WorldWideScience

Sample records for science molecular machines

  1. Operation of micro and molecular machines: a new concept with its origins in interface science.

    Science.gov (United States)

    Ariga, Katsuhiko; Ishihara, Shinsuke; Izawa, Hironori; Xia, Hong; Hill, Jonathan P

    2011-03-21

    A landmark accomplishment of nanotechnology would be successful fabrication of ultrasmall machines that can work like tweezers, motors, or even computing devices. Now we must consider how operation of micro- and molecular machines might be implemented for a wide range of applications. If these machines function only under limited conditions and/or require specialized apparatus then they are useless for practical applications. Therefore, it is important to carefully consider the access of functionality of the molecular or nanoscale systems by conventional stimuli at the macroscopic level. In this perspective, we will outline the position of micro- and molecular machines in current science and technology. Most of these machines are operated by light irradiation, application of electrical or magnetic fields, chemical reactions, and thermal fluctuations, which cannot always be applied in remote machine operation. We also propose strategies for molecular machine operation using the most conventional of stimuli, that of macroscopic mechanical force, achieved through mechanical operation of molecular machines located at an air-water interface. The crucial roles of the characteristics of an interfacial environment, i.e. connection between macroscopic dimension and nanoscopic function, and contact of media with different dielectric natures, are also described.

  2. Making molecular machines work

    NARCIS (Netherlands)

    Browne, Wesley R.; Feringa, Ben L.

    2006-01-01

    In this review we chart recent advances in what is at once an old and very new field of endeavour the achievement of control of motion at the molecular level including solid-state and surface-mounted rotors, and its natural progression to the development of synthetic molecular machines. Besides a

  3. Molecular sciences

    International Nuclear Information System (INIS)

    Anon.

    1975-01-01

    The research in molecular sciences summarized includes photochemistry, radiation chemistry, geophysics, electromechanics, heavy-element oxidizers , heavy element chemistry collisions, atoms, organic solids. A list of publications is included

  4. Molecular machines open cell membranes.

    Science.gov (United States)

    García-López, Víctor; Chen, Fang; Nilewski, Lizanne G; Duret, Guillaume; Aliyan, Amir; Kolomeisky, Anatoly B; Robinson, Jacob T; Wang, Gufeng; Pal, Robert; Tour, James M

    2017-08-30

    Beyond the more common chemical delivery strategies, several physical techniques are used to open the lipid bilayers of cellular membranes. These include using electric and magnetic fields, temperature, ultrasound or light to introduce compounds into cells, to release molecular species from cells or to selectively induce programmed cell death (apoptosis) or uncontrolled cell death (necrosis). More recently, molecular motors and switches that can change their conformation in a controlled manner in response to external stimuli have been used to produce mechanical actions on tissue for biomedical applications. Here we show that molecular machines can drill through cellular bilayers using their molecular-scale actuation, specifically nanomechanical action. Upon physical adsorption of the molecular motors onto lipid bilayers and subsequent activation of the motors using ultraviolet light, holes are drilled in the cell membranes. We designed molecular motors and complementary experimental protocols that use nanomechanical action to induce the diffusion of chemical species out of synthetic vesicles, to enhance the diffusion of traceable molecular machines into and within live cells, to induce necrosis and to introduce chemical species into live cells. We also show that, by using molecular machines that bear short peptide addends, nanomechanical action can selectively target specific cell-surface recognition sites. Beyond the in vitro applications demonstrated here, we expect that molecular machines could also be used in vivo, especially as their design progresses to allow two-photon, near-infrared and radio-frequency activation.

  5. Molecular machines open cell membranes

    Science.gov (United States)

    García-López, Víctor; Chen, Fang; Nilewski, Lizanne G.; Duret, Guillaume; Aliyan, Amir; Kolomeisky, Anatoly B.; Robinson, Jacob T.; Wang, Gufeng; Pal, Robert; Tour, James M.

    2017-08-01

    Beyond the more common chemical delivery strategies, several physical techniques are used to open the lipid bilayers of cellular membranes. These include using electric and magnetic fields, temperature, ultrasound or light to introduce compounds into cells, to release molecular species from cells or to selectively induce programmed cell death (apoptosis) or uncontrolled cell death (necrosis). More recently, molecular motors and switches that can change their conformation in a controlled manner in response to external stimuli have been used to produce mechanical actions on tissue for biomedical applications. Here we show that molecular machines can drill through cellular bilayers using their molecular-scale actuation, specifically nanomechanical action. Upon physical adsorption of the molecular motors onto lipid bilayers and subsequent activation of the motors using ultraviolet light, holes are drilled in the cell membranes. We designed molecular motors and complementary experimental protocols that use nanomechanical action to induce the diffusion of chemical species out of synthetic vesicles, to enhance the diffusion of traceable molecular machines into and within live cells, to induce necrosis and to introduce chemical species into live cells. We also show that, by using molecular machines that bear short peptide addends, nanomechanical action can selectively target specific cell-surface recognition sites. Beyond the in vitro applications demonstrated here, we expect that molecular machines could also be used in vivo, especially as their design progresses to allow two-photon, near-infrared and radio-frequency activation.

  6. Introducing Stable Radicals into Molecular Machines.

    Science.gov (United States)

    Wang, Yuping; Frasconi, Marco; Stoddart, J Fraser

    2017-09-27

    Ever since their discovery, stable organic radicals have received considerable attention from chemists because of their unique optical, electronic, and magnetic properties. Currently, one of the most appealing challenges for the chemical community is to develop sophisticated artificial molecular machines that can do work by consuming external energy, after the manner of motor proteins. In this context, radical-pairing interactions are important in addressing the challenge: they not only provide supramolecular assistance in the synthesis of molecular machines but also open the door to developing multifunctional systems relying on the various properties of the radical species. In this Outlook, by taking the radical cationic state of 1,1'-dialkyl-4,4'-bipyridinium (BIPY •+ ) as an example, we highlight our research on the art and science of introducing radical-pairing interactions into functional systems, from prototypical molecular switches to complex molecular machines, followed by a discussion of the (i) limitations of the current systems and (ii) future research directions for designing BIPY •+ -based molecular machines with useful functions.

  7. Nano Trek Beyond: Driving Nanocars/Molecular Machines at Interfaces.

    Science.gov (United States)

    Ariga, Katsuhiko; Mori, Taizo; Nakanishi, Waka

    2018-03-09

    In 2016, the Nobel Prize in Chemistry was awarded for pioneering work on molecular machines. Half a year later, in Toulouse, the first molecular car race, a "nanocar race", was held by using the tip of a scanning tunneling microscope as an electrical remote control. In this Focus Review, we discuss the current state-of-the-art in research on molecular machines at interfaces. In the first section, we briefly explain the science behind the nanocar race, followed by a selection of recent examples of controlling molecules on surfaces. Finally, motion synchronization and the functions of molecular machines at liquid interfaces are discussed. This new concept of molecular tuning at interfaces is also introduced as a method for the continuous modification and optimization of molecular structure for target functions. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  8. Molecular machines with bio-inspired mechanisms.

    Science.gov (United States)

    Zhang, Liang; Marcos, Vanesa; Leigh, David A

    2018-02-26

    The widespread use of molecular-level motion in key natural processes suggests that great rewards could come from bridging the gap between the present generation of synthetic molecular machines-which by and large function as switches-and the machines of the macroscopic world, which utilize the synchronized behavior of integrated components to perform more sophisticated tasks than is possible with any individual switch. Should we try to make molecular machines of greater complexity by trying to mimic machines from the macroscopic world or instead apply unfamiliar (and no doubt have to discover or invent currently unknown) mechanisms utilized by biological machines? Here we try to answer that question by exploring some of the advances made to date using bio-inspired machine mechanisms.

  9. Dynamics and Thermodynamics of Molecular Machines

    DEFF Research Database (Denmark)

    Golubeva, Natalia

    2014-01-01

    to their microscopic size, molecular motors are governed by principles fundamentally different from those describing the operation of man-made motors such as car engines. In this dissertation the dynamic and thermodynamic properties of molecular machines are studied using the tools of nonequilibrium statistical......Molecular machines, or molecular motors, are small biophysical devices that perform a variety of essential metabolic processes such as DNA replication, protein synthesis and intracellular transport. Typically, these machines operate by converting chemical energy into motion and mechanical work. Due...... mechanics. The first part focuses on noninteracting molecular machines described by a paradigmatic continuum model with the aim of comparing and contrasting such a description to the one offered by the widely used discrete models. Many molecular motors, for example, kinesin involved in cellular cargo...

  10. Stereodivergent synthesis with a programmable molecular machine

    Science.gov (United States)

    Kassem, Salma; Lee, Alan T. L.; Leigh, David A.; Marcos, Vanesa; Palmer, Leoni I.; Pisano, Simone

    2017-09-01

    It has been convincingly argued that molecular machines that manipulate individual atoms, or highly reactive clusters of atoms, with Ångström precision are unlikely to be realized. However, biological molecular machines routinely position rather less reactive substrates in order to direct chemical reaction sequences, from sequence-specific synthesis by the ribosome to polyketide synthases, where tethered molecules are passed from active site to active site in multi-enzyme complexes. Artificial molecular machines have been developed for tasks that include sequence-specific oligomer synthesis and the switching of product chirality, a photo-responsive host molecule has been described that is able to mechanically twist a bound molecular guest, and molecular fragments have been selectively transported in either direction between sites on a molecular platform through a ratchet mechanism. Here we detail an artificial molecular machine that moves a substrate between different activating sites to achieve different product outcomes from chemical synthesis. This molecular robot can be programmed to stereoselectively produce, in a sequential one-pot operation, an excess of any one of four possible diastereoisomers from the addition of a thiol and an alkene to an α,β-unsaturated aldehyde in a tandem reaction process. The stereodivergent synthesis includes diastereoisomers that cannot be selectively synthesized through conventional iminium-enamine organocatalysis. We anticipate that future generations of programmable molecular machines may have significant roles in chemical synthesis and molecular manufacturing.

  11. Macroscopic transport by synthetic molecular machines

    NARCIS (Netherlands)

    Berna, J; Leigh, DA; Lubomska, M; Mendoza, SM; Perez, EM; Rudolf, P; Teobaldi, G; Zerbetto, F

    Nature uses molecular motors and machines in virtually every significant biological process, but demonstrating that simpler artificial structures operating through the same gross mechanisms can be interfaced with - and perform physical tasks in - the macroscopic world represents a significant hurdle

  12. A nanoplasmonic switch based on molecular machines

    KAUST Repository

    Zheng, Yue Bing; Yang, Ying-Wei; Jensen, Lasse; Fang, Lei; Juluri, Bala Krishna; Weiss, Paul S.; Stoddart, J. Fraser; Huang, Tony Jun

    2009-01-01

    We aim to develop a molecular-machine-driven nanoplasmonic switch for its use in future nanophotonic integrated circuits (ICs) that have applications in optical communication, information processing, biological and chemical sensing. Experimental

  13. Light-driven molecular machine at ITIES

    International Nuclear Information System (INIS)

    Kornyshev, Alexei A; Kuimova, Marina; Kuznetsov, Alexander M; Ulstrup, Jens; Urbakh, Michael

    2007-01-01

    We suggest a principle of operation of a new molecular device that transforms the energy of light into repetitive mechanical motions. Such a device can also serve as a model system for the study of the effect of electric field on intramolecular electron transfer. We discuss the design of suitable molecular systems and the methods that may monitor the 'performance' of such a machine

  14. A nanoplasmonic switch based on molecular machines

    KAUST Repository

    Zheng, Yue Bing

    2009-06-01

    We aim to develop a molecular-machine-driven nanoplasmonic switch for its use in future nanophotonic integrated circuits (ICs) that have applications in optical communication, information processing, biological and chemical sensing. Experimental data show that an Au nanodisk array, coated with rotaxane molecular machines, switches its localized surface plasmon resonances (LSPR) reversibly when it is exposed to chemical oxidants and reductants. Conversely, bare Au nanodisks and disks coated with mechanically inert control compounds, do not display the same switching behavior. Along with calculations based on time-dependent density functional theory (TDDFT), these observations suggest that the nanoscale movements within surface-bound "molecular machines" can be used as the active components in plasmonic devices. ©2009 IEEE.

  15. From Molecule to Molecular Machines

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 23; Issue 3 ... In this review article, the concept of supramolecularchemistry, cooperativity responsible for interactions, techniquesfor determination of thermodynamic parameters ofcooperativity, and the contribution of supramolecular chemistryto ...

  16. Molecular computing: paths to chemical Turing machines.

    Science.gov (United States)

    Varghese, Shaji; Elemans, Johannes A A W; Rowan, Alan E; Nolte, Roeland J M

    2015-11-13

    To comply with the rapidly increasing demand of information storage and processing, new strategies for computing are needed. The idea of molecular computing, where basic computations occur through molecular, supramolecular, or biomolecular approaches, rather than electronically, has long captivated researchers. The prospects of using molecules and (bio)macromolecules for computing is not without precedent. Nature is replete with examples where the handling and storing of data occurs with high efficiencies, low energy costs, and high-density information encoding. The design and assembly of computers that function according to the universal approaches of computing, such as those in a Turing machine, might be realized in a chemical way in the future; this is both fascinating and extremely challenging. In this perspective, we highlight molecular and (bio)macromolecular systems that have been designed and synthesized so far with the objective of using them for computing purposes. We also present a blueprint of a molecular Turing machine, which is based on a catalytic device that glides along a polymer tape and, while moving, prints binary information on this tape in the form of oxygen atoms.

  17. Machine Learning Techniques in Clinical Vision Sciences.

    Science.gov (United States)

    Caixinha, Miguel; Nunes, Sandrina

    2017-01-01

    This review presents and discusses the contribution of machine learning techniques for diagnosis and disease monitoring in the context of clinical vision science. Many ocular diseases leading to blindness can be halted or delayed when detected and treated at its earliest stages. With the recent developments in diagnostic devices, imaging and genomics, new sources of data for early disease detection and patients' management are now available. Machine learning techniques emerged in the biomedical sciences as clinical decision-support techniques to improve sensitivity and specificity of disease detection and monitoring, increasing objectively the clinical decision-making process. This manuscript presents a review in multimodal ocular disease diagnosis and monitoring based on machine learning approaches. In the first section, the technical issues related to the different machine learning approaches will be present. Machine learning techniques are used to automatically recognize complex patterns in a given dataset. These techniques allows creating homogeneous groups (unsupervised learning), or creating a classifier predicting group membership of new cases (supervised learning), when a group label is available for each case. To ensure a good performance of the machine learning techniques in a given dataset, all possible sources of bias should be removed or minimized. For that, the representativeness of the input dataset for the true population should be confirmed, the noise should be removed, the missing data should be treated and the data dimensionally (i.e., the number of parameters/features and the number of cases in the dataset) should be adjusted. The application of machine learning techniques in ocular disease diagnosis and monitoring will be presented and discussed in the second section of this manuscript. To show the clinical benefits of machine learning in clinical vision sciences, several examples will be presented in glaucoma, age-related macular degeneration

  18. Learning surface molecular structures via machine vision

    Science.gov (United States)

    Ziatdinov, Maxim; Maksov, Artem; Kalinin, Sergei V.

    2017-08-01

    Recent advances in high resolution scanning transmission electron and scanning probe microscopies have allowed researchers to perform measurements of materials structural parameters and functional properties in real space with a picometre precision. In many technologically relevant atomic and/or molecular systems, however, the information of interest is distributed spatially in a non-uniform manner and may have a complex multi-dimensional nature. One of the critical issues, therefore, lies in being able to accurately identify (`read out') all the individual building blocks in different atomic/molecular architectures, as well as more complex patterns that these blocks may form, on a scale of hundreds and thousands of individual atomic/molecular units. Here we employ machine vision to read and recognize complex molecular assemblies on surfaces. Specifically, we combine Markov random field model and convolutional neural networks to classify structural and rotational states of all individual building blocks in molecular assembly on the metallic surface visualized in high-resolution scanning tunneling microscopy measurements. We show how the obtained full decoding of the system allows us to directly construct a pair density function—a centerpiece in analysis of disorder-property relationship paradigm—as well as to analyze spatial correlations between multiple order parameters at the nanoscale, and elucidate reaction pathway involving molecular conformation changes. The method represents a significant shift in our way of analyzing atomic and/or molecular resolved microscopic images and can be applied to variety of other microscopic measurements of structural, electronic, and magnetic orders in different condensed matter systems.

  19. Light-operated machines based on threaded molecular structures.

    Science.gov (United States)

    Credi, Alberto; Silvi, Serena; Venturi, Margherita

    2014-01-01

    Rotaxanes and related species represent the most common implementation of the concept of artificial molecular machines, because the supramolecular nature of the interactions between the components and their interlocked architecture allow a precise control on the position and movement of the molecular units. The use of light to power artificial molecular machines is particularly valuable because it can play the dual role of "writing" and "reading" the system. Moreover, light-driven machines can operate without accumulation of waste products, and photons are the ideal inputs to enable autonomous operation mechanisms. In appropriately designed molecular machines, light can be used to control not only the stability of the system, which affects the relative position of the molecular components but also the kinetics of the mechanical processes, thereby enabling control on the direction of the movements. This step forward is necessary in order to make a leap from molecular machines to molecular motors.

  20. Molecular active plasmonics: controlling plasmon resonances with molecular machines

    KAUST Repository

    Zheng, Yue Bing; Yang, Ying-Wei; Jensen, Lasse; Fang, Lei; Juluri, Bala Krishna; Flood, Amar H.; Weiss, Paul S.; Stoddart, J. Fraser; Huang, Tony Jun

    2009-01-01

    The paper studies the molecular-level active control of localized surface plasmon resonances (LSPRs) of Au nanodisk arrays with molecular machines. Two types of molecular machines - azobenzene and rotaxane - have been demonstrated to enable the reversible tuning of the LSPRs via the controlled mechanical movements. Azobenzene molecules have the property of trans-cis photoisomerization and enable the photo-induced nematic (N)-isotropic (I) phase transition of the liquid crystals (LCs) that contain the molecules as dopant. The phase transition of the azobenzene-doped LCs causes the refractive-index difference of the LCs, resulting in the reversible peak shift of the LSPRs of the embedded Au nanodisks due to the sensitivity of the LSPRs to the disks' surroundings' refractive index. Au nanodisk array, coated with rotaxanes, switches its LSPRs reversibly when it is exposed to chemical oxidants and reductants alternatively. The correlation between the peak shift of the LSPRs and the chemically driven mechanical movement of rotaxanes is supported by control experiments and a time-dependent density functional theory (TDDFT)-based, microscopic model.

  1. Molecular active plasmonics: controlling plasmon resonances with molecular machines

    KAUST Repository

    Zheng, Yue Bing

    2009-08-26

    The paper studies the molecular-level active control of localized surface plasmon resonances (LSPRs) of Au nanodisk arrays with molecular machines. Two types of molecular machines - azobenzene and rotaxane - have been demonstrated to enable the reversible tuning of the LSPRs via the controlled mechanical movements. Azobenzene molecules have the property of trans-cis photoisomerization and enable the photo-induced nematic (N)-isotropic (I) phase transition of the liquid crystals (LCs) that contain the molecules as dopant. The phase transition of the azobenzene-doped LCs causes the refractive-index difference of the LCs, resulting in the reversible peak shift of the LSPRs of the embedded Au nanodisks due to the sensitivity of the LSPRs to the disks\\' surroundings\\' refractive index. Au nanodisk array, coated with rotaxanes, switches its LSPRs reversibly when it is exposed to chemical oxidants and reductants alternatively. The correlation between the peak shift of the LSPRs and the chemically driven mechanical movement of rotaxanes is supported by control experiments and a time-dependent density functional theory (TDDFT)-based, microscopic model.

  2. Stochastic thermodynamics, fluctuation theorems and molecular machines

    International Nuclear Information System (INIS)

    Seifert, Udo

    2012-01-01

    Stochastic thermodynamics as reviewed here systematically provides a framework for extending the notions of classical thermodynamics such as work, heat and entropy production to the level of individual trajectories of well-defined non-equilibrium ensembles. It applies whenever a non-equilibrium process is still coupled to one (or several) heat bath(s) of constant temperature. Paradigmatic systems are single colloidal particles in time-dependent laser traps, polymers in external flow, enzymes and molecular motors in single molecule assays, small biochemical networks and thermoelectric devices involving single electron transport. For such systems, a first-law like energy balance can be identified along fluctuating trajectories. For a basic Markovian dynamics implemented either on the continuum level with Langevin equations or on a discrete set of states as a master equation, thermodynamic consistency imposes a local-detailed balance constraint on noise and rates, respectively. Various integral and detailed fluctuation theorems, which are derived here in a unifying approach from one master theorem, constrain the probability distributions for work, heat and entropy production depending on the nature of the system and the choice of non-equilibrium conditions. For non-equilibrium steady states, particularly strong results hold like a generalized fluctuation–dissipation theorem involving entropy production. Ramifications and applications of these concepts include optimal driving between specified states in finite time, the role of measurement-based feedback processes and the relation between dissipation and irreversibility. Efficiency and, in particular, efficiency at maximum power can be discussed systematically beyond the linear response regime for two classes of molecular machines, isothermal ones such as molecular motors, and heat engines such as thermoelectric devices, using a common framework based on a cycle decomposition of entropy production. (review article)

  3. Deep Generative Models for Molecular Science

    DEFF Research Database (Denmark)

    Jørgensen, Peter Bjørn; Schmidt, Mikkel Nørgaard; Winther, Ole

    2018-01-01

    Generative deep machine learning models now rival traditional quantum-mechanical computations in predicting properties of new structures, and they come with a significantly lower computational cost, opening new avenues in computational molecular science. In the last few years, a variety of deep...... generative models have been proposed for modeling molecules, which differ in both their model structure and choice of input features. We review these recent advances within deep generative models for predicting molecular properties, with particular focus on models based on the probabilistic autoencoder (or...

  4. Distinguished figures in mechanism and machine science

    CERN Document Server

    2014-01-01

    This book is composed of chapters that focus specifically on technological developments by distinguished figures in the history of MMS (Mechanism and Machine Science).  Biographies of well-known scientists are also included to describe their efforts and experiences, and surveys of their work and achievements, and a modern interpretation of their legacy are presented. After the first two volumes, the papers in this third volume again cover a wide range within the field of the History of Mechanical Engineering with specific focus on MMS and will be of interest and motivation to the work (historical or not) of many.

  5. Machine learning and pattern recognition from surface molecular architectures.

    Science.gov (United States)

    Maksov, Artem; Ziatdinov, Maxim; Fujii, Shintaro; Sumpter, Bobby; Kalinin, Sergei

    The ability to utilize molecular assemblies as data storage devices requires capability to identify individual molecular states on a scale of thousands of molecules. We present a novel method of applying machine learning techniques for extraction of positional and rotational information from ultra-high vacuum scanning tunneling microscopy (STM) images and apply it to self-assembled monolayer of π-bowl sumanene molecules on gold. From density functional theory (DFT) simulations, we assume existence of distinct polar and multiple azimuthal rotational states. We use DFT-generated templates in conjunction with Markov Chain Monte Carlo (MCMC) sampler and noise modeling to create synthetic images representative of our model. We extract positional information of each molecule and use nearest neighbor criteria to construct a graph input to Markov Random Field (MRF) model to identify polar rotational states. We train a convolutional Neural Network (cNN) on a synthetic dataset and combine it with MRF model to classify molecules based on their azimuthal rotational state. We demonstrate effectiveness of such approach compared to other methods. Finally, we apply our approach to experimental images and achieve complete rotational class information extraction. This research was sponsored by the Division of Materials Sciences and Engineering, Office of Science, Basic Energy Sciences, US DOE.

  6. Nanoscale swimmers: hydrodynamic interactions and propulsion of molecular machines

    Science.gov (United States)

    Sakaue, T.; Kapral, R.; Mikhailov, A. S.

    2010-06-01

    Molecular machines execute nearly regular cyclic conformational changes as a result of ligand binding and product release. This cyclic conformational dynamics is generally non-reciprocal so that under time reversal a different sequence of machine conformations is visited. Since such changes occur in a solvent, coupling to solvent hydrodynamic modes will generally result in self-propulsion of the molecular machine. These effects are investigated for a class of coarse grained models of protein machines consisting of a set of beads interacting through pair-wise additive potentials. Hydrodynamic effects are incorporated through a configuration-dependent mobility tensor, and expressions for the propulsion linear and angular velocities, as well as the stall force, are obtained. In the limit where conformational changes are small so that linear response theory is applicable, it is shown that propulsion is exponentially small; thus, propulsion is nonlinear phenomenon. The results are illustrated by computations on a simple model molecular machine.

  7. Observing invisible machines with invisible light: The mechanics of molecular machines

    NARCIS (Netherlands)

    Panman, M.R.

    2013-01-01

    Over the past few decades, chemists have designed and constructed a large variety of artificial molecular machines. Understanding of the fundamental principles behind motion at the molecular scale is key to the development of such devices. Motion at the molecular level is very different from that

  8. Controlling Motion at the Nanoscale: Rise of the Molecular Machines.

    Science.gov (United States)

    Abendroth, John M; Bushuyev, Oleksandr S; Weiss, Paul S; Barrett, Christopher J

    2015-08-25

    As our understanding and control of intra- and intermolecular interactions evolve, ever more complex molecular systems are synthesized and assembled that are capable of performing work or completing sophisticated tasks at the molecular scale. Commonly referred to as molecular machines, these dynamic systems comprise an astonishingly diverse class of motifs and are designed to respond to a plethora of actuation stimuli. In this Review, we outline the conditions that distinguish simple switches and rotors from machines and draw from a variety of fields to highlight some of the most exciting recent examples of opportunities for driven molecular mechanics. Emphasis is placed on the need for controllable and hierarchical assembly of these molecular components to display measurable effects at the micro-, meso-, and macroscales. As in Nature, this strategy will lead to dramatic amplification of the work performed via the collective action of many machines organized in linear chains, on functionalized surfaces, or in three-dimensional assemblies.

  9. Making and Operating Molecular Machines: A Multidisciplinary Challenge.

    Science.gov (United States)

    Baroncini, Massimo; Casimiro, Lorenzo; de Vet, Christiaan; Groppi, Jessica; Silvi, Serena; Credi, Alberto

    2018-02-01

    Movement is one of the central attributes of life, and a key feature in many technological processes. While artificial motion is typically provided by macroscopic engines powered by internal combustion or electrical energy, movement in living organisms is produced by machines and motors of molecular size that typically exploit the energy of chemical fuels at ambient temperature to generate forces and ultimately execute functions. The progress in several areas of chemistry, together with an improved understanding of biomolecular machines, has led to the development of a large variety of wholly synthetic molecular machines. These systems have the potential to bring about radical innovations in several areas of technology and medicine. In this Minireview, we discuss, with the help of a few examples, the multidisciplinary aspects of research on artificial molecular machines and highlight its translational character.

  10. Molecular Science Computing: 2010 Greenbook

    Energy Technology Data Exchange (ETDEWEB)

    De Jong, Wibe A.; Cowley, David E.; Dunning, Thom H.; Vorpagel, Erich R.

    2010-04-02

    This 2010 Greenbook outlines the science drivers for performing integrated computational environmental molecular research at EMSL and defines the next-generation HPC capabilities that must be developed at the MSC to address this critical research. The EMSL MSC Science Panel used EMSL’s vision and science focus and white papers from current and potential future EMSL scientific user communities to define the scientific direction and resulting HPC resource requirements presented in this 2010 Greenbook.

  11. Advances Towards Synthetic Machines at the Molecular and Nanoscale Level

    Directory of Open Access Journals (Sweden)

    Kristina Konstas

    2010-06-01

    Full Text Available The fabrication of increasingly smaller machines to the nanometer scale can be achieved by either a “top-down” or “bottom-up” approach. While the former is reaching its limits of resolution, the latter is showing promise for the assembly of molecular components, in a comparable approach to natural systems, to produce functioning ensembles in a controlled and predetermined manner. In this review we focus on recent progress in molecular systems that act as molecular machine prototypes such as switches, motors, vehicles and logic operators.

  12. In vitro molecular machine learning algorithm via symmetric internal loops of DNA.

    Science.gov (United States)

    Lee, Ji-Hoon; Lee, Seung Hwan; Baek, Christina; Chun, Hyosun; Ryu, Je-Hwan; Kim, Jin-Woo; Deaton, Russell; Zhang, Byoung-Tak

    2017-08-01

    Programmable biomolecules, such as DNA strands, deoxyribozymes, and restriction enzymes, have been used to solve computational problems, construct large-scale logic circuits, and program simple molecular games. Although studies have shown the potential of molecular computing, the capability of computational learning with DNA molecules, i.e., molecular machine learning, has yet to be experimentally verified. Here, we present a novel molecular learning in vitro model in which symmetric internal loops of double-stranded DNA are exploited to measure the differences between training instances, thus enabling the molecules to learn from small errors. The model was evaluated on a data set of twenty dialogue sentences obtained from the television shows Friends and Prison Break. The wet DNA-computing experiments confirmed that the molecular learning machine was able to generalize the dialogue patterns of each show and successfully identify the show from which the sentences originated. The molecular machine learning model described here opens the way for solving machine learning problems in computer science and biology using in vitro molecular computing with the data encoded in DNA molecules. Copyright © 2017. Published by Elsevier B.V.

  13. Atomic and molecular sciences

    International Nuclear Information System (INIS)

    Lane, N.F.

    1989-01-01

    The theoretical atomic and molecular physics program at Rice University addresses basic questions about the collision dynamics of electrons, atoms, ions and molecules, emphasizing processes related to possible new energy technologies and other applications. The program focuses on inelastic collision processes that are important in understanding energy and ionization balance in disturbed gases and plasmas. Emphasis is placed on systems and processes where some experimental information is available or where theoretical results may be expected to stimulate new measurements. Examples of current projects include: excitation and charge-transfer processes; orientation and alignment of excited states following collisions; Rydberg atom collisions with atoms and molecules; Penning ionization and ion-pair formation in atom-atom collisions; electron-impact ionization in dense, high-temperature plasmas; electron-molecule collisions; and related topics

  14. Machine learning molecular dynamics for the simulation of infrared spectra.

    Science.gov (United States)

    Gastegger, Michael; Behler, Jörg; Marquetand, Philipp

    2017-10-01

    Machine learning has emerged as an invaluable tool in many research areas. In the present work, we harness this power to predict highly accurate molecular infrared spectra with unprecedented computational efficiency. To account for vibrational anharmonic and dynamical effects - typically neglected by conventional quantum chemistry approaches - we base our machine learning strategy on ab initio molecular dynamics simulations. While these simulations are usually extremely time consuming even for small molecules, we overcome these limitations by leveraging the power of a variety of machine learning techniques, not only accelerating simulations by several orders of magnitude, but also greatly extending the size of systems that can be treated. To this end, we develop a molecular dipole moment model based on environment dependent neural network charges and combine it with the neural network potential approach of Behler and Parrinello. Contrary to the prevalent big data philosophy, we are able to obtain very accurate machine learning models for the prediction of infrared spectra based on only a few hundreds of electronic structure reference points. This is made possible through the use of molecular forces during neural network potential training and the introduction of a fully automated sampling scheme. We demonstrate the power of our machine learning approach by applying it to model the infrared spectra of a methanol molecule, n -alkanes containing up to 200 atoms and the protonated alanine tripeptide, which at the same time represents the first application of machine learning techniques to simulate the dynamics of a peptide. In all of these case studies we find an excellent agreement between the infrared spectra predicted via machine learning models and the respective theoretical and experimental spectra.

  15. MoleculeNet: a benchmark for molecular machine learning.

    Science.gov (United States)

    Wu, Zhenqin; Ramsundar, Bharath; Feinberg, Evan N; Gomes, Joseph; Geniesse, Caleb; Pappu, Aneesh S; Leswing, Karl; Pande, Vijay

    2018-01-14

    Molecular machine learning has been maturing rapidly over the last few years. Improved methods and the presence of larger datasets have enabled machine learning algorithms to make increasingly accurate predictions about molecular properties. However, algorithmic progress has been limited due to the lack of a standard benchmark to compare the efficacy of proposed methods; most new algorithms are benchmarked on different datasets making it challenging to gauge the quality of proposed methods. This work introduces MoleculeNet, a large scale benchmark for molecular machine learning. MoleculeNet curates multiple public datasets, establishes metrics for evaluation, and offers high quality open-source implementations of multiple previously proposed molecular featurization and learning algorithms (released as part of the DeepChem open source library). MoleculeNet benchmarks demonstrate that learnable representations are powerful tools for molecular machine learning and broadly offer the best performance. However, this result comes with caveats. Learnable representations still struggle to deal with complex tasks under data scarcity and highly imbalanced classification. For quantum mechanical and biophysical datasets, the use of physics-aware featurizations can be more important than choice of particular learning algorithm.

  16. Light-driven molecular machine at ITIES

    DEFF Research Database (Denmark)

    Kornyshev, A.A.; Kuimova, M.; Kuznetsov, A.M.

    2007-01-01

    We suggest a principle of operation of a new molecular device that transforms the energy of light into repetitive mechanical motions. Such a device can also serve as a model system for the study of the effect of electric field on intramolecular electron transfer. We discuss the design of suitable...

  17. Computational Nanotechnology Molecular Electronics, Materials and Machines

    Science.gov (United States)

    Srivastava, Deepak; Biegel, Bryan A. (Technical Monitor)

    2002-01-01

    This presentation covers research being performed on computational nanotechnology, carbon nanotubes and fullerenes at the NASA Ames Research Center. Topics cover include: nanomechanics of nanomaterials, nanotubes and composite materials, molecular electronics with nanotube junctions, kinky chemistry, and nanotechnology for solid-state quantum computers using fullerenes.

  18. An artificial molecular machine that builds an asymmetric catalyst

    Science.gov (United States)

    De Bo, Guillaume; Gall, Malcolm A. Y.; Kuschel, Sonja; De Winter, Julien; Gerbaux, Pascal; Leigh, David A.

    2018-05-01

    Biomolecular machines perform types of complex molecular-level tasks that artificial molecular machines can aspire to. The ribosome, for example, translates information from the polymer track it traverses (messenger RNA) to the new polymer it constructs (a polypeptide)1. The sequence and number of codons read determines the sequence and number of building blocks incorporated into the biomachine-synthesized polymer. However, neither control of sequence2,3 nor the transfer of length information from one polymer to another (which to date has only been accomplished in man-made systems through template synthesis)4 is easily achieved in the synthesis of artificial macromolecules. Rotaxane-based molecular machines5-7 have been developed that successively add amino acids8-10 (including β-amino acids10) to a growing peptide chain by the action of a macrocycle moving along a mono-dispersed oligomeric track derivatized with amino-acid phenol esters. The threaded macrocycle picks up groups that block its path and links them through successive native chemical ligation reactions11 to form a peptide sequence corresponding to the order of the building blocks on the track. Here, we show that as an alternative to translating sequence information, a rotaxane molecular machine can transfer the narrow polydispersity of a leucine-ester-derivatized polystyrene chain synthesized by atom transfer radical polymerization12 to a molecular-machine-made homo-leucine oligomer. The resulting narrow-molecular-weight oligomer folds to an α-helical secondary structure13 that acts as an asymmetric catalyst for the Juliá-Colonna epoxidation14,15 of chalcones.

  19. From Chemical Topology to Molecular Machines (Nobel Lecture).

    Science.gov (United States)

    Sauvage, Jean-Pierre

    2017-09-04

    To a large extent, the field of "molecular machines" started after several groups were able to prepare, reasonably easily, interlocking ring compounds (named catenanes for compounds consisting of interlocking rings and rotaxanes for rings threaded by molecular filaments or axes). Important families of molecular machines not belonging to the interlocking world were also designed, prepared, and studied but, for most of them, their elaboration was more recent than that of catenanes or rotaxanes. Since the creation of interlocking ring molecules is so important in relation to the molecular machinery area, we will start with this aspect of our work. The second part will naturally be devoted to the dynamic properties of such systems and to the compounds for which motions can be directed in a controlled manner from the outside, that is, molecular machines. We will restrict our discussion to a very limited number of examples which we consider as particularly representative of the field. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. Machine learning and data science in soft materials engineering.

    Science.gov (United States)

    Ferguson, Andrew L

    2018-01-31

    In many branches of materials science it is now routine to generate data sets of such large size and dimensionality that conventional methods of analysis fail. Paradigms and tools from data science and machine learning can provide scalable approaches to identify and extract trends and patterns within voluminous data sets, perform guided traversals of high-dimensional phase spaces, and furnish data-driven strategies for inverse materials design. This topical review provides an accessible introduction to machine learning tools in the context of soft and biological materials by 'de-jargonizing' data science terminology, presenting a taxonomy of machine learning techniques, and surveying the mathematical underpinnings and software implementations of popular tools, including principal component analysis, independent component analysis, diffusion maps, support vector machines, and relative entropy. We present illustrative examples of machine learning applications in soft matter, including inverse design of self-assembling materials, nonlinear learning of protein folding landscapes, high-throughput antimicrobial peptide design, and data-driven materials design engines. We close with an outlook on the challenges and opportunities for the field.

  1. Machine learning and data science in soft materials engineering

    Science.gov (United States)

    Ferguson, Andrew L.

    2018-01-01

    In many branches of materials science it is now routine to generate data sets of such large size and dimensionality that conventional methods of analysis fail. Paradigms and tools from data science and machine learning can provide scalable approaches to identify and extract trends and patterns within voluminous data sets, perform guided traversals of high-dimensional phase spaces, and furnish data-driven strategies for inverse materials design. This topical review provides an accessible introduction to machine learning tools in the context of soft and biological materials by ‘de-jargonizing’ data science terminology, presenting a taxonomy of machine learning techniques, and surveying the mathematical underpinnings and software implementations of popular tools, including principal component analysis, independent component analysis, diffusion maps, support vector machines, and relative entropy. We present illustrative examples of machine learning applications in soft matter, including inverse design of self-assembling materials, nonlinear learning of protein folding landscapes, high-throughput antimicrobial peptide design, and data-driven materials design engines. We close with an outlook on the challenges and opportunities for the field.

  2. Machine learning of molecular properties: Locality and active learning

    Science.gov (United States)

    Gubaev, Konstantin; Podryabinkin, Evgeny V.; Shapeev, Alexander V.

    2018-06-01

    In recent years, the machine learning techniques have shown great potent1ial in various problems from a multitude of disciplines, including materials design and drug discovery. The high computational speed on the one hand and the accuracy comparable to that of density functional theory on another hand make machine learning algorithms efficient for high-throughput screening through chemical and configurational space. However, the machine learning algorithms available in the literature require large training datasets to reach the chemical accuracy and also show large errors for the so-called outliers—the out-of-sample molecules, not well-represented in the training set. In the present paper, we propose a new machine learning algorithm for predicting molecular properties that addresses these two issues: it is based on a local model of interatomic interactions providing high accuracy when trained on relatively small training sets and an active learning algorithm of optimally choosing the training set that significantly reduces the errors for the outliers. We compare our model to the other state-of-the-art algorithms from the literature on the widely used benchmark tests.

  3. Molecular machines operating on the nanoscale: from classical to quantum

    Directory of Open Access Journals (Sweden)

    Igor Goychuk

    2016-03-01

    Full Text Available The main physical features and operating principles of isothermal nanomachines in the microworld, common to both classical and quantum machines, are reviewed. Special attention is paid to the dual, constructive role of dissipation and thermal fluctuations, the fluctuation–dissipation theorem, heat losses and free energy transduction, thermodynamic efficiency, and thermodynamic efficiency at maximum power. Several basic models are considered and discussed to highlight generic physical features. This work examines some common fallacies that continue to plague the literature. In particular, the erroneous beliefs that one should minimize friction and lower the temperature for high performance of Brownian machines, and that the thermodynamic efficiency at maximum power cannot exceed one-half are discussed. The emerging topic of anomalous molecular motors operating subdiffusively but very efficiently in the viscoelastic environment of living cells is also discussed.

  4. Molecular science for drug development and biomedicine.

    Science.gov (United States)

    Zhong, Wei-Zhu; Zhou, Shu-Feng

    2014-11-04

    With the avalanche of biological sequences generated in the postgenomic age, molecular science is facing an unprecedented challenge, i.e., how to timely utilize the huge amount of data to benefit human beings. Stimulated by such a challenge, a rapid development has taken place in molecular science, particularly in the areas associated with drug development and biomedicine, both experimental and theoretical. The current thematic issue was launched with the focus on the topic of "Molecular Science for Drug Development and Biomedicine", in hopes to further stimulate more useful techniques and findings from various approaches of molecular science for drug development and biomedicine.[...].

  5. Evolution of cell cycle control: same molecular machines, different regulation

    DEFF Research Database (Denmark)

    de Lichtenberg, Ulrik; Jensen, Thomas Skøt; Brunak, Søren

    2007-01-01

    Decades of research has together with the availability of whole genomes made it clear that many of the core components involved in the cell cycle are conserved across eukaryotes, both functionally and structurally. These proteins are organized in complexes and modules that are activated or deacti......Decades of research has together with the availability of whole genomes made it clear that many of the core components involved in the cell cycle are conserved across eukaryotes, both functionally and structurally. These proteins are organized in complexes and modules that are activated...... for assembling the same molecular machines just in time for action....

  6. Molecular science solving global problems

    International Nuclear Information System (INIS)

    Dunning, T.H. Jr.; Stults, B.R.

    1995-01-01

    From the late 1940s to the late 1980s, the Department of Energy (DOE) had a critical role in the Cold War. Many sites were built to contribute to the nation's nuclear weapons effort. However, not enough attention was paid to how the waste generated at these facilities should be handled. As a result, a number of sites fouled the soil around them or dumped low-level radioactive waste into nearby rivers. A DOE laboratory is under construction with a charter to help. Called the Environmental Molecular Sciences Laboratory (EMSL), this national user facility will be located at DOE's Pacific Northwest Laboratory (PNL) in Richland, WA. This laboratory has been funded by DOE and Congress to play a major role as the nation confronts the enormous challenge of reducing environmental and human risks from hundreds of government and industrial waste sites in an economically viable manner. The original proposal for the EMSL took a number of twists and turns on its way to its present form, but one thing remained constant: the belief that safe, permanent, cost-effective solutions to many of the country's environmental problems could be achieved only by multidisciplinary teams working to understand and control molecular processes. The processes of most concern are those that govern the transport and transformation of contaminants, the treatment and storage of high-level mixed wastes, and the risks those contaminants ultimately pose to workers and the public

  7. Discovery machines accelerators for science, technology, health and innovation

    CERN Document Server

    Australian Academy of Sciences

    2016-01-01

    Discovery machines: Accelerators for science, technology, health and innovation explores the science of particle accelerators, the machines that supercharge our ability to discover the secrets of nature and have opened up new tools in medicine, energy, manufacturing, and the environment as well as in pure research. Particle accelerators are now an essential ingredient in discovery science because they offer new ways to analyse the world, such as by probing objects with high energy x-rays or colliding them beams of electrons. They also have a huge—but often unnoticed—impact on all our lives; medical imaging, cancer treatment, new materials and even the chips that power our phones and computers have all been transformed by accelerators of various types. Research accelerators also provide fundamental infrastructure that encourages better collaboration between international and domestic scientists, organisations and governments.

  8. Contemporary machine learning: techniques for practitioners in the physical sciences

    Science.gov (United States)

    Spears, Brian

    2017-10-01

    Machine learning is the science of using computers to find relationships in data without explicitly knowing or programming those relationships in advance. Often without realizing it, we employ machine learning every day as we use our phones or drive our cars. Over the last few years, machine learning has found increasingly broad application in the physical sciences. This most often involves building a model relationship between a dependent, measurable output and an associated set of controllable, but complicated, independent inputs. The methods are applicable both to experimental observations and to databases of simulated output from large, detailed numerical simulations. In this tutorial, we will present an overview of current tools and techniques in machine learning - a jumping-off point for researchers interested in using machine learning to advance their work. We will discuss supervised learning techniques for modeling complicated functions, beginning with familiar regression schemes, then advancing to more sophisticated decision trees, modern neural networks, and deep learning methods. Next, we will cover unsupervised learning and techniques for reducing the dimensionality of input spaces and for clustering data. We'll show example applications from both magnetic and inertial confinement fusion. Along the way, we will describe methods for practitioners to help ensure that their models generalize from their training data to as-yet-unseen test data. We will finally point out some limitations to modern machine learning and speculate on some ways that practitioners from the physical sciences may be particularly suited to help. This work was performed by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

  9. Molecularization in nutritional science: a view from philosophy of science.

    Science.gov (United States)

    Ströhle, Alexander; Döring, Frank

    2010-10-01

    Over the past decade, a trend toward molecularization, which could be observed in almost all bioscientific disciplines, now appears to have also developed in nutritional science. However, molecular nutrition research gives birth to a series of questions. Therefore, we take a look at the epistemological foundation of (molecular) nutritional science. We (i) analyze the scientific status of (molecular) nutritional science and its position in the canon of other scientific disciplines, (ii) focus on the cognitive aims of nutritional science in general and (iii) on the chances and limits of molecular nutrition research in particular. By taking up the thoughts of an earlier work, we are analyzing (molecular) nutritional science from a strictly realist and emergentist-naturalist perspective. Methodologically, molecular nutrition research is bound to a microreductive research approach. We emphasize, however, that it need not be a radical microreductionism whose scientific reputation is not the best. Instead we favor moderate microreductionism, which combines reduction with integration. As mechanismic explanations are one of the primary aims of factual sciences, we consider it as the task of molecular nutrition research to find profound, i.e. molecular-mechanismic, explanations for the conditions, characteristics and changes of organisms related to the organism-nutrition environment interaction.

  10. Machine learning of accurate energy-conserving molecular force fields

    Science.gov (United States)

    Chmiela, Stefan; Tkatchenko, Alexandre; Sauceda, Huziel E.; Poltavsky, Igor; Schütt, Kristof T.; Müller, Klaus-Robert

    2017-01-01

    Using conservation of energy—a fundamental property of closed classical and quantum mechanical systems—we develop an efficient gradient-domain machine learning (GDML) approach to construct accurate molecular force fields using a restricted number of samples from ab initio molecular dynamics (AIMD) trajectories. The GDML implementation is able to reproduce global potential energy surfaces of intermediate-sized molecules with an accuracy of 0.3 kcal mol−1 for energies and 1 kcal mol−1 Å̊−1 for atomic forces using only 1000 conformational geometries for training. We demonstrate this accuracy for AIMD trajectories of molecules, including benzene, toluene, naphthalene, ethanol, uracil, and aspirin. The challenge of constructing conservative force fields is accomplished in our work by learning in a Hilbert space of vector-valued functions that obey the law of energy conservation. The GDML approach enables quantitative molecular dynamics simulations for molecules at a fraction of cost of explicit AIMD calculations, thereby allowing the construction of efficient force fields with the accuracy and transferability of high-level ab initio methods. PMID:28508076

  11. Machine learning of molecular electronic properties in chemical compound space

    Science.gov (United States)

    Montavon, Grégoire; Rupp, Matthias; Gobre, Vivekanand; Vazquez-Mayagoitia, Alvaro; Hansen, Katja; Tkatchenko, Alexandre; Müller, Klaus-Robert; Anatole von Lilienfeld, O.

    2013-09-01

    The combination of modern scientific computing with electronic structure theory can lead to an unprecedented amount of data amenable to intelligent data analysis for the identification of meaningful, novel and predictive structure-property relationships. Such relationships enable high-throughput screening for relevant properties in an exponentially growing pool of virtual compounds that are synthetically accessible. Here, we present a machine learning model, trained on a database of ab initio calculation results for thousands of organic molecules, that simultaneously predicts multiple electronic ground- and excited-state properties. The properties include atomization energy, polarizability, frontier orbital eigenvalues, ionization potential, electron affinity and excitation energies. The machine learning model is based on a deep multi-task artificial neural network, exploiting the underlying correlations between various molecular properties. The input is identical to ab initio methods, i.e. nuclear charges and Cartesian coordinates of all atoms. For small organic molecules, the accuracy of such a ‘quantum machine’ is similar, and sometimes superior, to modern quantum-chemical methods—at negligible computational cost.

  12. Machine learning of molecular electronic properties in chemical compound space

    International Nuclear Information System (INIS)

    Montavon, Grégoire; Müller, Klaus-Robert; Rupp, Matthias; Gobre, Vivekanand; Hansen, Katja; Tkatchenko, Alexandre; Vazquez-Mayagoitia, Alvaro; Anatole von Lilienfeld, O

    2013-01-01

    The combination of modern scientific computing with electronic structure theory can lead to an unprecedented amount of data amenable to intelligent data analysis for the identification of meaningful, novel and predictive structure–property relationships. Such relationships enable high-throughput screening for relevant properties in an exponentially growing pool of virtual compounds that are synthetically accessible. Here, we present a machine learning model, trained on a database of ab initio calculation results for thousands of organic molecules, that simultaneously predicts multiple electronic ground- and excited-state properties. The properties include atomization energy, polarizability, frontier orbital eigenvalues, ionization potential, electron affinity and excitation energies. The machine learning model is based on a deep multi-task artificial neural network, exploiting the underlying correlations between various molecular properties. The input is identical to ab initio methods, i.e. nuclear charges and Cartesian coordinates of all atoms. For small organic molecules, the accuracy of such a ‘quantum machine’ is similar, and sometimes superior, to modern quantum-chemical methods—at negligible computational cost. (paper)

  13. Knowledge machines digital transformations of the sciences and humanities

    CERN Document Server

    Meyer, Eric T

    2015-01-01

    In Knowledge Machines, Eric Meyer and Ralph Schroeder argue that digital technologies have fundamentally changed research practices in the sciences, social sciences, and humanities. Meyer and Schroeder show that digital tools and data, used collectively and in distributed mode -- which they term e-research -- have transformed not just the consumption of knowledge but also the production of knowledge. Digital technologies for research are reshaping how knowledge advances in disciplines that range from physics to literary analysis. Meyer and Schroeder map the rise of digital research and offer case studies from many fields, including biomedicine, social science uses of the Web, astronomy, and large-scale textual analysis in the humanities. They consider such topics as the challenges of sharing research data and of big data approaches, disciplinary differences and new forms of interdisciplinary collaboration, the shifting boundaries between researchers and their publics, and the ways that digital tools promote o...

  14. Solid surface vs. liquid surface: nanoarchitectonics, molecular machines, and DNA origami.

    Science.gov (United States)

    Ariga, Katsuhiko; Mori, Taizo; Nakanishi, Waka; Hill, Jonathan P

    2017-09-13

    The investigation of molecules and materials at interfaces is critical for the accumulation of new scientific insights and technological advances in the chemical and physical sciences. Immobilization on solid surfaces permits the investigation of different properties of functional molecules or materials with high sensitivity and high spatial resolution. Liquid surfaces also present important media for physicochemical innovation and insight based on their great flexibility and dynamicity, rapid diffusion of molecular components for mixing and rearrangements, as well as drastic spatial variation in the prevailing dielectric environment. Therefore, a comparative discussion of the relative merits of the properties of materials when positioned at solid or liquid surfaces would be informative regarding present-to-future developments of surface-based technologies. In this perspective article, recent research examples of nanoarchitectonics, molecular machines, DNA nanotechnology, and DNA origami are compared with respect to the type of surface used, i.e. solid surfaces vs. liquid surfaces, for future perspectives of interfacial physics and chemistry.

  15. New approaches in mathematical biology: Information theory and molecular machines

    International Nuclear Information System (INIS)

    Schneider, T.

    1995-01-01

    My research uses classical information theory to study genetic systems. Information theory was founded by Claude Shannon in the 1940's and has had an enormous impact on communications engineering and computer sciences. Shannon found a way to measure information. This measure can be used to precisely characterize the sequence conservation at nucleic-acid binding sites. The resulting methods, by completely replacing the use of ''consensus sequences'', provide better models for molecular biologists. An excess of conservation led us to do experimental work on bacteriophage T7 promoters and the F plasmid IncD repeats. The wonderful fidelity of telephone communications and compact disk (CD) music can be traced directly to Shannon's channel capacity theorem. When rederived for molecular biology, this theorem explains the surprising precision of many molecular events. Through connections with the Second Law of Thermodyanmics and Maxwell's Demon, this approach also has implications for the development of technology at the molecular level. Discussions of these topics are held on the internet news group bionet.info-theo. (author). (Abstract only)

  16. 2016 IFToMM Asian Conference on Mechanism and Machine Science (IFToMM Asian MMS 2016) & 2016 International Conference on Mechanism and Machine Science (CCMMS 2016)

    CERN Document Server

    Wang, Nianfeng; Huang, Yanjiang

    2017-01-01

    These proceedings collect the latest research results in mechanism and machine science, intended to reinforce and improve the role of mechanical systems in a variety of applications in daily life and industry. Gathering more than 120 academic papers, it addresses topics including: Computational kinematics, Machine elements, Actuators, Gearing and transmissions, Linkages and cams, Mechanism design, Dynamics of machinery, Tribology, Vehicle mechanisms, dynamics and design, Reliability, Experimental methods in mechanisms, Robotics and mechatronics, Biomechanics, Micro/nano mechanisms and machines, Medical/welfare devices, Nature and machines, Design methodology, Reconfigurable mechanisms and reconfigurable manipulators, and Origami mechanisms. This is the fourth installment in the IFToMM Asian conference series on Mechanism and Machine Science (ASIAN MMS 2016). The ASIAN MMS conference initiative was launched to provide a forum mainly for the Asian community working in Mechanism and Machine Science, in order to ...

  17. "Hypothetical machines": the science fiction dreams of Cold War social science.

    Science.gov (United States)

    Lemov, Rebecca

    2010-06-01

    The introspectometer was a "hypothetical machine" Robert K. Merton introduced in the course of a 1956 how-to manual describing an actual research technique, the focused interview. This technique, in turn, formed the basis of wartime morale research and consumer behavior studies as well as perhaps the most ubiquitous social science tool, the focus group. This essay explores a new perspective on Cold War social science made possible by comparing two kinds of apparatuses: one real, the other imaginary. Even as Merton explored the nightmare potential of such machines, he suggested that the clear aim of social science was to build them or their functional equivalent: recording machines to access a person's experiential stream of reality, with the ability to turn this stream into real-time data. In this way, the introspectometer marks and symbolizes a broader entry during the Cold War of science-fiction-style aspirations into methodological prescriptions and procedural manuals. This essay considers the growth of the genre of methodological visions and revisions, painstakingly argued and absorbed, but punctuated by sci-fi aims to transform "the human" and build newly penetrating machines. It also considers the place of the nearly real-, and the artificial "near-substitute" as part of an experimental urge that animated these sciences.

  18. Zooniverse - Web scale citizen science with people and machines. (Invited)

    Science.gov (United States)

    Smith, A.; Lynn, S.; Lintott, C.; Simpson, R.

