285 research outputs found
ENGINEERING NOVEL TERPENE PRODUCTION PLATFORMS IN THE YEAST SACCHAROMYCES CEREVISIAE
The chemical diversity and biological activities of terpene and terpenoids have served in the development of new flavors, fragrances, medicines and pesticides. While terpenes are made predominantly by plants and microbes in small amounts and as components of complex mixtures, chemical synthesis of terpenes remains technically challenging, costly and inefficient. In this dissertation, methods to create new yeast lines possessing a dispensable mevalonate biosynthetic pathway wherein carbon flux can be diverted to build any chemical class of terpene product are described. The ability of this line to generate diterpenes was next investigated. Using a 5.5 L fed bath fermentation system, about 569 mg/L kaurene and approximately 207 mg/L abietadiene plus 136 mg/L additional isomers were achieved. To engineer more highly modified diterpenes might have greater industrial, agricultural or medicinal applications, kaurenoic acid production reached 514 mg/L with byproduct kaurene and kaurenal at 71.7mg/L and 20.1mg/L, respectively, in fed batch fermentation conditions. Furthermore, ZXM lines for engineer monoterpene and ZXB lines for engineer triterpene were generated by additional specific genomic modification, 84.76 ±13.2 mg/L linalool, 20.54±3.8 mg/L nerolidol and 297.7mg/L squalene were accumulate in ZXM144 line ana ZXB line, respectively, in shake flask conditions
Dynamical topology and statistical properties of spatiotemporal chaos
For spatiotemporal chaos described by partial differential equations, there
are generally locations where the dynamical variable achieves its local
extremum or where the time partial derivative of the variable vanishes
instantaneously. To a large extent, the location and movement of these
topologically special points determine the qualitative structure of the
disordered states. We analyze numerically statistical properties of the
topologically special points in one-dimensional spatiotemporal chaos. The
probability distribution functions for the number of point, the lifespan, and
the distance covered during their lifetime are obtained from numerical
simulations. Mathematically, we establish a probabilistic model to describe the
dynamics of these topologically special points. In despite of the different
definitions in different spatiotemporal chaos, the dynamics of these special
points can be described in a uniform approach.Comment: 6 pages, 5 figure
The Rossiter-McLaughlin effect for exomoons or binary planets
In this paper we study possible signatures of binary planets or exomoons on
the Rossiter-McLaughlin (R-M) effect. Our analyses show that the R-M effect for
a binary planet or exomoon during its complete transit phase can be divided
into two parts. The first is the conventional one similar to the R-M effect
from the transit of a single planet, of which the mass and the projected area
are the combinations of the binary components; and the second is caused by the
orbital rotation of the binary components, which may add a sine- or linear-mode
deviation to the stellar radial velocity curve. We find that the latter effect
can be up to several or several ten m/s. By doing numerical simulations as well
as analytical analyses, we illustrate that the distribution and dispersion of
the latter effects obtained from multiple transit events can be used to
constrain the dynamical configuration of the binary planet, such as, how the
inner orbit of the binary planet is inclined to its orbit rotating around the
central star. We find that the signatures caused by the orbital rotation of the
binary components are more likely to be revealed if the two components of
binary planet have different masses and mass densities, especially if the heavy
one has a high mass density and the light one has a low density. Similar
signature on the R-M effect may also be revealed in a hierarchical triple star
system containing a dark compact binary and a tertiary star.Comment: 30 pages, 9 figure
Method and System for Terpene Production Platforms in Yeast
A method is provided for producing modified mutant yeast and the resulting yeast that can be used as a platform for terpene production. The method includes chemical mutagenesis to effect ergosterol dependent growth in yeast. Subsequently, these yeast are subjected to an erg9 knockout mutation to thereby produce ergosterol dependent growth/ erg9 knockout mutation yeast cell lines. The resulting yeast are well suited for use in the production of terpenes
Method and System for Diterpene Production Platforms in Yeast
A method is provided for modifying yeast to express mutant avian farnesyl disphospate synthase and the resulting modified yeast. The yeast advantageously includes additional mutants including but not limited to having ergosterol dependent growth and being erg-. The modified yeast are beneficial for the production of various terpenes including diterpenes
MoFaNeRF: Morphable Facial Neural Radiance Field
We propose a parametric model that maps free-view images into a vector space
of coded facial shape, expression and appearance with a neural radiance field,
namely Morphable Facial NeRF. Specifically, MoFaNeRF takes the coded facial
shape, expression and appearance along with space coordinate and view direction
as input to an MLP, and outputs the radiance of the space point for
photo-realistic image synthesis. Compared with conventional 3D morphable models
(3DMM), MoFaNeRF shows superiority in directly synthesizing photo-realistic
facial details even for eyes, mouths, and beards. Also, continuous face
morphing can be easily achieved by interpolating the input shape, expression
and appearance codes. By introducing identity-specific modulation and texture
encoder, our model synthesizes accurate photometric details and shows strong
representation ability. Our model shows strong ability on multiple applications
including image-based fitting, random generation, face rigging, face editing,
and novel view synthesis. Experiments show that our method achieves higher
representation ability than previous parametric models, and achieves
competitive performance in several applications. To the best of our knowledge,
our work is the first facial parametric model built upon a neural radiance
field that can be used in fitting, generation and manipulation. The code and
data is available at https://github.com/zhuhao-nju/mofanerf.Comment: accepted to ECCV2022; code available at
http://github.com/zhuhao-nju/mofaner
Statistical Simulator for the Engine Knock
This paper proposes a statistical simulator for the engine knock based on the
Mixture Density Network (MDN) and the accept-reject method. The proposed
simulator can generate the random knock intensity signal corresponding to the
input signal. The generated knock intensity has a consistent probability
distribution with the real engine. Firstly, the statistical analysis is
conducted with the experimental data. From the analysis results, some important
assumptions on the statistical properties of the knock intensity are made.
Regarding the knock intensity as a random variable on the discrete-time index,
it is independent and identically distributed if the input of the engine is
identical. The probability distribution of the knock intensity under identical
input can be approximated by the Gaussian Mixture Model(GMM). The parameter of
the GMM is a function of the input. Based on these assumptions, two
sub-problems for establishing the statistical simulator are formulated: One is
to approximate the function from input to the parameters of the knock intensity
distribution with an absolutely continuous function; The other one is to design
a random number generator that outputs the random data consistent with the
given distribution. The MDN is applied to approximate the probability density
of the knock intensity and the accept-reject algorithm is used for the random
number generator design. The proposed method is evaluated in experimental
data-based validation
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