Leveraging knowledge engineering and machine learning for microbial bio-manufacturing.

PubMed

Oyetunde, Tolutola; Bao, Forrest Sheng; Chen, Jiung-Wen; Martin, Hector Garcia; Tang, Yinjie J

2018-05-03

Genome scale modeling (GSM) predicts the performance of microbial workhorses and helps identify beneficial gene targets. GSM integrated with intracellular flux dynamics, omics, and thermodynamics have shown remarkable progress in both elucidating complex cellular phenomena and computational strain design (CSD). Nonetheless, these models still show high uncertainty due to a poor understanding of innate pathway regulations, metabolic burdens, and other factors (such as stress tolerance and metabolite channeling). Besides, the engineered hosts may have genetic mutations or non-genetic variations in bioreactor conditions and thus CSD rarely foresees fermentation rate and titer. Metabolic models play important role in design-build-test-learn cycles for strain improvement, and machine learning (ML) may provide a viable complementary approach for driving strain design and deciphering cellular processes. In order to develop quality ML models, knowledge engineering leverages and standardizes the wealth of information in literature (e.g., genomic/phenomic data, synthetic biology strategies, and bioprocess variables). Data driven frameworks can offer new constraints for mechanistic models to describe cellular regulations, to design pathways, to search gene targets, and to estimate fermentation titer/rate/yield under specified growth conditions (e.g., mixing, nutrients, and O 2 ). This review highlights the scope of information collections, database constructions, and machine learning techniques (such as deep learning and transfer learning), which may facilitate "Learn and Design" for strain development. Copyright © 2018. Published by Elsevier Inc.

Allocating dissipation across a molecular machine cycle to maximize flux

PubMed Central

Brown, Aidan I.; Sivak, David A.

2017-01-01

Biomolecular machines consume free energy to break symmetry and make directed progress. Nonequilibrium ATP concentrations are the typical free energy source, with one cycle of a molecular machine consuming a certain number of ATP, providing a fixed free energy budget. Since evolution is expected to favor rapid-turnover machines that operate efficiently, we investigate how this free energy budget can be allocated to maximize flux. Unconstrained optimization eliminates intermediate metastable states, indicating that flux is enhanced in molecular machines with fewer states. When maintaining a set number of states, we show that—in contrast to previous findings—the flux-maximizing allocation of dissipation is not even. This result is consistent with the coexistence of both “irreversible” and reversible transitions in molecular machine models that successfully describe experimental data, which suggests that, in evolved machines, different transitions differ significantly in their dissipation. PMID:29073016

Neuromorphic Optical Signal Processing and Image Understanding for Automated Target Recognition

DTIC Science & Technology

1989-12-01

34 Stochastic Learning Machine " Neuromorphic Target Identification * Cognitive Networks 3. Conclusions ..... ................ .. 12 4. Publications...16 5. References ...... ................... . 17 6. Appendices ....... .................. 18 I. Optoelectronic Neural Networks and...Learning Machines. II. Stochastic Optical Learning Machine. III. Learning Network for Extrapolation AccesFon For and Radar Target Identification

CMM Interim Check (U)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Montano, Joshua Daniel

2015-03-23

Coordinate Measuring Machines (CMM) are widely used in industry, throughout the Nuclear Weapons Complex and at Los Alamos National Laboratory (LANL) to verify part conformance to design definition. Calibration cycles for CMMs at LANL are predominantly one year in length. Unfortunately, several nonconformance reports have been generated to document the discovery of a certified machine found out of tolerance during a calibration closeout. In an effort to reduce risk to product quality two solutions were proposed – shorten the calibration cycle which could be costly, or perform an interim check to monitor the machine’s performance between cycles. The CMM interimmore » check discussed makes use of Renishaw’s Machine Checking Gauge. This off-the-shelf product simulates a large sphere within a CMM’s measurement volume and allows for error estimation. Data was gathered, analyzed, and simulated from seven machines in seventeen different configurations to create statistical process control run charts for on-the-floor monitoring.« less

A New High-Speed Oil-Free Turbine Engine Rotordynamic Simulator Test Rig

NASA Technical Reports Server (NTRS)

Howard, Samuel A.

2007-01-01

A new test rig has been developed for simulating high-speed turbomachinery rotor systems using Oil-Free foil air bearing technology. Foil air bearings have been used in turbomachinery, primarily air cycle machines, for the past four decades to eliminate the need for oil lubrication. The goal of applying this bearing technology to other classes of turbomachinery has prompted the fabrication of this test rig. The facility gives bearing designers the capability to test potential bearing designs with shafts that simulate the rotating components of a target machine without the high cost of building "make-and-break" hardware. The data collected from this rig can be used to make design changes to the shaft and bearings in subsequent design iterations. This paper describes the new test rig and demonstrates its capabilities through the initial run with a simulated shaft system.

Field precision machining technology of target chamber in ICF lasers

NASA Astrophysics Data System (ADS)

Xu, Yuanli; Wu, Wenkai; Shi, Sucun; Duan, Lin; Chen, Gang; Wang, Baoxu; Song, Yugang; Liu, Huilin; Zhu, Mingzhi

2016-10-01

In ICF lasers, many independent laser beams are required to be positioned on target with a very high degree of accuracy during a shot. The target chamber provides a precision platform and datum reference for final optics assembly and target collimation and location system. The target chamber consists of shell with welded flanges, reinforced concrete pedestal, and lateral support structure. The field precision machining technology of target chamber in ICF lasers have been developed based on ShenGuangIII (SGIII). The same center of the target chamber is adopted in the process of design, fabrication, and alignment. The technologies of beam collimation and datum reference transformation are developed for the fabrication, positioning and adjustment of target chamber. A supporting and rotating mechanism and a special drilling machine are developed to bore the holes of ports. An adjustment mechanism is designed to accurately position the target chamber. In order to ensure the collimation requirements of the beam leading and focusing and the target positioning, custom-machined spacers are used to accurately correct the alignment error of the ports. Finally, this paper describes the chamber center, orientation, and centering alignment error measurements of SGIII. The measurements show the field precision machining of SGIII target chamber meet its design requirement. These information can be used on similar systems.

Machine compliance in compression tests

NASA Astrophysics Data System (ADS)

Sousa, Pedro; Ivens, Jan; Lomov, Stepan V.

2018-05-01

The compression behavior of a material cannot be accurately determined if the machine compliance is not accounted prior to the measurements. This work discusses the machine compliance during a compressibility test with fiberglass fabrics. The thickness variation was measured during loading and unloading cycles with a relaxation stage of 30 minutes between them. The measurements were performed using an indirect technique based on the comparison between the displacement at a free compression cycle and the displacement with a sample. Relating to the free test, it has been noticed the nonexistence of machine relaxation during relaxation stage. Considering relaxation or not, the characteristic curves for a free compression cycle can be overlapped precisely in the majority of the points. For the compression test with sample, it was noticed a non-physical decrease of about 30 µm during the relaxation stage, what can be explained by the greater fabric relaxation in relation to the machine relaxation. Beyond the technique normally used, another technique was used which allows a constant thickness during relaxation. Within this second method, machine displacement with sample is simply subtracted to the machine displacement without sample being imposed as constant. If imposed as a constant it will remain constant during relaxation stage and it will suddenly decrease after relaxation. If constantly calculated it will decrease gradually during relaxation stage. Independently of the technique used the final result will remain unchanged. The uncertainty introduced by this imprecision is about ±15 µm.

Methods, systems and apparatus for adjusting duty cycle of pulse width modulated (PWM) waveforms

DOEpatents

Gallegos-Lopez, Gabriel; Kinoshita, Michael H; Ransom, Ray M; Perisic, Milun

2013-05-21

Embodiments of the present invention relate to methods, systems and apparatus for controlling operation of a multi-phase machine in a vector controlled motor drive system when the multi-phase machine operates in an overmodulation region. The disclosed embodiments provide a mechanism for adjusting a duty cycle of PWM waveforms so that the correct phase voltage command signals are applied at the angle transitions. This can reduce variations/errors in the phase voltage command signals applied to the multi-phase machine so that phase current may be properly regulated thus reducing current/torque oscillation, which can in turn improve machine efficiency and performance, as well as utilization of the DC voltage source.

Energy efficient quantum machines

NASA Astrophysics Data System (ADS)

Abah, Obinna; Lutz, Eric

2017-05-01

We investigate the performance of a quantum thermal machine operating in finite time based on shortcut-to-adiabaticity techniques. We compute efficiency and power for a paradigmatic harmonic quantum Otto engine by taking the energetic cost of the shortcut driving explicitly into account. We demonstrate that shortcut-to-adiabaticity machines outperform conventional ones for fast cycles. We further derive generic upper bounds on both quantities, valid for any heat engine cycle, using the notion of quantum speed limit for driven systems. We establish that these quantum bounds are tighter than those stemming from the second law of thermodynamics.

Realization of process improvement at a diagnostic radiology department with aid of simulation modeling.

PubMed

Oh, Hong-Choon; Toh, Hong-Guan; Giap Cheong, Eddy Seng

2011-11-01

Using the classical process improvement framework of Plan-Do-Study-Act (PDSA), the diagnostic radiology department of a tertiary hospital identified several patient cycle time reduction strategies. Experimentation of these strategies (which included procurement of new machines, hiring of new staff, redesign of queue system, etc.) through pilot scale implementation was impractical because it might incur substantial expenditure or be operationally disruptive. With this in mind, simulation modeling was used to test these strategies via performance of "what if" analyses. Using the output generated by the simulation model, the team was able to identify a cost-free cycle time reduction strategy, which subsequently led to a reduction of patient cycle time and achievement of a management-defined performance target. As healthcare professionals work continually to improve healthcare operational efficiency in response to rising healthcare costs and patient expectation, simulation modeling offers an effective scientific framework that can complement established process improvement framework like PDSA to realize healthcare process enhancement. © 2011 National Association for Healthcare Quality.

33 CFR 157.150 - Crude Oil Washing Operations and Equipment Manual: Recording information after inspections.

Code of Federal Regulations, 2010 CFR

2010-07-01

... MARINE ENVIRONMENT RELATING TO TANK VESSELS CARRYING OIL IN BULK Crude Oil Washing (COW) System on Tank... used to pass the inspections under § 157.140: (1) Pressure and flow of the crude oil pumped to the COW machines. (2) Revolutions, number of cycles, and length of cycles of each COW machine. (3) Pressure and...

Ideal thermodynamic processes of oscillatory-flow regenerative engines will go to ideal stirling cycle?

NASA Astrophysics Data System (ADS)

Luo, Ercang

2012-06-01

This paper analyzes the thermodynamic cycle of oscillating-flow regenerative machines. Unlike the classical analysis of thermodynamic textbooks, the assumptions for pistons' movement limitations are not needed and only ideal flowing and heat transfer should be maintained in our present analysis. Under such simple assumptions, the meso-scale thermodynamic cycles of each gas parcel in typical locations of a regenerator are analyzed. It is observed that the gas parcels in the regenerator undergo Lorentz cycle in different temperature levels, whereas the locus of all gas parcels inside the regenerator is the Ericson-like thermodynamic cycle. Based on this new finding, the author argued that ideal oscillating-flow machines without heat transfer and flowing losses is not the Stirling cycle. However, this new thermodynamic cycle can still achieve the same efficiency of the Carnot heat engine and can be considered a new reversible thermodynamic cycle under two constant-temperature heat sinks.

Application of target costing in machining

NASA Astrophysics Data System (ADS)

Gopalakrishnan, Bhaskaran; Kokatnur, Ameet; Gupta, Deepak P.

2004-11-01

In today's intensely competitive and highly volatile business environment, consistent development of low cost and high quality products meeting the functionality requirements is a key to a company's survival. Companies continuously strive to reduce the costs while still producing quality products to stay ahead in the competition. Many companies have turned to target costing to achieve this objective. Target costing is a structured approach to determine the cost at which a proposed product, meeting the quality and functionality requirements, must be produced in order to generate the desired profits. It subtracts the desired profit margin from the company's selling price to establish the manufacturing cost of the product. Extensive literature review revealed that companies in automotive, electronic and process industries have reaped the benefits of target costing. However target costing approach has not been applied in the machining industry, but other techniques based on Geometric Programming, Goal Programming, and Lagrange Multiplier have been proposed for application in this industry. These models follow a forward approach, by first selecting a set of machining parameters, and then determining the machining cost. Hence in this study we have developed an algorithm to apply the concepts of target costing, which is a backward approach that selects the machining parameters based on the required machining costs, and is therefore more suitable for practical applications in process improvement and cost reduction. A target costing model was developed for turning operation and was successfully validated using practical data.

An easy-to-use calculating machine to simulate steady state and non-steady-state preparative separations by multiple dual mode counter-current chromatography with semi-continuous loading of feed mixtures.

PubMed

Kostanyan, Artak E; Shishilov, Oleg N

2018-06-01

Multiple dual mode counter-current chromatography (MDM CCC) separation processes with semi-continuous large sample loading consist of a succession of two counter-current steps: with "x" phase (first step) and "y" phase (second step) flow periods. A feed mixture dissolved in the "x" phase is continuously loaded into a CCC machine at the beginning of the first step of each cycle over a constant time with the volumetric rate equal to the flow rate of the pure "x" phase. An easy-to-use calculating machine is developed to simulate the chromatograms and the amounts of solutes eluted with the phases at each cycle for steady-state (the duration of the flow periods of the phases is kept constant for all the cycles) and non-steady-state (with variable duration of alternating phase elution steps) separations. Using the calculating machine, the separation of mixtures containing up to five components can be simulated and designed. Examples of the application of the calculating machine for the simulation of MDM CCC processes are discussed. Copyright © 2018 Elsevier B.V. All rights reserved.

Elevated Temperature Fatigue Endurance of Three Ceramic Matrix Composites

NASA Technical Reports Server (NTRS)

Kalluri, Sreeramesh; Verrilli, Michael J.

2007-01-01

High-cycle fatigue endurance of three candidate materials for the acoustic liners of the Enabling Propulsion Materials Nozzle Program was investigated. The ceramic matrix composite materials investigated were N720/AS (Nextel 720, 3M Corporation), Sylramic S200 (Dow Corning), and UT 22. High-cycle fatigue tests were conducted in air at 910 C on as-machined specimens and on specimens subjected to tensile cyclic load excursions every 160 hr followed by thermal exposure at 910 C in a furnace up to total exposure times of 2066 and 4000 hr. All the fatigue tests were conducted in air at 100 Hz with a servohydraulic test machine. In the as-machined condition, among the three materials investigated only the Sylramic S200 exhibited a deterministic type of high-cycle fatigue behavior. Both the N720/AS and UT-22 exhibited significant scatter in the experimentally observed high-cycle fatigue lives. Among the thermally exposed specimens, N720/AS and Sylramic S200 materials exhibited a reduction in the high-cycle fatigue lives, particularly at the exposure time of 4000 hr.

Alternative thermodynamic cycle for the Stirling machine

NASA Astrophysics Data System (ADS)

Romanelli, Alejandro

2017-12-01

We develop an alternative thermodynamic cycle for the Stirling machine, where the polytropic process plays a central role. Analytical expressions for pressure and temperatures of the working gas are obtained as a function of the volume and the parameter that characterizes the polytropic process. This approach achieves closer agreement with the experimental pressure-volume diagram and can be adapted to any type of Stirling engine.

Methods, systems and apparatus for controlling operation of two alternating current (AC) machines

DOEpatents

Gallegos-Lopez, Gabriel [Torrance, CA; Nagashima, James M [Cerritos, CA; Perisic, Milun [Torrance, CA; Hiti, Silva [Redondo Beach, CA

2012-06-05

A system is provided for controlling two alternating current (AC) machines via a five-phase PWM inverter module. The system comprises a first control loop, a second control loop, and a current command adjustment module. The current command adjustment module operates in conjunction with the first control loop and the second control loop to continuously adjust current command signals that control the first AC machine and the second AC machine such that they share the input voltage available to them without compromising the target mechanical output power of either machine. This way, even when the phase voltage available to either one of the machines decreases, that machine outputs its target mechanical output power.

Study on effect of tool electrodes on surface finish during electrical discharge machining of Nitinol

NASA Astrophysics Data System (ADS)

Sahu, Anshuman Kumar; Chatterjee, Suman; Nayak, Praveen Kumar; Sankar Mahapatra, Siba

2018-03-01

Electrical discharge machining (EDM) is a non-traditional machining process which is widely used in machining of difficult-to-machine materials. EDM process can produce complex and intrinsic shaped component made of difficult-to-machine materials, largely applied in aerospace, biomedical, die and mold making industries. To meet the required applications, the EDMed components need to possess high accuracy and excellent surface finish. In this work, EDM process is performed using Nitinol as work piece material and AlSiMg prepared by selective laser sintering (SLS) as tool electrode along with conventional copper and graphite electrodes. The SLS is a rapid prototyping (RP) method to produce complex metallic parts by additive manufacturing (AM) process. Experiments have been carried out varying different process parameters like open circuit voltage (V), discharge current (Ip), duty cycle (τ), pulse-on-time (Ton) and tool material. The surface roughness parameter like average roughness (Ra), maximum height of the profile (Rt) and average height of the profile (Rz) are measured using surface roughness measuring instrument (Talysurf). To reduce the number of experiments, design of experiment (DOE) approach like Taguchi’s L27 orthogonal array has been chosen. The surface properties of the EDM specimen are optimized by desirability function approach and the best parametric setting is reported for the EDM process. Type of tool happens to be the most significant parameter followed by interaction of tool type and duty cycle, duty cycle, discharge current and voltage. Better surface finish of EDMed specimen can be obtained with low value of voltage (V), discharge current (Ip), duty cycle (τ) and pulse on time (Ton) along with the use of AlSiMg RP electrode.

A control technology evaluation of state-of-the-art, perchloroethylene dry-cleaning machines.

PubMed

Earnest, G Scott

2002-05-01

NIOSH researchers evaluated the ability of fifth-generation dry-cleaning machines to control occupational exposure to perchloroethylene (PERC). Use of these machines is mandated in some countries; however, less than 1 percent of all U.S. shops have them. A study was conducted at a U.S. dry-cleaning shop where two fifth-generation machines were used. Both machines had a refrigerated condenser as a primary control and a carbon adsorber as a secondary control to recover PERC vapors during the dry cycle. These machines were designed to lower the PERC concentration in the cylinder at the end of the dry cycle to below 290 ppm. A single-beam infrared photometer continuously monitors the PERC concentration in the machine cylinder, and a door interlock prevents opening until the concentration is below 290 ppm. Personal breathing zone air samples were measured for the machine operator and presser. The operator had time-weighted average (TWA) PERC exposures that were less than 2 ppm. Highest exposures occurred during loading and unloading the machine and when performing routine machine maintenance. All presser samples were below the limit of detection. Real-time video exposure monitoring showed that the operator had peak exposures near 160 ppm during loading and unloading the machine (below the OSHA maximum of 300 ppm). This exposure (160 ppm) is an order of magnitude lower than exposures with more traditional machines that are widely used in the United States. The evaluated machines were very effective at reducing TWA PERC exposures as well as peak exposures that occur during machine loading and unloading. State-of-the-art dry-cleaning machines equipped with refrigerated condensers, carbon adsorbers, drum monitors, and door interlocks can provide substantially better protection than more traditional machines that are widely used in the United States.

Cell-cycle research with synchronous cultures: an evaluation

NASA Technical Reports Server (NTRS)

Helmstetter, C. E.; Thornton, M.; Grover, N. B.

2001-01-01

The baby-machine system, which produces new-born Escherichia coli cells from cultures immobilized on a membrane, was developed many years ago in an attempt to attain optimal synchrony with minimal disturbance of steady-state growth. In the present article, we put forward a model to describe the behaviour of cells produced by this method, and provide quantitative evaluation of the parameters involved, at each of four different growth rates. Considering the high level of selection achievable with this technique and the natural dispersion in interdivision times, we believe that the output of the baby machine is probably close to optimal in terms of both quality and persistence of synchrony. We show that considerable information on events in the cell cycle can be obtained from populations with age distributions very much broader than those achieved with the baby machine and differing only modestly from steady state. The data presented here, together with the long and fruitful history of findings employing the baby-machine technique, suggest that minimisation of stress on cells is the single most important factor for successful cell-cycle analysis.

Heat transfer head for a Stirling cycle machine

NASA Technical Reports Server (NTRS)

Emigh, Stuart G. (Inventor); Noble, Jack E. (Inventor); Lehmann, Gregory A. (Inventor)

1991-01-01

A common heat acceptor is provided between opposed displacers in a Stirling cycle machine. It includes two sets of open channels in separate fluid communications with the expansion spaces of the receptive cyclinders. The channels confine movement of working fluid in separate paths that extend between the expansion space of one cylinder and the compression space of the other. The method for operating the machine involves alternatively directing working fluid from the expansion space of each cylinder in a fluid path leading to the compression space of the other cylinder and from the compression space of each cylinder in a fluid path leading to the expansion space of the other cylinder.

Twin target self-amplification-based DNA machine for highly sensitive detection of cancer-related gene.

PubMed

Xu, Huo; Jiang, Yifan; Liu, Dengyou; Liu, Kai; Zhang, Yafeng; Yu, Suhong; Shen, Zhifa; Wu, Zai-Sheng

2018-06-29

The sensitive detection of cancer-related genes is of great significance for early diagnosis and treatment of human cancers, and previous isothermal amplification sensing systems were often based on the reuse of target DNA, the amplification of enzymatic products and the accumulation of reporting probes. However, no reporting probes are able to be transformed into target species and in turn initiate the signal of other probes. Herein we reported a simple, isothermal and highly sensitive homogeneous assay system for tumor suppressor p53 gene detection based on a new autonomous DNA machine, where the signaling probe, molecular beacon (MB), was able to execute the function similar to target DNA besides providing the common signal. In the presence of target p53 gene, the operation of DNA machine can be initiated, and cyclical nucleic acid strand-displacement polymerization (CNDP) and nicking/polymerization cyclical amplification (NPCA) occur, during which the MB was opened by target species and cleaved by restriction endonuclease. In turn, the cleaved fragments could activate the next signaling process as target DNA did. According to the functional similarity, the cleaved fragment was called twin target, and the corresponding fashion to amplify the signal was named twin target self-amplification. Utilizing this newly-proposed DNA machine, the target DNA could be detected down to 0.1 pM with a wide dynamic range (6 orders of magnitude) and single-base mismatched targets were discriminated, indicating a very high assay sensitivity and good specificity. In addition, the DNA machine was not only used to screen the p53 gene in complex biological matrix but also was capable of practically detecting genomic DNA p53 extracted from A549 cell line. This indicates that the proposed DNA machine holds the potential application in biomedical research and early clinical diagnosis. Copyright © 2018 Elsevier B.V. All rights reserved.

Pulsed, Hydraulic Coal-Mining Machine

NASA Technical Reports Server (NTRS)

Collins, Earl R., Jr.

1986-01-01

In proposed coal-cutting machine, piston forces water through nozzle, expelling pulsed jet that cuts into coal face. Spring-loaded piston reciprocates at end of travel to refill water chamber. Machine a onecylinder, two-cycle, internal-combustion engine, fueled by gasoline, diesel fuel, or hydrogen. Fuel converted more directly into mechanical energy of water jet.

Ribosomal Translocation: One Step Closer to the Molecular Mechanism

PubMed Central

Shoji, Shinichiro; Walker, Sarah E.; Fredrick, Kurt

2010-01-01

Protein synthesis occurs in ribosomes, the targets of numerous antibiotics. How these large and complex machines read and move along mRNA have proven to be challenging questions. In this Review, we focus on translocation, the last step of the elongation cycle in which movement of tRNA and mRNA is catalyzed by elongation factor G. Translocation entails large-scale movements of the tRNAs and conformational changes in the ribosome that require numerous tertiary contacts to be disrupted and reformed. We highlight recent progress toward elucidating the molecular basis of translocation and how various antibiotics influence tRNA–mRNA movement. PMID:19173642

Replicating human expertise of mechanical ventilation waveform analysis in detecting patient-ventilator cycling asynchrony using machine learning.

PubMed

Gholami, Behnood; Phan, Timothy S; Haddad, Wassim M; Cason, Andrew; Mullis, Jerry; Price, Levi; Bailey, James M

2018-06-01

- Acute respiratory failure is one of the most common problems encountered in intensive care units (ICU) and mechanical ventilation is the mainstay of supportive therapy for such patients. A mismatch between ventilator delivery and patient demand is referred to as patient-ventilator asynchrony (PVA). An important hurdle in addressing PVA is the lack of a reliable framework for continuously and automatically monitoring the patient and detecting various types of PVA. - The problem of replicating human expertise of waveform analysis for detecting cycling asynchrony (i.e., delayed termination, premature termination, or none) was investigated in a pilot study involving 11 patients in the ICU under invasive mechanical ventilation. A machine learning framework is used to detect cycling asynchrony based on waveform analysis. - A panel of five experts with experience in PVA evaluated a total of 1377 breath cycles from 11 mechanically ventilated critical care patients. The majority vote was used to label each breath cycle according to cycling asynchrony type. The proposed framework accurately detected the presence or absence of cycling asynchrony with sensitivity (specificity) of 89% (99%), 94% (98%), and 97% (93%) for delayed termination, premature termination, and no cycling asynchrony, respectively. The system showed strong agreement with human experts as reflected by the kappa coefficients of 0.90, 0.91, and 0.90 for delayed termination, premature termination, and no cycling asynchrony, respectively. - The pilot study establishes the feasibility of using a machine learning framework to provide waveform analysis equivalent to an expert human. Copyright © 2018 Elsevier Ltd. All rights reserved.

Design Study for a Free-piston Vuilleumier Cycle Heat Pump

NASA Astrophysics Data System (ADS)

Matsue, Junji; Hoshino, Norimasa; Ikumi, Yonezou; Shirai, Hiroyuki

Conceptual design for a free-piston Vuilleumier cycle heat pump machine was proposed. The machine was designed based upon the numerical results of a dynamic analysis method. The method included the effect of self excitation vibration with dissipation caused by the flow friction of an oscillating working gas flow and solid friction of seals. It was found that the design values of reciprocating masses and spring constants proposed in published papers related to this study were suitable for practical use. The fundamental effects of heat exchanger elements on dynamic behaviors of the machine were clarified. It has been pointed out that some improvements were required for thermodynamic analysis of heat exchangers and working spaces.

A comparison of the fracture resistance of three machinable ceramics after thermal and mechanical fatigue.

PubMed

Yang, Rui; Arola, Dwayne; Han, Zhihui; Zhang, Xiuyin

2014-10-01

Mechanical and thermal fatigue may affect ceramic restorations in the oral environment. The purpose of this study was to determine the influence of thermal and mechanical cycling on the fracture load and fracture patterns of 3 machinable ceramics. Seventy-two human third molar teeth were prepared for bonding ceramic specimens of Sirona CEREC Blocs, IPS e.maxCAD, or inCoris ZI meso blocks. The 24 specimens of each ceramic were divided into 4 groups (n=6), which underwent no preloading (control), thermocycling (5°C-55°C, 2000 cycles), mechanical cycling (10(5) cycles, 100 N), and thermocycling (5°C-55°C, 2000 cycles) plus mechanical cycling (10(5) cycles, 100 N). The specimens were subsequently loaded to failure, and both stereomicroscopy and scanning electron microscopy were used to investigate the fracture patterns. The data were analyzed with 2-way ANOVA and the Fisher exact probability test (α=.05). Mechanical and thermal cycling had a significant influence on the critical load to failure of the 3 ceramics. No significant difference was found between mechanical cycling for 10(5) times and thermocycling for 2000 times within the same ceramic. The specimens of inCoris ZI experienced significantly higher fracture loads for all the groups. The fracture patterns of the 3 machinable ceramics showed that failure mainly occurred at the cement-dentin interface. The effects of combined thermal and mechanical cycling on the fracture load of ceramics were more significant than any individual mode of cyclic fatigue. Overall, the inCoris ZI resisted thermal and mechanical fatigue better than the Sirona CEREC and IPS e.maxCAD. Copyright © 2014 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

Express Control of the Mechanical Properties of High-Strength and Hard-to-Machine Materials at All Stages of the Technological Cycle of Producing Mechanical Engineering Products

NASA Astrophysics Data System (ADS)

Matyunin, V. M.; Marchenkov, A. Yu.; Demidov, A. N.; Karimbekov, M. A.

2017-12-01

It is shown that depth-sensing indentation can be used to perform express control of the mechanical properties of high-strength and hard-to-machine materials. This control can be performed at various stages of a technological cycle of processing materials and parts without preparing and testing tensile specimens, which will significantly reduce the consumption of materials, time, and labor.

C1 Domain-Targeted Isophthalate Derivatives Induce Cell Elongation and Cell Cycle Arrest in HeLa Cells

PubMed Central

Talman, Virpi; Tuominen, Raimo K.; Gennäs, Gustav Boije af; Yli-Kauhaluoma, Jari; Ekokoski, Elina

2011-01-01

Diacylglycerol (DAG)-mediated signaling pathways, such as those mediated by protein kinase C (PKC), are central in regulating cell proliferation and apoptosis. DAG-responsive C1 domains are therefore considered attractive drug targets. Our group has designed a novel class of compounds targeted to the DAG binding site within the C1 domain of PKC. We have previously shown that these 5-(hydroxymethyl)isophthalates modulate PKC activation in living cells. In this study we investigated their effects on HeLa human cervical cancer cell viability and proliferation by using standard cytotoxicity tests and an automated imaging platform with machine vision technology. Cellular effects and their mechanisms were further characterized with the most potent compound, HMI-1a3. Isophthalate derivatives with high affinity to the PKC C1 domain exhibited antiproliferative and non-necrotic cytotoxic effects on HeLa cells. The anti-proliferative effect was irreversible and accompanied by cell elongation. HMI-1a3 induced down-regulation of retinoblastoma protein and cyclins A, B1, D1, and E. Effects of isophthalates on cell morphology, cell proliferation and expression of cell cycle-related proteins were different from those induced by phorbol 12-myristate-13-acetate (PMA) or bryostatin 1, but correlated closely to binding affinities. Therefore, the results strongly indicate that the effect is C1 domain-mediated. PMID:21629792

Alumina additions may improve the damage tolerance of soft machined zirconia-based ceramics.

PubMed

Oilo, Marit; Tvinnereim, Helene M; Gjerdet, Nils Roar

2011-01-01

The aim of this study was to evaluate the damage tolerance of different zirconia-based materials. Bars of one hard machined and one soft machined dental zirconia and an experimental 95% zirconia 5% alumina ceramic were subjected to 100,000 stress cycles (n = 10), indented to provoke cracks on the tensile stress side (n = 10), and left untreated as controls (n = 10). The experimental material demonstrated a higher relative damage tolerance, with a 40% reduction compared to 68% for the hard machined zirconia and 84% for the soft machined zirconia.

EDM machinability of SiCw/Al composites

NASA Technical Reports Server (NTRS)

Ramulu, M.; Taya, M.

1989-01-01

Machinability of high temperature composites was investigated. Target materials, 15 and 25 vol pct SiC whisker-2124 aluminum composites, were machined by electrodischarge sinker machining and diamond saw. The machined surfaces of these metal matrix composites were examined by SEM and profilometry to determine the surface finish. Microhardness measurements were also performed on the as-machined composites.

Ada Compiler Validation Summary Report: Certificate Number 880318W1. 09042, International Business Machines Corporation, IBM Development System for the Ada Language, Version 2.1.0, IBM 4381 under MVS/XA, Host and Target

DTIC Science & Technology

1988-03-28

International Business Machines Corporation IBM Development System for the Ada Language, Version 2.1.0 IBM 4381 under MVS/XA, host and target Completion...Joint Program Office, AJPO 20. ABSTRACT (Continue on reverse side if necessary and identify by block number) International Business Machines Corporation...in the compiler listed in this declaration. I declare that International Business Machines Corporation is the owner of record of the object code of

Organic rankine cycle waste heat applications

DOEpatents

Brasz, Joost J.; Biederman, Bruce P.

2007-02-13

A machine designed as a centrifugal compressor is applied as an organic rankine cycle turbine by operating the machine in reverse. In order to accommodate the higher pressures when operating as a turbine, a suitable refrigerant is chosen such that the pressures and temperatures are maintained within established limits. Such an adaptation of existing, relatively inexpensive equipment to an application that may be otherwise uneconomical, allows for the convenient and economical use of energy that would be otherwise lost by waste heat to the atmosphere.

Image Understanding Workshop. Proceedings of a Workshop Held in Los Angeles, California on 23-25 February 1987. Volume 2

DTIC Science & Technology

1987-02-25

Modellierung von Kanten bei unregel. Navigation within a building, to be published in IEEE mifliger Rasterung in Bildverarbeitun uand Muster...converted them into equivalent machine cycles in Table 3-1. We took into account of 100 nanosecond 0 - 0, machine cycle time of the MPP. In MPP, NON- VON ...We show the result for the conjugate gradient method in of NON- VON . We assumed that the instructions which carry Table 4-4. The computation of four

Experimental investigation of the tip based micro/nano machining

NASA Astrophysics Data System (ADS)

Guo, Z.; Tian, Y.; Liu, X.; Wang, F.; Zhou, C.; Zhang, D.

2017-12-01

Based on the self-developed three dimensional micro/nano machining system, the effects of machining parameters and sample material on micro/nano machining are investigated. The micro/nano machining system is mainly composed of the probe system and micro/nano positioning stage. The former is applied to control the normal load and the latter is utilized to realize high precision motion in the xy plane. A sample examination method is firstly introduced to estimate whether the sample is placed horizontally. The machining parameters include scratching direction, speed, cycles, normal load and feed. According to the experimental results, the scratching depth is significantly affected by the normal load in all four defined scratching directions but is rarely influenced by the scratching speed. The increase of scratching cycle number can increase the scratching depth as well as smooth the groove wall. In addition, the scratching tests of silicon and copper attest that the harder material is easier to be removed. In the scratching with different feed amount, the machining results indicate that the machined depth increases as the feed reduces. Further, a cubic polynomial is used to fit the experimental results to predict the scratching depth. With the selected machining parameters of scratching direction d3/d4, scratching speed 5 μm/s and feed 0.06 μm, some more micro structures including stair, sinusoidal groove, Chinese character '田', 'TJU' and Chinese panda have been fabricated on the silicon substrate.

Programmable phase plate for tool modification in laser machining applications

DOEpatents

Thompson Jr., Charles A.; Kartz, Michael W.; Brase, James M.; Pennington, Deanna; Perry, Michael D.

2004-04-06

A system for laser machining includes a laser source for propagating a laser beam toward a target location, and a spatial light modulator having individual controllable elements capable of modifying a phase profile of the laser beam to produce a corresponding irradiance pattern on the target location. The system also includes a controller operably connected to the spatial light modulator for controlling the individual controllable elements. By controlling the individual controllable elements, the phase profile of the laser beam may be modified into a desired phase profile so as to produce a corresponding desired irradiance pattern on the target location capable of performing a machining operation on the target location.

Laser Machining of Melt Infiltrated Ceramic Matrix Composite

NASA Technical Reports Server (NTRS)

Jarmon, D. C.; Ojard, G.; Brewer, D.

2012-01-01

As interest grows in considering the use of ceramic matrix composites for critical components, the effects of different machining techniques, and the resulting machined surfaces, on strength need to be understood. This work presents the characterization of a Melt Infiltrated SiC/SiC composite material system machined by different methods. While a range of machining approaches were initially considered, only diamond grinding and laser machining were investigated on a series of tensile coupons. The coupons were tested for residual tensile strength, after a stressed steam exposure cycle. The data clearly differentiated the laser machined coupons as having better capability for the samples tested. These results, along with micro-structural characterization, will be presented.

Machine learning enhanced optical distance sensor

NASA Astrophysics Data System (ADS)

Amin, M. Junaid; Riza, N. A.

2018-01-01

Presented for the first time is a machine learning enhanced optical distance sensor. The distance sensor is based on our previously demonstrated distance measurement technique that uses an Electronically Controlled Variable Focus Lens (ECVFL) with a laser source to illuminate a target plane with a controlled optical beam spot. This spot with varying spot sizes is viewed by an off-axis camera and the spot size data is processed to compute the distance. In particular, proposed and demonstrated in this paper is the use of a regularized polynomial regression based supervised machine learning algorithm to enhance the accuracy of the operational sensor. The algorithm uses the acquired features and corresponding labels that are the actual target distance values to train a machine learning model. The optimized training model is trained over a 1000 mm (or 1 m) experimental target distance range. Using the machine learning algorithm produces a training set and testing set distance measurement errors of <0.8 mm and <2.2 mm, respectively. The test measurement error is at least a factor of 4 improvement over our prior sensor demonstration without the use of machine learning. Applications for the proposed sensor include industrial scenario distance sensing where target material specific training models can be generated to realize low <1% measurement error distance measurements.

Development of a Physical Employment Testing Battery for Infantry Soldiers: 11B Infantryman and 11C Infantryman - Indirect Fire

DTIC Science & Technology

2015-12-01

25mm barrel install (Task 5) and engage targets with an M2 machine gun (Task 12). During these tasks, the performance of one individual will affect...TOW Missile Launcher on BFV (Task 8) 43 1.9 Images of Move Under Direct Fire (Task 10) 44 1.10 Engage Targets with a .50 Caliber M2 Machine Gun ...Engage Targets with a .50 Caliber M2 Machine Gun While wearing a fighting load (approximately 83 lb) and working as a member of a two-person team

Measurement-induced operation of two-ion quantum heat machines

NASA Astrophysics Data System (ADS)

Chand, Suman; Biswas, Asoka

2017-03-01

We show how one can implement a quantum heat machine by using two interacting trapped ions, in presence of a thermal bath. The electronic states of the ions act like a working substance, while the vibrational mode is modelled as the cold bath. The heat exchange with the cold bath is mimicked by the projective measurement of the electronic states. We show how such measurement in a suitable basis can lead to either a quantum heat engine or a refrigerator, which undergoes a quantum Otto cycle. The local magnetic field is adiabatically changed during the heat cycle. The performance of the heat machine depends upon the interaction strength between the ions, the magnetic fields, and the measurement cost. In our model, the coupling to the hot and the cold baths is never switched off in an alternative fashion during the heat cycle, unlike other existing proposals of quantum heat engines. This makes our proposal experimentally realizable using current tapped-ion technology.

Measurement-induced operation of two-ion quantum heat machines.

PubMed

Chand, Suman; Biswas, Asoka

2017-03-01

We show how one can implement a quantum heat machine by using two interacting trapped ions, in presence of a thermal bath. The electronic states of the ions act like a working substance, while the vibrational mode is modelled as the cold bath. The heat exchange with the cold bath is mimicked by the projective measurement of the electronic states. We show how such measurement in a suitable basis can lead to either a quantum heat engine or a refrigerator, which undergoes a quantum Otto cycle. The local magnetic field is adiabatically changed during the heat cycle. The performance of the heat machine depends upon the interaction strength between the ions, the magnetic fields, and the measurement cost. In our model, the coupling to the hot and the cold baths is never switched off in an alternative fashion during the heat cycle, unlike other existing proposals of quantum heat engines. This makes our proposal experimentally realizable using current tapped-ion technology.

A Structural Perspective on the Dynamics of Kinesin Motors

PubMed Central

Hyeon, Changbong; Onuchic, José N.

2011-01-01

Despite significant fluctuation under thermal noise, biological machines in cells perform their tasks with exquisite precision. Using molecular simulation of a coarse-grained model and theoretical arguments, we envisaged how kinesin, a prototype of biological machines, generates force and regulates its dynamics to sustain persistent motor action. A structure-based model, which can be versatile in adapting its structure to external stresses while maintaining its native fold, was employed to account for several features of kinesin dynamics along the biochemical cycle. This analysis complements our current understandings of kinesin dynamics and connections to experiments. We propose a thermodynamic cycle for kinesin that emphasizes the mechanical and regulatory role of the neck linker and clarify issues related to the motor directionality, and the difference between the external stalling force and the internal tension responsible for the head-head coordination. The comparison between the thermodynamic cycle of kinesin and macroscopic heat engines highlights the importance of structural change as the source of work production in biomolecular machines. PMID:22261064

A self-contained quantum harmonic engine

NASA Astrophysics Data System (ADS)

Reid, B.; Pigeon, S.; Antezza, M.; De Chiara, G.

2017-12-01

We propose a system made of three quantum harmonic oscillators as a compact quantum engine for producing mechanical work. The three oscillators play respectively the role of the hot bath, the working medium and the cold bath. The working medium performs an Otto cycle during which its frequency is changed and it is sequentially coupled to each of the two other oscillators. As the two environments are finite, the lifetime of the machine is finite and after a number of cycles it stops working and needs to be reset. Remarkably, we show that this machine can extract more than 90% of the available energy during 70 cycles. Differently from usually investigated infinite-reservoir configurations, this machine allows the protection of induced quantum correlations and we analyse the entanglement and quantum discord generated during the strokes. Interestingly, we show that high work generation is always accompanied by large quantum correlations. Our predictions can be useful for energy management at the nanoscale, and can be relevant for experiments with trapped ions and experiments with light in integrated optical circuits.

Smarter Instruments, Smarter Archives: Machine Learning for Tactical Science

NASA Astrophysics Data System (ADS)

Thompson, D. R.; Kiran, R.; Allwood, A.; Altinok, A.; Estlin, T.; Flannery, D.

2014-12-01

There has been a growing interest by Earth and Planetary Sciences in machine learning, visualization and cyberinfrastructure to interpret ever-increasing volumes of instrument data. Such tools are commonly used to analyze archival datasets, but they can also play a valuable real-time role during missions. Here we discuss ways that machine learning can benefit tactical science decisions during Earth and Planetary Exploration. Machine learning's potential begins at the instrument itself. Smart instruments endowed with pattern recognition can immediately recognize science features of interest. This allows robotic explorers to optimize their limited communications bandwidth, triaging science products and prioritizing the most relevant data. Smart instruments can also target their data collection on the fly, using principles of experimental design to reduce redundancy and generally improve sampling efficiency for time-limited operations. Moreover, smart instruments can respond immediately to transient or unexpected phenomena. Examples include detections of cometary plumes, terrestrial floods, or volcanism. We show recent examples of smart instruments from 2014 tests including: aircraft and spacecraft remote sensing instruments that recognize cloud contamination, field tests of a "smart camera" for robotic surface geology, and adaptive data collection by X-Ray fluorescence spectrometers. Machine learning can also assist human operators when tactical decision making is required. Terrestrial scenarios include airborne remote sensing, where the decision to re-fly a transect must be made immediately. Planetary scenarios include deep space encounters or planetary surface exploration, where the number of command cycles is limited and operators make rapid daily decisions about where next to collect measurements. Visualization and modeling can reveal trends, clusters, and outliers in new data. This can help operators recognize instrument artifacts or spot anomalies in real time. We show recent examples from science data pipelines deployed onboard aircraft as well as tactical visualizations for non-image instrument data.

Ada Compiler Validation Summary Report: Certificate Number: 880318W1. 09041, International Business Machines Corporation, IBM Development System for the Ada Language, Version 2.1.0, IBM 4381 under VM/HPO, Host and Target

DTIC Science & Technology

1988-03-28

International Business Machines Corporation IBM Development System for the Ada Language, Version 2.1.0 IBM 4381 under VM/HPO, host and target DTIC...necessary and identify by block number) International Business Machines Corporation, IBM Development System for the Ada Language, Version 2.1.0, IBM...in the compiler listed in this declaration. I declare that International Business Machines Corporation is the owner of record of the object code of the

Ada Compiler Validation Summary Report: Certificate Number: 880318W1. 09043 International Business Machines Corporation IBM Development System for the Ada Language, Version 2.1.0 IBM 4381 under VM/HPO, Host IBM 4381 under MVS/XA, Target

DTIC Science & Technology

1988-03-28

International Business Machines Corporation IBM Development System for the Ada Language, Version 2.1.0 IBM 4381 under VM/HPO, host IBM 4381 under MVS/XA, target...Program Office, AJPO 20. ABSTRACT (Continue on reverse side if necessary and identify by block number) International Business Machines Corporation, IBM...Standard ANSI/MIL-STD-1815A in the compiler listed in this declaration. I declare that International Business Machines Corporation is the owner of record

Modern methodology of designing target reliability into rotating mechanical components

NASA Technical Reports Server (NTRS)

Kececioglu, D. B.; Chester, L. B.

1973-01-01

Experimentally determined distributional cycles-to-failure versus maximum alternating nominal strength (S-N) diagrams, and distributional mean nominal strength versus maximum alternating nominal strength (Goodman) diagrams are presented. These distributional S-N and Goodman diagrams are for AISI 4340 steel, R sub c 35/40 hardness, round, cylindrical specimens 0.735 in. in diameter and 6 in. long with a circumferential groove 0.145 in. radius for a theoretical stress concentration = 1.42 and 0.034 in. radius for a stress concentration = 2.34. The specimens are subjected to reversed bending and steady torque in specially built, three complex-fatigue research machines. Based on these results, the effects on the distributional S-N and Goodman diagrams and on service life of superimposing steady torque on reversed bending are established, as well as the effect of various stress concentrations. In addition a computer program for determining the three-parameter Weibull distribution representing the cycles-to-failure data, and two methods for calculating the reliability of components subjected to cumulative fatigue loads are given.

Applied physiology of cycling.

PubMed

Faria, I E

1984-01-01

Historically, the bicycle has evolved through the stages of a machine for efficient human transportation, a toy for children, a finely-tuned racing machine, and a tool for physical fitness development, maintenance and testing. Recently, major strides have been made in the aerodynamic design of the bicycle. These innovations have resulted in new land speed records for human powered machines. Performance in cycling is affected by a variety of factors, including aerobic and anaerobic capacity, muscular strength and endurance, and body composition. Bicycle races range from a 200m sprint to approximately 5000km. This vast range of competitive racing requires special attention to the principle of specificity of training. The physiological demands of cycling have been examined through the use of bicycle ergometers, rollers, cycling trainers, treadmill cycling, high speed photography, computer graphics, strain gauges, electromyography, wind tunnels, muscle biopsy, and body composition analysis. These techniques have been useful in providing definitive data for the development of a work/performance profile of the cyclist. Research evidence strongly suggests that when measuring the cyclist's aerobic or anaerobic capacity, a cycling protocol employing a high pedalling rpm should be used. The research bicycle should be modified to resemble a racing bicycle and the cyclist should wear cycling shoes. Prolonged cycling requires special nutritional considerations. Ingestion of carbohydrates, in solid form and carefully timed, influences performance. Caffeine appears to enhance lipid metabolism. Injuries, particularly knee problems which are prevalent among cyclists, may be avoided through the use of proper gearing and orthotics. Air pollution has been shown to impair physical performance. When pollution levels are high, training should be altered or curtailed. Effective training programmes simulate competitive conditions. Short and long interval training, blended with long distance tempo cycling, will exploit both the anaerobic and aerobic systems. Strength training, to be effective, must be performed with the specific muscle groups used in cycling, and at specific angles of involvement.

New concept for in-line OLED manufacturing

NASA Astrophysics Data System (ADS)

Hoffmann, U.; Landgraf, H.; Campo, M.; Keller, S.; Koening, M.

2011-03-01

A new concept of a vertical In-Line deposition machine for large area white OLED production has been developed. The concept targets manufacturing on large substrates (>= Gen 4, 750 x 920 mm2) using linear deposition source achieving a total material utilization of >= 50 % and tact time down to 80 seconds. The continuously improved linear evaporation sources for the organic material achieve thickness uniformity on Gen 4 substrate of better than +/- 3 % and stable deposition rates down to less than 0.1 nm m/min and up to more than 100 nm m/min. For Lithium-Fluoride but also for other high evaporation temperature materials like Magnesium or Silver a linear source with uniformity better than +/- 3 % has been developed. For Aluminum we integrated a vertical oriented point source using wire feed to achieve high (> 150 nm m/min) and stable deposition rates. The machine concept includes a new vertical vacuum handling and alignment system for Gen 4 shadow masks. A complete alignment cycle for the mask can be done in less than one minute achieving alignment accuracy in the range of several 10 μm.

Application of ultrafiltration in the pulp and paper industry: metals removal and whitewater reuse.

PubMed

Oliveira, C R; Silva, C M; Milanez, A F

2007-01-01

In the pulp and paper industry, the water use minimization is a constant target. One way to reduce water use is to recycle the effluent in a closed-cycle concept. In paper mills, the main source of liquid effluent is the so-called whitewater, which is the excess water, originated from pulp stock dewatering and other fibre contaminated water. This research studied the reuse of paper mill whitewater after membrane ultrafiltration (UF) in the paper machine and in the pulp bleach plant of an integrated mill. Contaminant removal and flux behaviour of the UF system were evaluated. The treatment by ultrafiltration was technically feasible and the treated whitewater had good potential to be reused in some processes in the paper machine. The reuse of ultrafiltered whitewater in the bleaching plant was not recommended because of the high level of soluble calcium present in this stream. Therefore, a combined treatment of the whitewater using the principle of precipitation and ultrafiltration was proposed showing good results and enabling the use of the treated whitewater in the bleach plant.

Motorcycle Diaries

ERIC Educational Resources Information Center

Gibbs, Hope J.

2005-01-01

This article relates the experiences of Jeff Fischer, an instructor in the Computer Integrated Machining department at South Central College (SCC) in North Mankato, Minnesota. Facing dwindling student enrollment and possible departmental budget costs, Fischer was able to turn his passion for custom-built cycles and the intricate machining that…

Trajectories of the ribosome as a Brownian nanomachine

DOE PAGES

Dashti, Ali; Schwander, Peter; Langlois, Robert; ...

2014-11-24

In a Brownian machine, there is a tiny device buffeted by the random motions of molecules in the environment, is capable of exploiting these thermal motions for many of the conformational changes in its work cycle. Such machines are now thought to be ubiquitous, with the ribosome, a molecular machine responsible for protein synthesis, increasingly regarded as prototypical. We present a new analytical approach capable of determining the free-energy landscape and the continuous trajectories of molecular machines from a large number of snapshots obtained by cryogenic electron microscopy. We demonstrate this approach in the context of experimental cryogenic electron microscopemore » images of a large ensemble of nontranslating ribosomes purified from yeast cells. The free-energy landscape is seen to contain a closed path of low energy, along which the ribosome exhibits conformational changes known to be associated with the elongation cycle. This approach allows model-free quantitative analysis of the degrees of freedom and the energy landscape underlying continuous conformational changes in nanomachines, including those important for biological function.« less

Coupling of kinesin ATP turnover to translocation and microtubule regulation: one engine, many machines.

PubMed

Friel, Claire T; Howard, Jonathon

2012-12-01

The cycle of ATP turnover is integral to the action of motor proteins. Here we discuss how variation in this cycle leads to variation of function observed amongst members of the kinesin superfamily of microtubule associated motor proteins. Variation in the ATP turnover cycle among superfamily members can tune the characteristic kinesin motor to one of the range of microtubule-based functions performed by kinesins. The speed at which ATP is hydrolysed affects the speed of translocation. The ratio of rate constants of ATP turnover in relation to association and dissociation from the microtubule influence the processivity of translocation. Variation in the rate-limiting step of the cycle can reverse the way in which the motor domain interacts with the microtubule producing non-motile kinesins. Because the ATP turnover cycle is not fully understood for the majority of kinesins, much work remains to show how the kinesin engine functions in such a wide variety of molecular machines.

Precision Robotic Assembly Machine

ScienceCinema

None

2017-12-09

The world's largest laser system is the National Ignition Facility (NIF), located at Lawrence Livermore National Laboratory. NIF's 192 laser beams are amplified to extremely high energy, and then focused onto a tiny target about the size of a BB, containing frozen hydrogen gas. The target must be perfectly machined to incredibly demanding specifications. The Laboratory's scientists and engineers have developed a device called the "Precision Robotic Assembly Machine" for this purpose. Its unique design won a prestigious R&D-100 award from R&D Magazine.

Automated Discovery of Machine-Specific Code Improvements

DTIC Science & Technology

1984-12-01

operation of the source language. Additional analysis may reveal special features of the target architecture that may be exploited to generate efficient...Additional analysis may reveal special features of the target architecture that may be exploited to generate efficient code. Such analysis is optional...incorporate knowledge of the source language, but do not refer to features of the target machine. These early phases are sometimes referred to as the

Carnot's cycle for small systems: Irreversibility and cost of operations

NASA Astrophysics Data System (ADS)

Sekimoto, Ken; Takagi, Fumiko; Hondou, Tsuyoshi

2000-12-01

In the thermodynamic limit, the existence of a maximal efficiency of energy conversion attainable by a Carnot cycle consisting of quasistatic isothermal and adiabatic processes precludes the existence of a perpetual machine of the second kind, whose cycles yield positive work in an isothermal environment. We employ the recently developed framework of the energetics of stochastic processes (called ``stochastic energetics'') to reanalyze the Carnot cycle in detail, taking account of fluctuations, without taking the thermodynamic limit. We find that in this nonmacroscopic situation both processes of connection to and disconnection from heat baths and adiabatic processes that cause distortion of the energy distribution are sources of inevitable irreversibility within the cycle. Also, the so-called null-recurrence property of the cumulative efficiency of energy conversion over many cycles and the irreversible property of isolated, purely mechanical processes under external ``macroscopic'' operations are discussed in relation to the impossibility of a perpetual machine, or Maxwell's demon. This analysis may serve as the basis for the design and analysis of mesoscopic energy converters in the near future.

In vitro wear of new indirect resin composites.

PubMed

Jain, V; Platt, J A; Moore, B K; Borges, G A

2009-01-01

This in vitro study evaluated the toothbrush abrasion wear, three-body Alabama wear and two-body pin-on-disc wear of four commercial indirect resin composites. Enamel shades of Radica (R), Sculpture Plus (S), Belleglass-NG (B) and Gradia Indirect (G) were used. For measuring wear due to toothbrush abrasion, six specimens of each group were fabricated, then brushed in a toothbrush abrasion machine for 20,000 cycles. Material loss was determined by weighing and conversion to volume loss. Three-body wear was measured on six samples for each group using an Alabama-type wear testing machine for 400,000 cycles. Wear depth was measured with a contact profilometer. For two-body wear, five disc specimens were prepared and tested in a two-body wear-testing machine against hydroxypatite sliders for 25,000 cycles. Data were analyzed with one-way analysis of variance (ANOVA) and Tukey test (alpha=0.05). Wear was the highest in Sculpture Plus by all three methods tested and the lowest wear was observed in Belleglass-NG. No statistical difference in wear was noted from Radica.

Augmentation of machine structure to improve its diagnosability

NASA Technical Reports Server (NTRS)

Hsieh, L.