    2013-12-01

    The Zooniverse (zooniverse.org) began in 2007 with the launch of Galaxy Zoo, a project in which more than 175,000 people provided shape analyses of more than 1 million galaxy images sourced from the Sloan Digital Sky Survey. These galaxy 'classifications', some 60 million in total, have since been used to produce more than 50 peer-reviewed publications based not only on the original research goals of the project but also because of serendipitous discoveries made by the volunteer community. Based upon the success of Galaxy Zoo the team have gone on to develop more than 25 web-based citizen science projects, all with a strong research focus in a range of subjects from astronomy to zoology where human-based analysis still exceeds that of machine intelligence. Over the past 6 years Zooniverse projects have collected more than 300 million data analyses from over 1 million volunteers providing fantastically rich datasets for not only the individuals working to produce research from their project but also the machine learning and computer vision research communities. The Zooniverse platform has always been developed to be the 'simplest thing that works' implementing only the most rudimentary algorithms for functionality such as task allocation and user-performance metrics - simplifications necessary to scale the Zooniverse such that the core team of developers and data scientists can remain small and the cost of running the computing infrastructure relatively modest. To date these simplifications have been appropriate for the data volumes and analysis tasks being addressed. This situation however is changing: next generation telescopes such as the Large Synoptic Sky Telescope (LSST) will produce data volumes dwarfing those previously analyzed. If citizen science is to have a part to play in analyzing these next-generation datasets then the Zooniverse will need to evolve into a smarter system capable for example of modeling the abilities of users and the complexities of

  19. Why Machine-Information Metaphors Are Bad for Science and Science Education

    Science.gov (United States)

    Pigliucci, Massimo; Boudry, Maarten

    2011-01-01

    Genes are often described by biologists using metaphors derived from computational science: they are thought of as carriers of information, as being the equivalent of "blueprints" for the construction of organisms. Likewise, cells are often characterized as "factories" and organisms themselves become analogous to machines. Accordingly, when the…

  20. Molecular Science Research Center 1992 annual report

    Energy Technology Data Exchange (ETDEWEB)

    Knotek, M.L.

    1994-01-01

    The Molecular Science Research Center is a designated national user facility, available to scientists from universities, industry, and other national laboratories. After an opening section, which includes conferences hosted, appointments, and projects, this document presents progress in the following fields: chemical structure and dynamics; environmental dynamics and simulation; macromolecular structure and dynamics; materials and interfaces; theory, modeling, and simulation; and computing and information sciences. Appendices are included: MSRC staff and associates, 1992 publications and presentations, activities, and acronyms and abbreviations.

  1. Molecular-Sized DNA or RNA Sequencing Machine | NCI Technology Transfer Center | TTC

    Science.gov (United States)

    The National Cancer Institute's Gene Regulation and Chromosome Biology Laboratory is seeking statements of capability or interest from parties interested in collaborative research to co-develop a molecular-sized DNA or RNA sequencing machine.

  2. Molecular Imprinting Applications in Forensic Science.

    Science.gov (United States)

    Yılmaz, Erkut; Garipcan, Bora; Patra, Hirak K; Uzun, Lokman

    2017-03-28

    Producing molecular imprinting-based materials has received increasing attention due to recognition selectivity, stability, cast effectiveness, and ease of production in various forms for a wide range of applications. The molecular imprinting technique has a variety of applications in the areas of the food industry, environmental monitoring, and medicine for diverse purposes like sample pretreatment, sensing, and separation/purification. A versatile usage, stability and recognition capabilities also make them perfect candidates for use in forensic sciences. Forensic science is a demanding area and there is a growing interest in molecularly imprinted polymers (MIPs) in this field. In this review, recent molecular imprinting applications in the related areas of forensic sciences are discussed while considering the literature of last two decades. Not only direct forensic applications but also studies of possible forensic value were taken into account like illicit drugs, banned sport drugs, effective toxins and chemical warfare agents in a review of over 100 articles. The literature was classified according to targets, material shapes, production strategies, detection method, and instrumentation. We aimed to summarize the current applications of MIPs in forensic science and put forth a projection of their potential uses as promising alternatives for benchmark competitors.

  3. Atomic and molecular science: progress and opportunities

    International Nuclear Information System (INIS)

    Mathur, D.

    2000-01-01

    In the contemporary scenario, atomic, molecular and optical (AMO) science focuses on the physical and chemical properties of the common building blocks of matter - atoms, molecules and light. The main characteristic of AMO science is that it is both an intellectually stimulating fundamental science and a powerful enabling science that supports an increasing number of other important areas of science and technology. In brief, the fundamental interests in atoms, molecules and clusters (as well as their ions) include studies of their structure and properties, their optical interactions, collisional properties, including quantum state-resolved studies, and interactions with external fields, solids and surfaces. Fundamental aspects of present-day optical sciences include studies of laser spectroscopy, nonlinear optics, quantum optics, optical interactions with condensed matter, ultrafast optics and coherent light sources. The enabling aspect of AMO science derives from efforts to control atoms, molecules, clusters, charged particles and light more precisely, to accurately to determine, experimentally and theoretically, their properties, and to invent new, methods of generating light with tailor-made properties

  4. Molecular Science Research Center, 1991 annual report

    Energy Technology Data Exchange (ETDEWEB)

    Knotek, M.L.

    1992-03-01

    During 1991, the Molecular Science Research Center (MSRC) experienced solid growth and accomplishment and the Environmental, and Molecular Sciences Laboratory (EMSL) construction project moved forward. We began with strong programs in chemical structure and dynamics and theory, modeling, and simulation, and both these programs continued to thrive. We also made significant advances in the development of programs in materials and interfaces and macromolecular structure and dynamics, largely as a result of the key staff recruited to lead these efforts. If there was one pervasive activity for the past year, however, it was to strengthen the role of the EMSL in the overall environmental restoration and waste management (ER/WM) mission at Hanford. These extended activities involved not only MSRC and EMSL staff but all PNL scientific and technical staff engaged in ER/WM programs.

  5. Machine learning for the structure-energy-property landscapes of molecular crystals.

    Science.gov (United States)

    Musil, Félix; De, Sandip; Yang, Jack; Campbell, Joshua E; Day, Graeme M; Ceriotti, Michele

    2018-02-07

    Molecular crystals play an important role in several fields of science and technology. They frequently crystallize in different polymorphs with substantially different physical properties. To help guide the synthesis of candidate materials, atomic-scale modelling can be used to enumerate the stable polymorphs and to predict their properties, as well as to propose heuristic rules to rationalize the correlations between crystal structure and materials properties. Here we show how a recently-developed machine-learning (ML) framework can be used to achieve inexpensive and accurate predictions of the stability and properties of polymorphs, and a data-driven classification that is less biased and more flexible than typical heuristic rules. We discuss, as examples, the lattice energy and property landscapes of pentacene and two azapentacene isomers that are of interest as organic semiconductor materials. We show that we can estimate force field or DFT lattice energies with sub-kJ mol -1 accuracy, using only a few hundred reference configurations, and reduce by a factor of ten the computational effort needed to predict charge mobility in the crystal structures. The automatic structural classification of the polymorphs reveals a more detailed picture of molecular packing than that provided by conventional heuristics, and helps disentangle the role of hydrogen bonded and π-stacking interactions in determining molecular self-assembly. This observation demonstrates that ML is not just a black-box scheme to interpolate between reference calculations, but can also be used as a tool to gain intuitive insights into structure-property relations in molecular crystal engineering.

  6. International Journal of Molecular Science 2017 Best Paper Award.

    Science.gov (United States)

    2017-11-02

    The Editors of the International Journal of Molecular Sciences have established the Best Paper Award to recognize the most outstanding articles published in the areas of molecular biology, molecular physics and chemistry that have been published in the International Journal of Molecular Sciences. The prizes have been awarded annually since 2012 [...].

  7. Molecular environmental science and synchrotron radiation sources

    Energy Technology Data Exchange (ETDEWEB)

    Brown, G.E. Jr. [Stanford Univ., CA (United States)

    1995-12-31

    Molecular environmental science is a relatively new field but focuses on the chemical and physical forms of toxic and/or radioactive contaminants in soils, sediments, man-made waste forms, natural waters, and the atmosphere; their possible reactions with inorganic and organic compounds, plants, and organisms in the environment; and the molecular-level factors that control their toxicity, bioavailability, and transport. The chemical speciation of a contaminant is a major factor in determining its behavior in the environment, and synchrotron-based X-ray absorption fine structure (XAFS) spectroscopy is one of the spectroscopies of choice to quantitatively determine speciation of heavy metal contaminants in situ without selective extraction or other sample treatment. The use of high-flux insertion device beam lines at synchrotron sources and multi-element array detectors has permitted XAFS studies of metals such as Se and As in natural soils at concentration levels as low as 50 ppm. The X-ray absorption near edge structure of these metals is particularly useful in determining their oxidation state. Examples of such studies will be presented, and new insertion device beam lines under development at SSRL and the Advanced Photon Source for molecular environmental science applications will be discussed.

  8. Environmental Molecular Sciences Laboratory 2004 Annual Report

    Energy Technology Data Exchange (ETDEWEB)

    White, Julia C.

    2005-04-17

    This 2004 Annual Report describes the research and accomplishments of staff and users of the W.R. Wiley Environmental Molecular Sciences Laboratory (EMSL), located in Richland, Washington. EMSL is a multidisciplinary, national scientific user facility and research organization, operated by Pacific Northwest National Laboratory (PNNL) for the U.S. Department of Energy's Office of Biological and Environmental Research. The resources and opportunities within the facility are an outgrowth of the U.S. Department of Energy's (DOE) commitment to fundamental research for understanding and resolving environmental and other critical scientific issues.

  9. Computational Nanotechnology of Molecular Materials, Electronics and Machines

    Science.gov (United States)

    Srivastava, D.; Biegel, Bryan A. (Technical Monitor)

    2002-01-01

    This viewgraph presentation covers carbon nanotubes, their characteristics, and their potential future applications. The presentation include predictions on the development of nanostructures and their applications, the thermal characteristics of carbon nanotubes, mechano-chemical effects upon carbon nanotubes, molecular electronics, and models for possible future nanostructure devices. The presentation also proposes a neural model for signal processing.

  10. Corporate Disruption in the Science of Machine Learning

    OpenAIRE

    Work, Sam

    2016-01-01

    This MSc dissertation considers the effects of the current corporate interest on researchers in the field of machine learning. Situated within the field's cyclical history of academic, public and corporate interest, this dissertation investigates how current researchers view recent developments and negotiate their own research practices within an environment of increased commercial interest and funding. The original research consists of in-depth interviews with 12 machine learning researchers...

  11. Brains--Computers--Machines: Neural Engineering in Science Classrooms

    Science.gov (United States)

    Chudler, Eric H.; Bergsman, Kristen Clapper

    2016-01-01

    Neural engineering is an emerging field of high relevance to students, teachers, and the general public. This feature presents online resources that educators and scientists can use to introduce students to neural engineering and to integrate core ideas from the life sciences, physical sciences, social sciences, computer science, and engineering…

  12. Synthetic Molecular Machines for Active Self-Assembly: Prototype Algorithms, Designs, and Experimental Study

    Science.gov (United States)

    Dabby, Nadine L.

    Computer science and electrical engineering have been the great success story of the twentieth century. The neat modularity and mapping of a language onto circuits has led to robots on Mars, desktop computers and smartphones. But these devices are not yet able to do some of the things that life takes for granted: repair a scratch, reproduce, regenerate, or grow exponentially fast--all while remaining functional. This thesis explores and develops algorithms, molecular implementations, and theoretical proofs in the context of "active self-assembly" of molecular systems. The long-term vision of active self-assembly is the theoretical and physical implementation of materials that are composed of reconfigurable units with the programmability and adaptability of biology's numerous molecular machines. En route to this goal, we must first find a way to overcome the memory limitations of molecular systems, and to discover the limits of complexity that can be achieved with individual molecules. One of the main thrusts in molecular programming is to use computer science as a tool for figuring out what can be achieved. While molecular systems that are Turing-complete have been demonstrated [Winfree, 1996], these systems still cannot achieve some of the feats biology has achieved. One might think that because a system is Turing-complete, capable of computing "anything," that it can do any arbitrary task. But while it can simulate any digital computational problem, there are many behaviors that are not "computations" in a classical sense, and cannot be directly implemented. Examples include exponential growth and molecular motion relative to a surface. Passive self-assembly systems cannot implement these behaviors because (a) molecular motion relative to a surface requires a source of fuel that is external to the system, and (b) passive systems are too slow to assemble exponentially-fast-growing structures. We call these behaviors "energetically incomplete" programmable

  13. Molecular beam studies with a time-of-flight machine

    International Nuclear Information System (INIS)

    Beijerinck, H.C.W.

    1975-01-01

    The study concerns the development of the time-of-flight method for the velocity analysis of molecular beams and its application to the measurement of the velocity dependence of the total cross-section of the noble gases. It reviews the elastic scattering theory, both in the framework of classical mechanics and in the quantum mechanical description. Attention is paid to the semiclassical correspondence of classical particle trajectories with the partial waves of the quantum mechanical solution. The total cross-section and the small angle differential cross-section are discussed with special emphasis on their relation. The results of this chapter are used later to derive the correction on the measured total cross-section due to the finite angular resolution of the apparatus. Reviewed also is the available information on the intermolecular potential of the Ar-Ar system. Then a discussion of the measurement of total cross-sections with the molecular beam method and the time-of-flight method is compared to other methods used. It is shown that the single burst time-of-flight method can be developed into a reliable and well-calibrated method for the analysis of the velocity distribution of molecular beams. A comparison of the single burst time-of-flight method with the cross-correlation time-of-flight method shows that the two methods are complementary and that the specific experimental circumstances determine which method is to be preferred. Molecular beam sources are discussed. The peaking factor formalism is introduced and helps to compare the performance of different types of sources. The effusive and the supersonic source are treated and recent experimental results are given. The multichannel source is treated in more detail. For the opaque mode, an experimental investigation of the velocity distribution and the angular distribution of the flow pattern is presented. Comparison of these results with Monte Carlo calculations for free molecular flow in a cylindrical

  14. A comparison of machine learning and Bayesian modelling for molecular serotyping.

    Science.gov (United States)

    Newton, Richard; Wernisch, Lorenz

    2017-08-11

    Streptococcus pneumoniae is a human pathogen that is a major cause of infant mortality. Identifying the pneumococcal serotype is an important step in monitoring the impact of vaccines used to protect against disease. Genomic microarrays provide an effective method for molecular serotyping. Previously we developed an empirical Bayesian model for the classification of serotypes from a molecular serotyping array. With only few samples available, a model driven approach was the only option. In the meanwhile, several thousand samples have been made available to us, providing an opportunity to investigate serotype classification by machine learning methods, which could complement the Bayesian model. We compare the performance of the original Bayesian model with two machine learning algorithms: Gradient Boosting Machines and Random Forests. We present our results as an example of a generic strategy whereby a preliminary probabilistic model is complemented or replaced by a machine learning classifier once enough data are available. Despite the availability of thousands of serotyping arrays, a problem encountered when applying machine learning methods is the lack of training data containing mixtures of serotypes; due to the large number of possible combinations. Most of the available training data comprises samples with only a single serotype. To overcome the lack of training data we implemented an iterative analysis, creating artificial training data of serotype mixtures by combining raw data from single serotype arrays. With the enhanced training set the machine learning algorithms out perform the original Bayesian model. However, for serotypes currently lacking sufficient training data the best performing implementation was a combination of the results of the Bayesian Model and the Gradient Boosting Machine. As well as being an effective method for classifying biological data, machine learning can also be used as an efficient method for revealing subtle biological

  15. DNA topology influences molecular machine lifetime in human serum

    Science.gov (United States)

    Goltry, Sara; Hallstrom, Natalya; Clark, Tyler; Kuang, Wan; Lee, Jeunghoon; Jorcyk, Cheryl; Knowlton, William B.; Yurke, Bernard; Hughes, William L.; Graugnard, Elton

    2015-06-01

    DNA nanotechnology holds the potential for enabling new tools for biomedical engineering, including diagnosis, prognosis, and therapeutics. However, applications for DNA devices are thought to be limited by rapid enzymatic degradation in serum and blood. Here, we demonstrate that a key aspect of DNA nanotechnology--programmable molecular shape--plays a substantial role in device lifetimes. These results establish the ability to operate synthetic DNA devices in the presence of endogenous enzymes and challenge the textbook view of near instantaneous degradation.DNA nanotechnology holds the potential for enabling new tools for biomedical engineering, including diagnosis, prognosis, and therapeutics. However, applications for DNA devices are thought to be limited by rapid enzymatic degradation in serum and blood. Here, we demonstrate that a key aspect of DNA nanotechnology--programmable molecular shape--plays a substantial role in device lifetimes. These results establish the ability to operate synthetic DNA devices in the presence of endogenous enzymes and challenge the textbook view of near instantaneous degradation. Electronic supplementary information (ESI) available: DNA sequences, fluorophore and quencher properties, equipment design, and degradation studies. See DOI: 10.1039/c5nr02283e

  16. Marine molecular biology: An emerging field of biological sciences

    Digital Repository Service at National Institute of Oceanography (India)

    Thakur, N.L.; Jain, R.; Natalio, F.; Hamer, B.; Thakur, A.N.; Muller, W.E.G.

    An appreciation of the potential applications of molecular biology is of growing importance in many areas of life sciences, including marine biology. During the past two decades, the development of sophisticated molecular technologies...

  17. Kernel Methods for Machine Learning with Life Science Applications

    DEFF Research Database (Denmark)

    Abrahamsen, Trine Julie

    Kernel methods refer to a family of widely used nonlinear algorithms for machine learning tasks like classification, regression, and feature extraction. By exploiting the so-called kernel trick straightforward extensions of classical linear algorithms are enabled as long as the data only appear a...

  18. Molecular thermodynamics for food science and engineering.

    Science.gov (United States)

    Nguyen, Phuong-Mai; Guiga, Wafa; Vitrac, Olivier

    2016-10-01

    We argue that thanks to molecular modeling approaches, many thermodynamic properties required in Food Science and Food Engineering will be calculable within a few hours from first principles in a near future. These new possibilities will enable to bridge via multiscale modeling composition, process and storage effects to reach global optimization, innovative concepts for food or its packaging. An outlook of techniques and a series of examples are given in this perspective. We emphasize solute chemical potentials in polymers, liquids and their mixtures as they cannot be understood and estimated without theory. The presented atomistic and coarse-grained methods offer a natural framework to their conceptualization in polynary systems, entangled or crosslinked homo- or heteropolymers. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. Internal force corrections with machine learning for quantum mechanics/molecular mechanics simulations.

    Science.gov (United States)

    Wu, Jingheng; Shen, Lin; Yang, Weitao

    2017-10-28

    Ab initio quantum mechanics/molecular mechanics (QM/MM) molecular dynamics simulation is a useful tool to calculate thermodynamic properties such as potential of mean force for chemical reactions but intensely time consuming. In this paper, we developed a new method using the internal force correction for low-level semiempirical QM/MM molecular dynamics samplings with a predefined reaction coordinate. As a correction term, the internal force was predicted with a machine learning scheme, which provides a sophisticated force field, and added to the atomic forces on the reaction coordinate related atoms at each integration step. We applied this method to two reactions in aqueous solution and reproduced potentials of mean force at the ab initio QM/MM level. The saving in computational cost is about 2 orders of magnitude. The present work reveals great potentials for machine learning in QM/MM simulations to study complex chemical processes.

  20. Structural and Conformational Chemistry from Electrochemical Molecular Machines. Replicating Biological Functions. A Review.

    Science.gov (United States)

    Otero, Toribio F

    2017-12-14

    Each constitutive chain of a conducting polymer electrode acts as a reversible multi-step electrochemical molecular motor: reversible reactions drive reversible conformational movements of the chain. The reaction-driven cooperative actuation of those molecular machines generates, or destroys, inside the film the free volume required to lodge/expel balancing counterions and solvent: reactions drive reversible film volume variations, which basic structural components are here identified and quantified from electrochemical responses. The content of the reactive dense gel (chemical molecular machines, ions and water) mimics that of the intracellular matrix in living functional cells. Reaction-driven properties (composition-dependent properties) and devices replicate biological functions and organs. An emerging technological world of soft, wet, reaction-driven, multifunctional and biomimetic devices and the concomitant zoomorphic or anthropomorphic robots is presented. © 2017 The Chemical Society of Japan & Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. Molecular Science Research Center annual report

    Energy Technology Data Exchange (ETDEWEB)

    Knotek, M.L.

    1991-01-01

    The Chemical Structure and Dynamics group is studying chemical kinetics and reactions dynamics of terrestrial and atmospheric processes as well as the chemistry of complex waste forms and waste storage media. Staff are using new laser systems and surface-mapping techniques in combination with molecular clusters that mimic adsorbate/surface interactions. The Macromolecular Structure and Dynamics group is determining biomolecular structure/function relationships for processes the control the biological transformation of contaminants and the health effects of toxic substances. The Materials and Interfaces program is generating information needed to design and synthesize advanced materials for the analysis and separation of mixed chemical waste, the long-term storage of concentrated hazardous materials, and the development of chemical sensors for environmental monitoring of various organic and inorganic species. The Theory, Modeling, and Simulation group is developing detailed molecular-level descriptions of the chemical, physical, and biological processes in natural and contaminated systems. Researchers are using the full spectrum of computational techniques. The Computer and Information Sciences group is developing new approaches to handle vast amounts of data and to perform calculations for complex natural systems. The EMSL will contain a high-performance computing facility, ancillary computing laboratories, and high-speed data acquisition systems for all major research instruments.

  2. Molecular forensic science of nuclear materials

    International Nuclear Information System (INIS)

    Wilkerson, Marianne Perry

    2010-01-01

    We are interested in applying our understanding of actinide chemical structure and bonding to broaden the suite of analytical tools available for nuclear forensic analyses. Uranium- and plutonium-oxide systems form under a variety of conditions, and these chemical species exhibit some of the most complex behavior of metal oxide systems known. No less intriguing is the ability of AnO 2 (An: U, Pu) to form non-stoichiometric species described as AnO 2+x . Environmental studies have shown the value of utilizing the chemical signatures of these actinide oxides materials to understand transport following release into the environment. Chemical speciation of actinide-oxide samples may also provide clues as to the age, source, process history, or transport of the material. The scientific challenge is to identify, measure and understand those aspects of speciation of actinide analytes that carry information about material origin and history most relevant to forensics. Here, we will describe our efforts in material synthesis and analytical methods development that we will use to provide the fundamental science required to characterize actinide oxide molecular structures for forensics science. Structural properties and initial results to measure structural variability of uranium oxide samples using synchrotron-based X-ray Absorption Fine Structure will be discussed.

  3. A Focus on Triazolium as a Multipurpose Molecular Station for pH-Sensitive Interlocked Crown-Ether-Based Molecular Machines.

    Science.gov (United States)

    Coutrot, Frédéric

    2015-10-01

    The control of motion of one element with respect to others in an interlocked architecture allows for different co-conformational states of a molecule. This can result in variations of physical or chemical properties. The increase of knowledge in the field of molecular interactions led to the design, the synthesis, and the study of various systems of molecular machinery in a wide range of interlocked architectures. In this field, the discovery of new molecular stations for macrocycles is an attractive way to conceive original molecular machines. In the very recent past, the triazolium moiety proved to interact with crown ethers in interlocked molecules, so that it could be used as an ideal molecular station. It also served as a molecular barrier in order to lock interlaced structures or to compartmentalize interlocked molecular machines. This review describes the recently reported examples of pH-sensitive triazolium-containing molecular machines and their peculiar features.

  4. Propulsion of a Molecular Machine by Asymmetric Distribution of Reaction Products

    Science.gov (United States)

    Golestanian, Ramin; Liverpool, Tanniemola B.; Ajdari, Armand

    2005-06-01

    A simple model for the reaction-driven propulsion of a small device is proposed as a model for (part of) a molecular machine in aqueous media. The motion of the device is driven by an asymmetric distribution of reaction products. The propulsive velocity of the device is calculated as well as the scale of the velocity fluctuations. The effects of hydrodynamic flow as well as a number of different scenarios for the kinetics of the reaction are addressed.

  5. A nanojet: propulsion of a molecular machine by an asymmetric distribution of reaction--products

    Science.gov (United States)

    Liverpool, Tanniemola; Golestanian, Ramin; Ajdari, Armand

    2006-03-01

    A simple model for the reaction-driven propulsion of a small device is proposed as a model for (part of) a molecular machine in aqueous media. Motion of the device is driven by an asymmetric distribution of reaction products. We calculate the propulsive velocity of the device as well as the scale of the velocity fluctuations. We also consider the effects of hydrodynamic flow as well as a number of different scenarios for the kinetics of the reaction.

  6. Big Machines and Big Science: 80 Years of Accelerators at Stanford

    Energy Technology Data Exchange (ETDEWEB)

    Loew, Gregory

    2008-12-16

    Longtime SLAC physicist Greg Loew will present a trip through SLAC's origins, highlighting its scientific achievements, and provide a glimpse of the lab's future in 'Big Machines and Big Science: 80 Years of Accelerators at Stanford.'

  7. Molecular machines in living cells. Seibutsu no bunshi kikai to sono system

    Energy Technology Data Exchange (ETDEWEB)

    Osawa, F. (Aichi Inst. of Tech., Nagoya (Japan))

    1992-12-20

    At first, flagellar motors of bacteria are reviewed as a typical example of molecular machines in living cells. A rotational motor is embedded in the cell membrane at the root of the flagellum. The driving power of the rotation is the flow of hydrogen ion from the inside to the outside of the cell. In a normal state of a bacterium, potential difference of about 0.2 V is produced by the ion pump existing in the cell membrane. A molecular motor of sliding motion of muscle attracts the attention on the relation of the input and output of the molecular motor. The mechanism of the smooth motion without fluctuation in the fluctuated environment and the fluctuated input is unknown. Next, the motion of Paramecium is discussed as an example of a system composed of a number of molecular machines. Paramecium moves to a place of a suitable temperature when placed in a water tank with temperature gradient, however, it does not stop the motion at the place of the suitable temperature and increases a probability to change the direction when leaving, that is it takes a method of indirect probabilistic control. 12 refs., 8 figs.

  8. High-pressure microscopy for tracking dynamic properties of molecular machines.

    Science.gov (United States)

    Nishiyama, Masayoshi

    2017-12-01

    High-pressure microscopy is one of the powerful techniques to visualize the effects of hydrostatic pressures on research targets. It could be used for monitoring the pressure-induced changes in the structure and function of molecular machines in vitro and in vivo. This review focuses on the dynamic properties of the assemblies and machines, analyzed by means of high-pressure microscopy measurement. We developed a high-pressure microscope that is optimized both for the best image formation and for the stability to hydrostatic pressure up to 150 MPa. Application of pressure could change polymerization and depolymerization processes of the microtubule cytoskeleton, suggesting a modulation of the intermolecular interaction between tubulin molecules. A novel motility assay demonstrated that high hydrostatic pressure induces counterclockwise (CCW) to clockwise (CW) reversals of the Escherichia coli flagellar motor. The present techniques could be extended to study how molecular machines in complicated systems respond to mechanical stimuli. Copyright © 2017 Elsevier B.V. All rights reserved.

  9. Motor proteins and molecular motors: how to operate machines at the nanoscale

    International Nuclear Information System (INIS)

    Kolomeisky, Anatoly B

    2013-01-01

    Several classes of biological molecules that transform chemical energy into mechanical work are known as motor proteins or molecular motors. These nanometer-sized machines operate in noisy stochastic isothermal environments, strongly supporting fundamental cellular processes such as the transfer of genetic information, transport, organization and functioning. In the past two decades motor proteins have become a subject of intense research efforts, aimed at uncovering the fundamental principles and mechanisms of molecular motor dynamics. In this review, we critically discuss recent progress in experimental and theoretical studies on motor proteins. Our focus is on analyzing fundamental concepts and ideas that have been utilized to explain the non-equilibrium nature and mechanisms of molecular motors. (topical review)

  10. On the Safety of Machine Learning: Cyber-Physical Systems, Decision Sciences, and Data Products.

    Science.gov (United States)

    Varshney, Kush R; Alemzadeh, Homa

    2017-09-01

    Machine learning algorithms increasingly influence our decisions and interact with us in all parts of our daily lives. Therefore, just as we consider the safety of power plants, highways, and a variety of other engineered socio-technical systems, we must also take into account the safety of systems involving machine learning. Heretofore, the definition of safety has not been formalized in a machine learning context. In this article, we do so by defining machine learning safety in terms of risk, epistemic uncertainty, and the harm incurred by unwanted outcomes. We then use this definition to examine safety in all sorts of applications in cyber-physical systems, decision sciences, and data products. We find that the foundational principle of modern statistical machine learning, empirical risk minimization, is not always a sufficient objective. We discuss how four different categories of strategies for achieving safety in engineering, including inherently safe design, safety reserves, safe fail, and procedural safeguards can be mapped to a machine learning context. We then discuss example techniques that can be adopted in each category, such as considering interpretability and causality of predictive models, objective functions beyond expected prediction accuracy, human involvement for labeling difficult or rare examples, and user experience design of software and open data.

  11. Environmental Molecular Sciences Laboratory Annual Report: Fiscal Year 2006

    Energy Technology Data Exchange (ETDEWEB)

    Foster, Nancy S.; Showalter, Mary Ann

    2007-03-23

    This report describes the activities and research performed at the Environmental Molecular Sciences Laboratory, a Department of Energy national scientific user facility at Pacific Northwest National Laboratory, during Fiscal Year 2006.

  12. Ghosts in the machine: publication planning in the medical sciences.

    Science.gov (United States)

    Sismondo, Sergio

    2009-04-01

    Publication of pharmaceutical company-sponsored research in medical journals, and its presentation at conferences and meetings, is mostly governed by 'publication plans' that extract the maximum amount of scientific and commercial value out of data and analyses through carefully constructed and placed papers. Clinical research is typically performed by contract research organizations, analyzed by company statisticians, written up by independent medical writers, approved and edited by academic researchers who then serve as authors, and the whole process organized and shepherded through to journal publication by publication planners. This paper reports on a conference of an international association of publication planners. It describes and analyzes their work in an ecological framework that relates it to marketing departments of pharmaceutical companies, medical journals and publishers, academic authors, and potential audiences. The medical research described here forms a new kind of corporate science, designed to look like traditional academic work, but performed largely to market products.

  13. Marine molecular biology: an emerging field of biological sciences.

    Science.gov (United States)

    Thakur, Narsinh L; Jain, Roopesh; Natalio, Filipe; Hamer, Bojan; Thakur, Archana N; Müller, Werner E G

    2008-01-01

    An appreciation of the potential applications of molecular biology is of growing importance in many areas of life sciences, including marine biology. During the past two decades, the development of sophisticated molecular technologies and instruments for biomedical research has resulted in significant advances in the biological sciences. However, the value of molecular techniques for addressing problems in marine biology has only recently begun to be cherished. It has been proven that the exploitation of molecular biological techniques will allow difficult research questions about marine organisms and ocean processes to be addressed. Marine molecular biology is a discipline, which strives to define and solve the problems regarding the sustainable exploration of marine life for human health and welfare, through the cooperation between scientists working in marine biology, molecular biology, microbiology and chemistry disciplines. Several success stories of the applications of molecular techniques in the field of marine biology are guiding further research in this area. In this review different molecular techniques are discussed, which have application in marine microbiology, marine invertebrate biology, marine ecology, marine natural products, material sciences, fisheries, conservation and bio-invasion etc. In summary, if marine biologists and molecular biologists continue to work towards strong partnership during the next decade and recognize intellectual and technological advantages and benefits of such partnership, an exciting new frontier of marine molecular biology will emerge in the future.

  14. Fundamental Approaches in Molecular Biology for Communication Sciences and Disorders

    Science.gov (United States)

    Bartlett, Rebecca S.; Jette, Marie E.; King, Suzanne N.; Schaser, Allison; Thibeault, Susan L.

    2012-01-01

    Purpose: This contemporary tutorial will introduce general principles of molecular biology, common deoxyribonucleic acid (DNA), ribonucleic acid (RNA), and protein assays and their relevance in the field of communication sciences and disorders. Method: Over the past 2 decades, knowledge of the molecular pathophysiology of human disease has…

  15. Simplify and Accelerate Earth Science Data Preparation to Systemize Machine Learning

    Science.gov (United States)

    Kuo, K. S.; Rilee, M. L.; Oloso, A.

    2017-12-01

    Data preparation is the most laborious and time-consuming part of machine learning. The effort required is usually more than linearly proportional to the varieties of data used. From a system science viewpoint, useful machine learning in Earth Science likely involves diverse datasets. Thus, simplifying data preparation to ease the systemization of machine learning in Earth Science is of immense value. The technologies we have developed and applied to an array database, SciDB, are explicitly designed for the purpose, including the innovative SpatioTemporal Adaptive-Resolution Encoding (STARE), a remapping tool suite, and an efficient implementation of connected component labeling (CCL). STARE serves as a universal Earth data representation that homogenizes data varieties and facilitates spatiotemporal data placement as well as alignment, to maximize query performance on massively parallel, distributed computing resources for a major class of analysis. Moreover, it converts spatiotemporal set operations into fast and efficient integer interval operations, supporting in turn moving-object analysis. Integrative analysis requires more than overlapping spatiotemporal sets. For example, meaningful comparison of temperature fields obtained with different means and resolutions requires their transformation to the same grid. Therefore, remapping has been implemented to enable integrative analysis. Finally, Earth Science investigations are generally studies of phenomena, e.g. tropical cyclone, atmospheric river, and blizzard, through their associated events, like hurricanes Katrina and Sandy. Unfortunately, except for a few high-impact phenomena, comprehensive episodic records are lacking. Consequently, we have implemented an efficient CCL tracking algorithm, enabling event-based investigations within climate data records beyond mere event presence. In summary, we have implemented the core unifying capabilities on a Big Data technology to enable systematic machine learning in

  16. Coupling Matched Molecular Pairs with Machine Learning for Virtual Compound Optimization.

    Science.gov (United States)

    Turk, Samo; Merget, Benjamin; Rippmann, Friedrich; Fulle, Simone

    2017-12-26

    Matched molecular pair (MMP) analyses are widely used in compound optimization projects to gain insights into structure-activity relationships (SAR). The analysis is traditionally done via statistical methods but can also be employed together with machine learning (ML) approaches to extrapolate to novel compounds. The here introduced MMP/ML method combines a fragment-based MMP implementation with different machine learning methods to obtain automated SAR decomposition and prediction. To test the prediction capabilities and model transferability, two different compound optimization scenarios were designed: (1) "new fragments" which occurs when exploring new fragments for a defined compound series and (2) "new static core and transformations" which resembles for instance the identification of a new compound series. Very good results were achieved by all employed machine learning methods especially for the new fragments case, but overall deep neural network models performed best, allowing reliable predictions also for the new static core and transformations scenario, where comprehensive SAR knowledge of the compound series is missing. Furthermore, we show that models trained on all available data have a higher generalizability compared to models trained on focused series and can extend beyond chemical space covered in the training data. Thus, coupling MMP with deep neural networks provides a promising approach to make high quality predictions on various data sets and in different compound optimization scenarios.

  17. Mastering the non-equilibrium assembly and operation of molecular machines.

    Science.gov (United States)

    Pezzato, Cristian; Cheng, Chuyang; Stoddart, J Fraser; Astumian, R Dean

    2017-09-18

    In mechanically interlocked compounds, such as rotaxanes and catenanes, the molecules are held together by mechanical rather than chemical bonds. These compounds can be engineered to have several well-defined mechanical states by incorporating recognition sites between the different components. The rates of the transitions between the recognition sites can be controlled by introducing steric "speed bumps" or electrostatically switchable gates. A mechanism for the absorption of energy can also be included by adding photoactive, catalytically active, or redox-active recognition sites, or even charges and dipoles. At equilibrium, these Mechanically Interlocked Molecules (MIMs) undergo thermally activated transitions continuously between their different mechanical states where every transition is as likely as its microscopic reverse. External energy, for example, light, external modulation of the chemical and/or physical environment or catalysis of an exergonic reaction, drives the system away from equilibrium. The absorption of energy from these processes can be used to favour some, and suppress other, transitions so that completion of a mechanical cycle in a direction in which work is done on the environment - the requisite of a molecular machine - is more likely than completion in a direction in which work is absorbed from the environment. In this Tutorial Review, we discuss the different design principles by which molecular machines can be engineered to use different sources of energy to carry out self-organization and the performance of work in their environments.

  18. Application of Machine Learning tools to recognition of molecular patterns in STM images

    Science.gov (United States)

    Maksov, Artem; Ziatdinov, Maxim; Fujii, Shintaro; Kiguchi, Manabu; Higashibayashi, Shuhei; Sakurai, Hidehiro; Kalinin, Sergei; Sumpter, Bobby

    The ability to utilize individual molecules and molecular assemblies as data storage elements has motivated scientist for years, concurrent with the continuous effort to shrink a size of data storage devices in microelectronics industry. One of the critical issues in this effort lies in being able to identify individual molecular assembly units (patterns), on a large scale in an automated fashion of complete information extraction. Here we present a novel method of applying machine learning techniques for extraction of positional and rotational information from scanning tunneling microscopy (STM) images of π-bowl sumanene molecules on gold. We use Markov Random Field (MRF) model to decode the polar rotational states for each molecule in a large scale STM image of molecular film. We further develop an algorithm that uses a convolutional Neural Network combined with MRF and input from density functional theory to classify molecules into different azimuthal rotational classes. Our results demonstrate that a molecular film is partitioned into distinctive azimuthal rotational domains consisting typically of 20-30 molecules. In each domain, the ``bowl-down'' molecules are generally surrounded by six nearest neighbor molecules in ``bowl-up'' configuration, and the resultant overall structure form a periodic lattice of rotational and polar states within each domain. Research was supported by the US Department of Energy.

  19. Atomic and molecular science with synchrotron radiation

    International Nuclear Information System (INIS)

    1989-01-01

    This paper discusses the following topics: electron correlation in atoms; atomic innershell excitation and decay mechanisms; timing experiments; x-ray scattering; properties of ionized species; electronic properties of actinide atoms; total photon-interaction cross sections; and molecular physics. 66 refs

  20. Molecular Science Computing Facility Scientific Challenges: Linking Across Scales

    Energy Technology Data Exchange (ETDEWEB)

    De Jong, Wibe A.; Windus, Theresa L.

    2005-07-01

    The purpose of this document is to define the evolving science drivers for performing environmental molecular research at the William R. Wiley Environmental Molecular Sciences Laboratory (EMSL) and to provide guidance associated with the next-generation high-performance computing center that must be developed at EMSL's Molecular Science Computing Facility (MSCF) in order to address this critical research. The MSCF is the pre-eminent computing facility?supported by the U.S. Department of Energy's (DOE's) Office of Biological and Environmental Research (BER)?tailored to provide the fastest time-to-solution for current computational challenges in chemistry and biology, as well as providing the means for broad research in the molecular and environmental sciences. The MSCF provides integral resources and expertise to emerging EMSL Scientific Grand Challenges and Collaborative Access Teams that are designed to leverage the multiple integrated research capabilities of EMSL, thereby creating a synergy between computation and experiment to address environmental molecular science challenges critical to DOE and the nation.

  1. Demystifying computer science for molecular ecologists.

    Science.gov (United States)

    Belcaid, Mahdi; Toonen, Robert J

    2015-06-01

    In this age of data-driven science and high-throughput biology, computational thinking is becoming an increasingly important skill for tackling both new and long-standing biological questions. However, despite its obvious importance and conspicuous integration into many areas of biology, computer science is still viewed as an obscure field that has, thus far, permeated into only a few of the biology curricula across the nation. A national survey has shown that lack of computational literacy in environmental sciences is the norm rather than the exception [Valle & Berdanier (2012) Bulletin of the Ecological Society of America, 93, 373-389]. In this article, we seek to introduce a few important concepts in computer science with the aim of providing a context-specific introduction aimed at research biologists. Our goal was to help biologists understand some of the most important mainstream computational concepts to better appreciate bioinformatics methods and trade-offs that are not obvious to the uninitiated. © 2015 John Wiley & Sons Ltd.

  2. Committee on Atomic, Molecular, and Optical Sciences (CAMOS)

    International Nuclear Information System (INIS)

    1992-01-01

    The Committee on Atomic, Molecular, and Optical Sciences is a standing committee under the auspices of the Board on Physics and Astronomy, Commission on Physical Sciences, Mathematics, and Applications of the National Academy of Sciences -- National Research Council. The atomic, molecular, and optical (AMO) sciences represent a broad and diverse field in which much of the research is carried out by small groups. These groups generally have not operated in concert with each other and, prior to the establishment of CAMOS, there was no single committee or organization that accepted the responsibility of monitoring the continuing development and assessing the general public health of the field as a whole. CAMOS has accepted this responsibility and currently provides a focus for the AMO community that is unique and essential. The membership of CAMOS is drawn from research laboratories in universities, industry, and government. Areas of expertise on the committee include atomic physics, molecular science, and optics. A special effort has been made to include a balanced representation from the three subfields. (A roster is attached.) CAMOS has conducted a number of studies related to the health of atomic and molecular science and is well prepared to response to requests for studies on specific issues. This report brief reviews the committee work of progress

  3. Committee on Atomic, Molecular, and Optical Sciences (CAMOS)

    International Nuclear Information System (INIS)

    1992-01-01

    The Committee on Atomic, Molecular and Optical Sciences (CAMOS) of the National Research Council (NRC) is charged with monitoring the health of the field of atomic, molecular, and optical (AMO) science in the United States. Accordingly, the Committee identifies and examines both broad and specific issues affecting the field. Regular meetings, teleconferences, briefings from agencies and the scientific community, the formation of study panels to prepare reports, and special symposia are among the mechanisms used by the CAMOS to meet its charge. This progress report presents a review of CAMOS activities from February 1, 1992 to January 31, 1993. This report also includes the status of activities associated with the CAMOS study on the field that is being conducted by the Panel on the Future of Atomic, Molecular, and Optical Sciences (FAMOS)

  4. THE MILKY WAY PROJECT: LEVERAGING CITIZEN SCIENCE AND MACHINE LEARNING TO DETECT INTERSTELLAR BUBBLES

    International Nuclear Information System (INIS)

    Beaumont, Christopher N.; Williams, Jonathan P.; Goodman, Alyssa A.; Kendrew, Sarah; Simpson, Robert

    2014-01-01

    We present Brut, an algorithm to identify bubbles in infrared images of the Galactic midplane. Brut is based on the Random Forest algorithm, and uses bubbles identified by >35,000 citizen scientists from the Milky Way Project to discover the identifying characteristics of bubbles in images from the Spitzer Space Telescope. We demonstrate that Brut's ability to identify bubbles is comparable to expert astronomers. We use Brut to re-assess the bubbles in the Milky Way Project catalog, and find that 10%-30% of the objects in this catalog are non-bubble interlopers. Relative to these interlopers, high-reliability bubbles are more confined to the mid-plane, and display a stronger excess of young stellar objects along and within bubble rims. Furthermore, Brut is able to discover bubbles missed by previous searches—particularly bubbles near bright sources which have low contrast relative to their surroundings. Brut demonstrates the synergies that exist between citizen scientists, professional scientists, and machine learning techniques. In cases where ''untrained' citizens can identify patterns that machines cannot detect without training, machine learning algorithms like Brut can use the output of citizen science projects as input training sets, offering tremendous opportunities to speed the pace of scientific discovery. A hybrid model of machine learning combined with crowdsourced training data from citizen scientists can not only classify large quantities of data, but also address the weakness of each approach if deployed alone

  5. Machine Learning Technologies and Their Applications for Science and Engineering Domains Workshop -- Summary Report

    Science.gov (United States)

    Ambur, Manjula; Schwartz, Katherine G.; Mavris, Dimitri N.

    2016-01-01

    The fields of machine learning and big data analytics have made significant advances in recent years, which has created an environment where cross-fertilization of methods and collaborations can achieve previously unattainable outcomes. The Comprehensive Digital Transformation (CDT) Machine Learning and Big Data Analytics team planned a workshop at NASA Langley in August 2016 to unite leading experts the field of machine learning and NASA scientists and engineers. The primary goal for this workshop was to assess the state-of-the-art in this field, introduce these leading experts to the aerospace and science subject matter experts, and develop opportunities for collaboration. The workshop was held over a three day-period with lectures from 15 leading experts followed by significant interactive discussions. This report provides an overview of the 15 invited lectures and a summary of the key discussion topics that arose during both formal and informal discussion sections. Four key workshop themes were identified after the closure of the workshop and are also highlighted in the report. Furthermore, several workshop attendees provided their feedback on how they are already utilizing machine learning algorithms to advance their research, new methods they learned about during the workshop, and collaboration opportunities they identified during the workshop.

  6. THE MILKY WAY PROJECT: LEVERAGING CITIZEN SCIENCE AND MACHINE LEARNING TO DETECT INTERSTELLAR BUBBLES

    Energy Technology Data Exchange (ETDEWEB)

    Beaumont, Christopher N.; Williams, Jonathan P. [Institute for Astronomy, University of Hawai' i, 2680 Woodlawn Drive, Honolulu, HI 96822 (United States); Goodman, Alyssa A. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Kendrew, Sarah; Simpson, Robert, E-mail: beaumont@ifa.hawaii.edu [Department of Astrophysics, University of Oxford, Denys Wilkinson Building, Keble Road, Oxford OX1 3RH (United Kingdom)

    2014-09-01

    We present Brut, an algorithm to identify bubbles in infrared images of the Galactic midplane. Brut is based on the Random Forest algorithm, and uses bubbles identified by >35,000 citizen scientists from the Milky Way Project to discover the identifying characteristics of bubbles in images from the Spitzer Space Telescope. We demonstrate that Brut's ability to identify bubbles is comparable to expert astronomers. We use Brut to re-assess the bubbles in the Milky Way Project catalog, and find that 10%-30% of the objects in this catalog are non-bubble interlopers. Relative to these interlopers, high-reliability bubbles are more confined to the mid-plane, and display a stronger excess of young stellar objects along and within bubble rims. Furthermore, Brut is able to discover bubbles missed by previous searches—particularly bubbles near bright sources which have low contrast relative to their surroundings. Brut demonstrates the synergies that exist between citizen scientists, professional scientists, and machine learning techniques. In cases where ''untrained' citizens can identify patterns that machines cannot detect without training, machine learning algorithms like Brut can use the output of citizen science projects as input training sets, offering tremendous opportunities to speed the pace of scientific discovery. A hybrid model of machine learning combined with crowdsourced training data from citizen scientists can not only classify large quantities of data, but also address the weakness of each approach if deployed alone.

  7. Communication: Understanding molecular representations in machine learning: The role of uniqueness and target similarity

    Science.gov (United States)

    Huang, Bing; von Lilienfeld, O. Anatole

    2016-10-01

    The predictive accuracy of Machine Learning (ML) models of molecular properties depends on the choice of the molecular representation. Inspired by the postulates of quantum mechanics, we introduce a hierarchy of representations which meet uniqueness and target similarity criteria. To systematically control target similarity, we simply rely on interatomic many body expansions, as implemented in universal force-fields, including Bonding, Angular (BA), and higher order terms. Addition of higher order contributions systematically increases similarity to the true potential energy and predictive accuracy of the resulting ML models. We report numerical evidence for the performance of BAML models trained on molecular properties pre-calculated at electron-correlated and density functional theory level of theory for thousands of small organic molecules. Properties studied include enthalpies and free energies of atomization, heat capacity, zero-point vibrational energies, dipole-moment, polarizability, HOMO/LUMO energies and gap, ionization potential, electron affinity, and electronic excitations. After training, BAML predicts energies or electronic properties of out-of-sample molecules with unprecedented accuracy and speed.

  8. Machine learning predictions of molecular properties: Accurate many-body potentials and nonlocality in chemical space

    International Nuclear Information System (INIS)

    Hansen, Katja; Biegler, Franziska; Ramakrishnan, Raghunathan; Pronobis, Wiktor; Lilienfeld, O. Anatole von; Müller, Klaus-Robert; Tkatchenko, Alexandre

    2015-01-01

    Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and apply a systematic hierarchy of efficient empirical methods to estimate atomization and total energies of molecules. These methods range from a simple sum over atoms, to addition of bond energies, to pairwise interatomic force fields, reaching to the more sophisticated machine learning approaches that are capable of describing collective interactions between many atoms or bonds. In the case of equilibrium molecular geometries, even simple pairwise force fields demonstrate prediction accuracy comparable to benchmark energies calculated using density functional theory with hybrid exchange-correlation functionals; however, accounting for the collective many-body interactions proves to be essential for approaching the 'holy grail' of chemical accuracy of 1 kcal/mol for both equilibrium and out-of-equilibrium geometries. This remarkable accuracy is achieved by a vectorized representation of molecules (so-called Bag of Bonds model) that exhibits strong nonlocality in chemical space. The same representation allows us to predict accurate electronic properties of molecules, such as their polarizability and molecular frontier orbital energies

  9. Femtochemistry and femtobiology ultrafast dynamics in molecular science

    CERN Document Server

    Douhal, Abderrazzak

    2002-01-01

    This book contains important contributions from top international scientists on the-state-of-the-art of femtochemistry and femtobiology at the beginning of the new millennium. It consists of reviews and papers on ultrafast dynamics in molecular science.The coverage of topics highlights several important features of molecular science from the viewpoint of structure (space domain) and dynamics (time domain). First of all, the book presents the latest developments, such as experimental techniques for understanding ultrafast processes in gas, condensed and complex systems, including biological mol

  10. Integration of molecular machines into supramolecular materials: actuation between equilibrium polymers and crystal-like gels.

    Science.gov (United States)

    Mariani, Giacomo; Goujon, Antoine; Moulin, Emilie; Rawiso, Michel; Giuseppone, Nicolas; Buhler, Eric

    2017-11-30

    In this article, the dynamic structure of complex supramolecular polymers composed of bistable [c2]daisy chain rotaxanes as molecular machines that are linked by ureidopyrimidinones (Upy) as recognition moieties was studied. pH actuation of the integrated mechanically active rotaxanes controls the contraction/extension of the polymer chains as well as their physical reticulation. Small-angle neutron and X-ray scattering were used to study in-depth the nanostructure of the contracted and extended polymer aggregates in toluene solution. The supramolecular polymers comprising contracted nanomachines were found to be equilibrium polymers with a mass that is concentration dependent in dilute and semidilute regimes. Surprisingly, the extended polymers form a gel network with a crystal-like internal structure that is independent of concentration and reminiscent of a pearl-necklace network.

  11. Environmental and Molecular Science Laboratory Arrow

    Energy Technology Data Exchange (ETDEWEB)

    2016-06-24

    Arrows is a software package that combines NWChem, SQL and NOSQL databases, email, and social networks (e.g. Twitter, Tumblr) that simplifies molecular and materials modeling and makes these modeling capabilities accessible to all scientists and engineers. EMSL Arrows is very simple to use. The user just emails chemical reactions to arrows@emsl.pnnl.gov and then an email is sent back with thermodynamic, reaction pathway (kinetic), spectroscopy, and other results. EMSL Arrows parses the email and then searches the database for the compounds in the reactions. If a compound isn't there, an NWChem calculation is setup and submitted to calculate it. Once the calculation is finished the results are entered into the database and then results are emailed back.

  12. Van der Waals and Molecular Science

    International Nuclear Information System (INIS)

    Kox, A J

    1997-01-01

    For many years it has been a source of amazement to scientists and historians of science that no serious scientific biography of J D van der Waals existed. When, more than ten years ago, I became engaged in a correspondence with the Russian historian of science B E Yavelow on the topic of van der Waals, whose biography he was writing, I was both pleased and a bit puzzled. It was clear that Yavelow had not done any archival research in the Netherlands himself, yet he was intimately familiar with many obscure facts from the life of van der Waals. Naturally, I was very curious to see the end result, which appeared in 1985, but although the Amsterdam University Library obtained a copy, my limited knowledge of Russian kept me from forming a judgement on the book. Finally, after more than ten years, an English edition has appeared. The two original Russian authors have joined forces with the well known scientist J S Rowlinson (who earlier edited an English translation of van der Waals's dissertation) to produce a revised and enlarged English version of the Russian original. Now that I have finally been able to study this work, I must admit to being much impressed. Both the life and the work of van der Waals are dealt with in an exemplary way: the authors' command of primary and secondary sources is impressive, as is their understanding of the Dutch social and educational circumstances in the last century. Teaching and research at the newly-founded University of Amsterdam, as well as activities in the Academy of Sciences, are discussed in great and interesting detail. Van der Waals's education and rise from a simple teacher to one of the foremost theoretical physicists in Europe teaches us much about his personality as well as about the opportunities offered by the Dutch educational system. In their discussion of the development of van der Waals's ideas and their impact (including an interesting chapter on the reception in Russia) the authors are not afraid to go into

  13. Historical and Epistemological Reflections on the Culture of Machines around the Renaissance: How Science and Technique Work?

    Directory of Open Access Journals (Sweden)

    Raffaele Pisano

    2014-10-01

    Full Text Available This paper is divided into two parts, this being the first one. The second is entitled ‘Historical and Epistemological Reflections on the Culture of Machines around Renaissance: Machines, Machineries and Perpetual Motion’ and will be published in Acta Baltica Historiae et Philosophiae Scientiarum in 2015. Based on our recent studies, we provide here a historical and epistemological feature on the role played by machines and machineries. Ours is an epistemological thesis based on a series of historical examples to show that the relations between theoretical science and the construction of machines cannot be taken for granted, a priori. Our analysis is mainly based on the culture of machines around 15th and 17th centuries, namely the epoch of Late Renaissance and Early Modern Age. For this is the period of scientific revolution and this age offers abundant interesting material for researches into the relations of theoretical science/construction of machines as well. However, to prove our epistemological thesis, we will also exploit examples of machines built in other historical periods. Particularly, a discussion concerning the relationship between science theory and the development of science art crafts produced by non-recognized scientists in a certain historical time is presented. The main questions are: when and why did the tension between science (physics, mathematics and geometry give rise to a new scientific approach to applied discipline such as studies on machines and machineries? What kind of science was used (if at all for projecting machines and machineries? Was science at the time a necessary precondition to build a machine? In the first part we will focus on the difference between Aristotelian-Euclidean and Archimedean approaches and we will outline the heritage of these two different approaches in late medieval and Renaissance science. In the second part, we will apply our reconstructions to some historical and epistemological

  14. Gravity Spy - Integrating LIGO detector characterization, citizen science, and machine learning

    Science.gov (United States)

    Zevin, Michael; Gravity Spy

    2016-06-01

    On September 14th 2015, the Advanced Laser Interferometer Gravitational-wave Observatory (aLIGO) made the first direct observation of gravitational waves and opened a new field of observational astronomy. However, being the most complicated and sensitve experiment ever undertaken in gravitational physics, aLIGO is susceptible to various sources of environmental and instrumental noise that hinder the search for more gravitational waves.Of particular concern are transient, non-Gaussian noise features known as glitches. Glitches can mimic true astrophysical gravitational waves, occur at a high enough frequency to be coherent between the two detectors, and generally worsen aLIGO's detection capabilities. The proper classification and charaterization of glitches is paramount in optimizing aLIGO's ability to detect gravitational waves. However, teaching computers to identify and morphologically classify these artifacts is exceedingly difficult.Human intuition has proven to be a useful tool in classifcation probelms such as this. Gravity Spy is an innovative, interdisciplinary project hosted by Zooniverse that combines aLIGO detector characterization, citizen science, machine learning, and social science. In this project, citizen scientists and computers will work together in a sybiotic relationship that leverages human pattern recognition and the ability of machine learning to process large amounts of data systematically: volunteers classify triggers from the aLIGO data steam that are constantly updated as aLIGO takes in new data, and these classifications are used to train machine learning algorithms which proceed to classify the bulk of aLIGO data and feed questionable glithces back to the users.In this talk, I will discuss the workflow and initial results of the Gravity Spy project with regard to aLIGO's future observing runs and highlight the potential of such citizen science projects in promoting nascent fields such as gravitational wave astrophysics.

  15. Hidden Markov models and other machine learning approaches in computational molecular biology

    Energy Technology Data Exchange (ETDEWEB)

    Baldi, P. [California Inst. of Tech., Pasadena, CA (United States)

    1995-12-31

    This tutorial was one of eight tutorials selected to be presented at the Third International Conference on Intelligent Systems for Molecular Biology which was held in the United Kingdom from July 16 to 19, 1995. Computational tools are increasingly needed to process the massive amounts of data, to organize and classify sequences, to detect weak similarities, to separate coding from non-coding regions, and reconstruct the underlying evolutionary history. The fundamental problem in machine learning is the same as in scientific reasoning in general, as well as statistical modeling: to come up with a good model for the data. In this tutorial four classes of models are reviewed. They are: Hidden Markov models; artificial Neural Networks; Belief Networks; and Stochastic Grammars. When dealing with DNA and protein primary sequences, Hidden Markov models are one of the most flexible and powerful alignments and data base searches. In this tutorial, attention is focused on the theory of Hidden Markov Models, and how to apply them to problems in molecular biology.

