63 research outputs found

    Design Of Dna Strand Displacement Based Circuits

    Get PDF
    DNA is the basic building block of any living organism. DNA is considered a popular candidate for future biological devices and circuits for solving genetic disorders and several other medical problems. With this objective in mind, this research aims at developing novel approaches for the design of DNA based circuits. There are many recent developments in the medical field such as the development of biological nanorobots, SMART drugs, and CRISPR-Cas9 technologies. There is a strong need for circuits that can work with these technologies and devices. DNA is considered a suitable candidate for designing such circuits because of the programmability of the DNA strands, small size, lightweight, known thermodynamics, higher parallelism, and exponentially reducing the cost of synthesizing techniques. The DNA strand displacement operation is useful in developing circuits with DNA strands. The circuit can be either a digital circuit, in which the logic high and logic low states of the DNA strand concentrations are considered as the signal, or it can be an analog circuit in which the concentration of the DNA strands itself will act as the signal. We developed novel approaches in this research for the design of digital, as well as analog circuits keeping in view of the number of DNA strands required for the circuit design. Towards this goal in the digital domain, we developed spatially localized DNA majority logic gates and an inverter logic gate that can be used with the existing seesaw based logic gates. The majority logic gates proposed in this research can considerably reduce the number of strands required in the design. The introduction of the logic inverter operation can translate the dual rail circuit architecture into a monorail architecture for the seesaw based logic circuits. It can also reduce the number of unique strands required for the design into approximately half. The reduction in the number of unique strands will consequently reduce the leakage reactions, circuit complexity, and cost associated with the DNA circuits. The real world biological inputs are analog in nature. If we can use those analog signals directly in the circuits, it can considerably reduce the resources required. Even though analog circuits are highly prone to noise, they are a perfect candidate for performing computations in the resource-limited environments, such as inside the cell. In the analog domain, we are developing a novel fuzzy inference engine using analog circuits such as the minimum gate, maximum gate, and fan-out gates. All the circuits discussed in this research were designed and tested in the Visual DSD software. The biological inputs are inherently fuzzy in nature, hence a fuzzy based system can play a vital role in future decision-making circuits. We hope that our research will be the first step towards realizing these larger goals. The ultimate aim of our research is to develop novel approaches for the design of circuits which can be used with the future biological devices to tackle many medical problems such as genetic disorders

    A Data-Analysis and Sensitivity-Optimization Framework for the KATRIN Experiment

    Get PDF
    Presently under construction, the Karlsruhe TRitium Neutrino (KATRIN) experiment is the next generation tritium beta-decay experiment to perform a direct kinematical measurement of the electron neutrino mass with an unprecedented sensitivity of 200 meV (90% C.L.). This thesis describes the implementation of a consistent data analysis framework, addressing technical aspects of the data taking process and statistical challenges of a neutrino mass estimation from the beta-decay electron spectrum