1973-01-01

Two methods of augmenting the structure of a sequential machine so that it is diagnosable are presented. The checkable (checking sequences) and repeated symbol distinguishing sequences (RDS) are discussed. It was found that as few as twice the number of outputs of the given machine is sufficient for constructing a state-output augmentation with RDS. Techniques for minimizing the number of states in resolving convergences and in resolving equivalent and nonreduced cycles are developed.

Evolutionary grinding model for nanometric control of surface roughness for aspheric optical surfaces.

PubMed

Han, Jeong-Yeol; Kim, Sug-Whan; Han, Inwoo; Kim, Geon-Hee

2008-03-17

A new evolutionary grinding process model has been developed for nanometric control of material removal from an aspheric surface of Zerodur substrate. The model incorporates novel control features such as i) a growing database; ii) an evolving, multi-variable regression equation; and iii) an adaptive correction factor for target surface roughness (Ra) for the next machine run. This process model demonstrated a unique evolutionary controllability of machining performance resulting in the final grinding accuracy (i.e. averaged difference between target and measured surface roughness) of -0.2+/-2.3(sigma) nm Ra over seven trial machine runs for the target surface roughness ranging from 115 nm to 64 nm Ra.

Spin Cycle

ERIC Educational Resources Information Center

Casey, Dick

2005-01-01

Laundry equipment is an investment, and the investment should be protected. To keep laundry equipment working at an optimum level, schools must maintain their machines. This article offers preventive-maintenance tips for washing machines and dryers. To prevent faucets from binding up, close and reopen the water faucets. This also is a great way to…

Combined high vacuum/high frequency fatigue tester

NASA Technical Reports Server (NTRS)

Honeycutt, C. R.; Martin, T. F.

1971-01-01

Apparatus permits application of significantly greater number of cycles or equivalent number of cycles in shorter time than conventional fatigue test machines. Environment eliminates problems associated with high temperature oxidation and with sensitivity of refractory alloy behavior to atmospheric contamination.

Impact of Spot Size and Spacing on the Quality of Robustly Optimized Intensity Modulated Proton Therapy Plans for Lung Cancer.

PubMed

Liu, Chenbin; Schild, Steven E; Chang, Joe Y; Liao, Zhongxing; Korte, Shawn; Shen, Jiajian; Ding, Xiaoning; Hu, Yanle; Kang, Yixiu; Keole, Sameer R; Sio, Terence T; Wong, William W; Sahoo, Narayan; Bues, Martin; Liu, Wei

2018-06-01

To investigate how spot size and spacing affect plan quality, robustness, and interplay effects of robustly optimized intensity modulated proton therapy (IMPT) for lung cancer. Two robustly optimized IMPT plans were created for 10 lung cancer patients: first by a large-spot machine with in-air energy-dependent large spot size at isocenter (σ: 6-15 mm) and spacing (1.3 σ), and second by a small-spot machine with in-air energy-dependent small spot size (σ: 2-6 mm) and spacing (5 mm). Both plans were generated by optimizing radiation dose to internal target volume on averaged 4-dimensional computed tomography scans using an in-house-developed IMPT planning system. The dose-volume histograms band method was used to evaluate plan robustness. Dose evaluation software was developed to model time-dependent spot delivery to incorporate interplay effects with randomized starting phases for each field per fraction. Patient anatomy voxels were mapped phase-to-phase via deformable image registration, and doses were scored using in-house-developed software. Dose-volume histogram indices, including internal target volume dose coverage, homogeneity, and organs at risk (OARs) sparing, were compared using the Wilcoxon signed-rank test. Compared with the large-spot machine, the small-spot machine resulted in significantly lower heart and esophagus mean doses, with comparable target dose coverage, homogeneity, and protection of other OARs. Plan robustness was comparable for targets and most OARs. With interplay effects considered, significantly lower heart and esophagus mean doses with comparable target dose coverage and homogeneity were observed using smaller spots. Robust optimization with a small spot-machine significantly improves heart and esophagus sparing, with comparable plan robustness and interplay effects compared with robust optimization with a large-spot machine. A small-spot machine uses a larger number of spots to cover the same tumors compared with a large-spot machine, which gives the planning system more freedom to compensate for the higher sensitivity to uncertainties and interplay effects for lung cancer treatments. Copyright © 2018 Elsevier Inc. All rights reserved.

Testing of the Support Vector Machine for Binary-Class Classification

NASA Technical Reports Server (NTRS)

Scholten, Matthew

2011-01-01

The Support Vector Machine is a powerful algorithm, useful in classifying data in to species. The Support Vector Machines implemented in this research were used as classifiers for the final stage in a Multistage Autonomous Target Recognition system. A single kernel SVM known as SVMlight, and a modified version known as a Support Vector Machine with K-Means Clustering were used. These SVM algorithms were tested as classifiers under varying conditions. Image noise levels varied, and the orientation of the targets changed. The classifiers were then optimized to demonstrate their maximum potential as classifiers. Results demonstrate the reliability of SMV as a method for classification. From trial to trial, SVM produces consistent results

Machine learning for predicting the response of breast cancer to neoadjuvant chemotherapy

PubMed Central

Mani, Subramani; Chen, Yukun; Li, Xia; Arlinghaus, Lori; Chakravarthy, A Bapsi; Abramson, Vandana; Bhave, Sandeep R; Levy, Mia A; Xu, Hua; Yankeelov, Thomas E

2013-01-01

Objective To employ machine learning methods to predict the eventual therapeutic response of breast cancer patients after a single cycle of neoadjuvant chemotherapy (NAC). Materials and methods Quantitative dynamic contrast-enhanced MRI and diffusion-weighted MRI data were acquired on 28 patients before and after one cycle of NAC. A total of 118 semiquantitative and quantitative parameters were derived from these data and combined with 11 clinical variables. We used Bayesian logistic regression in combination with feature selection using a machine learning framework for predictive model building. Results The best predictive models using feature selection obtained an area under the curve of 0.86 and an accuracy of 0.86, with a sensitivity of 0.88 and a specificity of 0.82. Discussion With the numerous options for NAC available, development of a method to predict response early in the course of therapy is needed. Unfortunately, by the time most patients are found not to be responding, their disease may no longer be surgically resectable, and this situation could be avoided by the development of techniques to assess response earlier in the treatment regimen. The method outlined here is one possible solution to this important clinical problem. Conclusions Predictive modeling approaches based on machine learning using readily available clinical and quantitative MRI data show promise in distinguishing breast cancer responders from non-responders after the first cycle of NAC. PMID:23616206

Novel target fabrication using 3D printing developed at University of Michigan

DOE PAGES

Klein, Sallee R.; Deininger, Michael; Gillespie, Robb S.; ...

2016-05-24

The University of Michigan has been fabricating targets for high-energy-density experiments for the past decade. We utilize the technique of machined acrylic bodies and mating components acting as constraints to build repeatable targets. Combining 3D printing with traditional machining, we are able to take advantage of the very best part of both aspects of manufacturing. Furthermore, we present several recent campaigns to act as showcase and introduction of our techniques and our experience with 3D printing, effecting how we utilize 3D printing in our target builds.

Novel target fabrication using 3D printing developed at University of Michigan

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klein, Sallee R.; Deininger, Michael; Gillespie, Robb S.

The University of Michigan has been fabricating targets for high-energy-density experiments for the past decade. We utilize the technique of machined acrylic bodies and mating components acting as constraints to build repeatable targets. Combining 3D printing with traditional machining, we are able to take advantage of the very best part of both aspects of manufacturing. Furthermore, we present several recent campaigns to act as showcase and introduction of our techniques and our experience with 3D printing, effecting how we utilize 3D printing in our target builds.

Advanced Airframe Structural Materials: A Primer and Cost Estimating Methodology

DTIC Science & Technology

1991-01-01

laying machines for larger, mildly con- toured parts such as wing and stabilizer skins. For such parts, automated tape laying machines can operate many...heat guns (90-130°F). However, thermoplastics require as much as 650°F for forming. Automated tape laying machines for these materials use warm...cycles to properly seat the plies onto the tool. This time-consuming process can sometimes be eliminated or reduced by the use of automated tape laying procedures

Evaluation of Military Range Berm Effectiveness in Protecting Red-cockaded Woodpecker Foraging and Nesting Habitat

DTIC Science & Technology

2011-04-01

Benning – Malone 5 Malone 5 is an unbermed SA machine gun (firing 7.62 mm or smaller caliber rounds) range with elevated firing and target boxes (~1...plots, not originally allocated. Fort Stewart – Kilo The Kilo range on Fort Stewart is an unbermed SA machine gun (firing 7.62 mm or smaller...is a bermed SA machine gun (firing 7.62 mm or smaller caliber rounds) range with elevated firing boxes and targets (~1-m high; Figures 6 and 7). The

Identification of Cell Cycle-Regulated Genes by Convolutional Neural Network.

PubMed

Liu, Chenglin; Cui, Peng; Huang, Tao

2017-01-01

The cell cycle-regulated genes express periodically with the cell cycle stages, and the identification and study of these genes can provide a deep understanding of the cell cycle process. Large false positives and low overlaps are big problems in cell cycle-regulated gene detection. Here, a computational framework called DLGene was proposed for cell cycle-regulated gene detection. It is based on the convolutional neural network, a deep learning algorithm representing raw form of data pattern without assumption of their distribution. First, the expression data was transformed to categorical state data to denote the changing state of gene expression, and four different expression patterns were revealed for the reported cell cycle-regulated genes. Then, DLGene was applied to discriminate the non-cell cycle gene and the four subtypes of cell cycle genes. Its performances were compared with six traditional machine learning methods. At last, the biological functions of representative cell cycle genes for each subtype are analyzed. Our method showed better and more balanced performance of sensitivity and specificity comparing to other machine learning algorithms. The cell cycle genes had very different expression pattern with non-cell cycle genes and among the cell-cycle genes, there were four subtypes. Our method not only detects the cell cycle genes, but also describes its expression pattern, such as when its highest expression level is reached and how it changes with time. For each type, we analyzed the biological functions of the representative genes and such results provided novel insight to the cell cycle mechanisms. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Key technology research of HILS based on real-time operating system

NASA Astrophysics Data System (ADS)

Wang, Fankai; Lu, Huiming; Liu, Che

2018-03-01

In order to solve the problems that the long development cycle of traditional simulation and digital simulation doesn't have the characteristics of real time, this paper designed a HILS(Hardware In the Loop Simulation) system based on the real-time operating platform xPC. This system solved the communication problems between HMI and Simulink models through the MATLAB engine interface, and realized the functions of system setting, offline simulation, model compiling and downloading, etc. Using xPC application interface and integrating the TeeChart ActiveX chart component to realize the monitoring function of real-time target application; Each functional block in the system is encapsulated in the form of DLL, and the data interaction between modules was realized by MySQL database technology. When the HILS system runs, search the address of the online xPC target by means of the Ping command, to establish the Tcp/IP communication between the two machines. The technical effectiveness of the developed system is verified through the typical power station control system.

Plasma Centrifuge Heat Engine - a Route to Non-thermal p- 11 B Fusion

NASA Astrophysics Data System (ADS)

Barnes, D. C.

2007-06-01

An invention [US Patent and Trademark Office App. Nos. 60/596567 (2005) and 60/766791 (2006)] combines centrifugal and dipole confinement, with recent oscillating plasma theory. The plasma undergoes compression/expansion (C/E), parallel to B by centrifugal force and perpendicular to B by B variation, providing a thermal cycle which recovers most (>95%) of heating as mechanical energy. This gives a "Q-amplifier" for beam-target systems. Centrifugally confined Boron plasma undergoes C/E by slow, cross-B interchange activity. Parallel and perpendicular C/E are matched by the rotation profile which arises naturally. Hot plasma is heated and cold plasma is cooled. Beam-target fusion reactions occur in the hot plasma region and expansion returns most of the heat energy as rotation energy. Rotation energy, in turn, produces waves which drive protons to an energy near the fusion peak cross section. A possible machine, including the arrangement of magnets and HV, is described.

Life cycle costing as a decision making tool for technology acquisition in radio-diagnosis

PubMed Central

Chakravarty, Abhijit; Debnath, Jyotindu

2014-01-01

Background Life cycle costing analysis is an emerging conceptual tool to validate capital investment in healthcare. Methods A preliminary study was done to analyze the long-term cost impact of acquiring a new 3 T MRI system when compared to technological upgradation of the existing 1.5 T MRI system with a view to evolve a decision matrix for correct investment planning and technology management. Operating costing method was utilized to estimate cost per unit MRI scan, costing inputs were considered for the existing 1.5 T and the proposed 3 T machine. Cost for each expected year in the life span of both 1.5 T and 3 T MRI scan options were then discounted to its Net Present Value. Net Present Value thus calculated for both the alternative options of 1.5 T and 3 T MRI machine was charted along with various intangible but critical Figures of Merit (FOM) to create a decision matrix for capital investment planning. Result Considering all fixed and variable costs contributing towards assumed operation, unit cost per MRI procedure was found to be Rs. 4244.58 for the 1.5 T upgrade and Rs. 6059.37 for the new 3 T MRI machine. Life Cycle Cost Analysis of the proposed 1.5 T upgrade and new 3 T machine showed a Net Present Value of Rs. 42,148,587.80 and Rs. 27,587,842.38 respectively. Conclusion The utility of life cycle costing as a strategic decision making tool towards evaluating alternative options for capital investment planning in health care environment is reiterated. PMID:25609862

40 CFR Appendix D to Subpart A of... - Harmonized Tariff Schedule Description of Products That May Contain Controlled Substances in...

Code of Federal Regulations, 2014 CFR

2014-07-01

... Conditioning/Heat Pump Equipment Domestic and commercial air conditioning and refrigeration equipment fall... cooling/heat cycle. 8415.82.00 Other, incorporating a refrigerating unit— Self-contained machines and... refrigerating or freezing equipment, electric or other; heat pumps, other than air conditioning machines of...

40 CFR Appendix D to Subpart A of... - Harmonized Tariff Schedule Description of Products That May Contain Controlled Substances in...

Code of Federal Regulations, 2011 CFR

2011-07-01

... Conditioning/Heat Pump Equipment Domestic and commercial air conditioning and refrigeration equipment fall... cooling/heat cycle. 8415.82.00 Other, incorporating a refrigerating unit— Self-contained machines and... refrigerating or freezing equipment, electric or other; heat pumps, other than air conditioning machines of...

40 CFR Appendix D to Subpart A of... - Harmonized Tariff Schedule Description of Products That May Contain Controlled Substances in...

Code of Federal Regulations, 2010 CFR

2010-07-01

... Conditioning/Heat Pump Equipment Domestic and commercial air conditioning and refrigeration equipment fall... cooling/heat cycle. 8415.82.00 Other, incorporating a refrigerating unit— Self-contained machines and... refrigerating or freezing equipment, electric or other; heat pumps, other than air conditioning machines of...

40 CFR Appendix D to Subpart A of... - Harmonized Tariff Schedule Description of Products That May Contain Controlled Substances in...

Code of Federal Regulations, 2013 CFR

2013-07-01

... Conditioning/Heat Pump Equipment Domestic and commercial air conditioning and refrigeration equipment fall... cooling/heat cycle. 8415.82.00 Other, incorporating a refrigerating unit— Self-contained machines and... refrigerating or freezing equipment, electric or other; heat pumps, other than air conditioning machines of...

40 CFR Appendix D to Subpart A of... - Harmonized Tariff Schedule Description of Products That May Contain Controlled Substances in...

Code of Federal Regulations, 2012 CFR

2012-07-01

... Conditioning/Heat Pump Equipment Domestic and commercial air conditioning and refrigeration equipment fall... cooling/heat cycle. 8415.82.00 Other, incorporating a refrigerating unit— Self-contained machines and... refrigerating or freezing equipment, electric or other; heat pumps, other than air conditioning machines of...

Financial heat machine

NASA Astrophysics Data System (ADS)

Khrennikov, Andrei

2005-05-01

We consider dynamics of financial markets as dynamics of expectations and discuss such a dynamics from the point of view of phenomenological thermodynamics. We describe a financial Carnot cycle and the financial analog of a heat machine. We see, that while in physics a perpetuum mobile is absolutely impossible, in economics such mobile may exist under some conditions.

Experimental investigation of time and repeated cycles in nucleate pool boiling of alumina/water nanofluid on polished and machined surfaces

NASA Astrophysics Data System (ADS)

Rajabzadeh Dareh, F.; Haghshenasfard, M.; Nasr Esfahany, M.; Salimi Jazi, H.

2018-06-01

Pool boiling heat transfer of pure water and nanofluids on a copper block has been studied experimentally. Nanofluids with various concentrations of 0.0025, 0.005 and 0.01 vol.% are employed and two simple surfaces (polished and machined copper surface) are used as the heating surfaces. The results indicated that the critical heat flux (CHF) in boiling of fluids on the polished surface is 7% higher than CHF on the machined surface. In the case of machined surface, the heat transfer coefficient (HTC) of 0.01 vol.% nanofluid is about 37% higher than HTC of base fluid, while in the polished surface the average HTC of 0.01% nanofluid is about 19% lower than HTC of the pure water. The results also showed that the boiling time and boiling cycles on the polished surface changes the heat transfer performance. By increasing the boiling time from 5 to 10 min, the roughness enhances about 150%, but by increasing the boiling time to 15 min, the roughness enhancement is only 8%.

Chatter active control in a lathe machine using magnetostrictive actuator

NASA Astrophysics Data System (ADS)

Nosouhi, R.; Behbahani, S.

2011-01-01

This paper analyzes the chatter phenomena in lathe machines. Chatter is one of the main causes of inaccuracy, reduction of life cycle of the machine and tool wear in machine tools. This phenomenon limits the depth of cut as a function of the cutting speed, which consequently reduces the material removal rate and machining efficiency. Chatter control is therefore important since it increases the stability region in machining and increases the critical depth of cut in machining case. To control the chatter in lathe machines, a magnetostrictive actuator is used. The materials with magnetostriction properties are kind of smart materials of which their length changes as a result of applying an exterior magnetic field, which make them suitable for control applications. It is assumed that the actuator applies the proper force exactly at the point where the machining force is applied on the tool. In this paper the chatter stability lobes is excelled as a result of applying a PID controller on the magnetostrictive actuator equipped-tool in turning.

20131201-1231_Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Thibedeau, Joe

2014-01-08

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Dec to 31 Dec 2013.

20131101-1130_Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Thibedeau, Joe

2013-12-02

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Nov to 30 Nov 2013.

20130416_Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Vanderhoff, Alex

2013-04-24

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 4/16/13.

20131001-1031_Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Thibedeau, Joe

2013-11-05

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 1 Oct 2013 to 31 Oct 2013.

20140201-0228_Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Thibedeau, Joe

2014-03-03

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Feb to 28 Feb 2014.

20130801-0831_Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Vanderhoff, Alex

2013-09-10

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 8/1/13 to 8/31/13.

20140101-0131_Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Thibedeau, Joe

2014-02-03

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Jan to 31 Jan 2014.

20140430_Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Thibedeau, Joe

2014-05-05

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 April to 30 April 2014.

20140301-0331_Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Thibedeau, Joe

2014-04-07

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Mar to 31 Mar 2014.

20140501-0531_Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Thibedeau, Joe

2014-06-02

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 May to 31 May 2014.

20140601-0630_Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Thibedeau, Joe

2014-06-30

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 June to 30 June 2014.

20140701-0731_Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Thibedeau, Joe

2014-07-31

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 July to 31 July 2014.

20130901-0930_Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Thibedeau, Joe

2013-10-25

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 1 September 2013 to 30 September 2013.

Green Machine Florida Canyon Hourly Data 20130731

DOE Data Explorer

Vanderhoff, Alex

2013-08-30

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 7/1/13 to 7/31/13.

20130501-20130531_Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Vanderhoff, Alex

2013-06-18

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from May 2013

Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Vanderhoff, Alex

2013-07-15

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 6/1/13 to 6/30/13

Virtual Employment Test Bed Operational Research and Systems Analysis to Test Armaments Designs Early in the Life Cycle

DTIC Science & Technology

2014-06-01

motion capture data used to determine position and orientation of a Soldier’s head, turret and the M2 machine gun • Controlling and acquiring user/weapon...data from the M2 simulation machine gun • Controlling paintball guns used to fire at the GPK during an experimental run • Sending and receiving TCP...Mounted, Armor/Cavalry, Combat Engineers, Field Artillery Cannon Crewmember, or MP duty assignment – Currently M2 .50 Caliber Machine Gun qualified

The paradigm compiler: Mapping a functional language for the connection machine

NASA Technical Reports Server (NTRS)

Dennis, Jack B.

1989-01-01

The Paradigm Compiler implements a new approach to compiling programs written in high level languages for execution on highly parallel computers. The general approach is to identify the principal data structures constructed by the program and to map these structures onto the processing elements of the target machine. The mapping is chosen to maximize performance as determined through compile time global analysis of the source program. The source language is Sisal, a functional language designed for scientific computations, and the target language is Paris, the published low level interface to the Connection Machine. The data structures considered are multidimensional arrays whose dimensions are known at compile time. Computations that build such arrays usually offer opportunities for highly parallel execution; they are data parallel. The Connection Machine is an attractive target for these computations, and the parallel for construct of the Sisal language is a convenient high level notation for data parallel algorithms. The principles and organization of the Paradigm Compiler are discussed.

Scanning Electron Microscopy Analysis of the Adaptation of Single-Unit Screw-Retained Computer-Aided Design/Computer-Aided Manufacture Abutments After Mechanical Cycling.

PubMed

Markarian, Roberto Adrian; Galles, Deborah Pedroso; Gomes França, Fabiana Mantovani

To measure the microgap between dental implants and custom abutments fabricated using different computer-aided design/computer-aided manufacture (CAD/CAM) methods before and after mechanical cycling. CAD software (Dental System, 3Shape) was used to design a custom abutment for a single-unit, screw-retained crown compatible with a 4.1-mm external hexagon dental implant. The resulting stereolithography file was sent for manufacturing using four CAD/CAM methods (n = 40): milling and sintering of zirconium dioxide (ZO group), cobalt-chromium (Co-Cr) sintered via selective laser melting (SLM group), fully sintered machined Co-Cr alloy (MM group), and machined and sintered agglutinated Co-Cr alloy powder (AM group). Prefabricated titanium abutments (TI group) were used as controls. Each abutment was placed on a dental implant measuring 4.1× 11 mm (SA411, SIN) inserted into an aluminum block. Measurements were taken using scanning electron microscopy (SEM) (×4,000) on four regions of the implant-abutment interface (IAI) and at a relative distance of 90 degrees from each other. The specimens were mechanically aged (1 million cycles, 2 Hz, 100 N, 37°C) and the IAI width was measured again using the same approach. Data were analyzed using two-way analysis of variance, followed by the Tukey test. After mechanical cycling, the best adaptation results were obtained from the TI (2.29 ± 1.13 μm), AM (3.58 ± 1.80 μm), and MM (1.89 ± 0.98 μm) groups. A significantly worse adaptation outcome was observed for the SLM (18.40 ± 20.78 μm) and ZO (10.42 ± 0.80 μm) groups. Mechanical cycling had a marked effect only on the AM specimens, which significantly increased the microgap at the IAI. Custom abutments fabricated using fully sintered machined Co-Cr alloy and machined and sintered agglutinated Co-Cr alloy powder demonstrated the best adaptation results at the IAI, similar to those obtained with commercial prefabricated titanium abutments after mechanical cycling. The adaptation of custom abutments made by means of SLM or milling and sintering of zirconium dioxide were worse both before and after mechanical cycling.

Identification of tissue-specific targeting peptide

NASA Astrophysics Data System (ADS)

Jung, Eunkyoung; Lee, Nam Kyung; Kang, Sang-Kee; Choi, Seung-Hoon; Kim, Daejin; Park, Kisoo; Choi, Kihang; Choi, Yun-Jaie; Jung, Dong Hyun

2012-11-01

Using phage display technique, we identified tissue-targeting peptide sets that recognize specific tissues (bone-marrow dendritic cell, kidney, liver, lung, spleen and visceral adipose tissue). In order to rapidly evaluate tissue-specific targeting peptides, we performed machine learning studies for predicting the tissue-specific targeting activity of peptides on the basis of peptide sequence information using four machine learning models and isolated the groups of peptides capable of mediating selective targeting to specific tissues. As a representative liver-specific targeting sequence, the peptide "DKNLQLH" was selected by the sequence similarity analysis. This peptide has a high degree of homology with protein ligands which can interact with corresponding membrane counterparts. We anticipate that our models will be applicable to the prediction of tissue-specific targeting peptides which can recognize the endothelial markers of target tissues.

Assessing heterogeneity in oligomeric AAA+ machines.

PubMed

Sysoeva, Tatyana A

2017-03-01

ATPases Associated with various cellular Activities (AAA+ ATPases) are molecular motors that use the energy of ATP binding and hydrolysis to remodel their target macromolecules. The majority of these ATPases form ring-shaped hexamers in which the active sites are located at the interfaces between neighboring subunits. Structural changes initiate in an active site and propagate to distant motor parts that interface and reshape the target macromolecules, thereby performing mechanical work. During the functioning cycle, the AAA+ motor transits through multiple distinct states. Ring architecture and placement of the catalytic sites at the intersubunit interfaces allow for a unique level of coordination among subunits of the motor. This in turn results in conformational differences among subunits and overall asymmetry of the motor ring as it functions. To date, a large amount of structural information has been gathered for different AAA+ motors, but even for the most characterized of them only a few structural states are known and the full mechanistic cycle cannot be yet reconstructed. Therefore, the first part of this work will provide a broad overview of what arrangements of AAA+ subunits have been structurally observed focusing on diversity of ATPase oligomeric ensembles and heterogeneity within the ensembles. The second part of this review will concentrate on methods that assess structural and functional heterogeneity among subunits of AAA+ motors, thus bringing us closer to understanding the mechanism of these fascinating molecular motors.

Honing process optimization algorithms

NASA Astrophysics Data System (ADS)

Kadyrov, Ramil R.; Charikov, Pavel N.; Pryanichnikova, Valeria V.

2018-03-01

This article considers the relevance of honing processes for creating high-quality mechanical engineering products. The features of the honing process are revealed and such important concepts as the task for optimization of honing operations, the optimal structure of the honing working cycles, stepped and stepless honing cycles, simulation of processing and its purpose are emphasized. It is noted that the reliability of the mathematical model determines the quality parameters of the honing process control. An algorithm for continuous control of the honing process is proposed. The process model reliably describes the machining of a workpiece in a sufficiently wide area and can be used to operate the CNC machine CC743.

Closed Brayton Cycle (CBC) Power Generation from an Electric Systems Perspective

NASA Astrophysics Data System (ADS)

Halsey, David G.; Fox, David A.

2006-01-01

Several forms of closed cycle heat engines exist to produce electrical energy suitable for space exploration or planetary surface applications. These engines include Stirling and Closed Brayton Cycle (CBC). Of these two, CBC has often been cited as providing the best balance of mass and efficiency for deep space or planetary power systems. Combined with an alternator on the same shaft, the hermetically sealed system provides the potential for long life and reliable operation. There is also a list of choices for the type of alternator. Choices include wound rotor machines, induction machines, switched reluctance machines, and permanent magnet generators (PMGs). In trades involving size, mass and efficiency the PMG is a favorable solution. This paper will discuss the consequences of using a CBC-PMG source for an electrical power system, and the system parameters that must be defined and controlled to provide a stable, useful power source. Considerations of voltage, frequency (including DC), and power quality will be discussed. Load interactions and constraints for various power types will also be addressed. Control of the CBC-PMG system during steady state operation and startup is also a factor.s

Sensitivity of Support Vector Machine Predictions of Passive Microwave Brightness Temperature Over Snow-covered Terrain in High Mountain Asia

NASA Astrophysics Data System (ADS)

Ahmad, J. A.; Forman, B. A.

2017-12-01

High Mountain Asia (HMA) serves as a water supply source for over 1.3 billion people, primarily in south-east Asia. Most of this water originates as snow (or ice) that melts during the summer months and contributes to the run-off downstream. In spite of its critical role, there is still considerable uncertainty regarding the total amount of snow in HMA and its spatial and temporal variation. In this study, the NASA Land Information Systems (LIS) is used to model the hydrologic cycle over the Indus basin. In addition, the ability of support vector machines (SVM), a machine learning technique, to predict passive microwave brightness temperatures at a specific frequency and polarization as a function of LIS-derived land surface model output is explored in a sensitivity analysis. Multi-frequency, multi-polarization passive microwave brightness temperatures as measured by the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) over the Indus basin are used as training targets during the SVM training process. Normalized sensitivity coefficients (NSC) are then computed to assess the sensitivity of a well-trained SVM to each LIS-derived state variable. Preliminary results conform with the known first-order physics. For example, input states directly linked to physical temperature like snow temperature, air temperature, and vegetation temperature have positive NSC's whereas input states that increase volume scattering such as snow water equivalent or snow density yield negative NSC's. Air temperature exhibits the largest sensitivity coefficients due to its inherent, high-frequency variability. Adherence of this machine learning algorithm to the first-order physics bodes well for its potential use in LIS as the observation operator within a radiance data assimilation system aimed at improving regional- and continental-scale snow estimates.

Protein thin film machines

NASA Astrophysics Data System (ADS)

Federici, Stefania; Oliviero, Giulio; Hamad-Schifferli, Kimberly; Bergese, Paolo

2010-12-01

We report the first example of microcantilever beams that are reversibly driven by protein thin film machines fuelled by cycling the salt concentration of the surrounding solution. We also show that upon the same salinity stimulus the drive can be completely reversed in its direction by introducing a surface coating ligand. Experimental results are throughout discussed within a general yet simple thermodynamic model.

Life and Reliability Characteristics of TurboBrayton Coolers

NASA Technical Reports Server (NTRS)

Breedlove, Jeff J.; Zagarola, Mark; Nellis, Greg; Dolan, Frank; Swift, Walt; Gibbon, Judith; Obenschain, Arthur F. (Technical Monitor)

2000-01-01

Wear and internal contaminants are two of the primary factors that influence reliable, long-life operation of turbo-Brayton cryocoolers. This paper describes tests that have been conducted and methods that have been developed for turbo-Brayton components and systems to assure reliable operation. The turbomachines used in these coolers employ self-acting gas bearings to support the miniature high-speed shafts, thus providing vibration-free operation. Because the bearings are self-acting, rubbing contact occurs during initial start-up and shutdown of the machines. Bearings and shafts are designed to endure multiple stop/start cycles without producing particles or surface features that would impair the proper operation of the machines. Test results are presented for a variety of turbomachines used in these systems. The tests document extended operating life and start/stop cycling behavior for machines over a range of time and temperature scales. Contaminants such as moisture and other residual gas impurities can be a source of degraded operation if they freeze out in sufficient quantities to block flow passages or if they mechanically affect the operation of the machines. A post-fabrication bakeout procedure has been successfully used to reduce residual internal contamination to acceptable levels in a closed cycle system. The process was developed during space qualification tests on the NICMOS cryocooler. Moisture levels were sampled over a six-month time interval confirming the effectiveness of the technique. A description of the bakeout procedure is presented.

Revisit of Machine Learning Supported Biological and Biomedical Studies.

PubMed

Yu, Xiang-Tian; Wang, Lu; Zeng, Tao

2018-01-01

Generally, machine learning includes many in silico methods to transform the principles underlying natural phenomenon to human understanding information, which aim to save human labor, to assist human judge, and to create human knowledge. It should have wide application potential in biological and biomedical studies, especially in the era of big biological data. To look through the application of machine learning along with biological development, this review provides wide cases to introduce the selection of machine learning methods in different practice scenarios involved in the whole biological and biomedical study cycle and further discusses the machine learning strategies for analyzing omics data in some cutting-edge biological studies. Finally, the notes on new challenges for machine learning due to small-sample high-dimension are summarized from the key points of sample unbalance, white box, and causality.

Particle Accelerator Focus Automation

NASA Astrophysics Data System (ADS)

Lopes, José; Rocha, Jorge; Redondo, Luís; Cruz, João

2017-08-01

The Laboratório de Aceleradores e Tecnologias de Radiação (LATR) at the Campus Tecnológico e Nuclear, of Instituto Superior Técnico (IST) has a horizontal electrostatic particle accelerator based on the Van de Graaff machine which is used for research in the area of material characterization. This machine produces alfa (He+) and proton (H+) beams of some μA currents up to 2 MeV/q energies. Beam focusing is obtained using a cylindrical lens of the Einzel type, assembled near the high voltage terminal. This paper describes the developed system that automatically focuses the ion beam, using a personal computer running the LabVIEW software, a multifunction input/output board and signal conditioning circuits. The focusing procedure consists of a scanning method to find the lens bias voltage which maximizes the beam current measured on a beam stopper target, which is used as feedback for the scanning cycle. This system, as part of a wider start up and shut down automation system built for this particle accelerator, brings great advantages to the operation of the accelerator by turning it faster and easier to operate, requiring less human presence, and adding the possibility of total remote control in safe conditions.

Centrifugal Microfluidic System for Nucleic Acid Amplification and Detection.

PubMed

Miao, Baogang; Peng, Niancai; Li, Lei; Li, Zheng; Hu, Fei; Zhang, Zengming; Wang, Chaohui

2015-11-04

We report here the development of a rapid PCR microfluidic system comprising a double-shaft turntable and centrifugal-based disc that rapidly drives the PCR mixture between chambers set at different temperatures, and the bidirectional flow improved the space utilization of the disc. Three heating resistors and thermistors maintained uniform, specific temperatures for the denaturation, annealing, and extension steps of the PCR. Infrared imaging showed that there was little thermal interference between reaction chambers; the system enabled the cycle number and reaction time of each step to be independently adjusted. To validate the function and efficiency of the centrifugal microfluidic system, a 350-base pair target gene from the hepatitis B virus was amplified and quantitated by fluorescence detection. By optimizing the cycling parameters, the reaction time was reduced to 32 min as compared to 120 min for a commercial PCR machine. DNA samples with concentrations ranging from 10 to 10⁶ copies/mL could be quantitatively analyzed using this system. This centrifugal-based microfluidic platform is a useful system and possesses industrialization potential that can be used for portable diagnostics.

Centrifugal Microfluidic System for Nucleic Acid Amplification and Detection

PubMed Central

Miao, Baogang; Peng, Niancai; Li, Lei; Li, Zheng; Hu, Fei; Zhang, Zengming; Wang, Chaohui

2015-01-01

We report here the development of a rapid PCR microfluidic system comprising a double-shaft turntable and centrifugal-based disc that rapidly drives the PCR mixture between chambers set at different temperatures, and the bidirectional flow improved the space utilization of the disc. Three heating resistors and thermistors maintained uniform, specific temperatures for the denaturation, annealing, and extension steps of the PCR. Infrared imaging showed that there was little thermal interference between reaction chambers; the system enabled the cycle number and reaction time of each step to be independently adjusted. To validate the function and efficiency of the centrifugal microfluidic system, a 350-base pair target gene from the hepatitis B virus was amplified and quantitated by fluorescence detection. By optimizing the cycling parameters, the reaction time was reduced to 32 min as compared to 120 min for a commercial PCR machine. DNA samples with concentrations ranging from 10 to 106 copies/mL could be quantitatively analyzed using this system. This centrifugal-based microfluidic platform is a useful system and possesses industrialization potential that can be used for portable diagnostics. PMID:26556354

Modeling guidance and recognition in categorical search: bridging human and computer object detection.

PubMed

Zelinsky, Gregory J; Peng, Yifan; Berg, Alexander C; Samaras, Dimitris

2013-10-08

Search is commonly described as a repeating cycle of guidance to target-like objects, followed by the recognition of these objects as targets or distractors. Are these indeed separate processes using different visual features? We addressed this question by comparing observer behavior to that of support vector machine (SVM) models trained on guidance and recognition tasks. Observers searched for a categorically defined teddy bear target in four-object arrays. Target-absent trials consisted of random category distractors rated in their visual similarity to teddy bears. Guidance, quantified as first-fixated objects during search, was strongest for targets, followed by target-similar, medium-similarity, and target-dissimilar distractors. False positive errors to first-fixated distractors also decreased with increasing dissimilarity to the target category. To model guidance, nine teddy bear detectors, using features ranging in biological plausibility, were trained on unblurred bears then tested on blurred versions of the same objects appearing in each search display. Guidance estimates were based on target probabilities obtained from these detectors. To model recognition, nine bear/nonbear classifiers, trained and tested on unblurred objects, were used to classify the object that would be fixated first (based on the detector estimates) as a teddy bear or a distractor. Patterns of categorical guidance and recognition accuracy were modeled almost perfectly by an HMAX model in combination with a color histogram feature. We conclude that guidance and recognition in the context of search are not separate processes mediated by different features, and that what the literature knows as guidance is really recognition performed on blurred objects viewed in the visual periphery.

Modeling guidance and recognition in categorical search: Bridging human and computer object detection

PubMed Central

Zelinsky, Gregory J.; Peng, Yifan; Berg, Alexander C.; Samaras, Dimitris

2013-01-01

Search is commonly described as a repeating cycle of guidance to target-like objects, followed by the recognition of these objects as targets or distractors. Are these indeed separate processes using different visual features? We addressed this question by comparing observer behavior to that of support vector machine (SVM) models trained on guidance and recognition tasks. Observers searched for a categorically defined teddy bear target in four-object arrays. Target-absent trials consisted of random category distractors rated in their visual similarity to teddy bears. Guidance, quantified as first-fixated objects during search, was strongest for targets, followed by target-similar, medium-similarity, and target-dissimilar distractors. False positive errors to first-fixated distractors also decreased with increasing dissimilarity to the target category. To model guidance, nine teddy bear detectors, using features ranging in biological plausibility, were trained on unblurred bears then tested on blurred versions of the same objects appearing in each search display. Guidance estimates were based on target probabilities obtained from these detectors. To model recognition, nine bear/nonbear classifiers, trained and tested on unblurred objects, were used to classify the object that would be fixated first (based on the detector estimates) as a teddy bear or a distractor. Patterns of categorical guidance and recognition accuracy were modeled almost perfectly by an HMAX model in combination with a color histogram feature. We conclude that guidance and recognition in the context of search are not separate processes mediated by different features, and that what the literature knows as guidance is really recognition performed on blurred objects viewed in the visual periphery. PMID:24105460

The research and application of visual saliency and adaptive support vector machine in target tracking field.

PubMed

Chen, Yuantao; Xu, Weihong; Kuang, Fangjun; Gao, Shangbing

2013-01-01

The efficient target tracking algorithm researches have become current research focus of intelligent robots. The main problems of target tracking process in mobile robot face environmental uncertainty. They are very difficult to estimate the target states, illumination change, target shape changes, complex backgrounds, and other factors and all affect the occlusion in tracking robustness. To further improve the target tracking's accuracy and reliability, we present a novel target tracking algorithm to use visual saliency and adaptive support vector machine (ASVM). Furthermore, the paper's algorithm has been based on the mixture saliency of image features. These features include color, brightness, and sport feature. The execution process used visual saliency features and those common characteristics have been expressed as the target's saliency. Numerous experiments demonstrate the effectiveness and timeliness of the proposed target tracking algorithm in video sequences where the target objects undergo large changes in pose, scale, and illumination.

Multiple man-machine interfaces

NASA Technical Reports Server (NTRS)

Stanton, L.; Cook, C. W.

1981-01-01

The multiple man machine interfaces inherent in military pilot training, their social implications, and the issue of possible negative feedback were explored. Modern technology has produced machines which can see, hear, and touch with greater accuracy and precision than human beings. Consequently, the military pilot is more a systems manager, often doing battle against a target he never sees. It is concluded that unquantifiable human activity requires motivation that is not intrinsic in a machine.

The application of machine learning techniques in the clinical drug therapy.

PubMed

Meng, Huan-Yu; Jin, Wan-Lin; Yan, Cheng-Kai; Yang, Huan

2018-05-25

The development of a novel drug is an extremely complicated process that includes the target identification, design and manufacture, and proper therapy of the novel drug, as well as drug dose selection, drug efficacy evaluation, and adverse drug reaction control. Due to the limited resources, high costs, long duration, and low hit-to-lead ratio in the development of pharmacogenetics and computer technology, machine learning techniques have assisted novel drug development and have gradually received more attention by researchers. According to current research, machine learning techniques are widely applied in the process of the discovery of new drugs and novel drug targets, the decision surrounding proper therapy and drug dose, and the prediction of drug efficacy and adverse drug reactions. In this article, we discussed the history, workflow, and advantages and disadvantages of machine learning techniques in the processes mentioned above. Although the advantages of machine learning techniques are fairly obvious, the application of machine learning techniques is currently limited. With further research, the application of machine techniques in drug development could be much more widespread and could potentially be one of the major methods used in drug development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

SU-E-T-113: Dose Distribution Using Respiratory Signals and Machine Parameters During Treatment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Imae, T; Haga, A; Saotome, N

Purpose: Volumetric modulated arc therapy (VMAT) is a rotational intensity-modulated radiotherapy (IMRT) technique capable of acquiring projection images during treatment. Treatment plans for lung tumors using stereotactic body radiotherapy (SBRT) are calculated with planning computed tomography (CT) images only exhale phase. Purpose of this study is to evaluate dose distribution by reconstructing from only the data such as respiratory signals and machine parameters acquired during treatment. Methods: Phantom and three patients with lung tumor underwent CT scans for treatment planning. They were treated by VMAT while acquiring projection images to derive their respiratory signals and machine parameters including positions ofmore » multi leaf collimators, dose rates and integrated monitor units. The respiratory signals were divided into 4 and 10 phases and machine parameters were correlated with the divided respiratory signals based on the gantry angle. Dose distributions of each respiratory phase were calculated from plans which were reconstructed from the respiratory signals and the machine parameters during treatment. The doses at isocenter, maximum point and the centroid of target were evaluated. Results and Discussion: Dose distributions during treatment were calculated using the machine parameters and the respiratory signals detected from projection images. Maximum dose difference between plan and in treatment distribution was −1.8±0.4% at centroid of target and dose differences of evaluated points between 4 and 10 phases were no significant. Conclusion: The present method successfully evaluated dose distribution using respiratory signals and machine parameters during treatment. This method is feasible to verify the actual dose for moving target.« less

Current Status of an Organic Rankine Cycle Engine Development Program

NASA Technical Reports Server (NTRS)

Barber, R. E.

1984-01-01

The steps taken to achieve improved bearing life in the organic Rankine cycle (ORC) engine being developed for use on solar parabolic dishes are presented. A summary of test results is given. Dynamic tests on the machine shaft and rotors of the ORC engine are also discussed.

Managing virtual machines with Vac and Vcycle

NASA Astrophysics Data System (ADS)

McNab, A.; Love, P.; MacMahon, E.

2015-12-01

We compare the Vac and Vcycle virtual machine lifecycle managers and our experiences in providing production job execution services for ATLAS, CMS, LHCb, and the GridPP VO at sites in the UK, France and at CERN. In both the Vac and Vcycle systems, the virtual machines are created outside of the experiment's job submission and pilot framework. In the case of Vac, a daemon runs on each physical host which manages a pool of virtual machines on that host, and a peer-to-peer UDP protocol is used to achieve the desired target shares between experiments across the site. In the case of Vcycle, a daemon manages a pool of virtual machines on an Infrastructure-as-a-Service cloud system such as OpenStack, and has within itself enough information to create the types of virtual machines to achieve the desired target shares. Both systems allow unused shares for one experiment to temporarily taken up by other experiements with work to be done. The virtual machine lifecycle is managed with a minimum of information, gathered from the virtual machine creation mechanism (such as libvirt or OpenStack) and using the proposed Machine/Job Features API from WLCG. We demonstrate that the same virtual machine designs can be used to run production jobs on Vac and Vcycle/OpenStack sites for ATLAS, CMS, LHCb, and GridPP, and that these technologies allow sites to be operated in a reliable and robust way.

A hip joint simulator study using simplified loading and motion cycles generating physiological wear paths and rates.

PubMed

Barbour, P S; Stone, M H; Fisher, J

1999-01-01

In some designs of hip joint simulator the cost of building a highly complex machine has been offset with the requirement for a large number of test stations. The application of the wear results generated by these machines depends on their ability to reproduce physiological wear rates and processes. In this study a hip joint simulator has been shown to reproduce physiological wear using only one load vector and two degrees of motion with simplified input cycles. The actual path of points on the femoral head relative to the acetabular cup were calculated and compared for physiological and simplified input cycles. The in vitro wear rates were found to be highly dependent on the shape of these paths and similarities could be drawn between the shape of the physiological paths and the simplified elliptical paths.

Creep Laboratory manual

NASA Astrophysics Data System (ADS)

Osgerby, S.; Loveday, M. S.

1992-06-01

A manual for the NPL Creep Laboratory, a collective name given to two testing laboratories, the Uniaxial Creep Laboratory and the Advanced High Temperature Mechanical Testing Laboratory, is presented. The first laboratory is devoted to uniaxial creep testing and houses approximately 50 high sensitivity creep machines including 10 constant stress cam lever machines. The second laboratory houses a low cycle fatigue testing machine of 100 kN capacity driven by a servo-electric actuator, five machines for uniaxial tensile creep testing of engineering ceramics at temperatures up to 1600C, and an electronic creep machine. Details of the operational procedures for carrying out uniaxial creep testing are given. Calibration procedures to be followed in order to comply with the specifications laid down by British standards, and to provide traceability back to the primary standards are described.

Genome scale enzyme–metabolite and drug–target interaction predictions using the signature molecular descriptor

DOE PAGES

Faulon, Jean-Loup; Misra, Milind; Martin, Shawn; ...

2007-11-23

Motivation: Identifying protein enzymatic or pharmacological activities are important areas of research in biology and chemistry. Biological and chemical databases are increasingly being populated with linkages between protein sequences and chemical structures. Additionally, there is now sufficient information to apply machine-learning techniques to predict interactions between chemicals and proteins at a genome scale. Current machine-learning techniques use as input either protein sequences and structures or chemical information. We propose here a method to infer protein–chemical interactions using heterogeneous input consisting of both protein sequence and chemical information. Results: Our method relies on expressing proteins and chemicals with a common cheminformaticsmore » representation. We demonstrate our approach by predicting whether proteins can catalyze reactions not present in training sets. We also predict whether a given drug can bind a target, in the absence of prior binding information for that drug and target. Lastly, such predictions cannot be made with current machine-learning techniques requiring binding information for individual reactions or individual targets.« less

Cycle life machine for AX-5 space suit

NASA Technical Reports Server (NTRS)

Schenberger, Deborah S.

1990-01-01

In order to accurately test the AX-5 space suit, a complex series of motions needed to be performed which provided a unique opportunity for mechanism design. The cycle life machine design showed how 3-D computer images can enhance mechanical design as well as help in visualizing mechanisms before manufacturing them. In the early stages of the design, potential problems in the motion of the joint and in the four bar linkage system were resolved using CAD. Since these problems would have been very difficult and tedious to solve on a drawing board, they would probably not have been addressed prior to fabrication, thus limiting the final design or requiring design modification after fabrication.

Molecular Machine Powered Surface Programmatic Chain Reaction for Highly Sensitive Electrochemical Detection of Protein.

PubMed

Zhu, Jing; Gan, Haiying; Wu, Jie; Ju, Huangxian

2018-04-17

A bipedal molecular machine powered surface programmatic chain reaction was designed for electrochemical signal amplification and highly sensitive electrochemical detection of protein. The bipedal molecular machine was built through aptamer-target specific recognition for the binding of one target protein with two DNA probes, which hybridized with surface-tethered hairpin DNA 1 (H1) via proximity effect to expose the prelocked toehold domain of H1 for the hybridization of ferrocene-labeled hairpin DNA 2 (H2-Fc). The toehold-mediated strand displacement reaction brought the electrochemical signal molecule Fc close to the electrode and meanwhile released the bipedal molecular machine to traverse the sensing surface by the surface programmatic chain reaction. Eventually, a large number of duplex structures of H1-H2 with ferrocene groups facing to the electrode were formed on the sensor surface to generate an amplified electrochemical signal. Using thrombin as a model target, this method showed a linear detection range from 2 pM to 20 nM with a detection limit of 0.76 pM. The proposed detection strategy was enzyme-free and allowed highly sensitive and selective detection of a variety of protein targets by using corresponding DNA-based affinity probes, showing potential application in bioanalysis.

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

PubMed Central

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. PMID:27242505

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

PubMed

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.

Multigrid methods in structural mechanics

NASA Technical Reports Server (NTRS)

Raju, I. S.; Bigelow, C. A.; Taasan, S.; Hussaini, M. Y.

1986-01-01

Although the application of multigrid methods to the equations of elasticity has been suggested, few such applications have been reported in the literature. In the present work, multigrid techniques are applied to the finite element analysis of a simply supported Bernoulli-Euler beam, and various aspects of the multigrid algorithm are studied and explained in detail. In this study, six grid levels were used to model half the beam. With linear prolongation and sequential ordering, the multigrid algorithm yielded results which were of machine accuracy with work equivalent to 200 standard Gauss-Seidel iterations on the fine grid. Also with linear prolongation and sequential ordering, the V(1,n) cycle with n greater than 2 yielded better convergence rates than the V(n,1) cycle. The restriction and prolongation operators were derived based on energy principles. Conserving energy during the inter-grid transfers required that the prolongation operator be the transpose of the restriction operator, and led to improved convergence rates. With energy-conserving prolongation and sequential ordering, the multigrid algorithm yielded results of machine accuracy with a work equivalent to 45 Gauss-Seidel iterations on the fine grid. The red-black ordering of relaxations yielded solutions of machine accuracy in a single V(1,1) cycle, which required work equivalent to about 4 iterations on the finest grid level.

Preliminary Investigation on Life Cycle Inventory of Powder Bed Fusion of Stainless Steel

NASA Astrophysics Data System (ADS)

Nyamekye, Patricia; Piili, Heidi; Leino, Maija; Salminen, Antti

Manufacturing of work pieces from stainless steel with laser additive manufacturing, known also as laser sintering or 3D printing may increase energy and material efficiency. The use of powder bed fusion offers advantages to make parts for dynamic applications of light weight and near-net-shape products. Due to these advantages among others, PBF may also reduce emissions and operational cost in various applications. However, there are only few life cycle assessment studies examining this subject despite its prospect to business opportunity. The application of Life Cycle Inventory (LCI) in Powder Bed Fusion (PBF) provides a distinct evaluation of material and energy consumption. LCI offers a possibility to improve knowledge of process efficiency. This study investigates effect of process sustainability in terms of raw material, energy and time consumption with PBF and CNC machining. The results of the experimental study indicated lower energy efficiency in the production process with PBF. This study revealed that specific energy consumption in PBF decreased when several components are built simultaneously than if they would be built individually. This is due to fact that energy consumption per part is lower. On the contrary, amount of energy needed to machine on part in case of CNC machining is lower when parts are done separately.

Dynamic Visual Acuity: a Functionally Relevant Research Tool

NASA Technical Reports Server (NTRS)

Peters, Brian T.; Brady, Rachel A.; Miller, Chris A.; Mulavara, Ajitkumar P.; Wood, Scott J.; Cohen, Helen S.; Bloomberg, Jacob J.

2010-01-01

Coordinated movements between the eyes and head are required to maintain a stable retinal image during head and body motion. The vestibulo-ocular reflex (VOR) plays a significant role in this gaze control system that functions well for most daily activities. However, certain environmental conditions or interruptions in normal VOR function can lead to inadequate ocular compensation, resulting in oscillopsia, or blurred vision. It is therefore possible to use acuity to determine when the environmental conditions, VOR function, or the combination of the two is not conductive for maintaining clear vision. Over several years we have designed and tested several tests of dynamic visual acuity (DVA). Early tests used the difference between standing and walking acuity to assess decrements in the gaze stabilization system after spaceflight. Supporting ground-based studies measured the responses from patients with bilateral vestibular dysfunction and explored the effects of visual target viewing distance and gait cycle events on walking acuity. Results from these studies show that DVA is affected by spaceflight, is degraded in patients with vestibular dysfunction, changes with target distance, and is not consistent across the gait cycle. We have recently expanded our research to include studies in which seated subjects are translated or rotated passively. Preliminary results from this work indicate that gaze stabilization ability may differ between similar active and passive conditions, may change with age, and can be affected by the location of the visual target with respect to the axis of motion. Use of DVA as a diagnostic tool is becoming more popular but the functional nature of the acuity outcome measure also makes it ideal for identifying conditions that could lead to degraded vision. By doing so, steps can be taken to alter the problematic environments to improve the man-machine interface and optimize performance.

Experimental research of kinetic and dynamic characteristics of temperature movements of machines

NASA Astrophysics Data System (ADS)

Parfenov, I. V.; Polyakov, A. N.

2018-03-01

Nowadays, the urgency of informational support of machines at different stages of their life cycle is increasing in the form of various experimental characteristics that determine the criteria for working capacity. The effectiveness of forming the base of experimental characteristics of machines is related directly to the duration of their field tests. In this research, the authors consider a new technique that allows reducing the duration of full-scale testing of machines by 30%. To this end, three new indicator coefficients were calculated in real time to determine the moments corresponding to the characteristic points. In the work, new terms for thermal characteristics of machine tools are introduced: kinetic and dynamic characteristics of the temperature movements of the machine. This allow taking into account not only the experimental values for the temperature displacements of the elements of the carrier system of the machine, but also their derivatives up to the third order, inclusively. The work is based on experimental data obtained in the course of full-scale thermal tests of a drilling-milling and boring CNC machine.

Self-Calibrating Surface Measuring Machine

NASA Astrophysics Data System (ADS)

Greenleaf, Allen H.

1983-04-01

A new kind of surface-measuring machine has been developed under government contract at Itek Optical Systems, a Division of Itek Corporation, to assist in the fabrication of large, highly aspheric optical elements. The machine uses four steerable distance-measuring interferometers at the corners of a tetrahedron to measure the positions of a retroreflective target placed at various locations against the surface being measured. Using four interferometers gives redundant information so that, from a set of measurement data, the dimensions of the machine as well as the coordinates of the measurement points can be determined. The machine is, therefore, self-calibrating and does not require a structure made to high accuracy. A wood-structured prototype of this machine was made whose key components are a simple form of air bearing steering mirror, a wide-angle cat's eye retroreflector used as the movable target, and tracking sensors and servos to provide automatic tracking of the cat's eye by the four laser beams. The data are taken and analyzed by computer. The output is given in terms of error relative to an equation of the desired surface. In tests of this machine, measurements of a 0.7 m diameter mirror blank have been made with an accuracy on the order of 0.2µm rms.

Behavioral Modeling for Mental Health using Machine Learning Algorithms.

