices. After integrating multi-dimensional information and extracting features, we design a novel CNN framework to forecast 24-h wind turbine power. Our method is implemented on the Keras deep learning platform and tested on 10 sets of 3-year wind turbine data from Hangzhou, China. The superior performance of the proposed method is demonstrated through comparisons using state-of-the-art techniques in wind turbine power forecasting.

Sign in / Sign up

Export Citation Format

Share Document