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Unexpected relationships among the various aminoacyl-tRNA synthetases continue to be uncovered. The question arises - is this mainly the result of promiscuous exchange, or is the confusion really a reflection of the differential loss of past duplications? Phylogenetic analysis may yet provide the answer.
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This tutorial will cover the basics of model-based prognostics, and include concepts such as modeling approaches, estimation and prediction algorithms, and how uncertainty is represented and quantified. Other topics covered will include structural model decomposition, system-level prognostics, prognostics of hybrid systems, and distributed prognostics. Several case studies, such as water recovery systems to the prediction of safety margins in the national airspace system will be used to explain different concepts of prognostics and demonstrate their application to real-world systems.
The Huntsville Operations Support Center (HOSC) is a distributed computer system used to provide real time data acquisition, analysis and display during NASA space missions and to perform simulation and study activities during non-mission times. The primary purpose is to provide a HOSC system simulation model that is used to investigate the effects of various HOSC system configurations. Such a model would be valuable in planning the future growth of HOSC and in ascertaining the effects of data rate variations, update table broadcasting and smart display terminal data requirements on the HOSC HYPERchannel network system. A simulation model was developed in PASCAL and results of the simulation model for various system configuraions were obtained. A tutorial of the model is presented and the results of simulation runs are presented. Some very high data rate situations were simulated to observe the effects of the HYPERchannel switch over from contention to priority mode under high channel loading.
The purpose of this tutorial is to demonstrate how to use Markov chain Monte Carlo (MCMC) to calibrate a model. By calibration, we mean the selection of model parameters (and, when relevant, structures). A common goal in model development and diagnostics is calibration, or the identification of model structures and parameters which are consistent with data. While models can be calibrated through hand-tuning parameters or minimizing simple error metrics such as root-mean-square-error (RMSE), these approaches can underrepresent the probabilistic nature of the data-generating process, as well as the potential for multiple model configurations to be consistent with the data. Probabilistic uncertainty quantification, which is the topic of this notebook, can address these concerns. This tutorial is presented as an appendix to the e-book: Addressing Uncertainty in MultiSector Dynamics Research.
Fluid models are essential for understanding and predicting low-temperature plasma (LTP) behavior in various scientific and industrial settings. This paper provides an introductory tutorial on fluid modeling of LTPs, covering model formulation, implementation, and computational simulations. The tutorial focuses on five main components of the formulation of LTP fluid models: fluid flow, energy, chemistry, electromagnetism, and material properties, as well as in essential aspects of model implementations, including multiscale phenomena, multiphysics coupling, and numerical convergence. Designed for students and early-career researchers, this work offers a practical foundation for developing and using fluid models, from in-house computational codes to commercial software, bridging fundamental theory with real-world applications.
This Tutorial provides a step-by-step guide on how to apply supervised machine-learning techniques to analyze diffraction and spectroscopy data. This Tutorial details four models—a reconstruction-focused model, a regression-focused model, a hybrid reconstruction/regression model, and a multimodal model—that use x-ray diffraction profiles and vibrational density of states spectra to predict various microstructural descriptors. In this Tutorial, we cover data pre-processing steps, constructions of the models via dimensionality reduction and regression, training, and analysis of these models. Comparisons of the model’s performance are provided, highlighting the strength and weakness of the various approaches utilized.
This tutorial offers a pedagogical guide to hybrid quantum processors that integrate discrete-variable (DV) qubits and continuous-variable (CV) oscillators. Aimed at computer scientists, engineers, and physicists, it provides an overview of the experimental, algorithmic, and architectural aspects of this novel and rapidly developing hardware model. Experimental realizations of this model include superconducting, trapped-ion, and neutral-atom platforms. By combining DV and CV components, hybrid oscillator-qubit processors enable a powerful new paradigm that offers complementary strengths for quantum control, error correction, computation, and simulation. Working toward the goal of a full-stack system connecting applications to CV-DV hardware, we define and formulate abstract machine models and instruction set architectures. These essential abstractions enable codesign of hardware and software, and resource estimation for exploring the potential of current and future hardware for computational and simulation tasks. Using these abstractions, we present both new and existing examples that illustrate the benefits of hybrid CV-DV processors relative to traditional DV-only hardware in computation as well as quantum simulation of physical models. Examples include algorithms for transferring states between DV and CV systems, performing the quantum Fourier transform, and simulation of lattice gauge theories. Relative to qubit-only hardware, the bosonic degrees of freedom natively available in hybrid architectures can substantially reduce the circuit complexity of simulations for physical models containing bosons. A key technique is the extension of quantum signal processing ideas to CV-DV systems. This work is intended to serve as a timely and comprehensive guide to this relatively unexplored yet promising approach to quantum computation and to provide a road map to guide future development.
PVSC tutorial demonstrating how to download irradiance data and sun position for a specific location, determine the orientation of a single-axis tracker system, calculate Plane of Array irradiance, and estimate the power output of a PV system.