  16. Prediction Errors of Molecular Machine Learning Models Lower than Hybrid DFT Error.

    Science.gov (United States)

    Faber, Felix A; Hutchison, Luke; Huang, Bing; Gilmer, Justin; Schoenholz, Samuel S; Dahl, George E; Vinyals, Oriol; Kearnes, Steven; Riley, Patrick F; von Lilienfeld, O Anatole

    2017-11-14

    We investigate the impact of choosing regressors and molecular representations for the construction of fast machine learning (ML) models of 13 electronic ground-state properties of organic molecules. The performance of each regressor/representation/property combination is assessed using learning curves which report out-of-sample errors as a function of training set size with up to ∼118k distinct molecules. Molecular structures and properties at the hybrid density functional theory (DFT) level of theory come from the QM9 database [ Ramakrishnan et al. Sci. Data 2014 , 1 , 140022 ] and include enthalpies and free energies of atomization, HOMO/LUMO energies and gap, dipole moment, polarizability, zero point vibrational energy, heat capacity, and the highest fundamental vibrational frequency. Various molecular representations have been studied (Coulomb matrix, bag of bonds, BAML and ECFP4, molecular graphs (MG)), as well as newly developed distribution based variants including histograms of distances (HD), angles (HDA/MARAD), and dihedrals (HDAD). Regressors include linear models (Bayesian ridge regression (BR) and linear regression with elastic net regularization (EN)), random forest (RF), kernel ridge regression (KRR), and two types of neural networks, graph convolutions (GC) and gated graph networks (GG). Out-of sample errors are strongly dependent on the choice of representation and regressor and molecular property. Electronic properties are typically best accounted for by MG and GC, while energetic properties are better described by HDAD and KRR. The specific combinations with the lowest out-of-sample errors in the ∼118k training set size limit are (free) energies and enthalpies of atomization (HDAD/KRR), HOMO/LUMO eigenvalue and gap (MG/GC), dipole moment (MG/GC), static polarizability (MG/GG), zero point vibrational energy (HDAD/KRR), heat capacity at room temperature (HDAD/KRR), and highest fundamental vibrational frequency (BAML/RF). We present numerical

  17. Advances in Molecular Rotational Spectroscopy for Applied Science

    Science.gov (United States)

    Harris, Brent; Fields, Shelby S.; Pulliam, Robin; Muckle, Matt; Neill, Justin L.

    2017-06-01

    Advances in chemical sensitivity and robust, solid-state designs for microwave/millimeter-wave instrumentation compel the expansion of molecular rotational spectroscopy as research tool into applied science. It is familiar to consider molecular rotational spectroscopy for air analysis. Those techniques for molecular rotational spectroscopy are included in our presentation of a more broad application space for materials analysis using Fourier Transform Molecular Rotational Resonance (FT-MRR) spectrometers. There are potentially transformative advantages for direct gas analysis of complex mixtures, determination of unknown evolved gases with parts per trillion detection limits in solid materials, and unambiguous chiral determination. The introduction of FT-MRR as an alternative detection principle for analytical chemistry has created a ripe research space for the development of new analytical methods and sampling equipment to fully enable FT-MRR. We present the current state of purpose-built FT-MRR instrumentation and the latest application measurements that make use of new sampling methods.

  18. BioImg.org: A Catalog of Virtual Machine Images for the Life Sciences.

    Science.gov (United States)

    Dahlö, Martin; Haziza, Frédéric; Kallio, Aleksi; Korpelainen, Eija; Bongcam-Rudloff, Erik; Spjuth, Ola

    2015-01-01

    Virtualization is becoming increasingly important in bioscience, enabling assembly and provisioning of complete computer setups, including operating system, data, software, and services packaged as virtual machine images (VMIs). We present an open catalog of VMIs for the life sciences, where scientists can share information about images and optionally upload them to a server equipped with a large file system and fast Internet connection. Other scientists can then search for and download images that can be run on the local computer or in a cloud computing environment, providing easy access to bioinformatics environments. We also describe applications where VMIs aid life science research, including distributing tools and data, supporting reproducible analysis, and facilitating education. BioImg.org is freely available at: https://bioimg.org.

  19. Time machine tales the science fiction adventures and philosophical puzzles of time travel

    CERN Document Server

    Nahin, Paul J

    2017-01-01

    This book contains a broad overview of time travel in science fiction, along with a detailed examination of the philosophical implications of time travel. The emphasis of this book is now on the philosophical and on science fiction, rather than on physics, as in the author's earlier books on the subject. In that spirit there are, for example, no Tech Notes filled with algebra, integrals, and differential equations, as there are in the first and second editions of TIME MACHINES. Writing about time travel is, today, a respectable business. It hasn’t always been so. After all, time travel, prima facie, appears to violate a fundamental law of nature; every effect has a cause, with the cause occurring before the effect. Time travel to the past, however, seems to allow, indeed to demand, backwards causation, with an effect (the time traveler emerging into the past as he exits from his time machine) occurring before its cause (the time traveler pushing the start button on his machine’s control panel to start his...

  20. New Trends in E-Science: Machine Learning and Knowledge Discovery in Databases

    Science.gov (United States)

    Brescia, Massimo

    2012-11-01

    Data mining, or Knowledge Discovery in Databases (KDD), while being the main methodology to extract the scientific information contained in Massive Data Sets (MDS), needs to tackle crucial problems since it has to orchestrate complex challenges posed by transparent access to different computing environments, scalability of algorithms, reusability of resources. To achieve a leap forward for the progress of e-science in the data avalanche era, the community needs to implement an infrastructure capable of performing data access, processing and mining in a distributed but integrated context. The increasing complexity of modern technologies carried out a huge production of data, whose related warehouse management and the need to optimize analysis and mining procedures lead to a change in concept on modern science. Classical data exploration, based on local user own data storage and limited computing infrastructures, is no more efficient in the case of MDS, worldwide spread over inhomogeneous data centres and requiring teraflop processing power. In this context modern experimental and observational science requires a good understanding of computer science, network infrastructures, Data Mining, etc. i.e. of all those techniques which fall into the domain of the so called e-science (recently assessed also by the Fourth Paradigm of Science). Such understanding is almost completely absent in the older generations of scientists and this reflects in the inadequacy of most academic and research programs. A paradigm shift is needed: statistical pattern recognition, object oriented programming, distributed computing, parallel programming need to become an essential part of scientific background. A possible practical solution is to provide the research community with easy-to understand, easy-to-use tools, based on the Web 2.0 technologies and Machine Learning methodology. Tools where almost all the complexity is hidden to the final user, but which are still flexible and able to

  1. Molecular Environmental Science and Synchrotron Radiation Facilities An Update of the 1995 DOE-Airlie Report on Molecular Environmental Science

    Energy Technology Data Exchange (ETDEWEB)

    Bargar, John R

    1999-05-07

    This workshop was requested by Dr. Robert Marianelli, Director of the DOE-BES Chemical Sciences Division, to update the findings of the Workshop on Molecular Environmental Sciences (MES) held at Airlie, VA, in July 1995. The Airlie Workshop Report defined the new interdisciplinary field referred to as Molecular Environmental Science (MES), reviewed the synchrotron radiation methods used in MES research, assessed the adequacy of synchrotron radiation facilities for research in this field, and summarized the beam time requirements of MES users based on a national MES user survey. The objectives of MES research are to provide information on the chemical and physical forms (speciation), spatial distribution, and reactivity of contaminants in natural materials and man-made waste forms, and to develop a fundamental understanding of the complex molecular-scale environmental processes, both chemical and biological, that affect the stability, transformations, mobility, and toxicity of contaminant species. These objectives require parallel studies of ''real'' environmental samples, which are complicated multi-phase mixtures with chemical and physical heterogeneities, and of simplified model systems in which variables can be controlled and fundamental processes can be examined. Only by this combination of approaches can a basic understanding of environmental processes at the molecular-scale be achieved.

  2. Molecular Environmental Science and Synchrotron Radiation Facilities An Update of the 1995 DOE-Airlie Report on Molecular Environmental Science

    International Nuclear Information System (INIS)

    Bargar, John R

    1999-01-01

    This workshop was requested by Dr. Robert Marianelli, Director of the DOE-BES Chemical Sciences Division, to update the findings of the Workshop on Molecular Environmental Sciences (MES) held at Airlie, VA, in July 1995. The Airlie Workshop Report defined the new interdisciplinary field referred to as Molecular Environmental Science (MES), reviewed the synchrotron radiation methods used in MES research, assessed the adequacy of synchrotron radiation facilities for research in this field, and summarized the beam time requirements of MES users based on a national MES user survey. The objectives of MES research are to provide information on the chemical and physical forms (speciation), spatial distribution, and reactivity of contaminants in natural materials and man-made waste forms, and to develop a fundamental understanding of the complex molecular-scale environmental processes, both chemical and biological, that affect the stability, transformations, mobility, and toxicity of contaminant species. These objectives require parallel studies of ''real'' environmental samples, which are complicated multi-phase mixtures with chemical and physical heterogeneities, and of simplified model systems in which variables can be controlled and fundamental processes can be examined. Only by this combination of approaches can a basic understanding of environmental processes at the molecular-scale be achieved

  3. Constant size descriptors for accurate machine learning models of molecular properties

    Science.gov (United States)

    Collins, Christopher R.; Gordon, Geoffrey J.; von Lilienfeld, O. Anatole; Yaron, David J.

    2018-06-01

    Two different classes of molecular representations for use in machine learning of thermodynamic and electronic properties are studied. The representations are evaluated by monitoring the performance of linear and kernel ridge regression models on well-studied data sets of small organic molecules. One class of representations studied here counts the occurrence of bonding patterns in the molecule. These require only the connectivity of atoms in the molecule as may be obtained from a line diagram or a SMILES string. The second class utilizes the three-dimensional structure of the molecule. These include the Coulomb matrix and Bag of Bonds, which list the inter-atomic distances present in the molecule, and Encoded Bonds, which encode such lists into a feature vector whose length is independent of molecular size. Encoded Bonds' features introduced here have the advantage of leading to models that may be trained on smaller molecules and then used successfully on larger molecules. A wide range of feature sets are constructed by selecting, at each rank, either a graph or geometry-based feature. Here, rank refers to the number of atoms involved in the feature, e.g., atom counts are rank 1, while Encoded Bonds are rank 2. For atomization energies in the QM7 data set, the best graph-based feature set gives a mean absolute error of 3.4 kcal/mol. Inclusion of 3D geometry substantially enhances the performance, with Encoded Bonds giving 2.4 kcal/mol, when used alone, and 1.19 kcal/mol, when combined with graph features.

  4. Mitochondrial AAA proteases--towards a molecular understanding of membrane-bound proteolytic machines.

    Science.gov (United States)

    Gerdes, Florian; Tatsuta, Takashi; Langer, Thomas

    2012-01-01

    Mitochondrial AAA proteases play an important role in the maintenance of mitochondrial proteostasis. They regulate and promote biogenesis of mitochondrial proteins by acting as processing enzymes and ensuring the selective turnover of misfolded proteins. Impairment of AAA proteases causes pleiotropic defects in various organisms including neurodegeneration in humans. AAA proteases comprise ring-like hexameric complexes in the mitochondrial inner membrane and are functionally conserved from yeast to man, but variations are evident in the subunit composition of orthologous enzymes. Recent structural and biochemical studies revealed how AAA proteases degrade their substrates in an ATP dependent manner. Intersubunit coordination of the ATP hydrolysis leads to an ordered ATP hydrolysis within the AAA ring, which ensures efficient substrate dislocation from the membrane and translocation to the proteolytic chamber. In this review, we summarize recent findings on the molecular mechanisms underlying the versatile functions of mitochondrial AAA proteases and their relevance to those of the other AAA+ machines. Copyright © 2011 Elsevier B.V. All rights reserved.

  5. Molecular machines regulating the release probability of synaptic vesicles at the active zone.

    Directory of Open Access Journals (Sweden)

    Christoph eKoerber

    2016-03-01

    Full Text Available The fusion of synaptic vesicles (SVs with the plasma membrane of the active zone (AZ upon arrival of an action potential (AP at the presynaptic compartment is a tightly regulated probabil-istic process crucial for information transfer. The probability of a SV to release its transmitter content in response to an AP, termed release probability (Pr, is highly diverse both at the level of entire synapses and individual SVs at a given synapse. Differences in Pr exist between different types of synapses, between synapses of the same type, synapses originating from the same axon and even between different SV subpopulations within the same presynaptic terminal. The Pr of SVs at the AZ is set by a complex interplay of different presynaptic properties including the availability of release-ready SVs, the location of the SVs relative to the voltage-gated calcium channels (VGCCs at the AZ, the magnitude of calcium influx upon arrival of the AP, the buffer-ing of calcium ions as well as the identity and sensitivity of the calcium sensor. These properties are not only interconnected, but can also be regulated dynamically to match the requirements of activity patterns mediated by the synapse. Here, we review recent advances in identifying mole-cules and molecular machines taking part in the determination of vesicular Pr at the AZ.

  6. Resonance – Journal of Science Education | Indian Academy of ...

    Indian Academy of Sciences (India)

    2016 Nobel Prize in Chemistry: Conferring Molecular Machines as Engines of Creativity ... Science Academies' 92nd Refresher Course in Experimental Physics ... Science Academies' Refresher Course on Advances in Molecular Biology.

  7. How to build a time machine: the real science of time travel

    CERN Document Server

    Clegg, Brian

    2013-01-01

    A pop science look at time travel technology, from Einstein to Ronald Mallett to present day experiments. Forget fiction: time travel is real.In How to Build a Time Machine, Brian Clegg provides an understanding of what time is and how it can be manipulated. He explores the fascinating world of physics and the remarkable possibilities of real time travel that emerge from quantum entanglement, superluminal speeds, neutron star cylinders and wormholes in space. With the fascinating paradoxes of time travel echoing in our minds will we realize that travel into the future might never be possible? Or will we realize there is no limit on what can be achieved, and take on this ultimate challenge? Only time will tell.

  8. Analysing and Rationalising Molecular and Materials Databases Using Machine-Learning

    Science.gov (United States)

    de, Sandip; Ceriotti, Michele

    Computational materials design promises to greatly accelerate the process of discovering new or more performant materials. Several collaborative efforts are contributing to this goal by building databases of structures, containing between thousands and millions of distinct hypothetical compounds, whose properties are computed by high-throughput electronic-structure calculations. The complexity and sheer amount of information has made manual exploration, interpretation and maintenance of these databases a formidable challenge, making it necessary to resort to automatic analysis tools. Here we will demonstrate how, starting from a measure of (dis)similarity between database items built from a combination of local environment descriptors, it is possible to apply hierarchical clustering algorithms, as well as dimensionality reduction methods such as sketchmap, to analyse, classify and interpret trends in molecular and materials databases, as well as to detect inconsistencies and errors. Thanks to the agnostic and flexible nature of the underlying metric, we will show how our framework can be applied transparently to different kinds of systems ranging from organic molecules and oligopeptides to inorganic crystal structures as well as molecular crystals. Funded by National Center for Computational Design and Discovery of Novel Materials (MARVEL) and Swiss National Science Foundation.

  9. Dynamics of polymers in a good solvent - a molecular dynamics study using the Connection Machine

    International Nuclear Information System (INIS)

    Shannon, S.R.; Choy, T.C.

    1996-01-01

    In recent times the use of molecular dynamics simulations has become an important tool in modelling and understanding the dynamics of interacting many-body systems. With recent advances in computing power it is now feasible to perform modelling of systems which contain a large number of interacting particles, and thus to simulate the behaviour of real systems reasonably. Our earlier discoveries of anomalous corrections to scaling behaviour of the Edward's polymer were applied to study the dynamical behaviour of two dimensional polymer systems - either a single chain immersed in a fluid, a pure polymer melt, or with any concentration of polymers in the fluid. By choosing a suitable interaction potential between the fluid particles and the monomers, we are able to study the experimentally observable time dependent structure factor of polymers in a good solvent. Simulations were performed using the Connection Machine CM5 supercomputer at the Australian National University which due to its fast multi- processor nearest neighbour communications facility, enables us to easily model large systems of at least 3000 fluid plus monomer particles. Our study is based on a finite difference solution of Newton's equations of motion i.e. the Verlet algorithm, and the results are used to test current theories of polymer dynamics, which were based primarily on the earlier models proposed by Rouse (1953) and Zimm (1956). In particular dynamical scaling predictions is scrutinised to examine the effects due to the anomalous corrections-to-scaling behaviour found in an earlier work using finite-size scaling analysis of Monte-Carlo data and now understood via a new perturbation concept

  10. Molecular surface science of heterogeneous catalysis. History and perspective

    International Nuclear Information System (INIS)

    Somorjai, G.A.

    1983-08-01

    A personal account is given of how the author became involved with modern surface science and how it was employed for studies of the chemistry of surfaces and heterogeneous catalysis. New techniques were developed for studying the properties of the surface monolayers: Auger electron spectroscopy, LEED, XPS, molecular beam surface scattering, etc. An apparatus was developed and used to study hydrocarbon conversion reactions on Pt, CO hydrogenation on Rh and Fe, and NH 3 synthesis on Fe. A model has been developed for the working Pt reforming catalyst. The three molecular ingredients that control catalytic properties are atomic surface structure, an active carbonaceous deposit, and the proper oxidation state of surface atoms. 40 references, 21 figures

  11. Molecular surface science of heterogeneous catalysis. History and perspective

    Energy Technology Data Exchange (ETDEWEB)

    Somorjai, G.A.

    1983-08-01

    A personal account is given of how the author became involved with modern surface science and how it was employed for studies of the chemistry of surfaces and heterogeneous catalysis. New techniques were developed for studying the properties of the surface monolayers: Auger electron spectroscopy, LEED, XPS, molecular beam surface scattering, etc. An apparatus was developed and used to study hydrocarbon conversion reactions on Pt, CO hydrogenation on Rh and Fe, and NH/sub 3/ synthesis on Fe. A model has been developed for the working Pt reforming catalyst. The three molecular ingredients that control catalytic properties are atomic surface structure, an active carbonaceous deposit, and the proper oxidation state of surface atoms. 40 references, 21 figures. (DLC)

  12. Scientific data management in the environmental molecular sciences laboratory

    Energy Technology Data Exchange (ETDEWEB)

    Bernard, P.R.; Keller, T.L.

    1995-09-01

    The Environmental Molecular Sciences Laboratory (EMSL) is currently under construction at Pacific Northwest Laboratory (PNL) for the U.S. Department of Energy (DOE). This laboratory will be used for molecular and environmental sciences research to identify comprehensive solutions to DOE`s environmental problems. Major facilities within the EMSL include the Molecular Sciences Computing Facility (MSCF), a laser-surface dynamics laboratory, a high-field nuclear magnetic resonance (NMR) laboratory, and a mass spectrometry laboratory. The EMSL is scheduled to open early in 1997 and will house about 260 resident and visiting scientists. It is anticipated that at least six (6) terabytes of data will be archived in the first year of operation. An object-oriented database management system (OODBMS) and a mass storage system will be integrated to provide an intelligent, automated mechanism to manage data. The resulting system, called the DataBase Computer System (DBCS), will provide total scientific data management capabilities to EMSL users. A prototype mass storage system based on the National Storage Laboratory`s (NSL) UniTree has been procured and is in limited use. This system consists of two independent hierarchies of storage devices. One hierarchy of lower capacity, slower speed devices provides support for smaller files transferred over the Fiber Distributed Data Interface (FDDI) network. Also part of the system is a second hierarchy of higher capacity, higher speed devices that will be used to support high performance clients (e.g., a large scale parallel processor). The ObjectStore OODBMS will be used to manage metadata for archived datasets, maintain relationships between archived datasets, and -hold small, duplicate subsets of archived datasets (i.e., derivative data). The interim system is called DBCS, Phase 0 (DBCS-0). The production system for the EMSL, DBCS Phase 1 (DBCS-1), will be procured and installed in the summer of 1996.

  13. Interdisciplinary research center devoted to molecular environmental science opens

    Science.gov (United States)

    Vaughan, David J.

    In October, a new research center opened at the University of Manchester in the United Kingdom. The center is the product of over a decade of ground-breaking interdisciplinary research in the Earth and related biological and chemical sciences at the university The center also responds to the British governments policy of investing in research infrastructure at key universities.The Williamson Research Centre, the first of its kind in Britain and among the first worldwide, is devoted to the emerging field of molecular environmental science. This field also aims to bring about a revolution in understanding of our environment. Though it may be a less violent revolution than some, perhaps, its potential is high for developments that could affect us all.

  14. Large-scale theoretical calculations in molecular science - design of a large computer system for molecular science and necessary conditions for future computers

    Energy Technology Data Exchange (ETDEWEB)

    Kashiwagi, H [Institute for Molecular Science, Okazaki, Aichi (Japan)

    1982-06-01

    A large computer system was designed and established for molecular science under the leadership of molecular scientists. Features of the computer system are an automated operation system and an open self-service system. Large-scale theoretical calculations have been performed to solve many problems in molecular science, using the computer system. Necessary conditions for future computers are discussed on the basis of this experience.

  15. Large-scale theoretical calculations in molecular science - design of a large computer system for molecular science and necessary conditions for future computers

    International Nuclear Information System (INIS)

    Kashiwagi, H.

    1982-01-01

    A large computer system was designed and established for molecular science under the leadership of molecular scientists. Features of the computer system are an automated operation system and an open self-service system. Large-scale theoretical calculations have been performed to solve many problems in molecular science, using the computer system. Necessary conditions for future computers are discussed on the basis of this experience. (orig.)

  16. Building a Collaboratory in Environmental and Molecular Science

    Energy Technology Data Exchange (ETDEWEB)

    Kouzes, R.T.; Myers, J.D.; Devaney, D.M.; Dunning, T.H.; Wise, J.A.

    1994-03-01

    A Collaboratory is a meta-laboratory that spans multiple geographical areas with collaborators interacting via electronic means. Collaboratories are designed to enable close ties between scientists in a given research area, promote collaborations involving scientists in diverse areas, accelerate the development and dissemination of basic knowledge, and minimize the time-lag between discovery and application. PNL is developing the concept of an Environmental and Molecular Sciences Collaboratory (EMSC) as a natural evolution of the EMSL project. The goal of the EMSC is to increase the efficiency of research and reduce the time required to implement new environmental remediation and preservation technologies. The EMSC will leverage the resources (intellectual and physical) of the EMSL by making them more accessible to remote collaborators as well as by making the resources of remote sites available to local researchers. It will provide a common set of computer hardware and software tools to support remote collaboration, a key step in establishing a collaborative culture for scientists in the theoretical, computational, and experimental molecular sciences across the nation. In short, the EMSC will establish and support an `electronic community of scientists researching and developing innovative environmental preservation and restoration technologies.

  17. Building a Collaboratory in Environmental and Molecular Science

    International Nuclear Information System (INIS)

    Kouzes, R.T.; Myers, J.D.; Devaney, D.M.; Dunning, T.H.; Wise, J.A.

    1994-03-01

    A Collaboratory is a meta-laboratory that spans multiple geographical areas with collaborators interacting via electronic means. Collaboratories are designed to enable close ties between scientists in a given research area, promote collaborations involving scientists in diverse areas, accelerate the development and dissemination of basic knowledge, and minimize the time-lag between discovery and application. PNL is developing the concept of an Environmental and Molecular Sciences Collaboratory (EMSC) as a natural evolution of the EMSL project. The goal of the EMSC is to increase the efficiency of research and reduce the time required to implement new environmental remediation and preservation technologies. The EMSC will leverage the resources (intellectual and physical) of the EMSL by making them more accessible to remote collaborators as well as by making the resources of remote sites available to local researchers. It will provide a common set of computer hardware and software tools to support remote collaboration, a key step in establishing a collaborative culture for scientists in the theoretical, computational, and experimental molecular sciences across the nation. In short, the EMSC will establish and support an 'electronic community of scientists researching and developing innovative environmental preservation and restoration technologies

  18. Advanced Digitization Techniques in Retrieval of Mechanism and Machine Science Resources

    Science.gov (United States)

    Lovasz, E.-Ch.; Gruescu, C. M.; Ciupe, V.; Carabas, I.; Margineanu, D.; Maniu, I.; Dehelean, N.

    The European project thinkMOTION works on the purpose of retrieving all-times content regarding mechanisms and machine science by means of creating a digital library, accessible to a broad public through the portal Europeana. DMG-Lib is intended to display the development in the field, from its very beginning up to now days. There is a large range of significant objects available, physically very heterogeneous and needing all to be digitized. The paper presents the workflow, the equipments and specific techniques used in digitization of documents featuring very different characteristics (size, texture, color, degree of preservation, resolution and so on). Once the workflow established on very detailed steps, the development of the workstation is treated. Special equipments designed and assembled at Universitatea "Politehnica" Timisoara are presented. A large series of software applications, including original programs, work for digitization itself, processing of images, management of files, automatic optoelectronic control of capture, storage of information in different stages of processing. An illustrating example is explained, showing the steps followed in order to obtain a clear, high-resolution image from an old original document (very valuable as a historical proof but very poor in quality regarding clarity, contrast and resolution).

  19. Molecular nutrition research: the modern way of performing nutritional science.

    Science.gov (United States)

    Norheim, Frode; Gjelstad, Ingrid Merethe Fange; Hjorth, Marit; Vinknes, Kathrine J; Langleite, Torgrim M; Holen, Torgeir; Jensen, Jørgen; Dalen, Knut Tomas; Karlsen, Anette S; Kielland, Anders; Rustan, Arild C; Drevon, Christian A

    2012-12-03

    In spite of amazing progress in food supply and nutritional science, and a striking increase in life expectancy of approximately 2.5 months per year in many countries during the previous 150 years, modern nutritional research has a great potential of still contributing to improved health for future generations, granted that the revolutions in molecular and systems technologies are applied to nutritional questions. Descriptive and mechanistic studies using state of the art epidemiology, food intake registration, genomics with single nucleotide polymorphisms (SNPs) and epigenomics, transcriptomics, proteomics, metabolomics, advanced biostatistics, imaging, calorimetry, cell biology, challenge tests (meals, exercise, etc.), and integration of all data by systems biology, will provide insight on a much higher level than today in a field we may name molecular nutrition research. To take advantage of all the new technologies scientists should develop international collaboration and gather data in large open access databases like the suggested Nutritional Phenotype database (dbNP). This collaboration will promote standardization of procedures (SOP), and provide a possibility to use collected data in future research projects. The ultimate goals of future nutritional research are to understand the detailed mechanisms of action for how nutrients/foods interact with the body and thereby enhance health and treat diet-related diseases.

  20. Comparison of combinatorial clustering methods on pharmacological data sets represented by machine learning-selected real molecular descriptors.

    Science.gov (United States)

    Rivera-Borroto, Oscar Miguel; Marrero-Ponce, Yovani; García-de la Vega, José Manuel; Grau-Ábalo, Ricardo del Corazón

    2011-12-27

    Cluster algorithms play an important role in diversity related tasks of modern chemoinformatics, with the widest applications being in pharmaceutical industry drug discovery programs. The performance of these grouping strategies depends on various factors such as molecular representation, mathematical method, algorithmical technique, and statistical distribution of data. For this reason, introduction and comparison of new methods are necessary in order to find the model that best fits the problem at hand. Earlier comparative studies report on Ward's algorithm using fingerprints for molecular description as generally superior in this field. However, problems still remain, i.e., other types of numerical descriptions have been little exploited, current descriptors selection strategy is trial and error-driven, and no previous comparative studies considering a broader domain of the combinatorial methods in grouping chemoinformatic data sets have been conducted. In this work, a comparison between combinatorial methods is performed,with five of them being novel in cheminformatics. The experiments are carried out using eight data sets that are well established and validated in the medical chemistry literature. Each drug data set was represented by real molecular descriptors selected by machine learning techniques, which are consistent with the neighborhood principle. Statistical analysis of the results demonstrates that pharmacological activities of the eight data sets can be modeled with a few of families with 2D and 3D molecular descriptors, avoiding classification problems associated with the presence of nonrelevant features. Three out of five of the proposed cluster algorithms show superior performance over most classical algorithms and are similar (or slightly superior in the most optimistic sense) to Ward's algorithm. The usefulness of these algorithms is also assessed in a comparative experiment to potent QSAR and machine learning classifiers, where they perform

  1. Science 101: Q--What Is the Physics behind Simple Machines?

    Science.gov (United States)

    Robertson, Bill

    2013-01-01

    Bill Robertson thinks that questioning the physics behind simple machines is a great idea because when he encounters the subject of simple machines in textbooks, activities, and classrooms, he seldom encounters, a scientific explanation of how they work. Instead, what one often sees is a discussion of load, effort, fulcrum, actual mechanical…

  2. Just Working with the Cellular Machine: A High School Game for Teaching Molecular Biology

    Science.gov (United States)

    Cardoso, Fernanda Serpa; Dumpel, Renata; Gomes da Silva, Luisa B.; Rodrigues, Carlos R.; Santos, Dilvani O.; Cabral, Lucio Mendes; Castro, Helena C.

    2008-01-01

    Molecular biology is a difficult comprehension subject due to its high complexity, thus requiring new teaching approaches. Herein, we developed an interdisciplinary board game involving the human immune system response against a bacterial infection for teaching molecular biology at high school. Initially, we created a database with several…

  3. Molecular metal catalysts on supports: organometallic chemistry meets surface science.

    Science.gov (United States)

    Serna, Pedro; Gates, Bruce C

    2014-08-19

    -support bonding and structure, which identify the supports as ligands with electron-donor properties that influence reactivity and catalysis. Each of the catalyst design variables has been varied independently, illustrated by mononuclear and tetranuclear iridium on zeolite HY and on MgO and by isostructural rhodium and iridium (diethylene or dicarbonyl) complexes on these supports. The data provide examples resolving the roles of the catalyst design variables and place the catalysis science on a firm foundation of organometallic chemistry linked with surface science. Supported molecular catalysts offer the advantages of characterization in the absence of solvents and with surface-science methods that do not require ultrahigh vacuum. Families of supported metal complexes have been made by replacement of ligands with others from the gas phase. Spectroscopically identified catalytic reaction intermediates help to elucidate catalyst performance and guide design. The methods are illustrated for supported complexes and clusters of rhodium, iridium, osmium, and gold used to catalyze reactions of small molecules that facilitate identification of the ligands present during catalysis: alkene dimerization and hydrogenation, H-D exchange in the reaction of H2 with D2, and CO oxidation. The approach is illustrated with the discovery of a highly active and selective MgO-supported rhodium carbonyl dimer catalyst for hydrogenation of 1,3-butadiene to give butenes.

  4. The art and science of rotating field machines design a practical approach

    CERN Document Server

    Ostović, Vlado

    2017-01-01

    This book highlights procedures utilized by the design departments of leading global manufacturers, offering readers essential insights into the electromagnetic and thermal design of rotating field (induction and synchronous) electric machines. Further, it details the physics of the key phenomena involved in the machines’ operation, conducts a thorough analysis and synthesis of polyphase windings, and presents the tools and methods used in the evaluation of winding performance. The book develops and solves the machines’ magnetic circuits, and determines their electromagnetic forces and torques. Special attention is paid to thermal problems in electrical machines, along with fluid flow computations. With a clear emphasis on the practical aspects of electric machine design and synthesis, the author applies his nearly 40 years of professional experience with electric machine manufacturers – both as an employee and consultant – to provide readers with the tools they need to determine fluid flow parameters...

  5. Machine Learning

    CERN Multimedia

    CERN. Geneva

    2017-01-01

    Machine learning, which builds on ideas in computer science, statistics, and optimization, focuses on developing algorithms to identify patterns and regularities in data, and using these learned patterns to make predictions on new observations. Boosted by its industrial and commercial applications, the field of machine learning is quickly evolving and expanding. Recent advances have seen great success in the realms of computer vision, natural language processing, and broadly in data science. Many of these techniques have already been applied in particle physics, for instance for particle identification, detector monitoring, and the optimization of computer resources. Modern machine learning approaches, such as deep learning, are only just beginning to be applied to the analysis of High Energy Physics data to approach more and more complex problems. These classes will review the framework behind machine learning and discuss recent developments in the field.

  6. Analysis of machining and machine tools

    CERN Document Server

    Liang, Steven Y

    2016-01-01

    This book delivers the fundamental science and mechanics of machining and machine tools by presenting systematic and quantitative knowledge in the form of process mechanics and physics. It gives readers a solid command of machining science and engineering, and familiarizes them with the geometry and functionality requirements of creating parts and components in today’s markets. The authors address traditional machining topics, such as: single and multiple point cutting processes grinding components accuracy and metrology shear stress in cutting cutting temperature and analysis chatter They also address non-traditional machining, such as: electrical discharge machining electrochemical machining laser and electron beam machining A chapter on biomedical machining is also included. This book is appropriate for advanced undergraduate and graduate mechani cal engineering students, manufacturing engineers, and researchers. Each chapter contains examples, exercises and their solutions, and homework problems that re...

  7. ISIS muons for materials and molecular science studies

    International Nuclear Information System (INIS)

    King, Philip J C; Cottrell, Stephen P; Hillier, Adrian D; Cox, Stephen F J; De Renzi, Roberto

    2013-01-01

    This paper marks the first 25 years of muon production at ISIS and the creation in that time of a facility dedicated to the use of these elementary particles as unique microscopic probes in condensed matter and molecular science. It introduces the basic techniques of muon spin rotation, relaxation and resonance, collectively known as μSR, that were already in use by specialist groups at other accelerator labs by the mid-1980s. It describes how these techniques have been implemented and made available at ISIS, beginning in 1987, and how they have evolved and improved since then. Ever widening applications embrace magnetism, superconductivity, interstitial diffusion and charge transport, semiconductors and dielectrics, chemical physics and radical chemistry. Over these first 25 years, a fully supported user facility has been established, open to all academic and industrial users. It presently comprises four scheduled instruments, optimized for different types of measurement, together with auxiliary equipment for radiofrequency or microwave spin manipulation and future plans for pump–probe laser excitation. (comment)

  8. Molecular Formula and Molecular Weight - NBDC NikkajiRDF | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available List Contact us NBDC NikkajiRDF Molecular Formula and Molecular Weight Data detail Data name Molecular Formula and Molecul...- Description of data contents This RDF data includes molecular formula and molecular weight of chemical sub...ikkajiRDF_MFMW.tar.gz File size: 404 MB Simple search URL - Data acquisition method The data was converted from data of molecul...ar formulas and molecular weights in Basic Information ( http://dbarchive.biosciencedbc.j... Policy | Contact Us Molecular Formula and Molecular Weight - NBDC NikkajiRDF | LSDB Archive ...

  9. Issues on machine learning for prediction of classes among molecular sequences of plants and animals

    Science.gov (United States)

    Stehlik, Milan; Pant, Bhasker; Pant, Kumud; Pardasani, K. R.

    2012-09-01

    Nowadays major laboratories of the world are turning towards in-silico experimentation due to their ease, reproducibility and accuracy. The ethical issues concerning wet lab experimentations are also minimal in in-silico experimentations. But before we turn fully towards dry lab simulations it is necessary to understand the discrepancies and bottle necks involved with dry lab experimentations. It is necessary before reporting any result using dry lab simulations to perform in-depth statistical analysis of the data. Keeping same in mind here we are presenting a collaborative effort to correlate findings and results of various machine learning algorithms and checking underlying regressions and mutual dependencies so as to develop an optimal classifier and predictors.

  10. Science Academies' Refresher Course on Advances in Molecular ...

    Indian Academy of Sciences (India)

    microRNAs, Ribozyme; molecular oncology; Genes in development and differentiation; Epigenetics and gene regulation; molecular biology of viruses; Restriction enzymes and modifications; Ge- netic engineering; Neurobiology; Bioinformatics- structural, functional and comparative genomics;. Metagenomics; Genome ...

  11. Mesoscale Simulation and Machine Learning of Asphaltene Aggregation Phase Behavior and Molecular Assembly Landscapes.

    Science.gov (United States)

    Wang, Jiang; Gayatri, Mohit A; Ferguson, Andrew L

    2017-05-11

    Asphaltenes constitute the heaviest fraction of the aromatic group in crude oil. Aggregation and precipitation of asphaltenes during petroleum processing costs the petroleum industry billions of dollars each year due to downtime and production inefficiencies. Asphaltene aggregation proceeds via a hierarchical self-assembly process that is well-described by the Yen-Mullins model. Nevertheless, the microscopic details of the emergent cluster morphologies and their relative stability under different processing conditions remain poorly understood. We perform coarse-grained molecular dynamics simulations of a prototypical asphaltene molecule to establish a phase diagram mapping the self-assembled morphologies as a function of temperature, pressure, and n-heptane:toluene solvent ratio informing how to control asphaltene aggregation by regulating external processing conditions. We then combine our simulations with graph matching and nonlinear manifold learning to determine low-dimensional free energy surfaces governing asphaltene self-assembly. In doing so, we introduce a variant of diffusion maps designed to handle data sets with large local density variations, and report the first application of many-body diffusion maps to molecular self-assembly to recover a pseudo-1D free energy landscape. Increasing pressure only weakly affects the landscape, serving only to destabilize the largest aggregates. Increasing temperature and toluene solvent fraction stabilizes small cluster sizes and loose bonding arrangements. Although the underlying molecular mechanisms differ, the strikingly similar effect of these variables on the free energy landscape suggests that toluene acts upon asphaltene self-assembly as an effective temperature.

  12. Recognizing molecular patterns by machine learning: An agnostic structural definition of the hydrogen bond

    International Nuclear Information System (INIS)

    Gasparotto, Piero; Ceriotti, Michele

    2014-01-01

    The concept of chemical bonding can ultimately be seen as a rationalization of the recurring structural patterns observed in molecules and solids. Chemical intuition is nothing but the ability to recognize and predict such patterns, and how they transform into one another. Here, we discuss how to use a computer to identify atomic patterns automatically, so as to provide an algorithmic definition of a bond based solely on structural information. We concentrate in particular on hydrogen bonding – a central concept to our understanding of the physical chemistry of water, biological systems, and many technologically important materials. Since the hydrogen bond is a somewhat fuzzy entity that covers a broad range of energies and distances, many different criteria have been proposed and used over the years, based either on sophisticate electronic structure calculations followed by an energy decomposition analysis, or on somewhat arbitrary choices of a range of structural parameters that is deemed to correspond to a hydrogen-bonded configuration. We introduce here a definition that is univocal, unbiased, and adaptive, based on our machine-learning analysis of an atomistic simulation. The strategy we propose could be easily adapted to similar scenarios, where one has to recognize or classify structural patterns in a material or chemical compound

  13. Recognizing molecular patterns by machine learning: An agnostic structural definition of the hydrogen bond

    Energy Technology Data Exchange (ETDEWEB)

    Gasparotto, Piero; Ceriotti, Michele, E-mail: michele.ceriotti@epfl.ch [Laboratory of Computational Science and Modeling, and National Center for Computational Design and Discovery of Novel Materials MARVEL, IMX, École Polytechnique Fédérale de Lausanne, 1015 Lausanne (Switzerland)

    2014-11-07

    The concept of chemical bonding can ultimately be seen as a rationalization of the recurring structural patterns observed in molecules and solids. Chemical intuition is nothing but the ability to recognize and predict such patterns, and how they transform into one another. Here, we discuss how to use a computer to identify atomic patterns automatically, so as to provide an algorithmic definition of a bond based solely on structural information. We concentrate in particular on hydrogen bonding – a central concept to our understanding of the physical chemistry of water, biological systems, and many technologically important materials. Since the hydrogen bond is a somewhat fuzzy entity that covers a broad range of energies and distances, many different criteria have been proposed and used over the years, based either on sophisticate electronic structure calculations followed by an energy decomposition analysis, or on somewhat arbitrary choices of a range of structural parameters that is deemed to correspond to a hydrogen-bonded configuration. We introduce here a definition that is univocal, unbiased, and adaptive, based on our machine-learning analysis of an atomistic simulation. The strategy we propose could be easily adapted to similar scenarios, where one has to recognize or classify structural patterns in a material or chemical compound.

  14. Recognizing molecular patterns by machine learning: An agnostic structural definition of the hydrogen bond

    Science.gov (United States)

    Gasparotto, Piero; Ceriotti, Michele

    2014-11-01

    The concept of chemical bonding can ultimately be seen as a rationalization of the recurring structural patterns observed in molecules and solids. Chemical intuition is nothing but the ability to recognize and predict such patterns, and how they transform into one another. Here, we discuss how to use a computer to identify atomic patterns automatically, so as to provide an algorithmic definition of a bond based solely on structural information. We concentrate in particular on hydrogen bonding - a central concept to our understanding of the physical chemistry of water, biological systems, and many technologically important materials. Since the hydrogen bond is a somewhat fuzzy entity that covers a broad range of energies and distances, many different criteria have been proposed and used over the years, based either on sophisticate electronic structure calculations followed by an energy decomposition analysis, or on somewhat arbitrary choices of a range of structural parameters that is deemed to correspond to a hydrogen-bonded configuration. We introduce here a definition that is univocal, unbiased, and adaptive, based on our machine-learning analysis of an atomistic simulation. The strategy we propose could be easily adapted to similar scenarios, where one has to recognize or classify structural patterns in a material or chemical compound.

  15. Body_Machine? Encounters of the Human and the Mechanical in Education, Industry and Science

    Science.gov (United States)

    Herman, Frederik; Priem, Karin; Thyssen, Geert

    2017-01-01

    This paper unveils the body_machine as a key element of dynamic mental maps that have come to shape both educational praxis and research. It traces and analyses instances in which the human and the mechanical encountered each other in metaphorical, material and visual forms, thereby blurring to some extent the boundaries between them while…

  16. Molecular Machines Determining the Fate of Endocytosed Synaptic Vesicles in Nerve Terminals.

    Science.gov (United States)

    Fassio, Anna; Fadda, Manuela; Benfenati, Fabio

    2016-01-01

    The cycle of a synaptic vesicle (SV) within the nerve terminal is a step-by-step journey with the final goal of ensuring the proper synaptic strength under changing environmental conditions. The SV cycle is a precisely regulated membrane traffic event in cells and, because of this, a plethora of membrane-bound and cytosolic proteins are devoted to assist SVs in each step of the journey. The cycling fate of endocytosed SVs determines both the availability for subsequent rounds of release and the lifetime of SVs in the terminal and is therefore crucial for synaptic function and plasticity. Molecular players that determine the destiny of SVs in nerve terminals after a round of exo-endocytosis are largely unknown. Here we review the functional role in SV fate of phosphorylation/dephosphorylation of SV proteins and of small GTPases acting on membrane trafficking at the synapse, as they are emerging as key molecules in determining the recycling route of SVs within the nerve terminal. In particular, we focus on: (i) the cyclin-dependent kinase-5 (cdk5) and calcineurin (CN) control of the recycling pool of SVs; (ii) the role of small GTPases of the Rab and ADP-ribosylation factor (Arf) families in defining the route followed by SV in their nerve terminal cycle. These regulatory proteins together with their synaptic regulators and effectors, are molecular nanomachines mediating homeostatic responses in synaptic plasticity and potential targets of drugs modulating the efficiency of synaptic transmission.

  17. MOLECULAR MACHINES DETERMINING THE FATE OF ENDOCYTOSED SYNAPTIC VESICLES IN NERVE TERMINALS

    Directory of Open Access Journals (Sweden)

    Anna eFassio

    2016-05-01

    Full Text Available The cycle of a synaptic vesicle (SV within the nerve terminal is a step-by-step journey with the final goal of ensuring the proper synaptic strength under changing environmental conditions.The SV cycle is a precisely regulated membrane traffic event in cells and, because of this, a plethora of membrane-bound and cytosolic proteins are devoted to assist SVs in each step of the journey. The cycling fate of endocytosed SVs determines both the availability for subsequent rounds of release and the lifetime of SVs in the terminal and is therefore crucial for synaptic function and plasticity. Molecular players that determine the destiny of SVs in nerve terminals after a round of exo-endocytosis are largely unknown. Here we review the functional role in SV fate of phosphorylation/dephosphorylation of SV proteins and of small GTPases acting on membrane trafficking at the synapse, as they are emerging as key molecules in determining the recycling route of SVs within the nerve terminal. In particular, we focus on (i the cyclin-dependent kinase-5 and calcineurin control of the recycling pool of SVs; (ii the role of small GTPases of the Rab and ADP-ribosylation factor (Arf families in defining the route followed by SV in their nerve terminal cycle. These regulatory proteins together with their synaptic regulators and effectors, are molecular nanomachines mediating homeostatic responses in synaptic plasticity and potential targets of drugs modulating the efficiency of synaptic transmission.

  18. Announcing the International Journal of Molecular Sciences Junior Scientists Travel Awards 2016

    Directory of Open Access Journals (Sweden)

    International Journal of Molecular Sciences Editorial Office

    2016-03-01

    Full Text Available With the goal of recognizing outstanding contributions to the field of molecular sciences by early-career investigators, including assistant professors, postdoctoral students and PhD students, [...

  19. Fast plane wave density functional theory molecular dynamics calculations on multi-GPU machines

    International Nuclear Information System (INIS)

    Jia, Weile; Fu, Jiyun; Cao, Zongyan; Wang, Long; Chi, Xuebin; Gao, Weiguo; Wang, Lin-Wang

    2013-01-01

    Plane wave pseudopotential (PWP) density functional theory (DFT) calculation is the most widely used method for material simulations, but its absolute speed stagnated due to the inability to use large scale CPU based computers. By a drastic redesign of the algorithm, and moving all the major computation parts into GPU, we have reached a speed of 12 s per molecular dynamics (MD) step for a 512 atom system using 256 GPU cards. This is about 20 times faster than the CPU version of the code regardless of the number of CPU cores used. Our tests and analysis on different GPU platforms and configurations shed lights on the optimal GPU deployments for PWP-DFT calculations. An 1800 step MD simulation is used to study the liquid phase properties of GaInP

  20. Synthesis of a pH-Sensitive Hetero[4]Rotaxane Molecular Machine that Combines [c2]Daisy and [2]Rotaxane Arrangements.

    Science.gov (United States)

    Waelès, Philip; Riss-Yaw, Benjamin; Coutrot, Frédéric

    2016-05-10

    The synthesis of a novel pH-sensitive hetero[4]rotaxane molecular machine through a self-sorting strategy is reported. The original tetra-interlocked molecular architecture combines a [c2]daisy chain scaffold linked to two [2]rotaxane units. Actuation of the system through pH variation is possible thanks to the specific interactions of the dibenzo-24-crown-8 (DB24C8) macrocycles for ammonium, anilinium, and triazolium molecular stations. Selective deprotonation of the anilinium moieties triggers shuttling of the unsubstituted DB24C8 along the [2]rotaxane units. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. Application of support vector machine to three-dimensional shape-based virtual screening using comprehensive three-dimensional molecular shape overlay with known inhibitors.

    Science.gov (United States)

    Sato, Tomohiro; Yuki, Hitomi; Takaya, Daisuke; Sasaki, Shunta; Tanaka, Akiko; Honma, Teruki

    2012-04-23

    In this study, machine learning using support vector machine was combined with three-dimensional (3D) molecular shape overlay, to improve the screening efficiency. Since the 3D molecular shape overlay does not use fingerprints or descriptors to compare two compounds, unlike 2D similarity methods, the application of machine learning to a 3D shape-based method has not been extensively investigated. The 3D similarity profile of a compound is defined as the array of 3D shape similarities with multiple known active compounds of the target protein and is used as the explanatory variable of support vector machine. As the measures of 3D shape similarity for our new prediction models, the prediction performances of the 3D shape similarity metrics implemented in ROCS, such as ShapeTanimoto and ScaledColor, were validated, using the known inhibitors of 15 target proteins derived from the ChEMBL database. The learning models based on the 3D similarity profiles stably outperformed the original ROCS when more than 10 known inhibitors were available as the queries. The results demonstrated the advantages of combining machine learning with the 3D similarity profile to process the 3D shape information of plural active compounds.

  2. Molecular Gastronomy: A Food Fad or an Interface for Science-based Cooking?

    NARCIS (Netherlands)

    Linden, van der E.; McClements, D.J.; Ubbink, J.

    2008-01-01

    A review is given over the field of molecular gastronomy and its relation to science and cooking. We begin with a brief history of the field of molecular gastronomy, the definition of the term itself, and the current controversy surrounding this term. We then highlight the distinction between

  3. Educational challenges of molecular life science: Characteristics and implications for education and research.

    Science.gov (United States)

    Tibell, Lena A E; Rundgren, Carl-Johan

    2010-01-01

    Molecular life science is one of the fastest-growing fields of scientific and technical innovation, and biotechnology has profound effects on many aspects of daily life-often with deep, ethical dimensions. At the same time, the content is inherently complex, highly abstract, and deeply rooted in diverse disciplines ranging from "pure sciences," such as math, chemistry, and physics, through "applied sciences," such as medicine and agriculture, to subjects that are traditionally within the remit of humanities, notably philosophy and ethics. Together, these features pose diverse, important, and exciting challenges for tomorrow's teachers and educational establishments. With backgrounds in molecular life science research and secondary life science teaching, we (Tibell and Rundgren, respectively) bring different experiences, perspectives, concerns, and awareness of these issues. Taking the nature of the discipline as a starting point, we highlight important facets of molecular life science that are both characteristic of the domain and challenging for learning and education. Of these challenges, we focus most detail on content, reasoning difficulties, and communication issues. We also discuss implications for education research and teaching in the molecular life sciences.

  4. Geospatial and machine learning techniques for wicked social science problems: analysis of crash severity on a regional highway corridor

    Science.gov (United States)

    Effati, Meysam; Thill, Jean-Claude; Shabani, Shahin

    2015-04-01

    The contention of this paper is that many social science research problems are too "wicked" to be suitably studied using conventional statistical and regression-based methods of data analysis. This paper argues that an integrated geospatial approach based on methods of machine learning is well suited to this purpose. Recognizing the intrinsic wickedness of traffic safety issues, such approach is used to unravel the complexity of traffic crash severity on highway corridors as an example of such problems. The support vector machine (SVM) and coactive neuro-fuzzy inference system (CANFIS) algorithms are tested as inferential engines to predict crash severity and uncover spatial and non-spatial factors that systematically relate to crash severity, while a sensitivity analysis is conducted to determine the relative influence of crash severity factors. Different specifications of the two methods are implemented, trained, and evaluated against crash events recorded over a 4-year period on a regional highway corridor in Northern Iran. Overall, the SVM model outperforms CANFIS by a notable margin. The combined use of spatial analysis and artificial intelligence is effective at identifying leading factors of crash severity, while explicitly accounting for spatial dependence and spatial heterogeneity effects. Thanks to the demonstrated effectiveness of a sensitivity analysis, this approach produces comprehensive results that are consistent with existing traffic safety theories and supports the prioritization of effective safety measures that are geographically targeted and behaviorally sound on regional highway corridors.

  5. Molecular mass spectrometry imaging in biomedical and life science research

    Czech Academy of Sciences Publication Activity Database

    Pól, Jaroslav; Strohalm, Martin; Havlíček, Vladimír; Volný, Michael

    2010-01-01

    Roč. 134, č. 5 (2010), s. 423-443 ISSN 0948-6143 R&D Projects: GA MŠk LC545; GA ČR GPP206/10/P018 Institutional research plan: CEZ:AV0Z50200510 Keywords : Mass spectrometry * Chemical imaging * Molecular imaging Subject RIV: EE - Microbiology, Virology Impact factor: 4.727, year: 2010

  6. Ultrafast phenomena in molecular sciences femtosecond physics and chemistry

    CERN Document Server

    Bañares, Luis

    2014-01-01

    This book presents the latest developments in Femtosecond Chemistry and Physics for the study of ultrafast photo-induced molecular processes. Molecular systems, from the simplest H2 molecule to polymers or biological macromolecules, constitute central objects of interest for Physics, Chemistry and Biology, and despite the broad range of phenomena that they exhibit, they share some common behaviors. One of the most significant of those is that many of the processes involving chemical transformation (nuclear reorganization, bond breaking, bond making) take place in an extraordinarily short time, in or around the femtosecond temporal scale (1 fs = 10-15 s). A number of experimental approaches - very particularly the developments in the generation and manipulation of ultrashort laser pulses - coupled with theoretical progress, provide the ultrafast scientist with powerful tools to understand matter and its interaction with light, at this spatial and temporal scale. This book is an attempt to reunite some of the ...

  7. Gravity Spy: integrating advanced LIGO detector characterization, machine learning, and citizen science

    Science.gov (United States)

    Zevin, M; Coughlin, S; Bahaadini, S; Besler, E; Rohani, N; Allen, S; Cabero, M; Crowston, K; Katsaggelos, A K; Larson, S L; Lee, T K; Lintott, C; Littenberg, T B; Lundgren, A; Østerlund, C; Smith, J R; Trouille, L; Kalogera, V

    2018-01-01

    With the first direct detection of gravitational waves, the advanced laser interferometer gravitational-wave observatory (LIGO) has initiated a new field of astronomy by providing an alternative means of sensing the universe. The extreme sensitivity required to make such detections is achieved through exquisite isolation of all sensitive components of LIGO from non-gravitational-wave disturbances. Nonetheless, LIGO is still susceptible to a variety of instrumental and environmental sources of noise that contaminate the data. Of particular concern are noise features known as glitches, which are transient and non-Gaussian in their nature, and occur at a high enough rate so that accidental coincidence between the two LIGO detectors is non-negligible. Glitches come in a wide range of time-frequency-amplitude morphologies, with new morphologies appearing as the detector evolves. Since they can obscure or mimic true gravitational-wave signals, a robust characterization of glitches is paramount in the effort to achieve the gravitational-wave detection rates that are predicted by the design sensitivity of LIGO. This proves a daunting task for members of the LIGO Scientific Collaboration alone due to the sheer amount of data. In this paper we describe an innovative project that combines crowdsourcing with machine learning to aid in the challenging task of categorizing all of the glitches recorded by the LIGO detectors. Through the Zooniverse platform, we engage and recruit volunteers from the public to categorize images of time-frequency representations of glitches into pre-identified morphological classes and to discover new classes that appear as the detectors evolve. In addition, machine learning algorithms are used to categorize images after being trained on human-classified examples of the morphological classes. Leveraging the strengths of both classification methods, we create a combined method with the aim of improving the efficiency and accuracy of each individual

  8. Gravity Spy: integrating advanced LIGO detector characterization, machine learning, and citizen science

    International Nuclear Information System (INIS)

    Zevin, M; Coughlin, S; Larson, S L; Trouille, L; Kalogera, V; Bahaadini, S; Besler, E; Rohani, N; Katsaggelos, A K; Allen, S; Cabero, M; Lundgren, A; Crowston, K; Østerlund, C; Lee, T K; Lintott, C; Littenberg, T B; Smith, J R

    2017-01-01

    With the first direct detection of gravitational waves, the advanced laser interferometer gravitational-wave observatory (LIGO) has initiated a new field of astronomy by providing an alternative means of sensing the universe. The extreme sensitivity required to make such detections is achieved through exquisite isolation of all sensitive components of LIGO from non-gravitational-wave disturbances. Nonetheless, LIGO is still susceptible to a variety of instrumental and environmental sources of noise that contaminate the data. Of particular concern are noise features known as glitches , which are transient and non-Gaussian in their nature, and occur at a high enough rate so that accidental coincidence between the two LIGO detectors is non-negligible. Glitches come in a wide range of time-frequency-amplitude morphologies, with new morphologies appearing as the detector evolves. Since they can obscure or mimic true gravitational-wave signals, a robust characterization of glitches is paramount in the effort to achieve the gravitational-wave detection rates that are predicted by the design sensitivity of LIGO. This proves a daunting task for members of the LIGO Scientific Collaboration alone due to the sheer amount of data. In this paper we describe an innovative project that combines crowdsourcing with machine learning to aid in the challenging task of categorizing all of the glitches recorded by the LIGO detectors. Through the Zooniverse platform, we engage and recruit volunteers from the public to categorize images of time-frequency representations of glitches into pre-identified morphological classes and to discover new classes that appear as the detectors evolve. In addition, machine learning algorithms are used to categorize images after being trained on human-classified examples of the morphological classes. Leveraging the strengths of both classification methods, we create a combined method with the aim of improving the efficiency and accuracy of each individual

  9. What Makes You Tick? An Empirical Study of Space Science Related Social Media Communications Using Machine Learning

    Science.gov (United States)

    Hwong, Y. L.; Oliver, C.; Van Kranendonk, M. J.