    A Framework for Computing Discrete-Time Systems and Functions using DNA

    Get PDF
    University of Minnesota Ph.D. dissertation. July 2017. Major: Electrical/Computer Engineering. Advisors: Keshab Parhi, Marc Riedel. 1 computer file (PDF); xvii, 216 pages.Due to the recent advances in the field of synthetic biology, molecular computing has emerged as a non-conventional computing technology. A broad range of computational processes has been considered for molecular implementation. In this dissertation, we investigate the development of molecular systems for performing the following computations: signal processing, Markov chains, polynomials, and mathematical functions. First, we present a \textit{fully asynchronous} framework to design molecular signal processing algorithms. The framework maps each delay unit to two molecular types, i.e., first-type and second-type, and provides a 4-phase scheme to synchronize data flow for any multi-input/multi-output signal processing system. In the first phase, the input signal and values stored in all delay elements are consumed for computations. Results of computations are stored in the first-type molecules corresponding to the delay units and output variables. During the second phase, the values of the first-type molecules are transferred to the second-type molecules for the output variable. In the third phase, the concentrations of the first-type molecules are transferred to the second-type molecules associated with each delay element. Finally, in the fourth phase, the output molecules are collected. The method is illustrated by synthesizing a simple finite-impulse response (FIR) filter, an infinite-impulse response (IIR) filter, and an 8-point real-valued fast Fourier transform (FFT). The simulation results show that the proposed framework provides faster molecular signal processing systems compared to prior frameworks. We then present an overview of how continuous-time, discrete-time and digital signal processing systems can be implemented using molecular reactions. We also present molecular sensing systems where molecular reactions are used to implement analog-to-digital converters (ADCs) and digital-to-analog converters (DACs). These converters can be used to design mixed-signal processing molecular systems. A complete example of the addition of two molecules using digital implementation is described where the concentrations of two molecules are converted to digital by two 3-bit ADCs, and the 4-bit output of the digital adder is converted to analog by a 4-bit DAC. Furthermore, we describe implementation of other forms of molecular computation. We propose an approach to implement any first-order Markov chain using molecular reactions in general and DNA in particular. The Markov chain consists of two parts: a set of states and state transition probabilities. Each state is modeled by a unique molecular type, referred to as a data molecule. Each state transition is modeled by a unique molecular type, referred to as a control molecule, and a unique molecular reaction. Each reaction consumes data molecules of one state and produces data molecules of another state. The concentrations of control molecules are initialized according to the probabilities of corresponding state transitions in the chain. The steady-state probability of the Markov chain is computed by the equilibrium concentration of data molecules. We demonstrate our method for the Gambler’s Ruin problem as an instance of the Markov chain process. We analyze the method according to both the stochastic chemical kinetics and the mass-action kinetics model. Additionally, we propose a novel {\em unipolar molecular encoding} approach to compute a certain class of polynomials. In this molecular encoding, each variable is represented using two molecular types: a \mbox{type-0} and a \mbox{type-1}. The value is the ratio of the concentration of type-1 molecules to the sum of the concentrations of \mbox{type-0} and \mbox{type-1} molecules. With the new encoding, CRNs can compute any set of polynomial functions subject only to the limitation that these polynomials can be expressed as linear combinations of Bernstein basis polynomials with positive coefficients less than or equal to 1. The proposed encoding naturally exploits the expansion of a power-form polynomial into a Bernstein polynomial. We present molecular encoders for converting any input in a standard representation to the fractional representation, as well as decoders for converting the computed output from the fractional to a standard representation. Lastly, we expand the unipolar molecular encoding for bipolar molecular encoding and propose simple molecular circuits that can compute multiplication and scaled addition. Using these circuits, we design molecular circuits to compute more complex mathematical functions such as exe^{-x}, sin(x)\sin (x), and sigmoid(x)(x). According to this approach, we implement a molecular perceptron as a simple artificial neural network

    Formal Design and Analysis for DNA Implementations of Chemical Reaction Networks

    Get PDF
    In molecular programming, the Chemical Reaction Network model is often used to describe systems of interacting molecules. This model can describe either real systems, allowing us to analyze and determine their computational function; or describe hypothetical systems, with known computational function but perhaps no known physical example. One significant breakthrough in the field is that any Chemical Reaction Network can be approximated by a system using DNA Strand Displacement mechanisms. This allows the Chemical Reaction Network model to be treated like a programming language, where programs can be written in the abstract and then compiled into physical molecules. Given a programming language and a proof-of-concept compiler, one would want to take the compiler from the proof-of-concept stage into a more reliable, more systematic, and better understood process. This thesis is made up of my contributions to that effort. First, given a programming language and a compiler, it would be useful to formally verify that the compiler is correct. My collaborators, Qing Dong and Erik Winfree, and I defined a Chemical Reaction Network-specific form of bisimulation equivalence, which can compare two such networks and verify that one is (or is not) a correct implementation of the other. For example, the compiler-produced DNA circuit can be verified as an implementation of its abstract program, although this is not the only possible use. After defining this concept of equivalence, we show that it can be checked by algorithm; although various parts of the problem are NP-complete or PSPACE-complete, we give algorithms that meet these lower bounds. We also prove a number of interesting properties of Chemical Reaction Network bisimulation equivalence, including transitivity and modularity properties which are particularly useful for stepwise checking of large systems. We further extend this bisimulation method to linear Polymer Reaction Networks, a strictly more powerful abstraction which has been occasionally used in molecular programming. Again we prove complexity hardness results, which in this case are as expected uncomputable in the general case; however, many practical systems can still be verified, and we give one such example. Finally, we use bisimulation to identify a class of single-locus networks that are practical to implement. Thus we show a method of verification which can simplify use of the above-mentioned compiler by proving general statements of correctness about its results. Second, given a programming language and a concept of compiling it, it would be useful to optimize the result of the compilation. One particular area of optimization is the number of DNA strands per prepared complex; some experiments suggest that systems with no more than 2 strands per complex are more robust. Lulu Qian and I developed some proposed DNA Strand Displacement schemes for general Chemical Reaction Network implementations with no more than 2 strands per complex, and a number of other desirable properties. Meanwhile, having been shown to be useful for many reasons, the mechanisms of DNA Strand Displacement have recently been formalized, abstracted, and analyzed. I show that this formalization, combined with the bisimulation methods above, can prove various statements about the limits of DNA Strand Displacement systems. For example, a set of desirable conditions including the 2-strand limit cannot be achieved by any general Chemical Reaction Network implementation scheme. I also observe that two of the new schemes we discovered, each meeting all but one condition of the impossible set, were found in the process of coming up with this proof. I thus argue that through formalization of DNA Strand Displacement we can have a more systematic method of finding and designing molecular programs, and of knowing when the programs we want do not exist.</p

