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