    2016-12-01

    The rise of social media has transformed the way the public engages with scientists and science organisations. `Retweet', `Like', `Share' and `Comment' are a few ways users engage with messages on Twitter and Facebook, two of the most popular social media platforms. Despite the availability of big data from these digital footprints, research into social media science communication is scant. This paper presents the results of an empirical study into the processes and outcomes of space science related social media communications using machine learning. The study is divided into two main parts. The first part is dedicated to the use of supervised learning methods to investigate the features of highly engaging messages., e.g. highly retweeted tweets and shared Facebook posts. It is hypothesised that these messages contain certain psycholinguistic features that are unique to the field of space science. We built a predictive model to forecast the engagement levels of social media posts. By using four feature sets (n-grams, psycholinguistics, grammar and social media), we were able to achieve prediction accuracies in the vicinity of 90% using three supervised learning algorithms (Naive Bayes, linear classifier and decision tree). We conducted the same experiments on social media messages from three other fields (politics, business and non-profit) and discovered several features that are exclusive to space science communications: anger, authenticity, hashtags, visual descriptions and a tentative tone. The second part of the study focuses on the extraction of topics from a corpus of texts using topic modelling. This part of the study is exploratory in nature and uses an unsupervised method called Latent Dirichlet Allocation (LDA) to uncover previously unknown topics within a large body of documents. Preliminary results indicate a strong potential of topic model algorithms to automatically uncover themes hidden within social media chatters on space related issues, with

  10. ClimateNet: A Machine Learning dataset for Climate Science Research

    Science.gov (United States)

    Prabhat, M.; Biard, J.; Ganguly, S.; Ames, S.; Kashinath, K.; Kim, S. K.; Kahou, S.; Maharaj, T.; Beckham, C.; O'Brien, T. A.; Wehner, M. F.; Williams, D. N.; Kunkel, K.; Collins, W. D.

    2017-12-01

    Deep Learning techniques have revolutionized commercial applications in Computer vision, speech recognition and control systems. The key for all of these developments was the creation of a curated, labeled dataset ImageNet, for enabling multiple research groups around the world to develop methods, benchmark performance and compete with each other. The success of Deep Learning can be largely attributed to the broad availability of this dataset. Our empirical investigations have revealed that Deep Learning is similarly poised to benefit the task of pattern detection in climate science. Unfortunately, labeled datasets, a key pre-requisite for training, are hard to find. Individual research groups are typically interested in specialized weather patterns, making it hard to unify, and share datasets across groups and institutions. In this work, we are proposing ClimateNet: a labeled dataset that provides labeled instances of extreme weather patterns, as well as associated raw fields in model and observational output. We develop a schema in NetCDF to enumerate weather pattern classes/types, store bounding boxes, and pixel-masks. We are also working on a TensorFlow implementation to natively import such NetCDF datasets, and are providing a reference convolutional architecture for binary classification tasks. Our hope is that researchers in Climate Science, as well as ML/DL, will be able to use (and extend) ClimateNet to make rapid progress in the application of Deep Learning for Climate Science research.

  11. Relativistic quantum chemistry the fundamental theory of molecular science

    CERN Document Server

    Reiher, Markus

    2014-01-01

    Einstein proposed his theory of special relativity in 1905. For a long time it was believed that this theory has no significant impact on chemistry. This view changed in the 1970s when it was realized that (nonrelativistic) Schrödinger quantum mechanics yields results on molecular properties that depart significantly from experimental results. Especially when heavy elements are involved, these quantitative deviations can be so large that qualitative chemical reasoning and understanding is affected. For this to grasp the appropriate many-electron theory has rapidly evolved. Nowadays relativist

  12. Natural Language Processing (NLP), Machine Learning (ML), and Semantics in Polar Science

    Science.gov (United States)

    Duerr, R.; Ramdeen, S.

    2017-12-01

    One of the interesting features of Polar Science is that it historically has been extremely interdisciplinary, encompassing all of the physical and social sciences. Given the ubiquity of specialized terminology in each field, enabling researchers to find, understand, and use all of the heterogeneous data needed for polar research continues to be a bottleneck. Within the informatics community, semantics has broadly accepted as a solution to these problems, yet progress in developing reusable semantic resources has been slow. The NSF-funded ClearEarth project has been adapting the methods and tools from other communities such as Biomedicine to the Earth sciences with the goal of enhancing progress and the rate at which the needed semantic resources can be created. One of the outcomes of the project has been a better understanding of the differences in the way linguists and physical scientists understand disciplinary text. One example of these differences is the tendency for each discipline and often disciplinary subfields to expend effort in creating discipline specific glossaries where individual terms often are comprised of more than one word (e.g., first-year sea ice). Often each term in a glossary is imbued with substantial contextual or physical meaning - meanings which are rarely explicitly called out within disciplinary texts; meaning which are therefore not immediately accessible to those outside that discipline or subfield; meanings which can often be represented semantically. Here we show how recognition of these difference and the use of glossaries can be used to speed up the annotation processes endemic to NLP, enable inter-community recognition and possible reconciliation of terminology differences. A number of processes and tools will be described, as will progress towards semi-automated generation of ontology structures.

  13. Integration of molecular pathology, epidemiology and social science for global precision medicine.

    Science.gov (United States)

    Nishi, Akihiro; Milner, Danny A; Giovannucci, Edward L; Nishihara, Reiko; Tan, Andy S; Kawachi, Ichiro; Ogino, Shuji

    2016-01-01

    The precision medicine concept and the unique disease principle imply that each patient has unique pathogenic processes resulting from heterogeneous cellular genetic and epigenetic alterations and interactions between cells (including immune cells) and exposures, including dietary, environmental, microbial and lifestyle factors. As a core method field in population health science and medicine, epidemiology is a growing scientific discipline that can analyze disease risk factors and develop statistical methodologies to maximize utilization of big data on populations and disease pathology. The evolving transdisciplinary field of molecular pathological epidemiology (MPE) can advance biomedical and health research by linking exposures to molecular pathologic signatures, enhancing causal inference and identifying potential biomarkers for clinical impact. The MPE approach can be applied to any diseases, although it has been most commonly used in neoplastic diseases (including breast, lung and colorectal cancers) because of availability of various molecular diagnostic tests. However, use of state-of-the-art genomic, epigenomic and other omic technologies and expensive drugs in modern healthcare systems increases racial, ethnic and socioeconomic disparities. To address this, we propose to integrate molecular pathology, epidemiology and social science. Social epidemiology integrates the latter two fields. The integrative social MPE model can embrace sociology, economics and precision medicine, address global health disparities and inequalities, and elucidate biological effects of social environments, behaviors and networks. We foresee advancements of molecular medicine, including molecular diagnostics, biomedical imaging and targeted therapeutics, which should benefit individuals in a global population, by means of an interdisciplinary approach of integrative MPE and social health science.

  14. Molecular catalysis science: Perspective on unifying the fields of catalysis.

    Science.gov (United States)

    Ye, Rong; Hurlburt, Tyler J; Sabyrov, Kairat; Alayoglu, Selim; Somorjai, Gabor A

    2016-05-10

    Colloidal chemistry is used to control the size, shape, morphology, and composition of metal nanoparticles. Model catalysts as such are applied to catalytic transformations in the three types of catalysts: heterogeneous, homogeneous, and enzymatic. Real-time dynamics of oxidation state, coordination, and bonding of nanoparticle catalysts are put under the microscope using surface techniques such as sum-frequency generation vibrational spectroscopy and ambient pressure X-ray photoelectron spectroscopy under catalytically relevant conditions. It was demonstrated that catalytic behavior and trends are strongly tied to oxidation state, the coordination number and crystallographic orientation of metal sites, and bonding and orientation of surface adsorbates. It was also found that catalytic performance can be tuned by carefully designing and fabricating catalysts from the bottom up. Homogeneous and heterogeneous catalysts, and likely enzymes, behave similarly at the molecular level. Unifying the fields of catalysis is the key to achieving the goal of 100% selectivity in catalysis.

  15. Rosalind Franklin and the DNA molecular structure: A case of history of science to learn about the nature of science

    Directory of Open Access Journals (Sweden)

    José Antonio Acevedo-Díaz

    2016-08-01

    Full Text Available The Rosalind Franklin’s case regarding the elucidation of the molecular structure of DNA is presented as an interesting story of the history of science to address a set of questions related to the nature of science (NOS from an explicit and reflective approach. The teaching proposal is aimed to the pre-service teachers training in NOS issues and its didactics. Attention is given to both epistemic and non-epistemic aspects in the narration and the NOS questions asked for reflecting about them. Also, some methodological recommendations for implementing the didactic proposal in science classroom are offered. This involves the follows: (i in small groups, the students read the controversy and respond to some questions on NOS; (ii they present their responses to the whole-class; and (iii they revise their initial responses in light of the whole-class discussion.

  16. Large-Scale Sentinel-1 Processing for Solid Earth Science and Urgent Response using Cloud Computing and Machine Learning

    Science.gov (United States)

    Hua, H.; Owen, S. E.; Yun, S. H.; Agram, P. S.; Manipon, G.; Starch, M.; Sacco, G. F.; Bue, B. D.; Dang, L. B.; Linick, J. P.; Malarout, N.; Rosen, P. A.; Fielding, E. J.; Lundgren, P.; Moore, A. W.; Liu, Z.; Farr, T.; Webb, F.; Simons, M.; Gurrola, E. M.

    2017-12-01

    present some of our findings from applying machine learning and data analytics on the processed SAR data streams. We will also present lessons learned on how to ease the SAR community onto interfacing with these cloud-based SAR science data systems.

  17. Educational Challenges of Molecular Life Science: Characteristics and Implications for Education and Research

    Science.gov (United States)

    Tibell, Lena A. E.; Rundgren, Carl-Johan

    2010-01-01

    Molecular life science is one of the fastest-growing fields of scientific and technical innovation, and biotechnology has profound effects on many aspects of daily life--often with deep, ethical dimensions. At the same time, the content is inherently complex, highly abstract, and deeply rooted in diverse disciplines ranging from "pure…

  18. Data Mining and Machine Learning Tools for Combinatorial Material Science of All-Oxide Photovoltaic Cells.

    Science.gov (United States)

    Yosipof, Abraham; Nahum, Oren E; Anderson, Assaf Y; Barad, Hannah-Noa; Zaban, Arie; Senderowitz, Hanoch

    2015-06-01

    Growth in energy demands, coupled with the need for clean energy, are likely to make solar cells an important part of future energy resources. In particular, cells entirely made of metal oxides (MOs) have the potential to provide clean and affordable energy if their power conversion efficiencies are improved. Such improvements require the development of new MOs which could benefit from combining combinatorial material sciences for producing solar cells libraries with data mining tools to direct synthesis efforts. In this work we developed a data mining workflow and applied it to the analysis of two recently reported solar cell libraries based on Titanium and Copper oxides. Our results demonstrate that QSAR models with good prediction statistics for multiple solar cells properties could be developed and that these models highlight important factors affecting these properties in accord with experimental findings. The resulting models are therefore suitable for designing better solar cells. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. Machine medical ethics

    CERN Document Server

    Pontier, Matthijs

    2015-01-01

    The essays in this book, written by researchers from both humanities and sciences, describe various theoretical and experimental approaches to adding medical ethics to a machine in medical settings. Medical machines are in close proximity with human beings, and getting closer: with patients who are in vulnerable states of health, who have disabilities of various kinds, with the very young or very old, and with medical professionals. In such contexts, machines are undertaking important medical tasks that require emotional sensitivity, knowledge of medical codes, human dignity, and privacy. As machine technology advances, ethical concerns become more urgent: should medical machines be programmed to follow a code of medical ethics? What theory or theories should constrain medical machine conduct? What design features are required? Should machines share responsibility with humans for the ethical consequences of medical actions? How ought clinical relationships involving machines to be modeled? Is a capacity for e...

  20. Quantitative structure–activity relationship model for amino acids as corrosion inhibitors based on the support vector machine and molecular design

    International Nuclear Information System (INIS)

    Zhao, Hongxia; Zhang, Xiuhui; Ji, Lin; Hu, Haixiang; Li, Qianshu

    2014-01-01

    Highlights: • Nonlinear quantitative structure–activity relationship (QSAR) model was built by the support vector machine. • Descriptors for QSAR model were selected by principal component analysis. • Binding energy was taken as one of the descriptors for QSAR model. • Acidic solution and protonation of the inhibitor were considered. - Abstract: The inhibition performance of nineteen amino acids was studied by theoretical methods. The affection of acidic solution and protonation of inhibitor were considered in molecular dynamics simulation and the results indicated that the protonated amino-group was not adsorbed on Fe (1 1 0) surface. Additionally, a nonlinear quantitative structure–activity relationship (QSAR) model was built by the support vector machine. The correlation coefficient was 0.97 and the root mean square error, the differences between predicted and experimental inhibition efficiencies (%), was 1.48. Furthermore, five new amino acids were theoretically designed and their inhibition efficiencies were predicted by the built QSAR model

  1. The Environmental and Molecular Sciences Laboratory project -- Continuous evolution in leadership

    International Nuclear Information System (INIS)

    Knutson, D.E.; McClusky, J.K.

    1994-10-01

    The Environmental and Molecular Sciences Laboratory (EMSL) construction project at Pacific Northwest Laboratory (PNL) in Richland, Washington, is a $230M Major Systems Acquisition for the US Department of Energy (DOE). The completed laboratory will be a national user facility that provides unparalleled capabilities for scientists involved in environmental molecular science research. This project, approved for construction by the Secretary of Energy in October 1993, is underway. The United States is embarking on an environmental cleanup effort that dwarfs previous scientific enterprise. Using current best available technology, the projected costs of cleaning up the tens of thousands of toxic waste sites, including DOE sites, is estimated to exceed one trillion dollars. The present state of scientific knowledge regarding the effects of exogenous chemicals on human biology is very limited. Long term environmental research at the molecular level is needed to resolve the concerns, and form the building blocks for a structure of cost effective process improvement and regulatory reform

  2. The Environmental and Molecular Sciences Laboratory project -- Continuous evolution in leadership

    Energy Technology Data Exchange (ETDEWEB)

    Knutson, D.E.; McClusky, J.K.

    1994-10-01

    The Environmental and Molecular Sciences Laboratory (EMSL) construction project at Pacific Northwest Laboratory (PNL) in Richland, Washington, is a $230M Major Systems Acquisition for the US Department of Energy (DOE). The completed laboratory will be a national user facility that provides unparalleled capabilities for scientists involved in environmental molecular science research. This project, approved for construction by the Secretary of Energy in October 1993, is underway. The United States is embarking on an environmental cleanup effort that dwarfs previous scientific enterprise. Using current best available technology, the projected costs of cleaning up the tens of thousands of toxic waste sites, including DOE sites, is estimated to exceed one trillion dollars. The present state of scientific knowledge regarding the effects of exogenous chemicals on human biology is very limited. Long term environmental research at the molecular level is needed to resolve the concerns, and form the building blocks for a structure of cost effective process improvement and regulatory reform.

  3. Elements in nucleotide sensing and hydrolysis of the AAA+ disaggregation machine ClpB: a structure-based mechanistic dissection of a molecular motor

    Energy Technology Data Exchange (ETDEWEB)

    Zeymer, Cathleen, E-mail: cathleen.zeymer@mpimf-heidelberg.mpg.de; Barends, Thomas R. M.; Werbeck, Nicolas D.; Schlichting, Ilme; Reinstein, Jochen, E-mail: cathleen.zeymer@mpimf-heidelberg.mpg.de [Max Planck Institute for Medical Research, Jahnstrasse 29, 69120 Heidelberg (Germany)

    2014-02-01

    High-resolution crystal structures together with mutational analysis and transient kinetics experiments were utilized to understand nucleotide sensing and the regulation of the ATPase cycle in an AAA+ molecular motor. ATPases of the AAA+ superfamily are large oligomeric molecular machines that remodel their substrates by converting the energy from ATP hydrolysis into mechanical force. This study focuses on the molecular chaperone ClpB, the bacterial homologue of Hsp104, which reactivates aggregated proteins under cellular stress conditions. Based on high-resolution crystal structures in different nucleotide states, mutational analysis and nucleotide-binding kinetics experiments, the ATPase cycle of the C-terminal nucleotide-binding domain (NBD2), one of the motor subunits of this AAA+ disaggregation machine, is dissected mechanistically. The results provide insights into nucleotide sensing, explaining how the conserved sensor 2 motif contributes to the discrimination between ADP and ATP binding. Furthermore, the role of a conserved active-site arginine (Arg621), which controls binding of the essential Mg{sup 2+} ion, is described. Finally, a hypothesis is presented as to how the ATPase activity is regulated by a conformational switch that involves the essential Walker A lysine. In the proposed model, an unusual side-chain conformation of this highly conserved residue stabilizes a catalytically inactive state, thereby avoiding unnecessary ATP hydrolysis.

  4. Improved Prediction of Blood-Brain Barrier Permeability Through Machine Learning with Combined Use of Molecular Property-Based Descriptors and Fingerprints.

    Science.gov (United States)

    Yuan, Yaxia; Zheng, Fang; Zhan, Chang-Guo

    2018-03-21

    Blood-brain barrier (BBB) permeability of a compound determines whether the compound can effectively enter the brain. It is an essential property which must be accounted for in drug discovery with a target in the brain. Several computational methods have been used to predict the BBB permeability. In particular, support vector machine (SVM), which is a kernel-based machine learning method, has been used popularly in this field. For SVM training and prediction, the compounds are characterized by molecular descriptors. Some SVM models were based on the use of molecular property-based descriptors (including 1D, 2D, and 3D descriptors) or fragment-based descriptors (known as the fingerprints of a molecule). The selection of descriptors is critical for the performance of a SVM model. In this study, we aimed to develop a generally applicable new SVM model by combining all of the features of the molecular property-based descriptors and fingerprints to improve the accuracy for the BBB permeability prediction. The results indicate that our SVM model has improved accuracy compared to the currently available models of the BBB permeability prediction.

  5. Elements in nucleotide sensing and hydrolysis of the AAA+ disaggregation machine ClpB: a structure-based mechanistic dissection of a molecular motor

    International Nuclear Information System (INIS)

    Zeymer, Cathleen; Barends, Thomas R. M.; Werbeck, Nicolas D.; Schlichting, Ilme; Reinstein, Jochen

    2014-01-01

    High-resolution crystal structures together with mutational analysis and transient kinetics experiments were utilized to understand nucleotide sensing and the regulation of the ATPase cycle in an AAA+ molecular motor. ATPases of the AAA+ superfamily are large oligomeric molecular machines that remodel their substrates by converting the energy from ATP hydrolysis into mechanical force. This study focuses on the molecular chaperone ClpB, the bacterial homologue of Hsp104, which reactivates aggregated proteins under cellular stress conditions. Based on high-resolution crystal structures in different nucleotide states, mutational analysis and nucleotide-binding kinetics experiments, the ATPase cycle of the C-terminal nucleotide-binding domain (NBD2), one of the motor subunits of this AAA+ disaggregation machine, is dissected mechanistically. The results provide insights into nucleotide sensing, explaining how the conserved sensor 2 motif contributes to the discrimination between ADP and ATP binding. Furthermore, the role of a conserved active-site arginine (Arg621), which controls binding of the essential Mg 2+ ion, is described. Finally, a hypothesis is presented as to how the ATPase activity is regulated by a conformational switch that involves the essential Walker A lysine. In the proposed model, an unusual side-chain conformation of this highly conserved residue stabilizes a catalytically inactive state, thereby avoiding unnecessary ATP hydrolysis

  6. Synthetic small molecules as machines: a chemistry perspective

    Indian Academy of Sciences (India)

    PGhosh

    2017-07-01

    Jul 1, 2017 ... Indian Association for the Cultivation of Science. 2A & 2B Raja S. C. ... Many research groups reported in the 1950s and 1960s that their reaction .... A molecular-level machine can be defined as “an assembly of a distinct ...

  7. A preliminary exploration of Advanced Molecular Bio-Sciences Research Center

    International Nuclear Information System (INIS)

    Yamada, Yutaka; Yanai, Takanori; Onodera, Jun'ichi; Yamagami, Mutsumi; Sakata, Hiroshi; Sota, Masahiro; Takemura, Tatsuo; Koyama, Kenji; Sato, Fumiaki

    2000-01-01

    Low-dose and low-dose-rate radiation effects on life-span, pathological changes, hemopoiesis and cytokine production in experimental animals have been investigated in our laboratory. In the intermediate period of the investigation, an expert committee on radiation biology, which was composed of two task groups, was organized. The purposes of the committee were to assess of previous studies and plan future research for Advanced Molecular Bio-Sciences Research Center (AMBIC). In its report, the committee emphasized the necessity of molecular research in radiation biology and ecology, and proposed six subjects for the research: 1) Molecular carcinogenesis of low-dose radiation; 2) Radiation effects on the immune system and hemopoietic system; 3) Molecular mechanisms of hereditary effect; 4) Non cancer effect of low-dose radiation; 5) Gene targeting for ion transport system in plants; 6) Bioremediation with transgenic plant and bacteria. Exploration of the AMBIC project will continue under the committee's direction. (author)

  8. A preliminary exploration of the advanced molecular bio-sciences research center

    International Nuclear Information System (INIS)

    Yanai, Takanori; Yamada, Yutaka; Tanaka, Kimio; Yamagami, Mutsumi; Sota, Masahiro; Takemura, Tatsuo; Koyama, Kenji; Sato, Fumiaki

    2001-01-01

    Low dose and low dose rate radiation effects on lifespan, pathological changes, hemopoiesis and cytokine production in mice have been investigated in our laboratory. In the intermediate period of the investigation, an expert committee on radiation biology was organized. The purposes of the committee were to assess previous studies and advise on a future research plan for the Advanced Molecular Bio-Sciences Research Center (AMBIC). The committee emphasized the necessity of molecular research in radiation biology, and proposed the following five subjects: 1) molecular carcinogenesis by low dose radiation; 2) radiation effects on the immune and hemopoietic systems; 3) molecular mechanisms of hereditary effect; 4) noncancer diseases of low dose radiation, and 5) cellular mechanisms by low dose radiation. (author)

  9. Cheminformatics Research at the Unilever Centre for Molecular Science Informatics Cambridge.

    Science.gov (United States)

    Fuchs, Julian E; Bender, Andreas; Glen, Robert C

    2015-09-01

    The Centre for Molecular Informatics, formerly Unilever Centre for Molecular Science Informatics (UCMSI), at the University of Cambridge is a world-leading driving force in the field of cheminformatics. Since its opening in 2000 more than 300 scientific articles have fundamentally changed the field of molecular informatics. The Centre has been a key player in promoting open chemical data and semantic access. Though mainly focussing on basic research, close collaborations with industrial partners ensured real world feedback and access to high quality molecular data. A variety of tools and standard protocols have been developed and are ubiquitous in the daily practice of cheminformatics. Here, we present a retrospective of cheminformatics research performed at the UCMSI, thereby highlighting historical and recent trends in the field as well as indicating future directions.

  10. Potato agriculture, late blight science, and the molecularization of plant pathology.

    Science.gov (United States)

    Turner, R Steven

    2008-01-01

    By the mid-1980s nucleic-acid based methods were penetrating the farthest reaches of biological science, triggering rivalries among practitioners, altering relationships among subfields, and transforming the research front. This article delivers a "bottom up" analysis of that transformation at work in one important area of biological science, plant pathology, by tracing the "molecularization" of efforts to understand and control one notorious plant disease -- the late blight of potatoes. It mobilizes the research literature of late blight science as a tool through which to trace the changing typography of the research front from 1983 to 2003. During these years molecularization intensified the traditional fragmentation of the late blight research community, even as it dramatically integrated study of the causal organism into broader areas of biology. In these decades the pathogen responsible for late blight, the oomycete "Phytophthora infestans," was discovered to be undergoing massive, frightening, and still largely unexplained genetic diversification -- a circumstance that lends the episode examined here an urgency that reinforces its historiographical significance as a case-study in the molecularization of the biological sciences.

  11. Report of the workshop on accelerator-based atomic and molecular science

    International Nuclear Information System (INIS)

    Meyerhof, W.E.

    1981-01-01

    This Workshop, held in New London, NH on July 27-30, 1980, had a registration of 43, representing an estimated one-third of all principal investigators in the United States in this research subfield. The workshop was organized into 5 working groups for the purpose of (1) identifying some vital physics problems which experimental and theoretical atomic and molecular science can address with current and projected techniques; (2) establishing facilities and equipment needs required to realize solutions to these problems; (3) formulating suggestions for a coherent national policy concerning this discipline; (4) assessing and projecting the manpower situation; and (5) evaluating the relations of this interdisciplinary science to other fields. Recommedations deal with equipment and operating costs for small accelerator laboratories, especially at universities; instrumentation of ion beam lines dedicated to atomic and molecular science at some large accelerators; development of low-velocity, high charge-state ion sources; synchrotron light sources; improvement or replacement of tandem van de Graaff accelerators; high-energy beam lines for atomic physics; the needs for postdoctoral support in this subfield; new accelerator development; need for representatives from atomic and molecular science on program committees for large national accelerator facilities; and the contributions the field can make to applied physics problems

  12. Integration of Molecular Pathology, Epidemiology, and Social Science for Global Precision Medicine

    Science.gov (United States)

    Nishi, Akihiro; Milner, Danny A; Giovannucci, Edward L.; Nishihara, Reiko; Tan, Andy S.; Kawachi, Ichiro; Ogino, Shuji

    2015-01-01

    Summary The precision medicine concept and the unique disease principle imply that each patient has unique pathogenic processes resulting from heterogeneous cellular genetic and epigenetic alterations, and interactions between cells (including immune cells) and exposures, including dietary, environmental, microbial, and lifestyle factors. As a core method field in population health science and medicine, epidemiology is a growing scientific discipline that can analyze disease risk factors, and develop statistical methodologies to maximize utilization of big data on populations and disease pathology. The evolving transdisciplinary field of molecular pathological epidemiology (MPE) can advance biomedical and health research by linking exposures to molecular pathologic signatures, enhancing causal inference, and identifying potential biomarkers for clinical impact. The MPE approach can be applied to any diseases, although it has been most commonly used in neoplastic diseases (including breast, lung and colorectal cancers) because of availability of various molecular diagnostic tests. However, use of state-of-the-art genomic, epigenomic and other omic technologies and expensive drugs in modern healthcare systems increases racial, ethnic and socioeconomic disparities. To address this, we propose to integrate molecular pathology, epidemiology, and social science. Social epidemiology integrates the latter two fields. The integrative social MPE model can embrace sociology, economics and precision medicine, address global health disparities and inequalities, and elucidate biological effects of social environments, behaviors, and networks. We foresee advancements of molecular medicine, including molecular diagnostics, biomedical imaging, and targeted therapeutics, which should benefit individuals in a global population, by means of an interdisciplinary approach of integrative MPE and social health science. PMID:26636627

  13. Belowground Carbon Cycling Processes at the Molecular Scale: An EMSL Science Theme Advisory Panel Workshop

    Energy Technology Data Exchange (ETDEWEB)

    Hess, Nancy J.; Brown, Gordon E.; Plata, Charity

    2014-02-21

    As part of the Belowground Carbon Cycling Processes at the Molecular Scale workshop, an EMSL Science Theme Advisory Panel meeting held in February 2013, attendees discussed critical biogeochemical processes that regulate carbon cycling in soil. The meeting attendees determined that as a national scientific user facility, EMSL can provide the tools and expertise needed to elucidate the molecular foundation that underlies mechanistic descriptions of biogeochemical processes that control carbon allocation and fluxes at the terrestrial/atmospheric interface in landscape and regional climate models. Consequently, the workshop's goal was to identify the science gaps that hinder either development of mechanistic description of critical processes or their accurate representation in climate models. In part, this report offers recommendations for future EMSL activities in this research area. The workshop was co-chaired by Dr. Nancy Hess (EMSL) and Dr. Gordon Brown (Stanford University).

  14. The Atomic, Molecular and Optical Science instrument at the Linac Coherent Light Source

    Energy Technology Data Exchange (ETDEWEB)

    Ferguson, Ken R. [Linac Coherent Light Source, SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA 94025 (United States); Department of Applied Physics, Stanford University, 348 Via Pueblo, Stanford, CA 94305 (United States); Bucher, Maximilian; Bozek, John D.; Carron, Sebastian; Castagna, Jean-Charles [Linac Coherent Light Source, SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA 94025 (United States); Coffee, Ryan [Linac Coherent Light Source, SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA 94025 (United States); Pulse Institute, Stanford University and SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA 94025 (United States); Curiel, G. Ivan; Holmes, Michael; Krzywinski, Jacek; Messerschmidt, Marc; Minitti, Michael; Mitra, Ankush; Moeller, Stefan; Noonan, Peter; Osipov, Timur; Schorb, Sebastian; Swiggers, Michele; Wallace, Alexander; Yin, Jing [Linac Coherent Light Source, SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA 94025 (United States); Bostedt, Christoph, E-mail: bostedt@slac.stanford.edu [Linac Coherent Light Source, SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA 94025 (United States); Pulse Institute, Stanford University and SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA 94025 (United States)

    2015-04-17

    A description of the Atomic, Molecular and Optical Sciences (AMO) instrument at the Linac Coherent Light Source is presented. Recent scientific highlights illustrate the imaging, time-resolved spectroscopy and high-power density capabilities of the AMO instrument. The Atomic, Molecular and Optical Science (AMO) instrument at the Linac Coherent Light Source (LCLS) provides a tight soft X-ray focus into one of three experimental endstations. The flexible instrument design is optimized for studying a wide variety of phenomena requiring peak intensity. There is a suite of spectrometers and two photon area detectors available. An optional mirror-based split-and-delay unit can be used for X-ray pump–probe experiments. Recent scientific highlights illustrate the imaging, time-resolved spectroscopy and high-power density capabilities of the AMO instrument.

  15. Molecular biology in marine science: Scientific questions, technological approaches, and practical implications

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1994-12-31

    This report describes molecular techniques that could be invaluable in addressing process-oriented problems in the ocean sciences that have perplexed oceanographers for decades, such as understanding the basis for biogeochemical processes, recruitment processes, upper-ocean dynamics, biological impacts of global warming, and ecological impacts of human activities. The coupling of highly sophisticated methods, such as satellite remote sensing, which permits synoptic monitoring of chemical, physical, and biological parameters over large areas, with the power of modern molecular tools for ``ground truthing`` at small scales could allow scientists to address questions about marine organisms and the ocean in which they live that could not be answered previously. Clearly, the marine sciences are on the threshold of an exciting new frontier of scientific discovery and economic opportunity.

  16. Environmental Molecular Sciences Laboratory Operations System: Version 4.0 - system requirements specification

    Energy Technology Data Exchange (ETDEWEB)

    Kashporenko, D.

    1996-07-01

    This document is intended to provide an operations standard for the Environmental Molecular Sciences Laboratory OPerations System (EMSL OPS). It is directed toward three primary audiences: (1) Environmental Molecular Sciences Laboratory (EMSL) facility and operations personnel; (2) laboratory line managers and staff; and (3) researchers, equipment operators, and laboratory users. It is also a statement of system requirements for software developers of EMSL OPS. The need for a finely tuned, superior research environment as provided by the US Department of Energy`s (DOE) Environmental Molecular Sciences Laboratory has never been greater. The abrupt end of the Cold War and the realignment of national priorities caused major US and competing overseas laboratories to reposition themselves in a highly competitive research marketplace. For a new laboratory such as the EMSL, this means coming into existence in a rapidly changing external environment. For any major laboratory, these changes create funding uncertainties and increasing global competition along with concomitant demands for higher standards of research product quality and innovation. While more laboratories are chasing fewer funding dollars, research ideas and proposals, especially for molecular-level research in the materials and biological sciences, are burgeoning. In such an economically constrained atmosphere, reduced costs, improved productivity, and strategic research project portfolio building become essential to establish and maintain any distinct competitive advantage. For EMSL, this environment and these demands require clear operational objectives, specific goals, and a well-crafted strategy. Specific goals will evolve and change with the evolution of the nature and definition of DOE`s environmental research needs. Hence, EMSL OPS is designed to facilitate migration of these changes with ease into every pertinent job function, creating a facile {open_quotes}learning organization.{close_quotes}

  17. Machine learning with R

    CERN Document Server

    Lantz, Brett

    2013-01-01

    Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain insight from your data. Perhaps you already know a bit about machine learning, but have never used R; or

  18. Systems biology for molecular life sciences and its impact in biomedicine.

    Science.gov (United States)

    Medina, Miguel Ángel

    2013-03-01

    Modern systems biology is already contributing to a radical transformation of molecular life sciences and biomedicine, and it is expected to have a real impact in the clinical setting in the next years. In this review, the emergence of systems biology is contextualized with a historic overview, and its present state is depicted. The present and expected future contribution of systems biology to the development of molecular medicine is underscored. Concerning the present situation, this review includes a reflection on the "inflation" of biological data and the urgent need for tools and procedures to make hidden information emerge. Descriptions of the impact of networks and models and the available resources and tools for applying them in systems biology approaches to molecular medicine are provided as well. The actual current impact of systems biology in molecular medicine is illustrated, reviewing two cases, namely, those of systems pharmacology and cancer systems biology. Finally, some of the expected contributions of systems biology to the immediate future of molecular medicine are commented.

  19. Art Advancing Science: Filmmaking Leads to Molecular Insights at the Nanoscale.

    Science.gov (United States)

    Reilly, Charles; Ingber, Donald E

    2017-12-26

    Many have recognized the potential value of facilitating activities that span the art-science interface for the benefit of society; however, there are few examples that demonstrate how pursuit of an artistic agenda can lead to scientific insights. Here, we describe how we set out to produce an entertaining short film depicting the fertilization of the egg by sperm as a parody of a preview for another Star Wars movie to excite the public about science, but ended up developing a simulation tool for multiscale modeling. To produce an aesthetic that communicates mechanical continuity across spatial scales, we developed custom strategies that integrate physics-based animation software from the entertainment industry with molecular dynamics simulation tools, using experimental data from research publications. Using this approach, we were able to depict biological physicality across multiple spatial scales, from how sperm tails move to collective molecular behavior within the axoneme to how the molecular motor, dynein, produces force at the nanometer scale. The dynein simulations, which were validated by replicating results of past simulations and cryo-electron microscopic studies, also predicted a potential mechanism for how ATP hydrolysis drives dynein motion along the microtubule as well as how dynein changes its conformation when it goes through the power stroke. Thus, pursuit of an artistic work led to insights into biology at the nanoscale as well as the development of a highly generalizable modeling and simulation technology that has utility for nanoscience and any other area of scientific investigation that involves analysis of complex multiscale systems.

  20. Machine Shop Grinding Machines.

    Science.gov (United States)

    Dunn, James

    This curriculum manual is one in a series of machine shop curriculum manuals intended for use in full-time secondary and postsecondary classes, as well as part-time adult classes. The curriculum can also be adapted to open-entry, open-exit programs. Its purpose is to equip students with basic knowledge and skills that will enable them to enter the…

  1. Earle K. Plyler Prize Lecture: The Three Pillars of Ultrafast Molecular Science - Time, Phase, Intensity

    Science.gov (United States)

    Stolow, Albert

    polyatomic molecules, including high harmonic generation (HHG). We discuss an experimental method, Channel-Resolved Above Threshold Ionization (CRATI), which directly unveils the electronic channels participating in the attosecond molecular strong field ionization response [10]. This work was supported by the National Research Council of Canada and the Natural Sciences & Engineering Research Council.

  2. Super-Resolution Molecular and Functional Imaging of Nanoscale Architectures in Life and Materials Science

    KAUST Repository

    Habuchi, Satoshi

    2014-06-12

    Super-resolution (SR) fluorescence microscopy has been revolutionizing the way in which we investigate the structures, dynamics, and functions of a wide range of nanoscale systems. In this review, I describe the current state of various SR fluorescence microscopy techniques along with the latest developments of fluorophores and labeling for the SR microscopy. I discuss the applications of SR microscopy in the fields of life science and materials science with a special emphasis on quantitative molecular imaging and nanoscale functional imaging. These studies open new opportunities for unraveling the physical, chemical, and optical properties of a wide range of nanoscale architectures together with their nanostructures and will enable the development of new (bio-)nanotechnology.

  3. Molecular pathological epidemiology of epigenetics: emerging integrative science to analyze environment, host, and disease.

    Science.gov (United States)

    Ogino, Shuji; Lochhead, Paul; Chan, Andrew T; Nishihara, Reiko; Cho, Eunyoung; Wolpin, Brian M; Meyerhardt, Jeffrey A; Meissner, Alexander; Schernhammer, Eva S; Fuchs, Charles S; Giovannucci, Edward

    2013-04-01

    Epigenetics acts as an interface between environmental/exogenous factors, cellular responses, and pathological processes. Aberrant epigenetic signatures are a hallmark of complex multifactorial diseases (including neoplasms and malignancies such as leukemias, lymphomas, sarcomas, and breast, lung, prostate, liver, and colorectal cancers). Epigenetic signatures (DNA methylation, mRNA and microRNA expression, etc) may serve as biomarkers for risk stratification, early detection, and disease classification, as well as targets for therapy and chemoprevention. In particular, DNA methylation assays are widely applied to formalin-fixed, paraffin-embedded archival tissue specimens as clinical pathology tests. To better understand the interplay between etiological factors, cellular molecular characteristics, and disease evolution, the field of 'molecular pathological epidemiology (MPE)' has emerged as an interdisciplinary integration of 'molecular pathology' and 'epidemiology'. In contrast to traditional epidemiological research including genome-wide association studies (GWAS), MPE is founded on the unique disease principle, that is, each disease process results from unique profiles of exposomes, epigenomes, transcriptomes, proteomes, metabolomes, microbiomes, and interactomes in relation to the macroenvironment and tissue microenvironment. MPE may represent a logical evolution of GWAS, termed 'GWAS-MPE approach'. Although epigenome-wide association study attracts increasing attention, currently, it has a fundamental problem in that each cell within one individual has a unique, time-varying epigenome. Having a similar conceptual framework to systems biology, the holistic MPE approach enables us to link potential etiological factors to specific molecular pathology, and gain novel pathogenic insights on causality. The widespread application of epigenome (eg, methylome) analyses will enhance our understanding of disease heterogeneity, epigenotypes (CpG island methylator

  4. Interactive Multimodal Molecular Set – Designing Ludic Engaging Science Learning Content

    DEFF Research Database (Denmark)

    Thorsen, Tine Pinholt; Christiansen, Kasper Holm Bonde; Jakobsen Sillesen, Kristian

    2014-01-01

    This paper reports on an exploratory study investigating 10 primary school students’ interaction with an interactive multimodal molecular set fostering ludic engaging science learning content in primary schools (8th and 9th grade). The concept of the prototype design was to bridge the physical...... and virtual worlds with electronic tags and, through this, blend the familiarity of the computer and toys, to create a tool that provided a ludic approach to learning about atoms and molecules. The study was inspired by the participatory design and informant design methodologies and included design...

  5. Frames of scientific evidence: How journalists represent the (un)certainty of molecular medicine in science television programs.

    Science.gov (United States)

    Ruhrmann, Georg; Guenther, Lars; Kessler, Sabrina Heike; Milde, Jutta

    2015-08-01

    For laypeople, media coverage of science on television is a gateway to scientific issues. Defining scientific evidence is central to the field of science, but there are still questions if news coverage of science represents scientific research findings as certain or uncertain. The framing approach is a suitable framework to classify different media representations; it is applied here to investigate the frames of scientific evidence in film clips (n=207) taken from science television programs. Molecular medicine is the domain of interest for this analysis, due to its high proportion of uncertain and conflicting research findings and risks. The results indicate that television clips vary in their coverage of scientific evidence of molecular medicine. Four frames were found: Scientific Uncertainty and Controversy, Scientifically Certain Data, Everyday Medical Risks, and Conflicting Scientific Evidence. They differ in their way of framing scientific evidence and risks of molecular medicine. © The Author(s) 2013.

  6. On the use of Cloud Computing and Machine Learning for Large-Scale SAR Science Data Processing and Quality Assessment Analysi

    Science.gov (United States)

    Hua, H.

    2016-12-01

    Geodetic imaging is revolutionizing geophysics, but the scope of discovery has been limited by labor-intensive technological implementation of the analyses. The Advanced Rapid Imaging and Analysis (ARIA) project has proven capability to automate SAR data processing and analysis. Existing and upcoming SAR missions such as Sentinel-1A/B and NISAR are also expected to generate massive amounts of SAR data. This has brought to the forefront the need for analytical tools for SAR quality assessment (QA) on the large volumes of SAR data-a critical step before higher-level time series and velocity products can be reliably generated. Initially leveraging an advanced hybrid-cloud computing science data system for performing large-scale processing, machine learning approaches were augmented for automated analysis of various quality metrics. Machine learning-based user-training of features, cross-validation, prediction models were integrated into our cloud-based science data processing flow to enable large-scale and high-throughput QA analytics for enabling improvements to the production quality of geodetic data products.

  7. Hybrid Light-Matter States in a Molecular and Material Science Perspective.

    Science.gov (United States)

    Ebbesen, Thomas W

    2016-11-15

    The notion that light and matter states can be hybridized the way s and p orbitals are mixed is a concept that is not familiar to most chemists and material scientists. Yet it has much potential for molecular and material sciences that is just beginning to be explored. For instance, it has already been demonstrated that the rate and yield of chemical reactions can be modified and that the conductivity of organic semiconductors and nonradiative energy transfer can be enhanced through the hybridization of electronic transitions. The hybridization is not limited to electronic transitions; it can be applied for instance to vibrational transitions to selectively perturb a given bond, opening new possibilities to change the chemical reactivity landscape and to use it as a tool in (bio)molecular science and spectroscopy. Such results are not only the consequence of the new eigenstates and energies generated by the hybridization. The hybrid light-matter states also have unusual properties: they can be delocalized over a very large number of molecules (up to ca. 10 5 ), and they become dispersive or momentum-sensitive. Importantly, the hybridization occurs even in the absence of light because it is the zero-point energies of the molecular and optical transitions that generate the new light-matter states. The present work is not a review but rather an Account from the author's point of view that first introduces the reader to the underlying concepts and details of the features of hybrid light-matter states. It is shown that light-matter hybridization is quite easy to achieve: all that is needed is to place molecules or a material in a resonant optical cavity (e.g., between two parallel mirrors) under the right conditions. For vibrational strong coupling, microfluidic IR cells can be used to study the consequences for chemistry in the liquid phase. Examples of modified properties are given to demonstrate the full potential for the molecular and material sciences. Finally an

  8. Virtual screening approach to identifying influenza virus neuraminidase inhibitors using molecular docking combined with machine-learning-based scoring function.

    Science.gov (United States)

    Zhang, Li; Ai, Hai-Xin; Li, Shi-Meng; Qi, Meng-Yuan; Zhao, Jian; Zhao, Qi; Liu, Hong-Sheng

    2017-10-10

    In recent years, an epidemic of the highly pathogenic avian influenza H7N9 virus has persisted in China, with a high mortality rate. To develop novel anti-influenza therapies, we have constructed a machine-learning-based scoring function (RF-NA-Score) for the effective virtual screening of lead compounds targeting the viral neuraminidase (NA) protein. RF-NA-Score is more accurate than RF-Score, with a root-mean-square error of 1.46, Pearson's correlation coefficient of 0.707, and Spearman's rank correlation coefficient of 0.707 in a 5-fold cross-validation study. The performance of RF-NA-Score in a docking-based virtual screening of NA inhibitors was evaluated with a dataset containing 281 NA inhibitors and 322 noninhibitors. Compared with other docking-rescoring virtual screening strategies, rescoring with RF-NA-Score significantly improved the efficiency of virtual screening, and a strategy that averaged the scores given by RF-NA-Score, based on the binding conformations predicted with AutoDock, AutoDock Vina, and LeDock, was shown to be the best strategy. This strategy was then applied to the virtual screening of NA inhibitors in the SPECS database. The 100 selected compounds were tested in an in vitro H7N9 NA inhibition assay, and two compounds with novel scaffolds showed moderate inhibitory activities. These results indicate that RF-NA-Score improves the efficiency of virtual screening for NA inhibitors, and can be used successfully to identify new NA inhibitor scaffolds. Scoring functions specific for other drug targets could also be established with the same method.

  9. Bridge between control science and technology. Volume 5 Manufacturing man-machine systems, computers, components, traffic control, space applications

    Energy Technology Data Exchange (ETDEWEB)

    Rembold, U; Kempf, K G; Towill, D R; Johannsen, G; Paul, M

    1985-01-01

    Among the topics discussed are: robotics; CAD/CAM applications; and man-machine systems. Consideration is also given to: tools and software for system design and integration; communication systems for real-time computer control; fail-safe design of real-time computer systems; and microcomputer-based control systems. Additional topics discussed include: programmable and intelligent components and instruments in automatic control; transportation systems; and space applications of automatic control systems.

  10. The machine body metaphor: From science and technology to physical education and sport, in France (1825-1935).

    Science.gov (United States)

    Gleyse, J

    2013-12-01

    The long history of the conception of physical exercise in France may be viewed as a function of a series of changes in understanding the body. Scientific concepts were used to present the body in official texts by authors specializing in the subject, or to describe them, as did Michel Foucault, as epistemic changes. A departure occurred during the 19th century that is clearly demonstrated in the writings of Gustave Adolphe Hirn. This breakthrough concerned the idea of considering the organism as an energy-generating machine. This metaphor was employed in describing the body during physical exercise from the 17th to the 19th centuries, when the body was thought of as mechanical. Such metaphors were used by the most relevant figures writing at the end of the 19th century in the rationale that is examined in this paper. It shows how Hirn, Marey, Lagrange, Demenij, Hebert, and Tissié saw the body and how they employed machine metaphors when referring to it. These machine metaphors are analyzed from the time of their scientific and technological origins up to their current use in physical and sports education. This analysis will contribute to the understanding of how a scientific metaphor comes to be in common use and may lead to particular exercise practices. © 2012 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  11. Challenging the Science Curriculum Paradigm: Teaching Primary Children Atomic-Molecular Theory

    Science.gov (United States)

    Haeusler, Carole; Donovan, Jennifer

    2017-11-01

    Solutions to global issues demand the involvement of scientists, yet concern exists about retention rates in science as students pass through school into University. Young children are curious about science, yet are considered incapable of grappling with abstract and microscopic concepts such as atoms, sub-atomic particles, molecules and DNA. School curricula for primary (elementary) aged children reflect this by their limitation to examining only what phenomena are without providing any explanatory frameworks for how or why they occur. This research challenges the assumption that atomic-molecular theory is too difficult for young children, examining new ways of introducing atomic theory to 9 year olds and seeks to verify their efficacy in producing genuine learning in the participants. Early results in three cases in different schools indicate these novel methods fostered further interest in science, allowed diverse children to engage and learn aspects of atomic theory, and satisfied the children's desire for intellectual challenge. Learning exceeded expectations as demonstrated in the post-interview findings. Learning was also remarkably robust, as demonstrated in two schools 8 weeks after the intervention and, in one school, 1 year after their first exposure to ideas about atoms, elements and molecules.

  12. Molecular Contamination on Anodized Aluminum Components of the Genesis Science Canister

    Science.gov (United States)

    Burnett, D. S.; McNamara, K. M.; Jurewicz, A.; Woolum, D.

    2005-01-01

    Inspection of the interior of the Genesis science canister after recovery in Utah, and subsequently at JSC, revealed a darkening on the aluminum canister shield and other canister components. There has been no such observation of film contamination on the collector surfaces, and preliminary spectroscopic ellipsometry measurements support the theory that the films observed on the anodized aluminum components do not appear on the collectors to any significant extent. The Genesis Science Team has made an effort to characterize the thickness and composition of the brown stain and to determine if it is associated with molecular outgassing.Detailed examination of the surfaces within the Genesis science canister reveals that the brown contamination is observed to varying degrees, but only on surfaces exposed in space to the Sun and solar wind hydrogen. In addition, the materials affected are primarily composed of anodized aluminum. A sharp line separating the sun and shaded portion of the thermal closeout panel is shown. This piece was removed from a location near the gold foil collector within the canister. Future plans include a reassembly of the canister components to look for large-scale patterns of contamination within the canister to aid in revealing the root cause.

  13. Molecular pathological epidemiology: new developing frontiers of big data science to study etiologies and pathogenesis.

    Science.gov (United States)

    Hamada, Tsuyoshi; Keum, NaNa; Nishihara, Reiko; Ogino, Shuji

    2017-03-01

    Molecular pathological epidemiology (MPE) is an integrative field that utilizes molecular pathology to incorporate interpersonal heterogeneity of a disease process into epidemiology. In each individual, the development and progression of a disease are determined by a unique combination of exogenous and endogenous factors, resulting in different molecular and pathological subtypes of the disease. Based on "the unique disease principle," the primary aim of MPE is to uncover an interactive relationship between a specific environmental exposure and disease subtypes in determining disease incidence and mortality. This MPE approach can provide etiologic and pathogenic insights, potentially contributing to precision medicine for personalized prevention and treatment. Although breast, prostate, lung, and colorectal cancers have been among the most commonly studied diseases, the MPE approach can be used to study any disease. In addition to molecular features, host immune status and microbiome profile likely affect a disease process, and thus serve as informative biomarkers. As such, further integration of several disciplines into MPE has been achieved (e.g., pharmaco-MPE, immuno-MPE, and microbial MPE), to provide novel insights into underlying etiologic mechanisms. With the advent of high-throughput sequencing technologies, available genomic and epigenomic data have expanded dramatically. The MPE approach can also provide a specific risk estimate for each disease subgroup, thereby enhancing the impact of genome-wide association studies on public health. In this article, we present recent progress of MPE, and discuss the importance of accounting for the disease heterogeneity in the era of big-data health science and precision medicine.

  14. Molecular Properties of Drugs Interacting with SLC22 Transporters OAT1, OAT3, OCT1, and OCT2: A Machine-Learning Approach.

    Science.gov (United States)

    Liu, Henry C; Goldenberg, Anne; Chen, Yuchen; Lun, Christina; Wu, Wei; Bush, Kevin T; Balac, Natasha; Rodriguez, Paul; Abagyan, Ruben; Nigam, Sanjay K

    2016-10-01

    Statistical analysis was performed on physicochemical descriptors of ∼250 drugs known to interact with one or more SLC22 "drug" transporters (i.e., SLC22A6 or OAT1, SLC22A8 or OAT3, SLC22A1 or OCT1, and SLC22A2 or OCT2), followed by application of machine-learning methods and wet laboratory testing of novel predictions. In addition to molecular charge, organic anion transporters (OATs) were found to prefer interacting with planar structures, whereas organic cation transporters (OCTs) interact with more three-dimensional structures (i.e., greater SP3 character). Moreover, compared with OAT1 ligands, OAT3 ligands possess more acyclic tetravalent bonds and have a more zwitterionic/cationic character. In contrast, OCT1 and OCT2 ligands were not clearly distinquishable form one another by the methods employed. Multiple pharmacophore models were generated on the basis of the drugs and, consistent with the machine-learning analyses, one unique pharmacophore created from ligands of OAT3 possessed cationic properties similar to OCT ligands; this was confirmed by quantitative atomic property field analysis. Virtual screening with this pharmacophore, followed by transport assays, identified several cationic drugs that selectively interact with OAT3 but not OAT1. Although the present analysis may be somewhat limited by the need to rely largely on inhibition data for modeling, wet laboratory/in vitro transport studies, as well as analysis of drug/metabolite handling in Oat and Oct knockout animals, support the general validity of the approach-which can also be applied to other SLC and ATP binding cassette drug transporters. This may make it possible to predict the molecular properties of a drug or metabolite necessary for interaction with the transporter(s), thereby enabling better prediction of drug-drug interactions and drug-metabolite interactions. Furthermore, understanding the overlapping specificities of OATs and OCTs in the context of dynamic transporter tissue

  15. Prediction of overall in vitro microsomal stability of drug candidates based on molecular modeling and support vector machines. Case study of novel arylpiperazines derivatives.

    Directory of Open Access Journals (Sweden)

    Szymon Ulenberg

    Full Text Available Other than efficacy of interaction with the molecular target, metabolic stability is the primary factor responsible for the failure or success of a compound in the drug development pipeline. The ideal drug candidate should be stable enough to reach its therapeutic site of action. Despite many recent excellent achievements in the field of computational methods supporting drug metabolism studies, a well-recognized procedure to model and predict metabolic stability quantitatively is still lacking. This study proposes a workflow for developing quantitative metabolic stability-structure relationships, taking a set of 30 arylpiperazine derivatives as an example. The metabolic stability of the compounds was assessed in in vitro incubations in the presence of human liver microsomes and NADPH and subsequently quantified by liquid chromatography-mass spectrometry (LC-MS. Density functional theory (DFT calculations were used to obtain 30 models of the molecules, and Dragon software served as a source of structure-based molecular descriptors. For modeling structure-metabolic stability relationships, Support Vector Machines (SVM, a non-linear machine learning technique, were found to be more effective than a regression technique, based on the validation parameters obtained. Moreover, for the first time, general sites of metabolism for arylpiperazines bearing the 4-aryl-2H-pyrido[1,2-c]pyrimidine-1,3-dione system were defined by analysis of Q-TOF-MS/MS spectra. The results indicated that the application of one of the most advanced chemometric techniques combined with a simple and quick in vitro procedure and LC-MS analysis provides a novel and valuable tool for predicting metabolic half-life values. Given the reduced time and simplicity of analysis, together with the accuracy of the predictions obtained, this is a valid approach for predicting metabolic stability using structural data. The approach presented provides a novel, comprehensive and reliable tool

  16. Molecular Environmental Science: An Assessment of Research Accomplishments, Available Synchrotron Radiation Facilities, and Needs

    International Nuclear Information System (INIS)

    Brown, G

    2004-01-01

    Synchrotron-based techniques are fundamental to research in ''Molecular Environmental Science'' (MES), an emerging field that involves molecular-level studies of chemical and biological processes affecting the speciation, properties, and behavior of contaminants, pollutants, and nutrients in the ecosphere. These techniques enable the study of aqueous solute complexes, poorly crystalline materials, solid-liquid interfaces, mineral-aqueous solution interactions, microbial biofilm-heavy metal interactions, heavy metal-plant interactions, complex material microstructures, and nanomaterials, all of which are important components or processes in the environment. Basic understanding of environmental materials and processes at the molecular scale is essential for risk assessment and management, and reduction of environmental pollutants at field, landscape, and global scales. One of the main purposes of this report is to illustrate the role of synchrotron radiation (SR)-based studies in environmental science and related fields and their impact on environmental problems of importance to society. A major driving force for MES research is the need to characterize, treat, and/or dispose of vast quantities of contaminated materials, including groundwater, sediments, and soils, and to process wastes, at an estimated cost exceeding 150 billion dollars through 2070. A major component of this problem derives from high-level nuclear waste. Other significant components come from mining and industrial wastes, atmospheric pollutants derived from fossil fuel consumption, agricultural pesticides and fertilizers, and the pollution problems associated with animal waste run-off, all of which have major impacts on human health and welfare. Addressing these problems requires the development of new characterization and processing technologies--efforts that require information on the chemical speciation of heavy metals, radionuclides, and xenobiotic organic compounds and their reactions with

  17. Molecular Environmental Science: An Assessment of Research Accomplishments, Available Synchrotron Radiation Facilities, and Needs

    Energy Technology Data Exchange (ETDEWEB)

    Brown, G

    2004-02-05

    Synchrotron-based techniques are fundamental to research in ''Molecular Environmental Science'' (MES), an emerging field that involves molecular-level studies of chemical and biological processes affecting the speciation, properties, and behavior of contaminants, pollutants, and nutrients in the ecosphere. These techniques enable the study of aqueous solute complexes, poorly crystalline materials, solid-liquid interfaces, mineral-aqueous solution interactions, microbial biofilm-heavy metal interactions, heavy metal-plant interactions, complex material microstructures, and nanomaterials, all of which are important components or processes in the environment. Basic understanding of environmental materials and processes at the molecular scale is essential for risk assessment and management, and reduction of environmental pollutants at field, landscape, and global scales. One of the main purposes of this report is to illustrate the role of synchrotron radiation (SR)-based studies in environmental science and related fields and their impact on environmental problems of importance to society. A major driving force for MES research is the need to characterize, treat, and/or dispose of vast quantities of contaminated materials, including groundwater, sediments, and soils, and to process wastes, at an estimated cost exceeding 150 billion dollars through 2070. A major component of this problem derives from high-level nuclear waste. Other significant components come from mining and industrial wastes, atmospheric pollutants derived from fossil fuel consumption, agricultural pesticides and fertilizers, and the pollution problems associated with animal waste run-off, all of which have major impacts on human health and welfare. Addressing these problems requires the development of new characterization and processing technologies--efforts that require information on the chemical speciation of heavy metals, radionuclides, and xenobiotic organic compounds and

  18. Molecular environmental science : an assessment of research accomplishments, available synchrotron radiation facilities, and needs.