    DEVELOPMENT OF NANO/MICROELECTROMECHANICAL SYSTEM (N/MEMS) SWITCHES

    Get PDF
    Ph.DDOCTOR OF PHILOSOPH

    NASA Tech Briefs, September 1997

    Get PDF
    Topics include: Data Acquisition and Analysis; Electronic Components and Circuits; Electronic Systems; Physical Sciences; Materials; Computer Software; Mechanics; Machinery/Automation; Manufacturing/Fabrication; Mathematics and Information Sciences

    Non-invasive power gating techniques for bursty computation workloads using micro-electro-mechanical relays

    Get PDF
    PhD ThesisElectrostatically-actuated Micro-Electro-Mechanical/Nano-Electro- Mechanical (MEM/NEM) relays are promising devices overcoming the energy-efficiency limitations of CMOS transistors. Many exploratory research projects are currently under way investigating the mechanical, electrical and logical characteristics of MEM/NEM relays. One particular issue that this work addresses is the need for a scalable and accurate physical model of the MEM/NEM switches that can be plugged into the standard EDA software. The existing models are accurate and detailed but they suffer from the convergence problem. This problem requires finding ad-hoc workarounds and significantly impacts the designer’s productivity. In this thesis we propose a new simplified Verilog-AMS model. To test scalability of the proposed model we cross-checked it against our analysis of a range of benchmark circuits. Results show that, compared to standard models, the proposed model is sufficiently accurate with an average of 6% error and can handle larger designs without divergence. This thesis also investigates the modelling, designing and optimization of various MEM/NEM switches using 3D Finite Element Analysis (FEA) performed by the COMSOL multiphysics simulation tool. An extensive parametric sweep simulation is performed to study the energy-latency trade-offs of MEM/NEM relays. To accurately simulate MEMS/NEMS-based digital circuits, a Verilog-AMS model is proposed based on the evaluated parameters obtained from the multiphysics simulation tool. This allows an accurate calibration of the MEM/NEM relays with a significant reduction in simulation speed compared to that of 3D FEA exercised on COMSOL tool. The effectiveness of two power gating approaches in asynchronous micropipelines is also investigated using MEM/NEM switches and sleep transistors in reducing idle power dissipation with a particular target throughput. Sleep transistors are traditionally used to power gate idle circuits, however, these transistors have fundamental limitations in their effectiveness. Alternatively, MEM/NEM relays with zero leakage current can achieve greater energy savings under a certain data rate and design architecture. An asynchronous FIR filter 4 phase bundled data handshake protocol is presented. Implementation is accomplished in 90nm technology node and simulation exercised at various data rates and design complexities. It was demonstrated that our proposed approach offers 69% energy improvements at a data rate 1KHz compared to 39% of the previous work. The current trends for greater heterogeneity in future Systems-on- Chip (SoC) do not only concern their functionality but also their timing and power aspects. The increasing diversity of timing and power supply conditions, and associated concurrently operating modes, within an SoC calls for more efficient power delivery networks (PDN) for battery operated devices. This is especially important for systems with mixed duty cycling, where some parts are required to work regularly with low-throughput while other parts are activated spontaneously, i.e. in bursts. To improve their reaction time vs energy efficiency, this work proposes to incorporate a power-switching network based on MEM relays to switch the SoC power-performance state (PPS) into an active mode while eliminating the leakage current when it is idle. Results show that even with today0s large and high pull-in voltages, a MEM-relay-based power switching network (PSN) can achieve a 1000x savings in energy compared to its CMOS counterpart for low duty cycle. A simple case of optimising an on-chip charge pump required to switch-on the relay has been investigated and its energy-latency overhead has been evaluated. Heterogeneous many-core systems are increasingly being employed in modern embedded platforms for high throughput at low energy cost considerations. These applications typically exhibit bursty workloads that provide opportunities to minimize system energy. CMOS-based power gating circuitry, typically consisting of sleep transistors, is used as an effective technique for idle energy reduction in such applications. However, these transistors contribute high leakage current when driving large capacitive loads, making effective energy minimization challenging. This thesis proposes a novel MEMS-based idle energy control approach. Core to this approach is an integrated sleep mode management based on the performance-energy states and bursty workloads indicated by the performance counters. A number of PARSEC benchmark applications are used as case studies of bursty workloads, including CPU- and memory- intensive ones. These applications are exercised on an Exynos 5422 heterogeneous many-core platform, engineered with a performance counter facilities, showing 55.5% energy savings compared with an on-demand governor. Furthermore, an extensive trade-off analysis demonstrates the comparative advantages of the MEMS-based controller, including zero-leakage current and non-invasive implementations suitable for commercial off-the-shelf systems.Higher committee of education development in Iraq (HCED