Tutorial at the upcoming BIRS workshop https://www.birs.ca/events/2025/5-day-workshops/25w5381/schedule
This document explains all the necessary steps in order to generate optimized C code from Simulink Models. This document also covers some general information on good programming practices, selection of variable types, how to organize models and subsystems, and finally how to test the generated C code and compare it with data from MATLAB.
Space missions with small crews extending over several years with time-delay preventing normal conversations with people on earth will raise many challenges for training. Of special interest are possible three-year missions to Mars, requiring refresher instruction and learning new skills based on unexpected problems with machines and environmental conditions. For example, the crew will be required to monitor and repair more complex life support systems for air and water recycling than we even know how to build today. Highly educated astronauts, often with several doctorate degrees, require a very different mode of interaction than we have developed for school children or even typical college students. Explanation methods may need to differ-using analogies and techniques from different domains-depending on whether the astronaut is an astrophysicist, a pilot, or a geologist.Virtual reality (e.g., for Hubble repair missions) and "integrated" simulations (involving role-playing and emphasizing failure scenarios) are the most common advanced forms of instruction used in space flight today. The emphasis is on collaborative, embodied interaction with the same workstations and tools used in practice (e.g., a cockpit simulator). Otherwise, computerized instructional technology used by NASA is not model-based or tutorial in nature. This discussion will review some of the key instructional methods used at NASA over the past two decades and consider why ITS methods have not been exploited. Some of the problems and opportunities for training for Mars missions are examined, including how using robots in exploration activities will help but raise new training problems. These ideas will be illustrated with examples from the BrahmsVE system in which a browser- based virtual reality display with avatars allows interacting with a distributed multiagent system, in which agents can be people, robots, or software programs. Using BrahmsVE may provide a way for astronauts to interact with proxies of people who serve as instructional coaches on Mars.
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The CARE 3 reliability model for aircraft avionics and control systems is described by utilizing a number of examples which frequently use state-of-the-art mathematical modeling techniques as a basis for their exposition. Behavioral decomposition followed by aggregration were used in an attempt to deal with reliability models with a large number of states. A comprehensive set of models of the fault-handling processes in a typical fault-tolerant system was used. These models were semi-Markov in nature, thus removing the usual restrictions of exponential holding times within the coverage model. The aggregate model is a non-homogeneous Markov chain, thus allowing the times to failure to posses Weibull-like distributions. Because of the departures from traditional models, the solution method employed is that of Kolmogorov integral equations, which are evaluated numerically.
A step-by-step tutorial of the methods and tools used for the reliability analysis of fault-tolerant systems is presented. Emphasis is on the representation of architectural features in mathematical models. Details of the mathematical solution of complex reliability models are not presented. Instead the use of several recently developed computer programs--SURE, ASSIST, STEM, PAWS--which automate the generation and solution of these models is described.
The World Ocean Circulation Experiment (WOCE) Young Investigator Workshops goals and objectives are: a) to familiarize Young Investigators with WOCE models, datasets and estimation procedures; b) to offer intensive hands-on exposure to these models ard methods; c) to build collaborations among junior scientists and more senior WOCE investigators; and finally, d) to generate ideas and projects leading to fundable WOCE synthesis projects. To achieve these goals and objectives, the Workshop will offer a mixture of tutorial lectures on numerical models and estimation procedures, advanced seminars on current WOCE synthesis activities and related projects, and the opportunity to conduct small projects which put into practice the techniques advanced in the lectures.
This paper is intended as a tutorial introduction to certain aspects of response surface modeling, for the experimentalist who has started to explore these methods as a means of improving productivity and quality in wind tunnel testing and other aerospace applications. A brief review of the productivity advantages of response surface modeling in aerospace research is followed by a description of the advantages of a common coding scheme that scales and centers independent variables. The benefits of model term reduction are reviewed. A constraint on model term reduction with coded factors is described in some detail, which requires such models to be well-formulated, or hierarchical. Examples illustrate the consequences of ignoring this constraint. The implication for automated regression model reduction procedures is discussed, and some opinions formed from the author s experience are offered on coding, model reduction, and hierarchy.
The interface between two immiscible liquids with immobilized photosynthetic pigments can serve as the simplest model of a biological membrane convenient for the investigation of photoprocesses accompanied by spatial separation of charges. As it follows from thermodynamics, if the resolvation energies of substrates and products are very different, the interface between two immiscible liquids may act as a catalyst. Theoretical aspects of charge transfer reactions at oil/water interfaces are discussed. Conditions under which the free energy of activation of the interfacial reaction of electron transfer decreases are established. The activation energy of electron transfer depends on the charges of the reactants and dielectric permittivity of the non-aqueous phase. This can be useful when choosing a pair of immiscible solvents to decrease the activation energy of the reaction in question or to inhibit an undesired process. Experimental interfacial catalytic systems are discussed. Amphiphilic molecules such as chlorophyll or porphyrins were studied as catalysts of electron transfer reactions at the oil/water interface.