    Energy Technology Data Exchange (ETDEWEB)

    Brown, G. E., Jr.; Sutton, S. R.; Bargar, J. R.; Shuh, D. K.; Fenter, P. A.; Kemner, K. M.

    2004-10-20

    Synchrotron-based techniques are fundamental to research in ''Molecular Environmental Science'' (MES), an emerging field that involves molecular-level studies of chemical and biological processes affecting the speciation, properties, and behavior of contaminants, pollutants, and nutrients in the ecosphere. These techniques enable the study of aqueous solute complexes, poorly crystalline materials, solid-liquid interfaces, mineral-aqueous solution interactions, microbial biofilm-heavy metal interactions, heavy metal-plant interactions, complex material microstructures, and nanomaterials, all of which are important components or processes in the environment. Basic understanding of environmental materials and processes at the molecular scale is essential for risk assessment and management, and reduction of environmental pollutants at field, landscape, and global scales. One of the main purposes of this report is to illustrate the role of synchrotron radiation (SR)-based studies in environmental science and related fields and their impact on environmental problems of importance to society. A major driving force for MES research is the need to characterize, treat, and/or dispose of vast quantities of contaminated materials, including groundwater, sediments, and soils, and to process wastes, at an estimated cost exceeding 150 billion dollars through 2070. A major component of this problem derives from high-level nuclear waste. Other significant components come from mining and industrial wastes, atmospheric pollutants derived from fossil fuel consumption, agricultural pesticides and fertilizers, and the pollution problems associated with animal waste run-off, all of which have major impacts on human health and welfare. Addressing these problems requires the development of new characterization and processing technologies--efforts that require information on the chemical speciation of heavy metals, radionuclides, and xenobiotic organic compounds and

  19. DNA-based machines.

    Science.gov (United States)

    Wang, Fuan; Willner, Bilha; Willner, Itamar

    2014-01-01

    The base sequence in nucleic acids encodes substantial structural and functional information into the biopolymer. This encoded information provides the basis for the tailoring and assembly of DNA machines. A DNA machine is defined as a molecular device that exhibits the following fundamental features. (1) It performs a fuel-driven mechanical process that mimics macroscopic machines. (2) The mechanical process requires an energy input, "fuel." (3) The mechanical operation is accompanied by an energy consumption process that leads to "waste products." (4) The cyclic operation of the DNA devices, involves the use of "fuel" and "anti-fuel" ingredients. A variety of DNA-based machines are described, including the construction of "tweezers," "walkers," "robots," "cranes," "transporters," "springs," "gears," and interlocked cyclic DNA structures acting as reconfigurable catenanes, rotaxanes, and rotors. Different "fuels", such as nucleic acid strands, pH (H⁺/OH⁻), metal ions, and light, are used to trigger the mechanical functions of the DNA devices. The operation of the devices in solution and on surfaces is described, and a variety of optical, electrical, and photoelectrochemical methods to follow the operations of the DNA machines are presented. We further address the possible applications of DNA machines and the future perspectives of molecular DNA devices. These include the application of DNA machines as functional structures for the construction of logic gates and computing, for the programmed organization of metallic nanoparticle structures and the control of plasmonic properties, and for controlling chemical transformations by DNA machines. We further discuss the future applications of DNA machines for intracellular sensing, controlling intracellular metabolic pathways, and the use of the functional nanostructures for drug delivery and medical applications.

  20. Invoking the Ghosts in the Machine: Reassessing the Evolution of the Science/Religion Phenomena - Alternative Perspectives

    OpenAIRE

    Shalet, Danielle

    2015-01-01

    This thesis is an in-depth critical analysis of the nature of the science/religion relationship. The purpose of this project is to expose the problems associated with the many fallacies related to these phenomena, and to evaluate the reasons behind certain perceptions. It outlines the damage done through years of misconceiving and misunderstanding the concepts of science and religion, and to address what led to such inadequacies in interpretation, emphasizing the use of insufficient and archa...

  1. Sustainable machining

    CERN Document Server

    2017-01-01

    This book provides an overview on current sustainable machining. Its chapters cover the concept in economic, social and environmental dimensions. It provides the reader with proper ways to handle several pollutants produced during the machining process. The book is useful on both undergraduate and postgraduate levels and it is of interest to all those working with manufacturing and machining technology.

  2. Science, art, and mistery in the statues and in the anatomical machines of the prince of sansevero: the masterpieces of the "Sansevero Chapel".

    Science.gov (United States)

    Della Monica, Matteo; Galzerano, Domenico; Di Michele, Sara; Acquaviva, Fabio; Gregorio, Giovanni; Lonardo, Fortunato; Sguazzo, Francesca; Scarano, Francesca; Lama, Diana; Scarano, Gioacchino

    2013-11-01

    During the 18th century in Naples, Raimondo di Sangro, Prince of Sansevero, completed works on the family chapel, the so-called "Cappella Sansevero." The chapel houses statues of extraordinary beauty and spectacularly detailed but also, in the basement, two human skeletons known as the "Anatomical Machines" ("Macchine Anatomiche"). These two skeletons, a man and a pregnant woman, are entirely surrounded by their circulatory systems, just as if these were suddenly fixed. Legend, believed as truth until few years ago, says that Prince Raimondo had prepared and injected an unknown embalming substance in the blood vessels of two of his servants convicting them to eternal fixity. Recent investigations have demonstrated that, while the bones are authentic, the blood vessels are actually extraordinary artifacts that also reproduce some congenital malformations. The dreadful aspect of these two skeletons appears to be in strident contrast with the classic beauty of the statues which glorify and celebrate the ideal of morphology. Conversely, the two Anatomical Machines, protagonists of legends and superstitions since centuries, represent a marvelous example of science mixed with art. © 2013 Wiley Periodicals, Inc.

  3. Molecular Nutrition Research—The Modern Way Of Performing Nutritional Science

    Science.gov (United States)

    Norheim, Frode; Gjelstad, Ingrid M. F.; Hjorth, Marit; Vinknes, Kathrine J.; Langleite, Torgrim M.; Holen, Torgeir; Jensen, Jørgen; Dalen, Knut Tomas; Karlsen, Anette S.; Kielland, Anders; Rustan, Arild C.; Drevon, Christian A.

    2012-01-01

    In spite of amazing progress in food supply and nutritional science, and a striking increase in life expectancy of approximately 2.5 months per year in many countries during the previous 150 years, modern nutritional research has a great potential of still contributing to improved health for future generations, granted that the revolutions in molecular and systems technologies are applied to nutritional questions. Descriptive and mechanistic studies using state of the art epidemiology, food intake registration, genomics with single nucleotide polymorphisms (SNPs) and epigenomics, transcriptomics, proteomics, metabolomics, advanced biostatistics, imaging, calorimetry, cell biology, challenge tests (meals, exercise, etc.), and integration of all data by systems biology, will provide insight on a much higher level than today in a field we may name molecular nutrition research. To take advantage of all the new technologies scientists should develop international collaboration and gather data in large open access databases like the suggested Nutritional Phenotype database (dbNP). This collaboration will promote standardization of procedures (SOP), and provide a possibility to use collected data in future research projects. The ultimate goals of future nutritional research are to understand the detailed mechanisms of action for how nutrients/foods interact with the body and thereby enhance health and treat diet-related diseases. PMID:23208524

  4. Molecular Nutrition Research—The Modern Way Of Performing Nutritional Science

    Directory of Open Access Journals (Sweden)

    Arild C. Rustan

    2012-12-01

    Full Text Available In spite of amazing progress in food supply and nutritional science, and a striking increase in life expectancy of approximately 2.5 months per year in many countries during the previous 150 years, modern nutritional research has a great potential of still contributing to improved health for future generations, granted that the revolutions in molecular and systems technologies are applied to nutritional questions. Descriptive and mechanistic studies using state of the art epidemiology, food intake registration, genomics with single nucleotide polymorphisms (SNPs and epigenomics, transcriptomics, proteomics, metabolomics, advanced biostatistics, imaging, calorimetry, cell biology, challenge tests (meals, exercise, etc., and integration of all data by systems biology, will provide insight on a much higher level than today in a field we may name molecular nutrition research. To take advantage of all the new technologies scientists should develop international collaboration and gather data in large open access databases like the suggested Nutritional Phenotype database (dbNP. This collaboration will promote standardization of procedures (SOP, and provide a possibility to use collected data in future research projects. The ultimate goals of future nutritional research are to understand the detailed mechanisms of action for how nutrients/foods interact with the body and thereby enhance health and treat diet-related diseases.

  5. Integration of pharmacology, molecular pathology, and population data science to support precision gastrointestinal oncology.

    Science.gov (United States)

    Ogino, Shuji; Jhun, Iny; Mata, Douglas A; Soong, Thing Rinda; Hamada, Tsuyoshi; Liu, Li; Nishihara, Reiko; Giannakis, Marios; Cao, Yin; Manson, JoAnn E; Nowak, Jonathan A; Chan, Andrew T

    2017-01-01

    Precision medicine has a goal of customizing disease prevention and treatment strategies. Under the precision medicine paradigm, each patient has unique pathologic processes resulting from cellular genomic, epigenomic, proteomic, and metabolomic alterations, which are influenced by pharmacological, environmental, microbial, dietary, and lifestyle factors. Hence, to realize the promise of precision medicine, multi-level research methods that can comprehensively analyze many of these variables are needed. In order to address this gap, the integrative field of molecular pathology and population data science (i.e., molecular pathological epidemiology) has been developed to enable such multi-level analyses, especially in gastrointestinal cancer research. Further integration of pharmacology can improve our understanding of drug effects, and inform decision-making of drug use at both the individual and population levels. Such integrative research demonstrated potential benefits of aspirin in colorectal carcinoma with PIK3CA mutations, providing the basis for new clinical trials. Evidence also suggests that HPGD (15-PDGH) expression levels in normal colon and the germline rs6983267 polymorphism that relates to tumor CTNNB1 (β-catenin)/ WNT signaling status may predict the efficacy of aspirin for cancer chemoprevention. As immune checkpoint blockade targeting the CD274 (PD-L1)/ PDCD1 (PD-1) pathway for microsatellite instability-high (or mismatch repair-deficient) metastatic gastrointestinal or other tumors has become standard of care, potential modifying effects of dietary, lifestyle, microbial, and environmental factors on immunotherapy need to be studied to further optimize treatment strategies. With its broad applicability, our integrative approach can provide insights into the interactive role of medications, exposures, and molecular pathology, and guide the development of precision medicine.

  6. Landscape of Innovation for Cardiovascular Pharmaceuticals: From Basic Science to New Molecular Entities.

    Science.gov (United States)

    Beierlein, Jennifer M; McNamee, Laura M; Walsh, Michael J; Kaitin, Kenneth I; DiMasi, Joseph A; Ledley, Fred D

    2017-07-01

    This study examines the complete timelines of translational science for new cardiovascular therapeutics from the initiation of basic research leading to identification of new drug targets through clinical development and US Food and Drug Administration (FDA) approval of new molecular entities (NMEs) based on this research. This work extends previous studies by examining the association between the growth of research on drug targets and approval of NMEs associated with these targets. Drawing on research on innovation in other technology sectors, where technological maturity is an important determinant in the success or failure of new product development, an analytical model was used to characterize the growth of research related to the known targets for all 168 approved cardiovascular therapeutics. Categorizing and mapping the technological maturity of cardiovascular therapeutics reveal that (1) there has been a distinct transition from phenotypic to targeted methods for drug discovery, (2) the durations of clinical and regulatory processes were significantly influenced by changes in FDA practice, and (3) the longest phase of the translational process was the time required for technology to advance from initiation of research to a statistically defined established point of technology maturation (mean, 30.8 years). This work reveals a normative association between metrics of research maturation and approval of new cardiovascular therapeutics and suggests strategies for advancing translational science by accelerating basic and applied research and improving the synchrony between the maturation of this research and drug development initiatives. Copyright © 2017 Elsevier HS Journals, Inc. All rights reserved.

  7. Thinking science with thinking machines: The multiple realities of basic and applied knowledge in a research border zone.

    Science.gov (United States)

    Hoffman, Steve G

    2015-04-01

    Some scholars dismiss the distinction between basic and applied science as passé, yet substantive assumptions about this boundary remain obdurate in research policy, popular rhetoric, the sociology and philosophy of science, and, indeed, at the level of bench practice. In this article, I draw on a multiple ontology framework to provide a more stable affirmation of a constructivist position in science and technology studies that cannot be reduced to a matter of competing perspectives on a single reality. The analysis is grounded in ethnographic research in the border zone of Artificial Intelligence science. I translate in-situ moments in which members of neighboring but differently situated labs engage in three distinct repertoires that render the reality of basic and applied science: partitioning, flipping, and collapsing. While the essences of scientific objects are nowhere to be found, the boundary between basic and applied is neither illusion nor mere propaganda. Instead, distinctions among scientific knowledge are made real as a matter of course.

  8. Natural Nano-Machines

    Indian Academy of Sciences (India)

    Administrator

    transport, ion pump, ATP syn- thase. A popularized ..... gas. A lice: I could not understand how A T P m olecules serve as fuels for m olecular m achines. ..... [16] V Balzani, M Venturi and A Credi, Molecular Devices and Machines: a Journey into ...

  9. Committee on Atomic, Molecular, and Optical Sciences (CAMOS). Technical progress report ampersand continuation proposal, February 1, 1993--January 31, 1994

    International Nuclear Information System (INIS)

    Taylor, R.D.

    1997-01-01

    The Committee on Atomic, Molecular and Optical Sciences (CAMOS) of the National Research Council (NRC) is charged with monitoring the health of the field of atomic, molecular, and optical (AMO) science in the United States. Accordingly, the Committee identifies and examines both broad and specific issues affecting the field. Regular meetings, teleconferences, briefings from agencies and the scientific community, the formation of study panels to prepare reports, and special symposia are among the mechanisms used by the CAMOS to meet its charge. This progress report presents a review of CAMOS activities from February 1, 1993 to January 31, 1994. The details of prior activities are discussed in earlier progress reports. This report also includes the status of activities associated with the CAMOS study on the field that is being conducted by the Panel on the Future of Atomic, Molecular, and Optical Sciences (FAMOS). During the above period, CAMOS has continued to track and participate in, when requested, discussions on the health of the field. Much of the perspective of CAMOS has been presented in the recently-published report Research Briefing on Selected Opportunities in Atomic, Molecular, and Optical Sciences. That report has served as the basis for briefings to representatives of the federal government as well as the community-at-large. In keeping with its charge to monitor the health of the field, CAMOS launched a study designed to highlight future directions of the field

  10. European analytical column No. 36 from the Division of Analytical Chemistry (DAC) of the European Association for Chemical and Molecular Sciences (EuCheMS)

    DEFF Research Database (Denmark)

    Karlberg, Bo; Emons, Hendrik; Andersen, Jens Enevold Thaulov

    2008-01-01

    European analytical column no. 36 from the division of analytical chemistry (DAC) of the European association for chemical and molecular sciences (EuCheMS)......European analytical column no. 36 from the division of analytical chemistry (DAC) of the European association for chemical and molecular sciences (EuCheMS)...

  11. A Turing Machine Simulator.

    Science.gov (United States)

    Navarro, Aaron B.

    1981-01-01

    Presents a program in Level II BASIC for a TRS-80 computer that simulates a Turing machine and discusses the nature of the device. The program is run interactively and is designed to be used as an educational tool by computer science or mathematics students studying computational or automata theory. (MP)

  12. Simple machines

    CERN Document Server

    Graybill, George

    2007-01-01

    Just how simple are simple machines? With our ready-to-use resource, they are simple to teach and easy to learn! Chocked full of information and activities, we begin with a look at force, motion and work, and examples of simple machines in daily life are given. With this background, we move on to different kinds of simple machines including: Levers, Inclined Planes, Wedges, Screws, Pulleys, and Wheels and Axles. An exploration of some compound machines follows, such as the can opener. Our resource is a real time-saver as all the reading passages, student activities are provided. Presented in s

  13. [Molecular imaging; current status and future prospects in USA].

    Science.gov (United States)

    Kobayashi, Hisataka

    2007-02-01

    The goal of this review is to introduce the definition, current status, and future prospects of the molecular imaging, which has recently been a hot topic in medicine and the biological science in USA. In vivo imaging methods to visualize the molecular events and functions in organs or animals/humans are overviewed and discussed especially in combinations of imaging modalities (machines) and contrast agents(chemicals) used in the molecular imaging. Next, the close relationship between the molecular imaging and the nanotechnology, an important part of nanomedicine, is stressed from the aspect of united multidisciplinary sciences such as physics, chemistry, biology, and medicine.

  14. A post-genomic surprise. The molecular reinscription of race in science, law and medicine.

    Science.gov (United States)

    Duster, Troy

    2015-03-01

    The completion of the first draft of the Human Genome Map in 2000 was widely heralded as the promise and future of genetics-based medicines and therapies - so much so that pundits began referring to the new century as 'The Century of Genetics'. Moreover, definitive assertions about the overwhelming similarities of all humans' DNA (99.9 per cent) by the leaders of the Human Genome Project were trumpeted as the end of racial thinking about racial taxonomies of human genetic differences. But the first decade of the new century brought unwelcomed surprises. First, gene therapies turned out to be far more complicated than any had anticipated - and instead the pharmaceutical industry turned to a focus on drugs that might be 'related' to population differences based upon genetic markers. While the language of 'personalized medicine' dominated this frame, research on racially and ethnically designated populations differential responsiveness to drugs dominated the empirical work in the field. Ancestry testing and 'admixture research' would play an important role in a new kind of molecular reification of racial categories. Moreover, the capacity of the super-computer to map differences reverberated into personal identification that would affect both the criminal justice system and forensic science, and generate new levels of concern about personal privacy. Social scientists in general, and sociologists in particular, have been caught short by these developments - relying mainly on assertions that racial categories are socially constructed, regionally and historically contingent, and politically arbitrary. While these assertions are true, the imprimatur of scientific legitimacy has shifted the burden, since now 'admixture research' can claim that its results get at the 'reality' of human differentiation, not the admittedly flawed social constructions of racial categories. Yet what was missing from this framing of the problem: 'admixture research' is itself based upon socially

  15. AutoIHC-scoring: a machine learning framework for automated Allred scoring of molecular expression in ER- and PR-stained breast cancer tissue.

    Science.gov (United States)

    Tewary, S; Arun, I; Ahmed, R; Chatterjee, S; Chakraborty, C

    2017-11-01

    In prognostic evaluation of breast cancer Immunohistochemical (IHC) markers namely, oestrogen receptor (ER) and progesterone receptor (PR) are widely used. The expert pathologist investigates qualitatively the stained tissue slide under microscope to provide the Allred score; which is clinically used for therapeutic decision making. Such qualitative judgment is time-consuming, tedious and more often suffers from interobserver variability. As a result, it leads to imprecise IHC score for ER and PR. To overcome this, there is an urgent need of developing a reliable and efficient IHC quantifier for high throughput decision making. In view of this, our study aims at developing an automated IHC profiler for quantitative assessment of ER and PR molecular expression from stained tissue images. We propose here to use CMYK colour space for positively and negatively stained cell extraction for proportion score. Also colour features are used for quantitative assessment of intensity scoring among the positively stained cells. Five different machine learning models namely artificial neural network, Naïve Bayes, K-nearest neighbours, decision tree and random forest are considered for learning the colour features using average red, green and blue pixel values of positively stained cell patches. Fifty cases of ER- and PR-stained tissues have been evaluated for validation with the expert pathologist's score. All five models perform adequately where random forest shows the best correlation with the expert's score (Pearson's correlation coefficient = 0.9192). In the proposed approach the average variation of diaminobenzidine (DAB) to nuclear area from the expert's score is found to be 7.58%, as compared to 27.83% for state-of-the-art ImmunoRatio software. © 2017 The Authors Journal of Microscopy © 2017 Royal Microscopical Society.

  16. Potential applications of luminescent molecular rotors in food science and engineering.

    Science.gov (United States)

    Alhassawi, Fatemah M; Corradini, Maria G; Rogers, Michael A; Ludescher, Richard D

    2017-06-29

    Fluorescent molecular rotors (MRs) are compounds whose emission is modulated by segmental mobility; photoexcitation generates a locally excited (LE), planar state that can relax either by radiative decay (emission of a photon) or by formation of a twisted intramolecular charge transfer (TICT) state that can relax nonradiatively due to internal rotation. If the local environment around the probe allows for rapid internal rotation in the excited state, fast non-radiative decay can either effectively quench the fluorescence or generate a second, red-shifted emission band. Conversely, any environmental restriction to twisting in the excited state due to free volume, crowding or viscosity, slows rotational relaxation and promotes fluorescence emission from the LE state. The environmental sensitivity of MRs has been exploited extensively in biological applications to sense microviscosity in biofluids, the stability and physical state of biomembranes, and conformational changes in macromolecules. The application of MRs in food research, however, has been only marginally explored. In this review, we summarize the main characteristics of fluorescent MRs, their current applications in biological research and their current and potential applications as sensors of physical properties in food science and engineering.

  17. Molecular tools for bathing water assessment in Europe: Balancing social science research with a rapidly developing environmental science evidence-base.

    Science.gov (United States)

    Oliver, David M; Hanley, Nick D; van Niekerk, Melanie; Kay, David; Heathwaite, A Louise; Rabinovici, Sharyl J M; Kinzelman, Julie L; Fleming, Lora E; Porter, Jonathan; Shaikh, Sabina; Fish, Rob; Chilton, Sue; Hewitt, Julie; Connolly, Elaine; Cummins, Andy; Glenk, Klaus; McPhail, Calum; McRory, Eric; McVittie, Alistair; Giles, Amanna; Roberts, Suzanne; Simpson, Katherine; Tinch, Dugald; Thairs, Ted; Avery, Lisa M; Vinten, Andy J A; Watts, Bill D; Quilliam, Richard S

    2016-02-01

    The use of molecular tools, principally qPCR, versus traditional culture-based methods for quantifying microbial parameters (e.g., Fecal Indicator Organisms) in bathing waters generates considerable ongoing debate at the science-policy interface. Advances in science have allowed the development and application of molecular biological methods for rapid (~2 h) quantification of microbial pollution in bathing and recreational waters. In contrast, culture-based methods can take between 18 and 96 h for sample processing. Thus, molecular tools offer an opportunity to provide a more meaningful statement of microbial risk to water-users by providing near-real-time information enabling potentially more informed decision-making with regard to water-based activities. However, complementary studies concerning the potential costs and benefits of adopting rapid methods as a regulatory tool are in short supply. We report on findings from an international Working Group that examined the breadth of social impacts, challenges, and research opportunities associated with the application of molecular tools to bathing water regulations.

  18. Face machines

    Energy Technology Data Exchange (ETDEWEB)

    Hindle, D.

    1999-06-01

    The article surveys latest equipment available from the world`s manufacturers of a range of machines for tunnelling. These are grouped under headings: excavators; impact hammers; road headers; and shields and tunnel boring machines. Products of thirty manufacturers are referred to. Addresses and fax numbers of companies are supplied. 5 tabs., 13 photos.

  19. Electric machine

    Science.gov (United States)

    El-Refaie, Ayman Mohamed Fawzi [Niskayuna, NY; Reddy, Patel Bhageerath [Madison, WI

    2012-07-17

    An interior permanent magnet electric machine is disclosed. The interior permanent magnet electric machine comprises a rotor comprising a plurality of radially placed magnets each having a proximal end and a distal end, wherein each magnet comprises a plurality of magnetic segments and at least one magnetic segment towards the distal end comprises a high resistivity magnetic material.

  20. Machine Learning.

    Science.gov (United States)

    Kirrane, Diane E.

    1990-01-01

    As scientists seek to develop machines that can "learn," that is, solve problems by imitating the human brain, a gold mine of information on the processes of human learning is being discovered, expert systems are being improved, and human-machine interactions are being enhanced. (SK)

  1. Nonplanar machines

    International Nuclear Information System (INIS)

    Ritson, D.

    1989-05-01

    This talk examines methods available to minimize, but never entirely eliminate, degradation of machine performance caused by terrain following. Breaking of planar machine symmetry for engineering convenience and/or monetary savings must be balanced against small performance degradation, and can only be decided on a case-by-case basis. 5 refs

  2. Molecular Mechanistic Reasoning: Toward Bridging the Gap between the Molecular and Cellular Levels in Life Science Education

    Science.gov (United States)

    van Mil, Marc H. W.; Postma, Paulien A.; Boerwinkel, Dirk Jan; Klaassen, Kees; Waarlo, Arend Jan

    2016-01-01

    Although learning about DNA, RNA, and proteins is part of the upper secondary biology curriculum in most countries, many studies report that students fail to connect molecular knowledge to phenomena at the higher level of cells, organs, and organisms. As a result, many students use memorization and rote learning as a coping strategy when presented…

  3. The Machine within the Machine

    CERN Multimedia

    Katarina Anthony

    2014-01-01

    Although Virtual Machines are widespread across CERN, you probably won't have heard of them unless you work for an experiment. Virtual machines - known as VMs - allow you to create a separate machine within your own, allowing you to run Linux on your Mac, or Windows on your Linux - whatever combination you need.   Using a CERN Virtual Machine, a Linux analysis software runs on a Macbook. When it comes to LHC data, one of the primary issues collaborations face is the diversity of computing environments among collaborators spread across the world. What if an institute cannot run the analysis software because they use different operating systems? "That's where the CernVM project comes in," says Gerardo Ganis, PH-SFT staff member and leader of the CernVM project. "We were able to respond to experimentalists' concerns by providing a virtual machine package that could be used to run experiment software. This way, no matter what hardware they have ...

  4. Machine translation

    Energy Technology Data Exchange (ETDEWEB)

    Nagao, M

    1982-04-01

    Each language has its own structure. In translating one language into another one, language attributes and grammatical interpretation must be defined in an unambiguous form. In order to parse a sentence, it is necessary to recognize its structure. A so-called context-free grammar can help in this respect for machine translation and machine-aided translation. Problems to be solved in studying machine translation are taken up in the paper, which discusses subjects for semantics and for syntactic analysis and translation software. 14 references.

  5. Nanomedicine: tiny particles and machines give huge gains.

    Science.gov (United States)

    Tong, Sheng; Fine, Eli J; Lin, Yanni; Cradick, Thomas J; Bao, Gang

    2014-02-01

    Nanomedicine is an emerging field that integrates nanotechnology, biomolecular engineering, life sciences and medicine; it is expected to produce major breakthroughs in medical diagnostics and therapeutics. Nano-scale structures and devices are compatible in size with proteins and nucleic acids in living cells. Therefore, the design, characterization and application of nano-scale probes, carriers and machines may provide unprecedented opportunities for achieving a better control of biological processes, and drastic improvements in disease detection, therapy, and prevention. Recent advances in nanomedicine include the development of nanoparticle (NP)-based probes for molecular imaging, nano-carriers for drug/gene delivery, multifunctional NPs for theranostics, and molecular machines for biological and medical studies. This article provides an overview of the nanomedicine field, with an emphasis on NPs for imaging and therapy, as well as engineered nucleases for genome editing. The challenges in translating nanomedicine approaches to clinical applications are discussed.

  6. Instrumentation and control and human machine interface science and technology road-map in support of advanced reactors and fuel programs in the U.S

    International Nuclear Information System (INIS)

    Miller, D. W.; Arndt, S. A.; Bond, L. J.; Dudenhoeffer, D.; Hallbert, B.; Holcomb, D. E.; Wood, R. T.; Naser, J. A.; O'Hara, J.; Quinn, E. L.

    2006-01-01

    The purpose of this paper is to provide an overview of the current status of the Instrumentation, Control and Human Machine Interface (ICHMI) Science and Technology road-map being developed to address the major challenges in this technical area for the Gen IV and other U.S. Dept. of Energy (DOE) initiatives that support future deployments of nuclear energy systems. Reliable, capable ICHMI systems will be necessary for the advanced nuclear plants to be economically competitive. ICHMI enables measurement, control, protection, monitoring, and maintenance for processes and components. Through improvements in the technologies and demonstration of their use to facilitate licensing, ICHMI can contribute to the reduction of plant operations and maintenance costs while helping to ensure high plant availability. The impact of ICHMI can be achieved through effective use of the technologies to improve operational efficiency and optimize use of human resources. However, current licensing experience with digital I and C systems has provided lessons learned concerning the difficulties that can be encountered when introducing advanced technologies with expanded capabilities. Thus, in the development of advanced nuclear power designs, it will be important to address both the technical foundations of ICHMI systems as well as their licensing considerations. The ICHMI road-map will identify the necessary research, development and demonstration activities that are essential to facilitate necessary technology advancement and resolve outstanding issues. (authors)

  7. Instrumentation and control and human machine interface science and technology Road-map in support of advanced reactors and fuel programs in the U.S

    International Nuclear Information System (INIS)

    Miller, D. W.; Arndt, S. A.; Dudenhoeffer, D.; Hallbert, B.; Bond, L. J.; Holcomb, D. E.; Wood, R. T.; Naser, J. A.; O'Hara, J.; Quinn, E. L.

    2008-01-01

    The purpose of this paper is to provide an overview of the current status of the Instrumentation, Control and Human Machine Interface (ICHMI) Science and Technology Road-map (Reference xi) that was developed to address the major challenges in this technical area for the Gen IV and other U.S. Department of Energy (DOE) initiatives that support future deployments of nuclear energy systems. Reliable, capable ICHMI systems will be necessary for the advanced nuclear plants to be economically competitive. ICHMI enables measurement, control, protection, monitoring, and maintenance for processes and components. Through improvements in the technologies and demonstration of their use to facilitate licensing, ICHMI can contribute to the reduction of plant operations and maintenance costs while helping to ensure high plant availability. The impact of ICHMI can be achieved through effective use of the technologies to improve operational efficiency and optimize use of human resources. However, current licensing experience with digital I and C systems has provided lessons learned concerning the difficulties that can be encountered when introducing advanced technologies with expanded capabilities. Thus, in the development of advanced nuclear power designs, it will be important to address both the technical foundations of ICHMI systems and their licensing considerations. The ICHMI Road-map will identify the necessary research, development and demonstration activities that are essential to facilitate necessary technology advancement and resolve outstanding issues. (authors)

  8. Instrumentation and Control and Human Machine Interface Science and Technology Roadmap in Support of Advanced Reactors and Fuel Programs in the U.S

    International Nuclear Information System (INIS)

    Miller, Don W.; Arndt, Steven A.; Dudenhoeffer, Donald D.; Hallbert, Bruce P.; Bond, Leonard J.; Holcomb, David E.; Wood, Richard T.; Naser, Joseph A.; O'Hara, John M.; Quinn, Edward L.

    2008-01-01

    The purpose of this paper is to provide an overview of the current status of the Instrumentation, Control and Human Machine Interface (ICHMI) Science and Technology Roadmap (Reference xi) that was developed to address the major challenges in this technical area for the Gen IV and other U.S. Department of Energy (DOE) initiatives that support future deployments of nuclear energy systems. Reliable, capable ICHMI systems will be necessary for the advanced nuclear plants to be economically competitive. ICHMI enables measurement, control, protection, monitoring, and maintenance for processes and components. Through improvements in the technologies and demonstration of their use to facilitate licensing, ICHMI can contribute to the reduction of plant operations and maintenance costs while helping to ensure high plant availability. The impact of ICHMI can be achieved through effective use of the technologies to improve operational efficiency and optimize use of human resources. However, current licensing experience with digital I and C systems has provided lessons learned concerning the difficulties that can be encountered when introducing advanced technologies with expanded capabilities. Thus, in the development of advanced nuclear power designs, it will be important to address both the technical foundations of ICHMI systems and their licensing considerations. The ICHMI roadmap will identify the necessary research, development and demonstration activities that are essential to facilitate necessary technology advancement and resolve outstanding issues

  9. Super-Resolution Molecular and Functional Imaging of Nanoscale Architectures in Life and Materials Science

    KAUST Repository

    Habuchi, Satoshi

    2014-01-01

    fluorescence microscopy techniques along with the latest developments of fluorophores and labeling for the SR microscopy. I discuss the applications of SR microscopy in the fields of life science and materials science with a special emphasis on quantitative

  10. Machine Translation

    Indian Academy of Sciences (India)

    Research Mt System Example: The 'Janus' Translating Phone Project. The Janus ... based on laptops, and simultaneous translation of two speakers in a dialogue. For more ..... The current focus in MT research is on using machine learning.

  11. Artificial molecular motors

    NARCIS (Netherlands)

    Kassem, Salma; van Leeuwen, Thomas; Lubbe, Anouk S.; Wilson, Miriam R.; Feringa, Ben L.; Leigh, David A.

    2017-01-01

    Motor proteins are nature's solution for directing movement at the molecular level. The field of artificial molecular motors takes inspiration from these tiny but powerful machines. Although directional motion on the nanoscale performed by synthetic molecular machines is a relatively new

  12. Quantum Machine Learning

    Science.gov (United States)

    Biswas, Rupak

    2018-01-01

    Quantum computing promises an unprecedented ability to solve intractable problems by harnessing quantum mechanical effects such as tunneling, superposition, and entanglement. The Quantum Artificial Intelligence Laboratory (QuAIL) at NASA Ames Research Center is the space agency's primary facility for conducting research and development in quantum information sciences. QuAIL conducts fundamental research in quantum physics but also explores how best to exploit and apply this disruptive technology to enable NASA missions in aeronautics, Earth and space sciences, and space exploration. At the same time, machine learning has become a major focus in computer science and captured the imagination of the public as a panacea to myriad big data problems. In this talk, we will discuss how classical machine learning can take advantage of quantum computing to significantly improve its effectiveness. Although we illustrate this concept on a quantum annealer, other quantum platforms could be used as well. If explored fully and implemented efficiently, quantum machine learning could greatly accelerate a wide range of tasks leading to new technologies and discoveries that will significantly change the way we solve real-world problems.

  13. Machine Protection

    International Nuclear Information System (INIS)

    Zerlauth, Markus; Schmidt, Rüdiger; Wenninger, Jörg

    2012-01-01

    The present architecture of the machine protection system is being recalled and the performance of the associated systems during the 2011 run will be briefly summarized. An analysis of the causes of beam dumps as well as an assessment of the dependability of the machine protection systems (MPS) itself is being presented. Emphasis will be given to events that risked exposing parts of the machine to damage. Further improvements and mitigations of potential holes in the protection systems will be evaluated along with their impact on the 2012 run. The role of rMPP during the various operational phases (commissioning, intensity ramp up, MDs...) will be discussed along with a proposal for the intensity ramp up for the start of beam operation in 2012

  14. Machine Learning

    Energy Technology Data Exchange (ETDEWEB)

    Chikkagoudar, Satish; Chatterjee, Samrat; Thomas, Dennis G.; Carroll, Thomas E.; Muller, George

    2017-04-21

    The absence of a robust and unified theory of cyber dynamics presents challenges and opportunities for using machine learning based data-driven approaches to further the understanding of the behavior of such complex systems. Analysts can also use machine learning approaches to gain operational insights. In order to be operationally beneficial, cybersecurity machine learning based models need to have the ability to: (1) represent a real-world system, (2) infer system properties, and (3) learn and adapt based on expert knowledge and observations. Probabilistic models and Probabilistic graphical models provide these necessary properties and are further explored in this chapter. Bayesian Networks and Hidden Markov Models are introduced as an example of a widely used data driven classification/modeling strategy.

  15. Machine Protection

    CERN Document Server

    Zerlauth, Markus; Wenninger, Jörg

    2012-01-01

    The present architecture of the machine protection system is being recalled and the performance of the associated systems during the 2011 run will be briefly summarized. An analysis of the causes of beam dumps as well as an assessment of the dependability of the machine protection systems (MPS) itself is being presented. Emphasis will be given to events that risked exposing parts of the machine to damage. Further improvements and mitigations of potential holes in the protection systems will be evaluated along with their impact on the 2012 run. The role of rMPP during the various operational phases (commissioning, intensity ramp up, MDs...) will be discussed along with a proposal for the intensity ramp up for the start of beam operation in 2012.

  16. Machine Protection

    Energy Technology Data Exchange (ETDEWEB)

    Zerlauth, Markus; Schmidt, Rüdiger; Wenninger, Jörg [European Organization for Nuclear Research, Geneva (Switzerland)

    2012-07-01

    The present architecture of the machine protection system is being recalled and the performance of the associated systems during the 2011 run will be briefly summarized. An analysis of the causes of beam dumps as well as an assessment of the dependability of the machine protection systems (MPS) itself is being presented. Emphasis will be given to events that risked exposing parts of the machine to damage. Further improvements and mitigations of potential holes in the protection systems will be evaluated along with their impact on the 2012 run. The role of rMPP during the various operational phases (commissioning, intensity ramp up, MDs...) will be discussed along with a proposal for the intensity ramp up for the start of beam operation in 2012.

  17. Teletherapy machine

    International Nuclear Information System (INIS)

    Panyam, Vinatha S.; Rakshit, Sougata; Kulkarni, M.S.; Pradeepkumar, K.S.

    2017-01-01

    Radiation Standards Section (RSS), RSSD, BARC is the national metrology institute for ionizing radiation. RSS develops and maintains radiation standards for X-ray, beta, gamma and neutron radiations. In radiation dosimetry, traceability, accuracy and consistency of radiation measurements is very important especially in radiotherapy where the success of patient treatment is dependent on the accuracy of the dose delivered to the tumour. Cobalt teletherapy machines have been used in the treatment of cancer since the early 1950s and India had its first cobalt teletherapy machine installed at the Cancer Institute, Chennai in 1956

  18. An art history of machines?

    Directory of Open Access Journals (Sweden)

    Daniel Bridgman

    2016-12-01

    Full Text Available A toast offered in honor of Donald Preziosi on the cusp of his seventy-fifth birthday, this essay considers a range of machine metaphors, their art historical settings, and their implications. Addressing the mythography of Daedalus and his wonder machines in relation to art history’s machinic enterprises, an ancient art-archaeology seminar Preziosi directed at UCLA (in 1988 and the book, Rethinking Art History: Meditations on a Coy Science (1989 form the focus of my thinking about Preziosi’s work. At issue across the essay is the work of recursion, when machines make machines and in so doing create a recessive subjectivity for the maker. The essay ends with the speculation that art history’s disciplinary machinery may owe its generative strength to a perpetual need for replacement parts.

  19. Deep learning: Using machine learning to study biological vision

    OpenAIRE

    Majaj, Najib; Pelli, Denis

    2017-01-01

    Today most vision-science presentations mention machine learning. Many neuroscientists use machine learning to decode neural responses. Many perception scientists try to understand recognition by living organisms. To them, machine learning offers a reference of attainable performance based on learned stimuli. This brief overview of the use of machine learning in biological vision touches on its strengths, weaknesses, milestones, controversies, and current directions.

  20. Opportunities and limitations related to the application of plant-derived lipid molecular proxies in soil science

    Directory of Open Access Journals (Sweden)

    B. Jansen

    2017-11-01

    Full Text Available The application of lipids in soils as molecular proxies, also often referred to as biomarkers, has dramatically increased in the last decades. Applications range from inferring changes in past vegetation composition, climate, and/or human presence to unraveling the input and turnover of soil organic matter (SOM. The molecules used are extractable and non-extractable lipids, including ester-bound lipids. In addition, the carbon or hydrogen isotopic composition of such molecules is used. While holding great promise, the application of soil lipids as molecular proxies comes with several constraining factors, the most important of which are (i variability in the molecular composition of plant-derived organic matter both internally and between individual plants, (ii variability in (the relative contribution of input pathways into the soil, and (iii the transformation and/or (selective degradation of (some of the molecules once present in the soil. Unfortunately, the information about such constraining factors and their impact on the applicability of molecular proxies is fragmented and scattered. The purpose of this study is to provide a critical review of the current state of knowledge with respect to the applicability of molecular proxies in soil science, specifically focusing on the factors constraining such applicability. Variability in genetic, ontogenetic, and environmental factors influences plant n-alkane patterns in such a way that no unique compounds or specific molecular proxies pointing to, for example, plant community differences or environmental influences, exist. Other components, such as n-alcohols, n-fatty acids, and cutin- and suberin-derived monomers, have received far less attention in this respect. Furthermore, there is a high diversity of input pathways offering both opportunities and limitations for the use of molecular proxies at the same time. New modeling approaches might offer a possibility to unravel such mixed input

  1. An ab initio molecular

    Indian Academy of Sciences (India)

    mechanisms of two molecular crystals: An ab initio molecular dynamics ... for Computation in Molecular and Materials Science and Department of Chemistry, School of ..... NSAF Foundation of National Natural Science Foun- ... Matter 14 2717.

  2. Machine testning

    DEFF Research Database (Denmark)

    De Chiffre, Leonardo

    This document is used in connection with a laboratory exercise of 3 hours duration as a part of the course GEOMETRICAL METROLOGY AND MACHINE TESTING. The exercise includes a series of tests carried out by the student on a conventional and a numerically controled lathe, respectively. This document...

  3. Ethers on Si(001): A prime example for the common ground between surface science and molecular organic chemistry

    KAUST Repository

    Pecher, Lisa

    2017-09-15

    Using computational chemistry, we show that the adsorption of ether molecules on Si(001) under ultra-high vacuum conditions can be understood with textbook organic chemistry. The two-step reaction mechanism of (1) dative bond formation between the ether oxygen and a Lewis acidic surface atom and (2) a nucleophilic attack of a nearby Lewis basic surface atom is analysed in detail and found to mirror the acid-catalysed ether cleavage in solution. The O-Si dative bond is found to be the strongest of its kind and reactivity from this state defies the Bell-Evans-Polanyi principle. Electron rearrangement during the C-O bond cleavage is visualized using a newly developed bonding analysis method, which shows that the mechanism of nucleophilic substitutions on semiconductor surfaces is identical to molecular chemistry SN2 reactions. Our findings thus illustrate how the fields of surface science and molecular chemistry can mutually benefit and unexpected insight can be gained.

  4. Ethers on Si(001): A prime example for the common ground between surface science and molecular organic chemistry

    KAUST Repository

    Pecher, Lisa; Laref, Slimane; Raupach, Marc; Tonner, Ralf Ewald

    2017-01-01

    Using computational chemistry, we show that the adsorption of ether molecules on Si(001) under ultra-high vacuum conditions can be understood with textbook organic chemistry. The two-step reaction mechanism of (1) dative bond formation between the ether oxygen and a Lewis acidic surface atom and (2) a nucleophilic attack of a nearby Lewis basic surface atom is analysed in detail and found to mirror the acid-catalysed ether cleavage in solution. The O-Si dative bond is found to be the strongest of its kind and reactivity from this state defies the Bell-Evans-Polanyi principle. Electron rearrangement during the C-O bond cleavage is visualized using a newly developed bonding analysis method, which shows that the mechanism of nucleophilic substitutions on semiconductor surfaces is identical to molecular chemistry SN2 reactions. Our findings thus illustrate how the fields of surface science and molecular chemistry can mutually benefit and unexpected insight can be gained.

  5. Machine rates for selected forest harvesting machines

    Science.gov (United States)

    R.W. Brinker; J. Kinard; Robert Rummer; B. Lanford

    2002-01-01

    Very little new literature has been published on the subject of machine rates and machine cost analysis since 1989 when the Alabama Agricultural Experiment Station Circular 296, Machine Rates for Selected Forest Harvesting Machines, was originally published. Many machines discussed in the original publication have undergone substantial changes in various aspects, not...

  6. Applications of neural networks to real-time data processing at the Environmental and Molecular Sciences Laboratory (EMSL)

    International Nuclear Information System (INIS)

    Keller, P.E.; Kouzes, R.T.; Kangas, L.J.

    1993-06-01

    Detailed design of the Environmental and Molecular Sciences Laboratory (EMSL) at the Pacific Northwest Laboratory (PNL) is nearing completion and construction is scheduled to begin later this year. This facility will assist in the environmental restoration and waste management mission at the Hanford Site. This paper identifies several real-time data processing applications within the EMSL where neural networks can potentially be beneficial. These applications include real-time sensor data acquisition and analysis, spectral analysis, process control, theoretical modeling, and data compression

  7. Microfluidics' great promise for Biology - Microfluidics as a new engine for the molecular sciences

    KAUST Repository

    Kodzius, Rimantas

    2010-06-04

    History of the Life Sciences Origins of life Discoveries and instrumentation The power of genetic variation Diagnostics based on DNA/ protein variation Genomic scanning providers DNA sequencing companies Microfluidics story Commercial products available P

  8. Surface and catalysis science in the Materials and Molecular Research Division

    International Nuclear Information System (INIS)

    1980-01-01

    Surface science studies at Lawrence Berkeley Laboratory are detailed. Subject areas include: structure of surfaces and adsorbed monolayers; reduction and oxidation of surfaces; catalytic chemistry; and structure of interfaces and thin films

  9. The impact of computer science in molecular medicine: enabling high-throughput research.

    Science.gov (United States)

    de la Iglesia, Diana; García-Remesal, Miguel; de la Calle, Guillermo; Kulikowski, Casimir; Sanz, Ferran; Maojo, Víctor

    2013-01-01

    The Human Genome Project and the explosion of high-throughput data have transformed the areas of molecular and personalized medicine, which are producing a wide range of studies and experimental results and providing new insights for developing medical applications. Research in many interdisciplinary fields is resulting in data repositories and computational tools that support a wide diversity of tasks: genome sequencing, genome-wide association studies, analysis of genotype-phenotype interactions, drug toxicity and side effects assessment, prediction of protein interactions and diseases, development of computational models, biomarker discovery, and many others. The authors of the present paper have developed several inventories covering tools, initiatives and studies in different computational fields related to molecular medicine: medical informatics, bioinformatics, clinical informatics and nanoinformatics. With these inventories, created by mining the scientific literature, we have carried out several reviews of these fields, providing researchers with a useful framework to locate, discover, search and integrate resources. In this paper we present an analysis of the state-of-the-art as it relates to computational resources for molecular medicine, based on results compiled in our inventories, as well as results extracted from a systematic review of the literature and other scientific media. The present review is based on the impact of their related publications and the available data and software resources for molecular medicine. It aims to provide information that can be useful to support ongoing research and work to improve diagnostics and therapeutics based on molecular-level insights.

  10. Electric machines

    CERN Document Server

    Gross, Charles A

    2006-01-01

    BASIC ELECTROMAGNETIC CONCEPTSBasic Magnetic ConceptsMagnetically Linear Systems: Magnetic CircuitsVoltage, Current, and Magnetic Field InteractionsMagnetic Properties of MaterialsNonlinear Magnetic Circuit AnalysisPermanent MagnetsSuperconducting MagnetsThe Fundamental Translational EM MachineThe Fundamental Rotational EM MachineMultiwinding EM SystemsLeakage FluxThe Concept of Ratings in EM SystemsSummaryProblemsTRANSFORMERSThe Ideal n-Winding TransformerTransformer Ratings and Per-Unit ScalingThe Nonideal Three-Winding TransformerThe Nonideal Two-Winding TransformerTransformer Efficiency and Voltage RegulationPractical ConsiderationsThe AutotransformerOperation of Transformers in Three-Phase EnvironmentsSequence Circuit Models for Three-Phase Transformer AnalysisHarmonics in TransformersSummaryProblemsBASIC MECHANICAL CONSIDERATIONSSome General PerspectivesEfficiencyLoad Torque-Speed CharacteristicsMass Polar Moment of InertiaGearingOperating ModesTranslational SystemsA Comprehensive Example: The ElevatorP...

  11. Charging machine

    International Nuclear Information System (INIS)

    Medlin, J.B.

    1976-01-01

    A charging machine for loading fuel slugs into the process tubes of a nuclear reactor includes a tubular housing connected to the process tube, a charging trough connected to the other end of the tubular housing, a device for loading the charging trough with a group of fuel slugs, means for equalizing the coolant pressure in the charging trough with the pressure in the process tubes, means for pushing the group of fuel slugs into the process tube and a latch and a seal engaging the last object in the group of fuel slugs to prevent the fuel slugs from being ejected from the process tube when the pusher is removed and to prevent pressure liquid from entering the charging machine. 3 claims, 11 drawing figures

  12. Genesis machines

    CERN Document Server

    Amos, Martyn

    2014-01-01

    Silicon chips are out. Today's scientists are using real, wet, squishy, living biology to build the next generation of computers. Cells, gels and DNA strands are the 'wetware' of the twenty-first century. Much smaller and more intelligent, these organic computers open up revolutionary possibilities. Tracing the history of computing and revealing a brave new world to come, Genesis Machines describes how this new technology will change the way we think not just about computers - but about life itself.

  13. Quo vadis, Intelligent Machine?

    Directory of Open Access Journals (Sweden)

    Rosemarie Velik

    2010-09-01

    Full Text Available Artificial Intelligence (AI is a branch of computer science concerned with making computers behave like humans. At least this was the original idea. However, it turned out that this is no task easy to be solved. This article aims to give a comprehensible review on the last 60 years of artificial intelligence taking a philosophical viewpoint. It is outlined what happened so far in AI, what is currently going on in this research area, and what can be expected in future. The goal is to mediate an understanding for the developments and changes in thinking in course of time about how to achieve machine intelligence. The clear message is that AI has to join forces with neuroscience and other brain disciplines in order to make a step towards the development of truly intelligent machines.

  14. MLnet report: training in Europe on machine learning

    OpenAIRE

    Ellebrecht, Mario; Morik, Katharina

    1999-01-01

    Machine learning techniques offer opportunities for a variety of applications and the theory of machine learning investigates problems that are of interest for other fields of computer science (e.g., complexity theory, logic programming, pattern recognition). However, the impacts of machine learning can only be recognized by those who know the techniques and are able to apply them. Hence, teaching machine learning is necessary before this field can diversify computer science. In order ...

  15. Protein Science by DNA Sequencing: How Advances in Molecular Biology Are Accelerating Biochemistry.

    Science.gov (United States)

    Higgins, Sean A; Savage, David F

    2018-01-09

    A fundamental goal of protein biochemistry is to determine the sequence-function relationship, but the vastness of sequence space makes comprehensive evaluation of this landscape difficult. However, advances in DNA synthesis and sequencing now allow researchers to assess the functional impact of every single mutation in many proteins, but challenges remain in library construction and the development of general assays applicable to a diverse range of protein functions. This Perspective briefly outlines the technical innovations in DNA manipulation that allow massively parallel protein biochemistry and then summarizes the methods currently available for library construction and the functional assays of protein variants. Areas in need of future innovation are highlighted with a particular focus on assay development and the use of computational analysis with machine learning to effectively traverse the sequence-function landscape. Finally, applications in the fundamentals of protein biochemistry, disease prediction, and protein engineering are presented.

  16. A molecular surface science study of the structure of adsorbates on surfaces: Importance to lubrication

    International Nuclear Information System (INIS)

    Mate, C.M.

    1986-09-01

    The interaction and bonding of atoms and molecules on metal surfaces is explored under ultra-high vacuum conditions using a variety of surface science techniques: high resolution electron energy loss spectroscopy (HREELS), low energy electron diffraction (LEED), thermal desorption spectroscopy (TDS), Auger electron spectroscopy (AES), work function measurements, and second harmonic generation (SHG). 164 refs., 51 figs., 3 tabs

  17. Research briefing on selected opportunities in atomic, molecular, and optical sciences

    International Nuclear Information System (INIS)

    1991-01-01

    This report discusses research on the following topics: The Laser-Atom Revolution; Controlling Dynamical Pathways; Nonclassical States of Light; Transient States of Atomic Systems; New Light Generation and Handling; Clusters; Atomic Physics at User Facilities; and Impacts of AMO Sciences on Modern Technologies

  18. Molecular Energy and Environmental Science: A Workshop Sponsored by The National Science Foundation and The Department of Energy May 26-27, 1999 in Rosemont, Illinois

    Energy Technology Data Exchange (ETDEWEB)

    Stair, Peter C [Northwestern Univ., Evanston, IL (United States); DeSimone, Joseph M. [University of North Carolina Chapel Hill; Frost, John W. [Michigan State Univ., East Lansing, MI (United States)

    1999-05-26

    Energy and the environment pose major scientific and technological challenges for the 21st century. New technologies for increasing the efficiency of harvesting and utilizing energy resources are essential to the nation’s economic competitiveness. At the same time, the quality of life in the United States depends inherently on the environmental impact of energy production and utilization. This interdependence makes it imperative to develop a better understanding of the environment and new strategies for minimizing the impact of energy-related activities. Recent advances in techniques for the synthesis and characterization of chemicals and materials and for the molecular control of biological organisms make it possible, for the first time, to address this imperative. Chemistry, with its focus on the molecular level, plays a central role in addressing the needs for fundamental understanding and technology development in both the energy and environmental fields. Understanding environmental processes and consequences requires studying natural systems, rather than focussing exclusively on laboratory models. Natural systems and their complexity pose an enormous, perhaps the ultimate, challenge to chemists, and will provide them with varied and exciting new problems for years to come. In addition, the complexity of the underlying systems and processes often requires multi-disciplinary programs that bridge the interfaces between chemistry and other disciplines. (See Figure 1) This has ramifications in the approach to funding research and suggests needs for broadening the educational training of future scientists and engineers in these programs. Figure 1. NSF and DOE should consider sponsoring research centers and focused research groups organized to optimize their impact on Technological Challenges of national interest. The research will have significant impact if it addresses issues of fundamental molecular science in one or more Enabling Research Areas. Approximately 7

  19. Controlling Variables in Molecular Gel Science: How Can We Improve the State of the Art?

    Directory of Open Access Journals (Sweden)

    Richard G. Weiss

    2018-03-01

    Full Text Available By design, no references are included in this article. It is intended to be a series of recommendations in which the focus is on lab practices for investigating substances rather than on the substances being investigated. Thus, it discusses some specific areas of concern identified by the author. Other scientists are encouraged to add to or amend the contents. This article should be read as a “living” document, like a blog in which many gel scientists work, over time, to achieve a consensus about reporting everything from acronyms and definitions to procedures and methods. For those entering the field and seeking compendia on the subject, the author suggests “Googling” the words “molecular gels” or “molecular gels books”.