PubMed

Srividya, M; Mohanavalli, S; Bhalaji, N

2018-04-03

Mental health is an indicator of emotional, psychological and social well-being of an individual. It determines how an individual thinks, feels and handle situations. Positive mental health helps one to work productively and realize their full potential. Mental health is important at every stage of life, from childhood and adolescence through adulthood. Many factors contribute to mental health problems which lead to mental illness like stress, social anxiety, depression, obsessive compulsive disorder, drug addiction, and personality disorders. It is becoming increasingly important to determine the onset of the mental illness to maintain proper life balance. The nature of machine learning algorithms and Artificial Intelligence (AI) can be fully harnessed for predicting the onset of mental illness. Such applications when implemented in real time will benefit the society by serving as a monitoring tool for individuals with deviant behavior. This research work proposes to apply various machine learning algorithms such as support vector machines, decision trees, naïve bayes classifier, K-nearest neighbor classifier and logistic regression to identify state of mental health in a target group. The responses obtained from the target group for the designed questionnaire were first subject to unsupervised learning techniques. The labels obtained as a result of clustering were validated by computing the Mean Opinion Score. These cluster labels were then used to build classifiers to predict the mental health of an individual. Population from various groups like high school students, college students and working professionals were considered as target groups. The research presents an analysis of applying the aforementioned machine learning algorithms on the target groups and also suggests directions for future work.

Efficient full-chip SRAF placement using machine learning for best accuracy and improved consistency

NASA Astrophysics Data System (ADS)

Wang, Shibing; Baron, Stanislas; Kachwala, Nishrin; Kallingal, Chidam; Sun, Dezheng; Shu, Vincent; Fong, Weichun; Li, Zero; Elsaid, Ahmad; Gao, Jin-Wei; Su, Jing; Ser, Jung-Hoon; Zhang, Quan; Chen, Been-Der; Howell, Rafael; Hsu, Stephen; Luo, Larry; Zou, Yi; Zhang, Gary; Lu, Yen-Wen; Cao, Yu

2018-03-01

Various computational approaches from rule-based to model-based methods exist to place Sub-Resolution Assist Features (SRAF) in order to increase process window for lithography. Each method has its advantages and drawbacks, and typically requires the user to make a trade-off between time of development, accuracy, consistency and cycle time. Rule-based methods, used since the 90 nm node, require long development time and struggle to achieve good process window performance for complex patterns. Heuristically driven, their development is often iterative and involves significant engineering time from multiple disciplines (Litho, OPC and DTCO). Model-based approaches have been widely adopted since the 20 nm node. While the development of model-driven placement methods is relatively straightforward, they often become computationally expensive when high accuracy is required. Furthermore these methods tend to yield less consistent SRAFs due to the nature of the approach: they rely on a model which is sensitive to the pattern placement on the native simulation grid, and can be impacted by such related grid dependency effects. Those undesirable effects tend to become stronger when more iterations or complexity are needed in the algorithm to achieve required accuracy. ASML Brion has developed a new SRAF placement technique on the Tachyon platform that is assisted by machine learning and significantly improves the accuracy of full chip SRAF placement while keeping consistency and runtime under control. A Deep Convolutional Neural Network (DCNN) is trained using the target wafer layout and corresponding Continuous Transmission Mask (CTM) images. These CTM images have been fully optimized using the Tachyon inverse mask optimization engine. The neural network generated SRAF guidance map is then used to place SRAF on full-chip. This is different from our existing full-chip MB-SRAF approach which utilizes a SRAF guidance map (SGM) of mask sensitivity to improve the contrast of optical image at the target pattern edges. In this paper, we demonstrate that machine learning assisted SRAF placement can achieve a superior process window compared to the SGM model-based SRAF method, while keeping the full-chip runtime affordable, and maintain consistency of SRAF placement . We describe the current status of this machine learning assisted SRAF technique and demonstrate its application to full chip mask synthesis and discuss how it can extend the computational lithography roadmap.

Structural dynamics of the MecA-ClpC complex: a type II AAA+ protein unfolding machine.

PubMed

Liu, Jing; Mei, Ziqing; Li, Ningning; Qi, Yutao; Xu, Yanji; Shi, Yigong; Wang, Feng; Lei, Jianlin; Gao, Ning

2013-06-14

The MecA-ClpC complex is a bacterial type II AAA(+) molecular machine responsible for regulated unfolding of substrates, such as transcription factors ComK and ComS, and targeting them to ClpP for degradation. The six subunits of the MecA-ClpC complex form a closed barrel-like structure, featured with three stacked rings and a hollow passage, where substrates are threaded and translocated through successive pores. Although the general concepts of how polypeptides are unfolded and translocated by internal pore loops of AAA(+) proteins have long been conceived, the detailed mechanistic model remains elusive. With cryoelectron microscopy, we captured four different structures of the MecA-ClpC complexes. These complexes differ in the nucleotide binding states of the two AAA(+) rings and therefore might presumably reflect distinctive, representative snapshots from a dynamic unfolding cycle of this hexameric complex. Structural analysis reveals that nucleotide binding and hydrolysis modulate the hexameric complex in a number of ways, including the opening of the N-terminal ring, the axial and radial positions of pore loops, the compactness of the C-terminal ring, as well as the relative rotation between the two nucleotide-binding domain rings. More importantly, our structural and biochemical data indicate there is an active allosteric communication between the two AAA(+) rings and suggest that concerted actions of the two AAA(+) rings are required for the efficiency of the substrate unfolding and translocation. These findings provide important mechanistic insights into the dynamic cycle of the MecA-ClpC unfoldase and especially lay a foundation toward the complete understanding of the structural dynamics of the general type II AAA(+) hexamers.

A fuel-limited isothermal DNA machine for the sensitive detection of cellular deoxyribonucleoside triphosphates.

PubMed

Dong, Jiantong; Wu, Tongbo; Xiao, Yu; Xu, Lei; Fang, Simin; Zhao, Meiping

2016-09-29

A fuel-limited isothermal DNA machine has been built for the sensitive fluorescence detection of cellular deoxyribonucleoside triphosphates (dNTPs) at the fmol level, which greatly reduces the required sample cell number. Upon the input of the limiting target dNTP, the machine runs automatically at 37 °C without the need for higher temperature.

IKAP: A heuristic framework for inference of kinase activities from Phosphoproteomics data.

PubMed

Mischnik, Marcel; Sacco, Francesca; Cox, Jürgen; Schneider, Hans-Christoph; Schäfer, Matthias; Hendlich, Manfred; Crowther, Daniel; Mann, Matthias; Klabunde, Thomas

2016-02-01

Phosphoproteomics measurements are widely applied in cellular biology to detect changes in signalling dynamics. However, due to the inherent complexity of phosphorylation patterns and the lack of knowledge on how phosphorylations are related to functions, it is often not possible to directly deduce protein activities from those measurements. Here, we present a heuristic machine learning algorithm that infers the activities of kinases from Phosphoproteomics data using kinase-target information from the PhosphoSitePlus database. By comparing the estimated kinase activity profiles to the measured phosphosite profiles, it is furthermore possible to derive the kinases that are most likely to phosphorylate the respective phosphosite. We apply our approach to published datasets of the human cell cycle generated from HeLaS3 cells, and insulin signalling dynamics in mouse hepatocytes. In the first case, we estimate the activities of 118 at six cell cycle stages and derive 94 new kinase-phosphosite links that can be validated through either database or motif information. In the second case, the activities of 143 kinases at eight time points are estimated and 49 new kinase-target links are derived. The algorithm is implemented in Matlab and be downloaded from github. It makes use of the Optimization and Statistics toolboxes. https://github.com/marcel-mischnik/IKAP.git. marcel.mischnik@gmail.com Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Significant improvements of electrical discharge machining performance by step-by-step updated adaptive control laws

NASA Astrophysics Data System (ADS)

Zhou, Ming; Wu, Jianyang; Xu, Xiaoyi; Mu, Xin; Dou, Yunping

2018-02-01

In order to obtain improved electrical discharge machining (EDM) performance, we have dedicated more than a decade to correcting one essential EDM defect, the weak stability of the machining, by developing adaptive control systems. The instabilities of machining are mainly caused by complicated disturbances in discharging. To counteract the effects from the disturbances on machining, we theoretically developed three control laws from minimum variance (MV) control law to minimum variance and pole placements coupled (MVPPC) control law and then to a two-step-ahead prediction (TP) control law. Based on real-time estimation of EDM process model parameters and measured ratio of arcing pulses which is also called gap state, electrode discharging cycle was directly and adaptively tuned so that a stable machining could be achieved. To this end, we not only theoretically provide three proved control laws for a developed EDM adaptive control system, but also practically proved the TP control law to be the best in dealing with machining instability and machining efficiency though the MVPPC control law provided much better EDM performance than the MV control law. It was also shown that the TP control law also provided a burn free machining.

A Cooperative Approach to Virtual Machine Based Fault Injection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Naughton III, Thomas J; Engelmann, Christian; Vallee, Geoffroy R

Resilience investigations often employ fault injection (FI) tools to study the effects of simulated errors on a target system. It is important to keep the target system under test (SUT) isolated from the controlling environment in order to maintain control of the experiement. Virtual machines (VMs) have been used to aid these investigations due to the strong isolation properties of system-level virtualization. A key challenge in fault injection tools is to gain proper insight and context about the SUT. In VM-based FI tools, this challenge of target con- text is increased due to the separation between host and guest (VM).more » We discuss an approach to VM-based FI that leverages virtual machine introspection (VMI) methods to gain insight into the target s context running within the VM. The key to this environment is the ability to provide basic information to the FI system that can be used to create a map of the target environment. We describe a proof- of-concept implementation and a demonstration of its use to introduce simulated soft errors into an iterative solver benchmark running in user-space of a guest VM.« less

High temperature solar photon engines. [heat engines for terrestrial and space-based solar power plants

NASA Technical Reports Server (NTRS)

Hertzberg, A.; Decher, R.; Mattick, A. T.; Lau, C. V.

1978-01-01

High temperature heat engines designed to make maximum use of the thermodynamic potential of concentrated solar radiation are described. Plasmas between 2000 K and 4000 K can be achieved by volumetric absorption of radiation in alkali metal vapors, leading to thermal efficiencies up to 75% for terrestrial solar power plants and up to 50% for space power plants. Two machines capable of expanding hot plasmas using practical technology are discussed. A binary Rankine cycle uses fluid mechanical energy transfer in a device known as the 'Comprex' or 'energy exchanger.' The second machine utilizes magnetohydrodynamics in a Brayton cycle for space applications. Absorption of solar energy and plasma radiation losses are investigated for a solar superheater using potassium vapor.

Target specific compound identification using a support vector machine.

PubMed

Plewczynski, Dariusz; von Grotthuss, Marcin; Spieser, Stephane A H; Rychlewski, Leszek; Wyrwicz, Lucjan S; Ginalski, Krzysztof; Koch, Uwe

2007-03-01

In many cases at the beginning of an HTS-campaign, some information about active molecules is already available. Often known active compounds (such as substrate analogues, natural products, inhibitors of a related protein or ligands published by a pharmaceutical company) are identified in low-throughput validation studies of the biochemical target. In this study we evaluate the effectiveness of a support vector machine applied for those compounds and used to classify a collection with unknown activity. This approach was aimed at reducing the number of compounds to be tested against the given target. Our method predicts the biological activity of chemical compounds based on only the atom pairs (AP) two dimensional topological descriptors. The supervised support vector machine (SVM) method herein is trained on compounds from the MDL drug data report (MDDR) known to be active for specific protein target. For detailed analysis, five different biological targets were selected including cyclooxygenase-2, dihydrofolate reductase, thrombin, HIV-reverse transcriptase and antagonists of the estrogen receptor. The accuracy of compound identification was estimated using the recall and precision values. The sensitivities for all protein targets exceeded 80% and the classification performance reached 100% for selected targets. In another application of the method, we addressed the absence of an initial set of active compounds for a selected protein target at the beginning of an HTS-campaign. In such a case, virtual high-throughput screening (vHTS) is usually applied by using a flexible docking procedure. However, the vHTS experiment typically contains a large percentage of false positives that should be verified by costly and time-consuming experimental follow-up assays. The subsequent use of our machine learning method was found to improve the speed (since the docking procedure was not required for all compounds from the database) and also the accuracy of the HTS hit lists (the enrichment factor).

Brainstorming: weighted voting prediction of inhibitors for protein targets.

PubMed

Plewczynski, Dariusz

2011-09-01

The "Brainstorming" approach presented in this paper is a weighted voting method that can improve the quality of predictions generated by several machine learning (ML) methods. First, an ensemble of heterogeneous ML algorithms is trained on available experimental data, then all solutions are gathered and a consensus is built between them. The final prediction is performed using a voting procedure, whereby the vote of each method is weighted according to a quality coefficient calculated using multivariable linear regression (MLR). The MLR optimization procedure is very fast, therefore no additional computational cost is introduced by using this jury approach. Here, brainstorming is applied to selecting actives from large collections of compounds relating to five diverse biological targets of medicinal interest, namely HIV-reverse transcriptase, cyclooxygenase-2, dihydrofolate reductase, estrogen receptor, and thrombin. The MDL Drug Data Report (MDDR) database was used for selecting known inhibitors for these protein targets, and experimental data was then used to train a set of machine learning methods. The benchmark dataset (available at http://bio.icm.edu.pl/∼darman/chemoinfo/benchmark.tar.gz ) can be used for further testing of various clustering and machine learning methods when predicting the biological activity of compounds. Depending on the protein target, the overall recall value is raised by at least 20% in comparison to any single machine learning method (including ensemble methods like random forest) and unweighted simple majority voting procedures.

Machining-induced deformation in stepped specimens of PH 13-8 Mo, 18 nickel maraging steel grade 200T1 and grain-refined HP 9-4-20

NASA Technical Reports Server (NTRS)

Wigley, D. A.

1985-01-01

The results of a study to evaluate the dimensional changes created during machining and subsequent cycling to cryogenic temperatures for three different metallic alloys are presented. Experimental techniques are described and results presented for 18 Ni Grade 200 maraging steel, PH-13-8 Mo stainless steel, and Grain-refined HP 9-4-20.

Variability in the skin exposure of machine operators exposed to cutting fluids.

PubMed

Wassenius, O; Järvholm, B; Engström, T; Lillienberg, L; Meding, B

1998-04-01

This study describes a new technique for measuring skin exposure to cutting fluids and evaluates the variability of skin exposure among machine operators performing cyclic (repetitive) work. The technique is based on video recording and subsequent analysis of the video tape by means of computer-synchronized video equipment. The time intervals at which the machine operator's hand was exposed to fluid were registered, and the total wet time of the skin was calculated by assuming different evaporation times for the fluid. The exposure of 12 operators with different work methods was analyzed in 6 different workshops, which included a range of machine types, from highly automated metal cutting machines (ie, actual cutting and chip removal machines) requiring operator supervision to conventional metal cutting machines, where the operator was required to maneuver the machine and manually exchange products. The relative wet time varied between 0% and 100%. A significant association between short cycle time and high relative wet time was noted. However, there was no relationship between the degree of automatization of the metal cutting machines and wet time. The study shows that skin exposure to cutting fluids can vary considerably between machine operators involved in manufacturing processes using different types of metal cutting machines. The machine type was not associated with dermal wetness. The technique appears to give objective information about dermal wetness.

Real-time, adaptive machine learning for non-stationary, near chaotic gasoline engine combustion time series.

PubMed

Vaughan, Adam; Bohac, Stanislav V

2015-10-01

Fuel efficient Homogeneous Charge Compression Ignition (HCCI) engine combustion timing predictions must contend with non-linear chemistry, non-linear physics, period doubling bifurcation(s), turbulent mixing, model parameters that can drift day-to-day, and air-fuel mixture state information that cannot typically be resolved on a cycle-to-cycle basis, especially during transients. In previous work, an abstract cycle-to-cycle mapping function coupled with ϵ-Support Vector Regression was shown to predict experimentally observed cycle-to-cycle combustion timing over a wide range of engine conditions, despite some of the aforementioned difficulties. The main limitation of the previous approach was that a partially acasual randomly sampled training dataset was used to train proof of concept offline predictions. The objective of this paper is to address this limitation by proposing a new online adaptive Extreme Learning Machine (ELM) extension named Weighted Ring-ELM. This extension enables fully causal combustion timing predictions at randomly chosen engine set points, and is shown to achieve results that are as good as or better than the previous offline method. The broader objective of this approach is to enable a new class of real-time model predictive control strategies for high variability HCCI and, ultimately, to bring HCCI's low engine-out NOx and reduced CO2 emissions to production engines. Copyright © 2015 Elsevier Ltd. All rights reserved.

Analysis of Availability of Longwall-Shearer Based On Its Working Cycle

NASA Astrophysics Data System (ADS)

Brodny, Jaroslaw; Tutak, Magdalena

2017-12-01

Effective use of any type of devices, particularly machines has very significant meaning for mining enterprises. High costs of their purchase and tenancy cause that these enterprises tend to the best use of own technical potential. However, characteristics of mining production causes that this process not always proceeds without interferences. Practical experiences show that determination of objective measure of utilization of machine in mining company is not simple. In the paper methodology allowing to solve this problem is presented. Longwall-shearer, as the most important machine between longwall mechanical complex. Also it was assumed that the most significant meaning for determination of effectiveness of longwall-shearer has its availability, i.e. its effective time of work related to standard time. Such an approach is conforming to OEE model. However, specification of mining branch causes that determined availability do not give actual state of longwall-shearer’s operation. Therefore, this availability was related to the operation cycle of longwall-shearer. In presented example a longwall-shearer works in unidirectional cycle of mining. It causes that in one direction longwall-shearer mines, moving with operating velocity, and in other direction it does not mine and moves with manoeuvre velocity. Such defined working cycle became a base for determinate availability of longwall-shearer. Using indications of industrial automatic system for each of working shift there were determined number of cycles of longwall-shearer and availability of each one. Accepted of such way of determination of availability of longwall-shearer enabled to perform accurate analysis of losses of its availability. These losses result from non-planned shutdowns of longwall-shearer. Thanks to performed analysis based on the operating cycle of longwall-shearer time of its standstill for particular phase of cycle were determined. Presented methodology of determination of longwall-shearer’s availability enables to obtain information which may be used for optimization of mining process. Knowledge of particular phases of longwall-shearer’s operation, in which reduced availability occurs, allows to direct the repairing actions exactly to these regions. Developed methodology and obtained results create great opportunities for practical application and improvement of effectiveness of underground exploitation.

Global linear-irreversible principle for optimization in finite-time thermodynamics

NASA Astrophysics Data System (ADS)

Johal, Ramandeep S.

2018-03-01

There is intense effort into understanding the universal properties of finite-time models of thermal machines —at optimal performance— such as efficiency at maximum power, coefficient of performance at maximum cooling power, and other such criteria. In this letter, a global principle consistent with linear irreversible thermodynamics is proposed for the whole cycle —without considering details of irreversibilities in the individual steps of the cycle. This helps to express the total duration of the cycle as τ \\propto {\\bar{Q}^2}/{Δ_\\text{tot}S} , where \\bar{Q} models the effective heat transferred through the machine during the cycle, and Δ_ \\text{tot} S is the total entropy generated. By taking \\bar{Q} in the form of simple algebraic means (such as arithmetic and geometric means) over the heats exchanged by the reservoirs, the present approach is able to predict various standard expressions for figures of merit at optimal performance, as well as the bounds respected by them. It simplifies the optimization procedure to a one-parameter optimization, and provides a fresh perspective on the issue of universality at optimal performance, for small difference in reservoir temperatures. As an illustration, we compare the performance of a partially optimized four-step endoreversible cycle with the present approach.

Internal adaptation, marginal accuracy and microleakage of a pressable versus a machinable ceramic laminate veneers.

PubMed

Aboushelib, Moustafa Nabil; Elmahy, Waleed AbdelMeguid; Ghazy, Mohammed Hamed

2012-08-01

The aim of this study was to evaluate the internal adaptation and marginal properties of ceramic laminate veneers fabricated using pressable and machinable CAD/CAM techniques. 40 ceramic laminate veneers were fabricated by either milling ceramic blocks using a CAD/CAM system (group 1 n=20) or press-on veneering using lost wax technique (group 2 n=20). The veneers were acid etched using hydrofluoric acid, silanated, and cemented on their corresponding prepared teeth. All specimens were stored under water (37 °C) for 60 days, then received thermocycling (15,000 cycles between 5 and 55 °C and dwell time of 90 s) followed by cyclic loading (100,000 cycles between 50 and 100 N) before immersion in basic fuchsine dye for 24 h. Half of the specimens in each group were sectioned in labio-lingual direction and the rest were horizontally sectioned using precision cutting machine (n=10). Dye penetration, internal cement film thickness, and vertical and horizontal marginal gaps at the incisal and cervical regions were measured (α=0.05). Pressable ceramic veneers demonstrated significantly lower (F=8.916, P<0.005) vertical and horizontal marginal gaps at the cervical and incisal margins and lower cement film thickness (F=50.921, P<0.001) compared to machinable ceramic veneers. The inferior marginal properties of machinable ceramic veneers were associated with significantly higher microleakage values. Pressable ceramic laminate veneers produced higher marginal adaptation, homogenous and thinner cement film thickness, and improved resistance to microleakage compared to machinable ceramic veneers. The manufacturing process influences internal and marginal fit of ceramic veneers. Therefore, dentist and laboratory technicians should choose a manufacturing process with careful consideration. Copyright © 2012 Elsevier Ltd. All rights reserved.

Synaptic Vesicle-Recycling Machinery Components as Potential Therapeutic Targets

PubMed Central

Li, Ying C.

2017-01-01

Presynaptic nerve terminals are highly specialized vesicle-trafficking machines. Neurotransmitter release from these terminals is sustained by constant local recycling of synaptic vesicles independent from the neuronal cell body. This independence places significant constraints on maintenance of synaptic protein complexes and scaffolds. Key events during the synaptic vesicle cycle—such as exocytosis and endocytosis—require formation and disassembly of protein complexes. This extremely dynamic environment poses unique challenges for proteostasis at synaptic terminals. Therefore, it is not surprising that subtle alterations in synaptic vesicle cycle-associated proteins directly or indirectly contribute to pathophysiology seen in several neurologic and psychiatric diseases. In contrast to the increasing number of examples in which presynaptic dysfunction causes neurologic symptoms or cognitive deficits associated with multiple brain disorders, synaptic vesicle-recycling machinery remains an underexplored drug target. In addition, irrespective of the involvement of presynaptic function in the disease process, presynaptic machinery may also prove to be a viable therapeutic target because subtle alterations in the neurotransmitter release may counter disease mechanisms, correct, or compensate for synaptic communication deficits without the need to interfere with postsynaptic receptor signaling. In this article, we will overview critical properties of presynaptic release machinery to help elucidate novel presynaptic avenues for the development of therapeutic strategies against neurologic and neuropsychiatric disorders. PMID:28265000

Microstructural and hardness changes in aluminum alloy Al-7075: Correlating machining and equal channel angular pressing

NASA Astrophysics Data System (ADS)

Imbrogno, Stano; Segebade, Eric; Fellmeth, Andreas; Gerstenmeyer, Michael; Zanger, Frederik; Schulze, Volker; Umbrello, Domenico

2017-10-01

Recently, the study and understanding of surface integrity of various materials after machining is becoming one of the interpretative keys to quantify a product's quality and life cycle performance. The possibility to provide fundamental details about the mechanical response and the behavior of the affected material layers caused by thermo-mechanical loads resulting from machining operations can help the designer to produce parts with superior quality. The aim of this work is to study the experimental outcomes obtained from orthogonal cutting tests and a Severe Plastic Deformation (SPD) process known as Equal Channel Angular Pressing (ECAP) in order to find possible links regarding induced microstructural and hardness changes between machined surface layer and SPD-bulk material for Al-7075. This scientific investigation aims to establish the basis for an innovative method to study and quantify metallurgical phenomena that occur beneath the machined surface of bulk material.

Cell cycle-tailored targeting of metastatic melanoma: Challenges and opportunities.

PubMed

Haass, Nikolas K; Gabrielli, Brian

2017-07-01

The advent of targeted therapies of metastatic melanoma, such as MAPK pathway inhibitors and immune checkpoint antagonists, has turned dermato-oncology from the "bad guy" to the "poster child" in oncology. Current targeted therapies are effective, although here is a clear need to develop combination therapies to delay the onset of resistance. Many antimelanoma drugs impact on the cell cycle but are also dependent on certain cell cycle phases resulting in cell cycle phase-specific drug insensitivity. Here, we raise the question: Have combination trials been abandoned prematurely as ineffective possibly only because drug scheduling was not optimized? Firstly, if both drugs of a combination hit targets in the same melanoma cell, cell cycle-mediated drug insensitivity should be taken into account when planning combination therapies, timing of dosing schedules and choice of drug therapies in solid tumors. Secondly, if the combination is designed to target different tumor cell subpopulations of a heterogeneous tumor, one drug effective in a particular subpopulation should not negatively impact on the other drug targeting another subpopulation. In addition to the role of cell cycle stage and progression on standard chemotherapeutics and targeted drugs, we discuss the utilization of cell cycle checkpoint control defects to enhance chemotherapeutic responses or as targets themselves. We propose that cell cycle-tailored targeting of metastatic melanoma could further improve therapy outcomes and that our real-time cell cycle imaging 3D melanoma spheroid model could be utilized as a tool to measure and design drug scheduling approaches. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The development and testing of the thermal break divertor monoblock target design delivering 20 MW m-2 heat load capability

NASA Astrophysics Data System (ADS)

Fursdon, M.; Barrett, T.; Domptail, F.; Evans, Ll M.; Luzginova, N.; Greuner, N. H.; You, J.-H.; Li, M.; Richou, M.; Gallay, F.; Visca, E.

2017-12-01

The design and development of a novel plasma facing component (for fusion power plants) is described. The component uses the existing ‘monoblock’ construction which consists of a tungsten ‘block’ joined via a copper interlayer to a through CuCrZr cooling pipe. In the new concept the interlayer stiffness and conductivity properties are tuned so that stress in the principal structural element of the component (the cooling pipe) is reduced. Following initial trials with off-the-shelf materials, the concept was realized by machined features in an otherwise solid copper interlayer. The shape and distribution of the features were tuned by finite element analyses subject to ITER structural design criterion in-vessel components (SDC-IC) design rules. Proof of concept mock-ups were manufactured using a two stage brazing process verified by tomography and micrographic inspection. Full assemblies were inspected using ultrasound and thermographic (SATIR) test methods at ENEA and CEA respectively. High heat flux tests using IPP’s GLADIS facility showed that 200 cycles at 20 MW m-2 and five cycles at 25 MW m-2 could be sustained without apparent component damage. Further testing and component development is planned.

Cost of unreliability method to estimate loss of revenue based on unreliability data: Case study of Printing Company

NASA Astrophysics Data System (ADS)

alhilman, Judi

2017-12-01

In the production line process of the printing office, the reliability of the printing machine plays a very important role, if the machine fail it can disrupt production target so that the company will suffer huge financial loss. One method to calculate the financial loss cause by machine failure is use the Cost of Unreliability(COUR) method. COUR method works based on down time machine and costs associated with unreliability data. Based on the calculation of COUR method, so the sum of cost due to unreliability printing machine during active repair time and downtime is 1003,747.00.

Method and apparatus for improved wire saw slurry

DOEpatents

Costantini, Michael A.; Talbott, Jonathan A.; Chandra, Mohan; Prasad, Vishwanath; Caster, Allison; Gupta, Kedar P.; Leyvraz, Philippe

2000-09-05

A slurry recycle process for use in free-abrasive machining operations such as for wire saws used in wafer slicing of ingots, where the used slurry is separated into kerf-rich and abrasive-rich components, and the abrasive-rich component is reconstituted into a makeup slurry. During the process, the average particle size of the makeup slurry is controlled by monitoring the condition of the kerf and abrasive components and making necessary adjustments to the separating force and dwell time of the separator apparatus. Related pre-separator and post separator treatments, and feedback of one or the other separator slurry output components for mixing with incoming used slurry and recirculation through the separator, provide further effectiveness and additional control points in the process. The kerf-rich component is eventually or continually removed; the abrasive-rich component is reconstituted into a makeup slurry with a controlled, average particle size such that the products of the free-abrasive machining method using the recycled slurry process of the invention are of consistent high quality with less TTV deviation from cycle to cycle for a prolonged period or series of machining operations.

Device for Extracting Flavors and Fragrances

NASA Technical Reports Server (NTRS)

Chang, F. R.

1986-01-01

Machine for making coffee and tea in weightless environment may prove even more valuable on Earth as general extraction apparatus. Zero-gravity beverage maker uses piston instead of gravity to move hot water and beverage from one chamber to other and dispense beverage. Machine functions like conventional coffeemaker during part of operating cycle and includes additional features that enable operation not only in zero gravity but also extraction under pressure in presence or absence of gravity.

Ada Compiler Validation Summary Report: Certificate Number: 890420W1. 10074 International Business Machines Corporation, IBM Development System for the Ada Language MVS Ada Compiler, Version 2.1.1 IBM 4381 (Host and Target)

DTIC Science & Technology

1989-04-20

20. ARS1AAI . (Contimne on reverse side olnetessary *rwenPtif) by bfoci nur~be’) International Business Machines Corporation, IBM Development System...Number: AVF-VSR-261.0789 89-01-26-TEL Ada COMPILER VALIDATION SUMMARY REPORT: Certificate Number: 890420W1.10074 International Business Machines...computer. The compiler was tested using command scripts provided by International Business Machines Corporation and reviewed by the validation team. The

10 CFR 75.4 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... uranium or enriching uranium in the isotope 235, zirconium tubes, heavy water or deuterium, nuclear-grade..., irradiated fuel element chopping machines, and hot cells. Nuclear fuel cycle-related research and development...

10 CFR 75.4 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

...); (3) A fuel fabrication plant; (4) An enrichment plant or isotope separation plant for the separation..., irradiated fuel element chopping machines, and hot cells. Nuclear fuel cycle-related research and development...

10 CFR 75.4 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-01-01

...); (3) A fuel fabrication plant; (4) An enrichment plant or isotope separation plant for the separation..., irradiated fuel element chopping machines, and hot cells. Nuclear fuel cycle-related research and development...

The Simpsons program 6-D phase space tracking with acceleration

NASA Astrophysics Data System (ADS)

Machida, S.

1993-12-01

A particle tracking code, Simpsons, in 6-D phase space including energy ramping has been developed to model proton synchrotrons and storage rings. We take time as the independent variable to change machine parameters and diagnose beam quality in a quite similar way as real machines, unlike existing tracking codes for synchrotrons which advance a particle element by element. Arbitrary energy ramping and rf voltage curves as a function of time are read as an input file for defining a machine cycle. The code is used to study beam dynamics with time dependent parameters. Some of the examples from simulations of the Superconducting Super Collider (SSC) boosters are shown.

Poster — Thur Eve — 49: Unexpected Output Drops: Pitted Blackholes in Tungsten

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hudson, A; Pierce, G; University of Calgary, Department of Oncology, Calgary AB

2014-08-15

During the daily measurement of radiation output of a 6 MV beam on a Varian Trilogy Linear Accelerator the output dropped below 2% and initiated a call to action by physics to determine the cause. Over the course of weeks the cause of the issue was diagnosed to be a defect in the target, resulting in a drop in output and an asymmetry of the beam. Steps were taken to return the machine to clinical service while parts were on order while ensuring the safety of patient treatment. The machine target was replaced and the machine continues to operate asmore » expected. A drop in output is usually a rarity and a defect in the target is possibly more rare. This experience demonstrated the importance of routine QC measurement, recording and analyzing daily output and symmetry values. In addition, this event showcased the importance of a multi-disciplinary approach in a high-pressure situation to effectively troubleshoot unique events to ensure consistence, safety patient treatment.« less

Creating the New from the Old: Combinatorial Libraries Generation with Machine-Learning-Based Compound Structure Optimization.

PubMed

Podlewska, Sabina; Czarnecki, Wojciech M; Kafel, Rafał; Bojarski, Andrzej J

2017-02-27

The growing computational abilities of various tools that are applied in the broadly understood field of computer-aided drug design have led to the extreme popularity of virtual screening in the search for new biologically active compounds. Most often, the source of such molecules consists of commercially available compound databases, but they can also be searched for within the libraries of structures generated in silico from existing ligands. Various computational combinatorial approaches are based solely on the chemical structure of compounds, using different types of substitutions for new molecules formation. In this study, the starting point for combinatorial library generation was the fingerprint referring to the optimal substructural composition in terms of the activity toward a considered target, which was obtained using a machine learning-based optimization procedure. The systematic enumeration of all possible connections between preferred substructures resulted in the formation of target-focused libraries of new potential ligands. The compounds were initially assessed by machine learning methods using a hashed fingerprint to represent molecules; the distribution of their physicochemical properties was also investigated, as well as their synthetic accessibility. The examination of various fingerprints and machine learning algorithms indicated that the Klekota-Roth fingerprint and support vector machine were an optimal combination for such experiments. This study was performed for 8 protein targets, and the obtained compound sets and their characterization are publically available at http://skandal.if-pan.krakow.pl/comb_lib/ .

SU-F-SPS-11: The Dosimetric Comparison of Truebeam 2.0 and Cyberknife M6 Treatment Plans for Brain SRS Treatment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mabhouti, H; Sanli, E; Cebe, M

Purpose: Brain stereotactic radiosurgery involves the use of precisely directed, single session radiation to create a desired radiobiologic response within the brain target with acceptable minimal effects on surrounding structures or tissues. In this study, the dosimetric comparison of Truebeam 2.0 and Cyberknife M6 treatment plans were made. Methods: For Truebeam 2.0 machine, treatment planning were done using 2 full arc VMAT technique with 6 FFF beam on the CT scan of Randophantom simulating the treatment of sterotactic treatments for one brain metastasis. The dose distribution were calculated using Eclipse treatment planning system with Acuros XB algorithm. The treatment planningmore » of the same target were also done for Cyberknife M6 machine with Multiplan treatment planning system using Monte Carlo algorithm. Using the same film batch, the net OD to dose calibration curve was obtained using both machine by delivering 0- 800 cGy. Films were scanned 48 hours after irradiation using an Epson 1000XL flatbed scanner. Dose distribution were measured using EBT3 film dosimeter. The measured and calculated doses were compared. Results: The dose distribution in the target and 2 cm beyond the target edge were calculated on TPSs and measured using EBT3 film. For cyberknife plans, the gamma analysis passing rates between measured and calculated dose distributions were 99.2% and 96.7% for target and peripheral region of target respectively. For Truebeam plans, the gamma analysis passing rates were 99.1% and 95.5% for target and peripheral region of target respectively. Conclusion: Although, target dose distribution calculated accurately by Acuros XB and Monte Carlo algorithms, Monte carlo calculation algorithm predicts dose distribution around the peripheral region of target more accurately than Acuros algorithm.« less

Business not as usual

NASA Technical Reports Server (NTRS)

1991-01-01

Typical design simplification ideas which reduce costs; combustion chamber design simplification; combustion chambers; castings vs. machined and welded forgings; automated inspection; and life cycle costs are outlined. This presentation is represented by viewgraphs.

Ultra precision machining

NASA Astrophysics Data System (ADS)

Debra, Daniel B.; Hesselink, Lambertus; Binford, Thomas

1990-05-01

There are a number of fields that require or can use to advantage very high precision in machining. For example, further development of high energy lasers and x ray astronomy depend critically on the manufacture of light weight reflecting metal optical components. To fabricate these optical components with machine tools they will be made of metal with mirror quality surface finish. By mirror quality surface finish, it is meant that the dimensions tolerances on the order of 0.02 microns and surface roughness of 0.07. These accuracy targets fall in the category of ultra precision machining. They cannot be achieved by a simple extension of conventional machining processes and techniques. They require single crystal diamond tools, special attention to vibration isolation, special isolation of machine metrology, and on line correction of imperfection in the motion of the machine carriages on their way.

High-resolution Temporal Representations of Alcohol and Tobacco Behaviors from Social Media Data.

PubMed

Huang, Tom; Elghafari, Anas; Relia, Kunal; Chunara, Rumi

2017-11-01

Understanding tobacco- and alcohol-related behavioral patterns is critical for uncovering risk factors and potentially designing targeted social computing intervention systems. Given that we make choices multiple times per day, hourly and daily patterns are critical for better understanding behaviors. Here, we combine natural language processing, machine learning and time series analyses to assess Twitter activity specifically related to alcohol and tobacco consumption and their sub-daily, daily and weekly cycles. Twitter self-reports of alcohol and tobacco use are compared to other data streams available at similar temporal resolution. We assess if discussion of drinking by inferred underage versus legal age people or discussion of use of different types of tobacco products can be differentiated using these temporal patterns. We find that time and frequency domain representations of behaviors on social media can provide meaningful and unique insights, and we discuss the types of behaviors for which the approach may be most useful.

In vitro wear of Ionofil Molar AC quick glass-ionomer cement.

PubMed

Abesi, Farida; Safarcherati, Hengameh; Sadati, Javad; Kheirollahi, Hossein

2011-01-01

The aim of this study was to evaluate the three-body wear-resistance of one type of restorative glass-ionomer cement (GIC). Specimen including conventional GIC (Ionofil Molar AC Quick: IMACQ), hybrid ionomer (Fuji II LC), and composite resin (Heliomolar) were tested in a wearing machine. In this machine, a 6 kg load was applied via pressable chromium-cobalt bar at 5,000, 10,000, 20,000, 40,000, 80,000, 120,000 cycles. Specimen weight was measured by an electronical weight balance before and after each cycle. Data were analyzed using one-way analysis of variance (ANOVA) followed by a t-test, and a paired t-test at P≤0.05. The highest weight loss has been found in Fuji II LC, then in GIC IMACQ and the least wear rate has been reported in heliomolar composite in all cycles except 120,000 cycles. In 120,000 cycles, the highest weight loss was seen in GIC IMACQ, then Fuji II LC, and finally heliomolar composite. There was a statistically significant difference in weight loss between GIC IMACQ and heliomolar composite (P=0/001). The wear rate of GIC IMACQ was between those of heliomolar composite and Fuji II LC glass ionomer in all cycles except 120,000 cycles. The most important advantage of this new-generation glass ionomer is its good manipulability and also high wear-resistance compared to the hybrid ionomer. Therefore, it is suggested that it can be used as restorative material in class I restorations in primary teeth.

Trends of Occupational Fatalities Involving Machines, United States, 1992–2010

PubMed Central

Marsh, Suzanne M.; Fosbroke, David E.

2016-01-01

Background This paper describes trends of occupational machine-related fatalities from 1992–2010. We examine temporal patterns by worker demographics, machine types (e.g., stationary, mobile), and industries. Methods We analyzed fatalities from Census of Fatal Occupational Injuries data provided by the Bureau of Labor Statistics to the National Institute for Occupational Safety and Health. We used injury source to identify machine-related incidents and Poisson regression to assess trends over the 19-year period. Results There was an average annual decrease of 2.8% in overall machine-related fatality rates from 1992 through 2010. Mobile machine-related fatality rates decreased an average of 2.6% annually and stationary machine-related rates decreased an average of 3.5% annually. Groups that continued to be at high risk included older workers; self-employed; and workers in agriculture/forestry/fishing, construction, and mining. Conclusion Addressing dangers posed by tractors, excavators, and other mobile machines needs to continue. High-risk worker groups should receive targeted information on machine safety. PMID:26358658

Is whole-culture synchronization biology's 'perpetual-motion machine'?

PubMed

Cooper, Stephen

2004-06-01

Whole-culture or batch synchronization cannot, in theory, produce a synchronized culture because it violates a fundamental law that proposes that no batch treatment can alter the cell-age order of a culture. In analogy with the history of perpetual-motion machines, it is suggested that the study of these whole-culture 'synchronization' methods might lead to an understanding of general biological principles even though these methods cannot be used to study the normal cell cycle.

The therapeutic potential of cell cycle targeting in multiple myeloma.

PubMed

Maes, Anke; Menu, Eline; Veirman, Kim De; Maes, Ken; Vand Erkerken, Karin; De Bruyne, Elke

2017-10-27

Proper cell cycle progression through the interphase and mitosis is regulated by coordinated activation of important cell cycle proteins (including cyclin-dependent kinases and mitotic kinases) and several checkpoint pathways. Aberrant activity of these cell cycle proteins and checkpoint pathways results in deregulation of cell cycle progression, which is one of the key hallmarks of cancer. Consequently, intensive research on targeting these cell cycle regulatory proteins identified several candidate small molecule inhibitors that are able to induce cell cycle arrest and even apoptosis in cancer cells. Importantly, several of these cell cycle regulatory proteins have also been proposed as therapeutic targets in the plasma cell malignancy multiple myeloma (MM). Despite the enormous progress in the treatment of MM the past 5 years, MM still remains most often incurable due to the development of drug resistance. Deregulated expression of the cyclins D is observed in virtually all myeloma patients, emphasizing the potential therapeutic interest of cyclin-dependent kinase inhibitors in MM. Furthermore, other targets have also been identified in MM, such as microtubules, kinesin motor proteins, aurora kinases, polo-like kinases and the anaphase promoting complex/cyclosome. This review will provide an overview of the cell cycle proteins and checkpoint pathways deregulated in MM and discuss the therapeutic potential of targeting proteins or protein complexes involved in cell cycle control in MM.

Ejected Particle Size Distributions from Shocked Metal Surfaces

DOE PAGES

Schauer, M. M.; Buttler, W. T.; Frayer, D. K.; ...

2017-04-12

Here, we present size distributions for particles ejected from features machined onto the surface of shocked Sn targets. The functional form of the size distributions is assumed to be log-normal, and the characteristic parameters of the distribution are extracted from the measured angular distribution of light scattered from a laser beam incident on the ejected particles. We also found strong evidence for a bimodal distribution of particle sizes with smaller particles evolved from features machined into the target surface and larger particles being produced at the edges of these features.

Ejected Particle Size Distributions from Shocked Metal Surfaces

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schauer, M. M.; Buttler, W. T.; Frayer, D. K.

Here, we present size distributions for particles ejected from features machined onto the surface of shocked Sn targets. The functional form of the size distributions is assumed to be log-normal, and the characteristic parameters of the distribution are extracted from the measured angular distribution of light scattered from a laser beam incident on the ejected particles. We also found strong evidence for a bimodal distribution of particle sizes with smaller particles evolved from features machined into the target surface and larger particles being produced at the edges of these features.

Thermal Management and Reliability of Automotive Power Electronics and Electric Machines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Narumanchi, Sreekant V; Bennion, Kevin S; Cousineau, Justine E

Low-cost, high-performance thermal management technologies are helping meet aggressive power density, specific power, cost, and reliability targets for power electronics and electric machines. The National Renewable Energy Laboratory is working closely with numerous industry and research partners to help influence development of components that meet aggressive performance and cost targets through development and characterization of cooling technologies, and thermal characterization and improvements of passive stack materials and interfaces. Thermomechanical reliability and lifetime estimation models are important enablers for industry in cost-and time-effective design.

Dynamic behavior of a rolling housing

NASA Astrophysics Data System (ADS)

Gentile, A.; Messina, A. M.; Trentadue, Bartolo

1994-09-01

One of the major objectives of industry is to curtail costs. An element, among others, that enables to achieve such goal is the efficiency of the production cycle machines. Such efficiency lies in the reliability of the upkeeping operations. Among maintenance procedures, measuring and analyzing vibrations is a way to detect structure modifications over the machine's lifespan. Further, the availability of a mathematical model describing the influence of each individual part of the machine on the total dynamic behavior of the whole machine may help localizing breakdowns during diagnosis operations. The paper hereof illustrates an analytical-numerical model which can simulate the behavior of a rolling housing. The aforesaid mathematical model has been obtained by FEM techniques, the dynamic response by mode superposition and the synthesis of the vibration time sequence in the frequency versus by FFT numerical techniques.

Minimal universal quantum heat machine.

PubMed

Gelbwaser-Klimovsky, D; Alicki, R; Kurizki, G

2013-01-01

In traditional thermodynamics the Carnot cycle yields the ideal performance bound of heat engines and refrigerators. We propose and analyze a minimal model of a heat machine that can play a similar role in quantum regimes. The minimal model consists of a single two-level system with periodically modulated energy splitting that is permanently, weakly, coupled to two spectrally separated heat baths at different temperatures. The equation of motion allows us to compute the stationary power and heat currents in the machine consistent with the second law of thermodynamics. This dual-purpose machine can act as either an engine or a refrigerator (heat pump) depending on the modulation rate. In both modes of operation, the maximal Carnot efficiency is reached at zero power. We study the conditions for finite-time optimal performance for several variants of the model. Possible realizations of the model are discussed.

The Universal Anaesthesia Machine (UAM): assessment of a new anaesthesia workstation built with global health in mind.

PubMed

de Beer, D A H; Nesbitt, F D; Bell, G T; Rapuleng, A

2017-04-01

The Universal Anaesthesia Machine has been developed as a complete anaesthesia workstation for use in low- and middle-income countries, where the provision of safe general anaesthesia is often compromised by unreliable supply of electricity and anaesthetic gases. We performed a functional and clinical assessment of this anaesthetic machine, with particular reference to novel features and functioning in the intended environment. The Universal Anaesthesia Machine was found to be reliable, safe and consistent across a range of tests during targeted functional testing. © 2016 The Association of Anaesthetists of Great Britain and Ireland.

Ada (Trade Name) Compiler Validation Summary Report: International Business Machines Corporation. IBM Development System for the Ada Language System, Version 1.1.0, IBM 4381 under VM/SP CMS Host, IBM 4381 under MVS Target

DTIC Science & Technology

1988-05-20

AVF Control Number: AVF-VSR-84.1087 ’S (0 87-03-10-TEL I- Ada® COMPILER VALIDATION SUMMARY REPORT: International Business Machines Corporation IBM...System, Version 1.1.0, International Business Machines Corporation, Wright-Patterson AFB. IBM 4381 under VM/SP CMS, Release 3.6 (host) and IBM 4381...an IBM 4381 operating under MVS, Release 3.8. On-site testing was performed 18 May 1987 through 20 May 1987 at International Business Machines

Ada Compiler Validation Summary Report: Certificate Number 89020W1. 10073: International Business Machines Corporation, IBM Development System for the Ada Language, VM/CMS Ada Compiler, Version 2.1.1, IBM 3083 (Host and Target)

DTIC Science & Technology

1989-04-20

International Business Machines Corporation) IBM Development System for the Ada Language, VN11/CMS Ada Compiler, Version 2.1.1, Wright-Patterson AFB, IBM 3083...890420W1.10073 International Business Machines Corporation IBM Development System for the Ada Language VM/CMS Ada Compiler Version 2.1.1 IBM 3083... International Business Machines Corporation and reviewed by the validation team. The compiler was tested using all default option settings except for the

Ada Compiler Validation Summary Report: Certificate Number: 890420W1. 10075 International Business Machines Corporation. IBM Development System, for the Ada Language CMS/MVS Ada Cross Compiler, Version 2.1.1 IBM 3083 Host and IBM 4381 Target

DTIC Science & Technology

1989-04-20

International business Machines Corporati,:i IBM Development System for the Ada Language, CMS/MVS Ada Cross Compiler, Version 2.1.1, Wright-Patterson AFB, IBM...VALIDATION SUMMARY REPORT: Certificate Number: 890420W1.10075 International Business Machines Corporation IBM Development System for the Ada Language CMS...command scripts provided by International Business Machines Corporation and reviewed by the validation team. The compiler was tested using all default

Automated solar module assembly line

NASA Technical Reports Server (NTRS)

Bycer, M.

1980-01-01

The solar module assembly machine which Kulicke and Soffa delivered under this contract is a cell tabbing and stringing machine, and capable of handling a variety of cells and assembling strings up to 4 feet long which then can be placed into a module array up to 2 feet by 4 feet in a series of parallel arrangement, and in a straight or interdigitated array format. The machine cycle is 5 seconds per solar cell. This machine is primarily adapted to 3 inch diameter round cells with two tabs between cells. Pulsed heat is used as the bond technique for solar cell interconnects. The solar module assembly machine unloads solar cells from a cassette, automatically orients them, applies flux and solders interconnect ribbons onto the cells. It then inverts the tabbed cells, connects them into cell strings, and delivers them into a module array format using a track mounted vacuum lance, from which they are taken to test and cleaning benches prior to final encapsulation into finished solar modules. Throughout the machine the solar cell is handled very carefully, and any contact with the collector side of the cell is avoided or minimized.

Autonomous proximity operations using machine vision for trajectory control and pose estimation

NASA Technical Reports Server (NTRS)

Cleghorn, Timothy F.; Sternberg, Stanley R.

1991-01-01

A machine vision algorithm was developed which permits guidance control to be maintained during autonomous proximity operations. At present this algorithm exists as a simulation, running upon an 80386 based personal computer, using a ModelMATE CAD package to render the target vehicle. However, the algorithm is sufficiently simple, so that following off-line training on a known target vehicle, it should run in real time with existing vision hardware. The basis of the algorithm is a sequence of single camera images of the target vehicle, upon which radial transforms were performed. Selected points of the resulting radial signatures are fed through a decision tree, to determine whether the signature matches that of the known reference signatures for a particular view of the target. Based upon recognized scenes, the position of the maneuvering vehicle with respect to the target vehicles can be calculated, and adjustments made in the former's trajectory. In addition, the pose and spin rates of the target satellite can be estimated using this method.

Work stress of women in sewing machine operation.

PubMed

Nag, A; Desai, H; Nag, P K

1992-06-01

The study examined the work stresses of 107 women who were engaged in sewing machine operation in small garment manufacturing units. Of the three types of sewing machines (motor-operated, full and half shuttle foot-operated), 74% of the machines were foot-operated, where throttle action of the lower limb is required to move the shuttle of the machine. The motor-operated machines were faster than the foot-operated machines. The short cycle sewing work involves repetitive action of hand and feet. The women had to maintain a constant seated position on a stool without backrest and the body inclined forward. Long-term sewing work had a cumulative load on the musculo-skeletal structures, including the vertebral column and reflected in the form of high prevalence of discomfort and pain in different body parts. About 68% of the women complained of back pain, among whom 35% reported a persistent low back pain. Common sewing work accident is piercing of the needle through the fingers, particularly the right forefingers. Unsatisfactory man-machine incompatibility, work posture and fatigue, improper coordination of eye, leg and hand are the major problems of the operators. The design mis-match of the work place may be significantly improved by taking women's anthropometric dimensions in modifying the workplace, i.e. the seat surface, seat height, work height, backrest, etc.

Towards a molecular logic machine

NASA Astrophysics Data System (ADS)

Remacle, F.; Levine, R. D.

2001-06-01

Finite state logic machines can be realized by pump-probe spectroscopic experiments on an isolated molecule. The most elaborate setup, a Turing machine, can be programmed to carry out a specific computation. We argue that a molecule can be similarly programmed, and provide examples using two photon spectroscopies. The states of the molecule serve as the possible states of the head of the Turing machine and the physics of the problem determines the possible instructions of the program. The tape is written in an alphabet that allows the listing of the different pump and probe signals that are applied in a given experiment. Different experiments using the same set of molecular levels correspond to different tapes that can be read and processed by the same head and program. The analogy to a Turing machine is not a mechanical one and is not completely molecular because the tape is not part of the molecular machine. We therefore also discuss molecular finite state machines, such as sequential devices, for which the tape is not part of the machine. Nonmolecular tapes allow for quite long input sequences with a rich alphabet (at the level of 7 bits) and laser pulse shaping experiments provide concrete examples. Single molecule spectroscopies show that a single molecule can be repeatedly cycled through a logical operation.

Large-scale prediction of adverse drug reactions using chemical, biological, and phenotypic properties of drugs.

PubMed

Liu, Mei; Wu, Yonghui; Chen, Yukun; Sun, Jingchun; Zhao, Zhongming; Chen, Xue-wen; Matheny, Michael Edwin; Xu, Hua

2012-06-01

Adverse drug reaction (ADR) is one of the major causes of failure in drug development. Severe ADRs that go undetected until the post-marketing phase of a drug often lead to patient morbidity. Accurate prediction of potential ADRs is required in the entire life cycle of a drug, including early stages of drug design, different phases of clinical trials, and post-marketing surveillance. Many studies have utilized either chemical structures or molecular pathways of the drugs to predict ADRs. Here, the authors propose a machine-learning-based approach for ADR prediction by integrating the phenotypic characteristics of a drug, including indications and other known ADRs, with the drug's chemical structures and biological properties, including protein targets and pathway information. A large-scale study was conducted to predict 1385 known ADRs of 832 approved drugs, and five machine-learning algorithms for this task were compared. This evaluation, based on a fivefold cross-validation, showed that the support vector machine algorithm outperformed the others. Of the three types of information, phenotypic data were the most informative for ADR prediction. When biological and phenotypic features were added to the baseline chemical information, the ADR prediction model achieved significant improvements in area under the curve (from 0.9054 to 0.9524), precision (from 43.37% to 66.17%), and recall (from 49.25% to 63.06%). Most importantly, the proposed model successfully predicted the ADRs associated with withdrawal of rofecoxib and cerivastatin. The results suggest that phenotypic information on drugs is valuable for ADR prediction. Moreover, they demonstrate that different models that combine chemical, biological, or phenotypic information can be built from approved drugs, and they have the potential to detect clinically important ADRs in both preclinical and post-marketing phases.

Bean Soup Translation: Flexible, Linguistically-Motivated Syntax for Machine Translation

ERIC Educational Resources Information Center

Mehay, Dennis Nolan

2012-01-01

Machine translation (MT) systems attempt to translate texts from one language into another by translating words from a "source language" and rearranging them into fluent utterances in a "target language." When the two languages organize concepts in very different ways, knowledge of their general sentence structure, or…

Machine Learning Based Classification of Microsatellite Variation: An Effective Approach for Phylogeographic Characterization of Olive Populations.

PubMed

Torkzaban, Bahareh; Kayvanjoo, Amir Hossein; Ardalan, Arman; Mousavi, Soraya; Mariotti, Roberto; Baldoni, Luciana; Ebrahimie, Esmaeil; Ebrahimi, Mansour; Hosseini-Mazinani, Mehdi

2015-01-01

Finding efficient analytical techniques is overwhelmingly turning into a bottleneck for the effectiveness of large biological data. Machine learning offers a novel and powerful tool to advance classification and modeling solutions in molecular biology. However, these methods have been less frequently used with empirical population genetics data. In this study, we developed a new combined approach of data analysis using microsatellite marker data from our previous studies of olive populations using machine learning algorithms. Herein, 267 olive accessions of various origins including 21 reference cultivars, 132 local ecotypes, and 37 wild olive specimens from the Iranian plateau, together with 77 of the most represented Mediterranean varieties were investigated using a finely selected panel of 11 microsatellite markers. We organized data in two '4-targeted' and '16-targeted' experiments. A strategy of assaying different machine based analyses (i.e. data cleaning, feature selection, and machine learning classification) was devised to identify the most informative loci and the most diagnostic alleles to represent the population and the geography of each olive accession. These analyses revealed microsatellite markers with the highest differentiating capacity and proved efficiency for our method of clustering olive accessions to reflect upon their regions of origin. A distinguished highlight of this study was the discovery of the best combination of markers for better differentiating of populations via machine learning models, which can be exploited to distinguish among other biological populations.

