Cascaded Linear Regulator with Positive Voltage Tracking Switching Regulator

This thesis presents the design, simulation, and hardware implementation of a proposed method for improving efficiency of voltage regulator. Typically, voltage regulator used for noise-sensitive and low-power applications involves the use of a linear regulator due to its high power-supply rejection ratio properties. However, the efficiency of a linear regulator depends heavily on the difference between its input voltage and output voltage. A larger voltage difference across the linear regulator results in higher losses. Therefore, reducing the voltage difference is the key in increasing regulator’s efficiency. In this thesis, a pre switching regulator stage with positive voltage tracking cascaded to a linear regulator is proposed to provide an input voltage to a linear regulator that is slightly above the output of the linear regulator. The tracking capability is needed to provide the flexibility in having different positive output voltage levels while maintaining high overall regulator’s efficiency. Results from simulation and hardware implementation of the proposed system showed efficiency improvement of up to 23% in cases where an adjustable output voltage is necessary. Load regulation performance of the proposed method was also overall better compared to the case without the output voltage tracking method

Information-theoretic analysis of the directional influence between cellular processes

Inferring the directionality of interactions between cellular processes is a major challenge in systems biology. Time-lagged correlations allow to discriminate between alternative models, but they still rely on assumed underlying interactions. Here, we use the transfer entropy (TE), an information-theoretic quantity that quantifies the directional influence between fluctuating variables in a model-free way. We present a theoretical approach to compute the transfer entropy, even when the noise has an extrinsic component or in the presence of feedback. We re-analyze the experimental data from Kiviet et al. (2014) where fluctuations in gene expression of metabolic enzymes and growth rate have been measured in single cells of E. coli. We confirm the formerly detected modes between growth and gene expression, while prescribing more stringent conditions on the structure of noise sources. We furthermore point out practical requirements in terms of length of time series and sampling time which must be satisfied in order to infer optimally transfer entropy from times series of fluctuations.Comment: 24 pages, 7 figure

Universal motifs and the diversity of autocatalytic systems

Autocatalysis is essential for the origin of life and chemical evolution. However, the lack of a unified framework so far prevents a systematic study of autocatalysis. Here, we derive, from basic principles, general stoichiometric conditions for catalysis and autocatalysis in chemical reaction networks. This allows for a classification of minimal autocatalytic motifs called cores. While all known autocatalytic systems indeed contain minimal motifs, the classification also reveals hitherto unidentified motifs.We further examine conditions for kinetic viability of such networks, which depends on the autocatalytic motifs they contain and is notably increased by internal catalytic cycles. Finally, we show how this framework extends the range of conceivable autocatalytic systems, by applying our stoichiometric and kinetic analysis to autocatalysis emerging from coupled compartments. The unified approach to autocatalysis presented in this work lays a foundation toward the building of a systems-level theory of chemical evolution

Generation and filtering of gene expression noise by the bacterial cell cycle

Supplementary methods. (DOCX 1071 kb

Selection dynamics in transient compartmentalization

Transient compartments have been recently shown to be able to maintain functional replicators in the context of prebiotic studies. Motivated by this experiment, we show that a broad class of selection dynamics is able to achieve this goal. We identify two key parameters, the relative amplification of non-active replicators (parasites) and the size of compartments. Since the basic ingredients of our model are the competition between a host and its parasite, and the diversity generated by small size compartments, our results are relevant to various phage-bacteria or virus-host ecology problems.Comment: 11 pages, 10 figure

Real-time Human Detection in Fire Scenarios using Infrared and Thermal Imaging Fusion

Fire is considered one of the most serious threats to human lives which results in a high probability of fatalities. Those severe consequences stem from the heavy smoke emitted from a fire that mostly restricts the visibility of escaping victims and rescuing squad. In such hazardous circumstances, the use of a vision-based human detection system is able to improve the ability to save more lives. To this end, a thermal and infrared imaging fusion strategy based on multiple cameras for human detection in low-visibility scenarios caused by smoke is proposed in this paper. By processing with multiple cameras, vital information can be gathered to generate more useful features for human detection. Firstly, the cameras are calibrated using a Light Heating Chessboard. Afterward, the features extracted from the input images are merged prior to being passed through a lightweight deep neural network to perform the human detection task. The experiments conducted on an NVIDIA Jetson Nano computer demonstrated that the proposed method can process with reasonable speed and can achieve favorable performance with a [email protected] of 95%.Comment: 5 pages, 6 figures, 2 table

Robustness of compositional heredity to the growth and division dynamics of prebiotic compartments

An important transition after the origin of life was the first emergence of a Darwinian population, self-reproducing entities exhibiting differential reproduction, phenotypic variation, and inheritance of phenotypic traits. The simplest system we can imagine to have these properties would consist of a compartmentalized autocatalytic reaction system that exhibits two growth states with different chemical compositions. Identifying the chemical composition as the phenotype, this accounts for two of the properties. However, it is not clear what are the necessary conditions for such a chemical system to exhibit inheritance of the compositional states upon growth and division of the compartment. We show that for a general class of autocatalytic chemical systems subject to serial dilution, the inheritance of compositional information only occurs when the time interval between dilutions is below a critical threshold that depends on the efficiency of the catalytic reactions. Further, we show that these thresholds provide rigorous bounds on the properties required for the inheritance of the chemical compositional state for general growth and division cycles. Our result suggests that a serial dilution experiment, which is much easier to set up in a laboratory, can be used to test whether a given autocatalytic chemical system can exhibit heredity. Lastly, we apply our results to a realistic autocatalytic system based on the Azoarcus ribozyme and suggest a protocol to experimentally test whether this system can exhibit heredity.Comment: 30 pages, 22 figure