    Using MapReduce Streaming for Distributed Life Simulation on the Cloud

    Get PDF
    Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

    12th EASN International Conference on "Innovation in Aviation & Space for opening New Horizons"

    Get PDF
    Epoxy resins show a combination of thermal stability, good mechanical performance, and durability, which make these materials suitable for many applications in the Aerospace industry. Different types of curing agents can be utilized for curing epoxy systems. The use of aliphatic amines as curing agent is preferable over the toxic aromatic ones, though their incorporation increases the flammability of the resin. Recently, we have developed different hybrid strategies, where the sol-gel technique has been exploited in combination with two DOPO-based flame retardants and other synergists or the use of humic acid and ammonium polyphosphate to achieve non-dripping V-0 classification in UL 94 vertical flame spread tests, with low phosphorous loadings (e.g., 1-2 wt%). These strategies improved the flame retardancy of the epoxy matrix, without any detrimental impact on the mechanical and thermal properties of the composites. Finally, the formation of a hybrid silica-epoxy network accounted for the establishment of tailored interphases, due to a better dispersion of more polar additives in the hydrophobic resin

    Hadron models and related New Energy issues

    Get PDF
    The present book covers a wide-range of issues from alternative hadron models to their likely implications in New Energy research, including alternative interpretation of lowenergy reaction (coldfusion) phenomena. The authors explored some new approaches to describe novel phenomena in particle physics. M Pitkanen introduces his nuclear string hypothesis derived from his Topological Geometrodynamics theory, while E. Goldfain discusses a number of nonlinear dynamics methods, including bifurcation, pattern formation (complex GinzburgLandau equation) to describe elementary particle masses. Fu Yuhua discusses a plausible method for prediction of phenomena related to New Energy development. F. Smarandache discusses his unmatter hypothesis, and A. Yefremov et al. discuss Yang-Mills field from Quaternion Space Geometry. Diego Rapoport discusses theoretical link between Torsion fields and Hadronic Mechanic. A.H. Phillips discusses semiconductor nanodevices, while V. and A. Boju discuss Digital Discrete and Combinatorial methods and their likely implications in New Energy research. Pavel Pintr et al. describe planetary orbit distance from modified Schrödinger equation, and M. Pereira discusses his new Hypergeometrical description of Standard Model of elementary particles. The present volume will be suitable for researchers interested in New Energy issues, in particular their link with alternative hadron models and interpretation
    corecore