Predicting drug-target interactions using restricted Boltzmann machines.

PubMed

Wang, Yuhao; Zeng, Jianyang

2013-07-01

In silico prediction of drug-target interactions plays an important role toward identifying and developing new uses of existing or abandoned drugs. Network-based approaches have recently become a popular tool for discovering new drug-target interactions (DTIs). Unfortunately, most of these network-based approaches can only predict binary interactions between drugs and targets, and information about different types of interactions has not been well exploited for DTI prediction in previous studies. On the other hand, incorporating additional information about drug-target relationships or drug modes of action can improve prediction of DTIs. Furthermore, the predicted types of DTIs can broaden our understanding about the molecular basis of drug action. We propose a first machine learning approach to integrate multiple types of DTIs and predict unknown drug-target relationships or drug modes of action. We cast the new DTI prediction problem into a two-layer graphical model, called restricted Boltzmann machine, and apply a practical learning algorithm to train our model and make predictions. Tests on two public databases show that our restricted Boltzmann machine model can effectively capture the latent features of a DTI network and achieve excellent performance on predicting different types of DTIs, with the area under precision-recall curve up to 89.6. In addition, we demonstrate that integrating multiple types of DTIs can significantly outperform other predictions either by simply mixing multiple types of interactions without distinction or using only a single interaction type. Further tests show that our approach can infer a high fraction of novel DTIs that has been validated by known experiments in the literature or other databases. These results indicate that our approach can have highly practical relevance to DTI prediction and drug repositioning, and hence advance the drug discovery process. Software and datasets are available on request. Supplementary data are available at Bioinformatics online.

Business Case Analysis for Replacing the Mazak 30Y Mill-Turn Machine in SM-39. Summary

DOE Office of Scientific and Technical Information (OSTI.GOV)

Booth, Steven Richard; Dinehart, Timothy Grant; Benson, Faith Ann

2015-03-19

Business case studies are being looked at to support procurement of new machines and capital equipment in the SM-39 and TA-03-0102 machine shops. The first effort conducted economic analysis of replacing the Mazak 30Y Mill-Turn Machine located in SM-39. To determine the value of switching machinery, a baseline scenario was compared with a future scenario where new machinery was purchased and installed. The conditions under the two scenarios were defined via interviews with subject matter experts in terms of one-time and periodic costs. The results of the analysis were compiled in a life-cycle cost/benefit table. The costs of procuring, installing,more » and maintaining a new machine were balanced against the costs avoided by replacing older machinery. Productivity savings were included as a measure to show the costs avoided by being able to produce parts at a quicker and more efficient pace.« less

The Breakthrough Listen Search for Intelligent Life

NASA Astrophysics Data System (ADS)

Croft, Steve; Siemion, Andrew; De Boer, David; Enriquez, J. Emilio; Foster, Griffin; Gajjar, Vishal; Hellbourg, Greg; Hickish, Jack; Isaacson, Howard; Lebofsky, Matt; MacMahon, David; Price, Daniel; Werthimer, Dan

2018-01-01

The $100M, 10-year philanthropic "Breakthrough Listen" project is driving an unprecedented expansion of the search for intelligent life beyond Earth. Modern instruments allow ever larger regions of parameter space (luminosity function, duty cycle, beaming fraction, frequency coverage) to be explored, which is enabling us to place meaningful physical limits on the prevalence of transmitting civilizations. Data volumes are huge, and preclude long-term storage of the raw data products, so real-time and machine learning processing techniques must be employed to identify candidate signals as well as simultaneously classifying interfering sources. However, the Galaxy is now known to be a target-rich environment, teeming with habitable planets.Data from Breakthrough Listen can also be used by researchers in other areas of astronomy to study pulsars, fast radio bursts, and a range of other science targets. Breakthrough Listen is already underway in the optical and radio bands, and is also engaging with facilities across the world, including Square Kilometer Array precursors and pathfinders. I will give an overview of the technology, science goals, data products, and roadmap of Breakthrough Listen, as we attempt to answer one of humanity's oldest questions: Are we alone?

Cell cycle proteins as promising targets in cancer therapy.

PubMed

Otto, Tobias; Sicinski, Piotr

2017-01-27

Cancer is characterized by uncontrolled tumour cell proliferation resulting from aberrant activity of various cell cycle proteins. Therefore, cell cycle regulators are considered attractive targets in cancer therapy. Intriguingly, animal models demonstrate that some of these proteins are not essential for proliferation of non-transformed cells and development of most tissues. By contrast, many cancers are uniquely dependent on these proteins and hence are selectively sensitive to their inhibition. After decades of research on the physiological functions of cell cycle proteins and their relevance for cancer, this knowledge recently translated into the first approved cancer therapeutic targeting of a direct regulator of the cell cycle. In this Review, we focus on proteins that directly regulate cell cycle progression (such as cyclin-dependent kinases (CDKs)), as well as checkpoint kinases, Aurora kinases and Polo-like kinases (PLKs). We discuss the role of cell cycle proteins in cancer, the rationale for targeting them in cancer treatment and results of clinical trials, as well as the future therapeutic potential of various cell cycle inhibitors.

Flat Tile Armour Cooled by Hypervapotron Tube: a Possible Technology for ITER

NASA Astrophysics Data System (ADS)

Schlosser, J.; Escourbiac, F.; Merola, M.; Schedler, B.; Bayetti, P.; Missirlian, M.; Mitteau, R.; Robin-Vastra, I.

Carbon fibre composite (CFC) flat tile armours for actively cooled plasma facing components (PFC’s) are an important challenge for controlled fusion machines. Flat tile concepts, water cooled by tubes, were studied, developed, tested and finally operated with success in Tore Supra. The components were designed for 10 MW/m2 and mock-ups were successfully fatigue tested at 15 MW/m2, 1000 cycles. For ITER, a tube-in-tile concept was developed and mock-ups sustained up to 25 MW/m2 for 1000 cycles without failure. Recently flat tile armoured mock-ups cooled by a hypervapotron tube successfully sustained a cascade failure test under a mean heat flux of 10 MW/m2 but with a doubling of the heat flux on some tiles to simulate missing tiles (500 cycles). This encouraging results lead to reconsider the limits for flat tile concept when cooled by hypervapotron (HV) tube. New tests are now scheduled to investigate these limits in regard to the ITER requirements. Experimental evidence of the concept could be gained in Tore Supra by installing a new limiter into the machine.

Testing of molded high temperature plastic actuator road seals for use in advanced aircraft hydraulic systems

NASA Technical Reports Server (NTRS)

Waterman, A. W.; Huxford, R. L.; Nelson, W. G.

1976-01-01

Molded high temperature plastic first and second stage rod seal elements were evaluated in seal assemblies to determine performance characteristics. These characteristics were compared with the performance of machined seal elements. The 6.35 cm second stage Chevron seal assembly was tested using molded Chevrons fabricated from five molding materials. Impulse screening tests conducted over a range of 311 K to 478 K revealed thermal setting deficiencies in the aromatic polyimide molding materials. Seal elements fabricated from aromatic copolyester materials structurally failed during impulse cycle calibration. Endurance testing of 3.85 million cycles at 450 K using MIL-H-83283 fluid showed poorer seal performance with the unfilled aromatic polyimide material than had been attained with seals machined from Vespel SP-21 material. The 6.35 cm first stage step-cut compression loaded seal ring fabricated from copolyester injection molding material failed structurally during impulse cycle calibration. Molding of complex shape rod seals was shown to be a potentially controllable technique, but additional molding material property testing is recommended.

Fatigue Behavior of Crystalline-Reinforced Glass-Ceramics.

PubMed

Vicari, Carolina Barbosa; Magalhães, Bárbara de Oliveira; Griggs, Jason Alan; Borba, Márcia

2018-01-03

To evaluate the fatigue behavior of two crystalline-reinforced ceramics: leucite-reinforced (VL) and lithium disilicate-based (VD) glass-ceramics. Bar-shaped specimens (16 × 4 × 1.2 mm) were produced for each ceramic using prefabricated CAD/CAM blocks. For each group, 30 specimens were subjected to a three-point flexural strength test in a universal testing machine. For VL and VD, 36 and 41 specimens were subjected to a cyclic fatigue test, respectively. The cyclic fatigue test was performed with a pneumatic mechanical cycling machine (1 Hz; 37°C distilled water). Specimens were tested at two stress levels for each preset lifetime (10 3 and 10 4 cycles for VL; 10 4 and 10 5 cycles for VD) following the boundary technique. Fractography was performed with a scanning electron microscope. Data were analyzed with Weibull analysis. There were significant differences among groups for characteristic strength (σ 0 ) and Weibull modulus (m), as the confidence intervals did not overlap. The VD group presented the highest values of σ 0 , but the lowest Weibull modulus. Both groups showed a reduction of approximately 60% of the initial flexural strength (σ f ) after cycling for 10 4 cycles. For VD tested in fatigue, there was no degradation of σ f when the number of cycles was increased from 10 4 to 10 5 . The VL group showed an 18% decrease in σ f when the number of cycles increased from 10 3 to 10 4 . Flexural strength values estimated for a 5% probability of failure were 36 MPa for VL and 55 MPa for VD, after 10 4 cycles. Both glass-ceramics showed similar strength degradation (60%) after a lifetime of 10 4 cycles, despite their distinct mechanical properties. Mechanical cycling in humid conditions proved to be an important factor for the degradation of the mechanical properties of crystalline-reinforced glass-ceramics. © 2018 by the American College of Prosthodontists.

Prospects for small cryocoolers. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Radebaugh, R.

1982-01-01

Small cryocoolers are commonly used in the areas of infrared detection, satellite communication, and cryopumps. Some emerging application areas deal with SQUID and Josephson junction devices, which require temperatures of about 8 K or below. The need for high reliability in these small cryocoolers has dictated the use of regenerative-cycle machines, but such machines are presently limited to temperatures above about 8 K. This paper discusses some of the research being done to improve reliability, decrease noise, and reduce the low-temperature limit of small cryocoolers.

Relativistic Velocity Addition Law from Machine Gun Analogy

NASA Astrophysics Data System (ADS)

Rothenstein, Bernhard; Popescu, Stefan

2009-01-01

Many derivations of the relativistic addition law of parallel velocities without use of the Lorentz transformations (LT) are known.1-5 Some of them are based on thought experiments that require knowledge of the time dilation and the length contraction effects.1,4,5 Other derivations involve the Doppler effect in the optic domain considered from three inertial reference frames in relative motion.6 A few derivations simply involve only the principle of constancy of the light velocity.2 Such derivations are interesting for the teaching of special relativity theory since the relativistic addition of velocities leads directly to the LT.7 The derivation we propose is based on a machine gun-target analogy8 of the acoustic Doppler effect, considered from the rest frame of the machine gun and from the rest frame of the target.

Improving virtual screening predictive accuracy of Human kallikrein 5 inhibitors using machine learning models.

PubMed

Fang, Xingang; Bagui, Sikha; Bagui, Subhash

2017-08-01

The readily available high throughput screening (HTS) data from the PubChem database provides an opportunity for mining of small molecules in a variety of biological systems using machine learning techniques. From the thousands of available molecular descriptors developed to encode useful chemical information representing the characteristics of molecules, descriptor selection is an essential step in building an optimal quantitative structural-activity relationship (QSAR) model. For the development of a systematic descriptor selection strategy, we need the understanding of the relationship between: (i) the descriptor selection; (ii) the choice of the machine learning model; and (iii) the characteristics of the target bio-molecule. In this work, we employed the Signature descriptor to generate a dataset on the Human kallikrein 5 (hK 5) inhibition confirmatory assay data and compared multiple classification models including logistic regression, support vector machine, random forest and k-nearest neighbor. Under optimal conditions, the logistic regression model provided extremely high overall accuracy (98%) and precision (90%), with good sensitivity (65%) in the cross validation test. In testing the primary HTS screening data with more than 200K molecular structures, the logistic regression model exhibited the capability of eliminating more than 99.9% of the inactive structures. As part of our exploration of the descriptor-model-target relationship, the excellent predictive performance of the combination of the Signature descriptor and the logistic regression model on the assay data of the Human kallikrein 5 (hK 5) target suggested a feasible descriptor/model selection strategy on similar targets. Copyright © 2017 Elsevier Ltd. All rights reserved.

Device-Free Localization via an Extreme Learning Machine with Parameterized Geometrical Feature Extraction.

PubMed

Zhang, Jie; Xiao, Wendong; Zhang, Sen; Huang, Shoudong

2017-04-17

Device-free localization (DFL) is becoming one of the new technologies in wireless localization field, due to its advantage that the target to be localized does not need to be attached to any electronic device. In the radio-frequency (RF) DFL system, radio transmitters (RTs) and radio receivers (RXs) are used to sense the target collaboratively, and the location of the target can be estimated by fusing the changes of the received signal strength (RSS) measurements associated with the wireless links. In this paper, we will propose an extreme learning machine (ELM) approach for DFL, to improve the efficiency and the accuracy of the localization algorithm. Different from the conventional machine learning approaches for wireless localization, in which the above differential RSS measurements are trivially used as the only input features, we introduce the parameterized geometrical representation for an affected link, which consists of its geometrical intercepts and differential RSS measurement. Parameterized geometrical feature extraction (PGFE) is performed for the affected links and the features are used as the inputs of ELM. The proposed PGFE-ELM for DFL is trained in the offline phase and performed for real-time localization in the online phase, where the estimated location of the target is obtained through the created ELM. PGFE-ELM has the advantages that the affected links used by ELM in the online phase can be different from those used for training in the offline phase, and can be more robust to deal with the uncertain combination of the detectable wireless links. Experimental results show that the proposed PGFE-ELM can improve the localization accuracy and learning speed significantly compared with a number of the existing machine learning and DFL approaches, including the weighted K-nearest neighbor (WKNN), support vector machine (SVM), back propagation neural network (BPNN), as well as the well-known radio tomographic imaging (RTI) DFL approach.

Device-Free Localization via an Extreme Learning Machine with Parameterized Geometrical Feature Extraction

PubMed Central

Zhang, Jie; Xiao, Wendong; Zhang, Sen; Huang, Shoudong

2017-01-01

Device-free localization (DFL) is becoming one of the new technologies in wireless localization field, due to its advantage that the target to be localized does not need to be attached to any electronic device. In the radio-frequency (RF) DFL system, radio transmitters (RTs) and radio receivers (RXs) are used to sense the target collaboratively, and the location of the target can be estimated by fusing the changes of the received signal strength (RSS) measurements associated with the wireless links. In this paper, we will propose an extreme learning machine (ELM) approach for DFL, to improve the efficiency and the accuracy of the localization algorithm. Different from the conventional machine learning approaches for wireless localization, in which the above differential RSS measurements are trivially used as the only input features, we introduce the parameterized geometrical representation for an affected link, which consists of its geometrical intercepts and differential RSS measurement. Parameterized geometrical feature extraction (PGFE) is performed for the affected links and the features are used as the inputs of ELM. The proposed PGFE-ELM for DFL is trained in the offline phase and performed for real-time localization in the online phase, where the estimated location of the target is obtained through the created ELM. PGFE-ELM has the advantages that the affected links used by ELM in the online phase can be different from those used for training in the offline phase, and can be more robust to deal with the uncertain combination of the detectable wireless links. Experimental results show that the proposed PGFE-ELM can improve the localization accuracy and learning speed significantly compared with a number of the existing machine learning and DFL approaches, including the weighted K-nearest neighbor (WKNN), support vector machine (SVM), back propagation neural network (BPNN), as well as the well-known radio tomographic imaging (RTI) DFL approach. PMID:28420187

ABB's advanced steam turbine program

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chellini, R.

Demand for industrial steam turbines for combined-cycle applications and cogeneration plants has influenced turbine manufacturers to standardize their machines to reduce delivery time and cost. ABB, also a supplier of turnkey plants, manufactures steam turbines in Finspong, Sweden, at the former ASEA Stal facilities and in Nuernberg, Germany, at the former AEG facilities. The companies have joined forces, setting up the advanced Steam Turbine Program (ATP) that, once completed, will cover a power range from two to 100 MW. The company decided to use two criteria as a starting point, the high efficiency design of the Swedish turbines and themore » high reliability of the German machines. Thus, the main task was combining the two designs in standard machines that could be assembled quickly into predefined packages to meet specific needs of combined-cycle and cogeneration plants specified by customers. In carrying out this project, emphasis was put on cost reduction as one of the main goals. The first results of the ATP program, presented by ABB Turbinen Nuernberg, is the range of 2-30 MW turbines covered by two frame sizes comprising standard components supporting the thermodynamic module. An important feature is the standardization of the speed reduction gearbox.« less

Physics in the laundromat

NASA Astrophysics Data System (ADS)

McDonald, Kirk T.

1998-03-01

The spin cycle of a washing machine involves motion that is stabilized by the Coriolis force, similar to the case of the motion of shafts of large turbines. This system is an example of a stable inverted pendulum.

Salient Feature Identification and Analysis using Kernel-Based Classification Techniques for Synthetic Aperture Radar Automatic Target Recognition

DTIC Science & Technology

2014-03-27

and machine learning for a range of research including such topics as medical imaging [10] and handwriting recognition [11]. The type of feature...1989. [11] C. Bahlmann, B. Haasdonk, and H. Burkhardt, “Online handwriting recognition with support vector machines-a kernel approach,” in Eighth...International Workshop on Frontiers in Handwriting Recognition, pp. 49–54, IEEE, 2002. [12] C. Cortes and V. Vapnik, “Support-vector networks,” Machine

Adapting human-machine interfaces to user performance.

PubMed

Danziger, Zachary; Fishbach, Alon; Mussa-Ivaldi, Ferdinando A

2008-01-01

The goal of this study was to create and examine machine learning algorithms that adapt in a controlled and cadenced way to foster a harmonious learning environment between the user of a human-machine interface and the controlled device. In this experiment, subjects' high-dimensional finger motions remotely controlled the joint angles of a simulated planar 2-link arm, which was used to hit targets on a computer screen. Subjects were required to move the cursor at the endpoint of the simulated arm.

Parallel machine architecture and compiler design facilities

NASA Technical Reports Server (NTRS)

Kuck, David J.; Yew, Pen-Chung; Padua, David; Sameh, Ahmed; Veidenbaum, Alex

1990-01-01

The objective is to provide an integrated simulation environment for studying and evaluating various issues in designing parallel systems, including machine architectures, parallelizing compiler techniques, and parallel algorithms. The status of Delta project (which objective is to provide a facility to allow rapid prototyping of parallelized compilers that can target toward different machine architectures) is summarized. Included are the surveys of the program manipulation tools developed, the environmental software supporting Delta, and the compiler research projects in which Delta has played a role.

Superconducting Coil Winding Machine Control System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nogiec, J. M.; Kotelnikov, S.; Makulski, A.

The Spirex coil winding machine is used at Fermilab to build coils for superconducting magnets. Recently this ma-chine was equipped with a new control system, which al-lows operation from both a computer and a portable remote control unit. This control system is distributed between three layers, implemented on a PC, real-time target, and FPGA, providing respectively HMI, operational logic and direct controls. The system controls motion of all mechan-ical components and regulates the cable tension. Safety is ensured by a failsafe, redundant system.

Compiler writing system detail design specification. Volume 1: Language specification

NASA Technical Reports Server (NTRS)

Arthur, W. J.

1974-01-01

Construction within the Meta language for both language and target machine specification is reported. The elements of the function language as a meaning and syntax are presented, and the structure of the target language is described which represents the target dependent object text representation of applications programs.

Stirling cryocooler test results and design model verification

NASA Astrophysics Data System (ADS)

Shimko, Martin A.; Stacy, W. D.; McCormick, John A.

A long-life Stirling cycle cryocooler being developed for spaceborne applications is described. The results from tests on a preliminary breadboard version of the cryocooler used to demonstrate the feasibility of the technology and to validate the generator design code used in its development are presented. This machine achieved a cold-end temperature of 65 K while carrying a 1/2-W cooling load. The basic machine is a double-acting, flexure-bearing, split Stirling design with linear electromagnetic drives for the expander and compressors. Flat metal diaphragms replace pistons for sweeping and sealing the machine working volumes. The double-acting expander couples to a laminar-channel counterflow recuperative heat exchanger for regeneration. The PC-compatible design code developed for this design approach calculates regenerator loss, including heat transfer irreversibilities, pressure drop, and axial conduction in the regenerator walls. The code accurately predicted cooler performance and assisted in diagnosing breadboard machine flaws during shakedown and development testing.

TargetSpy: a supervised machine learning approach for microRNA target prediction.

PubMed

Sturm, Martin; Hackenberg, Michael; Langenberger, David; Frishman, Dmitrij

2010-05-28

Virtually all currently available microRNA target site prediction algorithms require the presence of a (conserved) seed match to the 5' end of the microRNA. Recently however, it has been shown that this requirement might be too stringent, leading to a substantial number of missed target sites. We developed TargetSpy, a novel computational approach for predicting target sites regardless of the presence of a seed match. It is based on machine learning and automatic feature selection using a wide spectrum of compositional, structural, and base pairing features covering current biological knowledge. Our model does not rely on evolutionary conservation, which allows the detection of species-specific interactions and makes TargetSpy suitable for analyzing unconserved genomic sequences.In order to allow for an unbiased comparison of TargetSpy to other methods, we classified all algorithms into three groups: I) no seed match requirement, II) seed match requirement, and III) conserved seed match requirement. TargetSpy predictions for classes II and III are generated by appropriate postfiltering. On a human dataset revealing fold-change in protein production for five selected microRNAs our method shows superior performance in all classes. In Drosophila melanogaster not only our class II and III predictions are on par with other algorithms, but notably the class I (no-seed) predictions are just marginally less accurate. We estimate that TargetSpy predicts between 26 and 112 functional target sites without a seed match per microRNA that are missed by all other currently available algorithms. Only a few algorithms can predict target sites without demanding a seed match and TargetSpy demonstrates a substantial improvement in prediction accuracy in that class. Furthermore, when conservation and the presence of a seed match are required, the performance is comparable with state-of-the-art algorithms. TargetSpy was trained on mouse and performs well in human and drosophila, suggesting that it may be applicable to a broad range of species. Moreover, we have demonstrated that the application of machine learning techniques in combination with upcoming deep sequencing data results in a powerful microRNA target site prediction tool http://www.targetspy.org.

TargetSpy: a supervised machine learning approach for microRNA target prediction

PubMed Central

2010-01-01

Background Virtually all currently available microRNA target site prediction algorithms require the presence of a (conserved) seed match to the 5' end of the microRNA. Recently however, it has been shown that this requirement might be too stringent, leading to a substantial number of missed target sites. Results We developed TargetSpy, a novel computational approach for predicting target sites regardless of the presence of a seed match. It is based on machine learning and automatic feature selection using a wide spectrum of compositional, structural, and base pairing features covering current biological knowledge. Our model does not rely on evolutionary conservation, which allows the detection of species-specific interactions and makes TargetSpy suitable for analyzing unconserved genomic sequences. In order to allow for an unbiased comparison of TargetSpy to other methods, we classified all algorithms into three groups: I) no seed match requirement, II) seed match requirement, and III) conserved seed match requirement. TargetSpy predictions for classes II and III are generated by appropriate postfiltering. On a human dataset revealing fold-change in protein production for five selected microRNAs our method shows superior performance in all classes. In Drosophila melanogaster not only our class II and III predictions are on par with other algorithms, but notably the class I (no-seed) predictions are just marginally less accurate. We estimate that TargetSpy predicts between 26 and 112 functional target sites without a seed match per microRNA that are missed by all other currently available algorithms. Conclusion Only a few algorithms can predict target sites without demanding a seed match and TargetSpy demonstrates a substantial improvement in prediction accuracy in that class. Furthermore, when conservation and the presence of a seed match are required, the performance is comparable with state-of-the-art algorithms. TargetSpy was trained on mouse and performs well in human and drosophila, suggesting that it may be applicable to a broad range of species. Moreover, we have demonstrated that the application of machine learning techniques in combination with upcoming deep sequencing data results in a powerful microRNA target site prediction tool http://www.targetspy.org. PMID:20509939

Process for laser machining and surface treatment

DOEpatents

Neil, George R.; Shinn, Michelle D.

2004-10-26

An improved method and apparatus increasing the accuracy and reducing the time required to machine materials, surface treat materials, and allow better control of defects such as particulates in pulsed laser deposition. The speed and quality of machining is improved by combining an ultrashort pulsed laser at high average power with a continuous wave laser. The ultrashort pulsed laser provides an initial ultrashort pulse, on the order of several hundred femtoseconds, to stimulate an electron avalanche in the target material. Coincident with the ultrashort pulse or shortly after it, a pulse from a continuous wave laser is applied to the target. The micromachining method and apparatus creates an initial ultrashort laser pulse to ignite the ablation followed by a longer laser pulse to sustain and enlarge on the ablation effect launched in the initial pulse. The pulse pairs are repeated at a high pulse repetition frequency and as often as desired to produce the desired micromachining effect. The micromachining method enables a lower threshold for ablation, provides more deterministic damage, minimizes the heat affected zone, minimizes cracking or melting, and reduces the time involved to create the desired machining effect.

Cogs in the endless machine: lakes, climate change and nutrient cycles: a review.

PubMed

Moss, Brian

2012-09-15

Lakes have, rather grandly, been described as sentinels, integrators and regulators of climate change (Williamson et al., Limnol. Oceanogr. 2009; 54: 2273-82). Lakes are also part of the continuum of the water cycle, cogs in a machine that processes water and elements dissolved and suspended in myriad forms. Assessing the changes in the functioning of the cogs and the machine with respect to these substances as climate changes is clearly important, but difficult. Many other human-induced influences, not least eutrophication, that impact on catchment areas and consequently on lakes, have generally complicated the recording of recent change in sediment records and modern sets of data. The least confounded evidence comes from remote lakes in mountain and polar regions and suggests effects of warming that include mobilisation of ions and increased amounts of phosphorus. A cottage industry has arisen in deduction and prediction of the future effects of climate change on lakes, but the results are very general and precision is marred not only by confounding influences but by the complexity of the lake system and the infinite variety of possible future scenarios. A common conclusion, however, is that warming will increase the intensity of symptoms of eutrophication. Direct experimentation, though expensive and still unusual and confined to shallow lake and wetland systems is perhaps the most reliable approach. Results suggest increased symptoms of eutrophication, and changes in ecosystem structure, but in some respects are different from those deduced from comparisons along latitudinal gradients or by inference from knowledge of lake behaviour. Experiments have shown marked increases in community respiration compared with gross photosynthesis in mesocosm systems and it may be that the most significant churnings of these cogs in the earth-air-water machine will be in their influence on the carbon cycle, with possibly large positive feedback effects on warming. Copyright © 2011 Elsevier B.V. All rights reserved.

Design of a line-VISAR interferometer system for the Sandia Z Machine

NASA Astrophysics Data System (ADS)

Galbraith, J.; Austin, K.; Baker, J.; Bettencourt, R.; Bliss, E.; Celeste, J.; Clancy, T.; Cohen, S.; Crosley, M.; Datte, P.; Fratanduono, D.; Frieders, G.; Hammer, J.; Jackson, J.; Johnson, D.; Jones, M.; Koen, D.; Lusk, J.; Martinez, A.; Massey, W.; McCarville, T.; McLean, H.; Raman, K.; Rodriguez, S.; Spencer, D.; Springer, P.; Wong, J.

2017-08-01

A joint team comprised of Lawrence Livermore National Laboratory (LLNL) and Sandia National Laboratory (SNL) personnel is designing a line-VISAR (Velocity Interferometer System for Any Reflector) for the Sandia Z Machine, Z Line-VISAR. The diagnostic utilizes interferometry to assess current delivery as a function of radius during a magnetically-driven implosion. The Z Line-VISAR system is comprised of the following: a two-leg line-VISAR interferometer, an eight-channel Gated Optical Imager (GOI), and a fifty-meter transport beampath to/from the target of interest. The Z Machine presents unique optomechanical design challenges. The machine utilizes magnetically driven pulsed power to drive a target to elevated temperatures and pressures useful for high energy density science. Shock accelerations exceeding 30g and a strong electromagnetic pulse (EMP) are generated during the shot event as the machine discharges currents of over 25 million amps. Sensitive optical components must be protected from shock loading, and electrical equipment must be adequately shielded from the EMP. The optical design must accommodate temperature and humidity fluctuations in the facility as well as airborne hydrocarbons from the pulsed power components. We will describe the engineering design and concept of operations of the Z Line-VISAR system. Focus will be on optomechanical design.

Ada Compiler Validation Summary Report: Certificate Number: 900121S1. 10251 Computer Sciences Corporation MC Ada V1.2.Beta/Concurrent Computer Corporation Concurrent/Masscomp 5600 Host To Concurrent/Masscomp 5600 (Dual 68020 Processor Configuration) Target

DTIC Science & Technology

1990-04-23

developed Ada Real - Time Operating System (ARTOS) for bare machine environments(Target), ACW 1.1I0. " ; - -M.UIECTTERMS Ada programming language, Ada...configuration) Operating System: CSC developed Ada Real - Time Operating System (ARTOS) for bare machine environments Memory Size: 4MB 2.2...Test Method Testing of the MC Ado V1.2.beta/ Concurrent Computer Corporation compiler and the CSC developed Ada Real - Time Operating System (ARTOS) for

Machine processing of ERTS and ground truth data

NASA Technical Reports Server (NTRS)

Rogers, R. H. (Principal Investigator); Peacock, K.

1973-01-01

The author has identified the following significant results. Results achieved by ERTS-Atmospheric Experiment PR303, whose objective is to establish a radiometric calibration technique, are reported. This technique, which determines and removes solar and atmospheric parameters that degrade the radiometric fidelity of ERTS-1 data, transforms the ERTS-1 sensor radiance measurements to absolute target reflectance signatures. A radiant power measuring instrument and its use in determining atmospheric parameters needed for ground truth are discussed. The procedures used and results achieved in machine processing ERTS-1 computer -compatible tapes and atmospheric parameters to obtain target reflectance are reviewed.

Towards a generalized energy prediction model for machine tools

PubMed Central

Bhinge, Raunak; Park, Jinkyoo; Law, Kincho H.; Dornfeld, David A.; Helu, Moneer; Rachuri, Sudarsan

2017-01-01

Energy prediction of machine tools can deliver many advantages to a manufacturing enterprise, ranging from energy-efficient process planning to machine tool monitoring. Physics-based, energy prediction models have been proposed in the past to understand the energy usage pattern of a machine tool. However, uncertainties in both the machine and the operating environment make it difficult to predict the energy consumption of the target machine reliably. Taking advantage of the opportunity to collect extensive, contextual, energy-consumption data, we discuss a data-driven approach to develop an energy prediction model of a machine tool in this paper. First, we present a methodology that can efficiently and effectively collect and process data extracted from a machine tool and its sensors. We then present a data-driven model that can be used to predict the energy consumption of the machine tool for machining a generic part. Specifically, we use Gaussian Process (GP) Regression, a non-parametric machine-learning technique, to develop the prediction model. The energy prediction model is then generalized over multiple process parameters and operations. Finally, we apply this generalized model with a method to assess uncertainty intervals to predict the energy consumed to machine any part using a Mori Seiki NVD1500 machine tool. Furthermore, the same model can be used during process planning to optimize the energy-efficiency of a machining process. PMID:28652687

Towards a generalized energy prediction model for machine tools.

PubMed

Bhinge, Raunak; Park, Jinkyoo; Law, Kincho H; Dornfeld, David A; Helu, Moneer; Rachuri, Sudarsan

2017-04-01

Energy prediction of machine tools can deliver many advantages to a manufacturing enterprise, ranging from energy-efficient process planning to machine tool monitoring. Physics-based, energy prediction models have been proposed in the past to understand the energy usage pattern of a machine tool. However, uncertainties in both the machine and the operating environment make it difficult to predict the energy consumption of the target machine reliably. Taking advantage of the opportunity to collect extensive, contextual, energy-consumption data, we discuss a data-driven approach to develop an energy prediction model of a machine tool in this paper. First, we present a methodology that can efficiently and effectively collect and process data extracted from a machine tool and its sensors. We then present a data-driven model that can be used to predict the energy consumption of the machine tool for machining a generic part. Specifically, we use Gaussian Process (GP) Regression, a non-parametric machine-learning technique, to develop the prediction model. The energy prediction model is then generalized over multiple process parameters and operations. Finally, we apply this generalized model with a method to assess uncertainty intervals to predict the energy consumed to machine any part using a Mori Seiki NVD1500 machine tool. Furthermore, the same model can be used during process planning to optimize the energy-efficiency of a machining process.

Perception of mind and dehumanization: Human, animal, or machine?

PubMed

Morera, María D; Quiles, María N; Correa, Ana D; Delgado, Naira; Leyens, Jacques-Philippe

2016-08-02

Dehumanization is reached through several approaches, including the attribute-based model of mind perception and the metaphor-based model of dehumanization. We performed two studies to find different (de)humanized images for three targets: Professional people, Evil people, and Lowest of the low. In Study 1, we examined dimensions of mind, expecting the last two categories to be dehumanized through denial of agency (Lowest of the low) or experience (Evil people), compared with humanized targets (Professional people). Study 2 aimed to distinguish these targets using metaphors. We predicted that Evil and Lowest of the low targets would suffer mechanistic and animalistic dehumanization, respectively; our predictions were confirmed, but the metaphor-based model nuanced these results: animalistic and mechanistic dehumanization were shown as overlapping rather than independent. Evil persons were perceived as "killing machines" and "predators." Finally, Lowest of the low were not animalized but considered human beings. We discuss possible interpretations. © 2016 International Union of Psychological Science.

Active machine learning-driven experimentation to determine compound effects on protein patterns.

PubMed

Naik, Armaghan W; Kangas, Joshua D; Sullivan, Devin P; Murphy, Robert F

2016-02-03

High throughput screening determines the effects of many conditions on a given biological target. Currently, to estimate the effects of those conditions on other targets requires either strong modeling assumptions (e.g. similarities among targets) or separate screens. Ideally, data-driven experimentation could be used to learn accurate models for many conditions and targets without doing all possible experiments. We have previously described an active machine learning algorithm that can iteratively choose small sets of experiments to learn models of multiple effects. We now show that, with no prior knowledge and with liquid handling robotics and automated microscopy under its control, this learner accurately learned the effects of 48 chemical compounds on the subcellular localization of 48 proteins while performing only 29% of all possible experiments. The results represent the first practical demonstration of the utility of active learning-driven biological experimentation in which the set of possible phenotypes is unknown in advance.

Design, fabrication, and performance of foil journal bearing for the brayton rotating unit

NASA Technical Reports Server (NTRS)

Licht, L.; Branger, M.

1973-01-01

Foil bearings were designed and manufactured to replace pivoted-shoe journal bearings in an existing Brayton Cycle turbo-alternator-compressor. The design of this unconventional rotor support was accomplished within the constraints and space limitations imposed by the present machine, and the substitution of foil bearings was effected without changes or modification other machine components. A housing and a test rig were constructed to incorporate the new foil-bearing support into a unified assemble with an air-driven rotor and the gimbal-mounted thrust bearing, seals, and shrouds of an actual Brayton Rotating Unit. The foil bearing required no external pressure source, and stable self-acting rotation was achieved at all speeds up to 43,200 rpm. Excellent wipe-wear characteristics of the foil bearing permitted well over 1000 start-stop cycles with no deterioriation of performance in the entire speed range.

Estimation of wear in total hip replacement using a ten station hip simulator.

PubMed

Brummitt, K; Hardaker, C S

1996-01-01

The results of hip simulator tests on a total of 16 total hip joints, all of them 22.25 mm Charnley designs, are presented. Wear at up to 6.75 million cycles was assessed by using a coordinate measuring machine. The results gave good agreement with clinical estimates of wear rate on the same design of joint replacement from a number of sources. Good agreement was also obtained when comparison was made with the published results from more sophisticated simulators. The major source of variation in the results was found to occur in the first million cycles where creep predominates. The results of this study support the use of this type of simplified simulator for estimating wear in a total hip prosthesis. The capability to test a significant number of joints simultaneously may make this mechanism preferable to more complex machines in many cases.

The direct-stress fatigue strength of 17S-T aluminum alloy throughout the range from 1/2 to 500,000,000 cycles of stress

NASA Technical Reports Server (NTRS)

Hartmann, E C; Stickley, G W

1942-01-01

Fatigue-test were conducted on six specimens made from 3/4-inch-diameter 17S-T rolled-and-drawn rod for the purpose of obtaining additional data on the fatigue life of the material at stresses up to the static strength. The specimens were tested in direct tension using a stress range from zero to a maximum in tension. A static testing machine was used to apply repeated loads in the case of the first three specimens; the other three specimens were tested in a direct tension-compression fatigue machine. The direct-stress fatigue curve obtained for the material indicates that, in the range of stresses above about two-thirds the tensile strength, the fatigue strength is higher than might be expected by simply extrapolating the ordinary curve of stress plotted against the number of cycles determined at lower stresses.

Evaluation of a Texaco gasification/endash/combined-cycle plant with Kraftwerk Union gas turbines: Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jacob, J.T.; Chu, L.A.

The modular nature of gasification-combined-cycle (GCC) plants is known to facilitate capacity addition in increments (phased construction) that may match more closely with the anticipated growth in electrical load. Because the gas turbines are the primary building blocks of a phased GCC plant, utility planners are investigating in more detail prospective gas turbines of current and advanced designs developed by several manufacturers. This report summarizes the results of the evaluation of a GCC power plant based on the Kraftwerk Union Model V84.2 gas turbines of the current design now offered for the US market. The design of the Model V84.2more » machine, a scaled-down version of Kraftwerk Union's 50 Hz Model V94 machine, incorporates features suitable for burning gases, such as coal-derived synthesis gas. 14 figs., 42 tabs.« less

Analysis and Assessment of Environmental Load of Vending Machines by a LCA Method, and Eco-Improvement Effect

NASA Astrophysics Data System (ADS)

Kimura, Yukio; Sadamichi, Yucho; Maruyama, Naoki; Kato, Seizo

These days the environmental impact due to vending machines'(VM) diffusion has greatly been discussed. This paper describes the numerical evaluation of the environmental impact by using the LCA (Life Cycle Assessment) scheme and then proposes eco-improvements' strategy toward environmentally conscious products(ECP). A new objective and universal consolidated method for the LCA-evaluation, so-called LCA-NETS(Numerical Eco-load Standardization ) developed by the authors is applied to the present issue. As a result, the environmental loads at the 5years' operation and the material procurement stages are found to dominate others over the life cycle. Further eco-improvement is realized by following the order of the LCA-NETS magnitude; namely, energy saving, materials reducing, parts' re-using, and replacing with low environmental load material. Above all, parts' re-using is specially recommendable for significant reduction of the environmental loads toward ECP.

Linear sine wave profiling to machine instability targets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schmidt, Derek William; Martinez, John Israel

2016-08-01

Specialized machining processes and programming have been developed to deliver thin tin and copper Richtmyer-Meshkov instability targets that have different amplitude perturbations across the face of one 4-in.-diameter target. Typical targets have anywhere from two to five different regions of sine waves that have different amplitudes varying from 4 to 200 μm across the face of the target. The puck is composed of multiple rings that are zero press fit together and diamond turned to create a flat platform with a tolerance of 2 μm for the shock experiment. A custom software program was written in Labview to write themore » point-to-point program for the diamond-turning profiler through the X-Y-Z movements to cut the pure planar straight sine wave geometry. As a result, the software is optimized to push the profile of the whole part into the face while eliminating any unneeded passes that do not cut any material.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bates, Robert; McConnell, Elizabeth

Machining methods across many industries generally require multiple operations to machine and process advanced materials, features with micron precision, and complex shapes. The resulting multiple machining platforms can significantly affect manufacturing cycle time and the precision of the final parts, with a resultant increase in cost and energy consumption. Ultrafast lasers represent a transformative and disruptive technology that removes material with micron precision and in a single step manufacturing process. Such precision results from athermal ablation without modification or damage to the remaining material which is the key differentiator between ultrafast laser technologies and traditional laser technologies or mechanical processes.more » Athermal ablation without modification or damage to the material eliminates post-processing or multiple manufacturing steps. Combined with the appropriate technology to control the motion of the work piece, ultrafast lasers are excellent candidates to provide breakthrough machining capability for difficult-to-machine materials. At the project onset in early 2012, the project team recognized that substantial effort was necessary to improve the application of ultrafast laser and precise motion control technologies (for micromachining difficult-to-machine materials) to further the aggregate throughput and yield improvements over conventional machining methods. The project described in this report advanced these leading-edge technologies thru the development and verification of two platforms: a hybrid enhanced laser chassis and a multi-application testbed.« less

Evaluation of the eZono 4000 with eZGuide for ultrasound-guided procedures.

PubMed

Gadsden, Jeff; Latmore, Malikah; Levine, Daniel M

2015-05-01

Ultrasound-guided procedures are increasingly common in a variety of acute care settings, such as the operating room, critical care unit and emergency room. However, accurate judgment of needle tip position using traditional ultrasound technology is frequently difficult, and serious injury can result from inadvertently advancing beyond or through the target. Needle navigation is a recent innovation that allows the clinician to visualize the needle position and trajectory in real time as it approaches the target. A novel ultrasound machine has recently been introduced that is portable and designed for procedural guidance. The eZono 4000™ features an innovative needle navigation technology that is simple to use and permits the use of a wide range of commercially available needles, avoiding the inconvenience and cost of proprietary equipment. This article discusses this new ultrasound machine in the context of other currently available ultrasound machines featuring needle navigation.

The ligand binding mechanism to purine nucleoside phosphorylase elucidated via molecular dynamics and machine learning.

PubMed

Decherchi, Sergio; Berteotti, Anna; Bottegoni, Giovanni; Rocchia, Walter; Cavalli, Andrea

2015-01-27

The study of biomolecular interactions between a drug and its biological target is of paramount importance for the design of novel bioactive compounds. In this paper, we report on the use of molecular dynamics (MD) simulations and machine learning to study the binding mechanism of a transition state analogue (DADMe-immucillin-H) to the purine nucleoside phosphorylase (PNP) enzyme. Microsecond-long MD simulations allow us to observe several binding events, following different dynamical routes and reaching diverse binding configurations. These simulations are used to estimate kinetic and thermodynamic quantities, such as kon and binding free energy, obtaining a good agreement with available experimental data. In addition, we advance a hypothesis for the slow-onset inhibition mechanism of DADMe-immucillin-H against PNP. Combining extensive MD simulations with machine learning algorithms could therefore be a fruitful approach for capturing key aspects of drug-target recognition and binding.

Dynamism in a Semiconductor Industrial Machine Allocation Problem using a Hybrid of the Bio-inspired and Musical-Harmony Approach

NASA Astrophysics Data System (ADS)

Kalsom Yusof, Umi; Nor Akmal Khalid, Mohd

2015-05-01

Semiconductor industries need to constantly adjust to the rapid pace of change in the market. Most manufactured products usually have a very short life cycle. These scenarios imply the need to improve the efficiency of capacity planning, an important aspect of the machine allocation plan known for its complexity. Various studies have been performed to balance productivity and flexibility in the flexible manufacturing system (FMS). Many approaches have been developed by the researchers to determine the suitable balance between exploration (global improvement) and exploitation (local improvement). However, not much work has been focused on the domain of machine allocation problem that considers the effects of machine breakdowns. This paper develops a model to minimize the effect of machine breakdowns, thus increasing the productivity. The objectives are to minimize system unbalance and makespan as well as increase throughput while satisfying the technological constraints such as machine time availability. To examine the effectiveness of the proposed model, results for throughput, system unbalance and makespan on real industrial datasets were performed with applications of intelligence techniques, that is, a hybrid of genetic algorithm and harmony search. The result aims to obtain a feasible solution to the domain problem.

Application of grey-fuzzy approach in parametric optimization of EDM process in machining of MDN 300 steel

NASA Astrophysics Data System (ADS)

Protim Das, Partha; Gupta, P.; Das, S.; Pradhan, B. B.; Chakraborty, S.

2018-01-01

Maraging steel (MDN 300) find its application in many industries as it exhibits high hardness which are very difficult to machine material. Electro discharge machining (EDM) is an extensively popular machining process which can be used in machining of such materials. Optimization of response parameters are essential for effective machining of these materials. Past researchers have already used Taguchi for obtaining the optimal responses of EDM process for this material with responses such as material removal rate (MRR), tool wear rate (TWR), relative wear ratio (RWR), and surface roughness (SR) considering discharge current, pulse on time, pulse off time, arc gap, and duty cycle as process parameters. In this paper, grey relation analysis (GRA) with fuzzy logic is applied to this multi objective optimization problem to check the responses by an implementation of the derived parametric setting. It was found that the parametric setting derived by the proposed method results in better a response than those reported by the past researchers. Obtained results are also verified using the technique for order of preference by similarity to ideal solution (TOPSIS). The predicted result also shows that there is a significant improvement in comparison to the results of past researchers.

Effects of Process Parameters and Cryotreated Electrode on the Radial Overcut of Aisi 304 IN SiC Powder Mixed Edm

NASA Astrophysics Data System (ADS)

Bhaumik, Munmun; Maity, Kalipada

Powder mixed electro discharge machining (PMEDM) is further advancement of conventional electro discharge machining (EDM) where the powder particles are suspended in the dielectric medium to enhance the machining rate as well as surface finish. Cryogenic treatment is introduced in this process for improving the tool life and cutting tool properties. In the present investigation, the characterization of the cryotreated tempered electrode was performed. An attempt has been made to study the effect of cryotreated double tempered electrode on the radial overcut (ROC) when SiC powder is mixed in the kerosene dielectric during electro discharge machining of AISI 304. The process performance has been evaluated by means of ROC when peak current, pulse on time, gap voltage, duty cycle and powder concentration are considered as process parameters and machining is performed by using tungsten carbide electrodes (untreated and double tempered electrodes). A regression analysis was performed to correlate the data between the response and the process parameters. Microstructural analysis was carried out on the machined surfaces. Least radial overcut was observed for conventional EDM as compared to powder mixed EDM. Cryotreated double tempered electrode significantly reduced the radial overcut than untreated electrode.

Low cycle fatigue properties of MAR-M-246 Hf in hydrogen. [a cast nickel-base alloy

NASA Technical Reports Server (NTRS)

Warren, J. R.

1979-01-01

The transverse, low cycle fatigue properties were determined for directionally solidified and single crystal samples of a cast nickel-base alloy proposed for use in space propulsion systems in pure or partial high pressure hydrogen environments at elevated temperatures. The test temperature was 760 C (1400F) and the pressure of the gaseous hydrogen was 34.5 MPa (5000 psig). Low cycle fatique life was established by strain controlled testing using smooth specimens and a servohydraulic closed-loop test machine modified with a high pressure environmental chamber. Results and conclusions are discussed.

Targeting hardwoods

Treesearch

Douglass F. Jacobs

2011-01-01

Increasing demand for hardwood seedlings has prompted research to identify target seedling characteristics that promote hardwood plantation establishment. Operational establishment of hardwood plantations has typically emphasized seed collection from non-improved genetic sources, bareroot nursery seedling production, and spring planting using machine planters. The...

Method and apparatus for executing an asynchronous clutch-to-clutch shift in a hybrid transmission

DOEpatents

Demirovic, Besim; Gupta, Pinaki; Kaminsky, Lawrence A.; Naqvi, Ali K.; Heap, Anthony H.; Sah, Jy-Jen F.

2014-08-12

A hybrid transmission includes first and second electric machines. A method for operating the hybrid transmission in response to a command to execute a shift from an initial continuously variable mode to a target continuously variable mode includes increasing torque of an oncoming clutch associated with operating in the target continuously variable mode and correspondingly decreasing a torque of an off-going clutch associated with operating in the initial continuously variable mode. Upon deactivation of the off-going clutch, torque outputs of the first and second electric machines and the torque of the oncoming clutch are controlled to synchronize the oncoming clutch. Upon synchronization of the oncoming clutch, the torque for the oncoming clutch is increased and the transmission is operated in the target continuously variable mode.

Machine vision for various manipulation tasks

NASA Astrophysics Data System (ADS)

Domae, Yukiyasu

2017-03-01

Bin-picking, re-grasping, pick-and-place, kitting, etc. There are many manipulation tasks in the fields of automation of factory, warehouse and so on. The main problem of the automation is that the target objects (items/parts) have various shapes, weights and surface materials. In my talk, I will show latest machine vision systems and algorithms against the problem.

Improvement of automatic fish feeder machine design

NASA Astrophysics Data System (ADS)

Chui Wei, How; Salleh, S. M.; Ezree, Abdullah Mohd; Zaman, I.; Hatta, M. H.; Zain, B. A. Md; Mahzan, S.; Rahman, M. N. A.; Mahmud, W. A. W.

2017-10-01

Nation Plan of action for management of fishing is target to achieve an efficient, equitable and transparent management of fishing capacity in marine capture fisheries by 2018. However, several factors influence the fishery production and efficiency of marine system such as automatic fish feeder machine could be taken in consideration. Two latest fish feeder machines have been chosen as the reference for this study. Based on the observation, it has found that the both machine was made with heavy structure, low water and temperature resistance materials. This research’s objective is to develop the automatic feeder machine to increase the efficiency of fish feeding. The experiment has conducted to testing the new design of machine. The new machine with maximum storage of 5 kg and functioning with two DC motors. This machine able to distribute 500 grams of pellets within 90 seconds and longest distance of 4.7 meter. The higher speed could reduce time needed and increase the distance as well. The minimum speed range for both motor is 110 and 120 with same full speed range of 255.

MBASIC batch processor architectural overview

NASA Technical Reports Server (NTRS)

Reynolds, S. M.

1978-01-01

The MBASIC (TM) batch processor, a language translator designed to operate in the MBASIC (TM) environment is described. Features include: (1) a CONVERT TO BATCH command, usable from the ready mode; and (2) translation of the users program in stages through several levels of intermediate language and optimization. The processor is to be designed and implemented in both machine-independent and machine-dependent sections. The architecture is planned so that optimization processes are transparent to the rest of the system and need not be included in the first design implementation cycle.

Towards Polarised Antiprotons: Machine Developments for Spin-Filtering Studies

NASA Astrophysics Data System (ADS)

Lenisa, Paolo

2016-02-01

We address the commissioning of the experimental equipment and the machine studies required for the first spin-filtering experiment with protons at the COSY ring in Jülich (Germany) at a beam kinetic energy of 49.3 MeV. The implementation of a low-beta insertion made it possible to achieve beam lifetimes of 8000 s in the presence of a dense polarized hydrogen storage cell target. The developed techniques can be directly applied to antiproton machines and allow for the determination of the spin-dependent pbar-p cross sections via spin-filtering.

The method of micro-motion cycle feature extraction based on confidence coefficient evaluation criteria

NASA Astrophysics Data System (ADS)

Tang, Chuanzi; Ren, Hongmei; Bo, Li; Jing, Huang

2017-11-01

In radar target recognition, the micro motion characteristics of target is one of the characteristics that researchers pay attention to at home and abroad, in which the characteristics of target precession cycle is one of the important characteristics of target movement characteristics. Periodic feature extraction methods have been studied for years, the complex shape of the target and the scattering center stack lead to random fluctuations of the RCS. These random fluctuations also exist certain periodicity, which has a great influence on the target recognition result. In order to solve the problem, this paper proposes a extraction method of micro-motion cycle feature based on confidence coefficient evaluation criteria.

AC Loss Analysis of MgB2-Based Fully Superconducting Machines

NASA Astrophysics Data System (ADS)

Feddersen, M.; Haran, K. S.; Berg, F.

2017-12-01

Superconducting electric machines have shown potential for significant increase in power density, making them attractive for size and weight sensitive applications such as offshore wind generation, marine propulsion, and hybrid-electric aircraft propulsion. Superconductors exhibit no loss under dc conditions, though ac current and field produce considerable losses due to hysteresis, eddy currents, and coupling mechanisms. For this reason, many present machines are designed to be partially superconducting, meaning that the dc field components are superconducting while the ac armature coils are conventional conductors. Fully superconducting designs can provide increases in power density with significantly higher armature current; however, a good estimate of ac losses is required to determine the feasibility under the machines intended operating conditions. This paper aims to characterize the expected losses in a fully superconducting machine targeted towards aircraft, based on an actively-shielded, partially superconducting machine from prior work. Various factors are examined such as magnet strength, operating frequency, and machine load to produce a model for the loss in the superconducting components of the machine. This model is then used to optimize the design of the machine for minimal ac loss while maximizing power density. Important observations from the study are discussed.

Plant microRNA-Target Interaction Identification Model Based on the Integration of Prediction Tools and Support Vector Machine

PubMed Central

Meng, Jun; Shi, Lin; Luan, Yushi

2014-01-01

Background Confident identification of microRNA-target interactions is significant for studying the function of microRNA (miRNA). Although some computational miRNA target prediction methods have been proposed for plants, results of various methods tend to be inconsistent and usually lead to more false positive. To address these issues, we developed an integrated model for identifying plant miRNA–target interactions. Results Three online miRNA target prediction toolkits and machine learning algorithms were integrated to identify and analyze Arabidopsis thaliana miRNA-target interactions. Principle component analysis (PCA) feature extraction and self-training technology were introduced to improve the performance. Results showed that the proposed model outperformed the previously existing methods. The results were validated by using degradome sequencing supported Arabidopsis thaliana miRNA-target interactions. The proposed model constructed on Arabidopsis thaliana was run over Oryza sativa and Vitis vinifera to demonstrate that our model is effective for other plant species. Conclusions The integrated model of online predictors and local PCA-SVM classifier gained credible and high quality miRNA-target interactions. The supervised learning algorithm of PCA-SVM classifier was employed in plant miRNA target identification for the first time. Its performance can be substantially improved if more experimentally proved training samples are provided. PMID:25051153

High purity tungsten targets

NASA Technical Reports Server (NTRS)

1975-01-01

High purity tungsten, which is used for targets in X-ray tubes was considered for space processing. The demand for X-ray tubes was calculated using the growth rates for dental and medical X-ray machines. It is concluded that the cost benefits are uncertain.

Coating glass-ionomer cements with a nanofilled resin.