  20. Science review: Mechanisms of impaired adrenal function in sepsis and molecular actions of glucocorticoids

    OpenAIRE

    Prigent, Hélène; Maxime, Virginie; Annane, Djillali

    2004-01-01

    This review describes current knowledge on the mechanisms that underlie glucocorticoid insufficiency in sepsis and the molecular action of glucocorticoids. In patients with severe sepsis, numerous factors predispose to glucocorticoid insufficiency, including drugs, coagulation disorders and inflammatory mediators. These factors may compromise the hypothalamic–pituitary axis (i.e. secondary adrenal insufficiency) or the adrenal glands (i.e. primary adrenal failure), or may impair glucocorticoi...

  1. Representational Machines

    DEFF Research Database (Denmark)

    Photography not only represents space. Space is produced photographically. Since its inception in the 19th century, photography has brought to light a vast array of represented subjects. Always situated in some spatial order, photographic representations have been operatively underpinned by social...... to the enterprises of the medium. This is the subject of Representational Machines: How photography enlists the workings of institutional technologies in search of establishing new iconic and social spaces. Together, the contributions to this edited volume span historical epochs, social environments, technological...... possibilities, and genre distinctions. Presenting several distinct ways of producing space photographically, this book opens a new and important field of inquiry for photography research....

  2. Shear machines

    International Nuclear Information System (INIS)

    Astill, M.; Sunderland, A.; Waine, M.G.

    1980-01-01

    A shear machine for irradiated nuclear fuel elements has a replaceable shear assembly comprising a fuel element support block, a shear blade support and a clamp assembly which hold the fuel element to be sheared in contact with the support block. A first clamp member contacts the fuel element remote from the shear blade and a second clamp member contacts the fuel element adjacent the shear blade and is advanced towards the support block during shearing to compensate for any compression of the fuel element caused by the shear blade (U.K.)

  3. Machine speech and speaking about machines

    Energy Technology Data Exchange (ETDEWEB)

    Nye, A. [Univ. of Wisconsin, Whitewater, WI (United States)

    1996-12-31

    Current philosophy of language prides itself on scientific status. It boasts of being no longer contaminated with queer mental entities or idealist essences. It theorizes language as programmable variants of formal semantic systems, reimaginable either as the properly epiphenomenal machine functions of computer science or the properly material neural networks of physiology. Whether or not such models properly capture the physical workings of a living human brain is a question that scientists will have to answer. I, as a philosopher, come at the problem from another direction. Does contemporary philosophical semantics, in its dominant truth-theoretic and related versions, capture actual living human thought as it is experienced, or does it instead reflect, regardless of (perhaps dubious) scientific credentials, pathology of thought, a pathology with a disturbing social history.

  4. Electricity of machine tool

    International Nuclear Information System (INIS)

    Gijeon media editorial department

    1977-10-01

    This book is divided into three parts. The first part deals with electricity machine, which can taints from generator to motor, motor a power source of machine tool, electricity machine for machine tool such as switch in main circuit, automatic machine, a knife switch and pushing button, snap switch, protection device, timer, solenoid, and rectifier. The second part handles wiring diagram. This concludes basic electricity circuit of machine tool, electricity wiring diagram in your machine like milling machine, planer and grinding machine. The third part introduces fault diagnosis of machine, which gives the practical solution according to fault diagnosis and the diagnostic method with voltage and resistance measurement by tester.

  5. Environmentally Friendly Machining

    CERN Document Server

    Dixit, U S; Davim, J Paulo

    2012-01-01

    Environment-Friendly Machining provides an in-depth overview of environmentally-friendly machining processes, covering numerous different types of machining in order to identify which practice is the most environmentally sustainable. The book discusses three systems at length: machining with minimal cutting fluid, air-cooled machining and dry machining. Also covered is a way to conserve energy during machining processes, along with useful data and detailed descriptions for developing and utilizing the most efficient modern machining tools. Researchers and engineers looking for sustainable machining solutions will find Environment-Friendly Machining to be a useful volume.

  6. Can machine learning explain human learning?

    NARCIS (Netherlands)

    Vahdat, M.; Oneto, L.; Anguita, D.; Funk, M.; Rauterberg, G.W.M.

    2016-01-01

    Learning Analytics (LA) has a major interest in exploring and understanding the learning process of humans and, for this purpose, benefits from both Cognitive Science, which studies how humans learn, and Machine Learning, which studies how algorithms learn from data. Usually, Machine Learning is

  7. Machine Protection

    CERN Document Server

    Schmidt, R

    2014-01-01

    The protection of accelerator equipment is as old as accelerator technology and was for many years related to high-power equipment. Examples are the protection of powering equipment from overheating (magnets, power converters, high-current cables), of superconducting magnets from damage after a quench and of klystrons. The protection of equipment from beam accidents is more recent. It is related to the increasing beam power of high-power proton accelerators such as ISIS, SNS, ESS and the PSI cyclotron, to the emission of synchrotron light by electron–positron accelerators and FELs, and to the increase of energy stored in the beam (in particular for hadron colliders such as LHC). Designing a machine protection system requires an excellent understanding of accelerator physics and operation to anticipate possible failures that could lead to damage. Machine protection includes beam and equipment monitoring, a system to safely stop beam operation (e.g. dumping the beam or stopping the beam at low energy) and an ...

  8. Machine Translation - A Gentle Introduction

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 3; Issue 7. Machine Translation - A Gentle Introduction. Durgesh D Rao. General Article Volume 3 Issue 7 July 1998 pp 61-70. Fulltext. Click here to view fulltext PDF. Permanent link: https://www.ias.ac.in/article/fulltext/reso/003/07/0061-0070 ...

  9. Machine Learning Approaches Toward Building Predictive Models for Small Molecule Modulators of miRNA and Its Utility in Virtual Screening of Molecular Databases.

    Science.gov (United States)

    Periwal, Vinita; Scaria, Vinod

    2017-01-01

    The ubiquitous role of microRNAs (miRNAs) in a number of pathological processes has suggested that they could act as potential drug targets. RNA-binding small molecules offer an attractive means for modulating miRNA function. The availability of bioassay data sets for a variety of biological assays and molecules in public domain provides a new opportunity toward utilizing them to create models and further utilize them for in silico virtual screening approaches to prioritize or assign potential functions for small molecules. Here, we describe a computational strategy based on machine learning for creation of predictive models from high-throughput biological screens for virtual screening of small molecules with the potential to inhibit microRNAs. Such models could be potentially used for computational prioritization of small molecules before performing high-throughput biological assay.

  10. DAE-BRNS life sciences symposium on molecular biology of stress response and its applications

    International Nuclear Information System (INIS)

    2005-01-01

    The world of living organisms is full of challenges from their surroundings and these organisms learn to adapt themselves to the changes - some transient and some permanent - in these surroundings. The demands on adaptability to stress are very strong for extremophiles that live in harsh conditions such as cold or hot temperatures, salinity and hyperbaric habitats. The stress could be biotic (e.g. infection or parasitism) or abiotic (e.g. temperature, light, salinity, heavy metals etc.) Evolutionarily living organisms have developed different shapes, coloration, habits etc. to survive in their habitats. The molecular mechanisms of these biological adaptations have become clearer only in recent years from the studies on the biological responses of an organism to stresses during its life time. Such responses are characterized by activation of certain genes and synthesis of proteins and metabolites, which facilitate amelioration of the stress. The molecular biology (biochemistry and genetics) of stress response is being constantly unravelled thanks to the availability of highly sensitive and high throughput techniques and a plethora of extremophilic experimental systems such as archaebacteria, radio resistant bacteria and midges, plants surviving in cold etc. An interesting outcome of this voluminous research has been the knowledge that responses to a group of stresses share common mechanisms, at least in part. This reflects the biologically conservationist trend among otherwise diverse organisms and stresses. In this symposium several papers and posters in the area of molecular biology of stress are presented in addition to some very interesting and promising-to-be informative and stimulating plenary lectures and invited talks from highly reputed scientists. The papers relevant to INIS are indexed separately

  11. Atomic and molecular sciences. Progress report No. 8, April 1, 1981-March 31, 1982

    International Nuclear Information System (INIS)

    Walters, G.K.; Lane, N.F.

    1981-01-01

    The atomic and molecular physics program at Rice University addresses fundamental problems in structure, radiation-induced gas- and condensed-phase reaction kinetics and dynamics, and the mutual interactions of radiation, atoms, molecules, electrons and ions, particularly in highly unusual or exotic environments. The program emphasizes fundamental studies relating to new sources of energy, with close interaction between experimental and theoretical aspects of the research. Progress in the experimental program is reported in two principal areas, A) time resolved spectroscopy, and B) reactions in a flowing helium afterglow

  12. A survey of machine readable data bases

    Science.gov (United States)

    Matlock, P.

    1981-01-01

    Forty-two of the machine readable data bases available to the technologist and researcher in the natural sciences and engineering are described and compared with the data bases and date base services offered by NASA.

  13. The laboratory technology of discrete molecular separation: the historical development of gel electrophoresis and the material epistemology of biomolecular science, 1945-1970.

    Science.gov (United States)

    Chiang, Howard Hsueh-hao

    2009-01-01

    Preparative and analytical methods developed by separation scientists have played an important role in the history of molecular biology. One such early method is gel electrophoresis, a technique that uses various types of gel as its supporting medium to separate charged molecules based on size and other properties. Historians of science, however, have only recently begun to pay closer attention to this material epistemological dimension of biomolecular science. This paper substantiates the historiographical thread that explores the relationship between modern laboratory practice and the production of scientific knowledge. It traces the historical development of gel electrophoresis from the mid-1940s to the mid-1960s, with careful attention to the interplay between technical developments and disciplinary shifts, especially the rise of molecular biology in this time-frame. Claiming that the early 1950s marked a decisive shift in the evolution of electrophoretic methods from moving boundary to zone electrophoresis, I reconstruct various trajectories in which scientists such as Oliver Smithies sought out the most desirable solid supporting medium for electrophoretic instrumentation. Biomolecular knowledge, I argue, emerged in part from this process of seeking the most appropriate supporting medium that allowed for discrete molecular separation and visualization. The early 1950s, therefore, marked not only an important turning point in the history of separation science, but also a transformative moment in the history of the life sciences as the growth of molecular biology depended in part on the epistemological access to the molecular realm available through these evolving technologies.

  14. Soft X-Ray Microscopy and Spectroscopy at the Molecular Environmental Science Beamline at the Advanced Light Source

    Energy Technology Data Exchange (ETDEWEB)

    Bluhm, Hendrik; Andersson, Klas J.; Araki, Tohru; Benzerara, Karim; Brown, Gordon E.; Dynes, Jay J.; Ghosal, Sutapa; Gilles, Mary K.; Hansen, Hans C.; Hemminger, J. C.; Hitchcock, Adam P.; Ketteler, Guido; Kilcoyne, Arthur L.; Kneedler, Eric M.; Lawrence, John R.; Leppard, Gary G.; Majzlam, Juraj; Mun, B. S.; Myneni, Satish C.; Nilsson, Anders R.; Ogasawara, Hirohito; Ogletree, D. F.; Pecher, Klaus H.; Salmeron, Miquel B.; Shuh, David K.; Tonner, Brian; Tyliszczak, Tolek; Warwick, Tony; Yoon, T. H.

    2006-02-01

    We present examples of the application of synchrotron-based spectroscopies and microscopies to environmentally-relevant samples. The experiments were performed at the Molecular Environmental Science beamline (11.0.2) at the Advanced Light Source, Lawrence Berkeley National Laboratory. Examples range from the study of water monolayers on Pt(111) single crystal surfaces using X-ray emission spectroscopy and the examination of alkali halide solution/water vapor interfaces using ambient pressure photoemission spectroscopy, to the investigation of actinides, river-water biofilms, Al-containing colloids and mineral-bacteria suspensions using scanning transmission X-ray spectromicroscopy. The results of our experiments show that spectroscopy and microscopy in the soft X-ray energy range are excellent tools for the investigation of environmentally relevant samples under realistic conditions, i.e. with water or water vapor present at ambient temperature.

  15. The environmental and molecular sciences laboratory project: Continuous evolution in leadership

    International Nuclear Information System (INIS)

    Knutson, D.E.; McClusky, J.K.

    1995-09-01

    The United States is embarking on an environmental cleanup effort that dwarfs previous scientific enterprise. Using current best available technology, the projected costs of cleaning up the tens of abounds of toxic waste sites, including DOE sites, is estimated to exceed one trillion dollars. That level of expenditure contains no guarantee that the sites can be restored to their original condition, and no consensus on ''how clean is clean enough.'' ''Ultimately, the scientific challenge is to determine as accurately as possible each term in the path that links the source of the contaminant with the particular biological end points or health effects and to understand the mechanisms that connect them. However, the present state of scientific knowledge regarding the effects of exogenous chemicals on human biology is very limited. Understanding the connections at the molecular level is, at best, a blurred picture and often a black box.'' Long term environmental research at the molecular level is needed to resolve the concerns, and form the building blocks for a structure of cost effective process improvement and regulatory reform

  16. The environmental and molecular sciences laboratory project: Continuous evolution in leadership

    Energy Technology Data Exchange (ETDEWEB)

    Knutson, D.E.; McClusky, J.K.

    1995-09-01

    The United States is embarking on an environmental cleanup effort that dwarfs previous scientific enterprise. Using current best available technology, the projected costs of cleaning up the tens of abounds of toxic waste sites, including DOE sites, is estimated to exceed one trillion dollars. That level of expenditure contains no guarantee that the sites can be restored to their original condition, and no consensus on ``how clean is clean enough.`` ``Ultimately, the scientific challenge is to determine as accurately as possible each term in the path that links the source of the contaminant with the particular biological end points or health effects and to understand the mechanisms that connect them. However, the present state of scientific knowledge regarding the effects of exogenous chemicals on human biology is very limited. Understanding the connections at the molecular level is, at best, a blurred picture and often a black box.`` Long term environmental research at the molecular level is needed to resolve the concerns, and form the building blocks for a structure of cost effective process improvement and regulatory reform.

  17. Micro-machined calorimetric biosensors

    Science.gov (United States)

    Doktycz, Mitchel J.; Britton, Jr., Charles L.; Smith, Stephen F.; Oden, Patrick I.; Bryan, William L.; Moore, James A.; Thundat, Thomas G.; Warmack, Robert J.

    2002-01-01

    A method and apparatus are provided for detecting and monitoring micro-volumetric enthalpic changes caused by molecular reactions. Micro-machining techniques are used to create very small thermally isolated masses incorporating temperature-sensitive circuitry. The thermally isolated masses are provided with a molecular layer or coating, and the temperature-sensitive circuitry provides an indication when the molecules of the coating are involved in an enthalpic reaction. The thermally isolated masses may be provided singly or in arrays and, in the latter case, the molecular coatings may differ to provide qualitative and/or quantitative assays of a substance.

  18. The experimental teaching reform in biochemistry and molecular biology for undergraduate students in Peking University Health Science Center.

    Science.gov (United States)

    Yang, Xiaohan; Sun, Luyang; Zhao, Ying; Yi, Xia; Zhu, Bin; Wang, Pu; Lin, Hong; Ni, Juhua

    2015-01-01

    Since 2010, second-year undergraduate students of an eight-year training program leading to a Doctor of Medicine degree or Doctor of Philosophy degree in Peking University Health Science Center (PKUHSC) have been required to enter the "Innovative talent training project." During that time, the students joined a research lab and participated in some original research work. There is a critical educational need to prepare these students for the increasing accessibility of research experience. The redesigned experimental curriculum of biochemistry and molecular biology was developed to fulfill such a requirement, which keeps two original biochemistry experiments (Gel filtration and Enzyme kinetics) and adds a new two-experiment component called "Analysis of anti-tumor drug induced apoptosis." The additional component, also known as the "project-oriented experiment" or the "comprehensive experiment," consists of Western blotting and a DNA laddering assay to assess the effects of etoposide (VP16) on the apoptosis signaling pathways. This reformed laboratory teaching system aims to enhance the participating students overall understanding of important biological research techniques and the instrumentation involved, and to foster a better understanding of the research process all within a classroom setting. Student feedback indicated that the updated curriculum helped them improve their operational and self-learning capability, and helped to increase their understanding of theoretical knowledge and actual research processes, which laid the groundwork for their future research work. © 2015 The International Union of Biochemistry and Molecular Biology.

  19. Ethers on Si(001): A Prime Example for the Common Ground between Surface Science and Molecular Organic Chemistry.

    Science.gov (United States)

    Pecher, Lisa; Laref, Slimane; Raupach, Marc; Tonner, Ralf

    2017-11-20

    By using computational chemistry it has been shown that the adsorption of ether molecules on Si(001) under ultrahigh vacuum conditions can be understood with classical concepts of organic chemistry. Detailed analysis of the two-step reaction mechanism-1) formation of a dative bond between the ether oxygen atom and a Lewis acidic surface atom and 2) nucleophilic attack of a nearby Lewis basic surface atom-shows that it mirrors acid-catalyzed ether cleavage in solution. The O-Si dative bond is the strongest of its kind, and the reactivity in step 2 defies the Bell-Evans-Polanyi principle. Electron rearrangement during C-O bond cleavage has been visualized with a newly developed method for analyzing bonding, which shows that the mechanism of nucleophilic substitutions on semiconductor surfaces is identical to molecular S N 2 reactions. Our findings illustrate how surface science and molecular chemistry can mutually benefit from each other and unexpected insight can be gained. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. Machine Protection

    International Nuclear Information System (INIS)

    Schmidt, R

    2014-01-01

    The protection of accelerator equipment is as old as accelerator technology and was for many years related to high-power equipment. Examples are the protection of powering equipment from overheating (magnets, power converters, high-current cables), of superconducting magnets from damage after a quench and of klystrons. The protection of equipment from beam accidents is more recent. It is related to the increasing beam power of high-power proton accelerators such as ISIS, SNS, ESS and the PSI cyclotron, to the emission of synchrotron light by electron–positron accelerators and FELs, and to the increase of energy stored in the beam (in particular for hadron colliders such as LHC). Designing a machine protection system requires an excellent understanding of accelerator physics and operation to anticipate possible failures that could lead to damage. Machine protection includes beam and equipment monitoring, a system to safely stop beam operation (e.g. dumping the beam or stopping the beam at low energy) and an interlock system providing the glue between these systems. The most recent accelerator, the LHC, will operate with about 3 × 10 14 protons per beam, corresponding to an energy stored in each beam of 360 MJ. This energy can cause massive damage to accelerator equipment in case of uncontrolled beam loss, and a single accident damaging vital parts of the accelerator could interrupt operation for years. This article provides an overview of the requirements for protection of accelerator equipment and introduces the various protection systems. Examples are mainly from LHC, SNS and ESS

  1. Science literacy and meaningful learning: status of public high school students from Rio de Janeiro face to molecular biology concepts

    Directory of Open Access Journals (Sweden)

    Daniel Alves Escodino

    2013-12-01

    Full Text Available In this work we aimed to determine the level of Molecular Biology (MB science literacy of students from two Brazilian public schools which do not consider the rogerian theory for class planning and from another institution, Cap UERJ, which favours this theory. We applied semiclosed questionnaires specific to the different groups of science literacy levels. Besides, we have asked them to perform conceptual maps with MB concepts in order to observe if they have experienced meaningful learning. Finally, we prepared MB classes for students of the three schools, considering their conceptual maps and tried to evaluate, through a second map execution, if the use of alternative didactics material, which consider meaningful learning process, would have any effect over the appropriation of new concepts. We observed that most students are placed at Functional literacy level. Nonetheless, several students from CAp were also settled at the higher Conceptual and Procedural levels. We found that most students have not experienced meaningful learning and that the employment of didactic material and implementation of proposals which consider the cognitive structure of the students had a significant effect on the appropriation of several concepts.

  2. Machine terms dictionary

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1979-04-15

    This book gives descriptions of machine terms which includes machine design, drawing, the method of machine, machine tools, machine materials, automobile, measuring and controlling, electricity, basic of electron, information technology, quality assurance, Auto CAD and FA terms and important formula of mechanical engineering.

  3. Design and Evaluation of a Digital Module with Guided Peer Feedback for Student Learning Biotechnology and Molecular Life Sciences, Attitudinal Change, and Satisfaction

    Science.gov (United States)

    Noroozi, Omid; Mulder, Martin

    2017-01-01

    This study aims to investigate the impacts of a digital learning module with guided peer feedback on students' domain-specific knowledge gain and their attitudinal change in the field of biotechnology and molecular life sciences. The extent to which the use of this module is appreciated by students is studied as well. A pre-test, post-test design…

  4. Design and evaluation of a digital module with guided peer feedback for student learning biotechnology and molecular life sciences, attitudinal change, and satisfaction

    NARCIS (Netherlands)

    Noroozi, Omid; Mulder, Martin

    2017-01-01

    This study aims to investigate the impacts of a digital learning module with guided peer feedback on students' domain-specific knowledge gain and their attitudinal change in the field of biotechnology and molecular life sciences. The extent to which the use of this module is appreciated by

  5. Nuclear science fights malaria. Radiation and molecular techniques can play targeted roles

    International Nuclear Information System (INIS)

    Groth, Steffen; Khan, Baldip; Robinson, Alan; Hendrichs, Jorge

    2001-01-01

    Malaria is the most important insect transmitted disease. Globally there are 300 to 500 million clinical cases of malaria a year. They result in two million deaths per year (one every 30 seconds), more than 90% of which occur in sub-Saharan Africa. More than 90% of those affected are children less than five years old. The economic impact of the disease is felt disproportionately by poor families who may spend a fourth of their annual income on prevention and control measures. The causative agents are parasites of the genus Plasmodium and they are transmitted only by female mosquitoes of the genus Anopheles. Among key strategies to control malaria are the surveillance of anti-malarial drug efficacy through monitoring the levels of drug resistance, and the reduction of mosquito populations. Nuclear techniques can play important roles in these efforts to combat malaria. This article reports on IAEA activities associated with drug-resistant malaria and describes how molecular methods making use of radioactive isotopes can provide a great advantage in the diagnosis of resistance. The article further presents the IAEA's plans for initiating a research programme to assess the feasibility of developing the Sterile Insect Technique (SIT) as a complementary method to control the vector of malaria

  6. Multi-phase alternative current machine winding design | Khan ...

    African Journals Online (AJOL)

    ... single-phase to 18-phase excitation. Experimental results of a five-phase induction machine supplied from a static five-phase supply are provided to support the proposed design. Keywords: AC machine, Multi-phase machine, Stator winding, Five-phase. International Journal of Engineering, Science and Technology, Vol.

  7. Addiction Machines

    Directory of Open Access Journals (Sweden)

    James Godley

    2011-10-01

    Full Text Available Entry into the crypt William Burroughs shared with his mother opened and shut around a failed re-enactment of William Tell’s shot through the prop placed upon a loved one’s head. The accidental killing of his wife Joan completed the installation of the addictation machine that spun melancholia as manic dissemination. An early encryptment to which was added the audio portion of abuse deposited an undeliverable message in WB. Wil- liam could never tell, although his corpus bears the in- scription of this impossibility as another form of pos- sibility. James Godley is currently a doctoral candidate in Eng- lish at SUNY Buffalo, where he studies psychoanalysis, Continental philosophy, and nineteenth-century litera- ture and poetry (British and American. His work on the concept of mourning and “the dead” in Freudian and Lacanian approaches to psychoanalytic thought and in Gothic literature has also spawned an essay on zombie porn. Since entering the Academy of Fine Arts Karlsruhe in 2007, Valentin Hennig has studied in the classes of Sil- via Bächli, Claudio Moser, and Corinne Wasmuht. In 2010 he spent a semester at the Dresden Academy of Fine Arts. His work has been shown in group exhibi- tions in Freiburg and Karlsruhe.

  8. Machine musicianship

    Science.gov (United States)

    Rowe, Robert

    2002-05-01

    The training of musicians begins by teaching basic musical concepts, a collection of knowledge commonly known as musicianship. Computer programs designed to implement musical skills (e.g., to make sense of what they hear, perform music expressively, or compose convincing pieces) can similarly benefit from access to a fundamental level of musicianship. Recent research in music cognition, artificial intelligence, and music theory has produced a repertoire of techniques that can make the behavior of computer programs more musical. Many of these were presented in a recently published book/CD-ROM entitled Machine Musicianship. For use in interactive music systems, we are interested in those which are fast enough to run in real time and that need only make reference to the material as it appears in sequence. This talk will review several applications that are able to identify the tonal center of musical material during performance. Beyond this specific task, the design of real-time algorithmic listening through the concurrent operation of several connected analyzers is examined. The presentation includes discussion of a library of C++ objects that can be combined to perform interactive listening and a demonstration of their capability.

  9. Prediction of compounds activity in nuclear receptor signaling and stress pathway assays using machine learning algorithms and low dimensional molecular descriptors

    Directory of Open Access Journals (Sweden)

    Filip eStefaniak

    2015-12-01

    Full Text Available Toxicity evaluation of newly synthesized or used compounds is one of the main challenges during product development in many areas of industry. For example, toxicity is the second reason - after lack of efficacy - for failure in preclinical and clinical studies of drug candidates. To avoid attrition at the late stage of the drug development process, the toxicity analyses are employed at the early stages of a discovery pipeline, along with activity and selectivity enhancing. Although many assays for screening in vitro toxicity are available, their massive application is not always time and cost effective. Thus the need for fast and reliable in silico tools, which can be used not only for toxicity prediction of existing compounds, but also for prioritization of compounds planned for synthesis or acquisition. Here I present the benchmark results of the combination of various attribute selection methods and machine learning algorithms and their application to the data sets of the Tox21 Data Challenge. The best performing method: Best First for attribute selection with the Rotation Forest/ADTree classifier offers good accuracy for most tested cases. For 11 out of 12 targets, the AUROC value for the final evaluation set was ≥0.72, while for three targets the AUROC value was ≥ 0.80, with the average AUROC being 0.784±0.069. The use of two-dimensional descriptors sets enables fast screening and compound prioritization even for a very large database. Open source tools used in this project make the presented approach widely available and encourage the community to further improve the presented scheme.

  10. Molecular Environmental Science Using Synchrotron Radiation: Chemistry and Physics of Waste Form Materials. Final Report

    International Nuclear Information System (INIS)

    Lindle, Dennis W.

    2011-01-01

    Production of defense-related nuclear materials has generated large volumes of complex chemical wastes containing a mixture of radionuclides. The disposition of these wastes requires conversion of the liquid and solid-phase components into durable, solid forms suitable for long-term immobilization. Specially formulated glass compositions and ceramics such as pyrochlores and apatites are the main candidates for these wastes. An important consideration linked to the durability of waste-form materials is the local structure around the waste components. Equally important is the local structure of constituents of the glass and ceramic host matrix. Knowledge of the structure in the waste-form host matrices is essential, prior to and subsequent to waste incorporation, to evaluate and develop improved waste-form compositions based on scientific considerations. This project used the soft-x-ray synchrotron-radiation-based technique of near-edge x-ray-absorption fine structure (NEXAFS) as a unique method for investigating oxidation states and structures of low-Z elemental constituents forming the backbones of glass and ceramic host matrices for waste-form materials. In addition, light metal ions in ceramic hosts, such as titanium, are also ideal for investigation by NEXAFS in the soft-x-ray region. Thus, one of the main objectives was to understand outstanding issues in waste-form science via NEXAFS investigations and to translate this understanding into better waste-form materials, followed by eventual capability to investigate 'real' waste-form materials by the same methodology. We conducted several detailed structural investigations of both pyrochlore ceramic and borosilicate-glass materials during the project and developed improved capabilities at Beamline 6.3.1 of the Advanced Light Source (ALS) to perform the studies.

  11. Molecular Environmental Science Using Synchrotron Radiation: Chemistry and Physics of Waste Form Materials

    Energy Technology Data Exchange (ETDEWEB)

    Lindle, Dennis W.

    2011-04-21

    Production of defense-related nuclear materials has generated large volumes of complex chemical wastes containing a mixture of radionuclides. The disposition of these wastes requires conversion of the liquid and solid-phase components into durable, solid forms suitable for long-term immobilization. Specially formulated glass compositions and ceramics such as pyrochlores and apatites are the main candidates for these wastes. An important consideration linked to the durability of waste-form materials is the local structure around the waste components. Equally important is the local structure of constituents of the glass and ceramic host matrix. Knowledge of the structure in the waste-form host matrices is essential, prior to and subsequent to waste incorporation, to evaluate and develop improved waste-form compositions based on scientific considerations. This project used the soft-x-ray synchrotron-radiation-based technique of near-edge x-ray-absorption fine structure (NEXAFS) as a unique method for investigating oxidation states and structures of low-Z elemental constituents forming the backbones of glass and ceramic host matrices for waste-form materials. In addition, light metal ions in ceramic hosts, such as titanium, are also ideal for investigation by NEXAFS in the soft-x-ray region. Thus, one of the main objectives was to understand outstanding issues in waste-form science via NEXAFS investigations and to translate this understanding into better waste-form materials, followed by eventual capability to investigate “real” waste-form materials by the same methodology. We conducted several detailed structural investigations of both pyrochlore ceramic and borosilicate-glass materials during the project and developed improved capabilities at Beamline 6.3.1 of the Advanced Light Source (ALS) to perform the studies.

  12. Traditional machining processes research advances

    CERN Document Server

    2015-01-01

    This book collects several examples of research in machining processes. Chapter 1 provides information on polycrystalline diamond tool material and its emerging applications. Chapter 2 is dedicated to the analysis of orthogonal cutting experiments using diamond-coated tools with force and temperature measurements. Chapter 3 describes the estimation of cutting forces and tool wear using modified mechanistic models in high performance turning. Chapter 4 contains information on cutting under gas shields for industrial applications. Chapter 5 is dedicated to the machinability of magnesium and its alloys. Chapter 6 provides information on grinding science. Finally, chapter 7 is dedicated to flexible integration of shape and functional modelling of machine tool spindles in a design framework.    

  13. Build your own time machine

    CERN Document Server

    Clegg, Brian

    2012-01-01

    There is no physical law to prevent time travel nothing in physics to say it is impossible. So who is to say it can't be done? In Build Your Own Time Machine, acclaimed science writer Brian Clegg takes inspiration from his childhood heroes, Doctor Who and H. G. Wells, to explain the nature of time. How do we understand it and why measure it the way we do? How did the theories of one man change the way time was perceived by the world? Why wouldn't H. G. Wells's time machine have worked? And what would we need to do to make a real one? Build Your Own Time Machine explores the amazing possib

  14. Proceedings of DAE-BRNS life sciences symposium 2011 on advances in molecular and cell biology of stress response

    International Nuclear Information System (INIS)

    2011-01-01

    This series of symposia in life sciences was initiated for the purpose of facilitating strong interactions among the national research fraternity working in the areas of bio-medical and agricultural sciences of relevance and interest for the Department of Atomic Energy, Government of India. Dedicated research efforts in the Bhabha Atomic Research Centre and other DAE institutions for nearly four decades have not only resulted in the development of technologies and products to improve the quality of human life, but have made impactful contributions in several contemporary areas in basic biological sciences. It is natural that keep visiting certain themes more than once. Biology of stress response is one such theme. The first symposium in the series was devoted to this field. And six years is long enough a time for catching up with the new developments. Stress to a system at equilibrium induces homeostatic mechanisms that ameliorate the stress. Entire living world, from microbes to man, have evolved such response mechanisms. Often a given battery of responsive genes may take care of more than one stresses and there may also be some redundancy in signalling or effector pathways to a response. Oxidative stress in one of the most common stresses that most living systems have to endure. Such a stress could be induced by a wide variety of insults including ionizing radiation, visible light, antibiotics, xenobiotics, metal ions, environmental pollutants, carcinogens, infectious agents etc. It may contribute to some inflammatory and autoimmune diseases. It also plays an important role in killing of intracellular pathogens. In recent years mechanistic details of body's antioxidant defences are being increasingly revealed. Even more interesting are the new findings that suggest that prooxidants may induce an adaptive response to help cells survive against death induced by higher levels of reactive oxygen species (ROS). The role of prosurvival transcription factors like NRF-2

  15. Machine technology: a survey

    International Nuclear Information System (INIS)

    Barbier, M.M.

    1981-01-01

    An attempt was made to find existing machines that have been upgraded and that could be used for large-scale decontamination operations outdoors. Such machines are in the building industry, the mining industry, and the road construction industry. The road construction industry has yielded the machines in this presentation. A review is given of operations that can be done with the machines available

  16. Machine Shop Lathes.

    Science.gov (United States)

    Dunn, James

    This guide, the second in a series of five machine shop curriculum manuals, was designed for use in machine shop courses in Oklahoma. The purpose of the manual is to equip students with basic knowledge and skills that will enable them to enter the machine trade at the machine-operator level. The curriculum is designed so that it can be used in…

  17. Superconducting rotating machines

    International Nuclear Information System (INIS)

    Smith, J.L. Jr.; Kirtley, J.L. Jr.; Thullen, P.

    1975-01-01

    The opportunities and limitations of the applications of superconductors in rotating electric machines are given. The relevant properties of superconductors and the fundamental requirements for rotating electric machines are discussed. The current state-of-the-art of superconducting machines is reviewed. Key problems, future developments and the long range potential of superconducting machines are assessed

  18. Machine learning: Trends, perspectives, and prospects.

    Science.gov (United States)

    Jordan, M I; Mitchell, T M

    2015-07-17

    Machine learning addresses the question of how to build computers that improve automatically through experience. It is one of today's most rapidly growing technical fields, lying at the intersection of computer science and statistics, and at the core of artificial intelligence and data science. Recent progress in machine learning has been driven both by the development of new learning algorithms and theory and by the ongoing explosion in the availability of online data and low-cost computation. The adoption of data-intensive machine-learning methods can be found throughout science, technology and commerce, leading to more evidence-based decision-making across many walks of life, including health care, manufacturing, education, financial modeling, policing, and marketing. Copyright © 2015, American Association for the Advancement of Science.

  19. A proposal to establish an international network in molecular microbiology and genetic engineering for scientific cooperation and prevention of misuse of biological sciences in the framework of science for peace

    International Nuclear Information System (INIS)

    Becker, Y.

    1998-01-01

    The conference on 'Science and Technology for Construction of Peace' which was organized by the Landau Network Coordination Center and A. Volta Center for Scientific Culture dealt with conversion of military and technological capacities into sustainable civilian application. The ideas regarding the conversion of nuclear warheads into nuclear energy for civilian-use led to the idea that the extension of this trend of thought to molecular biology and genetic engineering, will be a useful contribution to Science for Peace. This idea of developing a Cooperation Network in Molecular Biology and Genetic Engineering that will function parallel to and with the Landau Network Coordination in the 'A. Volta' Center was discussed in the Second International Symposium on Science for Peace, Jerusalem, January 1997. It is the reason for the inclusion of the biological aspects in the deliberations of our Forum. It is hoped that the establishment of an international network in molecular biology and genetic engineering, similar to the Landau Network in physics, will support and achieve the decommissioning of biological weapons. Such a network in microbiology and genetic engineering will contribute to the elimination of biological weapons and to contributions to Science for Peace and to Culture of Peace activities of UNESCO. (author)

  20. Data Science in the Research Domain Criteria Era: Relevance of Machine Learning to the Study of Stress Pathology, Recovery, and Resilience.

    Science.gov (United States)

    Galatzer-Levy, Isaac R; Ruggles, Kelly; Chen, Zhe

    2018-01-01

    Diverse environmental and biological systems interact to influence individual differences in response to environmental stress. Understanding the nature of these complex relationships can enhance the development of methods to: (1) identify risk, (2) classify individuals as healthy or ill, (3) understand mechanisms of change, and (4) develop effective treatments. The Research Domain Criteria (RDoC) initiative provides a theoretical framework to understand health and illness as the product of multiple inter-related systems but does not provide a framework to characterize or statistically evaluate such complex relationships. Characterizing and statistically evaluating models that integrate multiple levels (e.g. synapses, genes, environmental factors) as they relate to outcomes that a free from prior diagnostic benchmarks represents a challenge requiring new computational tools that are capable to capture complex relationships and identify clinically relevant populations. In the current review, we will summarize machine learning methods that can achieve these goals.

  1. Molecular Modeling

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 9; Issue 5. Molecular Modeling: A Powerful Tool for Drug Design and Molecular Docking. Rama Rao Nadendla. General Article Volume 9 Issue 5 May 2004 pp 51-60. Fulltext. Click here to view fulltext PDF. Permanent link:

  2. science

    International Development Research Centre (IDRC) Digital Library (Canada)

    David Spurgeon

    Give us the tools: science and technology for development. Ottawa, ...... altered technical rela- tionships among the factors used in the process of production, and the en- .... to ourselves only the rights of audit and periodic substantive review." If a ...... and destroying scarce water reserves, recreational areas and a generally.

  3. Nonlinear machine learning in soft materials engineering and design

    Science.gov (United States)

    Ferguson, Andrew

    The inherently many-body nature of molecular folding and colloidal self-assembly makes it challenging to identify the underlying collective mechanisms and pathways governing system behavior, and has hindered rational design of soft materials with desired structure and function. Fundamentally, there exists a predictive gulf between the architecture and chemistry of individual molecules or colloids and the collective many-body thermodynamics and kinetics. Integrating machine learning techniques with statistical thermodynamics provides a means to bridge this divide and identify emergent folding pathways and self-assembly mechanisms from computer simulations or experimental particle tracking data. We will survey a few of our applications of this framework that illustrate the value of nonlinear machine learning in understanding and engineering soft materials: the non-equilibrium self-assembly of Janus colloids into pinwheels, clusters, and archipelagos; engineering reconfigurable ''digital colloids'' as a novel high-density information storage substrate; probing hierarchically self-assembling onjugated asphaltenes in crude oil; and determining macromolecular folding funnels from measurements of single experimental observables. We close with an outlook on the future of machine learning in soft materials engineering, and share some personal perspectives on working at this disciplinary intersection. We acknowledge support for this work from a National Science Foundation CAREER Award (Grant No. DMR-1350008) and the Donors of the American Chemical Society Petroleum Research Fund (ACS PRF #54240-DNI6).

  4. TH-C-17A-06: A Hardware Implementation and Evaluation of Robotic SPECT: Toward Molecular Imaging Onboard Radiation Therapy Machines

    International Nuclear Information System (INIS)

    Yan, S; Touch, M; Bowsher, J; Yin, F; Cheng, L

    2014-01-01

    Purpose: To construct a robotic SPECT system and demonstrate its capability to image a thorax phantom on a radiation therapy flat-top couch. The system has potential for on-board functional and molecular imaging in radiation therapy. Methods: A robotic SPECT imaging system was developed utilizing a Digirad 2020tc detector and a KUKA KR150-L110 robot. An imaging study was performed with the PET CT Phantom, which includes 5 spheres: 10, 13, 17, 22 and 28 mm in diameter. Sphere-tobackground concentration ratio was 6:1 of Tc99m. The phantom was placed on a flat-top couch. SPECT projections were acquired with a parallel-hole collimator and a single pinhole collimator. The robotic system navigated the detector tracing the flat-top table to maintain the closest possible proximity to the phantom. For image reconstruction, detector trajectories were described by six parameters: radius-of-rotation, x and z detector shifts, and detector rotation θ, tilt ϕ and twist γ. These six parameters were obtained from the robotic system by calibrating the robot base and tool coordinates. Results: The robotic SPECT system was able to maneuver parallel-hole and pinhole collimated SPECT detectors in close proximity to the phantom, minimizing impact of the flat-top couch on detector-to-COR (center-ofrotation) distance. In acquisitions with background at 1/6th sphere activity concentration, photopeak contamination was heavy, yet the 17, 22, and 28 mm diameter spheres were readily observed with the parallel hole imaging, and the single, targeted sphere (28 mm diameter) was readily observed in the pinhole region-of-interest (ROI) imaging. Conclusion: Onboard SPECT could be achieved by a robot maneuvering a SPECT detector about patients in position for radiation therapy on a flat-top couch. The robot inherent coordinate frame could be an effective means to estimate detector pose for use in SPECT image reconstruction. PHS/NIH/NCI grant R21-CA156390-01A1

  5. Articles on Practical Cybernetics. Computer-Developed Computers; Heuristics and Modern Sciences; Linguistics and Practice; Cybernetics and Moral-Ethical Considerations; and Men and Machines at the Chessboard.

    Science.gov (United States)

    Berg, A. I.; And Others

    Five articles which were selected from a Russian language book on cybernetics and then translated are presented here. They deal with the topics of: computer-developed computers, heuristics and modern sciences, linguistics and practice, cybernetics and moral-ethical considerations, and computer chess programs. (Author/JY)

  6. PARTIAL SUPPORT OF THE COMMITTEE OF ATOMIC, MOLECULAR, AND OPTICAL SCIENCES Final Report for the period September 30, 2008 to June 30, 2014

    Energy Technology Data Exchange (ETDEWEB)

    Lancaster, James

    2015-06-29

    This report is the final report for the 2008-2014 cycle of DOE support for the Committee on Atomic, Molecular, and Optical Sciences. Highlights of the committee’s activities over this period included: • Meetings of the committee were held semiannually (Washington, DC in April and Irvine, CA in October) for four of the six years and annually the last two years (Washington, DC in April). • Committee meetings included half-day focus sessions on each of the areas identified in the last AMO decadal survey as having great scientific promise and short summaries of the focus session were prepared and delivered to sponsoring agencies. • CAMOS initiated a study that has been funded on high intensity lasers. DOE support for CAMOS has been of central importance to the committee’s ability to continue to fulfill its mandate to the Board on Physics and Astronomy and to the wider atomic, molecular, and optical sciences research community.

  7. Nanotechnology: A molecular assembler

    Science.gov (United States)

    Kelly, T. Ross; Snapper, Marc L.

    2017-09-01

    The idea of nanometre-scale machines that can assemble molecules has long been thought of as the stuff of science fiction. Such a machine has now been built -- and might herald a new model for organic synthesis. See Letter p.374

  8. Using Phun to Study ``Perpetual Motion'' Machines

    Science.gov (United States)

    Koreš, Jaroslav

    2012-05-01

    The concept of "perpetual motion" has a long history. The Indian astronomer and mathematician Bhaskara II (12th century) was the first person to describe a perpetual motion (PM) machine. An example of a 13th- century PM machine is shown in Fig. 1. Although the law of conservation of energy clearly implies the impossibility of PM construction, over the centuries numerous proposals for PM have been made, involving ever more elements of modern science in their construction. It is possible to test a variety of PM machines in the classroom using a program called Phun2 or its commercial version Algodoo.3 The programs are designed to simulate physical processes and we can easily simulate mechanical machines using them. They provide an intuitive graphical environment controlled with a mouse; a programming language is not needed. This paper describes simulations of four different (supposed) PM machines.4

  9. Understanding the influence of buckwheat bran on wheat dough baking performance: Mechanistic insights from molecular and material science approaches.

    Science.gov (United States)

    Zanoletti, Miriam; Marti, Alessandra; Marengo, Mauro; Iametti, Stefania; Pagani, M Ambrogina; Renzetti, Stefano

    2017-12-01

    A molecular and material science approach is used to describe the influence of coarse and fine buckwheat bran on wheat dough properties and bread textural quality. Focus is given on (i) gluten solvation and structural arrangements in presence of bran as studied by front-face fluorescence; (ii) thermo-mechanical behavior of dough during heating studied by dynamic mechanical thermal analysis and (iii) texture of bread crumb analyzed in terms of a cellular solid. The thermo-mechanical behavior of dough was found to be largely related to starch phase transitions during heating. The use of thermodynamic approaches to biopolymer melting revealed that key transitions such as the onset of starch gelatinization were function of the interplay of water and bran volume fractions in the dough. Front-face fluorescence studies in wheat dough revealed that gluten solvation and structural arrangements were delayed by increasing bran addition level and reduction in particle size, as indicated by the drastic decrease in the protein surface hydrophobicity index. Variations in gluten structure could be strongly related to dough baking performance, i.e. specific volume. With regards to texture, the approach revealed that crumb texture was controlled by variations in density, moisture and bran volume fractions. Overall, this study elucidates a number of physical mechanisms describing the influence of buckwheat bran addition to dough and bread quality. These mechanisms strongly pointed at the influence of bran on water partitioning among the main polymeric components. In the future, these mechanisms should be investigated with bran material of varying source, composition and structure. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Machine tool structures

    CERN Document Server

    Koenigsberger, F

    1970-01-01

    Machine Tool Structures, Volume 1 deals with fundamental theories and calculation methods for machine tool structures. Experimental investigations into stiffness are discussed, along with the application of the results to the design of machine tool structures. Topics covered range from static and dynamic stiffness to chatter in metal cutting, stability in machine tools, and deformations of machine tool structures. This volume is divided into three sections and opens with a discussion on stiffness specifications and the effect of stiffness on the behavior of the machine under forced vibration c

  11. [Analysis of hot spots and trend of molecular pharmacognosy research based on project supported by National Natural Science Foundation of 1995-2014].

    Science.gov (United States)

    Wang, Jun-Wen; Liu, Yang; Tong, Yuan-Yuan; Yang, Ce; Li, Hai-Yan

    2016-05-01

    This study collected 1995-2014 molecular pharmacognosy study, a total of 595 items, funded by Natural Science Foundation of China (NSFC). TDA and Excel software were used to analyze the data of the projects about general situation, hot spots of research with rank analytic and correlation analytic methods. Supported by NSFC molecular pharmacognosy projects and funding a gradual increase in the number of, the proportion of funds for pharmaceutical research funding tends to be stable; mainly supported by molecular biology methods of genuine medicinal materials, secondary metabolism and Germplasm Resources Research; hot drugs including Radix Salviae Miltiorrhizae, Radix Rehmanniae, Cordyceps sinensis, hot contents including tanshinone biosynthesis, Rehmannia glutinosa continuous cropping obstacle. Copyright© by the Chinese Pharmaceutical Association.

  12. Probabilistic machine learning and artificial intelligence.

    Science.gov (United States)

    Ghahramani, Zoubin

    2015-05-28

    How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.

  13. Probabilistic machine learning and artificial intelligence

    Science.gov (United States)

    Ghahramani, Zoubin

    2015-05-01

    How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.

  14. Design of full body workout machine

    OpenAIRE

    Pathak, Suman

    2017-01-01

    The purpose of this thesis was to design a full body workout machine. The main goal was to make a workout machine that was inexpensive, covered a small area and light in weight. This thesis was commissioned by HAMK University of Applied Sciences. This topic was proposed by the author himself after realizing the need for an ideal workout machine that would fulfil all one´s requirements. He had been going to gym regularly for two years. Based on his experience, gyms were overcrowded with eq...

  15. Decadal Assessment and Outlook Report on Atomic Molecular and Optical Science. Final Progress Report to the Department of Energy

    International Nuclear Information System (INIS)

    Donald Shapero; Michael Moloney

    2006-01-01

    The committee was charged to produce a comprehensive report on the status of AMO Science. The committee was charged to produce a report that: 1. Reviewed the field of AMO science, emphasize recent accomplishments, and identify new opportunities and compelling scientific questions; 2. Identified the impact of AMO science on other scientific fields, emerging technologies, and national needs; 3. Identified future workforce, societal and educational needs for AMO science; and 4. Made recommendations on how the US research enterprise might realize the full potential of AMO science. The committee also produced an intermediate report addressing key research issues and themes facing the research community

  16. Quantum cloning machines and the applications

    Energy Technology Data Exchange (ETDEWEB)

    Fan, Heng, E-mail: hfan@iphy.ac.cn [Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences, Beijing 100190 (China); Collaborative Innovation Center of Quantum Matter, Beijing 100190 (China); Wang, Yi-Nan; Jing, Li [School of Physics, Peking University, Beijing 100871 (China); Yue, Jie-Dong [Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences, Beijing 100190 (China); Shi, Han-Duo; Zhang, Yong-Liang; Mu, Liang-Zhu [School of Physics, Peking University, Beijing 100871 (China)

    2014-11-20

    No-cloning theorem is fundamental for quantum mechanics and for quantum information science that states an unknown quantum state cannot be cloned perfectly. However, we can try to clone a quantum state approximately with the optimal fidelity, or instead, we can try to clone it perfectly with the largest probability. Thus various quantum cloning machines have been designed for different quantum information protocols. Specifically, quantum cloning machines can be designed to analyze the security of quantum key distribution protocols such as BB84 protocol, six-state protocol, B92 protocol and their generalizations. Some well-known quantum cloning machines include universal quantum cloning machine, phase-covariant cloning machine, the asymmetric quantum cloning machine and the probabilistic quantum cloning machine. In the past years, much progress has been made in studying quantum cloning machines and their applications and implementations, both theoretically and experimentally. In this review, we will give a complete description of those important developments about quantum cloning and some related topics. On the other hand, this review is self-consistent, and in particular, we try to present some detailed formulations so that further study can be taken based on those results.

  17. Quantum cloning machines and the applications

    International Nuclear Information System (INIS)

    Fan, Heng; Wang, Yi-Nan; Jing, Li; Yue, Jie-Dong; Shi, Han-Duo; Zhang, Yong-Liang; Mu, Liang-Zhu

    2014-01-01

    No-cloning theorem is fundamental for quantum mechanics and for quantum information science that states an unknown quantum state cannot be cloned perfectly. However, we can try to clone a quantum state approximately with the optimal fidelity, or instead, we can try to clone it perfectly with the largest probability. Thus various quantum cloning machines have been designed for different quantum information protocols. Specifically, quantum cloning machines can be designed to analyze the security of quantum key distribution protocols such as BB84 protocol, six-state protocol, B92 protocol and their generalizations. Some well-known quantum cloning machines include universal quantum cloning machine, phase-covariant cloning machine, the asymmetric quantum cloning machine and the probabilistic quantum cloning machine. In the past years, much progress has been made in studying quantum cloning machines and their applications and implementations, both theoretically and experimentally. In this review, we will give a complete description of those important developments about quantum cloning and some related topics. On the other hand, this review is self-consistent, and in particular, we try to present some detailed formulations so that further study can be taken based on those results

  18. MITS machine operations

    International Nuclear Information System (INIS)

    Flinchem, J.

    1980-01-01

    This document contains procedures which apply to operations performed on individual P-1c machines in the Machine Interface Test System (MITS) at AiResearch Manufacturing Company's Torrance, California Facility

  19. Brain versus Machine Control.

    Directory of Open Access Journals (Sweden)

    Jose M Carmena

    2004-12-01

    Full Text Available Dr. Octopus, the villain of the movie "Spiderman 2", is a fusion of man and machine. Neuroscientist Jose Carmena examines the facts behind this fictional account of a brain- machine interface

  20. Applied machining technology

    CERN Document Server

    Tschätsch, Heinz

    2010-01-01

    Machining and cutting technologies are still crucial for many manufacturing processes. This reference presents all important machining processes in a comprehensive and coherent way. It includes many examples of concrete calculations, problems and solutions.

  1. Machining with abrasives

    CERN Document Server

    Jackson, Mark J

    2011-01-01

    Abrasive machining is key to obtaining the desired geometry and surface quality in manufacturing. This book discusses the fundamentals and advances in the abrasive machining processes. It provides a complete overview of developing areas in the field.

  2. Man-machine interactions 3

    CERN Document Server

    Czachórski, Tadeusz; Kozielski, Stanisław

    2014-01-01

    Man-Machine Interaction is an interdisciplinary field of research that covers many aspects of science focused on a human and machine in conjunction.  Basic goal of the study is to improve and invent new ways of communication between users and computers, and many different subjects are involved to reach the long-term research objective of an intuitive, natural and multimodal way of interaction with machines.  The rapid evolution of the methods by which humans interact with computers is observed nowadays and new approaches allow using computing technologies to support people on the daily basis, making computers more usable and receptive to the user's needs.   This monograph is the third edition in the series and presents important ideas, current trends and innovations in  the man-machine interactions area.  The aim of this book is to introduce not only hardware and software interfacing concepts, but also to give insights into the related theoretical background. Reader is provided with a compilation of high...

  3. Machine learning topological states

    Science.gov (United States)

    Deng, Dong-Ling; Li, Xiaopeng; Das Sarma, S.

    2017-11-01

    Artificial neural networks and machine learning have now reached a new era after several decades of improvement where applications are to explode in many fields of science, industry, and technology. Here, we use artificial neural networks to study an intriguing phenomenon in quantum physics—the topological phases of matter. We find that certain topological states, either symmetry-protected or with intrinsic topological order, can be represented with classical artificial neural networks. This is demonstrated by using three concrete spin systems, the one-dimensional (1D) symmetry-protected topological cluster state and the 2D and 3D toric code states with intrinsic topological orders. For all three cases, we show rigorously that the topological ground states can be represented by short-range neural networks in an exact and efficient fashion—the required number of hidden neurons is as small as the number of physical spins and the number of parameters scales only linearly with the system size. For the 2D toric-code model, we find that the proposed short-range neural networks can describe the excited states with Abelian anyons and their nontrivial mutual statistics as well. In addition, by using reinforcement learning we show that neural networks are capable of finding the topological ground states of nonintegrable Hamiltonians with strong interactions and studying their topological phase transitions. Our results demonstrate explicitly the exceptional power of neural networks in describing topological quantum states, and at the same time provide valuable guidance to machine learning of topological phases in generic lattice models.

  4. Machine protection systems

    CERN Document Server

    Macpherson, A L

    2010-01-01

    A summary of the Machine Protection System of the LHC is given, with particular attention given to the outstanding issues to be addressed, rather than the successes of the machine protection system from the 2009 run. In particular, the issues of Safe Machine Parameter system, collimation and beam cleaning, the beam dump system and abort gap cleaning, injection and dump protection, and the overall machine protection program for the upcoming run are summarised.

  5. Dictionary of machine terms

    International Nuclear Information System (INIS)

    1990-06-01

    This book has introduction of dictionary of machine terms, and a compilation committee and introductory remarks. It gives descriptions of the machine terms in alphabetical order from a to Z and also includes abbreviation of machine terms and symbol table, way to read mathematical symbols and abbreviation and terms of drawings.

  6. Mankind, machines and people

    Energy Technology Data Exchange (ETDEWEB)

    Hugli, A

    1984-01-01

    The following questions are addressed: is there a difference between machines and men, between human communication and communication with machines. Will we ever reach the point when the dream of artificial intelligence becomes a reality. Will thinking machines be able to replace the human spirit in all its aspects. Social consequences and philosophical aspects are addressed. 8 references.

  7. A Universal Reactive Machine

    DEFF Research Database (Denmark)

    Andersen, Henrik Reif; Mørk, Simon; Sørensen, Morten U.

    1997-01-01

    Turing showed the existence of a model universal for the set of Turing machines in the sense that given an encoding of any Turing machine asinput the universal Turing machine simulates it. We introduce the concept of universality for reactive systems and construct a CCS processuniversal...

  8. HTS machine laboratory prototype

    DEFF Research Database (Denmark)

    machine. The machine comprises six stationary HTS field windings wound from both YBCO and BiSCOO tape operated at liquid nitrogen temperature and enclosed in a cryostat, and a three phase armature winding spinning at up to 300 rpm. This design has full functionality of HTS synchronous machines. The design...