PubMed

Bonifácio, Clarissa Calil; Werner, Arie; Kleverlaan, Cornelis Johanes

2012-12-01

The objective of this study was to investigate the effect of a nanofilled resin coat on the flexural strength (FS) and the early wear (after 50,000 and 200,000 cycles) of the glass-ionomer cements Fuji IX GP Extra (FIXE) and Ketac Molar Aplicap (KM). Specimens were prepared and half of them were coated with G-Coat plus. The uncoated specimens were used as controls. Flexural strength (n = 10) was evaluated after 24 h using a 3-point bending test on a universal testing machine (ISO 9917-2). Wear (n = 20) was evaluated after 50,000 and 200,000 cycles using the ACTA wear machine. One-way, two-way ANOVA and Tukey post-hoc tests were used to analyze differences in FS and wear. For FIXE the coat significantly increased the FS and the wear along the two time spans. KM did not show a significant difference in FS with the coat. Improvements in wear were observed only after 50,000 cycles. Based on these laboratory results, it is concluded that G-coat Plus is indicated in association with GP IX Extra with the aim to improve the mechanical properties of the former. However, this study is limited to a short-term observation.

Oil-Free Rotor Support Technologies for Long Life, Closed Cycle Brayton Turbines

NASA Technical Reports Server (NTRS)

Lucero, John M.; DellaCorte, Christopher

2004-01-01

The goal of this study is to provide technological support to ensure successful life and operation of a 50-300 kW dynamic power conversion system specifically with response to the rotor support system. By utilizing technical expertise in tribology, bearings, rotordynamic, solid lubricant coatings and extensive test facilities, valuable input for mission success is provided. A discussion of the history of closed cycle Brayton turboalternators (TA) will be included. This includes the 2 kW Mini-Brayton Rotating Unit (Mini-BRU), the 10kW Brayton Rotating Unit (BRU) and the 125 kW turboalternator-compressor (TAC) designed in mid 1970's. Also included is the development of air-cycle machines and terrestrial oil-free gas turbine power systems in the form of microturbines, specifically Capstone microturbines. A short discussion of the self-acting compliant surface hydrodynamic fluid film bearings, or foil bearings, will follow, including a short history of the load capacity advances, the NASA coatings advancements as well as design model advances. Successes in terrestrial based machines will be noted and NASA tribology and bearing research test facilities will be described. Finally, implementation of a four step integration process will be included in the discussion.

Combined Auditory and Vibrotactile Feedback for Human-Machine-Interface Control.

PubMed

Thorp, Elias B; Larson, Eric; Stepp, Cara E

2014-01-01

The purpose of this study was to determine the effect of the addition of binary vibrotactile stimulation to continuous auditory feedback (vowel synthesis) for human-machine interface (HMI) control. Sixteen healthy participants controlled facial surface electromyography to achieve 2-D targets (vowels). Eight participants used only real-time auditory feedback to locate targets whereas the other eight participants were additionally alerted to having achieved targets with confirmatory vibrotactile stimulation at the index finger. All participants trained using their assigned feedback modality (auditory alone or combined auditory and vibrotactile) over three sessions on three days and completed a fourth session on the third day using novel targets to assess generalization. Analyses of variance performed on the 1) percentage of targets reached and 2) percentage of trial time at the target revealed a main effect for feedback modality: participants using combined auditory and vibrotactile feedback performed significantly better than those using auditory feedback alone. No effect was found for session or the interaction of feedback modality and session, indicating a successful generalization to novel targets but lack of improvement over training sessions. Future research is necessary to determine the cognitive cost associated with combined auditory and vibrotactile feedback during HMI control.

Contributions a la caracterisation et a l'amelioration de l'usinabilite de pieces d'acier elaborees par metallurgie des poudres

NASA Astrophysics Data System (ADS)

Boilard, Patrick

Even though powder metallurgy (P/M) is a near net shape process, a large number of parts still require one or more machining operations during the course of their elaboration and/or their finishing. The main objectives of the work presented in this thesis are centered on the elaboration of blends with enhanced machinability, as well as helping with the definition and in the characterization of the machinability of P/M parts. Enhancing machinability can be done in various ways, through the use of machinability additives and by decreasing the amount of porosity of the parts. These different ways of enhancing machinability have been investigated thoroughly, by systematically planning and preparing series of samples in order to obtain valid and repeatable results leading to meaningful conclusions relevant to the P/M domain. Results obtained during the course of the work are divided into three main chapters: (1) the effect of machining parameters on machinability, (2) the effect of additives on machinability, and (3) the development and the characterization of high density parts obtained by liquid phase sintering. Regarding the effect of machining parameters on machinability, studies were performed on parameters such as rotating speed, feed, tool position and diameter of the tool. Optimal cutting parameters are found for drilling operations performed on a standard FC-0208 blend, for different machinability criteria. Moreover, study of material removal rates shows the sensitivity of the machinability criteria for different machining parameters and indicates that thrust force is more regular than tool wear and slope of the drillability curve in the characterization of machinability. The chapter discussing the effect of various additives on machinability reveals many interesting results. First, work carried out on MoS2 additions reveals the dissociation of this additive and the creation of metallic sulphides (namely CuxS sulphides) when copper is present. Results also show that it is possible to reduce the amount of MoS2 in the blend so as to lower the dimensional change and the cost (blend Mo8A), while enhancing machinability and keeping hardness values within the same range (70 HRB). Second, adding enstatite (MgO·SiO2) permits the observation of the mechanisms occurring with the use of this additive. It is found that the stability of enstatite limits the diffusion of graphite during sintering, leading to the presence of free graphite in the pores, thus enhancing machinability. Furthermore, a lower amount of graphite in the matrix leads to a lower hardness, which is also beneficial to machinability. It is also found that the presence of copper enhances the diffusion of graphite, through the formation of a liquid phase during sintering. With the objective of improving machinability by reaching higher densities, blends were developed for densification through liquid phase sintering. High density samples are obtained (>7.5 g/cm3) for blends prepared with Fe-C-P constituents, namely with 0.5%P and 2.4%C. By systematically studying the effect of different parameters, the importance of the chemical composition (mainly the carbon content) and the importance of the sintering cycle (particularly the cooling rate) are demonstrated. Moreover, various heat treatments studied illustrate the different microstructures achievable for this system, showing various amounts of cementite, pearlite and free graphite. Although the machinability is limited for samples containing large amounts of cementite, it can be greatly improved with very slow cooling, leading to graphitization of the carbon in presence of phosphorus. Adequate control of the sintering cycle on samples made from FGS1625 powder leads to the obtention of high density (≥7.0 g/cm 3) microstructures containing various amounts of pearlite, ferrite and free graphite. Obtaining ferritic microstructures with free graphite designed for very high machinability (tool wear <1.0%) or fine pearlitic microstructures with excellent mechanical properties (transverse rupture strength >1600 MPa) is therefore possible. These results show that improvement of machinability through higher densities is limited by microstructure. Indeed, for the studied samples, microstructure is dominant in the determination of machinability, far more important than density, judging by the influence of cementite or of the volume fraction of free graphite on machinability for example. (Abstract shortened by UMI.)

Clinical implementation of target tracking by breathing synchronized delivery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tewatia, Dinesh; Zhang Tiezhi; Tome, Wolfgang

2006-11-15

Target-tracking techniques can be categorized based on the mechanism of the feedback loop. In real time tracking, breathing-delivery phase correlation is provided to the treatment delivery hardware. Clinical implementation of target tracking in real time requires major hardware modifications. In breathing synchronized delivery (BSD), the patient is guided to breathe in accordance with target motion derived from four-dimensional computed tomography (4D-CT). Violations of mechanical limitations of hardware are to be avoided at the treatment planning stage. Hardware modifications are not required. In this article, using sliding window IMRT delivery as an example, we have described step-by-step the implementation of targetmore » tracking by the BSD technique: (1) A breathing guide is developed from patient's normal breathing pattern. The patient tries to reproduce this guiding cycle by following the display in the goggles; (2) 4D-CT scans are acquired at all the phases of the breathing cycle; (3) The average tumor trajectory is obtained by deformable image registration of 4D-CT datasets and is smoothed by Fourier filtering; (4) Conventional IMRT planning is performed using the images at reference phase (full exhalation phase) and a leaf sequence based on optimized fluence map is generated; (5) Assuming the patient breathes with a reproducible breathing pattern and the machine maintains a constant dose rate, the treatment process is correlated with the breathing phase; (6) The instantaneous average tumor displacement is overlaid on the dMLC position at corresponding phase; and (7) DMLC leaf speed and acceleration are evaluated to ensure treatment delivery. A custom-built mobile phantom driven by a computer-controlled stepper motor was used in the dosimetry verification. A stepper motor was programmed such that the phantom moved according to the linear component of tumor motion used in BSD treatment planning. A conventional plan was delivered on the phantom with and without motion. The BSD plan was also delivered on the phantom that moved with the prescheduled pattern and synchronized with the delivery of each beam. Film dosimetry showed underdose and overdose in the superior and inferior regions of the target, respectively, if the tumor motion is not compensated during the delivery. BSD delivery resulted in a dose distribution very similar to the planned treatments.« less

Optimization of Support Vector Machine (SVM) for Object Classification

NASA Technical Reports Server (NTRS)

Scholten, Matthew; Dhingra, Neil; Lu, Thomas T.; Chao, Tien-Hsin

2012-01-01

The Support Vector Machine (SVM) is a powerful algorithm, useful in classifying data into species. The SVMs implemented in this research were used as classifiers for the final stage in a Multistage Automatic Target Recognition (ATR) system. A single kernel SVM known as SVMlight, and a modified version known as a SVM with K-Means Clustering were used. These SVM algorithms were tested as classifiers under varying conditions. Image noise levels varied, and the orientation of the targets changed. The classifiers were then optimized to demonstrate their maximum potential as classifiers. Results demonstrate the reliability of SVM as a method for classification. From trial to trial, SVM produces consistent results.

Evaluation of Community-Based Policy, Systems, and Environment Interventions Targeting the Vending Machines.

PubMed

Garcia, Kristen M; Garney, Whitney R; Primm, Kristin M; McLeroy, Kenneth R

The American Heart Association conducted policy, systems, and environmental (PSE) focused interventions to increase healthy vending in 8 communities. PSE interventions were assessed using the Nutrition Environment Measures Survey Vending Assessment to see changes in the food environment. Baseline and follow-up assessments were conducted with 3 settings and a total of 19 machines. PSE changes resulted in increased availability of healthy options and decreased unhealthy options. Implementation of PSE interventions targeting the food environment can be an effective method of providing increased access to healthy foods and beverages with the goal of increasing consumption to decrease chronic diseases.

Ergonomic factors and production target evaluation in eucalyptus timber harvesting operations in mountainous terrains.

PubMed

de Souza, Amaury Paulo; Minette, Luciano José; Sanches, André Luis Petean; da Silva, Emília Pio; Rodrigues, Valéria Antônia Justino; de Oliveira, Luciana Aparecida

2012-01-01

There are several forest operations involved in Eucalyptus timber harvesting. This study was carried out during brush-cutting; tree felling, bucking, delimbing, piling and manual extraction operations, with the following objectives: a) analyzing, ergonomically, two systems of brush-cutting: one manual and the other semi-mechanized, using two different machines; b) ergonomically evaluating three different brands of pruner machines used in delimbing felled trees. c) determining the feasible target of productivity as a function of ergonomic factors relevant to establish the time of resting pauses for workers in manual and semi-mechanized timber harvesting systems in mountainous terrain. Brush-cutting, either manual or semimechanized, is an activity carried out prior to timber harvesting. It is usually a hard work, with low productivity when compared with mechanized systems. Pruner machines have been used by forest companies, due to the great possibilities to improve productivity, quality and the health of workers. Ergonomics is a discipline that promotes the adequacy of work to the physical and mental characteristics of human beings, seeking to design production systems and products considering relevant aspects, including social, organizational and environmental factors. Companies should consider the ergonomic factor in the determination of daily worker production targets.

More physics in the laundromat

NASA Astrophysics Data System (ADS)

Denny, Mark

2010-12-01

The physics of a washing machine spin cycle is extended to include the spin-up and spin-down phases. We show that, for realistic parameters, an adiabatic approximation applies, and thus the familiar forced, damped harmonic oscillator analysis can be applied to these phases.

Comparative analysis of machine learning methods in ligand-based virtual screening of large compound libraries.

PubMed

Ma, Xiao H; Jia, Jia; Zhu, Feng; Xue, Ying; Li, Ze R; Chen, Yu Z

2009-05-01

Machine learning methods have been explored as ligand-based virtual screening tools for facilitating drug lead discovery. These methods predict compounds of specific pharmacodynamic, pharmacokinetic or toxicological properties based on their structure-derived structural and physicochemical properties. Increasing attention has been directed at these methods because of their capability in predicting compounds of diverse structures and complex structure-activity relationships without requiring the knowledge of target 3D structure. This article reviews current progresses in using machine learning methods for virtual screening of pharmacodynamically active compounds from large compound libraries, and analyzes and compares the reported performances of machine learning tools with those of structure-based and other ligand-based (such as pharmacophore and clustering) virtual screening methods. The feasibility to improve the performance of machine learning methods in screening large libraries is discussed.

Synergistic target combination prediction from curated signaling networks: Machine learning meets systems biology and pharmacology.

PubMed

Chua, Huey Eng; Bhowmick, Sourav S; Tucker-Kellogg, Lisa

2017-10-01

Given a signaling network, the target combination prediction problem aims to predict efficacious and safe target combinations for combination therapy. State-of-the-art in silico methods use Monte Carlo simulated annealing (mcsa) to modify a candidate solution stochastically, and use the Metropolis criterion to accept or reject the proposed modifications. However, such stochastic modifications ignore the impact of the choice of targets and their activities on the combination's therapeutic effect and off-target effects, which directly affect the solution quality. In this paper, we present mascot, a method that addresses this limitation by leveraging two additional heuristic criteria to minimize off-target effects and achieve synergy for candidate modification. Specifically, off-target effects measure the unintended response of a signaling network to the target combination and is often associated with toxicity. Synergy occurs when a pair of targets exerts effects that are greater than the sum of their individual effects, and is generally a beneficial strategy for maximizing effect while minimizing toxicity. mascot leverages on a machine learning-based target prioritization method which prioritizes potential targets in a given disease-associated network to select more effective targets (better therapeutic effect and/or lower off-target effects); and on Loewe additivity theory from pharmacology which assesses the non-additive effects in a combination drug treatment to select synergistic target activities. Our experimental study on two disease-related signaling networks demonstrates the superiority of mascot in comparison to existing approaches. Copyright © 2017 Elsevier Inc. All rights reserved.

Cycle accurate and cycle reproducible memory for an FPGA based hardware accelerator

DOEpatents

Asaad, Sameh W.; Kapur, Mohit

2016-03-15

A method, system and computer program product are disclosed for using a Field Programmable Gate Array (FPGA) to simulate operations of a device under test (DUT). The DUT includes a device memory having a number of input ports, and the FPGA is associated with a target memory having a second number of input ports, the second number being less than the first number. In one embodiment, a given set of inputs is applied to the device memory at a frequency Fd and in a defined cycle of time, and the given set of inputs is applied to the target memory at a frequency Ft. Ft is greater than Fd and cycle accuracy is maintained between the device memory and the target memory. In an embodiment, a cycle accurate model of the DUT memory is created by separating the DUT memory interface protocol from the target memory storage array.

Towards the application of one-dimensional sonomyography for powered upper-limb prosthetic control using machine learning models.

PubMed

Guo, Jing-Yi; Zheng, Yong-Ping; Xie, Hong-Bo; Koo, Terry K

2013-02-01

The inherent properties of surface electromyography limit its potential for multi-degrees of freedom control. Our previous studies demonstrated that wrist angle could be predicted by muscle thickness measured from B-mode ultrasound, and hence, it could be an alternative signal for prosthetic control. However, an ultrasound imaging machine is too bulky and expensive. We aim to utilize a portable A-mode ultrasound system to examine the feasibility of using one-dimensional sonomyography (i.e. muscle thickness signals detected by A-mode ultrasound) to predict wrist angle with three different machine learning models - (1) support vector machine (SVM), (2) radial basis function artificial neural network (RBF ANN), and (3) back-propagation artificial neural network (BP ANN). Feasibility study using nine healthy subjects. Each subject performed wrist extension guided at 15, 22.5, and 30 cycles/minute, respectively. Data obtained from 22.5 cycles/minute trials was used to train the models and the remaining trials were used for cross-validation. Prediction accuracy was quantified by relative root mean square error (RMSE) and correlation coefficients (CC). Excellent prediction was noted using SVM (RMSE = 13%, CC = 0.975), which outperformed the other methods. It appears that one-dimensional sonomyography could be an alternative signal for prosthetic control. Clinical relevance Surface electromyography has inherent limitations that prohibit its full functional use for prosthetic control. Research that explores alternative signals to improve prosthetic control (such as the one-dimensional sonomyography signals evaluated in this study) may revolutionize powered prosthesis design and ultimately benefit amputee patients.

High-resolution Temporal Representations of Alcohol and Tobacco Behaviors from Social Media Data

PubMed Central

Huang, Tom; Elghafari, Anas; Relia, Kunal; Chunara, Rumi

2017-01-01

Understanding tobacco- and alcohol-related behavioral patterns is critical for uncovering risk factors and potentially designing targeted social computing intervention systems. Given that we make choices multiple times per day, hourly and daily patterns are critical for better understanding behaviors. Here, we combine natural language processing, machine learning and time series analyses to assess Twitter activity specifically related to alcohol and tobacco consumption and their sub-daily, daily and weekly cycles. Twitter self-reports of alcohol and tobacco use are compared to other data streams available at similar temporal resolution. We assess if discussion of drinking by inferred underage versus legal age people or discussion of use of different types of tobacco products can be differentiated using these temporal patterns. We find that time and frequency domain representations of behaviors on social media can provide meaningful and unique insights, and we discuss the types of behaviors for which the approach may be most useful. PMID:29264592

APOLLO: a quality assessment service for single and multiple protein models.

PubMed

Wang, Zheng; Eickholt, Jesse; Cheng, Jianlin

2011-06-15

We built a web server named APOLLO, which can evaluate the absolute global and local qualities of a single protein model using machine learning methods or the global and local qualities of a pool of models using a pair-wise comparison approach. Based on our evaluations on 107 CASP9 (Critical Assessment of Techniques for Protein Structure Prediction) targets, the predicted quality scores generated from our machine learning and pair-wise methods have an average per-target correlation of 0.671 and 0.917, respectively, with the true model quality scores. Based on our test on 92 CASP9 targets, our predicted absolute local qualities have an average difference of 2.60 Å with the actual distances to native structure. http://sysbio.rnet.missouri.edu/apollo/. Single and pair-wise global quality assessment software is also available at the site.

Homopolar machine for reversible energy storage and transfer systems

DOEpatents

Stillwagon, Roy E.

1978-01-01

A homopolar machine designed to operate as a generator and motor in reversibly storing and transferring energy between the machine and a magnetic load coil for a thermo-nuclear reactor. The machine rotor comprises hollow thin-walled cylinders or sleeves which form the basis of the system by utilizing substantially all of the rotor mass as a conductor thus making it possible to transfer substantially all the rotor kinetic energy electrically to the load coil in a highly economical and efficient manner. The rotor is divided into multiple separate cylinders or sleeves of modular design, connected in series and arranged to rotate in opposite directions but maintain the supply of current in a single direction to the machine terminals. A stator concentrically disposed around the sleeves consists of a hollow cylinder having a number of excitation coils each located radially outward from the ends of adjacent sleeves. Current collected at an end of each sleeve by sleeve slip rings and brushes is transferred through terminals to the magnetic load coil. Thereafter, electrical energy returned from the coil then flows through the machine which causes the sleeves to motor up to the desired speed in preparation for repetition of the cycle. To eliminate drag on the rotor between current pulses, the brush rigging is designed to lift brushes from all slip rings in the machine.

Homopolar machine for reversible energy storage and transfer systems

DOEpatents

Stillwagon, Roy E.

1981-01-01

A homopolar machine designed to operate as a generator and motor in reversibly storing and transferring energy between the machine and a magnetic load coil for a thermo-nuclear reactor. The machine rotor comprises hollow thin-walled cylinders or sleeves which form the basis of the system by utilizing substantially all of the rotor mass as a conductor thus making it possible to transfer substantially all the rotor kinetic energy electrically to the load coil in a highly economical and efficient manner. The rotor is divided into multiple separate cylinders or sleeves of modular design, connected in series and arranged to rotate in opposite directions but maintain the supply of current in a single direction to the machine terminals. A stator concentrically disposed around the sleeves consists of a hollow cylinder having a number of excitation coils each located radially outward from the ends of adjacent sleeves. Current collected at an end of each sleeve by sleeve slip rings and brushes is transferred through terminals to the magnetic load coil. Thereafter, electrical energy returned from the coil then flows through the machine which causes the sleeves to motor up to the desired speed in preparation for repetition of the cycle. To eliminate drag on the rotor between current pulses, the brush rigging is designed to lift brushes from all slip rings in the machine.

The effect of CPP-ACP on enamel wear under severe erosive conditions.

PubMed

Ranjitkar, Sarbin; Kaidonis, John A; Richards, Lindsay C; Townsend, Grant C

2009-06-01

In addition to its role as a remineralizing agent in preventing dental caries, recent evidence has shown that casein phosphopeptide-amorphous calcium phosphate (CPP-ACP) can protect teeth against erosion. The aim of this study was to determine whether CPP-ACP could reduce enamel wear rates under severe erosive conditions simulating heavy attrition and gastric regurgitation. Enamel specimens were subjected to 10,000 wear cycles at a load of 100 N and pH 1.2 in a tooth wear machine. The machine was stopped every 2 min (160 cycles), and CPP-ACP in the form of a paste was applied for 5 min in experimental group 1. A paste with the same formulation but without CPP-ACP was applied in experimental group 2. No paste was applied in the control group. A linear mixed model analysis indicated that the mean wear rates in experimental group 1 (0.44+/-0.05 mm(3) per 1000 cycles) and in experimental group 2 (0.63+/-0.06 mm(3) per 1000 cycles) were significantly lower than that in the control group (0.92+/-0.11 mm(3) per 1000 cycles) (p<0.05). The mean wear rate in experimental group 1 was also lower than that in experimental group 2 (p<0.05). Wear facets in experimental groups 1 and 2 were noted to be smoother and more polished than those in the control group. Both remineralizing and lubricating properties of the paste containing CPP-ACP appear to contribute to wear reduction in enamel. These findings may lead to new strategies for the clinical management of tooth wear.

Coordination of Myeloid Differentiation with Reduced Cell Cycle Progression by PU.1 Induction of MicroRNAs Targeting Cell Cycle Regulators and Lipid Anabolism.

PubMed

Solomon, Lauren A; Podder, Shreya; He, Jessica; Jackson-Chornenki, Nicholas L; Gibson, Kristen; Ziliotto, Rachel G; Rhee, Jess; DeKoter, Rodney P

2017-05-15

During macrophage development, myeloid progenitor cells undergo terminal differentiation coordinated with reduced cell cycle progression. Differentiation of macrophages from myeloid progenitors is accompanied by increased expression of the E26 transformation-specific transcription factor PU.1. Reduced PU.1 expression leads to increased proliferation and impaired differentiation of myeloid progenitor cells. It is not understood how PU.1 coordinates macrophage differentiation with reduced cell cycle progression. In this study, we utilized cultured PU.1-inducible myeloid cells to perform genome-wide chromatin immunoprecipitation sequencing (ChIP-seq) analysis coupled with gene expression analysis to determine targets of PU.1 that may be involved in regulating cell cycle progression. We found that genes encoding cell cycle regulators and enzymes involved in lipid anabolism were directly and inducibly bound by PU.1 although their steady-state mRNA transcript levels were reduced. Inhibition of lipid anabolism was sufficient to reduce cell cycle progression in these cells. Induction of PU.1 reduced expression of E2f1 , an important activator of genes involved in cell cycle and lipid anabolism, indirectly through microRNA 223. Next-generation sequencing identified microRNAs validated as targeting cell cycle and lipid anabolism for downregulation. These results suggest that PU.1 coordinates cell cycle progression with differentiation through induction of microRNAs targeting cell cycle regulators and lipid anabolism. Copyright © 2017 American Society for Microbiology.

New support vector machine-based method for microRNA target prediction.

PubMed

Li, L; Gao, Q; Mao, X; Cao, Y

2014-06-09

MicroRNA (miRNA) plays important roles in cell differentiation, proliferation, growth, mobility, and apoptosis. An accurate list of precise target genes is necessary in order to fully understand the importance of miRNAs in animal development and disease. Several computational methods have been proposed for miRNA target-gene identification. However, these methods still have limitations with respect to their sensitivity and accuracy. Thus, we developed a new miRNA target-prediction method based on the support vector machine (SVM) model. The model supplies information of two binding sites (primary and secondary) for a radial basis function kernel as a similarity measure for SVM features. The information is categorized based on structural, thermodynamic, and sequence conservation. Using high-confidence datasets selected from public miRNA target databases, we obtained a human miRNA target SVM classifier model with high performance and provided an efficient tool for human miRNA target gene identification. Experiments have shown that our method is a reliable tool for miRNA target-gene prediction, and a successful application of an SVM classifier. Compared with other methods, the method proposed here improves the sensitivity and accuracy of miRNA prediction. Its performance can be further improved by providing more training examples.

Compound Structure-Independent Activity Prediction in High-Dimensional Target Space.

PubMed

Balfer, Jenny; Hu, Ye; Bajorath, Jürgen

2014-08-01

Profiling of compound libraries against arrays of targets has become an important approach in pharmaceutical research. The prediction of multi-target compound activities also represents an attractive task for machine learning with potential for drug discovery applications. Herein, we have explored activity prediction in high-dimensional target space. Different types of models were derived to predict multi-target activities. The models included naïve Bayesian (NB) and support vector machine (SVM) classifiers based upon compound structure information and NB models derived on the basis of activity profiles, without considering compound structure. Because the latter approach can be applied to incomplete training data and principally depends on the feature independence assumption, SVM modeling was not applicable in this case. Furthermore, iterative hybrid NB models making use of both activity profiles and compound structure information were built. In high-dimensional target space, NB models utilizing activity profile data were found to yield more accurate activity predictions than structure-based NB and SVM models or hybrid models. An in-depth analysis of activity profile-based models revealed the presence of correlation effects across different targets and rationalized prediction accuracy. Taken together, the results indicate that activity profile information can be effectively used to predict the activity of test compounds against novel targets. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Accelerator Production of Isotopes for Medical Use

NASA Astrophysics Data System (ADS)

Lapi, Suzanne

2014-03-01

The increase in use of radioisotopes for medical imaging and therapy has led to the development of novel routes of isotope production. For example, the production and purification of longer-lived position emitting radiometals has been explored to allow for nuclear imaging agents based on peptides, antibodies and nanoparticles. These isotopes (64Cu, 89Zr, 86Y) are typically produced via irradiation of solid targets on smaller medical cyclotrons at dedicated facilities. Recently, isotope harvesting from heavy ion accelerator facilities has also been suggested. The Facility for Rare Isotope Beams (FRIB) will be a new national user facility for nuclear science to be completed in 2020. Radioisotopes could be produced by dedicated runs by primary users or may be collected synergistically from the water in cooling-loops for the primary beam dump that cycle the water at flow rates in excess of hundreds of gallons per minute. A liquid water target system for harvesting radioisotopes at the National Superconducting Cyclotron Laboratory (NSCL) was designed and constructed as the initial step in proof-of-principle experiments to harvest useful radioisotopes in this manner. This talk will provide an overview of isotope production using both dedicated machines and harvesting from larger accelerators typically used for nuclear physics. Funding from Department of Energy under DESC0007352 and DESC0006862.

Weldability, machinability and surfacing of commercial duplex stainless steel AISI2205 for marine applications - A recent review.

PubMed

Vinoth Jebaraj, A; Ajaykumar, L; Deepak, C R; Aditya, K V V

2017-05-01

In the present review, attempts have been made to analyze the metallurgical, mechanical, and corrosion properties of commercial marine alloy duplex stainless steel AISI 2205 with special reference to its weldability, machinability, and surfacing. In the first part, effects of various fusion and solid-state welding processes on joining DSS 2205 with similar and dissimilar metals are addressed. Microstructural changes during the weld cooling cycle such as austenite reformation, partitioning of alloying elements, HAZ transformations, and the intermetallic precipitations are analyzed and compared with the different welding techniques. In the second part, machinability of DSS 2205 is compared with the commercial ASS grades in order to justify the quality of machining. In the third part, the importance of surface quality in a marine exposure is emphasized and the enhancement of surface properties through peening techniques is highlighted. The research gaps and inferences highlighted in this review will be more useful for the fabrications involved in the marine applications.

Accurate Micro-Tool Manufacturing by Iterative Pulsed-Laser Ablation

NASA Astrophysics Data System (ADS)

Warhanek, Maximilian; Mayr, Josef; Dörig, Christian; Wegener, Konrad

2017-12-01

Iterative processing solutions, including multiple cycles of material removal and measurement, are capable of achieving higher geometric accuracy by compensating for most deviations manifesting directly on the workpiece. Remaining error sources are the measurement uncertainty and the repeatability of the material-removal process including clamping errors. Due to the lack of processing forces, process fluids and wear, pulsed-laser ablation has proven high repeatability and can be realized directly on a measuring machine. This work takes advantage of this possibility by implementing an iterative, laser-based correction process for profile deviations registered directly on an optical measurement machine. This way efficient iterative processing is enabled, which is precise, applicable for all tool materials including diamond and eliminates clamping errors. The concept is proven by a prototypical implementation on an industrial tool measurement machine and a nanosecond fibre laser. A number of measurements are performed on both the machine and the processed workpieces. Results show production deviations within 2 μm diameter tolerance.

Space Shuttle ET Friction Stir Weld Machines

NASA Technical Reports Server (NTRS)

Thompson, Jack M.

2003-01-01

NASA and Lockheed-Martin approached the FSW machine vendor community with a specification for longitudinal barrel production FSW weld machines and a shorter travel process development machine in June of 2000. This specification was based on three years of FSW process development on the Space Shuttle External Tank alloys, AL2 195-T8M4 and AL22 19-T87. The primary motivations for changing the ET longitudinal welds from the existing variable polarity Plasma Arc plasma weld process included: (1) Significantly reduced weld defect rates and related reduction in cycle time and uncertainty; (2) Many fewer process variables to control (5 vs. 17); (3) Fewer manufacturing steps; (4) Lower residual stresses and distortion; (5) Improved weld strengths, particularly at cryogenic temperatures; (6) Fewer hazards to production personnel. General Tool was the successful bidder. The equipment is at this writing installed and welding flight hardware. This paper is a means of sharing with the rest of the FSW community the unique features developed to assure NASA/L-M of successful production welds.

Norovirus Illness: Key Facts

MedlinePlus

... should— • handle soiled items carefully without agitating them, • wear rubber or disposable gloves while handling soiled items and wash your hands after, and wash the items with detergent at the maximum available cycle length then machine dry them. Visit CDC’s Norovirus Web site at ...

Trickle water and feeding system in plant culture and light-dark cycle effects on plant growth

NASA Technical Reports Server (NTRS)

Takano, T.; Inada, K.; Takanashi, J.

1987-01-01

Rockwool, as an inert medium covered or bagged with polyethylene film, can be effectively used for plant culture in space stations. The most important machine is the pump adjusting the dripping rate in the feeding system. Hydro-aeroponics may be adaptable to a space laboratory. The shortening of the light-dark cycles inhibits plant growth and induces an abnormal morphogenesis. A photoperiod of 12 hr dark may be needed for plant growth.

Side-welded fast response sheathed thermocouple

DOEpatents

Carr, K.R.

A method of fabricating the measuring junction of a grounded-junction sheathed thermocouple to obtain fast time response and good thermal cycling performance is provided. Slots are tooled or machined into the sheath wall at the measuring junction, the thermocouple wires are laser-welded into the slots. A thin metal closure cap is then laser-welded over the end of the sheath. Compared to a conventional grounded-junction thermocouple, the response time is 4 to 5 times faster and the thermal shock and cycling capabilities are substantially improved.

Method of calculating gas dynamics and heat transfer in single stage refrigeration units

NASA Technical Reports Server (NTRS)

Zhitomirskiy, I. S.; Popolskiy, A. B.

1974-01-01

A generalized mathematical model of gas-dynamic and heat transfer processes in single-stage regenerative installations operating in Stirling, MacMahon, Gifford-MacMahon, and pulsating tube cycles is proposed. A numerical method os solving initial equations on a digital computer is given. This makes it possible to calculate the change in the thermodynamic parameters in the working cycle in different machine components, as well as the dependence of cold productivity on the temperature level in the steady regime.

Side-welded fast response sheathed thermocouple

DOEpatents

Carr, Kenneth R.

1981-01-01

A method of fabricating the measuring junction of a grounded-junction sheathed thermocouple to obtain fast time response and good thermal cycling performance is provided. Slots are tooled or machined into the sheath wall at the measuring junction, the thermocouple wires are laser-welded into the slots. A thin metal closure cap is then laser-welded over the end of the sheath. Compared to a conventional grounded-junction thermocouple, the response time is 4-5 times faster and the thermal shock and cycling capabilities are substantially improved.

A new class of high-G and long-duration shock testing machines

NASA Astrophysics Data System (ADS)

Rastegar, Jahangir

2018-03-01

Currently available methods and systems for testing components for survival and performance under shock loading suffer from several shortcomings for use to simulate high-G acceleration events with relatively long duration. Such events include most munitions firing and target impact, vehicular accidents, drops from relatively high heights, air drops, impact between machine components, and other similar events. In this paper, a new class of shock testing machines are presented that can be used to subject components to be tested to high-G acceleration pulses of prescribed amplitudes and relatively long durations. The machines provide for highly repeatable testing of components. The components are mounted on an open platform for ease of instrumentation and video recording of their dynamic behavior during shock loading tests.

Performance study of a data flow architecture

NASA Technical Reports Server (NTRS)

Adams, George

1985-01-01

Teams of scientists studied data flow concepts, static data flow machine architecture, and the VAL language. Each team mapped its application onto the machine and coded it in VAL. The principal findings of the study were: (1) Five of the seven applications used the full power of the target machine. The galactic simulation and multigrid fluid flow teams found that a significantly smaller version of the machine (16 processing elements) would suffice. (2) A number of machine design parameters including processing element (PE) function unit numbers, array memory size and bandwidth, and routing network capability were found to be crucial for optimal machine performance. (3) The study participants readily acquired VAL programming skills. (4) Participants learned that application-based performance evaluation is a sound method of evaluating new computer architectures, even those that are not fully specified. During the course of the study, participants developed models for using computers to solve numerical problems and for evaluating new architectures. These models form the bases for future evaluation studies.

Active machine learning-driven experimentation to determine compound effects on protein patterns

PubMed Central

Naik, Armaghan W; Kangas, Joshua D; Sullivan, Devin P; Murphy, Robert F

2016-01-01

High throughput screening determines the effects of many conditions on a given biological target. Currently, to estimate the effects of those conditions on other targets requires either strong modeling assumptions (e.g. similarities among targets) or separate screens. Ideally, data-driven experimentation could be used to learn accurate models for many conditions and targets without doing all possible experiments. We have previously described an active machine learning algorithm that can iteratively choose small sets of experiments to learn models of multiple effects. We now show that, with no prior knowledge and with liquid handling robotics and automated microscopy under its control, this learner accurately learned the effects of 48 chemical compounds on the subcellular localization of 48 proteins while performing only 29% of all possible experiments. The results represent the first practical demonstration of the utility of active learning-driven biological experimentation in which the set of possible phenotypes is unknown in advance. DOI: http://dx.doi.org/10.7554/eLife.10047.001 PMID:26840049

Drosophila CLOCK target gene characterization: implications for circadian tissue-specific gene expression

PubMed Central

Abruzzi, Katharine Compton; Rodriguez, Joseph; Menet, Jerome S.; Desrochers, Jennifer; Zadina, Abigail; Luo, Weifei; Tkachev, Sasha; Rosbash, Michael

2011-01-01

CLOCK (CLK) is a master transcriptional regulator of the circadian clock in Drosophila. To identify CLK direct target genes and address circadian transcriptional regulation in Drosophila, we performed chromatin immunoprecipitation (ChIP) tiling array assays (ChIP–chip) with a number of circadian proteins. CLK binding cycles on at least 800 sites with maximal binding in the early night. The CLK partner protein CYCLE (CYC) is on most of these sites. The CLK/CYC heterodimer is joined 4–6 h later by the transcriptional repressor PERIOD (PER), indicating that the majority of CLK targets are regulated similarly to core circadian genes. About 30% of target genes also show cycling RNA polymerase II (Pol II) binding. Many of these generate cycling RNAs despite not being documented in prior RNA cycling studies. This is due in part to different RNA isoforms and to fly head tissue heterogeneity. CLK has specific targets in different tissues, implying that important CLK partner proteins and/or mechanisms contribute to gene-specific and tissue-specific regulation. PMID:22085964

Designing a connectionist network supercomputer.

PubMed

Asanović, K; Beck, J; Feldman, J; Morgan, N; Wawrzynek, J

1993-12-01

This paper describes an effort at UC Berkeley and the International Computer Science Institute to develop a supercomputer for artificial neural network applications. Our perspective has been strongly influenced by earlier experiences with the construction and use of a simpler machine. In particular, we have observed Amdahl's Law in action in our designs and those of others. These observations inspire attention to many factors beyond fast multiply-accumulate arithmetic. We describe a number of these factors along with rough expressions for their influence and then give the applications targets, machine goals and the system architecture for the machine we are currently designing.

Development of a Physical Employment Testing Battery for Armor Soldiers: 19D Cavalry Scout and 19K M1 Armor Crewman

DTIC Science & Technology

2015-12-01

M2 .50 Caliber Machine Gun on the Abrams Tank While wearing a task specific uniform weighing approximately 49 lb, Soldiers lifted the M2 .50...12 Engage Targets with a Caliber .50 M2 Machine Gun X 13 Lay a 120mm Mortar – Emplace Base Plate X 14 Lay a 120mm Mortar...17 Mount M2 .50 Cal Machine Gun Receiver on an Abrams Tank X 18 Stow Ammunition on an Abrams Tank (Load 120mm MPAT Round to the Ready Rack

Development of a Physical Employment Testing Battery for Infantry Soldiers: 11B Infantryman and 11C Infantryman-Indirect Fire

DTIC Science & Technology

2015-12-01

43 1.9 Images of Move Under Direct Fire (Task 10) 44 1.10 Engage Targets with a .50 Caliber M2 Machine Gun (Task 12) 45 1.11 Image of Lay a...Caliber M2 Machine Gun While wearing a fighting load (approximately 83 lb) and working as a member of a two-person team, Soldiers lifted and carried the... M2 HB Machine Gun with tripod (153 lb) a distance of 10 m. Army Standard: Successful completion of the task 13. Emplace Base Plate (11C

LHC Status and Upgrade Challenges

NASA Astrophysics Data System (ADS)

Smith, Jeffrey

2009-11-01

The Large Hadron Collider has had a trying start-up and a challenging operational future lays ahead. Critical to the machine's performance is controlling a beam of particles whose stored energy is equivalent to 80 kg of TNT. Unavoidable beam losses result in energy deposition throughout the machine and without adequate protection this power would result in quenching of the superconducting magnets. A brief overview of the machine layout and principles of operation will be reviewed including a summary of the September 2008 accident. The current status of the LHC, startup schedule and upgrade options to achieve the target luminosity will be presented.

Prediction of microRNA target genes using an efficient genetic algorithm-based decision tree.

PubMed

Rabiee-Ghahfarrokhi, Behzad; Rafiei, Fariba; Niknafs, Ali Akbar; Zamani, Behzad

2015-01-01

MicroRNAs (miRNAs) are small, non-coding RNA molecules that regulate gene expression in almost all plants and animals. They play an important role in key processes, such as proliferation, apoptosis, and pathogen-host interactions. Nevertheless, the mechanisms by which miRNAs act are not fully understood. The first step toward unraveling the function of a particular miRNA is the identification of its direct targets. This step has shown to be quite challenging in animals primarily because of incomplete complementarities between miRNA and target mRNAs. In recent years, the use of machine-learning techniques has greatly increased the prediction of miRNA targets, avoiding the need for costly and time-consuming experiments to achieve miRNA targets experimentally. Among the most important machine-learning algorithms are decision trees, which classify data based on extracted rules. In the present work, we used a genetic algorithm in combination with C4.5 decision tree for prediction of miRNA targets. We applied our proposed method to a validated human datasets. We nearly achieved 93.9% accuracy of classification, which could be related to the selection of best rules.

Influence of micromachined targets on laser accelerated proton beam profiles

NASA Astrophysics Data System (ADS)

Dalui, Malay; Permogorov, Alexander; Pahl, Hannes; Persson, Anders; Wahlström, Claes-Göran

2018-03-01

High intensity laser-driven proton acceleration from micromachined targets is studied experimentally in the target-normal-sheath-acceleration regime. Conical pits are created on the front surface of flat aluminium foils of initial thickness 12.5 and 3 μm using series of low energy pulses (0.5-2.5 μJ). Proton acceleration from such micromachined targets is compared with flat foils of equivalent thickness at a laser intensity of 7 × 1019 W cm-2. The maximum proton energy obtained from targets machined from 12.5 μm thick foils is found to be slightly lower than that of flat foils of equivalent remaining thickness, and the angular divergence of the proton beam is observed to increase as the depth of the pit approaches the foil thickness. Targets machined from 3 μm thick foils, on the other hand, show evidence of increasing the maximum proton energy when the depths of the structures are small. Furthermore, shallow pits on 3 μm thick foils are found to be efficient in reducing the proton beam divergence by a factor of up to three compared to that obtained from flat foils, while maintaining the maximum proton energy.

A comparison of machine learning techniques for detection of drug target articles.

PubMed

Danger, Roxana; Segura-Bedmar, Isabel; Martínez, Paloma; Rosso, Paolo

2010-12-01

Important progress in treating diseases has been possible thanks to the identification of drug targets. Drug targets are the molecular structures whose abnormal activity, associated to a disease, can be modified by drugs, improving the health of patients. Pharmaceutical industry needs to give priority to their identification and validation in order to reduce the long and costly drug development times. In the last two decades, our knowledge about drugs, their mechanisms of action and drug targets has rapidly increased. Nevertheless, most of this knowledge is hidden in millions of medical articles and textbooks. Extracting knowledge from this large amount of unstructured information is a laborious job, even for human experts. Drug target articles identification, a crucial first step toward the automatic extraction of information from texts, constitutes the aim of this paper. A comparison of several machine learning techniques has been performed in order to obtain a satisfactory classifier for detecting drug target articles using semantic information from biomedical resources such as the Unified Medical Language System. The best result has been achieved by a Fuzzy Lattice Reasoning classifier, which reaches 98% of ROC area measure. Copyright © 2010 Elsevier Inc. All rights reserved.

Prediction of microRNA target genes using an efficient genetic algorithm-based decision tree

PubMed Central

Rabiee-Ghahfarrokhi, Behzad; Rafiei, Fariba; Niknafs, Ali Akbar; Zamani, Behzad

2015-01-01

MicroRNAs (miRNAs) are small, non-coding RNA molecules that regulate gene expression in almost all plants and animals. They play an important role in key processes, such as proliferation, apoptosis, and pathogen–host interactions. Nevertheless, the mechanisms by which miRNAs act are not fully understood. The first step toward unraveling the function of a particular miRNA is the identification of its direct targets. This step has shown to be quite challenging in animals primarily because of incomplete complementarities between miRNA and target mRNAs. In recent years, the use of machine-learning techniques has greatly increased the prediction of miRNA targets, avoiding the need for costly and time-consuming experiments to achieve miRNA targets experimentally. Among the most important machine-learning algorithms are decision trees, which classify data based on extracted rules. In the present work, we used a genetic algorithm in combination with C4.5 decision tree for prediction of miRNA targets. We applied our proposed method to a validated human datasets. We nearly achieved 93.9% accuracy of classification, which could be related to the selection of best rules. PMID:26649272

Engineered Surface Properties of Porous Tungsten from Cryogenic Machining

NASA Astrophysics Data System (ADS)

Schoop, Julius Malte

Porous tungsten is used to manufacture dispenser cathodes due to it refractory properties. Surface porosity is critical to functional performance of dispenser cathodes because it allows for an impregnated ceramic compound to migrate to the emitting surface, lowering its work function. Likewise, surface roughness is important because it is necessary to ensure uniform wetting of the molten impregnate during high temperature service. Current industry practice to achieve surface roughness and surface porosity requirements involves the use of a plastic infiltrant during machining. After machining, the infiltrant is baked and the cathode pellet is impregnated. In this context, cryogenic machining is investigated as a substitutionary process for the current plastic infiltration process. Along with significant reductions in cycle time and resource use, surface quality of cryogenically machined un-infiltrated (as-sintered) porous tungsten has been shown to significantly outperform dry machining. The present study is focused on examining the relationship between machining parameters and cooling condition on the as-machined surface integrity of porous tungsten. The effects of cryogenic pre-cooling, rake angle, cutting speed, depth of cut and feed are all taken into consideration with respect to machining-induced surface morphology. Cermet and Polycrystalline diamond (PCD) cutting tools are used to develop high performance cryogenic machining of porous tungsten. Dry and pre-heated machining were investigated as a means to allow for ductile mode machining, yet severe tool-wear and undesirable smearing limited the feasibility of these approaches. By using modified PCD cutting tools, high speed machining of porous tungsten at cutting speeds up to 400 m/min is achieved for the first time. Beyond a critical speed, brittle fracture and built-up edge are eliminated as the result of a brittle to ductile transition. A model of critical chip thickness ( hc ) effects based on cutting force, temperature and surface roughness data is developed and used to study the deformation mechanisms of porous tungsten under different machining conditions. It is found that when hmax = hc, ductile mode machining of otherwise highly brittle porous tungsten is possible. The value of hc is approximately the same as the average ligament size of the 80% density porous tungsten workpiece.

The Slow Cycling Phenotype: A Growing Problem for Treatment Resistance in Melanoma.

PubMed

Ahn, Antonio; Chatterjee, Aniruddha; Eccles, Michael R

2017-06-01

Treatment resistance in metastatic melanoma is a longstanding issue. Current targeted therapy regimes in melanoma largely target the proliferating cancer population, leaving slow-cycling cancer cells undamaged. Consequently, slow-cycling cells are enriched upon drug therapy and can remain in the body for years until acquiring proliferative potential that triggers cancer relapse. Here we overview the molecular mechanisms of slow-cycling cells that underlie treatment resistance in melanoma. Three main areas of molecular reprogramming are discussed that mediate slow cycling and treatment resistance. First, a low microphthalmia-associated transcription factor (MITF) dedifferentiated state activates various signaling pathways. This includes WNT5A, EGFR, as well as other signaling activators, such as AXL and NF-κB. Second, the chromatin-remodeling factor Jumonji/ARID domain-containing protein 1B (JARID1B, KDM5B ) orchestrates and maintains slow cycling and treatment resistance in a small subpopulation of melanoma cells. Finally, a shift in metabolic state toward oxidative phosphorylation has been demonstrated to regulate treatment resistance in slow-cycling cells. Elucidation of the underlying processes of slow cycling and its utilization by melanoma cells may reveal new vulnerable characteristics as therapeutic targets. Moreover, combining current therapies with targeting slow-cycling subpopulations of melanoma cells may allow for more durable and greater treatment responses. Mol Cancer Ther; 16(6); 1002-9. ©2017 AACR . ©2017 American Association for Cancer Research.

Closeout of CRADA JSA 2012S004: Chapter 5, Integrated Control System, of the document of the ESS Conceptual Design Report, publicly available at https://europeanspallationsource.se/accelerator-documents

DOE Office of Scientific and Technical Information (OSTI.GOV)

Satogata, Todd

2013-04-22

The integrated control system (ICS) is responsible for the whole ESS machine and facility: accelerator, target, neutron scattering instruments and conventional facilities. This unified approach keeps the costs of development, maintenance and support relatively low. ESS has selected a standardised, field-proven controls framework, the Experimental Physics and Industrial Control System (EPICS), which was originally developed jointly by Argonne and Los Alamos National Laboratories. Complementing this selection are best practices and experience from similar facilities regarding platform standardisation, control system development and device integration and commissioning. The components of ICS include the control system core, the control boxes, the BLED databasemore » management system, and the human machine interface. The control system core is a set of systems and tools that make it possible for the control system to provide required data, information and services to engineers, operators, physicists and the facility itself. The core components are the timing system that makes possible clock synchronisation across the facility, the machine protection system (MPS) and the personnel protection system (PPS) that prevent damage to the machine and personnel, and a set of control system services. Control boxes are servers that control a collection of equipment (for example a radio frequency cavity). The integrated control system will include many control boxes that can be assigned to one supplier, such as an internal team, a collaborating institute or a commercial vendor. This approach facilitates a clear division of responsibilities and makes integration much easier. A control box is composed of a standardised hardware platform, components, development tools and services. On the top level, it interfaces with the core control system components (timing, MPS, PPS) and with the human-machine interface. At the bottom, it interfaces with the equipment and parts of the facility through a set of analog and digital signals, real-time control loops and other communication buses. The ICS central data management system is named BLED (beam line element databases). BLED is a set of databases, tools and services that is used to store, manage and access data. It holds vital control system configuration and physics-related (lattice) information about the accelerator, target and instruments. It facilitates control system configuration by bringing together direct input-output controller (IOC) con guration and real-time data from proton and neutron beam line models. BLED also simplifies development and speeds up the code-test-debug cycle. The set of tools that access BLED will be tailored to the needs of different categories of users, such as ESS staff physicists, engineers, and operators; external partner laboratories; and visiting experimental instrument users. The human-machine interface is vital to providing a high-quality experience to ICS users. It encompasses a wide array of devices and software tools, from control room screens to engineer terminal windows; from beam physics data tools to post-mortem data analysis tools. It serves users with a wide range of skills from widely varied backgrounds. The Controls Group is developing a set of user profiles to accommodate this diverse range of use-cases and users.« less

Process Development and Micro-Machining of MARBLE Foam-Cored Rexolite Hemi-Shell Ablator Capsules

DOE PAGES

Randolph, Randall Blaine; Oertel, John A.; Schmidt, Derek William; ...

2016-06-30

For this study, machined CH hemi-shell ablator capsules have been successfully produced by the MST-7 Target Fabrication Team at Los Alamos National Laboratory. Process development and micro-machining techniques have been developed to produce capsules for both the Omega and National Ignition Facility (NIF) campaigns. These capsules are gas filled up to 10 atm and consist of a machined plastic hemi-shell outer layer that accommodates various specially engineered low-density polystyrene foam cores. Machining and assembly of the two-part, step-jointed plastic hemi-shell outer layer required development of new techniques, processes, and tooling while still meeting very aggressive shot schedules for both campaigns.more » Finally, problems encountered and process improvements will be discussed that describe this very unique, complex capsule design approach through the first Omega proof-of-concept version to the larger NIF version.« less

Combining Machine Learning Systems and Multiple Docking Simulation Packages to Improve Docking Prediction Reliability for Network Pharmacology

PubMed Central

Hsin, Kun-Yi; Ghosh, Samik; Kitano, Hiroaki

2013-01-01

Increased availability of bioinformatics resources is creating opportunities for the application of network pharmacology to predict drug effects and toxicity resulting from multi-target interactions. Here we present a high-precision computational prediction approach that combines two elaborately built machine learning systems and multiple molecular docking tools to assess binding potentials of a test compound against proteins involved in a complex molecular network. One of the two machine learning systems is a re-scoring function to evaluate binding modes generated by docking tools. The second is a binding mode selection function to identify the most predictive binding mode. Results from a series of benchmark validations and a case study show that this approach surpasses the prediction reliability of other techniques and that it also identifies either primary or off-targets of kinase inhibitors. Integrating this approach with molecular network maps makes it possible to address drug safety issues by comprehensively investigating network-dependent effects of a drug or drug candidate. PMID:24391846

Development of machine learning models to predict inhibition of 3-dehydroquinate dehydratase.

PubMed

de Ávila, Maurício Boff; de Azevedo, Walter Filgueira

2018-04-20

In this study, we describe the development of new machine learning models to predict inhibition of the enzyme 3-dehydroquinate dehydratase (DHQD). This enzyme is the third step of the shikimate pathway and is responsible for the synthesis of chorismate, which is a natural precursor of aromatic amino acids. The enzymes of shikimate pathway are absent in humans, which make them protein targets for the design of antimicrobial drugs. We focus our study on the crystallographic structures of DHQD in complex with competitive inhibitors, for which experimental inhibition constant data is available. Application of supervised machine learning techniques was able to elaborate a robust DHQD-targeted model to predict binding affinity. Combination of high-resolution crystallographic structures and binding information indicates that the prevalence of intermolecular electrostatic interactions between DHQD and competitive inhibitors is of pivotal importance for the binding affinity against this enzyme. The present findings can be used to speed up virtual screening studies focused on the DHQD structure. © 2018 John Wiley & Sons A/S.

Predicting knee replacement damage in a simulator machine using a computational model with a consistent wear factor.

PubMed

Zhao, Dong; Sakoda, Hideyuki; Sawyer, W Gregory; Banks, Scott A; Fregly, Benjamin J

2008-02-01

Wear of ultrahigh molecular weight polyethylene remains a primary factor limiting the longevity of total knee replacements (TKRs). However, wear testing on a simulator machine is time consuming and expensive, making it impractical for iterative design purposes. The objectives of this paper were first, to evaluate whether a computational model using a wear factor consistent with the TKR material pair can predict accurate TKR damage measured in a simulator machine, and second, to investigate how choice of surface evolution method (fixed or variable step) and material model (linear or nonlinear) affect the prediction. An iterative computational damage model was constructed for a commercial knee implant in an AMTI simulator machine. The damage model combined a dynamic contact model with a surface evolution model to predict how wear plus creep progressively alter tibial insert geometry over multiple simulations. The computational framework was validated by predicting wear in a cylinder-on-plate system for which an analytical solution was derived. The implant damage model was evaluated for 5 million cycles of simulated gait using damage measurements made on the same implant in an AMTI machine. Using a pin-on-plate wear factor for the same material pair as the implant, the model predicted tibial insert wear volume to within 2% error and damage depths and areas to within 18% and 10% error, respectively. Choice of material model had little influence, while inclusion of surface evolution affected damage depth and area but not wear volume predictions. Surface evolution method was important only during the initial cycles, where variable step was needed to capture rapid geometry changes due to the creep. Overall, our results indicate that accurate TKR damage predictions can be made with a computational model using a constant wear factor obtained from pin-on-plate tests for the same material pair, and furthermore, that surface evolution method matters only during the initial "break in" period of the simulation.

Influence of the loading frequency on the wear rate of a polyethylene-on-metal lumbar intervertebral disc replacement.

PubMed

Kettler, Annette; Bushelow, Michael; Wilke, Hans-Joachim

2012-06-01

Pre-clinical wear testing of intervertebral disc prostheses is commonly carried out according to ISO 18192-1. Ten million multiaxial loading cycles are applied at a frequency of 1 Hz. At this frequency, testing takes about 4 months. Testing at higher frequencies would therefore be desirable. ISO 18192-1 also offers testing at 2 Hz; however, it says the impact on the implant material behaviour as well as on the accuracy of the test machine shall be investigated by the user. Since such data are not available so far, the aim of this study was to carry out comparative wear tests at 1 and 2 Hz. Seven Prodisc-L lumbar disc prostheses were tested. After a pre-soak period, the implants were placed in specimen cups filled with calf serum, mounted to a Spine Wear Simulator and loaded according to ISO 18192-1. Testing was carried out at a temperature of 37 ± 2 °C. Four million loading cycles were applied at 1 Hz and eight million at 2 Hz in an alternating sequence. Each time after 12 days of testing the implants were removed to measure the weight and the height of the polyethylene cores. Then, the test serum was exchanged and the implants were remounted to the testing machine. The mean wear rate was 5.6 ± 2.3 mg per million cycles at 1 Hz and 7.7 ± 1.6 mg per million cycles at 2 Hz during the first six million loading cycles (p < 0.05) and 2.0 ± 0.6 and 4.1 ± 0.7 mg per million cycles during the second six million cycles (p < 0.05). Similarly, the mean heightloss was also smaller at 1 Hz than at 2 Hz (p < 0.05) with -0.02 ± 0.02 mm versus -0.04 ± 0.02 mm per million cycles during the first half of testing and -0.01 ± 0.01 versus -0.02 ± 0.01 mm per million cycles during the second half. The accuracy of the test machine was within the limits described by ISO 18192-1 at both frequencies. The results showed that the wear rate was higher at the beginning than at the end of testing. Also, the results indicated that testing at 2 Hz increases the wear rate compared with 1 Hz in case of a polyethylene-on-metal implant design. In the absence of retrieval studies it is difficult to decide which rate results in a more physiological wear pattern. However, a loading frequency of 1 Hz is probably closer to physiology than 2 Hz since the loading amplitudes prescribed by ISO 18192-1 are high. They rather represent movements like tying shoes or standing up from a chair than walking or sitting. The authors therefore suggest testing at 1 Hz.

On the Road

ERIC Educational Resources Information Center

Collins, Mary Ellen

2012-01-01

Veteran development officers say the experience of visiting and traveling to different places or countries often feels like an endless cycle of getting lost, missing flights, and eating midnight dinners from hotel vending machines. Despite ongoing travel challenges, experienced road warriors have learned how to maximize their effectiveness,…

Low cost, SPF aluminum cryogenic tank structure for ALS

NASA Technical Reports Server (NTRS)

Anton, Claire E.; Rasmussen, Perry; Thompson, Curt; Latham, Richard; Hamilton, C. Howard; Ren, Ben; Gandhi, Chimata; Hardwick, Dallis

1992-01-01

Past production work has shown that cryogenic tank structure for the Shuttle Booster Rockets and the Titan system have very high life cycle costs for the fuel tank structure. The tanks are machined stiffener-skin combination that are subsequently formed into the required contour after machining. The material scrap rate for these configurations are usually high, and the loss of a tank panel due to forming or heat treatment problems is very costly. The idea of reducing the amount of scrap material and scrapped structural members has prompted the introduction of built-up structure for cryogenic tanks to be explored on the ALS program. A build-up structure approach that has shown improvements in life cycle cost over the conventional built-up approach is the use of superplastically formed (SPF) stiffened panels (reducing the overall part count and weight for the tank) resistance spot welded (RSW) to outer tank skin material. The stiffeners provide for general stability of the tank, while the skin material provides hoop direction continuity for the loads.

Simulation of cracking cores when molding piston components

NASA Astrophysics Data System (ADS)

Petrenko, Alena; Soukup, Josef

2014-08-01

The article deals with pistons casting made from aluminum alloy. Pistons are casting at steel mold with steel core. The casting is provided by gravity casting machine. The each machine is equipped by two metal molds, which are preheated above temperature 160 °C before use. The steel core is also preheated by flame. The metal molds and cores are heated up within the casting process. The temperature of the metal mold raise up to 200 °C and temperature of core is higher. The surface of the core is treated by nitration. The mold and core are cooled down by water during casting process. The core is overheated and its top part is finally cracked despite its intensive water-cooling. The life time cycle of the core is decreased to approximately 5 to 15 thousands casting, which is only 15 % of life time cycle of core for production of other pistons. The article presents the temperature analysis of the core.

Laser-fusion targets for reactors

DOEpatents

Nuckolls, John H.; Thiessen, Albert R.

1987-01-01

A laser target comprising a thermonuclear fuel capsule composed of a centrally located quantity of fuel surrounded by at least one or more layers or shells of material for forming an atmosphere around the capsule by a low energy laser prepulse. The fuel may be formed as a solid core or hollow shell, and, under certain applications, a pusher-layer or shell is located intermediate the fuel and the atmosphere forming material. The fuel is ignited by symmetrical implosion via energy produced by a laser, or other energy sources such as an electron beam machine or ion beam machine, whereby thermonuclear burn of the fuel capsule creates energy for applications such as generation of electricity via a laser fusion reactor.

Progress toward a unified kJ-machine CANDY

NASA Astrophysics Data System (ADS)

Kitagawa, Yoneyoshi; Mori, Yoshitaka; Komeda, Osamu; Hanayama, Ryohei; Ishii, Katsuhiro; Okihara, Shinichiro; Fujita, Kazuhisa; Nakayama, Suisei; Sekine, Takashi; Sato, Nakahiro; Kurita, Takashi; Kawashima, Toshiyuki; Watari, Takeshi; Kan, Hirofumi; Nakamura, Naoki; Kondo, Takuya; Fujine, Manabu; Azuma, Hirozumi; Motohiro, Tomoyoshi; Hioki, Tatsumi; Kakeno, Mitsutaka; Nishimura, Yasuhiko; Sunahara, Atsushi; Sentoku, Yasuhiko; Miura, Eisuke; Arikawa, Yasunobu; Nagai, Takahiro; Abe, Yuki; Ozaki, Satoshi; Noda, Akira

2016-03-01

To construct a unified experimental machine CANDY using a kJ DPSSL driver in the fast-ignition scheme, the Laser for Fast Ignition Experiment (LFEX) at Osaka is used, showing that the laser-driven ions heat the preimploded core of a deuterated polystyrene (CD) shell target from 0.8 keV to 2 keV, resulting in 5 x 108 DD neutrons best ever obtained in the scheme. 4-J/10-Hz DPSSL laser HAMA is for the first time applied to the CD shell implosion- core heating experiments in the fast ignition scheme to yield neutrons and also to a continuous target injection, which yields neutrons of 3 x 105 n/4πsr n/shot.

Electric machine differential for vehicle traction control and stability control

NASA Astrophysics Data System (ADS)

Kuruppu, Sandun Shivantha

Evolving requirements in energy efficiency and tightening regulations for reliable electric drivetrains drive the advancement of the hybrid electric (HEV) and full electric vehicle (EV) technology. Different configurations of EV and HEV architectures are evaluated for their performance. The future technology is trending towards utilizing distinctive properties in electric machines to not only to improve efficiency but also to realize advanced road adhesion controls and vehicle stability controls. Electric machine differential (EMD) is such a concept under current investigation for applications in the near future. Reliability of a power train is critical. Therefore, sophisticated fault detection schemes are essential in guaranteeing reliable operation of a complex system such as an EMD. The research presented here emphasize on implementation of a 4kW electric machine differential, a novel single open phase fault diagnostic scheme, an implementation of a real time slip optimization algorithm and an electric machine differential based yaw stability improvement study. The proposed d-q current signature based SPO fault diagnostic algorithm detects the fault within one electrical cycle. The EMD based extremum seeking slip optimization algorithm reduces stopping distance by 30% compared to hydraulic braking based ABS.

Review of smoothing methods for enhancement of noisy data from heavy-duty LHD mining machines

NASA Astrophysics Data System (ADS)

Wodecki, Jacek; Michalak, Anna; Stefaniak, Paweł

2018-01-01

Appropriate analysis of data measured on heavy-duty mining machines is essential for processes monitoring, management and optimization. Some particular classes of machines, for example LHD (load-haul-dump) machines, hauling trucks, drilling/bolting machines etc. are characterized with cyclicity of operations. In those cases, identification of cycles and their segments or in other words - simply data segmentation is a key to evaluate their performance, which may be very useful from the management point of view, for example leading to introducing optimization to the process. However, in many cases such raw signals are contaminated with various artifacts, and in general are expected to be very noisy, which makes the segmentation task very difficult or even impossible. To deal with that problem, there is a need for efficient smoothing methods that will allow to retain informative trends in the signals while disregarding noises and other undesired non-deterministic components. In this paper authors present a review of various approaches to diagnostic data smoothing. Described methods can be used in a fast and efficient way, effectively cleaning the signals while preserving informative deterministic behaviour, that is a crucial to precise segmentation and other approaches to industrial data analysis.

Camouflage target reconnaissance based on hyperspectral imaging technology

NASA Astrophysics Data System (ADS)

Hua, Wenshen; Guo, Tong; Liu, Xun

2015-08-01

Efficient camouflaged target reconnaissance technology makes great influence on modern warfare. Hyperspectral images can provide large spectral range and high spectral resolution, which are invaluable in discriminating between camouflaged targets and backgrounds. Hyperspectral target detection and classification technology are utilized to achieve single class and multi-class camouflaged targets reconnaissance respectively. Constrained energy minimization (CEM), a widely used algorithm in hyperspectral target detection, is employed to achieve one class camouflage target reconnaissance. Then, support vector machine (SVM), a classification method, is proposed to achieve multi-class camouflage target reconnaissance. Experiments have been conducted to demonstrate the efficiency of the proposed method.

Development of a wearable measurement and control unit for personal customizing machine-supported exercise.

PubMed

Wang, Zhihui; Tamura, Naoki; Kiryu, Tohru

2005-01-01

Wearable technology has been used in various health-related fields to develop advanced monitoring solutions. However, the monitoring function alone cannot meet all the requirements of personal customizing machine-supported exercise that have biosignal-based controls. In this paper, we propose a new wearable unit design equipped with measurement and control functions to support the personal customization process. The wearable unit can measure the heart rate and electromyogram signals during exercise and output workload control commands to the exercise machines. We then applied a prototype of the wearable unit to an Internet-based cycle ergometer system. The wearable unit was examined using twelve young people to check its feasibility. The results verified that the unit could successfully adapt to the control of the workload and was effective for continuously supporting gradual changes in physical activities.

Utilization of rotor kinetic energy storage for hybrid vehicles

DOEpatents

Hsu, John S [Oak Ridge, TN

2011-05-03

A power system for a motor vehicle having an internal combustion engine, the power system comprises an electric machine (12) further comprising a first excitation source (47), a permanent magnet rotor (28) and a magnetic coupling rotor (26) spaced from the permanent magnet rotor and at least one second excitation source (43), the magnetic coupling rotor (26) also including a flywheel having an inertial mass to store kinetic energy during an initial acceleration to an operating speed; and wherein the first excitation source is electrically connected to the second excitation source for power cycling such that the flywheel rotor (26) exerts torque on the permanent magnet rotor (28) to assist braking and acceleration of the permanent magnet rotor (28) and consequently, the vehicle. An axial gap machine and a radial gap machine are disclosed and methods of the invention are also disclosed.

Transient Characteristics of Free Piston Vuilleurnier Cycle Heat Pumps

NASA Astrophysics Data System (ADS)

Matsue, Junji; Fujimoto, Norioki; Shirai, Hiroyuki

A dynamic analysis of a free piston Vuilleumier cycle heat pump was performed using a time-stepping integration method to investigate transient characteristics under power controlling. The nonlinear relationship between displacement and force for pistons was taken into account for the motion of reciprocating components. The force for pistons is mainly caused by the pressure change of working gas varying with piston displacements; moreover nonlinear viscous dissipative force due to the oscillating flow of working gas in heat exchangers and discontinuous damping force caused by solid friction at piston seals and rod seals are included. The displacements of pistons and pressure changes in the Vuilleumier cycle heat pump were integrated by an ideal isothermal thermodynamic relationship. It was assumed that the flow friction was proportional to the kinematic pressure of working gas, and that the solid friction at the seals was due to the functions of the working gas pressure and the tension of seal springs. In order to investigate the transient characteristics of a proposed free piston Vuilleumier cycle heat pump machine when hot-side working gas temperatures and alternate force were changed, some calculations were performed and discussed. These calculation results make clear transient characteristics at starting and power controlling. It was further found that only a small amount of starter power is required in particular conditions. During controlling, the machine becomes unstable when there is ar elatively large reduction in cooling or heating power. Therefore, an auxiliary device is additionally needed to obtain stable operation, such as al inear motor.

Machine learning and docking models for Mycobacterium tuberculosis topoisomerase I.

PubMed

Ekins, Sean; Godbole, Adwait Anand; Kéri, György; Orfi, Lászlo; Pato, János; Bhat, Rajeshwari Subray; Verma, Rinkee; Bradley, Erin K; Nagaraja, Valakunja

2017-03-01

There is a shortage of compounds that are directed towards new targets apart from those targeted by the FDA approved drugs used against Mycobacterium tuberculosis. Topoisomerase I (Mttopo I) is an essential mycobacterial enzyme and a promising target in this regard. However, it suffers from a shortage of known inhibitors. We have previously used computational approaches such as homology modeling and docking to propose 38 FDA approved drugs for testing and identified several active molecules. To follow on from this, we now describe the in vitro testing of a library of 639 compounds. These data were used to create machine learning models for Mttopo I which were further validated. The combined Mttopo I Bayesian model had a 5 fold cross validation receiver operator characteristic of 0.74 and sensitivity, specificity and concordance values above 0.76 and was used to select commercially available compounds for testing in vitro. The recently described crystal structure of Mttopo I was also compared with the previously described homology model and then used to dock the Mttopo I actives norclomipramine and imipramine. In summary, we describe our efforts to identify small molecule inhibitors of Mttopo I using a combination of machine learning modeling and docking studies in conjunction with screening of the selected molecules for enzyme inhibition. We demonstrate the experimental inhibition of Mttopo I by small molecule inhibitors and show that the enzyme can be readily targeted for lead molecule development. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Machine Learning Approach to Predict Gene Regulatory Networks in Seed Development in Arabidopsis

PubMed Central

Ni, Ying; Aghamirzaie, Delasa; Elmarakeby, Haitham; Collakova, Eva; Li, Song; Grene, Ruth; Heath, Lenwood S.

2016-01-01

Gene regulatory networks (GRNs) provide a representation of relationships between regulators and their target genes. Several methods for GRN inference, both unsupervised and supervised, have been developed to date. Because regulatory relationships consistently reprogram in diverse tissues or under different conditions, GRNs inferred without specific biological contexts are of limited applicability. In this report, a machine learning approach is presented to predict GRNs specific to developing Arabidopsis thaliana embryos. We developed the Beacon GRN inference tool to predict GRNs occurring during seed development in Arabidopsis based on a support vector machine (SVM) model. We developed both global and local inference models and compared their performance, demonstrating that local models are generally superior for our application. Using both the expression levels of the genes expressed in developing embryos and prior known regulatory relationships, GRNs were predicted for specific embryonic developmental stages. The targets that are strongly positively correlated with their regulators are mostly expressed at the beginning of seed development. Potential direct targets were identified based on a match between the promoter regions of these inferred targets and the cis elements recognized by specific regulators. Our analysis also provides evidence for previously unknown inhibitory effects of three positive regulators of gene expression. The Beacon GRN inference tool provides a valuable model system for context-specific GRN inference and is freely available at https://github.com/BeaconProjectAtVirginiaTech/beacon_network_inference.git. PMID:28066488

Quantification of uncertainty in machining operations for on-machine acceptance.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Claudet, Andre A.; Tran, Hy D.; Su, Jiann-Chemg

2008-09-01

Manufactured parts are designed with acceptance tolerances, i.e. deviations from ideal design conditions, due to unavoidable errors in the manufacturing process. It is necessary to measure and evaluate the manufactured part, compared to the nominal design, to determine whether the part meets design specifications. The scope of this research project is dimensional acceptance of machined parts; specifically, parts machined using numerically controlled (NC, or also CNC for Computer Numerically Controlled) machines. In the design/build/accept cycle, the designer will specify both a nominal value, and an acceptable tolerance. As part of the typical design/build/accept business practice, it is required to verifymore » that the part did meet acceptable values prior to acceptance. Manufacturing cost must include not only raw materials and added labor, but also the cost of ensuring conformance to specifications. Ensuring conformance is a substantial portion of the cost of manufacturing. In this project, the costs of measurements were approximately 50% of the cost of the machined part. In production, cost of measurement would be smaller, but still a substantial proportion of manufacturing cost. The results of this research project will point to a science-based approach to reducing the cost of ensuring conformance to specifications. The approach that we take is to determine, a priori, how well a CNC machine can manufacture a particular geometry from stock. Based on the knowledge of the manufacturing process, we are then able to decide features which need further measurements from features which can be accepted 'as is' from the CNC. By calibration of the machine tool, and establishing a machining accuracy ratio, we can validate the ability of CNC to fabricate to a particular level of tolerance. This will eliminate the costs of checking for conformance for relatively large tolerances.« less

Electrical test prediction using hybrid metrology and machine learning

NASA Astrophysics Data System (ADS)

Breton, Mary; Chao, Robin; Muthinti, Gangadhara Raja; de la Peña, Abraham A.; Simon, Jacques; Cepler, Aron J.; Sendelbach, Matthew; Gaudiello, John; Emans, Susan; Shifrin, Michael; Etzioni, Yoav; Urenski, Ronen; Lee, Wei Ti

2017-03-01

Electrical test measurement in the back-end of line (BEOL) is crucial for wafer and die sorting as well as comparing intended process splits. Any in-line, nondestructive technique in the process flow to accurately predict these measurements can significantly improve mean-time-to-detect (MTTD) of defects and improve cycle times for yield and process learning. Measuring after BEOL metallization is commonly done for process control and learning, particularly with scatterometry (also called OCD (Optical Critical Dimension)), which can solve for multiple profile parameters such as metal line height or sidewall angle and does so within patterned regions. This gives scatterometry an advantage over inline microscopy-based techniques, which provide top-down information, since such techniques can be insensitive to sidewall variations hidden under the metal fill of the trench. But when faced with correlation to electrical test measurements that are specific to the BEOL processing, both techniques face the additional challenge of sampling. Microscopy-based techniques are sampling-limited by their small probe size, while scatterometry is traditionally limited (for microprocessors) to scribe targets that mimic device ground rules but are not necessarily designed to be electrically testable. A solution to this sampling challenge lies in a fast reference-based machine learning capability that allows for OCD measurement directly of the electrically-testable structures, even when they are not OCD-compatible. By incorporating such direct OCD measurements, correlation to, and therefore prediction of, resistance of BEOL electrical test structures is significantly improved. Improvements in prediction capability for multiple types of in-die electrically-testable device structures is demonstrated. To further improve the quality of the prediction of the electrical resistance measurements, hybrid metrology using the OCD measurements as well as X-ray metrology (XRF) is used. Hybrid metrology is the practice of combining information from multiple sources in order to enable or improve the measurement of one or more critical parameters. Here, the XRF measurements are used to detect subtle changes in barrier layer composition and thickness that can have second-order effects on the electrical resistance of the test structures. By accounting for such effects with the aid of the X-ray-based measurements, further improvement in the OCD correlation to electrical test measurements is achieved. Using both types of solution incorporation of fast reference-based machine learning on nonOCD-compatible test structures, and hybrid metrology combining OCD with XRF technology improvement in BEOL cycle time learning could be accomplished through improved prediction capability.

MIDAS Website. Revised

NASA Technical Reports Server (NTRS)

Goodman, Allen; Shively, R. Joy (Technical Monitor)

1997-01-01

MIDAS, Man-machine Integration Design and Analysis System, is a unique combination of software tools aimed at reducing design cycle time, supporting quantitative predictions of human-system effectiveness and improving the design of crew stations and their associated operating procedures. This project is supported jointly by the US Army and NASA.

Manpower/Hardware Life Cycle Cost Analysis Study.

DTIC Science & Technology

1979-11-06

designer will begin to learn, on a subconscious level, about the likely outcome of tradeoffs. At the high rate of use expected for these machines, he...one requiring considerable cost analytic expertise), and the model must be redocumented and partially or completely reprogrammed . All this is extremely

Isochronous (CW) Non-Scaling FFAGs: Design and Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnstone, C.; Berz, M.; Makino, K.

2010-11-04

The drive for higher beam power, high duty cycle, and reliable beams at reasonable cost has focused international attention and design effort on fixed field accelerators, notably Fixed-Field Alternating Gradient accelerators (FFAGs). High-intensity GeV proton drivers encounter duty cycle and space-charge limits in the synchrotron and machine size concerns in the weaker-focusing cyclotrons. A 10-20 MW proton driver is challenging, if even technically feasible, with conventional accelerators--with the possible exception of a SRF linac, which has a large associated cost and footprint. Recently, the concept of isochronous orbits has been explored and developed for nonscaling FFAGs using powerful new methodologiesmore » in FFAG accelerator design and simulation. The property of isochronous orbits enables the simplicity of fixed RF and, by tailoring a nonlinear radial field profile, the FFAG can remain isochronous beyond the energy reach of cyclotrons, well into the relativistic regime. With isochronous orbits, the machine proposed here has the high average current advantage and duty cycle of the cyclotron in combination with the strong focusing, smaller losses, and energy variability that are more typical of the synchrotron. This paper reports on these new advances in FFAG accelerator technology and presents advanced modeling tools for fixed-field accelerators unique to the code COSY INFINITY.« less

Phosphoric and electric utility fuel technology development

NASA Astrophysics Data System (ADS)

Breault, R. D.; Briggs, T. A.; Congdon, J. V.; Gelting, R. L.; Goller, G. J.; Luoma, W. L.; McCloskey, M. W.; Mientek, A. P.; Obrien, J. J.; Randall, S. A.

1985-05-01

Seventeen hundred hours and 11 thermal cycles were accumulated on the second 10 sq ft short stack at 120 psia and 405 F. A subscale cell out from 10 sq ft electrodes in the same batch used for the second 10 sq ft short stack accumulated over 4100 hours with performance conforming close to the E-line goal at 120 psia and 400 F. Over 14,870 hours and 42 thermal cycles were accumulated on the 3.7 sq ft, 30-cell short stack at 120 psia and 405 F. A subscale cell with GSB-18 catalyst completed over 10,000 hours of operation at 120 psia, 400 F. The full-size, 10 sq ft stack containment vessel and reactant gas manifolds were observed. The improved edge seal decreased leakage by more than 50% from the conventional edge seal. Cross-pressure tolerance also improved. Continuous automatic operation of the substrate forming machine was demonstrated by producing substrates at a 50% faster rate with high yields and low material loss. The cooler bonding cycle was significantly reduced by using a cold press in conjunction with the hot press. A lower cost stainless steel tubing is identified that could reduce cooler array cost by up to 50%. Assembly of the automated cell fill and assembly machine is initiated.

Application of Data Cubes for Improving Detection of Water Cycle Extreme Events

NASA Technical Reports Server (NTRS)

Albayrak, Arif; Teng, William

2015-01-01

As part of an ongoing NASA-funded project to remove a longstanding barrier to accessing NASA data (i.e., accessing archived time-step array data as point-time series), for the hydrology and other point-time series-oriented communities, "data cubes" are created from which time series files (aka "data rods") are generated on-the-fly and made available as Web services from the Goddard Earth Sciences Data and Information Services Center (GES DISC). Data cubes are data as archived rearranged into spatio-temporal matrices, which allow for easy access to the data, both spatially and temporally. A data cube is a specific case of the general optimal strategy of reorganizing data to match the desired means of access. The gain from such reorganization is greater the larger the data set. As a use case of our project, we are leveraging existing software to explore the application of the data cubes concept to machine learning, for the purpose of detecting water cycle extreme events, a specific case of anomaly detection, requiring time series data. We investigate the use of support vector machines (SVM) for anomaly classification. We show an example of detection of water cycle extreme events, using data from the Tropical Rainfall Measuring Mission (TRMM).

miREE: miRNA recognition elements ensemble

PubMed Central

2011-01-01

Background Computational methods for microRNA target prediction are a fundamental step to understand the miRNA role in gene regulation, a key process in molecular biology. In this paper we present miREE, a novel microRNA target prediction tool. miREE is an ensemble of two parts entailing complementary but integrated roles in the prediction. The Ab-Initio module leverages upon a genetic algorithmic approach to generate a set of candidate sites on the basis of their microRNA-mRNA duplex stability properties. Then, a Support Vector Machine (SVM) learning module evaluates the impact of microRNA recognition elements on the target gene. As a result the prediction takes into account information regarding both miRNA-target structural stability and accessibility. Results The proposed method significantly improves the state-of-the-art prediction tools in terms of accuracy with a better balance between specificity and sensitivity, as demonstrated by the experiments conducted on several large datasets across different species. miREE achieves this result by tackling two of the main challenges of current prediction tools: (1) The reduced number of false positives for the Ab-Initio part thanks to the integration of a machine learning module (2) the specificity of the machine learning part, obtained through an innovative technique for rich and representative negative records generation. The validation was conducted on experimental datasets where the miRNA:mRNA interactions had been obtained through (1) direct validation where even the binding site is provided, or through (2) indirect validation, based on gene expression variations obtained from high-throughput experiments where the specific interaction is not validated in detail and consequently the specific binding site is not provided. Conclusions The coupling of two parts: a sensitive Ab-Initio module and a selective machine learning part capable of recognizing the false positives, leads to an improved balance between sensitivity and specificity. miREE obtains a reasonable trade-off between filtering false positives and identifying targets. miREE tool is available online at http://didattica-online.polito.it/eda/miREE/ PMID:22115078

A comparative study of machine learning models for ethnicity classification

NASA Astrophysics Data System (ADS)

Trivedi, Advait; Bessie Amali, D. Geraldine

2017-11-01

This paper endeavours to adopt a machine learning approach to solve the problem of ethnicity recognition. Ethnicity identification is an important vision problem with its use cases being extended to various domains. Despite the multitude of complexity involved, ethnicity identification comes naturally to humans. This meta information can be leveraged to make several decisions, be it in target marketing or security. With the recent development of intelligent systems a sub module to efficiently capture ethnicity would be useful in several use cases. Several attempts to identify an ideal learning model to represent a multi-ethnic dataset have been recorded. A comparative study of classifiers such as support vector machines, logistic regression has been documented. Experimental results indicate that the logical classifier provides a much accurate classification than the support vector machine.

The effect of fresh gas flow rate and type of anesthesia machine on time to reach target sevoflurane concentration.

PubMed

Shin, Hye Won; Yu, Hae Na; Bae, Go Eun; Huh, Hyub; Park, Ji Yong; Kim, Ji Young

2017-01-19

Anesthesia machines have been developed by the application of new technology for rapid and easier control of anesthetic concentration. In this study, we used a test lung to investigate whether the time taken to reach the target sevoflurane concentration varies with the rate of fresh gas flow (FGF) and type of anesthesia machine (AM). We measured the times taken to reach the target sevoflurane concentration (2 minimum alveolar concentration = 4%) at variable rates of FGF (0.5, 1, or 3 L/min) and different types of AM (Primus ® , Perseus ® , and Zeus ® [Zeus ® -F; Zeus ® fresh gas mode, Zeus ® -A; Zeus ® auto-mode]). Concomitant ventilation was supplied using 100% O 2. The AMs were connected to a test lung. A sevoflurane vaporizer setting of 6% was used in Primus ® , Perseus ® , and Zeus ® -F; a target end-tidal setting of 4% was used in Zeus ® -A (from a vaporizer setting of 0%). The time taken to reach the target concentration was measured in every group. When the same AM was used (Primus ® , Perseus ® , or Zeus ® -F), the times to target concentration shortened as the FGF rate increased (P < 0.05). Conversely, when the same FGF rate was used, but with different AMs, the time to target concentration was shortest in Perseus ® , followed by Primus ® , and finally by Zeus ® -F (P < 0.05). With regards to both modes of Zeus ® , at FGF rates of 0.5 and 1 L/min, the time to target concentration was shorter in Zeus ® -A than in Zeus ® -F; however, the time was longer in Zeus ® -A than in Zeus ® -F at FGF rate of 3 L/min (P < 0.05). Shorter times taken to reach the target concentration were associated with high FGF rates, smaller internal volume of the AM, proximity of the fresh gas inlets to patients, absence of a decoupling system, and use of blower-driven ventilators in AM.

U.S. Army Research Laboratory (ARL) Corporate Dari Document Transcription and Translation Guidelines

DTIC Science & Technology

2012-10-01

text file format. 15. SUBJECT TERMS Transcription, Translation, guidelines, ground truth, Optical character recognition , OCR, Machine Translation, MT...foreign language into a target language in order to train, test, and evaluate optical character recognition (OCR) and machine translation (MT) embedded...graphic element and should not be transcribed. Elements that are not part of the primary text such as handwritten annotations or stamps should not be

Impact of machining on the flexural fatigue strength of glass and polycrystalline CAD/CAM ceramics.

PubMed

Fraga, Sara; Amaral, Marina; Bottino, Marco Antônio; Valandro, Luiz Felipe; Kleverlaan, Cornelis Johannes; May, Liliana Gressler

2017-11-01

To assess the effect of machining on the flexural fatigue strength and on the surface roughness of different computer-aided design, computer-aided manufacturing (CAD/CAM) ceramics by comparing machined and polished after machining specimens. Disc-shaped specimens of yttria-stabilized polycrystalline tetragonal zirconia (Y-TZP), leucite-, and lithium disilicate-based glass ceramics were prepared by CAD/CAM machining, and divided into two groups: machining (M) and machining followed by polishing (MP). The surface roughness was measured and the flexural fatigue strength was evaluated by the step-test method (n=20). The initial load and the load increment for each ceramic material were based on a monotonic test (n=5). A maximum of 10,000 cycles was applied in each load step, at 1.4Hz. Weibull probability statistics was used for the analysis of the flexural fatigue strength, and Mann-Whitney test (α=5%) to compare roughness between the M and MP conditions. Machining resulted in lower values of characteristic flexural fatigue strength than machining followed by polishing. The greatest reduction in flexural fatigue strength from MP to M was observed for Y-TZP (40%; M=536.48MPa; MP=894.50MPa), followed by lithium disilicate (33%; M=187.71MPa; MP=278.93MPa) and leucite (29%; M=72.61MPa; MP=102.55MPa). Significantly higher values of roughness (Ra) were observed for M compared to MP (leucite: M=1.59μm and MP=0.08μm; lithium disilicate: M=1.84μm and MP=0.13μm; Y-TZP: M=1.79μm and MP=0.18μm). Machining negatively affected the flexural fatigue strength of CAD/CAM ceramics, indicating that machining of partially or fully sintered ceramics is deleterious to fatigue strength. Copyright © 2017 The Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

[Evaluation of the learning curve of residents in localizing a phantom target with ultrasonography].

PubMed

Dessieux, T; Estebe, J-P; Bloc, S; Mercadal, L; Ecoffey, C

2008-10-01

Few information are available regarding the learning curve in ultrasonography and even less for ultrasound-guided regional anesthesia. This study aimed to evaluate in a training program the learning curve on a phantom of 12 residents novice in ultrasonography. Twelve trainees inexperienced in ultrasonography were given introductory training consisting of didactic formation on the various components of the portable ultrasound machine (i.e. on/off button, gain, depth, resolution, and image storage). Then, students performed three trials, in two sets of increased difficulty, at executing these predefined tasks: adjustments of the machine, then localization of a small plastic piece introduced into roasting pork (3 cm below the surface). At the end of the evaluation, the residents were asked to insert a 22 G needle into an exact predetermined target (i.e. point of fascia intersection). The progression of the needle was continuously controlled by ultrasound visualization using injection of a small volume of water (needle perpendicular to the longitudinal plane of the ultrasound beam). Two groups of two different examiners evaluated for each three trials the skill of the residents (quality, time to perform the machine adjustments, to localize the plastic target, and to hydrolocalize, and volume used for hydrolocalization). After each trial, residents evaluated their performance using a difficulty scale (0: easy to 10: difficult). All residents performed the adjustments from the last trial of each set, with a learning curve observed in terms of duration. Localization of the plastic piece was achieved by all residents at the 6th trial, with a shorter duration of localization. Hydrolocalization was achieved after the 4th trial by all subjects. Difficulty scale was correlated to the number of trials. All these results were independent of the experience of residents in regional anesthesia. Four trials were necessary to adjust correctly the machine, to localize a target, and to complete hydrolocalization. Ultrasonography in regional anesthesia seems to be a fast-learning technique, using this kind of practical training.

Non-symmetric approach to single-screw expander and compressor modeling

NASA Astrophysics Data System (ADS)

Ziviani, Davide; Groll, Eckhard A.; Braun, James E.; Horton, W. Travis; De Paepe, M.; van den Broek, M.

2017-08-01

Single-screw type volumetric machines are employed both as compressors in refrigeration systems and, more recently, as expanders in organic Rankine cycle (ORC) applications. The single-screw machine is characterized by having a central grooved rotor and two mating toothed starwheels that isolate the working chambers. One of the main features of such machine is related to the simultaneous occurrence of the compression or expansion processes on both sides of the main rotor which results in a more balanced loading on the main shaft bearings with respect to twin-screw machines. However, the meshing between starwheels and main rotor is a critical aspect as it heavily affects the volumetric performance of the machine. To allow flow interactions between the two sides of the rotor, a non-symmetric modelling approach has been established to obtain a more comprehensive model of the single-screw machine. The resulting mechanistic model includes in-chamber governing equations, leakage flow models, heat transfer mechanisms, viscous and mechanical losses. Forces and moments balances are used to estimate the loads on the main shaft bearings as well as on the starwheel bearings. An 11 kWe single-screw expander (SSE) adapted from an air compressor operating with R245fa as working fluid is used to validate the model. A total of 60 steady-steady points at four different rotational speeds have been collected to characterize the performance of the machine. The maximum electrical power output and overall isentropic efficiency measured were 7.31 kW and 51.91%, respectively.

Automatic Classification of Sub-Techniques in Classical Cross-Country Skiing Using a Machine Learning Algorithm on Micro-Sensor Data

PubMed Central

Seeberg, Trine M.; Tjønnås, Johannes; Haugnes, Pål; Sandbakk, Øyvind

2017-01-01

The automatic classification of sub-techniques in classical cross-country skiing provides unique possibilities for analyzing the biomechanical aspects of outdoor skiing. This is currently possible due to the miniaturization and flexibility of wearable inertial measurement units (IMUs) that allow researchers to bring the laboratory to the field. In this study, we aimed to optimize the accuracy of the automatic classification of classical cross-country skiing sub-techniques by using two IMUs attached to the skier’s arm and chest together with a machine learning algorithm. The novelty of our approach is the reliable detection of individual cycles using a gyroscope on the skier’s arm, while a neural network machine learning algorithm robustly classifies each cycle to a sub-technique using sensor data from an accelerometer on the chest. In this study, 24 datasets from 10 different participants were separated into the categories training-, validation- and test-data. Overall, we achieved a classification accuracy of 93.9% on the test-data. Furthermore, we illustrate how an accurate classification of sub-techniques can be combined with data from standard sports equipment including position, altitude, speed and heart rate measuring systems. Combining this information has the potential to provide novel insight into physiological and biomechanical aspects valuable to coaches, athletes and researchers. PMID:29283421

Development of an Organic Rankine Cycle system for exhaust energy recovery in internal combustion engines

NASA Astrophysics Data System (ADS)

Cipollone, Roberto; Bianchi, Giuseppe; Gualtieri, Angelo; Di Battista, Davide; Mauriello, Marco; Fatigati, Fabio

2015-11-01

Road transportation is currently one of the most influencing sectors for global energy consumptions and CO2 emissions. Nevertheless, more than one third of the fuel energy supplied to internal combustion engines is still rejected to the environment as thermal waste at the exhaust. Therefore, a greater fuel economy might be achieved recovering the energy from exhaust gases and converting it into useful power on board. In the current research activity, an ORC-based energy recovery system was developed and coupled with a diesel engine. The innovative feature of the recovery power unit relies upon the usage of sliding vane rotary machines as pump and expander. After a preliminary exhaust gas mapping, which allowed to assess the magnitude of the thermal power to be recovered, a thermodynamic analysis was carried out to design the ORC system and the sliding vane machines using R236fa as working fluid. An experimental campaign was eventually performed at different operating regimes according to the ESC procedure and investigated the recovery potential of the power unit at design and off-design conditions. Mechanical power recovered ranged from 0.7 kW up to 1.9 kW, with an overall cycle efficiency from 3.8% up to 4.8% respectively. These results candidate sliding vane machines as efficient and reliable devices for waste heat recovery applications.

The effect of sterilization and number of use on the accuracy of friction-style mechanical torque limiting devices for dental implants

PubMed Central

Fayaz, Ali; Mahshid, Minoo; Saboury, Aboulfazl; Sadr, Seyed Jalil; Ansari, Ghassem

2014-01-01

Background: Mechanical torque limiting devices (MTLDs) are necessary tools to control a peak torque and achieving target values of screw component of dental implants. Due to probable effect of autoclaving and number of use on the accuracy of these devices, this study aimed to evaluate the effect of sterilization and number of use on the accuracy of friction-style mechanical torque limiting devices (F-S MTLDs) in achieving their target torque values. Materials and Methods: Peak torque measurements of 15 new F-S MTLDs from three different manufacturers (Astra Tech, BioHorizons, Dr. Idhe) were measured ten times before and after 100 steam sterilization using a digital torque gauge. To simulate the clinical situation of aging (number of use) target torque application process was repeated 10 times after each sterilization cycle and the peak torque values were registered. Comparison of the mean differences with target torque in each cycle was performed using one sample t test. Considering the type of MTLDs as inter subject comparison, One-way repeated measure ANOVA was used to evaluate the absolute values of differences between devices of each manufacturer in each group (α = 0.05). Results: The results of this study in Dr. Idhe group showed that, mean of difference values significantly differed from the target torque (P = 0.002) until 75 cycles. In Astra Tech group, also mean of difference values with under estimation trend, showed a significant difference with the target torque (P < 0.001). Mean of difference values significantly differed from the target torque with under estimation trend during all the 100 cycles in BioHorizons group (P < 0.05). Conclusion: The torque output of each individual device stayed in 10% difference from target torque values before 100 sterilization cycles, but more than 10% difference from the target torque was seen in varying degrees during these consequent cycles. PMID:24688564

Development of a machine vision system for automated structural assembly

NASA Technical Reports Server (NTRS)

Sydow, P. Daniel; Cooper, Eric G.

1992-01-01

Research is being conducted at the LaRC to develop a telerobotic assembly system designed to construct large space truss structures. This research program was initiated within the past several years, and a ground-based test-bed was developed to evaluate and expand the state of the art. Test-bed operations currently use predetermined ('taught') points for truss structural assembly. Total dependence on the use of taught points for joint receptacle capture and strut installation is neither robust nor reliable enough for space operations. Therefore, a machine vision sensor guidance system is being developed to locate and guide the robot to a passive target mounted on the truss joint receptacle. The vision system hardware includes a miniature video camera, passive targets mounted on the joint receptacles, target illumination hardware, and an image processing system. Discrimination of the target from background clutter is accomplished through standard digital processing techniques. Once the target is identified, a pose estimation algorithm is invoked to determine the location, in three-dimensional space, of the target relative to the robots end-effector. Preliminary test results of the vision system in the Automated Structural Assembly Laboratory with a range of lighting and background conditions indicate that it is fully capable of successfully identifying joint receptacle targets throughout the required operational range. Controlled optical bench test results indicate that the system can also provide the pose estimation accuracy to define the target position.

Investigation of Low-Cycle Bending Fatigue of AISI 9310 Steel Spur Gears

NASA Technical Reports Server (NTRS)

Handschuh, Robert F.; Krantz, Timothy L.; Lerch, Bradley A.; Burke, Christopher S.

2007-01-01

An investigation of the low-cycle bending fatigue of spur gears made from AISI 9310 gear steel was completed. Tests were conducted using the single-tooth bending method to achieve crack initiation and propagation. Tests were conducted on spur gears in a fatigue test machine using a dedicated gear test fixture. Test loads were applied at the highest point of single tooth contact. Gear bending stresses for a given testing load were calculated using a linear-elastic finite element model. Test data were accumulated from 1/4 cycle to several thousand cycles depending on the test stress level. The relationship of stress and cycles for crack initiation was found to be semi-logarithmic. The relationship of stress and cycles for crack propagation was found to be linear. For the range of loads investigated, the crack propagation phase is related to the level of load being applied. Very high loads have comparable crack initiation and propagation times whereas lower loads can have a much smaller number of cycles for crack propagation cycles as compared to crack initiation.

Investigation of Low-Cycle Bending Fatigue of AISI 9310 Steel Spur Gears

NASA Technical Reports Server (NTRS)

Handschuh, Robert F.; Krantz, Timothy L.; Lerch, Bradley A.; Burke, Christopher S.

2007-01-01

An investigation of the low-cycle bending fatigue of spur gears made from AISI 9310 gear steel was completed. Tests were conducted using the single-tooth bending method to achieve crack initiation and propagation. Tests were conducted on spur gears in a fatigue test machine using a dedicated gear test fixture. Test loads were applied at the highest point of single tooth contact. Gear bending stresses for a given testing load were calculated using a linear-elastic finite element model. Test data were accumulated from 1/4 cycle to several thousand cycles depending on the test stress level. The relationship of stress and cycles for crack initiation was found to be semilogarithmic. The relationship of stress and cycles for crack propagation was found to be linear. For the range of loads investigated, the crack propagation phase is related to the level of load being applied. Very high loads have comparable crack initiation and propagation times whereas lower loads can have a much smaller number of cycles for crack propagation cycles as compared to crack initiation.

The effects of multiple repairs on Inconel 718 weld mechanical properties

NASA Technical Reports Server (NTRS)

Russell, C. K.; Nunes, A. C., Jr.; Moore, D.

1991-01-01

Inconel 718 weldments were repaired 3, 6, 9, and 13 times using the gas tungsten arc welding process. The welded panels were machined into mechanical test specimens, postweld heat treated, and nondestructively tested. Tensile properties and high cycle fatigue life were evaluated and the results compared to unrepaired weld properties. Mechanical property data were analyzed using the statistical methods of difference in means for tensile properties and difference in log means and Weibull analysis for high cycle fatigue properties. Statistical analysis performed on the data did not show a significant decrease in tensile or high cycle fatigue properties due to the repeated repairs. Some degradation was observed in all properties, however, it was minimal.

Toward polarized antiprotons: Machine development for spin-filtering experiments

NASA Astrophysics Data System (ADS)

Weidemann, C.; Rathmann, F.; Stein, H. J.; Lorentz, B.; Bagdasarian, Z.; Barion, L.; Barsov, S.; Bechstedt, U.; Bertelli, S.; Chiladze, D.; Ciullo, G.; Contalbrigo, M.; Dymov, S.; Engels, R.; Gaisser, M.; Gebel, R.; Goslawski, P.; Grigoriev, K.; Guidoboni, G.; Kacharava, A.; Kamerdzhiev, V.; Khoukaz, A.; Kulikov, A.; Lehrach, A.; Lenisa, P.; Lomidze, N.; Macharashvili, G.; Maier, R.; Martin, S.; Mchedlishvili, D.; Meyer, H. O.; Merzliakov, S.; Mielke, M.; Mikirtychiants, M.; Mikirtychiants, S.; Nass, A.; Nikolaev, N. N.; Oellers, D.; Papenbrock, M.; Pesce, A.; Prasuhn, D.; Retzlaff, M.; Schleichert, R.; Schröer, D.; Seyfarth, H.; Soltner, H.; Statera, M.; Steffens, E.; Stockhorst, H.; Ströher, H.; Tabidze, M.; Tagliente, G.; Engblom, P. Thörngren; Trusov, S.; Valdau, Yu.; Vasiliev, A.; Wüstner, P.

2015-02-01

The paper describes the commissioning of the experimental equipment and the machine studies required for the first spin-filtering experiment with protons at a beam kinetic energy of 49.3 MeV in COSY. The implementation of a low-β insertion made it possible to achieve beam lifetimes of τb=8000 s in the presence of a dense polarized hydrogen storage-cell target of areal density dt=(5.5 ±0.2 )×1 013 atoms /cm2 . The developed techniques can be directly applied to antiproton machines and allow the determination of the spin-dependent p ¯p cross sections via spin filtering.

Polarized light reveals stress in machined laminated plastics

NASA Technical Reports Server (NTRS)

Frankowski, J.

1967-01-01

Polarized light applied to drilled laminated plastic components exposes to the human eye the locked-in stresses that will result in fractures and delaminations when the soldering procedure takes place. This technique detects stresses early in the production cycle before appreciable man-hours are invested in an item destined for rejection.

Efficiently Ranking Hyphotheses in Machine Learning

NASA Technical Reports Server (NTRS)

Chien, Steve

1997-01-01

This paper considers the problem of learning the ranking of a set of alternatives based upon incomplete information (e.g. a limited number of observations). At each decision cycle, the system can output a complete ordering on the hypotheses or decide to gather additional information (e.g. observation) at some cost.

TargetMiner: microRNA target prediction with systematic identification of tissue-specific negative examples.

PubMed

Bandyopadhyay, Sanghamitra; Mitra, Ramkrishna

2009-10-15

Prediction of microRNA (miRNA) target mRNAs using machine learning approaches is an important area of research. However, most of the methods suffer from either high false positive or false negative rates. One reason for this is the marked deficiency of negative examples or miRNA non-target pairs. Systematic identification of non-target mRNAs is still not addressed properly, and therefore, current machine learning approaches are compelled to rely on artificially generated negative examples for training. In this article, we have identified approximately 300 tissue-specific negative examples using a novel approach that involves expression profiling of both miRNAs and mRNAs, miRNA-mRNA structural interactions and seed-site conservation. The newly generated negative examples are validated with pSILAC dataset, which elucidate the fact that the identified non-targets are indeed non-targets.These high-throughput tissue-specific negative examples and a set of experimentally verified positive examples are then used to build a system called TargetMiner, a support vector machine (SVM)-based classifier. In addition to assessing the prediction accuracy on cross-validation experiments, TargetMiner has been validated with a completely independent experimental test dataset. Our method outperforms 10 existing target prediction algorithms and provides a good balance between sensitivity and specificity that is not reflected in the existing methods. We achieve a significantly higher sensitivity and specificity of 69% and 67.8% based on a pool of 90 feature set and 76.5% and 66.1% using a set of 30 selected feature set on the completely independent test dataset. In order to establish the effectiveness of the systematically generated negative examples, the SVM is trained using a different set of negative data generated using the method in Yousef et al. A significantly higher false positive rate (70.6%) is observed when tested on the independent set, while all other factors are kept the same. Again, when an existing method (NBmiRTar) is executed with the our proposed negative data, we observe an improvement in its performance. These clearly establish the effectiveness of the proposed approach of selecting the negative examples systematically. TargetMiner is now available as an online tool at www.isical.ac.in/ approximately bioinfo_miu

Micro Fluidic Channel Machining on Fused Silica Glass Using Powder Blasting

PubMed Central

Jang, Ho-Su; Cho, Myeong-Woo; Park, Dong-Sam

2008-01-01

In this study, micro fluid channels are machined on fused silica glass via powder blasting, a mechanical etching process, and the machining characteristics of the channels are experimentally evaluated. In the process, material removal is performed by the collision of micro abrasives injected by highly compressed air on to the target surface. This approach can be characterized as an integration of brittle mode machining based on micro crack propagation. Fused silica glass, a high purity synthetic amorphous silicon dioxide, is selected as a workpiece material. It has a very low thermal expansion coefficient and excellent optical qualities and exceptional transmittance over a wide spectral range, especially in the ultraviolet range. The powder blasting process parameters affecting the machined results are injection pressure, abrasive particle size and density, stand-off distance, number of nozzle scanning, and shape/size of the required patterns. In this study, the influence of the number of nozzle scanning, abrasive particle size, and pattern size on the formation of micro channels is investigated. Machined shapes and surface roughness are measured using a 3-dimensional vision profiler and the results are discussed. PMID:27879730

Methods, systems and apparatus for controlling operation of two alternating current (AC) machines

DOEpatents

Gallegos-Lopez, Gabriel [Torrance, CA; Nagashima, James M [Cerritos, CA; Perisic, Milun [Torrance, CA; Hiti, Silva [Redondo Beach, CA

2012-02-14

A system is provided for controlling two AC machines. The system comprises a DC input voltage source that provides a DC input voltage, a voltage boost command control module (VBCCM), a five-phase PWM inverter module coupled to the two AC machines, and a boost converter coupled to the inverter module and the DC input voltage source. The boost converter is designed to supply a new DC input voltage to the inverter module having a value that is greater than or equal to a value of the DC input voltage. The VBCCM generates a boost command signal (BCS) based on modulation indexes from the two AC machines. The BCS controls the boost converter such that the boost converter generates the new DC input voltage in response to the BCS. When the two AC machines require additional voltage that exceeds the DC input voltage required to meet a combined target mechanical power required by the two AC machines, the BCS controls the boost converter to drive the new DC input voltage generated by the boost converter to a value greater than the DC input voltage.

Design study and performance analysis of 12S-14P field excitation flux switching motor for hybrid electric vehicle

NASA Astrophysics Data System (ADS)

Husin, Zhafir Aizat; Sulaiman, Erwan; Khan, Faisal; Mazlan, Mohamed Mubin Aizat; Othman, Syed Muhammad Naufal Syed

2015-05-01

This paper presents a new structure of 12slot-14pole field excitation flux switching motor (FEFSM) as an alternative candidate of non-Permanent Magnet (PM) machine for HEV drives. Design study, performance analysis and optimization of field excitation flux switching machine with non-rare-earth magnet for hybrid electric vehicle drive applications is done. The stator of projected machine consists of iron core made of electromagnetic steels, armature coils and field excitation coils as the only field mmf source. The rotor is consisted of only stack of iron and hence, it is reliable and appropriate for high speed operation. The design target is a machine with the maximum torque, power and power density, more than 210Nm, 123kW and 3.5kW/kg, respectively, which competes with interior permanent magnet synchronous machine used in existing hybrid electric vehicle. Some design feasibility studies on FEFSM based on 2D-FEA and deterministic optimization method will be applied to design the proposed machine.

Gasdynamic lasers and photon machines.

NASA Technical Reports Server (NTRS)

Christiansen, W. H.; Hertzberg, A.

1973-01-01

The basic operational highlights of CO2-N2 gasdynamic lasers (GDL's) are described. Features common to powerful gas lasers are indicated. A simplified model of the vibrational kinetics of the system is presented, and the importance of rapid expansion nozzles is shown from analytic solutions of the equations. A high-power pulsed GDL is described, along with estimations of power extraction. A closed-cycle laser is suggested, leading to a description of a photon generator/engine. Thermodynamic analysis of the closed-cycle laser illustrates in principle the possibility of direct conversion of laser energy to work.

Target detection cycle criteria when using the targeting task performance metric

NASA Astrophysics Data System (ADS)

Hixson, Jonathan G.; Jacobs, Eddie L.; Vollmerhausen, Richard H.

2004-12-01

The US Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate of the US Army (NVESD) has developed a new target acquisition metric to better predict the performance of modern electro-optical imagers. The TTP metric replaces the Johnson criteria. One problem with transitioning to the new model is that the difficulty of searching in a terrain has traditionally been quantified by an "N50." The N50 is the number of Johnson criteria cycles needed for the observer to detect the target half the time, assuming that the observer is not time limited. In order to make use of this empirical data base, a conversion must be found relating Johnson cycles for detection to TTP cycles for detection. This paper describes how that relationship is established. We have found that the relationship between Johnson and TTP is 1:2.7 for the recognition and identification tasks.

Integrative Analysis Reveals an Outcome-associated and Targetable Pattern of p53 and Cell Cycle Deregulation in Diffuse Large B-cell Lymphoma

PubMed Central

Monti, Stefano; Chapuy, Bjoern; Takeyama, Kunihiko; Rodig, Scott J; Hao, Yangsheng; Yeda, Kelly T.; Inguilizian, Haig; Mermel, Craig; Curie, Treeve; Dogan, Ahmed; Kutok, Jeffery L; Beroukim, Rameen; Neuberg, Donna; Habermann, Thomas; Getz, Gad; Kung, Andrew L; Golub, Todd R; Shipp, Margaret A

2013-01-01

Summary Diffuse large B-cell lymphoma (DLBCL) is a clinically and biologically heterogeneous disease with a high proliferation rate. By integrating copy number data with transcriptional profiles and performing pathway analysis in primary DLBCLs, we identified a comprehensive set of copy number alterations (CNAs) that decreased p53 activity and perturbed cell cycle regulation. Primary tumors either had multiple complementary alterations of p53 and cell cycle components or largely lacked these lesions. DLBCLs with p53 and cell cycle pathway CNAs had decreased abundance of p53 target transcripts and increased expression of E2F target genes and the Ki67 proliferation marker. CNAs of the CDKN2A-TP53-RB-E2F axis provide a structural basis for increased proliferation in DLBCL, predict outcome with current therapy and suggest targeted treatment approaches. PMID:22975378

[MicroRNA Target Prediction Based on Support Vector Machine Ensemble Classification Algorithm of Under-sampling Technique].

PubMed

Chen, Zhiru; Hong, Wenxue

2016-02-01

Considering the low accuracy of prediction in the positive samples and poor overall classification effects caused by unbalanced sample data of MicroRNA (miRNA) target, we proposes a support vector machine (SVM)-integration of under-sampling and weight (IUSM) algorithm in this paper, an under-sampling based on the ensemble learning algorithm. The algorithm adopts SVM as learning algorithm and AdaBoost as integration framework, and embeds clustering-based under-sampling into the iterative process, aiming at reducing the degree of unbalanced distribution of positive and negative samples. Meanwhile, in the process of adaptive weight adjustment of the samples, the SVM-IUSM algorithm eliminates the abnormal ones in negative samples with robust sample weights smoothing mechanism so as to avoid over-learning. Finally, the prediction of miRNA target integrated classifier is achieved with the combination of multiple weak classifiers through the voting mechanism. The experiment revealed that the SVM-IUSW, compared with other algorithms on unbalanced dataset collection, could not only improve the accuracy of positive targets and the overall effect of classification, but also enhance the generalization ability of miRNA target classifier.