  9. Your Sewing Machine.

    Science.gov (United States)

    Peacock, Marion E.

    The programed instruction manual is designed to aid the student in learning the parts, uses, and operation of the sewing machine. Drawings of sewing machine parts are presented, and space is provided for the student's written responses. Following an introductory section identifying sewing machine parts, the manual deals with each part and its…

  10. Quantum machine learning.

    Science.gov (United States)

    Biamonte, Jacob; Wittek, Peter; Pancotti, Nicola; Rebentrost, Patrick; Wiebe, Nathan; Lloyd, Seth

    2017-09-13

    Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Quantum systems produce atypical patterns that classical systems are thought not to produce efficiently, so it is reasonable to postulate that quantum computers may outperform classical computers on machine learning tasks. The field of quantum machine learning explores how to devise and implement quantum software that could enable machine learning that is faster than that of classical computers. Recent work has produced quantum algorithms that could act as the building blocks of machine learning programs, but the hardware and software challenges are still considerable.

  11. Asynchronized synchronous machines

    CERN Document Server

    Botvinnik, M M

    1964-01-01

    Asynchronized Synchronous Machines focuses on the theoretical research on asynchronized synchronous (AS) machines, which are "hybrids” of synchronous and induction machines that can operate with slip. Topics covered in this book include the initial equations; vector diagram of an AS machine; regulation in cases of deviation from the law of full compensation; parameters of the excitation system; and schematic diagram of an excitation regulator. The possible applications of AS machines and its calculations in certain cases are also discussed. This publication is beneficial for students and indiv

  12. COMPUTATIONAL SCIENCE CENTER

    International Nuclear Information System (INIS)

    DAVENPORT, J.

    2006-01-01

    Computational Science is an integral component of Brookhaven's multi science mission, and is a reflection of the increased role of computation across all of science. Brookhaven currently has major efforts in data storage and analysis for the Relativistic Heavy Ion Collider (RHIC) and the ATLAS detector at CERN, and in quantum chromodynamics. The Laboratory is host for the QCDOC machines (quantum chromodynamics on a chip), 10 teraflop/s computers which boast 12,288 processors each. There are two here, one for the Riken/BNL Research Center and the other supported by DOE for the US Lattice Gauge Community and other scientific users. A 100 teraflop/s supercomputer will be installed at Brookhaven in the coming year, managed jointly by Brookhaven and Stony Brook, and funded by a grant from New York State. This machine will be used for computational science across Brookhaven's entire research program, and also by researchers at Stony Brook and across New York State. With Stony Brook, Brookhaven has formed the New York Center for Computational Science (NYCCS) as a focal point for interdisciplinary computational science, which is closely linked to Brookhaven's Computational Science Center (CSC). The CSC has established a strong program in computational science, with an emphasis on nanoscale electronic structure and molecular dynamics, accelerator design, computational fluid dynamics, medical imaging, parallel computing and numerical algorithms. We have been an active participant in DOES SciDAC program (Scientific Discovery through Advanced Computing). We are also planning a major expansion in computational biology in keeping with Laboratory initiatives. Additional laboratory initiatives with a dependence on a high level of computation include the development of hydrodynamics models for the interpretation of RHIC data, computational models for the atmospheric transport of aerosols, and models for combustion and for energy utilization. The CSC was formed to bring together

  13. COMPUTATIONAL SCIENCE CENTER

    Energy Technology Data Exchange (ETDEWEB)

    DAVENPORT, J.

    2006-11-01

    Computational Science is an integral component of Brookhaven's multi science mission, and is a reflection of the increased role of computation across all of science. Brookhaven currently has major efforts in data storage and analysis for the Relativistic Heavy Ion Collider (RHIC) and the ATLAS detector at CERN, and in quantum chromodynamics. The Laboratory is host for the QCDOC machines (quantum chromodynamics on a chip), 10 teraflop/s computers which boast 12,288 processors each. There are two here, one for the Riken/BNL Research Center and the other supported by DOE for the US Lattice Gauge Community and other scientific users. A 100 teraflop/s supercomputer will be installed at Brookhaven in the coming year, managed jointly by Brookhaven and Stony Brook, and funded by a grant from New York State. This machine will be used for computational science across Brookhaven's entire research program, and also by researchers at Stony Brook and across New York State. With Stony Brook, Brookhaven has formed the New York Center for Computational Science (NYCCS) as a focal point for interdisciplinary computational science, which is closely linked to Brookhaven's Computational Science Center (CSC). The CSC has established a strong program in computational science, with an emphasis on nanoscale electronic structure and molecular dynamics, accelerator design, computational fluid dynamics, medical imaging, parallel computing and numerical algorithms. We have been an active participant in DOES SciDAC program (Scientific Discovery through Advanced Computing). We are also planning a major expansion in computational biology in keeping with Laboratory initiatives. Additional laboratory initiatives with a dependence on a high level of computation include the development of hydrodynamics models for the interpretation of RHIC data, computational models for the atmospheric transport of aerosols, and models for combustion and for energy utilization. The CSC was formed to

  14. Machine Phase Fullerene Nanotechnology: 1996

    Science.gov (United States)

    Globus, Al; Chancellor, Marisa K. (Technical Monitor)

    1997-01-01

    NASA has used exotic materials for spacecraft and experimental aircraft to good effect for many decades. In spite of many advances, transportation to space still costs about $10,000 per pound. Drexler has proposed a hypothetical nanotechnology based on diamond and investigated the properties of such molecular systems. These studies and others suggest enormous potential for aerospace systems. Unfortunately, methods to realize diamonoid nanotechnology are at best highly speculative. Recent computational efforts at NASA Ames Research Center and computation and experiment elsewhere suggest that a nanotechnology of machine phase functionalized fullerenes may be synthetically relatively accessible and of great aerospace interest. Machine phase materials are (hypothetical) materials consisting entirely or in large part of microscopic machines. In a sense, most living matter fits this definition. To begin investigation of fullerene nanotechnology, we used molecular dynamics to study the properties of carbon nanotube based gears and gear/shaft configurations. Experiments on C60 and quantum calculations suggest that benzyne may react with carbon nanotubes to form gear teeth. Han has computationally demonstrated that molecular gears fashioned from (14,0) single-walled carbon nanotubes and benzyne teeth should operate well at 50-100 gigahertz. Results suggest that rotation can be converted to rotating or linear motion, and linear motion may be converted into rotation. Preliminary results suggest that these mechanical systems can be cooled by a helium atmosphere. Furthermore, Deepak has successfully simulated using helical electric fields generated by a laser to power fullerene gears once a positive and negative charge have been added to form a dipole. Even with mechanical motion, cooling, and power; creating a viable nanotechnology requires support structures, computer control, a system architecture, a variety of components, and some approach to manufacture. Additional

  15. The Science of Pizza: The Molecular Origins of Cheese, Bread, and Digestion Using Interactive Activities for the General Public

    Science.gov (United States)

    Rowat, Amy C.; Rosenberg, Daniel; Hollar, Kathryn A.; Stone, Howard A.

    2010-01-01

    We describe a presentation on the science of pizza, which is designed for the general public including children ages 6 and older. The presentation focuses on the science of making and digesting cheese and bread. We highlight 4 major scientific themes: (1) how macromolecules such as carbohydrates and proteins are composed of atoms and small…

  16. Amplification macroscopique de mouvements nanométriques induits par des machines moléculaires

    OpenAIRE

    Goujon , Antoine

    2016-01-01

    The last twenty years have seen tremendous progresses in the design and synthesis of complex molecular machines, often inspired by the beauty of the machinery found in biological systems. However, amplification of the molecular machines motion over several orders of magnitude above their typical length scale is still an ambitious challenge. This work describes how self-organization of molecular machines or motors allows for the synthesis of materials translating the motions of their component...

  17. Using Machine Learning to Advance Personality Assessment and Theory.

    Science.gov (United States)

    Bleidorn, Wiebke; Hopwood, Christopher James

    2018-05-01

    Machine learning has led to important advances in society. One of the most exciting applications of machine learning in psychological science has been the development of assessment tools that can powerfully predict human behavior and personality traits. Thus far, machine learning approaches to personality assessment have focused on the associations between social media and other digital records with established personality measures. The goal of this article is to expand the potential of machine learning approaches to personality assessment by embedding it in a more comprehensive construct validation framework. We review recent applications of machine learning to personality assessment, place machine learning research in the broader context of fundamental principles of construct validation, and provide recommendations for how to use machine learning to advance our understanding of personality.

  18. Development of brewing science in (and since) the late 19th century: molecular profiles of 110-130 year old beers

    DEFF Research Database (Denmark)

    Walther, Andrea; Ravasio, Davide; Qin, Fen

    2015-01-01

    The 19th century witnessed many advances in scientific enzymology and microbiology that laid the foundations for modern biotechnological industries. In the current study, we analyze the content of original lager beer samples from the 1880s, 1890s and 1900s with emphasis on the carbohydrate content......, with decreasing contamination by enzymatic and microbial activities over this time span. Samples are sufficiently well preserved to allow comparisons to present-day references, thus yielding molecular signatures of the effects of 20th century science on beer production. Opposite to rather stable carbohydrate...

  19. Report of the joint seminar on solid state physics, atomic and molecular physics, and materials science in the energy region of tandem accelerators

    International Nuclear Information System (INIS)

    Kazumata, Yukio

    1993-01-01

    The joint seminar on Solid State Physics, Atomic and Molecular Physics and Materials Science in the Energy Region of Tandem Acceleration was held at Tokai Research Establishment of JAERI, for two days from January 22 to 23, 1991. About 60 physicists and material scientists participated and 18 papers were presented in this seminar. The topics presented in this seminar included lattice defects in semiconductors, ion-solid collisions, atomic collisions by high energy particles, radiation effects on high T c superconducting materials and FCC metals, radiation effects on materials of space and fusion reactors, uranium compounds and superlattice. (J.P.N.)

  20. Applying Machine Learning to Facilitate Autism Diagnostics: Pitfalls and Promises

    Science.gov (United States)

    Bone, Daniel; Goodwin, Matthew S.; Black, Matthew P.; Lee, Chi-Chun; Audhkhasi, Kartik; Narayanan, Shrikanth

    2015-01-01

    Machine learning has immense potential to enhance diagnostic and intervention research in the behavioral sciences, and may be especially useful in investigations involving the highly prevalent and heterogeneous syndrome of autism spectrum disorder. However, use of machine learning in the absence of clinical domain expertise can be tenuous and lead…

  1. RNA Polymerase II–The Transcription Machine

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 12; Issue 3. RNA Polymerase II – The Transcription Machine - Nobel Prize in Chemistry 2006. Jiyoti Verma Aruna Naorem Anand Kumar Manimala Sen Parag Sadhale. General Article Volume 12 Issue 3 March 2007 pp 47-53 ...

  2. Of Slot Machines and Broken Test Tubes

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 19; Issue 5. Of Slot Machines and Broken Test Tubes. S Mahadevan. General Article Volume 19 Issue 5 May 2014 pp 395-405. Fulltext. Click here to view fulltext PDF. Permanent link: https://www.ias.ac.in/article/fulltext/reso/019/05/0395-0405. Keywords.

  3. Pattern recognition & machine learning

    CERN Document Server

    Anzai, Y

    1992-01-01

    This is the first text to provide a unified and self-contained introduction to visual pattern recognition and machine learning. It is useful as a general introduction to artifical intelligence and knowledge engineering, and no previous knowledge of pattern recognition or machine learning is necessary. Basic for various pattern recognition and machine learning methods. Translated from Japanese, the book also features chapter exercises, keywords, and summaries.

  4. Support vector machines applications

    CERN Document Server

    Guo, Guodong

    2014-01-01

    Support vector machines (SVM) have both a solid mathematical background and good performance in practical applications. This book focuses on the recent advances and applications of the SVM in different areas, such as image processing, medical practice, computer vision, pattern recognition, machine learning, applied statistics, business intelligence, and artificial intelligence. The aim of this book is to create a comprehensive source on support vector machine applications, especially some recent advances.

  5. The Newest Machine Material

    International Nuclear Information System (INIS)

    Seo, Yeong Seop; Choe, Byeong Do; Bang, Meong Sung

    2005-08-01

    This book gives descriptions of machine material with classification of machine material and selection of machine material, structure and connection of material, coagulation of metal and crystal structure, equilibrium diagram, properties of metal material, elasticity and plasticity, biopsy of metal, material test and nondestructive test. It also explains steel material such as heat treatment of steel, cast iron and cast steel, nonferrous metal materials, non metallic materials, and new materials.

  6. Introduction to machine learning

    OpenAIRE

    Baştanlar, Yalın; Özuysal, Mustafa

    2014-01-01

    The machine learning field, which can be briefly defined as enabling computers make successful predictions using past experiences, has exhibited an impressive development recently with the help of the rapid increase in the storage capacity and processing power of computers. Together with many other disciplines, machine learning methods have been widely employed in bioinformatics. The difficulties and cost of biological analyses have led to the development of sophisticated machine learning app...

  7. Machinability of advanced materials

    CERN Document Server

    Davim, J Paulo

    2014-01-01

    Machinability of Advanced Materials addresses the level of difficulty involved in machining a material, or multiple materials, with the appropriate tooling and cutting parameters.  A variety of factors determine a material's machinability, including tool life rate, cutting forces and power consumption, surface integrity, limiting rate of metal removal, and chip shape. These topics, among others, and multiple examples comprise this research resource for engineering students, academics, and practitioners.

  8. Machining of titanium alloys

    CERN Document Server

    2014-01-01

    This book presents a collection of examples illustrating the resent research advances in the machining of titanium alloys. These materials have excellent strength and fracture toughness as well as low density and good corrosion resistance; however, machinability is still poor due to their low thermal conductivity and high chemical reactivity with cutting tool materials. This book presents solutions to enhance machinability in titanium-based alloys and serves as a useful reference to professionals and researchers in aerospace, automotive and biomedical fields.

  9. Redox control of molecular motion in switchable artificial nanoscale devices.

    Science.gov (United States)

    Credi, Alberto; Semeraro, Monica; Silvi, Serena; Venturi, Margherita

    2011-03-15

    The design, synthesis, and operation of molecular-scale systems that exhibit controllable motions of their component parts is a topic of great interest in nanoscience and a fascinating challenge of nanotechnology. The development of this kind of species constitutes the premise to the construction of molecular machines and motors, which in a not-too-distant future could find applications in fields such as materials science, information technology, energy conversion, diagnostics, and medicine. In the past 25 years the development of supramolecular chemistry has enabled the construction of an interesting variety of artificial molecular machines. These devices operate via electronic and molecular rearrangements and, like the macroscopic counterparts, they need energy to work as well as signals to communicate with the operator. Here we outline the design principles at the basis of redox switching of molecular motion in artificial nanodevices. Redox processes, chemically, electrically, or photochemically induced, can indeed supply the energy to bring about molecular motions. Moreover, in the case of electrically and photochemically induced processes, electrochemical and photochemical techniques can be used to read the state of the system, and thus to control and monitor the operation of the device. Some selected examples are also reported to describe the most representative achievements in this research area.

  10. Tribology in machine design

    CERN Document Server

    Stolarski, Tadeusz

    1999-01-01

    ""Tribology in Machine Design is strongly recommended for machine designers, and engineers and scientists interested in tribology. It should be in the engineering library of companies producing mechanical equipment.""Applied Mechanics ReviewTribology in Machine Design explains the role of tribology in the design of machine elements. It shows how algorithms developed from the basic principles of tribology can be used in a range of practical applications within mechanical devices and systems.The computer offers today's designer the possibility of greater stringen

  11. Induction machine handbook

    CERN Document Server

    Boldea, Ion

    2002-01-01

    Often called the workhorse of industry, the advent of power electronics and advances in digital control are transforming the induction motor into the racehorse of industrial motion control. Now, the classic texts on induction machines are nearly three decades old, while more recent books on electric motors lack the necessary depth and detail on induction machines.The Induction Machine Handbook fills industry's long-standing need for a comprehensive treatise embracing the many intricate facets of induction machine analysis and design. Moving gradually from simple to complex and from standard to

  12. Chaotic Boltzmann machines

    Science.gov (United States)

    Suzuki, Hideyuki; Imura, Jun-ichi; Horio, Yoshihiko; Aihara, Kazuyuki

    2013-01-01

    The chaotic Boltzmann machine proposed in this paper is a chaotic pseudo-billiard system that works as a Boltzmann machine. Chaotic Boltzmann machines are shown numerically to have computing abilities comparable to conventional (stochastic) Boltzmann machines. Since no randomness is required, efficient hardware implementation is expected. Moreover, the ferromagnetic phase transition of the Ising model is shown to be characterised by the largest Lyapunov exponent of the proposed system. In general, a method to relate probabilistic models to nonlinear dynamics by derandomising Gibbs sampling is presented. PMID:23558425

  13. Electrical machines & drives

    CERN Document Server

    Hammond, P

    1985-01-01

    Containing approximately 200 problems (100 worked), the text covers a wide range of topics concerning electrical machines, placing particular emphasis upon electrical-machine drive applications. The theory is concisely reviewed and focuses on features common to all machine types. The problems are arranged in order of increasing levels of complexity and discussions of the solutions are included where appropriate to illustrate the engineering implications. This second edition includes an important new chapter on mathematical and computer simulation of machine systems and revised discussions o

  14. Nanocomposites for Machining Tools

    Directory of Open Access Journals (Sweden)

    Daria Sidorenko

    2017-10-01

    Full Text Available Machining tools are used in many areas of production. To a considerable extent, the performance characteristics of the tools determine the quality and cost of obtained products. The main materials used for producing machining tools are steel, cemented carbides, ceramics and superhard materials. A promising way to improve the performance characteristics of these materials is to design new nanocomposites based on them. The application of micromechanical modeling during the elaboration of composite materials for machining tools can reduce the financial and time costs for development of new tools, with enhanced performance. This article reviews the main groups of nanocomposites for machining tools and their performance.

  15. Machine listening intelligence

    Science.gov (United States)

    Cella, C. E.

    2017-05-01

    This manifesto paper will introduce machine listening intelligence, an integrated research framework for acoustic and musical signals modelling, based on signal processing, deep learning and computational musicology.

  16. Rotating electrical machines

    CERN Document Server

    Le Doeuff, René

    2013-01-01

    In this book a general matrix-based approach to modeling electrical machines is promulgated. The model uses instantaneous quantities for key variables and enables the user to easily take into account associations between rotating machines and static converters (such as in variable speed drives).   General equations of electromechanical energy conversion are established early in the treatment of the topic and then applied to synchronous, induction and DC machines. The primary characteristics of these machines are established for steady state behavior as well as for variable speed scenarios. I

  17. Are there intelligent Turing machines?

    OpenAIRE

    Bátfai, Norbert

    2015-01-01

    This paper introduces a new computing model based on the cooperation among Turing machines called orchestrated machines. Like universal Turing machines, orchestrated machines are also designed to simulate Turing machines but they can also modify the original operation of the included Turing machines to create a new layer of some kind of collective behavior. Using this new model we can define some interested notions related to cooperation ability of Turing machines such as the intelligence quo...

  18. Machine learning landscapes and predictions for patient outcomes

    Science.gov (United States)

    Das, Ritankar; Wales, David J.

    2017-07-01

    The theory and computational tools developed to interpret and explore energy landscapes in molecular science are applied to the landscapes defined by local minima for neural networks. These machine learning landscapes correspond to fits of training data, where the inputs are vital signs and laboratory measurements for a database of patients, and the objective is to predict a clinical outcome. In this contribution, we test the predictions obtained by fitting to single measurements, and then to combinations of between 2 and 10 different patient medical data items. The effect of including measurements over different time intervals from the 48 h period in question is analysed, and the most recent values are found to be the most important. We also compare results obtained for neural networks as a function of the number of hidden nodes, and for different values of a regularization parameter. The predictions are compared with an alternative convex fitting function, and a strong correlation is observed. The dependence of these results on the patients randomly selected for training and testing decreases systematically with the size of the database available. The machine learning landscapes defined by neural network fits in this investigation have single-funnel character, which probably explains why it is relatively straightforward to obtain the global minimum solution, or a fit that behaves similarly to this optimal parameterization.

  19. 25 years and still going strong: 2'-O-(pyren-1-yl)methylribonucleotides - versatile building blocks for applications in molecular biology, diagnostics and materials science.

    Science.gov (United States)

    Hrdlicka, Patrick J; Karmakar, Saswata

    2017-11-29

    Oligonucleotides (ONs) modified with 2'-O-(pyren-1-yl)methylribonucleotides have been explored for a range of applications in molecular biology, nucleic acid diagnostics, and materials science for more than 25 years. The first part of this review provides an overview of synthetic strategies toward 2'-O-(pyren-1-yl)methylribonucleotides and is followed by a summary of biophysical properties of nucleic acid duplexes modified with these building blocks. Insights from structural studies are then presented to rationalize the reported properties. In the second part, applications of ONs modified with 2'-O-(pyren-1-yl)methyl-RNA monomers are reviewed, which include detection of RNA targets, discrimination of single nucleotide polymorphisms, formation of self-assembled pyrene arrays on nucleic acid scaffolds, the study of charge transfer phenomena in nucleic acid duplexes, and sequence-unrestricted recognition of double-stranded DNA. The predictable binding mode of the pyrene moiety, coupled with the microenvironment-dependent properties and synthetic feasibility, render 2'-O-(pyren-1-yl)methyl-RNA monomers as a promising class of pyrene-functionalized nucleotide building blocks for new applications in molecular biology, nucleic acid diagnostics, and materials science.

  20. Advanced molecular devices based on light-driven molecular motors

    NARCIS (Netherlands)

    Chen, Jiawen

    2015-01-01

    Nature has provided a large collection of molecular machines and devices that are among the most amazing nanostructures on this planet. These machines are able to operate complex biological processes which are of great importance in our organisms. Inspired by these natural devices, artificial

  1. Visualization and characterization of individual type III protein secretion machines in live bacteria.

    Science.gov (United States)

    Zhang, Yongdeng; Lara-Tejero, María; Bewersdorf, Jörg; Galán, Jorge E

    2017-06-06

    Type III protein secretion machines have evolved to deliver bacterially encoded effector proteins into eukaryotic cells. Although electron microscopy has provided a detailed view of these machines in isolation or fixed samples, little is known about their organization in live bacteria. Here we report the visualization and characterization of the Salmonella type III secretion machine in live bacteria by 2D and 3D single-molecule switching superresolution microscopy. This approach provided access to transient components of this machine, which previously could not be analyzed. We determined the subcellular distribution of individual machines, the stoichiometry of the different components of this machine in situ, and the spatial distribution of the substrates of this machine before secretion. Furthermore, by visualizing this machine in Salmonella mutants we obtained major insights into the machine's assembly. This study bridges a major resolution gap in the visualization of this nanomachine and may serve as a paradigm for the examination of other bacterially encoded molecular machines.

  2. Design and evaluation of a digital module with guided peer feedback for student learning biotechnology and molecular life sciences, attitudinal change, and satisfaction.

    Science.gov (United States)

    Noroozi, Omid; Mulder, Martin

    2017-01-02

    This study aims to investigate the impacts of a digital learning module with guided peer feedback on students' domain-specific knowledge gain and their attitudinal change in the field of biotechnology and molecular life sciences. The extent to which the use of this module is appreciated by students is studied as well. A pre-test, post-test design was used with 203 students who were randomly assigned to groups of three. They were asked to work on the digital module with the aim of exploring various perspectives, and the "pros and cons" on the topic of "Genetically Modified Organisms (GMOs)." The results suggest that the module can be used to foster students' domain-specific knowledge gain and their attitudinal change. Furthermore, the module was evaluated positively in terms of students' motivation and satisfaction with the learning experiences. © 2016 by The International Union of Biochemistry and Molecular Biology, 45(1):31-39, 2017. © 2016 The International Union of Biochemistry and Molecular Biology.

  3. Microsoft Azure machine learning

    CERN Document Server

    Mund, Sumit

    2015-01-01

    The book is intended for those who want to learn how to use Azure Machine Learning. Perhaps you already know a bit about Machine Learning, but have never used ML Studio in Azure; or perhaps you are an absolute newbie. In either case, this book will get you up-and-running quickly.

  4. The Hooey Machine.

    Science.gov (United States)

    Scarnati, James T.; Tice, Craig J.

    1992-01-01

    Describes how students can make and use Hooey Machines to learn how mechanical energy can be transferred from one object to another within a system. The Hooey Machine is made using a pencil, eight thumbtacks, one pushpin, tape, scissors, graph paper, and a plastic lid. (PR)

  5. Nanocomposites for Machining Tools

    DEFF Research Database (Denmark)

    Sidorenko, Daria; Loginov, Pavel; Mishnaevsky, Leon

    2017-01-01

    Machining tools are used in many areas of production. To a considerable extent, the performance characteristics of the tools determine the quality and cost of obtained products. The main materials used for producing machining tools are steel, cemented carbides, ceramics and superhard materials...

  6. A nucleonic weighing machine

    International Nuclear Information System (INIS)

    Anon.

    1978-01-01

    The design and operation of a nucleonic weighing machine fabricated for continuous weighing of material over conveyor belt are described. The machine uses a 40 mCi cesium-137 line source and a 10 litre capacity ionization chamber. It is easy to maintain as there are no moving parts. It can also be easily removed and reinstalled. (M.G.B.)

  7. An asymptotical machine

    Science.gov (United States)

    Cristallini, Achille

    2016-07-01

    A new and intriguing machine may be obtained replacing the moving pulley of a gun tackle with a fixed point in the rope. Its most important feature is the asymptotic efficiency. Here we obtain a satisfactory description of this machine by means of vector calculus and elementary trigonometry. The mathematical model has been compared with experimental data and briefly discussed.

  8. Machine learning with R

    CERN Document Server

    Lantz, Brett

    2015-01-01

    Perhaps you already know a bit about machine learning but have never used R, or perhaps you know a little R but are new to machine learning. In either case, this book will get you up and running quickly. It would be helpful to have a bit of familiarity with basic programming concepts, but no prior experience is required.

  9. The deleuzian abstract machines

    DEFF Research Database (Denmark)

    Werner Petersen, Erik

    2005-01-01

    To most people the concept of abstract machines is connected to the name of Alan Turing and the development of the modern computer. The Turing machine is universal, axiomatic and symbolic (E.g. operating on symbols). Inspired by Foucault, Deleuze and Guattari extended the concept of abstract...

  10. Human Machine Learning Symbiosis

    Science.gov (United States)

    Walsh, Kenneth R.; Hoque, Md Tamjidul; Williams, Kim H.

    2017-01-01

    Human Machine Learning Symbiosis is a cooperative system where both the human learner and the machine learner learn from each other to create an effective and efficient learning environment adapted to the needs of the human learner. Such a system can be used in online learning modules so that the modules adapt to each learner's learning state both…

  11. Precision machining commercialization

    International Nuclear Information System (INIS)

    1978-01-01

    To accelerate precision machining development so as to realize more of the potential savings within the next few years of known Department of Defense (DOD) part procurement, the Air Force Materials Laboratory (AFML) is sponsoring the Precision Machining Commercialization Project (PMC). PMC is part of the Tri-Service Precision Machine Tool Program of the DOD Manufacturing Technology Five-Year Plan. The technical resources supporting PMC are provided under sponsorship of the Department of Energy (DOE). The goal of PMC is to minimize precision machining development time and cost risk for interested vendors. PMC will do this by making available the high precision machining technology as developed in two DOE contractor facilities, the Lawrence Livermore Laboratory of the University of California and the Union Carbide Corporation, Nuclear Division, Y-12 Plant, at Oak Ridge, Tennessee

  12. Introduction to machine learning.

    Science.gov (United States)

    Baştanlar, Yalin; Ozuysal, Mustafa

    2014-01-01

    The machine learning field, which can be briefly defined as enabling computers make successful predictions using past experiences, has exhibited an impressive development recently with the help of the rapid increase in the storage capacity and processing power of computers. Together with many other disciplines, machine learning methods have been widely employed in bioinformatics. The difficulties and cost of biological analyses have led to the development of sophisticated machine learning approaches for this application area. In this chapter, we first review the fundamental concepts of machine learning such as feature assessment, unsupervised versus supervised learning and types of classification. Then, we point out the main issues of designing machine learning experiments and their performance evaluation. Finally, we introduce some supervised learning methods.

  13. LHC Report: machine development

    CERN Multimedia

    Rogelio Tomás García for the LHC team

    2015-01-01

    Machine development weeks are carefully planned in the LHC operation schedule to optimise and further study the performance of the machine. The first machine development session of Run 2 ended on Saturday, 25 July. Despite various hiccoughs, it allowed the operators to make great strides towards improving the long-term performance of the LHC.   The main goals of this first machine development (MD) week were to determine the minimum beam-spot size at the interaction points given existing optics and collimation constraints; to test new beam instrumentation; to evaluate the effectiveness of performing part of the beam-squeezing process during the energy ramp; and to explore the limits on the number of protons per bunch arising from the electromagnetic interactions with the accelerator environment and the other beam. Unfortunately, a series of events reduced the machine availability for studies to about 50%. The most critical issue was the recurrent trip of a sextupolar corrector circuit –...

  14. The Experimental Teaching Reform in Biochemistry and Molecular Biology for Undergraduate Students in Peking University Health Science Center

    Science.gov (United States)

    Yang, Xiaohan; Sun, Luyang; Zhao, Ying; Yi, Xia; Zhu, Bin; Wang, Pu; Lin, Hong; Ni, Juhua

    2015-01-01

    Since 2010, second-year undergraduate students of an eight-year training program leading to a Doctor of Medicine degree or Doctor of Philosophy degree in Peking University Health Science Center (PKUHSC) have been required to enter the "Innovative talent training project." During that time, the students joined a research lab and…

  15. Exploring the science of thinking independently together: Faraday Discussion Volume 204 - Complex Molecular Surfaces and Interfaces, Sheffield, UK, July 2017.

    Science.gov (United States)

    Samperi, M; Hirsch, B E; Diaz Fernandez, Y A

    2017-11-23

    The 2017 Faraday Discussion on Complex Molecular Surfaces and Interfaces brought together theoreticians and experimentalists from both physical and chemical backgrounds to discuss the relevant applied and fundamental research topics within the broader field of chemical surface analysis and characterization. Main discussion topics from the meeting included the importance of "disordered" two-dimensional (2D) molecular structures and the utility of kinetically trapped states. An emerging need for new experimental tools to address dynamics and kinetic pathways involved in self-assembled systems, as well as the future prospects and current limitations of in silico studies were also discussed. The following article provides a brief overview of the work presented and the challenges discussed during the meeting.

  16. Molecular Basis on Nitrogen Utilization in Rice(Recent Topics of the Agricultunal Biological Science in Tohoku University)

    OpenAIRE

    Toshihiko, HAYAKAWA; Soichi, KOJIMA; Mayumi, TABUCHI; Toru, KUDO; Tomoyuki, YAMAYA; Laboratory of Plant Cell Biochemistry, Department of Applied Plant Science, Division of Life Science, Graduate School of Agricultural Science, Tohoku University; Laboratory of Plant Cell Biochemistry, Department of Applied Plant Science, Division of Life Science, Graduate School of Agricultural Science, Tohoku University; Laboratory of Plant Cell Biochemistry, Department of Applied Plant Science, Division of Life Science, Graduate School of Agricultural Science, Tohoku University; Laboratory of Plant Cell Biochemistry, Department of Applied Plant Science, Division of Life Science, Graduate School of Agricultural Science, Tohoku University; Laboratory of Plant Cell Biochemistry, Department of Applied Plant Science, Division of Life Science, Graduate School of Agricultural Science, Tohoku University

    2008-01-01

    Rice (Oryza sativa L.) is the major provision for half of the world population and is the important model crop in terms of synteny. Nitrogen is a massive prerequisite element for rice during its life span. During evolutionary processes, rice has acquired strategic systems of nitrogen metabolism for the survival, i.e., the highly efficient ammonium assimilation in roots and nitrogen remobilization (nitrogen recycling). In our laboratory, research is underway to elucidate molecular mechanisms, ...

  17. Towards a Molecular Scale Understanding of Surface Chemistry and Photocatalysis on Metal Oxides: Surface Science Experiments and First Principles Theory

    Energy Technology Data Exchange (ETDEWEB)

    Diebold, Ulrike [Tulane Univ., New Orleans, LA (United States)

    2015-01-29

    This project has provided an increased understanding of molecular processes and structure-activity relationships in photocatalytic systems. This could ultimately lead to guidelines on how to make TiO2-based photocatalytic systems more efficient. This directly relates to the Program’s mission to develop a mechanistic understanding of chemical reactions that pertain to environmental remediation and pollution control; energy production (photoelectrochemical and production of hydrogen); and novel materials synthesis.

  18. Precise machine translation of computer science study

    CSIR Research Space (South Africa)

    Marais, L

    2015-07-01

    Full Text Available mobile (Android) application for translating discrete mathematics definitions between English and Afrikaans. The main component of the system is a Grammatical Framework (GF) application grammar which produces syntactically and semantically accurate...

  19. Machine Learning and Radiology

    Science.gov (United States)

    Wang, Shijun; Summers, Ronald M.

    2012-01-01

    In this paper, we give a short introduction to machine learning and survey its applications in radiology. We focused on six categories of applications in radiology: medical image segmentation, registration, computer aided detection and diagnosis, brain function or activity analysis and neurological disease diagnosis from fMR images, content-based image retrieval systems for CT or MRI images, and text analysis of radiology reports using natural language processing (NLP) and natural language understanding (NLU). This survey shows that machine learning plays a key role in many radiology applications. Machine learning identifies complex patterns automatically and helps radiologists make intelligent decisions on radiology data such as conventional radiographs, CT, MRI, and PET images and radiology reports. In many applications, the performance of machine learning-based automatic detection and diagnosis systems has shown to be comparable to that of a well-trained and experienced radiologist. Technology development in machine learning and radiology will benefit from each other in the long run. Key contributions and common characteristics of machine learning techniques in radiology are discussed. We also discuss the problem of translating machine learning applications to the radiology clinical setting, including advantages and potential barriers. PMID:22465077

  20. Machine learning and radiology.

    Science.gov (United States)

    Wang, Shijun; Summers, Ronald M

    2012-07-01

    In this paper, we give a short introduction to machine learning and survey its applications in radiology. We focused on six categories of applications in radiology: medical image segmentation, registration, computer aided detection and diagnosis, brain function or activity analysis and neurological disease diagnosis from fMR images, content-based image retrieval systems for CT or MRI images, and text analysis of radiology reports using natural language processing (NLP) and natural language understanding (NLU). This survey shows that machine learning plays a key role in many radiology applications. Machine learning identifies complex patterns automatically and helps radiologists make intelligent decisions on radiology data such as conventional radiographs, CT, MRI, and PET images and radiology reports. In many applications, the performance of machine learning-based automatic detection and diagnosis systems has shown to be comparable to that of a well-trained and experienced radiologist. Technology development in machine learning and radiology will benefit from each other in the long run. Key contributions and common characteristics of machine learning techniques in radiology are discussed. We also discuss the problem of translating machine learning applications to the radiology clinical setting, including advantages and potential barriers. Copyright © 2012. Published by Elsevier B.V.

  1. Molecular fountain.

    Energy Technology Data Exchange (ETDEWEB)

    Strecker, Kevin E.; Chandler, David W.

    2009-09-01

    A molecular fountain directs slowly moving molecules against gravity to further slow them to translational energies that they can be trapped and studied. If the molecules are initially slow enough they will return some time later to the position from which they were launched. Because this round trip time can be on the order of a second a single molecule can be observed for times sufficient to perform Hz level spectroscopy. The goal of this LDRD proposal was to construct a novel Molecular Fountain apparatus capable of producing dilute samples of molecules at near zero temperatures in well-defined user-selectable, quantum states. The slowly moving molecules used in this research are produced by the previously developed Kinematic Cooling technique, which uses a crossed atomic and molecular beam apparatus to generate single rotational level molecular samples moving slowly in the laboratory reference frame. The Kinematic Cooling technique produces cold molecules from a supersonic molecular beam via single collisions with a supersonic atomic beam. A single collision of an atom with a molecule occurring at the correct energy and relative velocity can cause a small fraction of the molecules to move very slowly vertically against gravity in the laboratory. These slowly moving molecules are captured by an electrostatic hexapole guiding field that both orients and focuses the molecules. The molecules are focused into the ionization region of a time-of-flight mass spectrometer and are ionized by laser radiation. The new molecular fountain apparatus was built utilizing a new design for molecular beam apparatus that has allowed us to miniaturize the apparatus. This new design minimizes the volumes and surface area of the machine allowing smaller pumps to maintain the necessary background pressures needed for these experiments.

  2. Fundamentals of machine design

    CERN Document Server

    Karaszewski, Waldemar

    2011-01-01

    A forum of researchers, educators and engineers involved in various aspects of Machine Design provided the inspiration for this collection of peer-reviewed papers. The resultant dissemination of the latest research results, and the exchange of views concerning the future research directions to be taken in this field will make the work of immense value to all those having an interest in the topics covered. The book reflects the cooperative efforts made in seeking out the best strategies for effecting improvements in the quality and the reliability of machines and machine parts and for extending

  3. Machine Learning for Hackers

    CERN Document Server

    Conway, Drew

    2012-01-01

    If you're an experienced programmer interested in crunching data, this book will get you started with machine learning-a toolkit of algorithms that enables computers to train themselves to automate useful tasks. Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation. Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you'll learn how to analyz

  4. Creativity in Machine Learning

    OpenAIRE

    Thoma, Martin

    2016-01-01

    Recent machine learning techniques can be modified to produce creative results. Those results did not exist before; it is not a trivial combination of the data which was fed into the machine learning system. The obtained results come in multiple forms: As images, as text and as audio. This paper gives a high level overview of how they are created and gives some examples. It is meant to be a summary of the current work and give people who are new to machine learning some starting points.

  5. Machine Tool Software

    Science.gov (United States)

    1988-01-01

    A NASA-developed software package has played a part in technical education of students who major in Mechanical Engineering Technology at William Rainey Harper College. Professor Hack has been using (APT) Automatically Programmed Tool Software since 1969 in his CAD/CAM Computer Aided Design and Manufacturing curriculum. Professor Hack teaches the use of APT programming languages for control of metal cutting machines. Machine tool instructions are geometry definitions written in APT Language to constitute a "part program." The part program is processed by the machine tool. CAD/CAM students go from writing a program to cutting steel in the course of a semester.

  6. Life sciences

    Energy Technology Data Exchange (ETDEWEB)

    Day, L. (ed.)

    1991-04-01

    This document is the 1989--1990 Annual Report for the Life Sciences Divisions of the University of California/Lawrence Berkeley Laboratory. Specific progress reports are included for the Cell and Molecular Biology Division, the Research Medicine and Radiation Biophysics Division (including the Advanced Light Source Life Sciences Center), and the Chemical Biodynamics Division. 450 refs., 46 figs. (MHB)

  7. Life sciences

    International Nuclear Information System (INIS)

    Day, L.

    1991-04-01

    This document is the 1989--1990 Annual Report for the Life Sciences Divisions of the University of California/Lawrence Berkeley Laboratory. Specific progress reports are included for the Cell and Molecular Biology Division, the Research Medicine and Radiation Biophysics Division (including the Advanced Light Source Life Sciences Center), and the Chemical Biodynamics Division. 450 refs., 46 figs

  8. Versatile piezoelectric pulsed molecular beam source for gaseous compounds and organic molecules with femtomole accuracy for UHV and surface science applications

    International Nuclear Information System (INIS)

    Schiesser, Alexander; Schaefer, Rolf

    2009-01-01

    This note describes the construction of a piezoelectric pulsed molecular beam source based upon a design presented in an earlier work [D. Proch and T. Trickl, Rev. Sci. Instrum. 60, 713 (1988)]. The design features significant modifications that permit the determination of the number of molecules in a beam pulse with an accuracy of 1x10 11 molecules per pulse. The 21 cm long plunger-nozzle setup allows the molecules to be brought to any point of the UHV chamber with very high intensity. Furthermore, besides typical gaseous compounds, also smaller organic molecules with a vapor pressure higher than 0.1 mbar at room temperature may serve as feed material. This makes the new design suitable for various applications in chemical and surface science studies.

  9. Aliens and time in the machine age

    Science.gov (United States)

    Brake, Mark; Hook, Neil

    2006-12-01

    The 19th century saw sweeping changes for the development of astrobiology, both in the constituency of empirical science encroaching upon all aspects of life and in the evolution of ideas, with Lyell's Principles of Geology radically raising expectation of the true age of the Earth and the drama of Darwinism questioning biblically literalist accounts of natural history. This paper considers the popular culture spun on the crackling loom of the emergent aspects of astrobiology of the day: Edward Bulwer-Lytton's The Coming Race (1871), which foretold the race of the future, and satirist Samuel Butler's anticipation of machine intelligence, `Darwin Among the Machines', in his Erewhon (1872). Finally, we look at the way Darwin, Huxley and natural selection travelled into space with French astronomer Camille Flammarion's immensely popular Récits de l'infini (Stories of Infinity, 1872), and the social Darwinism of H.G. Wells' The Time Machine (1895) and The War of the Worlds (1898). These works of popular culture presented an effective and inspiring communication of science; their crucial discourse was the reducible gap between the new worlds uncovered by science and exploration and the fantastic strange worlds of the imagination. As such they exemplify a way in which the culture and science of popular astrobiology can be fused.

  10. Machine learning a Bayesian and optimization perspective

    CERN Document Server

    Theodoridis, Sergios

    2015-01-01

    This tutorial text gives a unifying perspective on machine learning by covering both probabilistic and deterministic approaches, which rely on optimization techniques, as well as Bayesian inference, which is based on a hierarchy of probabilistic models. The book presents the major machine learning methods as they have been developed in different disciplines, such as statistics, statistical and adaptive signal processing and computer science. Focusing on the physical reasoning behind the mathematics, all the various methods and techniques are explained in depth, supported by examples and problems, giving an invaluable resource to the student and researcher for understanding and applying machine learning concepts. The book builds carefully from the basic classical methods to the most recent trends, with chapters written to be as self-contained as possible, making the text suitable for different courses: pattern recognition, statistical/adaptive signal processing, statistical/Bayesian learning, as well as shor...

  11. Coordinate measuring machines

    DEFF Research Database (Denmark)

    De Chiffre, Leonardo

    This document is used in connection with three exercises of 2 hours duration as a part of the course GEOMETRICAL METROLOGY AND MACHINE TESTING. The exercises concern three aspects of coordinate measuring: 1) Measuring and verification of tolerances on coordinate measuring machines, 2) Traceabilit...... and uncertainty during coordinate measurements, 3) Digitalisation and Reverse Engineering. This document contains a short description of each step in the exercise and schemes with room for taking notes of the results.......This document is used in connection with three exercises of 2 hours duration as a part of the course GEOMETRICAL METROLOGY AND MACHINE TESTING. The exercises concern three aspects of coordinate measuring: 1) Measuring and verification of tolerances on coordinate measuring machines, 2) Traceability...

  12. Machine Vision Handbook

    CERN Document Server

    2012-01-01

    The automation of visual inspection is becoming more and more important in modern industry as a consistent, reliable means of judging the quality of raw materials and manufactured goods . The Machine Vision Handbook  equips the reader with the practical details required to engineer integrated mechanical-optical-electronic-software systems. Machine vision is first set in the context of basic information on light, natural vision, colour sensing and optics. The physical apparatus required for mechanized image capture – lenses, cameras, scanners and light sources – are discussed followed by detailed treatment of various image-processing methods including an introduction to the QT image processing system. QT is unique to this book, and provides an example of a practical machine vision system along with extensive libraries of useful commands, functions and images which can be implemented by the reader. The main text of the book is completed by studies of a wide variety of applications of machine vision in insp...

  13. Enter the machine

    Science.gov (United States)

    Palittapongarnpim, Pantita; Sanders, Barry C.

    2018-05-01

    Quantum tomography infers quantum states from measurement data, but it becomes infeasible for large systems. Machine learning enables tomography of highly entangled many-body states and suggests a new powerful approach to this problem.

  14. Introduction to AC machine design

    CERN Document Server

    Lipo, Thomas A

    2018-01-01

    AC electrical machine design is a key skill set for developing competitive electric motors and generators for applications in industry, aerospace, and defense. This book presents a thorough treatment of AC machine design, starting from basic electromagnetic principles and continuing through the various design aspects of an induction machine. Introduction to AC Machine Design includes one chapter each on the design of permanent magnet machines, synchronous machines, and thermal design. It also offers a basic treatment of the use of finite elements to compute the magnetic field within a machine without interfering with the initial comprehension of the core subject matter. Based on the author's notes, as well as after years of classroom instruction, Introduction to AC Machine Design: * Brings to light more advanced principles of machine design--not just the basic principles of AC and DC machine behavior * Introduces electrical machine design to neophytes while also being a resource for experienced designers * ...

  15. Structure analysis of molecular systems in the Institute of Macromolecular Chemistry of the Czech Academy of Sciences

    Czech Academy of Sciences Publication Activity Database

    Hašek, Jindřich

    2010-01-01

    Roč. 17, 2a (2010), k32-k34 ISSN 1211-5894. [Struktura 2010. Soláň, 14.06.2010-17.06.2010] R&D Projects: GA AV ČR IAA500500701; GA ČR GA305/07/1073 Institutional research plan: CEZ:AV0Z40500505 Keywords : Academy of Sciences of the Czech Republic * X-ray structure analysis * crystallography Subject RIV: CD - Macromolecular Chemistry http:// xray .cz/ms/bul2010-2a/hasek.pdf

  16. Molecular Dynamics Simulations of a Linear Nanomotor Driven by Thermophoretic Forces

    DEFF Research Database (Denmark)

    Zambrano, Harvey A; Walther, Jens Honore; Jaffe, Richard L.

    Molecular Dynamics of a Linear Nanomotor Driven by Thermophoresis Harvey A. Zambrano1, Jens H. Walther1,2 and Richard L. Jaffe3 1Department of Mechanical Engineering, Fluid Mechanics, Technical University of Denmark, DK-2800 Lyngby, Denmark; 2Computational Science and Engineering Laboratory, ETH...... future molecular machines a complete understanding of the friction forces involved on the transport process at the molecular level have to be addressed.18 In this work we perform Molecular Dynamics (MD) simulations using the MD package FASTTUBE19 to study a molecular linear motor consisting of coaxial...... the valence forces within the CNT using Morse, harmonic angle and torsion potentials.19We include a nonbonded carbon-carbon Lennard-Jones potential to describe the vdW interaction between the carbon atoms within the double wall portion of the system. We equilibrate the system at 300K for 0.1 ns, by coupling...

  17. Metalworking and machining fluids

    Science.gov (United States)

    Erdemir, Ali; Sykora, Frank; Dorbeck, Mark

    2010-10-12

    Improved boron-based metal working and machining fluids. Boric acid and boron-based additives that, when mixed with certain carrier fluids, such as water, cellulose and/or cellulose derivatives, polyhydric alcohol, polyalkylene glycol, polyvinyl alcohol, starch, dextrin, in solid and/or solvated forms result in improved metalworking and machining of metallic work pieces. Fluids manufactured with boric acid or boron-based additives effectively reduce friction, prevent galling and severe wear problems on cutting and forming tools.

  18. Superconducting machines. Chapter 4

    International Nuclear Information System (INIS)

    Appleton, A.D.

    1977-01-01

    A brief account is given of the principles of superconductivity and superconductors. The properties of Nb-Ti superconductors and the method of flux stabilization are described. The basic features of superconducting d.c. machines are illustrated by the use of these machines for ship propulsion, steel-mill drives, industrial drives, aluminium production, and other d.c. power supplies. Superconducting a.c. generators and their design parameters are discussed. (U.K.)

  19. Quantum Machine Learning

    OpenAIRE

    Romero García, Cristian

    2017-01-01

    [EN] In a world in which accessible information grows exponentially, the selection of the appropriate information turns out to be an extremely relevant problem. In this context, the idea of Machine Learning (ML), a subfield of Artificial Intelligence, emerged to face problems in data mining, pattern recognition, automatic prediction, among others. Quantum Machine Learning is an interdisciplinary research area combining quantum mechanics with methods of ML, in which quantum properties allow fo...

  20. Human-machine interactions

    Science.gov (United States)

    Forsythe, J Chris [Sandia Park, NM; Xavier, Patrick G [Albuquerque, NM; Abbott, Robert G [Albuquerque, NM; Brannon, Nathan G [Albuquerque, NM; Bernard, Michael L [Tijeras, NM; Speed, Ann E [Albuquerque, NM

    2009-04-28

    Digital technology utilizing a cognitive model based on human naturalistic decision-making processes, including pattern recognition and episodic memory, can reduce the dependency of human-machine interactions on the abilities of a human user and can enable a machine to more closely emulate human-like responses. Such a cognitive model can enable digital technology to use cognitive capacities fundamental to human-like communication and cooperation to interact with humans.

  1. AAA+ Machines of Protein Destruction in Mycobacteria.

    Science.gov (United States)

    Alhuwaider, Adnan Ali H; Dougan, David A

    2017-01-01

    The bacterial cytosol is a complex mixture of macromolecules (proteins, DNA, and RNA), which collectively are responsible for an enormous array of cellular tasks. Proteins are central to most, if not all, of these tasks and as such their maintenance (commonly referred to as protein homeostasis or proteostasis) is vital for cell survival during normal and stressful conditions. The two key aspects of protein homeostasis are, (i) the correct folding and assembly of proteins (coupled with their delivery to the correct cellular location) and (ii) the timely removal of unwanted or damaged proteins from the cell, which are performed by molecular chaperones and proteases, respectively. A major class of proteins that contribute to both of these tasks are the AAA+ (ATPases associated with a variety of cellular activities) protein superfamily. Although much is known about the structure of these machines and how they function in the model Gram-negative bacterium Escherichia coli , we are only just beginning to discover the molecular details of these machines and how they function in mycobacteria. Here we review the different AAA+ machines, that contribute to proteostasis in mycobacteria. Primarily we will focus on the recent advances in the structure and function of AAA+ proteases, the substrates they recognize and the cellular pathways they control. Finally, we will discuss the recent developments related to these machines as novel drug targets.

  2. Some relations between quantum Turing machines and Turing machines

    OpenAIRE

    Sicard, Andrés; Vélez, Mario

    1999-01-01

    For quantum Turing machines we present three elements: Its components, its time evolution operator and its local transition function. The components are related with the components of deterministic Turing machines, the time evolution operator is related with the evolution of reversible Turing machines and the local transition function is related with the transition function of probabilistic and reversible Turing machines.

  3. Digitotalar dysmorphism: Molecular elucidation

    African Journals Online (AJOL)

    obtained for molecular studies. Since the distal arthrogryposes (DAs) are genetically heterogeneous, an unbiased approach to mutation ... Diseases and Molecular Medicine, Department of Pathology, Faculty of Health Sciences, University of Cape Town, South Africa, with an interest in molecular genetics of connective ...

  4. Reactor refueling machine simulator

    International Nuclear Information System (INIS)

    Rohosky, T.L.; Swidwa, K.J.

    1987-01-01

    This patent describes in combination: a nuclear reactor; a refueling machine having a bridge, trolley and hoist each driven by a separate motor having feedback means for generating a feedback signal indicative of movement thereof. The motors are operable to position the refueling machine over the nuclear reactor for refueling the same. The refueling machine also has a removable control console including means for selectively generating separate motor signals for operating the bridge, trolley and hoist motors and for processing the feedback signals to generate an indication of the positions thereof, separate output leads connecting each of the motor signals to the respective refueling machine motor, and separate input leads for connecting each of the feedback means to the console; and a portable simulator unit comprising: a single simulator motor; a single simulator feedback signal generator connected to the simulator motor for generating a simulator feedback signal in response to operation of the simulator motor; means for selectively connecting the output leads of the console to the simulator unit in place of the refueling machine motors, and for connecting the console input leads to the simulator unit in place of the refueling machine motor feedback means; and means for driving the single simulator motor in response to any of the bridge, trolley or hoist motor signals generated by the console and means for applying the simulator feedback signal to the console input lead associated with the motor signal being generated by the control console

  5. Even an old technique is suitable in the molecular world of science: the everted sac preparation turns 60 years old.

    Science.gov (United States)

    Hamilton, Kirk L

    2014-04-15

    An old proverb states "necessity is the mother of invention." This certainly holds true in science as one pursues research questions. Experimental techniques have evolved as scientists have asked more specific research questions. Indeed, techniques such as the Ussing chamber, the perfused renal tubule preparation, patch-clamp, polymerase chain reaction, and site-directed mutagenesis have been developed over the past 60 years. However, sometimes, simple techniques may be useful and still very informative, and this certainly applies to intestinal physiology. Indeed, Gerald Wiseman and Thomas Hastings Wilson described the intestinal everted sac preparation some 60 years ago. Since then, this technique has been used for numerous research purposes including determining ion, amino acid, water and solute transport across the intestinal epithelium; and drug metabolism, absorption, and interactions in pharmaceutical/pharmacological research and even in education. This article provides a historical review of the development of the in vitro intestinal preparation that led to the everted sac preparation and its use in science.

  6. [A new machinability test machine and the machinability of composite resins for core built-up].

    Science.gov (United States)

    Iwasaki, N

    2001-06-01

    A new machinability test machine especially for dental materials was contrived. The purpose of this study was to evaluate the effects of grinding conditions on machinability of core built-up resins using this machine, and to confirm the relationship between machinability and other properties of composite resins. The experimental machinability test machine consisted of a dental air-turbine handpiece, a control weight unit, a driving unit of the stage fixing the test specimen, and so on. The machinability was evaluated as the change in volume after grinding using a diamond point. Five kinds of core built-up resins and human teeth were used in this study. The machinabilities of these composite resins increased with an increasing load during grinding, and decreased with repeated grinding. There was no obvious correlation between the machinability and Vickers' hardness; however, a negative correlation was observed between machinability and scratch width.

  7. Advances in machine learning and data mining for astronomy

    CERN Document Server

    Way, Michael J

    2012-01-01

    Advances in Machine Learning and Data Mining for Astronomy documents numerous successful collaborations among computer scientists, statisticians, and astronomers who illustrate the application of state-of-the-art machine learning and data mining techniques in astronomy. Due to the massive amount and complexity of data in most scientific disciplines, the material discussed in this text transcends traditional boundaries between various areas in the sciences and computer science. The book's introductory part provides context to issues in the astronomical sciences that are also important to health

  8. Engineering of the 'PCAST machine'

    International Nuclear Information System (INIS)

    Sinnis, J.; Brooks, A.; Brown, T.

    1996-01-01

    The President's Committee of Advisors on Science and Technology (PCAST) has suggested that a device with a mission of ignition and moderate burn time could address the physics of burning plasmas at a lesser cost than ITER with its more comprehensive physics and technology mission. The Department of Energy commissioned a study to explore this PCAST suggestion. This paper describes the results of the engineering portion of the study of this 'PCAST Machine;' physics is covered in a companion paper authored by G.H. Neilson, et al; and the costs are covered in a companion paper by R.T. Simmons, et al. Both are published in the proceedings of this conference. The study was undertaken by a team under the direction of Bruce Montgomery that included representatives from MIT, PPPL, ORNL, LLNL, GA, Northrup-Grumman, and Stone and Webster. The performance requirements for the PCAST machine are to form and sustain a burning plasma for three helium accumulation times. The philosophy adopted for this design was to achieve the required performance at lower cost by decreasing the major radius to five meters, increasing the toroidal field to 7 tesla, and using stronger shaping. The major device parameters are given. 4 refs., 4 figs., 1 tab

  9. The Knife Machine. Module 15.

    Science.gov (United States)

    South Carolina State Dept. of Education, Columbia. Office of Vocational Education.