Eco-efficience et analyse des couts du cycle de vie: Developpement d'un outil d'aide a la conception dans l'industrie aeronautique

NASA Astrophysics Data System (ADS)

Mami, Fares

The aeronautical sector, responsible for about 3 % of the world emissions of greenhouse gases, predict a 70 % growth in 2025 and 300 % to 500 % in 2050 of its emissions compared to the level of 2005. The decision-makers must thus be supported in their choice of conception to integrate the environmental aspect into the decision-making. Our industrial partner in the aeronautical sector developed an expertise in Life Cycle Assessment (LCA) and seeks to integrate the costs and the environmental impacts in a systematic way into the ecodesign of products. Based on the literature review and the objectives of this research we propose a model of eco-efficiency, which integrates LCA with Life Cycle Costing (LCC). This model is consistent with defined cost cutting and environmental impacts reduction targets and allows a simple interpretation of the results while minimizing the efforts during data collection. The model is applied for 3D printing as an alternative production process in the manufacturing of an aircraft blocker door. 3D printing is a new technology of production working by addition of material and present interesting opportunities of cost cutting and environmental impacts, particularly in the aeronautical domain. The results showed that 3D printing, when associated with improvement in the topology of the part, allows an improvement both on costs and environmental impacts of the part life cycle. Nevertheless, the results are sensitive to the productivity of the 3D printing machine, in particular with costs when the productivity of the 3D printing is reduced. This eco-efficiency model presents several opportunities of improvement. A more elaborate definition of the objectives in reduction of environmental impacts would allow to direct the choices in design to considerations of eco-efficiency at a macro level. Moreover, the integration of the social dimension in the model constitutes an important stage to operationalize the stakes of environmental and social responsibility of the company.

Identification of novel plant peroxisomal targeting signals by a combination of machine learning methods and in vivo subcellular targeting analyses.

PubMed

Lingner, Thomas; Kataya, Amr R; Antonicelli, Gerardo E; Benichou, Aline; Nilssen, Kjersti; Chen, Xiong-Yan; Siemsen, Tanja; Morgenstern, Burkhard; Meinicke, Peter; Reumann, Sigrun

2011-04-01

In the postgenomic era, accurate prediction tools are essential for identification of the proteomes of cell organelles. Prediction methods have been developed for peroxisome-targeted proteins in animals and fungi but are missing specifically for plants. For development of a predictor for plant proteins carrying peroxisome targeting signals type 1 (PTS1), we assembled more than 2500 homologous plant sequences, mainly from EST databases. We applied a discriminative machine learning approach to derive two different prediction methods, both of which showed high prediction accuracy and recognized specific targeting-enhancing patterns in the regions upstream of the PTS1 tripeptides. Upon application of these methods to the Arabidopsis thaliana genome, 392 gene models were predicted to be peroxisome targeted. These predictions were extensively tested in vivo, resulting in a high experimental verification rate of Arabidopsis proteins previously not known to be peroxisomal. The prediction methods were able to correctly infer novel PTS1 tripeptides, which even included novel residues. Twenty-three newly predicted PTS1 tripeptides were experimentally confirmed, and a high variability of the plant PTS1 motif was discovered. These prediction methods will be instrumental in identifying low-abundance and stress-inducible peroxisomal proteins and defining the entire peroxisomal proteome of Arabidopsis and agronomically important crop plants.

The Development and Calculation of an Energy-saving Plant for Obtaining Water from Atmospheric Air

NASA Astrophysics Data System (ADS)

Uglanov, D. A.; Zheleznyak, K. E.; Chertykovsev, P. A.

2018-01-01

The article shows the calculation of characteristics of energy-efficient water generator from atmospheric air. This installation or the atmospheric water generator is the unique mechanism which produces safe drinking water by extraction it from air. The existing atmospheric generators allow to receive safe drinking water by means of process of condensation at air humidity at least equal to 35% and are capable to give to 25 liters of water in per day, and work from electricity. Authors offer to use instead of the condenser in the scheme of installation for increase volume of produced water by generator in per day, the following refrigerating machines: the vapor compression refrigerating machines (VCRM), the thermoelectric refrigerating machines (TRM) and the Stirling-cycle refrigerating machines (SRM). The paper describes calculation methods for each of refrigerating systems. Calculation of technical-and-economic indexes for the atmospheric water generator was carried out and the optimum system with the maximum volume of received water in per day was picked up. The atmospheric water generator which is considered in article will work from autonomous solar power station.

Friction Laws Derived From the Acoustic Emissions of a Laboratory Fault by Machine Learning

NASA Astrophysics Data System (ADS)

Rouet-Leduc, B.; Hulbert, C.; Ren, C. X.; Bolton, D. C.; Marone, C.; Johnson, P. A.

2017-12-01

Fault friction controls nearly all aspects of fault rupture, yet it is only possible to measure in the laboratory. Here we describe laboratory experiments where acoustic emissions are recorded from the fault. We find that by applying a machine learning approach known as "extreme gradient boosting trees" to the continuous acoustical signal, the fault friction can be directly inferred, showing that instantaneous characteristics of the acoustic signal are a fingerprint of the frictional state. This machine learning-based inference leads to a simple law that links the acoustic signal to the friction state, and holds for every stress cycle the laboratory fault goes through. The approach does not use any other measured parameter than instantaneous statistics of the acoustic signal. This finding may have importance for inferring frictional characteristics from seismic waves in Earth where fault friction cannot be measured.

A Java-based enterprise system architecture for implementing a continuously supported and entirely Web-based exercise solution.

PubMed

Wang, Zhihui; Kiryu, Tohru

2006-04-01

Since machine-based exercise still uses local facilities, it is affected by time and place. We designed a web-based system architecture based on the Java 2 Enterprise Edition that can accomplish continuously supported machine-based exercise. In this system, exercise programs and machines are loosely coupled and dynamically integrated on the site of exercise via the Internet. We then extended the conventional health promotion model, which contains three types of players (users, exercise trainers, and manufacturers), by adding a new player: exercise program creators. Moreover, we developed a self-describing strategy to accommodate a variety of exercise programs and provide ease of use to users on the web. We illustrate our novel design with examples taken from our feasibility study on a web-based cycle ergometer exercise system. A biosignal-based workload control approach was introduced to ensure that users performed appropriate exercise alone.

DOE Office of Scientific and Technical Information (OSTI.GOV)

V.T. Krivoshein; A.V. Makarov

The sequence of pushing coke ovens is one of the most important aspects of battery operation. The sequence must satisfy a number of technical and process conditions: (1) achieve maximum heating-wall life by avoiding destructive expansion pressure in freshly charged ovens and during pushing of the finished coke; (2) ensure uniform brickwork temperature and prevent overheating by compensating for the high thermal flux in freshly charged ovens due to accumulated heat in adjacent ovens that are in the second half of the coking cycle; (3) ensure the most favorable working conditions and safety for operating personnel; (4) provide additional opportunitiesmore » for repair personnel to perform various types of work, such as replacing coke-machine rails, without interrupting coal production; (5) perform the maximum number of coke-machine operations simultaneously: pushing, charging, and cleaning doors, frames, and standpipe elbows; and (6) reduce electricity consumption by minimizing idle travel of coke machines.« less

Active vibration and balance system for closed cycle thermodynamic machines

NASA Technical Reports Server (NTRS)

Augenblick, John E. (Inventor); Peterson, Allen A. (Inventor); White, Maurice A. (Inventor); Qiu, Songgang (Inventor)

2004-01-01

An active balance system is provided for counterbalancing vibrations of an axially reciprocating machine. The balance system includes a support member, a flexure assembly, a counterbalance mass, and a linear motor or an actuator. The support member is configured for attachment to the machine. The flexure assembly includes at least one flat spring having connections along a central portion and an outer peripheral portion. One of the central portion and the outer peripheral portion is fixedly mounted to the support member. The counterbalance mass is fixedly carried by the flexure assembly along another of the central portion and the outer peripheral portion. The linear motor has one of a stator and a mover fixedly mounted to the support member and another of the stator and the mover fixedly mounted to the counterbalance mass. The linear motor is operative to axially reciprocate the counterbalance mass. A method is also provided.

Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites.

PubMed

Betel, Doron; Koppal, Anjali; Agius, Phaedra; Sander, Chris; Leslie, Christina

2010-01-01

mirSVR is a new machine learning method for ranking microRNA target sites by a down-regulation score. The algorithm trains a regression model on sequence and contextual features extracted from miRanda-predicted target sites. In a large-scale evaluation, miRanda-mirSVR is competitive with other target prediction methods in identifying target genes and predicting the extent of their downregulation at the mRNA or protein levels. Importantly, the method identifies a significant number of experimentally determined non-canonical and non-conserved sites.

Guidance for Soil Sampling for Energetics and Metals

DTIC Science & Technology

2011-10-01

from tracer rounds used in machine guns ), and polycyclic aromatic hydrocarbons (from clay targets and “wad- ding” from shotgun shells) (USEPA 2003a...Sieving .......................................................................................................................... 63  8.2.4  Machine ...Ampleman et al. 2009 Grenade 40-mmHEDP M2 NG 144 76 5 Walsh M.R. et al. 2010 40-mm TP F15080 NG 127 2.2 5 Small Arms 5.56-mm Rifle WC844 NG 100

MMRP Guidance Document for Soil Sampling of Energetics and Metals

DTIC Science & Technology

2011-10-01

from tracer rounds used in machine guns ), and polycyclic aromatic hydrocarbons (from clay targets and “wad- ding” from shotgun shells) (USEPA 2003a...Sieving .......................................................................................................................... 63  8.2.4  Machine ...Ampleman et al. 2009 Grenade 40-mmHEDP M2 NG 144 76 5 Walsh M.R. et al. 2010 40-mm TP F15080 NG 127 2.2 5 Small Arms 5.56-mm Rifle WC844 NG 100

Navy Acquisition: Development of the AN/BSY-1 Combat System

DTIC Science & Technology

1992-01-01

AN/BSY-1, a computer-based combat system, is designed to detect, classify, track, and launch weapons at enemy surface, subsurface, and land targets. The Navy expects the AN/BSY-1 system to locate targets sooner than previous systems, allow operators to perform multiple tasks and address multiple targets concurrently, and reduce the time between detecting a target and launching weapons. The Navy has contracted with the International Business Machines (IBM) Corporation for 23 AN/BSY-1 systems, maintenance and operational trainers, and a software

Rapid freeze-drying cycle optimization using computer programs developed based on heat and mass transfer models and facilitated by tunable diode laser absorption spectroscopy (TDLAS).

PubMed

Kuu, Wei Y; Nail, Steven L

2009-09-01

Computer programs in FORTRAN were developed to rapidly determine the optimal shelf temperature, T(f), and chamber pressure, P(c), to achieve the shortest primary drying time. The constraint for the optimization is to ensure that the product temperature profile, T(b), is below the target temperature, T(target). Five percent mannitol was chosen as the model formulation. After obtaining the optimal sets of T(f) and P(c), each cycle was assigned with a cycle rank number in terms of the length of drying time. Further optimization was achieved by dividing the drying time into a series of ramping steps for T(f), in a cascading manner (termed the cascading T(f) cycle), to further shorten the cycle time. For the purpose of demonstrating the validity of the optimized T(f) and P(c), four cycles with different predicted lengths of drying time, along with the cascading T(f) cycle, were chosen for experimental cycle runs. Tunable diode laser absorption spectroscopy (TDLAS) was used to continuously measure the sublimation rate. As predicted, maximum product temperatures were controlled slightly below the target temperature of -25 degrees C, and the cascading T(f)-ramping cycle is the most efficient cycle design. In addition, the experimental cycle rank order closely matches with that determined by modeling.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Randolph, Randall Blaine; Oertel, John A.; Schmidt, Derek William

For this study, machined CH hemi-shell ablator capsules have been successfully produced by the MST-7 Target Fabrication Team at Los Alamos National Laboratory. Process development and micro-machining techniques have been developed to produce capsules for both the Omega and National Ignition Facility (NIF) campaigns. These capsules are gas filled up to 10 atm and consist of a machined plastic hemi-shell outer layer that accommodates various specially engineered low-density polystyrene foam cores. Machining and assembly of the two-part, step-jointed plastic hemi-shell outer layer required development of new techniques, processes, and tooling while still meeting very aggressive shot schedules for both campaigns.more » Finally, problems encountered and process improvements will be discussed that describe this very unique, complex capsule design approach through the first Omega proof-of-concept version to the larger NIF version.« less

Secure Autonomous Automated Scheduling (SAAS). Rev. 1.1

NASA Technical Reports Server (NTRS)

Walke, Jon G.; Dikeman, Larry; Sage, Stephen P.; Miller, Eric M.

2010-01-01

This report describes network-centric operations, where a virtual mission operations center autonomously receives sensor triggers, and schedules space and ground assets using Internet-based technologies and service-oriented architectures. For proof-of-concept purposes, sensor triggers are received from the United States Geological Survey (USGS) to determine targets for space-based sensors. The Surrey Satellite Technology Limited (SSTL) Disaster Monitoring Constellation satellite, the UK-DMC, is used as the space-based sensor. The UK-DMC's availability is determined via machine-to-machine communications using SSTL's mission planning system. Access to/from the UK-DMC for tasking and sensor data is via SSTL's and Universal Space Network's (USN) ground assets. The availability and scheduling of USN's assets can also be performed autonomously via machine-to-machine communications. All communication, both on the ground and between ground and space, uses open Internet standards

Estimate for interstage water injection in air compressor incorporated into gas-turbine cycles and combined power plants cycles

NASA Astrophysics Data System (ADS)

Kler, A. M.; Zakharov, Yu. B.; Potanina, Yu. M.

2017-05-01

The objects of study are the gas turbine (GT) plant and combined cycle power plant (CCPP) with opportunity for injection between the stages of air compressor. The objective of this paper is technical and economy optimization calculations for these classes of plants with water interstage injection. The integrated development environment "System of machine building program" was a tool for creating the mathematic models for these classes of power plants. Optimization calculations with the criterion of minimum for specific capital investment as a function of the unit efficiency have been carried out. For a gas-turbine plant, the economic gain from water injection exists for entire range of power efficiency. For the combined cycle plant, the economic benefit was observed only for a certain range of plant's power efficiency.

Boosted Regression Trees Outperforms Support Vector Machines in Predicting (Regional) Yields of Winter Wheat from Single and Cumulated Dekadal Spot-VGT Derived Normalized Difference Vegetation Indices

NASA Astrophysics Data System (ADS)

Stas, Michiel; Dong, Qinghan; Heremans, Stien; Zhang, Beier; Van Orshoven, Jos

2016-08-01

This paper compares two machine learning techniques to predict regional winter wheat yields. The models, based on Boosted Regression Trees (BRT) and Support Vector Machines (SVM), are constructed of Normalized Difference Vegetation Indices (NDVI) derived from low resolution SPOT VEGETATION satellite imagery. Three types of NDVI-related predictors were used: Single NDVI, Incremental NDVI and Targeted NDVI. BRT and SVM were first used to select features with high relevance for predicting the yield. Although the exact selections differed between the prefectures, certain periods with high influence scores for multiple prefectures could be identified. The same period of high influence stretching from March to June was detected by both machine learning methods. After feature selection, BRT and SVM models were applied to the subset of selected features for actual yield forecasting. Whereas both machine learning methods returned very low prediction errors, BRT seems to slightly but consistently outperform SVM.

Pricing and Availability Intervention in Vending Machines at Four Bus Garages

PubMed Central

Hannan, Peter J; Harnack, Lisa J; Mitchell, Nathan R; Toomey, Traci L; Gerlach, Anne

2009-01-01

Objective To evaluate the effects of lowering prices and increasing availability on sales of healthy foods and beverages from 33 vending machines in four bus garages as part of a multi-component worksite obesity prevention intervention. Methods Availability of healthy items was increased to 50% and prices were lowered at least 10% in the vending machines in two metropolitan bus garages for an 18-month period. Two control garages offered vending choices at usual availability and prices. Sales data were collected monthly from each of the vending machines at the four garages. Results Increases in availability to 50% and price reductions of an average of 31% resulted in 10-42% higher sales of the healthy items. Employees were most price-responsive for snack purchases. Conclusions Greater availability and lower prices on targeted food and beverage items from vending machines was associated with greater purchases of these items over an eighteen-month period. Efforts to promote healthful food purchases in worksite settings should incorporate these two strategies. PMID:20061884

Pricing and availability intervention in vending machines at four bus garages.

PubMed

French, Simone A; Hannan, Peter J; Harnack, Lisa J; Mitchell, Nathan R; Toomey, Traci L; Gerlach, Anne

2010-01-01

To evaluate the effects of lowering prices and increasing availability on sales of healthy foods and beverages from 33 vending machines in 4 bus garages as part of a multicomponent worksite obesity prevention intervention. Availability of healthy items was increased to 50% and prices were lowered at least 10% in the vending machines in two metropolitan bus garages for an 18-month period. Two control garages offered vending choices at usual availability and prices. Sales data were collected monthly from each of the vending machines at the four garages. Increases in availability to 50% and price reductions of an average of 31% resulted in 10% to 42% higher sales of the healthy items. Employees were mostly price responsive for snack purchases. Greater availability and lower prices on targeted food and beverage items from vending machines was associated with greater purchases of these items over an 18-month period. Efforts to promote healthful food purchases in worksite settings should incorporate these two strategies.

Target attribute-based false alarm rejection in small infrared target detection

NASA Astrophysics Data System (ADS)

Kim, Sungho

2012-11-01

Infrared search and track is an important research area in military applications. Although there are a lot of works on small infrared target detection methods, we cannot apply them in real field due to high false alarm rate caused by clutters. This paper presents a novel target attribute extraction and machine learning-based target discrimination method. Eight kinds of target features are extracted and analyzed statistically. Learning-based classifiers such as SVM and Adaboost are developed and compared with conventional classifiers for real infrared images. In addition, the generalization capability is also inspected for various infrared clutters.

Improved detection of chemical substances from colorimetric sensor data using probabilistic machine learning

NASA Astrophysics Data System (ADS)

Mølgaard, Lasse L.; Buus, Ole T.; Larsen, Jan; Babamoradi, Hamid; Thygesen, Ida L.; Laustsen, Milan; Munk, Jens Kristian; Dossi, Eleftheria; O'Keeffe, Caroline; Lässig, Lina; Tatlow, Sol; Sandström, Lars; Jakobsen, Mogens H.

2017-05-01

We present a data-driven machine learning approach to detect drug- and explosives-precursors using colorimetric sensor technology for air-sampling. The sensing technology has been developed in the context of the CRIM-TRACK project. At present a fully- integrated portable prototype for air sampling with disposable sensing chips and automated data acquisition has been developed. The prototype allows for fast, user-friendly sampling, which has made it possible to produce large datasets of colorimetric data for different target analytes in laboratory and simulated real-world application scenarios. To make use of the highly multi-variate data produced from the colorimetric chip a number of machine learning techniques are employed to provide reliable classification of target analytes from confounders found in the air streams. We demonstrate that a data-driven machine learning method using dimensionality reduction in combination with a probabilistic classifier makes it possible to produce informative features and a high detection rate of analytes. Furthermore, the probabilistic machine learning approach provides a means of automatically identifying unreliable measurements that could produce false predictions. The robustness of the colorimetric sensor has been evaluated in a series of experiments focusing on the amphetamine pre-cursor phenylacetone as well as the improvised explosives pre-cursor hydrogen peroxide. The analysis demonstrates that the system is able to detect analytes in clean air and mixed with substances that occur naturally in real-world sampling scenarios. The technology under development in CRIM-TRACK has the potential as an effective tool to control trafficking of illegal drugs, explosive detection, or in other law enforcement applications.

More complete gene silencing by fewer siRNAs: transparent optimized design and biophysical signature

PubMed Central

Ladunga, Istvan

2007-01-01

Highly accurate knockdown functional analyses based on RNA interference (RNAi) require the possible most complete hydrolysis of the targeted mRNA while avoiding the degradation of untargeted genes (off-target effects). This in turn requires significant improvements to target selection for two reasons. First, the average silencing activity of randomly selected siRNAs is as low as 62%. Second, applying more than five different siRNAs may lead to saturation of the RNA-induced silencing complex (RISC) and to the degradation of untargeted genes. Therefore, selecting a small number of highly active siRNAs is critical for maximizing knockdown and minimizing off-target effects. To satisfy these needs, a publicly available and transparent machine learning tool is presented that ranks all possible siRNAs for each targeted gene. Support vector machines (SVMs) with polynomial kernels and constrained optimization models select and utilize the most predictive effective combinations from 572 sequence, thermodynamic, accessibility and self-hairpin features over 2200 published siRNAs. This tool reaches an accuracy of 92.3% in cross-validation experiments. We fully present the underlying biophysical signature that involves free energy, accessibility and dinucleotide characteristics. We show that while complete silencing is possible at certain structured target sites, accessibility information improves the prediction of the 90% active siRNA target sites. Fast siRNA activity predictions can be performed on our web server at . PMID:17169992

Combinatorial support vector machines approach for virtual screening of selective multi-target serotonin reuptake inhibitors from large compound libraries.

PubMed

Shi, Z; Ma, X H; Qin, C; Jia, J; Jiang, Y Y; Tan, C Y; Chen, Y Z

2012-02-01

Selective multi-target serotonin reuptake inhibitors enhance antidepressant efficacy. Their discovery can be facilitated by multiple methods, including in silico ones. In this study, we developed and tested an in silico method, combinatorial support vector machines (COMBI-SVMs), for virtual screening (VS) multi-target serotonin reuptake inhibitors of seven target pairs (serotonin transporter paired with noradrenaline transporter, H(3) receptor, 5-HT(1A) receptor, 5-HT(1B) receptor, 5-HT(2C) receptor, melanocortin 4 receptor and neurokinin 1 receptor respectively) from large compound libraries. COMBI-SVMs trained with 917-1951 individual target inhibitors correctly identified 22-83.3% (majority >31.1%) of the 6-216 dual inhibitors collected from literature as independent testing sets. COMBI-SVMs showed moderate to good target selectivity in misclassifying as dual inhibitors 2.2-29.8% (majority <15.4%) of the individual target inhibitors of the same target pair and 0.58-7.1% of the other 6 targets outside the target pair. COMBI-SVMs showed low dual inhibitor false hit rates (0.006-0.056%, 0.042-0.21%, 0.2-4%) in screening 17 million PubChem compounds, 168,000 MDDR compounds, and 7-8181 MDDR compounds similar to the dual inhibitors. Compared with similarity searching, k-NN and PNN methods, COMBI-SVM produced comparable dual inhibitor yields, similar target selectivity, and lower false hit rate in screening 168,000 MDDR compounds. The annotated classes of many COMBI-SVMs identified MDDR virtual hits correlate with the reported effects of their predicted targets. COMBI-SVM is potentially useful for searching selective multi-target agents without explicit knowledge of these agents. Copyright © 2011 Elsevier Inc. All rights reserved.

Novel fabrication method for zirconia restorations: bonding strength of machinable ceramic to zirconia with resin cements.

PubMed

Kuriyama, Soichi; Terui, Yuichi; Higuchi, Daisuke; Goto, Daisuke; Hotta, Yasuhiro; Manabe, Atsufumi; Miyazaki, Takashi

2011-01-01

A novel method was developed to fabricate all-ceramic restorations which comprised CAD/CAM-fabricated machinable ceramic bonded to CAD/CAM-fabricated zirconia framework using resin cement. The feasibility of this fabrication method was assessed in this study by investigating the bonding strength of a machinable ceramic to zirconia. A machinable ceramic was bonded to a zirconia plate using three kinds of resin cements: ResiCem (RE), Panavia (PA), and Multilink (ML). Conventional porcelain-fused-to-zirconia specimens were also prepared to serve as control. Shear bond strength test (SBT) and Schwickerath crack initiation test (SCT) were carried out. SBT revealed that PA (40.42 MPa) yielded a significantly higher bonding strength than RE (28.01 MPa) and ML (18.89 MPa). SCT revealed that the bonding strengths of test groups using resin cement were significantly higher than those of Control. Notably, the bonding strengths of RE and ML were above 25 MPa even after 10,000 times of thermal cycling -adequately meeting the ISO 9693 standard for metal-ceramic restorations. These results affirmed the feasibility of the novel fabrication method, in that a CAD/CAM-fabricated machinable ceramic is bonded to a CAD/CAM-fabricated zirconia framework using a resin cement.

e-Learning Application for Machine Maintenance Process using Iterative Method in XYZ Company

NASA Astrophysics Data System (ADS)

Nurunisa, Suaidah; Kurniawati, Amelia; Pramuditya Soesanto, Rayinda; Yunan Kurnia Septo Hediyanto, Umar

2016-02-01

XYZ Company is a company based on manufacturing part for airplane, one of the machine that is categorized as key facility in the company is Millac 5H6P. As a key facility, the machines should be assured to work well and in peak condition, therefore, maintenance process is needed periodically. From the data gathering, it is known that there are lack of competency from the maintenance staff to maintain different type of machine which is not assigned by the supervisor, this indicate that knowledge which possessed by maintenance staff are uneven. The purpose of this research is to create knowledge-based e-learning application as a realization from externalization process in knowledge transfer process to maintain the machine. The application feature are adjusted for maintenance purpose using e-learning framework for maintenance process, the content of the application support multimedia for learning purpose. QFD is used in this research to understand the needs from user. The application is built using moodle with iterative method for software development cycle and UML Diagram. The result from this research is e-learning application as sharing knowledge media for maintenance staff in the company. From the test, it is known that the application make maintenance staff easy to understand the competencies.

Soil Nutrient Stocks in Sub-Saharan Africa: Modeling Soil Nutrients Using Machine Learning

NASA Astrophysics Data System (ADS)

Cooper, M. W.; Hengl, T.; Shepherd, K.; Heuvelink, G. B. M.

2017-12-01

We present the results of our work modeling 15 target soil nutrients at 250 meter resolution across Sub-Saharan Africa. We used a large stack of GIS layers as covariates, including layers on topography, climate, geology, hydrology and land cover. As training data we used ca. 59,000 soil samples harmonized across a number of projects and datasets, and we modeled each nutrient using an ensemble of random forest and gradient boosting algorithms, implemented using the R packages ranger and xgboost. Using cross validation, we determined that significant models can be produced for organic Carbon, total (organic) Nitrogen, total Phosphorus, and extractable Phosphorous, Potassium, Calcium, Magnesium, Sulfur, Sodium, Iron, Manganese, Zinc, Copper, Aluminum and Boron, with an R-square value between 40 and 95%. The main covariates explaining spatial distribution of nutrients were precipitation and land form parameters. However, we were unable to significantly predict Sulfur, Phosphorus and Boron as these could not be correlated with any environmental covariates we used. Although the accuracy of predictions looks promising, our predictions likely suffer from the significant spatial clustering of the sampling locations, as well as a lack of more detailed data on geology and parent material at a continental scale. These results will contribute to targeting agricultural investments and interventions, as well as targeting restoration efforts and estimating yield potential and yield gaps. These results were recently published in the journal Nutrient Cycling in Agroecosystems (DOI: 10.1007/s10705-017-9870-x) and the maps are available for download under the ODC Open Database License.

Automated Composites Processing Technology: Film Module

NASA Technical Reports Server (NTRS)

Hulcher, A. Bruce

2004-01-01

NASA's Marshall Space Flight Center (MSFC) has developed a technology that combines a film/adhesive laydown module with fiber placement technology to enable the processing of composite prepreg tow/tape and films, foils or adhesives on the same placement machine. The development of this technology grew out of NASA's need for lightweight, permeation-resistant cryogenic propellant tanks. Autoclave processing of high performance composites results in thermally-induced stresses due to differences in the coefficients of thermal expansion of the fiber and matrix resin components. These stresses, together with the reduction in temperature due to cryogen storage, tend to initiate microcracking within the composite tank wall. One way in which to mitigate this problem is to introduce a thin, crack-resistant polymer film or foil into the tank wall. Investigation into methods to automate the processing of thin film or foil materials into composites led to the development of this technology. The concept employs an automated film supply and feed module that may be designed to fit existing fiber placement machines, or may be designed as integral equipment to new machines. This patent-pending technology can be designed such that both film and foil materials may be processed simultaneously, leading to a decrease in part build cycle time. The module may be designed having a compaction device independent of the host machine, or may utilize the host machine's compactor. The film module functions are controlled by a dedicated system independent of the fiber placement machine controls. The film, foil, or adhesive is processed via pre-existing placement machine run programs, further reducing operational expense.

Genome-wide prediction and analysis of human tissue-selective genes using microarray expression data

PubMed Central

2013-01-01

Background Understanding how genes are expressed specifically in particular tissues is a fundamental question in developmental biology. Many tissue-specific genes are involved in the pathogenesis of complex human diseases. However, experimental identification of tissue-specific genes is time consuming and difficult. The accurate predictions of tissue-specific gene targets could provide useful information for biomarker development and drug target identification. Results In this study, we have developed a machine learning approach for predicting the human tissue-specific genes using microarray expression data. The lists of known tissue-specific genes for different tissues were collected from UniProt database, and the expression data retrieved from the previously compiled dataset according to the lists were used for input vector encoding. Random Forests (RFs) and Support Vector Machines (SVMs) were used to construct accurate classifiers. The RF classifiers were found to outperform SVM models for tissue-specific gene prediction. The results suggest that the candidate genes for brain or liver specific expression can provide valuable information for further experimental studies. Our approach was also applied for identifying tissue-selective gene targets for different types of tissues. Conclusions A machine learning approach has been developed for accurately identifying the candidate genes for tissue specific/selective expression. The approach provides an efficient way to select some interesting genes for developing new biomedical markers and improve our knowledge of tissue-specific expression. PMID:23369200

Improving Domain-specific Machine Translation by Constraining the Language Model

DTIC Science & Technology

2012-07-01

performance. To make up for the lack of parallel training data, one assumption is that more monolingual target language data should be used in building the...target language model. Prior work on domain-specific MT has focused on training target language models with monolingual 2 domain-specific data...showed that the using a large dictionary extracted from medical domain documents in a statistical MT system to generalize the training data significantly

Categorical vowel perception enhances the effectiveness and generalization of auditory feedback in human-machine-interfaces.

PubMed

Larson, Eric; Terry, Howard P; Canevari, Margaux M; Stepp, Cara E

2013-01-01

Human-machine interface (HMI) designs offer the possibility of improving quality of life for patient populations as well as augmenting normal user function. Despite pragmatic benefits, utilizing auditory feedback for HMI control remains underutilized, in part due to observed limitations in effectiveness. The goal of this study was to determine the extent to which categorical speech perception could be used to improve an auditory HMI. Using surface electromyography, 24 healthy speakers of American English participated in 4 sessions to learn to control an HMI using auditory feedback (provided via vowel synthesis). Participants trained on 3 targets in sessions 1-3 and were tested on 3 novel targets in session 4. An "established categories with text cues" group of eight participants were trained and tested on auditory targets corresponding to standard American English vowels using auditory and text target cues. An "established categories without text cues" group of eight participants were trained and tested on the same targets using only auditory cuing of target vowel identity. A "new categories" group of eight participants were trained and tested on targets that corresponded to vowel-like sounds not part of American English. Analyses of user performance revealed significant effects of session and group (established categories groups and the new categories group), and a trend for an interaction between session and group. Results suggest that auditory feedback can be effectively used for HMI operation when paired with established categorical (native vowel) targets with an unambiguous cue.

The seasonal-cycle climate model

NASA Technical Reports Server (NTRS)

Marx, L.; Randall, D. A.

1981-01-01

The seasonal cycle run which will become the control run for the comparison with runs utilizing codes and parameterizations developed by outside investigators is discussed. The climate model currently exists in two parallel versions: one running on the Amdahl and the other running on the CYBER 203. These two versions are as nearly identical as machine capability and the requirement for high speed performance will allow. Developmental changes are made on the Amdahl/CMS version for ease of testing and rapidity of turnaround. The changes are subsequently incorporated into the CYBER 203 version using vectorization techniques where speed improvement can be realized. The 400 day seasonal cycle run serves as a control run for both medium and long range climate forecasts alsensitivity studies.

Short term evaluation of harvesting systems for ecosystem management

Treesearch

Michael D. Erickson; Penn Peters; Curt Hassler

1995-01-01

Continuous time/motion studies have traditionally been the basis for productivity estimates of timber harvesting systems. The detailed data from such studies permits the researcher or analyst to develop mathematical relationships based on stand, system, and stem attributes for describing machine cycle times. The resulting equation(s) allow the analyst to estimate...

3 CFR 13642 - Executive Order 13642 of May 9, 2013. Making Open and Machine Readable the New Default for...

Code of Federal Regulations, 2014 CFR

2014-01-01

..., innovation, and scientific discovery that improves Americans' lives and contributes significantly to job... tools, and much more, improving Americans' lives in countless ways and leading to economic growth and... as an asset throughout its life cycle to promote interoperability and openness, and, wherever...

Applications of Support Vector Machine (SVM) Learning in Cancer Genomics

PubMed Central

HUANG, SHUJUN; CAI, NIANGUANG; PACHECO, PEDRO PENZUTI; NARANDES, SHAVIRA; WANG, YANG; XU, WAYNE

2017-01-01

Machine learning with maximization (support) of separating margin (vector), called support vector machine (SVM) learning, is a powerful classification tool that has been used for cancer genomic classification or subtyping. Today, as advancements in high-throughput technologies lead to production of large amounts of genomic and epigenomic data, the classification feature of SVMs is expanding its use in cancer genomics, leading to the discovery of new biomarkers, new drug targets, and a better understanding of cancer driver genes. Herein we reviewed the recent progress of SVMs in cancer genomic studies. We intend to comprehend the strength of the SVM learning and its future perspective in cancer genomic applications. PMID:29275361

Single-Molecule Real-Time 3D Imaging of the Transcription Cycle by Modulation Interferometry.

PubMed

Wang, Guanshi; Hauver, Jesse; Thomas, Zachary; Darst, Seth A; Pertsinidis, Alexandros

2016-12-15

Many essential cellular processes, such as gene control, employ elaborate mechanisms involving the coordination of large, multi-component molecular assemblies. Few structural biology tools presently have the combined spatial-temporal resolution and molecular specificity required to capture the movement, conformational changes, and subunit association-dissociation kinetics, three fundamental elements of how such intricate molecular machines work. Here, we report a 3D single-molecule super-resolution imaging study using modulation interferometry and phase-sensitive detection that achieves <2 nm axial localization precision, well below the few-nanometer-sized individual protein components. To illustrate the capability of this technique in probing the dynamics of complex macromolecular machines, we visualize the movement of individual multi-subunit E. coli RNA polymerases through the complete transcription cycle, dissect the kinetics of the initiation-elongation transition, and determine the fate of σ 70 initiation factors during promoter escape. Modulation interferometry sets the stage for single-molecule studies of several hitherto difficult-to-investigate multi-molecular transactions that underlie genome regulation. Copyright © 2016 Elsevier Inc. All rights reserved.

The Molecular Industrial Revolution: Automated Synthesis of Small Molecules.

PubMed

Trobe, Melanie; Burke, Martin D

2018-04-09

Today we are poised for a transition from the highly customized crafting of specific molecular targets by hand to the increasingly general and automated assembly of different types of molecules with the push of a button. Creating machines that are capable of making many different types of small molecules on demand, akin to that which has been achieved on the macroscale with 3D printers, is challenging. Yet important progress is being made toward this objective with two complementary approaches: 1) Automation of customized synthesis routes to different targets by machines that enable the use of many reactions and starting materials, and 2) automation of generalized platforms that make many different targets using common coupling chemistry and building blocks. Continued progress in these directions has the potential to shift the bottleneck in molecular innovation from synthesis to imagination, and thereby help drive a new industrial revolution on the molecular scale. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

NASA Astrophysics Data System (ADS)

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.

First experimental evidence of hydrodynamic tunneling of ultra-relativistic protons in extended solid copper target at the CERN HiRadMat facility

NASA Astrophysics Data System (ADS)

Schmidt, R.; Blanco Sancho, J.; Burkart, F.; Grenier, D.; Wollmann, D.; Tahir, N. A.; Shutov, A.; Piriz, A. R.

2014-08-01

A novel experiment has been performed at the CERN HiRadMat test facility to study the impact of the 440 GeV proton beam generated by the Super Proton Synchrotron on extended solid copper cylindrical targets. Substantial hydrodynamic tunneling of the protons in the target material has been observed that leads to significant lengthening of the projectile range, which confirms our previous theoretical predictions [N. A. Tahir et al., Phys. Rev. Spec. Top.-Accel. Beams 15, 051003 (2012)]. Simulation results show very good agreement with the experimental measurements. These results have very important implications on the machine protection design for powerful machines like the Large Hadron Collider (LHC), the future High Luminosity LHC, and the proposed huge 80 km circumference Future Circular Collider, which is currently being discussed at CERN. Another very interesting outcome of this work is that one may also study the field of High Energy Density Physics at this test facility.

Stride-Cycle Influences on Goal-Directed Head Movements Made During Walking

NASA Technical Reports Server (NTRS)

Peters, Brian T.; vanEmmerik, Richard E. A.; Bloomberg, Jacob J.

2006-01-01

Horizontal head movements were studied in six subjects as they made rapid horizontal gaze adjustments while walking. The aim of the present research was to determine if gait-cycle events alter the head movement response to a visual target acquisition task. Gaze shifts of approximately 40deg were elicited by a step change in the position of a visual target from a central location to a second location in the left or right horizontal periphery. The timing of the target position change was constrained to occur at 25,50,75 and 100% of the stride cycle. The trials were randomly presented as the subjects walked on a treadmill at their preferred speed (range: 1.25 to 1.48 m/s, mean: 1.39 +/- 0.09 m/s ) . Analyses focused on the movement onset latencies of the head and eyes and on the peak velocity and saccade amplitude of the head movement response. A comparison of the group means indicated that the head movement onset lagged the eye onset (262 ms versus 252 ms). The head and eye movement onset latencies were not affected by either the direction of the target change nor the point in the gait cycle during which the target relocation occurred. However, the presence of an interaction between the gait cycle events and the direction of the visual target shift indicates that the peak head saccade velocity and head saccade amplitude are affected by the natural head oscillations that occur while walking.

Feasibility Study of Jupiter Icy Moons Orbiter Permanent Magnet Alternator Start Sequence

NASA Technical Reports Server (NTRS)

Kenny, Barbara H.; Tokars, Roger P.

2006-01-01

The Jupiter Icy Moons Orbiter (JIMO) mission was a proposed, (recently cancelled) long duration science mission to study three moons of Jupiter: Callisto, Ganymede, and Europa. One design of the JIMO spacecraft used a nuclear heat source in conjunction with a Brayton rotating machine to generate electrical power for the electric thrusters and the spacecraft bus. The basic operation of the closed cycle Brayton system was as follows. The working fluid, a heliumxenon gas mixture, first entered a compressor, then went through a recuperator and hot-side heat exchanger, then expanded across a turbine that drove an alternator, then entered the cold-side of the recuperator and heat exchanger and finally returned to the compressor. The spacecraft was to be launched with the Brayton system off-line and the nuclear reactor shut down. Once the system was started, the helium-xenon gas would be circulated into the heat exchangers as the nuclear reactors were activated. Initially, the alternator unit would operate as a motor so as to drive the turbine and compressor to get the cycle started. This report investigated the feasibility of the start up sequence of a permanent magnet (PM) machine, similar in operation to the alternator unit, without any position or speed feedback sensors ("sensorless") and with a variable load torque. It is found that the permanent magnet machine can start with sensorless control and a load torque of up to 30 percent of the rated value.

Membrane Fusion Proteins as Nanomachines

NASA Astrophysics Data System (ADS)

Tamm, Lukas

2009-03-01

Membrane fusion is key to fertilization, virus infection, and neurotransmission. Specific proteins work like nanomachines to stitch together fluid, yet highly ordered lipid bilayers. The energy gained from large exothermic conformational changes of these proteins is utilized to fuse lipid bilayers that do not fuse spontaneously. Structural studies using x-ray crystallography and NMR spectroscopy have yielded detailed information about architecture and inner workings of these molecular machines. The question now is: how is mechanical energy gained from such protein transformations harnessed to transform membrane topology? To answer this question, we have determined that a boomerang-shaped structure of the influenza fusion peptide is critical to generate a high-energy binding intermediate in the target membrane and to return the ``boomerang'' to its place of release near the viral membrane for completion of the fusion cycle. In presynaptic exocytosis, receptor and acceptor SNAREs are zippered to form a helical bundle that is arrested shortly before the membrane. Ca binding to interlocked synaptotagmin releases the fusion block. Structural NMR and single molecule fluorescence data are combined to arrive at and further refine this picture.

Spin dynamics modeling in the AGS based on a stepwise ray-tracing method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dutheil, Yann

The AGS provides a polarized proton beam to RHIC. The beam is accelerated in the AGS from Gγ= 4.5 to Gγ = 45.5 and the polarization transmission is critical to the RHIC spin program. In the recent years, various systems were implemented to improve the AGS polarization transmission. These upgrades include the double partial snakes configuration and the tune jumps system. However, 100% polarization transmission through the AGS acceleration cycle is not yet reached. The current efficiency of the polarization transmission is estimated to be around 85% in typical running conditions. Understanding the sources of depolarization in the AGS ismore » critical to improve the AGS polarized proton performances. The complexity of beam and spin dynamics, which is in part due to the specialized Siberian snake magnets, drove a strong interest for original methods of simulations. For that, the Zgoubi code, capable of direct particle and spin tracking through field maps, was here used to model the AGS. A model of the AGS using the Zgoubi code was developed and interfaced with the current system through a simple command: the AgsFromSnapRampCmd. Interfacing with the machine control system allows for fast modelization using actual machine parameters. Those developments allowed the model to realistically reproduce the optics of the AGS along the acceleration ramp. Additional developments on the Zgoubi code, as well as on post-processing and pre-processing tools, granted long term multiturn beam tracking capabilities: the tracking of realistic beams along the complete AGS acceleration cycle. Beam multiturn tracking simulations in the AGS, using realistic beam and machine parameters, provided a unique insight into the mechanisms behind the evolution of the beam emittance and polarization during the acceleration cycle. Post-processing softwares were developed to allow the representation of the relevant quantities from the Zgoubi simulations data. The Zgoubi simulations proved particularly useful to better understand the polarization losses through horizontal intrinsic spin resonances The Zgoubi model as well as the tools developed were also used for some direct applications. For instance, some beam experiment simulations allowed an accurate estimation of the expected polarization gains from machine changes. In particular, the simulations that involved involved the tune jumps system provided an accurate estimation of polarization gains and the optimum settings that would improve the performance of the AGS.« less

Cycle simulation of the low-temperature triple-effect absorption chiller with vapor compression unit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, J.S.; Lee, H.

1999-07-01

The construction of a triple-effect absorption chiller machine using the lithium bromide-water solution as a working fluid is strongly limited by corrosion problems caused by the high generator temperature. In this work, three new cycles having the additional vapor compression units were suggested in order to lower the generator temperature of a triple-effect absorption chiller. Each new cycle has one compressor located at the different position which was used to elevate the pressure of the refrigerant vapor. Computer simulations were carried out in order to examine both the basic triple-effect cycle and three new cycles. All types of triple-effect absorptionmore » chiller cycles were found to be able to lower the temperature of high-temperature generator to the more favorable operation range. The COPs of three cycles calculated by considering the additional compressor works showed a small level of decrease or increase compared with that of the basic triple-effect cycle. Consequently, a low-temperature triple-effect absorption chiller can be possibly constructed by adapting one of three new cycles. A great advantage of these new cycles over the basic one is that the conventionally used lithium bromide-water solution can be successfully used as a working fluid without the danger of corrosion.« less

Quantum annealing versus classical machine learning applied to a simplified computational biology problem

PubMed Central

Li, Richard Y.; Di Felice, Rosa; Rohs, Remo; Lidar, Daniel A.

2018-01-01

Transcription factors regulate gene expression, but how these proteins recognize and specifically bind to their DNA targets is still debated. Machine learning models are effective means to reveal interaction mechanisms. Here we studied the ability of a quantum machine learning approach to predict binding specificity. Using simplified datasets of a small number of DNA sequences derived from actual binding affinity experiments, we trained a commercially available quantum annealer to classify and rank transcription factor binding. The results were compared to state-of-the-art classical approaches for the same simplified datasets, including simulated annealing, simulated quantum annealing, multiple linear regression, LASSO, and extreme gradient boosting. Despite technological limitations, we find a slight advantage in classification performance and nearly equal ranking performance using the quantum annealer for these fairly small training data sets. Thus, we propose that quantum annealing might be an effective method to implement machine learning for certain computational biology problems. PMID:29652405

Progress Toward Fabrication of Machined Metal Shells for the First Double-Shell Implosions at the National Ignition Facility

DOE PAGES

Cardenas, Tana; Schmidt, Derek W.; Loomis, Eric N.; ...

2018-01-25

The double-shell platform fielded at the National Ignition Facility requires developments in new machining techniques and robotic assembly stations to meet the experimental specifications. Current double-shell target designs use a dense high-Z inner shell, a foam cushion, and a low-Z outer shell. The design requires that the inner shell be gas filled using a fill tube. This tube impacts the entire machining and assembly design. Other intermediate physics designs have to be fielded to answer physics questions and advance the technology to be able to fabricate the full point design in the near future. One of these intermediate designs ismore » a mid-Z imaging design. The methods of designing, fabricating, and characterizing each of the major components of an imaging double shell are discussed with an emphasis on the fabrication of the machined outer metal shell.« less

Progress Toward Fabrication of Machined Metal Shells for the First Double-Shell Implosions at the National Ignition Facility

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cardenas, Tana; Schmidt, Derek W.; Loomis, Eric N.

The double-shell platform fielded at the National Ignition Facility requires developments in new machining techniques and robotic assembly stations to meet the experimental specifications. Current double-shell target designs use a dense high-Z inner shell, a foam cushion, and a low-Z outer shell. The design requires that the inner shell be gas filled using a fill tube. This tube impacts the entire machining and assembly design. Other intermediate physics designs have to be fielded to answer physics questions and advance the technology to be able to fabricate the full point design in the near future. One of these intermediate designs ismore » a mid-Z imaging design. The methods of designing, fabricating, and characterizing each of the major components of an imaging double shell are discussed with an emphasis on the fabrication of the machined outer metal shell.« less

Virtual Mission Operations of Remote Sensors With Rapid Access To and From Space

NASA Technical Reports Server (NTRS)

Ivancic, William D.; Stewart, Dave; Walke, Jon; Dikeman, Larry; Sage, Steven; Miller, Eric; Northam, James; Jackson, Chris; Taylor, John; Lynch, Scott;

MultiMiTar: a novel multi objective optimization based miRNA-target prediction method.

PubMed

Mitra, Ramkrishna; Bandyopadhyay, Sanghamitra

2011-01-01

Machine learning based miRNA-target prediction algorithms often fail to obtain a balanced prediction accuracy in terms of both sensitivity and specificity due to lack of the gold standard of negative examples, miRNA-targeting site context specific relevant features and efficient feature selection process. Moreover, all the sequence, structure and machine learning based algorithms are unable to distribute the true positive predictions preferentially at the top of the ranked list; hence the algorithms become unreliable to the biologists. In addition, these algorithms fail to obtain considerable combination of precision and recall for the target transcripts that are translationally repressed at protein level. In the proposed article, we introduce an efficient miRNA-target prediction system MultiMiTar, a Support Vector Machine (SVM) based classifier integrated with a multiobjective metaheuristic based feature selection technique. The robust performance of the proposed method is mainly the result of using high quality negative examples and selection of biologically relevant miRNA-targeting site context specific features. The features are selected by using a novel feature selection technique AMOSA-SVM, that integrates the multi objective optimization technique Archived Multi-Objective Simulated Annealing (AMOSA) and SVM. MultiMiTar is found to achieve much higher Matthew's correlation coefficient (MCC) of 0.583 and average class-wise accuracy (ACA) of 0.8 compared to the others target prediction methods for a completely independent test data set. The obtained MCC and ACA values of these algorithms range from -0.269 to 0.155 and 0.321 to 0.582, respectively. Moreover, it shows a more balanced result in terms of precision and sensitivity (recall) for the translationally repressed data set as compared to all the other existing methods. An important aspect is that the true positive predictions are distributed preferentially at the top of the ranked list that makes MultiMiTar reliable for the biologists. MultiMiTar is now available as an online tool at www.isical.ac.in/~bioinfo_miu/multimitar.htm. MultiMiTar software can be downloaded from www.isical.ac.in/~bioinfo_miu/multimitar-download.htm.

Extreme ultraviolet lithography machine

DOEpatents

Tichenor, Daniel A.; Kubiak, Glenn D.; Haney, Steven J.; Sweeney, Donald W.

2000-01-01

An extreme ultraviolet lithography (EUVL) machine or system for producing integrated circuit (IC) components, such as transistors, formed on a substrate. The EUVL machine utilizes a laser plasma point source directed via an optical arrangement onto a mask or reticle which is reflected by a multiple mirror system onto the substrate or target. The EUVL machine operates in the 10-14 nm wavelength soft x-ray photon. Basically the EUV machine includes an evacuated source chamber, an evacuated main or project chamber interconnected by a transport tube arrangement, wherein a laser beam is directed into a plasma generator which produces an illumination beam which is directed by optics from the source chamber through the connecting tube, into the projection chamber, and onto the reticle or mask, from which a patterned beam is reflected by optics in a projection optics (PO) box mounted in the main or projection chamber onto the substrate. In one embodiment of a EUVL machine, nine optical components are utilized, with four of the optical components located in the PO box. The main or projection chamber includes vibration isolators for the PO box and a vibration isolator mounting for the substrate, with the main or projection chamber being mounted on a support structure and being isolated.

Inertial aided cycle slip detection and identification for integrated PPP GPS and INS.

PubMed

Du, Shuang; Gao, Yang

2012-10-25

The recently developed integrated Precise Point Positioning (PPP) GPS/INS system can be useful to many applications, such as UAV navigation systems, land vehicle/machine automation and mobile mapping systems. Since carrier phase measurements are the primary observables in PPP GPS, cycle slips, which often occur due to high dynamics, signal obstructions and low satellite elevation, must be detected and repaired in order to ensure the navigation performance. In this research, a new algorithm of cycle slip detection and identification has been developed. With the aiding from INS, the proposed method jointly uses WL and EWL phase combinations to uniquely determine cycle slips in the L1 and L2 frequencies. To verify the efficiency of the algorithm, both tactical-grade and consumer-grade IMUs are tested by using a real dataset collected from two field tests. The results indicate that the proposed algorithm can efficiently detect and identify the cycle slips and subsequently improve the navigation performance of the integrated system.

3-D airborne ultrasound synthetic aperture imaging based on capacitive micromachined ultrasonic transducers.

PubMed

Park, Kwan Kyu; Khuri-Yakub, Butrus T

2013-09-01

In this paper, we present an airborne 3-D volumetric imaging system based on capacitive micromachined ultrasonic transducers (CMUTs). For this purpose we fabricated 89-kHz CMUTs where each CMUT is made of a circular single-crystal silicon plate with a radius of 1mm and a thickness of 20 μm, which is actuated by electrostatic force through a 20-μm vacuum gap. The measured transmit sensitivity at 300-V DC bias is 14.6 Pa/V and 24.2 Pa/V, when excited by a 30-cycle burst and a continuous wave, respectively. The measured receive sensitivity at 300-V DC bias is 16.6 mV/Pa (-35.6 dB re 1 V/Pa) for a 30-cycle burst. A 26×26 2-D array was implemented by mechanical scanning a co-located transmitter and receiver using the classic synthetic aperture (CSA) method. The measurement of a 1.6λ-size target at a distance of 500 mm presented a lateral resolution of 3.17° and also showed good agreement with the theoretical point spread function. The 3-D imaging of two plates at a distance of 350 mm and 400 mm was constructed to exhibit the capability of the imaging system. This study experimentally demonstrates that a 2-D CMUT array can be used for practical 3-D imaging applications in air, such as a human-machine interface. Copyright © 2013 Elsevier B.V. All rights reserved.

Analysis of Morphogenic Effect of hDAB2IP on Prostate Cancer and its Disease Correlation

DTIC Science & Technology

2005-02-01

Ezh2 protein became more prominent 96 hrs RESULTS after transfection. Under this condition , Profiling hDAB2IP and Ezh2 the elevated levels of hDAB2IP...Pirrotta, V., Poux, S., Melfi, R., S., Vessella, R., Lin, D. L., and Pilyugin, M. (2003) Genetica Pienta, K. J. (2001) In Vivo. 15, 117:191-197 163-168...performed using iCycler machine (Bio-Rad) and the reaction condition was as follow: 95’C (3 min) and 40 cycles amplification cycle (95 0C [30 sec], 55°C

Granule size control and targeting in pulsed spray fluid bed granulation.

PubMed

Ehlers, Henrik; Liu, Anchang; Räikkönen, Heikki; Hatara, Juha; Antikainen, Osmo; Airaksinen, Sari; Heinämäki, Jyrki; Lou, Honxiang; Yliruusi, Jouko

2009-07-30

The primary aim of the study was to investigate the effects of pulsed liquid feed on granule size. The secondary aim was to increase knowledge of this technique in granule size targeting. Pulsed liquid feed refers to the pump changing between on- and off-positions in sequences, called duty cycles. One duty cycle consists of one on- and off-period. The study was performed with a laboratory-scale top-spray fluid bed granulator with duty cycle length and atomization pressure as studied variables. The liquid feed rate, amount and inlet air temperature were constant. The granules were small, indicating that the powder has only undergone ordered mixing, nucleation and early growth. The effect of atomizing pressure on granule size depends on inlet air relative humidity, with premature binder evaporation as a reason. The duty cycle length was of critical importance to the end product attributes, by defining the extent of intermittent drying and rewetting. By varying only the duty cycle length, it was possible to control granule nucleation and growth, with a wider granule size target range in increased relative humidity. The present study confirms that pulsed liquid feed in fluid bed granulation is a useful tool in end product particle size targeting.

Machine Learning to Improve Energy Expenditure Estimation in Children With Disabilities: A Pilot Study in Duchenne Muscular Dystrophy.