    This module on the knife machine, one in a series dealing with industrial sewing machines, their attachments, and operation, covers one topic: performing special operations on the knife machine (a single needle or multi-needle machine which sews and cuts at the same time). These components are provided: an introduction, directions, an objective,…

  10. The Buttonhole Machine. Module 13.

    Science.gov (United States)

    South Carolina State Dept. of Education, Columbia. Office of Vocational Education.

    This module on the bottonhole machine, one in a series dealing with industrial sewing machines, their attachments, and operation, covers two topics: performing special operations on the buttonhole machine (parts and purpose) and performing special operations on the buttonhole machine (gauged buttonholes). For each topic these components are…

  11. Understanding and modelling Man-Machine Interaction

    International Nuclear Information System (INIS)

    Cacciabue, P.C.

    1991-01-01

    This paper gives an overview of the current state of the art in man machine systems interaction studies, focusing on the problems derived from highly automated working environments and the role of humans in the control loop. In particular, it is argued that there is a need for sound approaches to design and analysis of Man-Machine Interaction (MMI), which stem from the contribution of three expertises in interfacing domains, namely engineering, computer science and psychology: engineering for understanding and modelling plants and their material and energy conservation principles; psychology for understanding and modelling humans and their cognitive behaviours; computer science for converting models in sound simulations running in appropriate computer architectures. (author)

  12. Understanding and modelling man-machine interaction

    International Nuclear Information System (INIS)

    Cacciabue, P.C.

    1996-01-01

    This paper gives an overview of the current state of the art in man-machine system interaction studies, focusing on the problems derived from highly automated working environments and the role of humans in the control loop. In particular, it is argued that there is a need for sound approaches to the design and analysis of man-machine interaction (MMI), which stem from the contribution of three expertises in interfacing domains, namely engineering, computer science and psychology: engineering for understanding and modelling plants and their material and energy conservation principles; psychology for understanding and modelling humans an their cognitive behaviours; computer science for converting models in sound simulations running in appropriate computer architectures. (orig.)

  13. Machining of Metal Matrix Composites

    CERN Document Server

    2012-01-01

    Machining of Metal Matrix Composites provides the fundamentals and recent advances in the study of machining of metal matrix composites (MMCs). Each chapter is written by an international expert in this important field of research. Machining of Metal Matrix Composites gives the reader information on machining of MMCs with a special emphasis on aluminium matrix composites. Chapter 1 provides the mechanics and modelling of chip formation for traditional machining processes. Chapter 2 is dedicated to surface integrity when machining MMCs. Chapter 3 describes the machinability aspects of MMCs. Chapter 4 contains information on traditional machining processes and Chapter 5 is dedicated to the grinding of MMCs. Chapter 6 describes the dry cutting of MMCs with SiC particulate reinforcement. Finally, Chapter 7 is dedicated to computational methods and optimization in the machining of MMCs. Machining of Metal Matrix Composites can serve as a useful reference for academics, manufacturing and materials researchers, manu...

  14. ENVIROSUITE: USING STATE-OF-THE-ART SYNCHROTRON TECHNIQUES TO UNDERSTAND ENVIRONMENTAL REMEDIATION SCIENCE ISSUES AT THE MOLECULAR LEVEL.

    Energy Technology Data Exchange (ETDEWEB)

    FITTS,J.P.; KALB,P.D.; FRANCIS,A.J.; FUHRMANN,M.; DODGE,C.J.; GILLOW,J.B.

    2004-03-01

    Although DOE's Environmental Management program has made steady progress in cleaning up environmental legacies throughout the DOE complex, there are still significant remediation issues that remain to be solved. For example, DOE faces difficult challenges related to potential mobilization of radionuclides (e.g., actinides) and other hazardous contaminants in soils, removal and final treatment of high-level waste and residuals from leaking tanks, and the long-term stewardship of remediated sites and engineered disposal facilities, to name just a few. In some cases, new technologies and technology applications will be required based on current engineering expertise. In others, however, basic scientific research is needed to understand the mechanisms of how contaminants behave under specific conditions and how they interact with the environment, from which new engineering solutions can emerge. At Brookhaven National Laboratory (BNL) and Stony Brook University, scientists have teamed to use state-of-the-art synchrotron techniques to help understand the basic interactions of contaminants in the environment. Much of this work is conducted at the BNL National Synchrotron Light Source (NSLS), which is a user facility that provides high energy X-ray and ultraviolet photon beams to facilitate the examination of contaminants and materials at the molecular level. These studies allow us to determine how chemical speciation and structure control important parameters such as solubility, which in turn drive critical performance characteristics such as leaching. In one study for example, we are examining the effects of microbial activity on actinide contaminants under conditions anticipated at the Waste Isolation Pilot Plant. One possible outcome of this research is the identification of specific microbes that can trap uranium or other contaminants within the intracellular structure and help mitigate mobility. In another study, we are exploring the interaction of contaminants

  15. ENVIROSUITE: USING STATE-OF-THE-ART SYNCHROTRON TECHNIQUES TO UNDERSTAND ENVIRONMENTAL REMEDIATION SCIENCE ISSUES AT THE MOLECULAR LEVEL

    International Nuclear Information System (INIS)

    FITTS, J.P.; KALB, P.D.; FRANCIS, A.J.; FUHRMANN, M.; DODGE, C.J.; GILLOW, J.B.

    2004-01-01

    Although DOE's Environmental Management program has made steady progress in cleaning up environmental legacies throughout the DOE complex, there are still significant remediation issues that remain to be solved. For example, DOE faces difficult challenges related to potential mobilization of radionuclides (e.g., actinides) and other hazardous contaminants in soils, removal and final treatment of high-level waste and residuals from leaking tanks, and the long-term stewardship of remediated sites and engineered disposal facilities, to name just a few. In some cases, new technologies and technology applications will be required based on current engineering expertise. In others, however, basic scientific research is needed to understand the mechanisms of how contaminants behave under specific conditions and how they interact with the environment, from which new engineering solutions can emerge. At Brookhaven National Laboratory (BNL) and Stony Brook University, scientists have teamed to use state-of-the-art synchrotron techniques to help understand the basic interactions of contaminants in the environment. Much of this work is conducted at the BNL National Synchrotron Light Source (NSLS), which is a user facility that provides high energy X-ray and ultraviolet photon beams to facilitate the examination of contaminants and materials at the molecular level. These studies allow us to determine how chemical speciation and structure control important parameters such as solubility, which in turn drive critical performance characteristics such as leaching. In one study for example, we are examining the effects of microbial activity on actinide contaminants under conditions anticipated at the Waste Isolation Pilot Plant. One possible outcome of this research is the identification of specific microbes that can trap uranium or other contaminants within the intracellular structure and help mitigate mobility. In another study, we are exploring the interaction of contaminants with

  16. Virtual Machine Language Controls Remote Devices

    Science.gov (United States)

    2014-01-01

    Kennedy Space Center worked with Blue Sun Enterprises, based in Boulder, Colorado, to enhance the company's virtual machine language (VML) to control the instruments on the Regolith and Environment Science and Oxygen and Lunar Volatiles Extraction mission. Now the NASA-improved VML is available for crewed and uncrewed spacecraft, and has potential applications on remote systems such as weather balloons, unmanned aerial vehicles, and submarines.

  17. Virtual Machine in Automation Projects

    OpenAIRE

    Xing, Xiaoyuan

    2010-01-01

    Virtual machine, as an engineering tool, has recently been introduced into automation projects in Tetra Pak Processing System AB. The goal of this paper is to examine how to better utilize virtual machine for the automation projects. This paper designs different project scenarios using virtual machine. It analyzes installability, performance and stability of virtual machine from the test results. Technical solutions concerning virtual machine are discussed such as the conversion with physical...

  18. Non-conventional electrical machines

    CERN Document Server

    Rezzoug, Abderrezak

    2013-01-01

    The developments of electrical machines are due to the convergence of material progress, improved calculation tools, and new feeding sources. Among the many recent machines, the authors have chosen, in this first book, to relate the progress in slow speed machines, high speed machines, and superconducting machines. The first part of the book is dedicated to materials and an overview of magnetism, mechanic, and heat transfer.

  19. Advanced SLARette delivery machine

    International Nuclear Information System (INIS)

    Bodner, R.R.

    1995-01-01

    SLARette 1 equipment, comprising of a SLARette Delivery Machine, SLAR Tools, SLAR power supplies and SLAR Inspection Systems was designed, developed and manufactured to service fuel channels of CANDU 6 stations during the regular yearly station outages. The Mark 2 SLARette Delivery Machine uses a Push Tube system to provide the axial and rotary movements of the SLAR Tool. The Push Tubes are operated remotely but must be attached and removed manually. Since this operation is performed at the Reactor face, there is radiation dose involved for the workers. An Advanced SLARette Delivery Machine which incorporates a computer controlled telescoping Ram in the place of the Push Tubes has been recently designed and manufactured. Utilization of the Advanced SLARette Delivery Machine significantly reduces the amount of radiation dose picked up by the workers because the need to have workers at the face of the Reactor during the SLARette operation is greatly reduced. This paper describes the design, development and manufacturing process utilized to produce the Advanced SLARette Delivery Machine and the experience gained during the Gentilly-2 NGS Spring outage. (author)

  20. The Bearingless Electrical Machine

    Science.gov (United States)

    Bichsel, J.

    1992-01-01

    Electromagnetic bearings allow the suspension of solids. For rotary applications, the most important physical effect is the force of a magnetic circuit to a high permeable armature, called the MAXWELL force. Contrary to the commonly used MAXWELL bearings, the bearingless electrical machine will take advantage of the reaction force of a conductor carrying a current in a magnetic field. This kind of force, called Lorentz force, generates the torque in direct current, asynchronous and synchronous machines. The magnetic field, which already exists in electrical machines and helps to build up the torque, can also be used for the suspension of the rotor. Besides the normal winding of the stator, a special winding was added, which generates forces for levitation. So a radial bearing, which is integrated directly in the active part of the machine, and the motor use the laminated core simultaneously. The winding was constructed for the levitating forces in a special way so that commercially available standard ac inverters for drives can be used. Besides wholly magnetic suspended machines, there is a wide range of applications for normal drives with ball bearings. Resonances of the rotor, especially critical speeds, can be damped actively.

  1. Asymmetric quantum cloning machines

    International Nuclear Information System (INIS)

    Cerf, N.J.

    1998-01-01

    A family of asymmetric cloning machines for quantum bits and N-dimensional quantum states is introduced. These machines produce two approximate copies of a single quantum state that emerge from two distinct channels. In particular, an asymmetric Pauli cloning machine is defined that makes two imperfect copies of a quantum bit, while the overall input-to-output operation for each copy is a Pauli channel. A no-cloning inequality is derived, characterizing the impossibility of copying imposed by quantum mechanics. If p and p ' are the probabilities of the depolarizing channels associated with the two outputs, the domain in (√p,√p ' )-space located inside a particular ellipse representing close-to-perfect cloning is forbidden. This ellipse tends to a circle when copying an N-dimensional state with N→∞, which has a simple semi-classical interpretation. The symmetric Pauli cloning machines are then used to provide an upper bound on the quantum capacity of the Pauli channel of probabilities p x , p y and p z . The capacity is proven to be vanishing if (√p x , √p y , √p z ) lies outside an ellipsoid whose pole coincides with the depolarizing channel that underlies the universal cloning machine. Finally, the tradeoff between the quality of the two copies is shown to result from a complementarity akin to Heisenberg uncertainty principle. (author)

  2. Science, Passion & Compassion vs. Cancer: Tania Crombet MD PhD, Director of Clinical Research. Molecular Immunology Center, Havana.

    Science.gov (United States)

    Gory, Conner

    2016-10-01

    Soon after the Molecular Immunology Center (CIM) was established in 1994 (a founding institution of Havana's biotechnology and pharmaceutical campus known as the scientific pole), Dr Crombet completed her master's thesis there. She joined CIM's team in 1998 and in 2004 was designated Director of Clinical Research. She has participated in the research, development and clinical trials of some of Cuba's most innovative therapies and vaccines, including CIMAvax-EGF for non-small cell lung cancer patients. In 2015, this therapy completed Phase IV clinical trials in Cuba and is now used in primary health care services throughout the country's national health system. CIM and Roswell Park Cancer Institute (Buffalo, New York) received US Department of Treasury approval in 2015 to test CIMAvax-EGF and other CIM products in the United States, opening the way for the Food and Drug Administration (FDA) to consider joint ground-breaking Phase I and II clinical trials in the USA. Recent regulatory changes introduced by President Barack Obama may make applying for such licenses a thing of the past-at least that is what researchers hope. In any case, the work of Dr Crombet and the teams at CIM is making headway in cancer immunotherapy, within the broader goals of the institution's mandate…the subject of our interview.

  3. Application of data science tools to quantify and distinguish between structures and models in molecular dynamics datasets.

    Science.gov (United States)

    Kalidindi, Surya R; Gomberg, Joshua A; Trautt, Zachary T; Becker, Chandler A

    2015-08-28

    Structure quantification is key to successful mining and extraction of core materials knowledge from both multiscale simulations as well as multiscale experiments. The main challenge stems from the need to transform the inherently high dimensional representations demanded by the rich hierarchical material structure into useful, high value, low dimensional representations. In this paper, we develop and demonstrate the merits of a data-driven approach for addressing this challenge at the atomic scale. The approach presented here is built on prior successes demonstrated for mesoscale representations of material internal structure, and involves three main steps: (i) digital representation of the material structure, (ii) extraction of a comprehensive set of structure measures using the framework of n-point spatial correlations, and (iii) identification of data-driven low dimensional measures using principal component analyses. These novel protocols, applied on an ensemble of structure datasets output from molecular dynamics (MD) simulations, have successfully classified the datasets based on several model input parameters such as the interatomic potential and the temperature used in the MD simulations.

  4. Application of data science tools to quantify and distinguish between structures and models in molecular dynamics datasets

    International Nuclear Information System (INIS)

    Kalidindi, Surya R; Gomberg, Joshua A; Trautt, Zachary T; Becker, Chandler A

    2015-01-01

    Structure quantification is key to successful mining and extraction of core materials knowledge from both multiscale simulations as well as multiscale experiments. The main challenge stems from the need to transform the inherently high dimensional representations demanded by the rich hierarchical material structure into useful, high value, low dimensional representations. In this paper, we develop and demonstrate the merits of a data-driven approach for addressing this challenge at the atomic scale. The approach presented here is built on prior successes demonstrated for mesoscale representations of material internal structure, and involves three main steps: (i) digital representation of the material structure, (ii) extraction of a comprehensive set of structure measures using the framework of n-point spatial correlations, and (iii) identification of data-driven low dimensional measures using principal component analyses. These novel protocols, applied on an ensemble of structure datasets output from molecular dynamics (MD) simulations, have successfully classified the datasets based on several model input parameters such as the interatomic potential and the temperature used in the MD simulations. (paper)

  5. Human-Machine Communication

    International Nuclear Information System (INIS)

    Farbrot, J.E.; Nihlwing, Ch.; Svengren, H.

    2005-01-01

    New requirements for enhanced safety and design changes in process systems often leads to a step-wise installation of new information and control equipment in the control room of older nuclear power plants, where nowadays modern digital I and C solutions with screen-based human-machine interfaces (HMI) most often are introduced. Human factors (HF) expertise is then required to assist in specifying a unified, integrated HMI, where the entire integration of information is addressed to ensure an optimal and effective interplay between human (operators) and machine (process). Following a controlled design process is the best insurance for ending up with good solutions. This paper addresses the approach taken when introducing modern human-machine communication in the Oskarshamn 1 NPP, the results, and the lessons learned from this work with high operator involvement seen from an HF point of view. Examples of possibilities modern technology might offer for the operators are also addressed. (orig.)

  6. Machines and Metaphors

    Directory of Open Access Journals (Sweden)

    Ángel Martínez García-Posada

    2016-10-01

    Full Text Available The edition La ley del reloj. Arquitectura, máquinas y cultura moderna (Cátedra, Madrid, 2016 registers the useful paradox of the analogy between architecture and technique. Its author, the architect Eduardo Prieto, also a philosopher, professor and writer, acknowledges the obvious distance from machines to buildings, so great that it can only be solved using strange comparisons, since architecture does not move nor are the machines habitable, however throughout the book, from the origin of the metaphor of the machine, with clarity in his essay and enlightening erudition, he points out with certainty some concomitances of high interest, drawing throughout history a beautiful cartography of the fruitful encounter between organics and mechanics.

  7. Machine Learning for Security

    CERN Multimedia

    CERN. Geneva

    2015-01-01

    Applied statistics, aka ‘Machine Learning’, offers a wealth of techniques for answering security questions. It’s a much hyped topic in the big data world, with many companies now providing machine learning as a service. This talk will demystify these techniques, explain the math, and demonstrate their application to security problems. The presentation will include how-to’s on classifying malware, looking into encrypted tunnels, and finding botnets in DNS data. About the speaker Josiah is a security researcher with HP TippingPoint DVLabs Research Group. He has over 15 years of professional software development experience. Josiah used to do AI, with work focused on graph theory, search, and deductive inference on large knowledge bases. As rules only get you so far, he moved from AI to using machine learning techniques identifying failure modes in email traffic. There followed digressions into clustered data storage and later integrated control systems. Current ...

  8. Chatter and machine tools

    CERN Document Server

    Stone, Brian

    2014-01-01

    Focussing on occurrences of unstable vibrations, or Chatter, in machine tools, this book gives important insights into how to eliminate chatter with associated improvements in product quality, surface finish and tool wear. Covering a wide range of machining processes, including turning, drilling, milling and grinding, the author uses his research expertise and practical knowledge of vibration problems to provide solutions supported by experimental evidence of their effectiveness. In addition, this book contains links to supplementary animation programs that help readers to visualise the ideas detailed in the text. Advancing knowledge in chatter avoidance and suggesting areas for new innovations, Chatter and Machine Tools serves as a handbook for those desiring to achieve significant reductions in noise, longer tool and grinding wheel life and improved product finish.

  9. Predicting Outcomes of Hormone and Chemotherapy in the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC Study by Biochemically-inspired Machine Learning [version 3; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Eliseos J. Mucaki

    2017-05-01

    Full Text Available Genomic aberrations and gene expression-defined subtypes in the large METABRIC patient cohort have been used to stratify and predict survival. The present study used normalized gene expression signatures of paclitaxel drug response to predict outcome for different survival times in METABRIC patients receiving hormone (HT and, in some cases, chemotherapy (CT agents. This machine learning method, which distinguishes sensitivity vs. resistance in breast cancer cell lines and validates predictions in patients; was also used to derive gene signatures of other HT  (tamoxifen and CT agents (methotrexate, epirubicin, doxorubicin, and 5-fluorouracil used in METABRIC. Paclitaxel gene signatures exhibited the best performance, however the other agents also predicted survival with acceptable accuracies. A support vector machine (SVM model of paclitaxel response containing genes ABCB1, ABCB11, ABCC1, ABCC10, BAD, BBC3, BCL2, BCL2L1, BMF, CYP2C8, CYP3A4, MAP2, MAP4, MAPT, NR1I2, SLCO1B3, TUBB1, TUBB4A, and TUBB4B was 78.6% accurate in predicting survival of 84 patients treated with both HT and CT (median survival ≥ 4.4 yr. Accuracy was lower (73.4% in 304 untreated patients. The performance of other machine learning approaches was also evaluated at different survival thresholds. Minimum redundancy maximum relevance feature selection of a paclitaxel-based SVM classifier based on expression of genes BCL2L1, BBC3, FGF2, FN1, and TWIST1 was 81.1% accurate in 53 CT patients. In addition, a random forest (RF classifier using a gene signature (ABCB1, ABCB11, ABCC1, ABCC10, BAD, BBC3, BCL2, BCL2L1, BMF, CYP2C8, CYP3A4, MAP2, MAP4, MAPT, NR1I2,SLCO1B3, TUBB1, TUBB4A, and TUBB4B predicted >3-year survival with 85.5% accuracy in 420 HT patients. A similar RF gene signature showed 82.7% accuracy in 504 patients treated with CT and/or HT. These results suggest that tumor gene expression signatures refined by machine learning techniques can be useful for

  10. Predicting Outcomes of Hormone and Chemotherapy in the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) Study by Biochemically-inspired Machine Learning.

    Science.gov (United States)

    Mucaki, Eliseos J; Baranova, Katherina; Pham, Huy Q; Rezaeian, Iman; Angelov, Dimo; Ngom, Alioune; Rueda, Luis; Rogan, Peter K

    2016-01-01

    Genomic aberrations and gene expression-defined subtypes in the large METABRIC patient cohort have been used to stratify and predict survival. The present study used normalized gene expression signatures of paclitaxel drug response to predict outcome for different survival times in METABRIC patients receiving hormone (HT) and, in some cases, chemotherapy (CT) agents. This machine learning method, which distinguishes sensitivity vs. resistance in breast cancer cell lines and validates predictions in patients; was also used to derive gene signatures of other HT  (tamoxifen) and CT agents (methotrexate, epirubicin, doxorubicin, and 5-fluorouracil) used in METABRIC. Paclitaxel gene signatures exhibited the best performance, however the other agents also predicted survival with acceptable accuracies. A support vector machine (SVM) model of paclitaxel response containing genes  ABCB1, ABCB11, ABCC1, ABCC10, BAD, BBC3, BCL2, BCL2L1, BMF, CYP2C8, CYP3A4, MAP2, MAP4, MAPT, NR1I2, SLCO1B3, TUBB1, TUBB4A, and TUBB4B  was 78.6% accurate in predicting survival of 84 patients treated with both HT and CT (median survival ≥ 4.4 yr). Accuracy was lower (73.4%) in 304 untreated patients. The performance of other machine learning approaches was also evaluated at different survival thresholds. Minimum redundancy maximum relevance feature selection of a paclitaxel-based SVM classifier based on expression of genes  BCL2L1, BBC3, FGF2, FN1,  and  TWIST1   was 81.1% accurate in 53 CT patients. In addition, a random forest (RF) classifier using a gene signature ( ABCB1, ABCB11, ABCC1, ABCC10, BAD, BBC3, BCL2, BCL2L1, BMF, CYP2C8, CYP3A4, MAP2, MAP4, MAPT, NR1I2,SLCO1B3, TUBB1, TUBB4A,  and TUBB4B ) predicted >3-year survival with 85.5% accuracy in 420 HT patients. A similar RF gene signature showed 82.7% accuracy in 504 patients treated with CT and/or HT. These results suggest that tumor gene expression signatures refined by machine learning techniques can be useful for

  11. Machine learning for adaptive many-core machines a practical approach

    CERN Document Server

    Lopes, Noel

    2015-01-01

    The overwhelming data produced everyday and the increasing performance and cost requirements of applications?are transversal to a wide range of activities in society, from science to industry. In particular, the magnitude and complexity of the tasks that Machine Learning (ML) algorithms have to solve are driving the need to devise adaptive many-core machines that scale well with the volume of data, or in other words, can handle Big Data.This book gives a concise view on how to extend the applicability of well-known ML algorithms in Graphics Processing Unit (GPU) with data scalability in mind.

  12. Twin support vector machines models, extensions and applications

    CERN Document Server

    Jayadeva; Chandra, Suresh

    2017-01-01

    This book provides a systematic and focused study of the various aspects of twin support vector machines (TWSVM) and related developments for classification and regression. In addition to presenting most of the basic models of TWSVM and twin support vector regression (TWSVR) available in the literature, it also discusses the important and challenging applications of this new machine learning methodology. A chapter on “Additional Topics” has been included to discuss kernel optimization and support tensor machine topics, which are comparatively new but have great potential in applications. It is primarily written for graduate students and researchers in the area of machine learning and related topics in computer science, mathematics, electrical engineering, management science and finance.

  13. Clojure for machine learning

    CERN Document Server

    Wali, Akhil

    2014-01-01

    A book that brings out the strengths of Clojure programming that have to facilitate machine learning. Each topic is described in substantial detail, and examples and libraries in Clojure are also demonstrated.This book is intended for Clojure developers who want to explore the area of machine learning. Basic understanding of the Clojure programming language is required, but thorough acquaintance with the standard Clojure library or any libraries are not required. Familiarity with theoretical concepts and notation of mathematics and statistics would be an added advantage.

  14. Machine learning systems

    Energy Technology Data Exchange (ETDEWEB)

    Forsyth, R

    1984-05-01

    With the dramatic rise of expert systems has come a renewed interest in the fuel that drives them-knowledge. For it is specialist knowledge which gives expert systems their power. But extracting knowledge from human experts in symbolic form has proved arduous and labour-intensive. So the idea of machine learning is enjoying a renaissance. Machine learning is any automatic improvement in the performance of a computer system over time, as a result of experience. Thus a learning algorithm seeks to do one or more of the following: cover a wider range of problems, deliver more accurate solutions, obtain answers more cheaply, and simplify codified knowledge. 6 references.

  15. Machine tool evaluation

    International Nuclear Information System (INIS)

    Lunsford, B.E.

    1976-01-01

    Continued improvement in numerical control (NC) units and the mechanical components used in the construction of today's machine tools, necessitate the use of more precise instrumentation to calibrate and determine the capabilities of these systems. It is now necessary to calibrate most tape-control lathes to a tool-path positioning accuracy of +-300 microinches in the full slide travel and, on some special turning and boring machines, a capability of +-100 microinches must be achieved. The use of a laser interferometer to determine tool-path capabilities is described

  16. Electrical machines & their applications

    CERN Document Server

    Hindmarsh, J

    1984-01-01

    A self-contained, comprehensive and unified treatment of electrical machines, including consideration of their control characteristics in both conventional and semiconductor switched circuits. This new edition has been expanded and updated to include material which reflects current thinking and practice. All references have been updated to conform to the latest national (BS) and international (IEC) recommendations and a new appendix has been added which deals more fully with the theory of permanent-magnets, recognising the growing importance of permanent-magnet machines. The text is so arra

  17. Machine shop basics

    CERN Document Server

    Miller, Rex

    2004-01-01

    Use the right tool the right wayHere, fully updated to include new machines and electronic/digital controls, is the ultimate guide to basic machine shop equipment and how to use it. Whether you're a professional machinist, an apprentice, a trade student, or a handy homeowner, this fully illustrated volume helps you define tools and use them properly and safely. It's packed with review questions for students, and loaded with answers you need on the job.Mark Richard Miller is a Professor and Chairman of the Industrial Technology Department at Texas A&M University in Kingsville, T

  18. Electrical machines diagnosis

    CERN Document Server

    Trigeassou, Jean-Claude

    2013-01-01

    Monitoring and diagnosis of electrical machine faults is a scientific and economic issue which is motivated by objectives for reliability and serviceability in electrical drives.This book provides a survey of the techniques used to detect the faults occurring in electrical drives: electrical, thermal and mechanical faults of the electrical machine, faults of the static converter and faults of the energy storage unit.Diagnosis of faults occurring in electrical drives is an essential part of a global monitoring system used to improve reliability and serviceability. This diagnosis is perf

  19. Neutron irradiation therapy machine

    International Nuclear Information System (INIS)

    1980-01-01

    Conventional neutron irradiation therapy machines, based on the use of cyclotrons for producing neutron beams, use a superconducting magnet for the cyclotron's magnetic field. This necessitates complex liquid He equipment and presents problems in general hospital use. If conventional magnets are used, the weight of the magnet poles considerably complicates the design of the rotating gantry. Such a therapy machine, gantry and target facilities are described in detail. The use of protons and deuterons to produce the neutron beams is compared and contrasted. (U.K.)

  20. Man - Machine Communication

    CERN Document Server

    Petersen, Peter; Nielsen, Henning

    1984-01-01

    This report describes a Man-to-Machine Communication module which together with a STAC can take care of all operator inputs from the touch-screen, tracker balls and mechanical buttons. The MMC module can also contain a G64 card which could be a GPIB driver but many other G64 cards could be used. The soft-ware services the input devices and makes the results accessible from the CAMAC bus. NODAL functions for the Man Machine Communication is implemented in the STAC and in the ICC.

  1. MRTD: man versus machine

    Science.gov (United States)

    van Rheenen, Arthur D.; Taule, Petter; Thomassen, Jan Brede; Madsen, Eirik Blix

    2018-04-01

    We present Minimum-Resolvable Temperature Difference (MRTD) curves obtained by letting an ensemble of observers judge how many of the six four-bar patterns they can "see" in a set of images taken with different bar-to-background contrasts. The same images are analyzed using elemental signal analysis algorithms and machine-analysis based MRTD curves are obtained. We show that by adjusting the minimum required signal-to-noise ratio the machine-based MRTDs are very similar to the ones obtained with the help of the human observers.

  2. Advances in Machine Technology.

    Science.gov (United States)

    Clark, William R; Villa, Gianluca; Neri, Mauro; Ronco, Claudio

    2018-01-01

    Continuous renal replacement therapy (CRRT) machines have evolved into devices specifically designed for critically ill over the past 40 years. In this chapter, a brief history of this evolution is first provided, with emphasis on the manner in which changes have been made to address the specific needs of the critically ill patient with acute kidney injury. Subsequently, specific examples of technology developments for CRRT machines are discussed, including the user interface, pumps, pressure monitoring, safety features, and anticoagulation capabilities. © 2018 S. Karger AG, Basel.

  3. A physical implementation of the Turing machine accessed through Web

    Directory of Open Access Journals (Sweden)

    Marijo Maracic

    2008-11-01

    Full Text Available A Turing machine has an important role in education in the field of computer science, as it is a milestone in courses related to automata theory, theory of computation and computer architecture. Its value is also recognized in the Computing Curricula proposed by the Association for Computing Machinery (ACM and IEEE Computer Society. In this paper we present a physical implementation of the Turing machine accessed through Web. To enable remote access to the Turing machine, an implementation of the client-server architecture is built. The web interface is described in detail and illustrations of remote programming, initialization and the computation of the Turing machine are given. Advantages of such approach and expected benefits obtained by using remotely accessible physical implementation of the Turing machine as an educational tool in the teaching process are discussed.

  4. Microbiome Tools for Forensic Science.

    Science.gov (United States)

    Metcalf, Jessica L; Xu, Zhenjiang Z; Bouslimani, Amina; Dorrestein, Pieter; Carter, David O; Knight, Rob

    2017-09-01

    Microbes are present at every crime scene and have been used as physical evidence for over a century. Advances in DNA sequencing and computational approaches have led to recent breakthroughs in the use of microbiome approaches for forensic science, particularly in the areas of estimating postmortem intervals (PMIs), locating clandestine graves, and obtaining soil and skin trace evidence. Low-cost, high-throughput technologies allow us to accumulate molecular data quickly and to apply sophisticated machine-learning algorithms, building generalizable predictive models that will be useful in the criminal justice system. In particular, integrating microbiome and metabolomic data has excellent potential to advance microbial forensics. Copyright © 2017. Published by Elsevier Ltd.

  5. Machine learning application in the life time of materials

    OpenAIRE

    Yu, Xiaojiao

    2017-01-01

    Materials design and development typically takes several decades from the initial discovery to commercialization with the traditional trial and error development approach. With the accumulation of data from both experimental and computational results, data based machine learning becomes an emerging field in materials discovery, design and property prediction. This manuscript reviews the history of materials science as a disciplinary the most common machine learning method used in materials sc...

  6. Science | Argonne National Laboratory

    Science.gov (United States)

    Security Photon Sciences Physical Sciences & Engineering Energy Frontier Research Centers Scientific Publications Researchers Postdocs Exascale Computing Institute for Molecular Engineering at Argonne Work with Us About Safety News Careers Education Community Diversity Directory Argonne National Laboratory

  7. Design of rotating electrical machines

    CERN Document Server

    Pyrhonen , Juha; Hrabovcova , Valeria

    2013-01-01

    In one complete volume, this essential reference presents an in-depth overview of the theoretical principles and techniques of electrical machine design. This timely new edition offers up-to-date theory and guidelines for the design of electrical machines, taking into account recent advances in permanent magnet machines as well as synchronous reluctance machines. New coverage includes: Brand new material on the ecological impact of the motors, covering the eco-design principles of rotating electrical machinesAn expanded section on the design of permanent magnet synchronous machines, now repo

  8. Accelerator Mass Spectrometry with 15 UD pelletron at the Nuclear Science Centre, New Delhi

    International Nuclear Information System (INIS)

    Datta, S.K.

    1997-01-01

    The 15 UD Pelletron machine is widely used to carry on investigations in a variety of disciplines like nuclear physics, materials science, radiobiology etc. Accelerator Mass Spectrometry studies with 15 UD pelletron machine at Nuclear Science Centre are elaborated

  9. Machine learning properties of materials and molecules with entropy-regularized kernels

    Science.gov (United States)

    Ceriotti, Michele; Bartók, Albert; CsáNyi, GáBor; de, Sandip

    Application of machine-learning methods to physics, chemistry and materials science is gaining traction as a strategy to obtain accurate predictions of the properties of matter at a fraction of the typical cost of quantum mechanical electronic structure calculations. In this endeavor, one can leverage general-purpose frameworks for supervised-learning. It is however very important that the input data - for instance the positions of atoms in a molecule or solid - is processed into a form that reflects all the underlying physical symmetries of the problem, and that possesses the regularity properties that are required by machine-learning algorithms. Here we introduce a general strategy to build a representation of this kind. We will start from existing approaches to compare local environments (basically, groups of atoms), and combine them using techniques borrowed from optimal transport theory, discussing the relation between this idea and additive energy decompositions. We will present a few examples demonstrating the potential of this approach as a tool to predict molecular and materials' properties with an accuracy on par with state-of-the-art electronic structure methods. MARVEL NCCR (Swiss National Science Foundation) and ERC StG HBMAP (European Research Council, G.A. 677013).

  10. 55th International Conference of Machine Design Departments 2014

    CERN Document Server

    Berka, Ondrej; Petr, Karel; Lopot, František; Dub, Martin

    2016-01-01

    This book is based on the 55th International Conference of Machine Design Departments 2014 (ICMD 2014) which was hosted by the Czech Technical University in September 2014. It features scientific articles which solve progressive themes from the field of machine design. The book addresses a broad range of themes including tribology, hydraulics, materials science, product innovation and experimental methods. It presents the latest interdisciplinary high-tech work. People with an interest in the latest research results in the field of machine design and manufacturing engineering will value this book with contributions of leading academic scientists and experts from all around the world.

  11. Massively collaborative machine learning

    NARCIS (Netherlands)

    Rijn, van J.N.

    2016-01-01

    Many scientists are focussed on building models. We nearly process all information we perceive to a model. There are many techniques that enable computers to build models as well. The field of research that develops such techniques is called Machine Learning. Many research is devoted to develop

  12. Turbulence and Flying Machines

    Indian Academy of Sciences (India)

    other to make the aircraft roll. For example, a downward dis- placement of the left aileron causes the airplane to roll to the right. In Figure 4 the elevators have been deflected downwards, giving rise to a 'nose-down' moment about the pitch axis. Delaying Turbulence. In the last few decades, flying machines have proliferated ...

  13. Consuming a Machinic Servicescape

    OpenAIRE

    Hietanen, Joel; Andéhn, Mikael; Iddon, Thom; Denny, Iain; Ehnhage, Anna

    2016-01-01

    Consumer encounters with servicescapes tend to emphasize the harmonic tendency of their value-creating potential. We contest this assumption from a critical non-representational perspective that foregrounds the machinic and repressive potentiality of such con- sumption contexts. We offer the airport servicescape as an illustrative example. 

  14. War Machines and Ethics

    DEFF Research Database (Denmark)

    Nielsen, Thomas Galasz; Buhl, Kenneth Øhlenschlæger

    2018-01-01

    and save military lives. However, this opens up for discussions about ethical dilemmas about machines that autonomously are able to kill humans: What is an autonomous weapons system? What laws covers the use of fully autonomous weapons systems? Should it apply to International Humanitarian Law?...

  15. GPK heading machine

    Energy Technology Data Exchange (ETDEWEB)

    Krmasek, J.; Novosad, K.

    1981-01-01

    This article evaluates performance tests of the Soviet made GPK heading machine carried out in 4 coal mines in Czechoslovakia (Ostrava-Karvina region and Kladno mines). GPK works in coal seams and rocks with compression strength of 40 to 50 MPa. Dimensions of the tunnel are height 1.8 to 3.8 m and width 2.6 to 4.7 m, tunnel gradient plus to minus 10 degrees. GPK weighs 16 t, its conical shaped cutting head equipped with RKS-1 cutting tools is driven by an electric motor with 55 kW capacity. Undercarriage of the GPK, gathering-arm loader, hydraulic system, electric system and dust supression system (water spraying or pneumatic section) are characterized. Specifications of GPK heading machines are compared with PK-3r and F8 heading machines. Reliability, number of failures, dust level, noise, productivity depending on compression strength of rocks, heading rate in coal and in rocks, energy consumption, performance in inclined tunnels, and cutting tool wear are evaluated. Tests show that GPK can be used to drive tunnels in coal with rock constituting up to 50% of the tunnel crosscut, as long as rock compression strength does not exceed 50 MPa. In rocks characterized by higher compression strength cutting tool wear sharply increases. GPK is characterized by higher productivity than that of the PK-3r heading machine. Among the weak points of the GPK are: unsatisfactory reliability and excessive wear of its elements. (4 refs.) (In Czech)

  16. Machine Dictation and Transcription.

    Science.gov (United States)

    Harvey, Evelyn; And Others

    This instructional package contains both an instructor's manual and a student's manual for a course in machine dictation and transcription. The instructor's manual contains an overview with tips on teaching the course, letters for dictation, and a key to the letters. The student's manual contains an overview of the course and of the skills needed…

  17. ADAM: ADaptive Autonomous Machine

    NARCIS (Netherlands)

    van Oosten, Daan C.; Nijenhuis, Lucas F.J.; Bakkers, André; Vervoort, Wiek

    1996-01-01

    This paper describes a part of the development of an adaptive autonomous machine that is able to move in an unknown world extract knowledge out of the perceived data, has the possibility to reason, and finally has the capability to exchange experiences and knowledge with other agents. The agent is

  18. Machine Parts as Metaphor.

    Science.gov (United States)

    Porter, Gerald

    The connection between Language for Specific Purposes (LSP) and literature is discussed with examples of technical vocabulary drawn from a variety of writers, with particular attention to a sketch by the British dramatist Harold Pinter, "Trouble in the Works," which makes extensive use of the terminology of machine parts. It is noted…

  19. Machine-Learning Research

    OpenAIRE

    Dietterich, Thomas G.

    1997-01-01

    Machine-learning research has been making great progress in many directions. This article summarizes four of these directions and discusses some current open problems. The four directions are (1) the improvement of classification accuracy by learning ensembles of classifiers, (2) methods for scaling up supervised learning algorithms, (3) reinforcement learning, and (4) the learning of complex stochastic models.

  20. Hybrid machining processes perspectives on machining and finishing

    CERN Document Server

    Gupta, Kapil; Laubscher, R F

    2016-01-01

    This book describes various hybrid machining and finishing processes. It gives a critical review of the past work based on them as well as the current trends and research directions. For each hybrid machining process presented, the authors list the method of material removal, machining system, process variables and applications. This book provides a deep understanding of the need, application and mechanism of hybrid machining processes.

  1. Tanweer Hussain | Speakers | Indian Academy of Sciences

    Indian Academy of Sciences (India)

    Understanding the principles of design of molecular machines: A structural biology perspective View Presentation / View Video. The determination of the three-dimensional structures of molecular machines, using various approaches of structural biology, has played a major role in understanding the design of individual ...

  2. Machining of Machine Elements Made of Polymer Composite Materials

    Science.gov (United States)

    Baurova, N. I.; Makarov, K. A.

    2017-12-01

    The machining of the machine elements that are made of polymer composite materials (PCMs) or are repaired using them is considered. Turning, milling, and drilling are shown to be most widely used among all methods of cutting PCMs. Cutting conditions for the machining of PCMs are presented. The factors that most strongly affect the roughness parameters and the accuracy of cutting PCMs are considered.

  3. Turing Machines with One-sided Advice and Acceptance of the co-RE Languages

    Czech Academy of Sciences Publication Activity Database

    van Leeuwen, J.; Wiedermann, Jiří

    2017-01-01

    Roč. 153, č. 4 (2017), s. 347-366 ISSN 0169-2968 Grant - others:GA ČR(CZ) GA15-04960S Institutional support: RVO:67985807 Keywords : advice functions * co-RE language s * machine models * Turing machines Subject RIV: IN - Informatics, Computer Science OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 0.687, year: 2016

  4. Environmental assessment for the resiting, construction, and operation of the Environmental and Molecular Sciences Laboratory at the Hanford Site, Richland, Washington

    Energy Technology Data Exchange (ETDEWEB)

    1994-07-01

    This environmental assessment (EA) presents estimated environmental impacts from the resiting, construction, and operation of the US Department of Energy`s (DOE`s) Environmental and Molecular Sciences Laboratory (EMSL), which is proposed to be constructed and operated on land near the south boundary of the Hanford Site near Richland, Washington. The EMSL, if constructed, would be a modern research facility in which experimental, theoretical, and computational techniques can be focused on environmental restoration problems, such as the chemical and transport behavior of complex mixtures of contaminants in the environment. The EMSL design includes approximately 18,500 square meters (200,000 square feet) of floor space on a 12-hectare (30-acre) site. The proposed new site is located within the city limits of Richland in north Richland, at the south end of DOE`s 300 Area, on land to be deeded to the US by the Battelle Memorial Institute. Approximately 200 persons are expected to be employed in the EMSL and approximately 60 visiting scientists may be working in the EMSL at any given time. State-of-the-art equipment is expected to be installed and used in the EMSL. Small amounts of hazardous substances (chemicals and radionuclides) are expected to be used in experimental work in the EMSL.

  5. Traceability of On-Machine Tool Measurement: A Review

    Science.gov (United States)

    Gomez-Acedo, Eneko; Kortaberria, Gorka; Olarra, Aitor

    2017-01-01

    Nowadays, errors during the manufacturing process of high value components are not acceptable in driving industries such as energy and transportation. Sectors such as aerospace, automotive, shipbuilding, nuclear power, large science facilities or wind power need complex and accurate components that demand close measurements and fast feedback into their manufacturing processes. New measuring technologies are already available in machine tools, including integrated touch probes and fast interface capabilities. They provide the possibility to measure the workpiece in-machine during or after its manufacture, maintaining the original setup of the workpiece and avoiding the manufacturing process from being interrupted to transport the workpiece to a measuring position. However, the traceability of the measurement process on a machine tool is not ensured yet and measurement data is still not fully reliable enough for process control or product validation. The scientific objective is to determine the uncertainty on a machine tool measurement and, therefore, convert it into a machine integrated traceable measuring process. For that purpose, an error budget should consider error sources such as the machine tools, components under measurement and the interactions between both of them. This paper reviews all those uncertainty sources, being mainly focused on those related to the machine tool, either on the process of geometric error assessment of the machine or on the technology employed to probe the measurand. PMID:28696358

  6. Traceability of On-Machine Tool Measurement: A Review.

    Science.gov (United States)

    Mutilba, Unai; Gomez-Acedo, Eneko; Kortaberria, Gorka; Olarra, Aitor; Yagüe-Fabra, Jose A

    2017-07-11

    Nowadays, errors during the manufacturing process of high value components are not acceptable in driving industries such as energy and transportation. Sectors such as aerospace, automotive, shipbuilding, nuclear power, large science facilities or wind power need complex and accurate components that demand close measurements and fast feedback into their manufacturing processes. New measuring technologies are already available in machine tools, including integrated touch probes and fast interface capabilities. They provide the possibility to measure the workpiece in-machine during or after its manufacture, maintaining the original setup of the workpiece and avoiding the manufacturing process from being interrupted to transport the workpiece to a measuring position. However, the traceability of the measurement process on a machine tool is not ensured yet and measurement data is still not fully reliable enough for process control or product validation. The scientific objective is to determine the uncertainty on a machine tool measurement and, therefore, convert it into a machine integrated traceable measuring process. For that purpose, an error budget should consider error sources such as the machine tools, components under measurement and the interactions between both of them. This paper reviews all those uncertainty sources, being mainly focused on those related to the machine tool, either on the process of geometric error assessment of the machine or on the technology employed to probe the measurand.

  7. DESIGN OF GRASS BRIQUETTE MACHINE

    African Journals Online (AJOL)

    user

    E-mail addresses: 1 mike.ajieh@gmail.com, 2 dracigboanugo@yahoo.com, ... machine design was considered for processing biomass of grass origin. The machine operations include pulverization, compaction and extrusion of the briquettes.

  8. New Applications of Learning Machines

    DEFF Research Database (Denmark)

    Larsen, Jan

    * Machine learning framework for sound search * Genre classification * Music separation * MIMO channel estimation and symbol detection......* Machine learning framework for sound search * Genre classification * Music separation * MIMO channel estimation and symbol detection...

  9. Tattoo machines, needles and utilities.

    Science.gov (United States)

    Rosenkilde, Frank

    2015-01-01

    Starting out as a professional tattooist back in 1977 in Copenhagen, Denmark, Frank Rosenkilde has personally experienced the remarkable development of tattoo machines, needles and utilities: all the way from home-made equipment to industrial products of substantially improved quality. Machines can be constructed like the traditional dual-coil and single-coil machines or can be e-coil, rotary and hybrid machines, with the more convenient and precise rotary machines being the recent trend. This development has resulted in disposable needles and utilities. Newer machines are more easily kept clean and protected with foil to prevent crosscontaminations and infections. The machines and the tattooists' knowledge and awareness about prevention of infection have developed hand-in-hand. For decades, Frank Rosenkilde has been collecting tattoo machines. Part of his collection is presented here, supplemented by his personal notes. © 2015 S. Karger AG, Basel.

  10. QCD machines - present and future

    International Nuclear Information System (INIS)

    Christ, N.H.

    1991-01-01

    The present status of the currently working and nearly working dedicated QCD machines is reviewed and proposals for future machines are discussed with particular emphasis on the QCD Teraflop Project in the US. (orig.)

  11. Advances in Machine Learning and Data Mining for Astronomy

    Science.gov (United States)

    Way, Michael J.; Scargle, Jeffrey D.; Ali, Kamal M.; Srivastava, Ashok N.

    2012-03-01

    Advances in Machine Learning and Data Mining for Astronomy documents numerous successful collaborations among computer scientists, statisticians, and astronomers who illustrate the application of state-of-the-art machine learning and data mining techniques in astronomy. Due to the massive amount and complexity of data in most scientific disciplines, the material discussed in this text transcends traditional boundaries between various areas in the sciences and computer science. The book's introductory part provides context to issues in the astronomical sciences that are also important to health, social, and physical sciences, particularly probabilistic and statistical aspects of classification and cluster analysis. The next part describes a number of astrophysics case studies that leverage a range of machine learning and data mining technologies. In the last part, developers of algorithms and practitioners of machine learning and data mining show how these tools and techniques are used in astronomical applications. With contributions from leading astronomers and computer scientists, this book is a practical guide to many of the most important developments in machine learning, data mining, and statistics. It explores how these advances can solve current and future problems in astronomy and looks at how they could lead to the creation of entirely new algorithms within the data mining community.

  12. EAST machine assembly and its measurement system

    International Nuclear Information System (INIS)

    Wu, S.T.

    2005-01-01

    The EAST (HT-7U) superconducting tokamak consists of a superconducting poloidal field magnet system, a toroidal field magnet system, a vacuum vessel and in-vessel components, thermal shields and a cryostat vessel. The main parts of the machine have been delivered to ASIPP (Institute of Plasma Physics, Chinese Academy of Sciences) successionally from 2003. For its complicated constitution and precise requirement, a reasonable assembly procedure and measurement technique should be defined carefully. Before the assembly procedure, a reference frame has been set up with reference fiducial targets on the wall of the test hall by an industrial measurement system. After the torus of TF coils is formed, a new reference frame will be set up from the position of the TF torus. The vacuum vessel with all inner parts will be installed with reference of the new reference frame. The big size and mass of components, special configuration of the superconducting machine with tight installation tolerances of the HT-7U (EAST) machine result in complicated assembly procedure. The procedure had begun with the installation of the support frame and the base of cryostat vessel last year. In this paper, the requirements of the assembly precise for some key components of the machine are described. The reference frame for the assembly and maintenance is explained. The assembly procedure is introduced

  13. The ATLAS Higgs Machine Learning Challenge

    CERN Document Server

    Cowan, Glen; The ATLAS collaboration; Bourdarios, Claire

    2015-01-01

    High Energy Physics has been using Machine Learning techniques (commonly known as Multivariate Analysis) since the 1990s with Artificial Neural Net and more recently with Boosted Decision Trees, Random Forest etc. Meanwhile, Machine Learning has become a full blown field of computer science. With the emergence of Big Data, data scientists are developing new Machine Learning algorithms to extract meaning from large heterogeneous data. HEP has exciting and difficult problems like the extraction of the Higgs boson signal, and at the same time data scientists have advanced algorithms: the goal of the HiggsML project was to bring the two together by a “challenge”: participants from all over the world and any scientific background could compete online to obtain the best Higgs to tau tau signal significance on a set of ATLAS fully simulated Monte Carlo signal and background. Instead of HEP physicists browsing through machine learning papers and trying to infer which new algorithms might be useful for HEP, then c...

  14. Machine Learning Approaches in Cardiovascular Imaging.

    Science.gov (United States)

    Henglin, Mir; Stein, Gillian; Hushcha, Pavel V; Snoek, Jasper; Wiltschko, Alexander B; Cheng, Susan

    2017-10-01

    Cardiovascular imaging technologies continue to increase in their capacity to capture and store large quantities of data. Modern computational methods, developed in the field of machine learning, offer new approaches to leveraging the growing volume of imaging data available for analyses. Machine learning methods can now address data-related problems ranging from simple analytic queries of existing measurement data to the more complex challenges involved in analyzing raw images. To date, machine learning has been used in 2 broad and highly interconnected areas: automation of tasks that might otherwise be performed by a human and generation of clinically important new knowledge. Most cardiovascular imaging studies have focused on task-oriented problems, but more studies involving algorithms aimed at generating new clinical insights are emerging. Continued expansion in the size and dimensionality of cardiovascular imaging databases is driving strong interest in applying powerful deep learning methods, in particular, to analyze these data. Overall, the most effective approaches will require an investment in the resources needed to appropriately prepare such large data sets for analyses. Notwithstanding current technical and logistical challenges, machine learning and especially deep learning methods have much to offer and will substantially impact the future practice and science of cardiovascular imaging. © 2017 American Heart Association, Inc.

  15. Material Choice for spindle of machine tools

    Science.gov (United States)

    Gouasmi, S.; Merzoug, B.; Abba, G.; Kherredine, L.

    2012-02-01

    The requirements of contemporary industry and the flashing development of modern sciences impose restrictions on the majority of the elements of machines; the resulting financial constraints can be satisfied by a better output of the production equipment. As for those concerning the design, the resistance and the correct operation of the product, these require the development of increasingly precise parts, therefore the use of increasingly powerful tools [5]. The precision of machining and the output of the machine tools are generally determined by the precision of rotation of the spindle, indeed, more this one is large more the dimensions to obtain are in the zone of tolerance and the defects of shape are minimized. During the development of the machine tool, the spindle which by definition is a rotating shaft receiving and transmitting to the work piece or the cutting tool the rotational movement, must be designed according to certain optimal parameters to be able to ensure the precision required. This study will be devoted to the choice of the material of the spindle fulfilling the imposed requirements of precision.

  16. Material Choice for spindle of machine tools

    International Nuclear Information System (INIS)

    Gouasmi, S; Merzoug, B; Kherredine, L; Abba, G

    2012-01-01

    The requirements of contemporary industry and the flashing development of modern sciences impose restrictions on the majority of the elements of machines; the resulting financial constraints can be satisfied by a better output of the production equipment. As for those concerning the design, the resistance and the correct operation of the product, these require the development of increasingly precise parts, therefore the use of increasingly powerful tools [5]. The precision of machining and the output of the machine tools are generally determined by the precision of rotation of the spindle, indeed, more this one is large more the dimensions to obtain are in the zone of tolerance and the defects of shape are minimized. During the development of the machine tool, the spindle which by definition is a rotating shaft receiving and transmitting to the work piece or the cutting tool the rotational movement, must be designed according to certain optimal parameters to be able to ensure the precision required. This study will be devoted to the choice of the material of the spindle fulfilling the imposed requirements of precision.

  17. The Basics of Stellites in Machining Perspective

    Directory of Open Access Journals (Sweden)

    Md Shahanur Hasan

    2016-12-01

    Full Text Available Stellites are cobalt (Co-based superalloys available in two main combinations: (a a Tungsten (W group with composition of Co-Cr-W-C, and (b a Molybdenum (Mo group containing Co-Cr-Mo-C. Stellites possess outstanding corrosion resistance, oxidation resistance, wear resistance, heat resistance, and low magnetic permeability. Components made of stellites work well in highly corrosive environments and maintain these advantageous properties at elevated temperatures. Components made of stellites are widely used in the oil and gas, automotive, nuclear power, paper and pulp, chemical and petrochemical, refineries, automobile, aerospace and aircraft industries. By virtue of their nonmagnetic, anticorrosive and non-reactivity to human body-fluid properties, stellites are used in medical surgery and in surgical tools, tooth and bone implants and replacements, heart valves, and in heart pacemakers. The hardness range of stellites is from 32 to 55 HRC, which makes stellites brittle materials but they have a low Young’s modulus. Due to their high hardness, dense but non-homogeneous molecular structure and lower thermal conductivity, machining operations for parts made of stellites are extremely difficult, categorising stellites as difficult-to-machine materials like Ti-alloys, inconels, composites and stainless steels. Usually, machine components made of stellites are produced by a deposition method onto steel substrates instead of expensive solid stellite bars. The rough surfaces of deposited stellites are then finished by grinding, rather than some other economic machining process, which is costly and time-consuming, making stellite products very expensive. This paper provides a basic overview of stellites applicable in engineering, their significances and specific applications, advantages and disadvantages in respect of machining processes. A brief review on experimental research on economically rational cutting parameters for turning operations of

  18. Concept Representation Analysis in the Context of Human-Machine Interactions

    DEFF Research Database (Denmark)

    Badie, Farshad

    2016-01-01

    an inductive machine learning paradigm). The results will support figuring out the most significant key points for constructing a conceptual linkage between a human learning theory and a machine learning paradigm. Accordingly, I will construct a conceptual ground for expressing and analysing concepts......This article attempts to make a conceptual and epistemological junction between human learning and machine learning. I will be concerned with specifying and analysing the structure of concepts in the common ground between a concept-based human learning theory and a concept-based machine learning...... in the common ground of human and informatics sciences and in the context of human-machine interplays....

  19. Student Modeling and Machine Learning

    OpenAIRE

    Sison , Raymund; Shimura , Masamichi

    1998-01-01

    After identifying essential student modeling issues and machine learning approaches, this paper examines how machine learning techniques have been used to automate the construction of student models as well as the background knowledge necessary for student modeling. In the process, the paper sheds light on the difficulty, suitability and potential of using machine learning for student modeling processes, and, to a lesser extent, the potential of using student modeling techniques in machine le...

  20. Machine Translation Effect on Communication

    DEFF Research Database (Denmark)

    Jensen, Mika Yasuoka; Bjørn, Pernille

    2011-01-01

    Intercultural collaboration facilitated by machine translation has gradually spread in various settings. Still, little is known as for the practice of machine-translation mediated communication. This paper investigates how machine translation affects intercultural communication in practice. Based...... on communication in which multilingual communication system is applied, we identify four communication types and its’ influences on stakeholders’ communication process, especially focusing on establishment and maintenance of common ground. Different from our expectation that quality of machine translation results...