PubMed

Pande, Amit; Mohapatra, Prasant; Nicorici, Alina; Han, Jay J

2016-07-19

Children with physical impairments are at a greater risk for obesity and decreased physical activity. A better understanding of physical activity pattern and energy expenditure (EE) would lead to a more targeted approach to intervention. This study focuses on studying the use of machine-learning algorithms for EE estimation in children with disabilities. A pilot study was conducted on children with Duchenne muscular dystrophy (DMD) to identify important factors for determining EE and develop a novel algorithm to accurately estimate EE from wearable sensor-collected data. There were 7 boys with DMD, 6 healthy control boys, and 22 control adults recruited. Data were collected using smartphone accelerometer and chest-worn heart rate sensors. The gold standard EE values were obtained from the COSMED K4b2 portable cardiopulmonary metabolic unit worn by boys (aged 6-10 years) with DMD and controls. Data from this sensor setup were collected simultaneously during a series of concurrent activities. Linear regression and nonlinear machine-learning-based approaches were used to analyze the relationship between accelerometer and heart rate readings and COSMED values. Existing calorimetry equations using linear regression and nonlinear machine-learning-based models, developed for healthy adults and young children, give low correlation to actual EE values in children with disabilities (14%-40%). The proposed model for boys with DMD uses ensemble machine learning techniques and gives a 91% correlation with actual measured EE values (root mean square error of 0.017). Our results confirm that the methods developed to determine EE using accelerometer and heart rate sensor values in normal adults are not appropriate for children with disabilities and should not be used. A much more accurate model is obtained using machine-learning-based nonlinear regression specifically developed for this target population. ©Amit Pande, Prasant Mohapatra, Alina Nicorici, Jay J Han. Originally published in JMIR Rehabilitation and Assistive Technology (http://rehab.jmir.org), 19.07.2016.

Computational prediction of multidisciplinary team decision-making for adjuvant breast cancer drug therapies: a machine learning approach.

PubMed

Lin, Frank P Y; Pokorny, Adrian; Teng, Christina; Dear, Rachel; Epstein, Richard J

2016-12-01

Multidisciplinary team (MDT) meetings are used to optimise expert decision-making about treatment options, but such expertise is not digitally transferable between centres. To help standardise medical decision-making, we developed a machine learning model designed to predict MDT decisions about adjuvant breast cancer treatments. We analysed MDT decisions regarding adjuvant systemic therapy for 1065 breast cancer cases over eight years. Machine learning classifiers with and without bootstrap aggregation were correlated with MDT decisions (recommended, not recommended, or discussable) regarding adjuvant cytotoxic, endocrine and biologic/targeted therapies, then tested for predictability using stratified ten-fold cross-validations. The predictions so derived were duly compared with those based on published (ESMO and NCCN) cancer guidelines. Machine learning more accurately predicted adjuvant chemotherapy MDT decisions than did simple application of guidelines. No differences were found between MDT- vs. ESMO/NCCN- based decisions to prescribe either adjuvant endocrine (97%, p = 0.44/0.74) or biologic/targeted therapies (98%, p = 0.82/0.59). In contrast, significant discrepancies were evident between MDT- and guideline-based decisions to prescribe chemotherapy (87%, p < 0.01, representing 43% and 53% variations from ESMO/NCCN guidelines, respectively). Using ten-fold cross-validation, the best classifiers achieved areas under the receiver operating characteristic curve (AUC) of 0.940 for chemotherapy (95% C.I., 0.922-0.958), 0.899 for the endocrine therapy (95% C.I., 0.880-0.918), and 0.977 for trastuzumab therapy (95% C.I., 0.955-0.999) respectively. Overall, bootstrap aggregated classifiers performed better among all evaluated machine learning models. A machine learning approach based on clinicopathologic characteristics can predict MDT decisions about adjuvant breast cancer drug therapies. The discrepancy between MDT- and guideline-based decisions regarding adjuvant chemotherapy implies that certain non-clincopathologic criteria, such as patient preference and resource availability, are factored into clinical decision-making by local experts but not captured by guidelines.

Research on target tracking in coal mine based on optical flow method

NASA Astrophysics Data System (ADS)

Xue, Hongye; Xiao, Qingwei

2015-03-01

To recognize, track and count the bolting machine in coal mine video images, a real-time target tracking method based on the Lucas-Kanade sparse optical flow is proposed in this paper. In the method, we judge whether the moving target deviate from its trajectory, predicate and correct the position of the moving target. The method solves the problem of failure to track the target or lose the target because of the weak light, uneven illumination and blocking. Using the VC++ platform and Opencv lib we complete the recognition and tracking. The validity of the method is verified by the result of the experiment.

Unreal perpetual motion machine, Rydberg constant and Carnot non-unitary efficiency as a consequence of the atomic irreversibility

NASA Astrophysics Data System (ADS)

Lucia, Umberto

2018-02-01

A perpetual motion machine is a completely ideal engine which cannot be realized. Carnot introduced the concept of the ideal engine which operates on a completely reversible cycle, without any dissipation, but with an upper limit in it. So, even in ideal condition without any dissipation, there is something that prevents the conversion of all the energy absorbed by an ideal reservoir into work. But what is the cause of irreversibility? Here we highlight the atomic nature of this irreversibility, proving that it is no more than the continuous interaction of the atoms with the surrounding field. The macroscopic irreversibility is the consequence of the microscopic irreversibility.

A sparse matrix algorithm on the Boolean vector machine

NASA Technical Reports Server (NTRS)

Wagner, Robert A.; Patrick, Merrell L.

1988-01-01

VLSI technology is being used to implement a prototype Boolean Vector Machine (BVM), which is a large network of very small processors with equally small memories that operate in SIMD mode; these use bit-serial arithmetic, and communicate via cube-connected cycles network. The BVM's bit-serial arithmetic and the small memories of individual processors are noted to compromise the system's effectiveness in large numerical problem applications. Attention is presently given to the implementation of a basic matrix-vector iteration algorithm for space matrices of the BVM, in order to generate over 1 billion useful floating-point operations/sec for this iteration algorithm. The algorithm is expressed in a novel language designated 'BVM'.

Use of containerisation as an alternative to full virtualisation in grid environments.

NASA Astrophysics Data System (ADS)

Long, Robin

2015-12-01

Virtualisation is a key tool on the grid. It can be used to provide varying work environments or as part of a cloud infrastructure. Virtualisation itself carries certain overheads that decrease the performance of the system through requiring extra resources to virtualise the software and hardware stack, and CPU-cycles wasted instantiating or destroying virtual machines for each job. With the rise and improvements in containerisation, where only the software stack is kept separate and no hardware or kernel virtualisation is used, there is scope for speed improvements and efficiency increases over standard virtualisation. We compare containerisation and virtualisation, including a comparison against bare-metal machines as a benchmark.

Time-reversal imaging for classification of submerged elastic targets via Gibbs sampling and the Relevance Vector Machine.

PubMed

Dasgupta, Nilanjan; Carin, Lawrence

2005-04-01

Time-reversal imaging (TRI) is analogous to matched-field processing, although TRI is typically very wideband and is appropriate for subsequent target classification (in addition to localization). Time-reversal techniques, as applied to acoustic target classification, are highly sensitive to channel mismatch. Hence, it is crucial to estimate the channel parameters before time-reversal imaging is performed. The channel-parameter statistics are estimated here by applying a geoacoustic inversion technique based on Gibbs sampling. The maximum a posteriori (MAP) estimate of the channel parameters are then used to perform time-reversal imaging. Time-reversal implementation requires a fast forward model, implemented here by a normal-mode framework. In addition to imaging, extraction of features from the time-reversed images is explored, with these applied to subsequent target classification. The classification of time-reversed signatures is performed by the relevance vector machine (RVM). The efficacy of the technique is analyzed on simulated in-channel data generated by a free-field finite element method (FEM) code, in conjunction with a channel propagation model, wherein the final classification performance is demonstrated to be relatively insensitive to the associated channel parameters. The underlying theory of Gibbs sampling and TRI are presented along with the feature extraction and target classification via the RVM.

Virtual reality hardware and graphic display options for brain-machine interfaces

PubMed Central

Marathe, Amar R.; Carey, Holle L.; Taylor, Dawn M.

2009-01-01

Virtual reality hardware and graphic displays are reviewed here as a development environment for brain-machine interfaces (BMIs). Two desktop stereoscopic monitors and one 2D monitor were compared in a visual depth discrimination task and in a 3D target-matching task where able-bodied individuals used actual hand movements to match a virtual hand to different target hands. Three graphic representations of the hand were compared: a plain sphere, a sphere attached to the fingertip of a realistic hand and arm, and a stylized pacman-like hand. Several subjects had great difficulty using either stereo monitor for depth perception when perspective size cues were removed. A mismatch in stereo and size cues generated inappropriate depth illusions. This phenomenon has implications for choosing target and virtual hand sizes in BMI experiments. Target matching accuracy was about as good with the 2D monitor as with either 3D monitor. However, users achieved this accuracy by exploring the boundaries of the hand in the target with carefully controlled movements. This method of determining relative depth may not be possible in BMI experiments if movement control is more limited. Intuitive depth cues, such as including a virtual arm, can significantly improve depth perception accuracy with or without stereo viewing. PMID:18006069

Template For Aiming An X-Ray Machine

NASA Technical Reports Server (NTRS)

Morphet, W. J.

1994-01-01

Relatively inexpensive template helps in aligning x-ray machine with phenolic ring to be inspected for flaws. Phenolic ring in original application part of rocket nozzle. Concept also applicable to x-ray inspection of other rings. Template contains alignment holes for adjusting orientation, plus target spot for adjusting lateral position, of laser spotting beam. (Laser spotting beam coincides with the x-ray beam, turned on later, after alignment completed.) Use of template decreases positioning time and error, providing consistent sensitivity for detection of flaws.

AAAIC '88 - Aerospace Applications of Artificial Intelligence; Proceedings of the Fourth Annual Conference, Dayton, OH, Oct. 25-27, 1988. Volumes 1 2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, J.R.; Netrologic, Inc., San Diego, CA)

1988-01-01

Topics presented include integrating neural networks and expert systems, neural networks and signal processing, machine learning, cognition and avionics applications, artificial intelligence and man-machine interface issues, real time expert systems, artificial intelligence, and engineering applications. Also considered are advanced problem solving techniques, combinational optimization for scheduling and resource control, data fusion/sensor fusion, back propagation with momentum, shared weights and recurrency, automatic target recognition, cybernetics, optical neural networks.

Fast Fourier Transform algorithm design and tradeoffs

NASA Technical Reports Server (NTRS)

Kamin, Ray A., III; Adams, George B., III

1988-01-01

The Fast Fourier Transform (FFT) is a mainstay of certain numerical techniques for solving fluid dynamics problems. The Connection Machine CM-2 is the target for an investigation into the design of multidimensional Single Instruction Stream/Multiple Data (SIMD) parallel FFT algorithms for high performance. Critical algorithm design issues are discussed, necessary machine performance measurements are identified and made, and the performance of the developed FFT programs are measured. Fast Fourier Transform programs are compared to the currently best Cray-2 FFT program.

Exploring prediction uncertainty of spatial data in geostatistical and machine learning Approaches

NASA Astrophysics Data System (ADS)

Klump, J. F.; Fouedjio, F.

2017-12-01

Geostatistical methods such as kriging with external drift as well as machine learning techniques such as quantile regression forest have been intensively used for modelling spatial data. In addition to providing predictions for target variables, both approaches are able to deliver a quantification of the uncertainty associated with the prediction at a target location. Geostatistical approaches are, by essence, adequate for providing such prediction uncertainties and their behaviour is well understood. However, they often require significant data pre-processing and rely on assumptions that are rarely met in practice. Machine learning algorithms such as random forest regression, on the other hand, require less data pre-processing and are non-parametric. This makes the application of machine learning algorithms to geostatistical problems an attractive proposition. The objective of this study is to compare kriging with external drift and quantile regression forest with respect to their ability to deliver reliable prediction uncertainties of spatial data. In our comparison we use both simulated and real world datasets. Apart from classical performance indicators, comparisons make use of accuracy plots, probability interval width plots, and the visual examinations of the uncertainty maps provided by the two approaches. By comparing random forest regression to kriging we found that both methods produced comparable maps of estimated values for our variables of interest. However, the measure of uncertainty provided by random forest seems to be quite different to the measure of uncertainty provided by kriging. In particular, the lack of spatial context can give misleading results in areas without ground truth data. These preliminary results raise questions about assessing the risks associated with decisions based on the predictions from geostatistical and machine learning algorithms in a spatial context, e.g. mineral exploration.

In silico re-identification of properties of drug target proteins.

PubMed

Kim, Baeksoo; Jo, Jihoon; Han, Jonghyun; Park, Chungoo; Lee, Hyunju

2017-05-31

Computational approaches in the identification of drug targets are expected to reduce time and effort in drug development. Advances in genomics and proteomics provide the opportunity to uncover properties of druggable genomes. Although several studies have been conducted for distinguishing drug targets from non-drug targets, they mainly focus on the sequences and functional roles of proteins. Many other properties of proteins have not been fully investigated. Using the DrugBank (version 3.0) database containing nearly 6,816 drug entries including 760 FDA-approved drugs and 1822 of their targets and human UniProt/Swiss-Prot databases, we defined 1578 non-redundant drug target and 17,575 non-drug target proteins. To select these non-redundant protein datasets, we built four datasets (A, B, C, and D) by considering clustering of paralogous proteins. We first reassessed the widely used properties of drug target proteins. We confirmed and extended that drug target proteins (1) are likely to have more hydrophobic, less polar, less PEST sequences, and more signal peptide sequences higher and (2) are more involved in enzyme catalysis, oxidation and reduction in cellular respiration, and operational genes. In this study, we proposed new properties (essentiality, expression pattern, PTMs, and solvent accessibility) for effectively identifying drug target proteins. We found that (1) drug targetability and protein essentiality are decoupled, (2) druggability of proteins has high expression level and tissue specificity, and (3) functional post-translational modification residues are enriched in drug target proteins. In addition, to predict the drug targetability of proteins, we exploited two machine learning methods (Support Vector Machine and Random Forest). When we predicted drug targets by combining previously known protein properties and proposed new properties, an F-score of 0.8307 was obtained. When the newly proposed properties are integrated, the prediction performance is improved and these properties are related to drug targets. We believe that our study will provide a new aspect in inferring drug-target interactions.

Open set recognition of aircraft in aerial imagery using synthetic template models

NASA Astrophysics Data System (ADS)

Bapst, Aleksander B.; Tran, Jonathan; Koch, Mark W.; Moya, Mary M.; Swahn, Robert

2017-05-01

Fast, accurate and robust automatic target recognition (ATR) in optical aerial imagery can provide game-changing advantages to military commanders and personnel. ATR algorithms must reject non-targets with a high degree of confidence in a world with an infinite number of possible input images. Furthermore, they must learn to recognize new targets without requiring massive data collections. Whereas most machine learning algorithms classify data in a closed set manner by mapping inputs to a fixed set of training classes, open set recognizers incorporate constraints that allow for inputs to be labelled as unknown. We have adapted two template-based open set recognizers to use computer generated synthetic images of military aircraft as training data, to provide a baseline for military-grade ATR: (1) a frequentist approach based on probabilistic fusion of extracted image features, and (2) an open set extension to the one-class support vector machine (SVM). These algorithms both use histograms of oriented gradients (HOG) as features as well as artificial augmentation of both real and synthetic image chips to take advantage of minimal training data. Our results show that open set recognizers trained with synthetic data and tested with real data can successfully discriminate real target inputs from non-targets. However, there is still a requirement for some knowledge of the real target in order to calibrate the relationship between synthetic template and target score distributions. We conclude by proposing algorithm modifications that may improve the ability of synthetic data to represent real data.

Target Detection over the Diurnal Cycle Using a Multispectral Infrared Sensor.

PubMed

Zhao, Huijie; Ji, Zheng; Li, Na; Gu, Jianrong; Li, Yansong

2016-12-29

When detecting a target over the diurnal cycle, a conventional infrared thermal sensor might lose the target due to the thermal crossover, which could happen at any time throughout the day when the infrared image contrast between target and background in a scene is indistinguishable due to the temperature variation. In this paper, the benefits of using a multispectral-based infrared sensor over the diurnal cycle have been shown. Firstly, a brief theoretical analysis on how the thermal crossover influences a conventional thermal sensor, within the conditions where the thermal crossover would happen and why the mid-infrared (3~5 μm) multispectral technology is effective, is presented. Furthermore, the effectiveness of this technology is also described and we describe how the prototype design and multispectral technology is employed to help solve the thermal crossover detection problem. Thirdly, several targets are set up outside and imaged in the field experiment over a 24-h period. The experimental results show that the multispectral infrared imaging system can enhance the contrast of the detected images and effectively solve the failure of the conventional infrared sensor during the diurnal cycle, which is of great significance for infrared surveillance applications.

Target Detection over the Diurnal Cycle Using a Multispectral Infrared Sensor

PubMed Central

Zhao, Huijie; Ji, Zheng; Li, Na; Gu, Jianrong; Li, Yansong

2016-01-01

When detecting a target over the diurnal cycle, a conventional infrared thermal sensor might lose the target due to the thermal crossover, which could happen at any time throughout the day when the infrared image contrast between target and background in a scene is indistinguishable due to the temperature variation. In this paper, the benefits of using a multispectral-based infrared sensor over the diurnal cycle have been shown. Firstly, a brief theoretical analysis on how the thermal crossover influences a conventional thermal sensor, within the conditions where the thermal crossover would happen and why the mid-infrared (3~5 μm) multispectral technology is effective, is presented. Furthermore, the effectiveness of this technology is also described and we describe how the prototype design and multispectral technology is employed to help solve the thermal crossover detection problem. Thirdly, several targets are set up outside and imaged in the field experiment over a 24-h period. The experimental results show that the multispectral infrared imaging system can enhance the contrast of the detected images and effectively solve the failure of the conventional infrared sensor during the diurnal cycle, which is of great significance for infrared surveillance applications. PMID:28036073

Requirements Doc for Refurb of JASPER Facility in B131HB

DOE Office of Scientific and Technical Information (OSTI.GOV)

Knittel, Kenn M.

The Joint Actinide Shock Physics Experimental Research (JASPER) Program target fabrication facility is currently located in building 131 (B131) of the Lawrence Livermore National Laboratory (LLNL). A portion of this current facility has been committed to another program as part of a larger effort to consolidate LLNL capabilities into newer facilities. This facility assembles precision targets for scientific studies at the Nevada National Security Site (NNSS). B131 is also going through a modernization project to upgrade the infrastructure and abate asbestos. These activities will interrupt the continuous target fabrication efforts for the JASPER Program. Several options are explored to meetmore » the above conflicting requirements, with the final recommendation to prepare a new facility for JASPER target fabrication operations before modernization efforts begin in the current facility assigned to JASPER. This recommendation fits within all schedule constraints and minimizes the disruption to the JASPER Program. This option is not without risk, as it requires moving an aged, precision coordinate measuring machine, which is essential to the JASPER Program’s success. The selected option balances the risk to the machine with continuity of operations.« less

Markerless gating for lung cancer radiotherapy based on machine learning techniques

NASA Astrophysics Data System (ADS)

Lin, Tong; Li, Ruijiang; Tang, Xiaoli; Dy, Jennifer G.; Jiang, Steve B.

2009-03-01

In lung cancer radiotherapy, radiation to a mobile target can be delivered by respiratory gating, for which we need to know whether the target is inside or outside a predefined gating window at any time point during the treatment. This can be achieved by tracking one or more fiducial markers implanted inside or near the target, either fluoroscopically or electromagnetically. However, the clinical implementation of marker tracking is limited for lung cancer radiotherapy mainly due to the risk of pneumothorax. Therefore, gating without implanted fiducial markers is a promising clinical direction. We have developed several template-matching methods for fluoroscopic marker-less gating. Recently, we have modeled the gating problem as a binary pattern classification problem, in which principal component analysis (PCA) and support vector machine (SVM) are combined to perform the classification task. Following the same framework, we investigated different combinations of dimensionality reduction techniques (PCA and four nonlinear manifold learning methods) and two machine learning classification methods (artificial neural networks—ANN and SVM). Performance was evaluated on ten fluoroscopic image sequences of nine lung cancer patients. We found that among all combinations of dimensionality reduction techniques and classification methods, PCA combined with either ANN or SVM achieved a better performance than the other nonlinear manifold learning methods. ANN when combined with PCA achieves a better performance than SVM in terms of classification accuracy and recall rate, although the target coverage is similar for the two classification methods. Furthermore, the running time for both ANN and SVM with PCA is within tolerance for real-time applications. Overall, ANN combined with PCA is a better candidate than other combinations we investigated in this work for real-time gated radiotherapy.

The Molecular Industrial Revolution: Automated Synthesis of Small Molecules

PubMed Central

Trobe, Melanie; Burke, Martin D.

2018-01-01

The eighteenth and nineteenth centuries marked a sweeping transition from manual to automated manufacturing on the macroscopic scale. This enabled an unmatched period of human innovation that helped drive the Industrial Revolution. The impact on society was transformative, ultimately yielding substantial improvements in living conditions and lifespan in many parts of the world. During the same time period, the first manual syntheses of organic molecules was achieved. Now, two centuries later, we are poised for an analogous transition from highly customized crafting of specific molecular targets by hand to the increasingly general and automated assembly of many different types of molecules with the push of a button. Automation of customized small molecule synthesis pathways is already enabling safer, more reproducible, and readily scalable production of specific targets, and general machines now exist for the synthesis of a wide range of different peptides, oligonucleotides, and oligosaccharides. Creating general machines that are similarly capable of making many different types of small molecules on-demand, akin to that which has been achieved on the macroscopic scale with 3D printers, has proven to be substantially more challenging. Yet important progress is being made toward this potentially transformative objective with two complementary approaches: (1) automation of customized synthesis routes to different targets via machines that enable use of many different reactions and starting materials, and (2) automation of generalized platforms that make many different targets using common coupling chemistry and building blocks. Continued progress in these exciting directions has the potential to shift the bottleneck in molecular innovation from synthesis to imagination, and thereby help drive a new industrial revolution on the molecular scale. PMID:29513400

Information-Theoretic Performance Analysis of Sensor Networks via Markov Modeling of Time Series Data.

PubMed

Li, Yue; Jha, Devesh K; Ray, Asok; Wettergren, Thomas A; Yue Li; Jha, Devesh K; Ray, Asok; Wettergren, Thomas A; Wettergren, Thomas A; Li, Yue; Ray, Asok; Jha, Devesh K

2018-06-01

This paper presents information-theoretic performance analysis of passive sensor networks for detection of moving targets. The proposed method falls largely under the category of data-level information fusion in sensor networks. To this end, a measure of information contribution for sensors is formulated in a symbolic dynamics framework. The network information state is approximately represented as the largest principal component of the time series collected across the network. To quantify each sensor's contribution for generation of the information content, Markov machine models as well as x-Markov (pronounced as cross-Markov) machine models, conditioned on the network information state, are constructed; the difference between the conditional entropies of these machines is then treated as an approximate measure of information contribution by the respective sensors. The x-Markov models represent the conditional temporal statistics given the network information state. The proposed method has been validated on experimental data collected from a local area network of passive sensors for target detection, where the statistical characteristics of environmental disturbances are similar to those of the target signal in the sense of time scale and texture. A distinctive feature of the proposed algorithm is that the network decisions are independent of the behavior and identity of the individual sensors, which is desirable from computational perspectives. Results are presented to demonstrate the proposed method's efficacy to correctly identify the presence of a target with very low false-alarm rates. The performance of the underlying algorithm is compared with that of a recent data-driven, feature-level information fusion algorithm. It is shown that the proposed algorithm outperforms the other algorithm.

Lunar preform manufacturing

NASA Technical Reports Server (NTRS)

Leong, Gregory N.; Nease, Sandra; Lager, Vicky; Yaghjian, Raffy; Waller, Chris; Dorrity, J. Lewis

1992-01-01

A design for a machine to produce hollow, continuous fiber reinforced composite rods of lunar glass and a liquid crystalline matrix using the pultrusion process is presented. The glass fiber will be produced from the lunar surface, with the machine and matrix being transported to the moon. The process is adaptable to the low gravity and near-vacuum environment of the moon through the use of a thermoplastic matrix in fiber form as it enters the pultrusion process. With a power consumption of 5k W, the proposed machine will run continuously, unmanned in fourteen day cycles, matching the length of moon days. A number of dies could be included that would allow the machine to produce rods of varying diameter, I-beams, angles, and other structural members. These members could then be used for construction on the lunar surface or transported for use in orbit. The benefits of this proposal are in the savings in weight of the cargo each lunar mission would carry. The supply of glass on the moon is effectively endless, so enough rods would have to be produced to justify its transportation, operation, and capital cost. This should not be difficult as weight on lunar mission is at a premium.

Lunar preform manufacturing

NASA Technical Reports Server (NTRS)

Leong, Gregory N.; Nease, Sandra; Lager, Vicky; Yaghjian, Raffy; Waller, Chris

1992-01-01

A design for a machine to produce hollow, continuous fiber-reinforced composite rods of lunar glass and a liquid crystalline matrix using the pultrusion process is presented. The glass fiber will be produced from the lunar surface, with the machine and matrix being transported to the moon. The process is adaptable to the low gravity and near-vacuum environment of the moon through the use of a thermoplastic matrix in fiber form as it enters the pultrusion process. With a power consumption of 5 kW, the proposed machine will run unmanned continuously in fourteen-day cycles, matching the length of lunar days. A number of dies could be included that would allow the machine to produce rods of varying diameter, I-beams, angles, and other structural members. These members could then be used for construction on the lunar surface or transported for use in orbit. The benefits of this proposal are in the savings in weight of the cargo each lunar mission would carry. The supply of glass on the moon is effectively endless, so enough rods would have to be produced to justify its transportation, operation, and capital cost. This should not be difficult as weight on lunar mission is at a premium.

Intelligent power management in a vehicular system with multiple power sources

NASA Astrophysics Data System (ADS)

Murphey, Yi L.; Chen, ZhiHang; Kiliaris, Leonidas; Masrur, M. Abul

This paper presents an optimal online power management strategy applied to a vehicular power system that contains multiple power sources and deals with largely fluctuated load requests. The optimal online power management strategy is developed using machine learning and fuzzy logic. A machine learning algorithm has been developed to learn the knowledge about minimizing power loss in a Multiple Power Sources and Loads (M_PS&LD) system. The algorithm exploits the fact that different power sources used to deliver a load request have different power losses under different vehicle states. The machine learning algorithm is developed to train an intelligent power controller, an online fuzzy power controller, FPC_MPS, that has the capability of finding combinations of power sources that minimize power losses while satisfying a given set of system and component constraints during a drive cycle. The FPC_MPS was implemented in two simulated systems, a power system of four power sources, and a vehicle system of three power sources. Experimental results show that the proposed machine learning approach combined with fuzzy control is a promising technology for intelligent vehicle power management in a M_PS&LD power system.

Applications of Support Vector Machine (SVM) Learning in Cancer Genomics.

PubMed

Huang, Shujun; Cai, Nianguang; Pacheco, Pedro Penzuti; Narrandes, Shavira; Wang, Yang; Xu, Wayne

2018-01-01

Machine learning with maximization (support) of separating margin (vector), called support vector machine (SVM) learning, is a powerful classification tool that has been used for cancer genomic classification or subtyping. Today, as advancements in high-throughput technologies lead to production of large amounts of genomic and epigenomic data, the classification feature of SVMs is expanding its use in cancer genomics, leading to the discovery of new biomarkers, new drug targets, and a better understanding of cancer driver genes. Herein we reviewed the recent progress of SVMs in cancer genomic studies. We intend to comprehend the strength of the SVM learning and its future perspective in cancer genomic applications. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Dual linear structured support vector machine tracking method via scale correlation filter

NASA Astrophysics Data System (ADS)

Li, Weisheng; Chen, Yanquan; Xiao, Bin; Feng, Chen

2018-01-01

Adaptive tracking-by-detection methods based on structured support vector machine (SVM) performed well on recent visual tracking benchmarks. However, these methods did not adopt an effective strategy of object scale estimation, which limits the overall tracking performance. We present a tracking method based on a dual linear structured support vector machine (DLSSVM) with a discriminative scale correlation filter. The collaborative tracker comprised of a DLSSVM model and a scale correlation filter obtains good results in tracking target position and scale estimation. The fast Fourier transform is applied for detection. Extensive experiments show that our tracking approach outperforms many popular top-ranking trackers. On a benchmark including 100 challenging video sequences, the average precision of the proposed method is 82.8%.

The Portals 4.0 network programming interface.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barrett, Brian W.; Brightwell, Ronald Brian; Pedretti, Kevin

2012-11-01

This report presents a specification for the Portals 4.0 network programming interface. Portals 4.0 is intended to allow scalable, high-performance network communication between nodes of a parallel computing system. Portals 4.0 is well suited to massively parallel processing and embedded systems. Portals 4.0 represents an adaption of the data movement layer developed for massively parallel processing platforms, such as the 4500-node Intel TeraFLOPS machine. Sandias Cplant cluster project motivated the development of Version 3.0, which was later extended to Version 3.3 as part of the Cray Red Storm machine and XT line. Version 4.0 is targeted to the next generationmore » of machines employing advanced network interface architectures that support enhanced offload capabilities.« less

Object recognition of ladar with support vector machine

NASA Astrophysics Data System (ADS)

Sun, Jian-Feng; Li, Qi; Wang, Qi

2005-01-01

Intensity, range and Doppler images can be obtained by using laser radar. Laser radar can detect much more object information than other detecting sensor, such as passive infrared imaging and synthetic aperture radar (SAR), so it is well suited as the sensor of object recognition. Traditional method of laser radar object recognition is extracting target features, which can be influenced by noise. In this paper, a laser radar recognition method-Support Vector Machine is introduced. Support Vector Machine (SVM) is a new hotspot of recognition research after neural network. It has well performance on digital written and face recognition. Two series experiments about SVM designed for preprocessing and non-preprocessing samples are performed by real laser radar images, and the experiments results are compared.

An optimization methodology for heterogeneous minor actinides transmutation

NASA Astrophysics Data System (ADS)

Kooyman, Timothée; Buiron, Laurent; Rimpault, Gérald

2018-04-01

In the case of a closed fuel cycle, minor actinides transmutation can lead to a strong reduction in spent fuel radiotoxicity and decay heat. In the heterogeneous approach, minor actinides are loaded in dedicated targets located at the core periphery so that long-lived minor actinides undergo fission and are turned in shorter-lived fission products. However, such targets require a specific design process due to high helium production in the fuel, high flux gradient at the core periphery and low power production. Additionally, the targets are generally manufactured with a high content in minor actinides in order to compensate for the low flux level at the core periphery. This leads to negative impacts on the fuel cycle in terms of neutron source and decay heat of the irradiated targets, which penalize their handling and reprocessing. In this paper, a simplified methodology for the design of targets is coupled with a method for the optimization of transmutation which takes into account both transmutation performances and fuel cycle impacts. The uncertainties and performances of this methodology are evaluated and shown to be sufficient to carry out scoping studies. An illustration is then made by considering the use of moderating material in the targets, which has a positive impact on the minor actinides consumption but a negative impact both on fuel cycle constraints (higher decay heat and neutron) and on assembly design (higher helium production and lower fuel volume fraction). It is shown that the use of moderating material is an optimal solution of the transmutation problem with regards to consumption and fuel cycle impacts, even when taking geometrical design considerations into account.

Feasibility of retrofitting a university library with active workstations to reduce sedentary behavior.

PubMed

Maeda, Hotaka; Quartiroli, Alessandro; Vos, Paul W; Carr, Lucas J; Mahar, Matthew T

2014-05-01

Libraries are an inherently sedentary environment, but are an understudied setting for sedentary behavior interventions. To investigate the feasibility of incorporating portable pedal machines in a university library to reduce sedentary behaviors. The 11-week intervention targeted students at a university library. Thirteen portable pedal machines were placed in the library. Four forms of prompts (e-mail, library website, advertisement monitors, and poster) encouraging pedal machine use were employed during the first 4 weeks. Pedal machine use was measured via automatic timers on each machine and momentary time sampling. Daily library visits were measured using a gate counter. Individualized data were measured by survey. Data were collected in fall 2012 and analyzed in 2013. Mean (SD) cumulative pedal time per day was 95.5 (66.1) minutes. One or more pedal machines were observed being used 15% of the time (N=589). Pedal machines were used at least once by 7% of students (n=527). Controlled for gate count, no linear change of pedal machine use across days was found (b=-0.1 minutes, p=0.75) and the presence of the prompts did not change daily pedal time (p=0.63). Seven of eight items that assessed attitudes toward the intervention supported intervention feasibility (p<0.05). The unique non-individualized approach of retrofitting a library with pedal machines to reduce sedentary behavior seems feasible, but improvement of its effectiveness is needed. This study could inform future studies aimed at reshaping traditionally sedentary settings to improve public health. Copyright © 2014 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

Characteristics of utility cyclists in Queensland, Australia: an examination of the associations between individual, social, and environmental factors and utility cycling.

PubMed

Sahlqvist, Shannon L; Heesch, Kristiann C

2012-08-01

Initiatives to promote utility cycling in countries like Australia and the US, which have low rates of utility cycling, may be more effective if they first target recreational cyclists. This study aimed to describe patterns of utility cycling and examine its correlates, among cyclists in Queensland, Australia. An online survey was administered to adult members of a state-based cycling community and advocacy group (n=1813). The survey asked about demographic characteristics and cycling behavior, motivators and constraints. Utility cycling patterns were described, and logistic regression modeling was used to examine associations between utility cycling and other variables. Forty-seven percent of respondents reported utility cycling: most did so to commute (86%). Most journeys (83%) were >5 km. Being male, younger, employed full-time, or university-educated increased the likelihood of utility cycling (P<.05). Perceiving cycling to be a cheap or a convenient form of transport was associated with utility cycling (P<.05). The moderate rate of utility cycling among recreational cyclists highlights a potential to promote utility cycling among this group. To increase utility cycling, strategies should target female and older recreational cyclists and focus on making cycling a cheap and convenient mode of transport.

Insect-machine interface based neurocybernetics.

PubMed

Bozkurt, Alper; Gilmour, Robert F; Sinha, Ayesa; Stern, David; Lal, Amit

2009-06-01

We present details of a novel bioelectric interface formed by placing microfabricated probes into insect during metamorphic growth cycles. The inserted microprobes emerge with the insect where the development of tissue around the electronics during the pupal development allows mechanically stable and electrically reliable structures coupled to the insect. Remarkably, the insects do not react adversely or otherwise to the inserted electronics in the pupae stage, as is true when the electrodes are inserted in adult stages. We report on the electrical and mechanical characteristics of this novel bioelectronic interface, which we believe would be adopted by many investigators trying to investigate biological behavior in insects with negligible or minimal traumatic effect encountered when probes are inserted in adult stages. This novel insect-machine interface also allows for hybrid insect-machine platforms for further studies. As an application, we demonstrate our first results toward navigation of flight in moths. When instrumented with equipment to gather information for environmental sensing, such insects potentially can assist man to monitor the ecosystems that we share with them for sustainability. The simplicity of the optimized surgical procedure we invented allows for batch insertions to the insect for automatic and mass production of such hybrid insect-machine platforms. Therefore, our bioelectronic interface and hybrid insect-machine platform enables multidisciplinary scientific and engineering studies not only to investigate the details of insect behavioral physiology but also to control it.

Comparative study of CW, nanosecond- and femtosecond-pulsed laser microcutting of AZ31 magnesium alloy stents.

PubMed

Gökhan Demir, Ali; Previtali, Barbara

2014-06-01

Magnesium alloys constitute an interesting solution for cardiovascular stents due to their biocompatibility and biodegradability in human body. Laser microcutting is the industrially accepted method for stent manufacturing. However, the laser-material interaction should be well investigated to control the quality characteristics of the microcutting process that concern the surface roughness, chemical composition, and microstructure of the final device. Despite the recent developments in industrial laser systems, a universal laser source that can be manipulated flexibly in terms of process parameters is far from reality. Therefore, comparative studies are required to demonstrate processing capabilities. In particular, the laser pulse duration is a key factor determining the processing regime. This work approaches the laser microcutting of AZ31 Mg alloy from the perspective of a comparative study to evaluate the machining capabilities in continuous wave (CW), ns- and fs-pulsed regimes. Three industrial grade machining systems were compared to reach a benchmark in machining quality, productivity, and ease of postprocessing. The results confirmed that moving toward the ultrashort pulse domain the machining quality increases, but the need for postprocessing remains. The real advantage of ultrashort pulsed machining was the ease in postprocessing and maintaining geometrical integrity of the stent mesh after chemical etching. Resultantly, the overall production cycle time was shortest for fs-pulsed laser system, despite the fact that CW laser system provided highest cutting speed.

Silver nanoclusters-assisted ion-exchange reaction with CdTe quantum dots for photoelectrochemical detection of adenosine by target-triggering multiple-cycle amplification strategy.

PubMed

Zhao, Yang; Tan, Lu; Gao, Xiaoshan; Jie, Guifen; Huang, Tingyu

2018-07-01

Herein, we successfully devised a novel photoelectrochemical (PEC) platform for ultrasensitive detection of adenosine by target-triggering cascade multiple cycle amplification based on the silver nanoparticles-assisted ion-exchange reaction with CdTe quantum dots (QDs). In the presence of target adenosine, DNA s1 is released from the aptamer and then hybridizes with hairpin DNA (HP1), which could initiate the cycling cleavage process under the reaction of nicking endonuclease. Then the product (DNA b) of cycle I could act as the "DNA trigger" of cycle II to further generate a large number of DNA s1, which again go back to cycle I, thus a cascade multiple DNA cycle amplification was carried out to produce abundant DNA c. These DNA c fragments with the cytosine (C)-rich loop were captured by magnetic beads, and numerous silver nanoclusters (Ag NCs) were synthesized by AgNO 3 and sodium borohydride. The dissolved AgNCs released numerous silver ions which could induce ion exchange reaction with the CdTe QDs, thus resulting in greatly amplified change of photocurrent for target detection. The detection linear range for adenosine was 1.0 fM ~10 nM with the detection limit of 0.5 fM. The present PEC strategy combining cascade multiple DNA cycle amplification and AgNCs-induced ion-exchange reaction with QDs provides new insight into rapid, and ultrasensitive PEC detection of different biomolecules, which showed great potential for detecting trace amounts in bioanalysis and clinical biomedicine. Copyright © 2018 Elsevier B.V. All rights reserved.

TargetM6A: Identifying N6-Methyladenosine Sites From RNA Sequences via Position-Specific Nucleotide Propensities and a Support Vector Machine.

PubMed

Li, Guang-Qing; Liu, Zi; Shen, Hong-Bin; Yu, Dong-Jun

2016-10-01

As one of the most ubiquitous post-transcriptional modifications of RNA, N 6 -methyladenosine ( [Formula: see text]) plays an essential role in many vital biological processes. The identification of [Formula: see text] sites in RNAs is significantly important for both basic biomedical research and practical drug development. In this study, we designed a computational-based method, called TargetM6A, to rapidly and accurately target [Formula: see text] sites solely from the primary RNA sequences. Two new features, i.e., position-specific nucleotide/dinucleotide propensities (PSNP/PSDP), are introduced and combined with the traditional nucleotide composition (NC) feature to formulate RNA sequences. The extracted features are further optimized to obtain a much more compact and discriminative feature subset by applying an incremental feature selection (IFS) procedure. Based on the optimized feature subset, we trained TargetM6A on the training dataset with a support vector machine (SVM) as the prediction engine. We compared the proposed TargetM6A method with existing methods for predicting [Formula: see text] sites by performing stringent jackknife tests and independent validation tests on benchmark datasets. The experimental results show that the proposed TargetM6A method outperformed the existing methods for predicting [Formula: see text] sites and remarkably improved the prediction performances, with MCC = 0.526 and AUC = 0.818. We also provided a user-friendly web server for TargetM6A, which is publicly accessible for academic use at http://csbio.njust.edu.cn/bioinf/TargetM6A.

Optimization and Simulation of Plastic Injection Process using Genetic Algorithm and Moldflow

NASA Astrophysics Data System (ADS)

Martowibowo, Sigit Yoewono; Kaswadi, Agung

2017-03-01

The use of plastic-based products is continuously increasing. The increasing demands for thinner products, lower production costs, yet higher product quality has triggered an increase in the number of research projects on plastic molding processes. An important branch of such research is focused on mold cooling system. Conventional cooling systems are most widely used because they are easy to make by using conventional machining processes. However, the non-uniform cooling processes are considered as one of their weaknesses. Apart from the conventional systems, there are also conformal cooling systems that are designed for faster and more uniform plastic mold cooling. In this study, the conformal cooling system is applied for the production of bowl-shaped product made of PP AZ564. Optimization is conducted to initiate machine setup parameters, namely, the melting temperature, injection pressure, holding pressure and holding time. The genetic algorithm method and Moldflow were used to optimize the injection process parameters at a minimum cycle time. It is found that, an optimum injection molding processes could be obtained by setting the parameters to the following values: T M = 180 °C; P inj = 20 MPa; P hold = 16 MPa and t hold = 8 s, with a cycle time of 14.11 s. Experiments using the conformal cooling system yielded an average cycle time of 14.19 s. The studied conformal cooling system yielded a volumetric shrinkage of 5.61% and the wall shear stress was found at 0.17 MPa. The difference between the cycle time obtained through simulations and experiments using the conformal cooling system was insignificant (below 1%). Thus, combining process parameters optimization and simulations by using genetic algorithm method with Moldflow can be considered as valid.

Recognition of Time Stamps on Full-Disk Hα Images Using Machine Learning Methods

NASA Astrophysics Data System (ADS)

Xu, Y.; Huang, N.; Jing, J.; Liu, C.; Wang, H.; Fu, G.

2016-12-01

Observation and understanding of the physics of the 11-year solar activity cycle and 22-year magnetic cycle are among the most important research topics in solar physics. The solar cycle is responsible for magnetic field and particle fluctuation in the near-earth environment that have been found increasingly important in affecting the living of human beings in the modern era. A systematic study of large-scale solar activities, as made possible by our rich data archive, will further help us to understand the global-scale magnetic fields that are closely related to solar cycles. The long-time-span data archive includes both full-disk and high-resolution Hα images. Prior to the widely use of CCD cameras in 1990s, 35-mm films were the major media to store images. The research group at NJIT recently finished the digitization of film data obtained by the National Solar Observatory (NSO) and Big Bear Solar Observatory (BBSO) covering the period of 1953 to 2000. The total volume of data exceeds 60 TB. To make this huge database scientific valuable, some processing and calibration are required. One of the most important steps is to read the time stamps on all of the 14 million images, which is almost impossible to be done manually. We implemented three different methods to recognize the time stamps automatically, including Optical Character Recognition (OCR), Classification Tree and TensorFlow. The latter two are known as machine learning algorithms which are very popular now a day in pattern recognition area. We will present some sample images and the results of clock recognition from all three methods.

Upscaling Ameriflux observations to assess drought impacts on gross primary productivity across the Southwest

NASA Astrophysics Data System (ADS)

Barnes, M.; Moore, D. J.; Scott, R. L.; MacBean, N.; Ponce-Campos, G. E.; Breshears, D. D.

2017-12-01

Both satellite observations and eddy covariance estimates provide crucial information about the Earth's carbon, water and energy cycles. Continuous measurements from flux towers facilitate exploration of the exchange of carbon dioxide, water and energy between the land surface and the atmosphere at fine temporal and spatial scales, while satellite observations can fill in the large spatial gaps of in-situ measurements and provide long-term temporal continuity. The Southwest (Southwest United States and Northwest Mexico) and other semi-arid regions represent a key uncertainty in interannual variability in carbon uptake. Comparisons of existing global upscaled gross primary production (GPP) products with flux tower data at sites across the Southwest show widespread mischaracterization of seasonality in vegetation carbon uptake, resulting in large (up to 200%) errors in annual carbon uptake estimates. Here, remotely sensed and distributed meteorological inputs are used to upscale GPP estimates from 25 Ameriflux towers across the Southwest to the regional scale using a machine learning approach. Our random forest model incorporates two novel features that improve the spatial and temporal variability in GPP. First, we incorporate a multi-scalar drought index at multiple timescales to account for differential seasonality between ecosystem types. Second, our machine learning algorithm was trained on twenty five ecologically diverse sites to optimize both the monthly variability in and the seasonal cycle of GPP. The product and its components will be used to examine drought impacts on terrestrial carbon cycling across the Southwest including the effects of drought seasonality and on carbon uptake. Our spatially and temporally continuous upscaled GPP product drawing from both ground and satellite data over the Southwest region helps us understand linkages between the carbon and water cycles in semi-arid ecosystems and informs predictions of vegetation response to future climate conditions.

The influence of cyclic shear fatigue on the bracket-adhesive-enamel complex: an in vitro study.

PubMed

Daratsianos, Nikolaos; Musabegovic, Ena; Reimann, Susanne; Grüner, Manfred; Jäger, Andreas; Bourauel, Christoph

2013-05-01

To describe the effect of fatigue on the strength of the bracket-adhesive-enamel complex and characterize the fatigue behavior of the materials tested. Upper central incisor brackets (Discovery(®), Dentaurum) were bonded with a light-curing (Transbond XT™, 3M Unitek) and a chemically-curing adhesive (Concise™, 3M Unitek) on bovine teeth embedded in cylindrical resign bases and stored in water at 37(±2)°C for 24 (±2)h. The first 15 specimens were tested with a universal testing machine ZMART.PRO(®) (Zwick GmbH & Co. KG, Ulm, Germany) for ultimate shear bond strength according to the DIN-13990-2-standard. The remaining three groups of 20 specimens underwent fatigue staircase testing of 100, 1000 and 3000 cycles at 1Hz with a self-made testing machine. The survived specimens were subjected to shear strength testing. The fatigued specimens showed decreased shear strength with both adhesives at all cycle levels. The shear strength after fatigue for 100, 1000 and 3000 cycles was in the Concise™-groups 34.8%, 59.0%, 47.3% and in the Transbond™ XT-groups 33.6%, 23.1%, 27.3% relative to the ultimate shear strength. The fatigue life of the Concise™-groups decreased with increasing stress and Transbond™ XT showed lower fatigue ratio with no obvious trend. The specimens bonded with Transbond™ XT showed typically favorable fracture modes in contrary to Concise™. Fatigue of the bracket-adhesive-enamel complex decreased its shear strength. The staircase method can provide a standardized experimental protocol for fatigue studies, however testing at various cycle numbers is recommended. Copyright © 2013 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Measurement of Nanoparticles Release during Drilling of Polymer Nanocomposites

NASA Astrophysics Data System (ADS)

Gendre, L.; Marchante Rodriguez, V.; Abhyankar, H.; Blackburn, K.; Brighton, J. L.

2015-05-01

Nanomaterials are one of the promising technologies of this century. The Project on Emerging Nanotechnologies [1] reports more than 1600 consumer products based on nanotechnology that are currently on the market and advantages link to the reinforcement of polymeric materials using nano-fillers are not to demonstrate anymore. However, the concerns about safety and its consumer perception can slow down the acceptance of nanocomposites. Indeed, during its life-cycle, a nanotechnology-based product can release nano-sized particles exposing workers, consumers and environment and the risk involved in the use and disposal of such particles is not well known. The current legislation concerning chemicals and environment protection doesn't explicitly cover nanomaterials and changes undergone by nanoparticles during the products’ life cycle. Also, the possible physio-chemical changes that the nanoparticles may undergo during its life cycle are unknown. Industries need a standard method to evaluate nanoparticles release during products’ life cycle in order to improve the knowledge in nanomaterials risk assessment and the legislation, and to inform customers about the safety of nanomaterials and nanoproducts. This work aims to propose a replicable method in order to assess the release of nanoparticles during the machining of nanocomposites in a controlled environment. For this purpose, a new experimental set-up was implemented and issues observed in previous methods (background noise due to uncontrolled ambient environment and the process itself, unrepeatable machining parameters) were solved. A characterisation and validation of the chamber used is presented in this paper. Also, preliminary testing on drilling of polymer-based nanocomposites (Polyamide-6/Glass Fibre reinforced with nano-SiO2) manufactured by extrusion and injection moulding were achieved.

Predicting ground contact events for a continuum of gait types: An application of targeted machine learning using principal component analysis.

PubMed

Osis, Sean T; Hettinga, Blayne A; Ferber, Reed

2016-05-01

An ongoing challenge in the application of gait analysis to clinical settings is the standardized detection of temporal events, with unobtrusive and cost-effective equipment, for a wide range of gait types. The purpose of the current study was to investigate a targeted machine learning approach for the prediction of timing for foot strike (or initial contact) and toe-off, using only kinematics for walking, forefoot running, and heel-toe running. Data were categorized by gait type and split into a training set (∼30%) and a validation set (∼70%). A principal component analysis was performed, and separate linear models were trained and validated for foot strike and toe-off, using ground reaction force data as a gold-standard for event timing. Results indicate the model predicted both foot strike and toe-off timing to within 20ms of the gold-standard for more than 95% of cases in walking and running gaits. The machine learning approach continues to provide robust timing predictions for clinical use, and may offer a flexible methodology to handle new events and gait types. Copyright © 2016 Elsevier B.V. All rights reserved.

Machinability of CAD-CAM materials.

PubMed

Chavali, Ramakiran; Nejat, Amir H; Lawson, Nathaniel C

2017-08-01

Although new materials are available for computer-aided design and computer-aided manufacturing (CAD-CAM) fabrication, limited information is available regarding their machinability. The depth of penetration of a milling tool into a material during a timed milling cycle may indicate its machinability. The purpose of this in vitro study was to compare the tool penetration rate for 2 polymer-containing CAD-CAM materials (Lava Ultimate and Enamic) and 2 ceramic-based CAD-CAM materials (e.max CAD and Celtra Duo). The materials were sectioned into 4-mm-thick specimens (n=5/material) and polished with 320-grit SiC paper. Each specimen was loaded into a custom milling apparatus. The apparatus pushed the specimens against a milling tool (E4D Tapered 2016000) rotating at 40 000 RPM with a constant force of 0.98 N. After a 6-minute timed milling cycle, the length of each milling cut was measured with image analysis software under a digital light microscope. Representative specimens and milling tools were examined with scanning electron microscopy (SEM) and energy dispersive x-ray spectroscopy. The penetration rate of Lava Ultimate (3.21 ±0.46 mm/min) and Enamic (2.53 ±0.57 mm/min) was significantly greater than that of e.max CAD (1.12 ±0.32 mm/min) or Celtra Duo (0.80 ±0.21 mm/min) materials. SEM observations showed little tool damage, regardless of material type. Residual material was found on the tools used with polymer-containing materials, and wear of the embedding medium was seen on the tools used with the ceramic-based materials. Edge chipping was noted on cuts made in the ceramic-based materials. Lava Ultimate and Enamic have greater machinability and less edge chipping than e.max CAD and Celtra Duo. Copyright © 2016 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

Nonequilibrium quantum absorption refrigerator

NASA Astrophysics Data System (ADS)

Du, Jian-Ying; Zhang, Fu-Lin

2018-06-01

We study a quantum absorption refrigerator, in which a target qubit is cooled by two machine qubits in a nonequilibrium steady-state. It is realized by a strong internal coupling in the two-qubit fridge and a vanishing tripartite interaction among the whole system. The coherence of a machine virtual qubit is investigated as quantumness of the fridge. A necessary condition for cooling shows that the quantum coherence is beneficial to the nonequilibrium fridge, while it is detrimental as far as the maximum coefficient of performance (COP) and the COP at maximum power are concerned. Here, the COP is defined only in terms of heat currents caused by the tripartite interaction, with the one maintaining the two-qubit nonequilibrium state being excluded. The later can be considered to have no direct involvement in extracting heat from the target, as it is not affected by the tripartite interaction.

Versatile and Programmable DNA Logic Gates on Universal and Label-Free Homogeneous Electrochemical Platform.

PubMed

Ge, Lei; Wang, Wenxiao; Sun, Ximei; Hou, Ting; Li, Feng

2016-10-04

Herein, a novel universal and label-free homogeneous electrochemical platform is demonstrated, on which a complete set of DNA-based two-input Boolean logic gates (OR, NAND, AND, NOR, INHIBIT, IMPLICATION, XOR, and XNOR) is constructed by simply and rationally deploying the designed DNA polymerization/nicking machines without complicated sequence modulation. Single-stranded DNA is employed as the proof-of-concept target/input to initiate or prevent the DNA polymerization/nicking cyclic reactions on these DNA machines to synthesize numerous intact G-quadruplex sequences or binary G-quadruplex subunits as the output. The generated output strands then self-assemble into G-quadruplexes that render remarkable decrease to the diffusion current response of methylene blue and, thus, provide the amplified homogeneous electrochemical readout signal not only for the logic gate operations but also for the ultrasensitive detection of the target/input. This system represents the first example of homogeneous electrochemical logic operation. Importantly, the proposed homogeneous electrochemical logic gates possess the input/output homogeneity and share a constant output threshold value. Moreover, the modular design of DNA polymerization/nicking machines enables the adaptation of these homogeneous electrochemical logic gates to various input and output sequences. The results of this study demonstrate the versatility and universality of the label-free homogeneous electrochemical platform in the design of biomolecular logic gates and provide a potential platform for the further development of large-scale DNA-based biocomputing circuits and advanced biosensors for multiple molecular targets.

Feature extraction algorithm for space targets based on fractal theory

NASA Astrophysics Data System (ADS)

Tian, Balin; Yuan, Jianping; Yue, Xiaokui; Ning, Xin

2007-11-01

In order to offer a potential for extending the life of satellites and reducing the launch and operating costs, satellite servicing including conducting repairs, upgrading and refueling spacecraft on-orbit become much more frequently. Future space operations can be more economically and reliably executed using machine vision systems, which can meet real time and tracking reliability requirements for image tracking of space surveillance system. Machine vision was applied to the research of relative pose for spacecrafts, the feature extraction algorithm was the basis of relative pose. In this paper fractal geometry based edge extraction algorithm which can be used in determining and tracking the relative pose of an observed satellite during proximity operations in machine vision system was presented. The method gets the gray-level image distributed by fractal dimension used the Differential Box-Counting (DBC) approach of the fractal theory to restrain the noise. After this, we detect the consecutive edge using Mathematical Morphology. The validity of the proposed method is examined by processing and analyzing images of space targets. The edge extraction method not only extracts the outline of the target, but also keeps the inner details. Meanwhile, edge extraction is only processed in moving area to reduce computation greatly. Simulation results compared edge detection using the method which presented by us with other detection methods. The results indicate that the presented algorithm is a valid method to solve the problems of relative pose for spacecrafts.

Assessing the druggability of protein-protein interactions by a supervised machine-learning method.

PubMed

Sugaya, Nobuyoshi; Ikeda, Kazuyoshi

2009-08-25

Protein-protein interactions (PPIs) are challenging but attractive targets of small molecule drugs for therapeutic interventions of human diseases. In this era of rapid accumulation of PPI data, there is great need for a methodology that can efficiently select drug target PPIs by holistically assessing the druggability of PPIs. To address this need, we propose here a novel approach based on a supervised machine-learning method, support vector machine (SVM). To assess the druggability of the PPIs, 69 attributes were selected to cover a wide range of structural, drug and chemical, and functional information on the PPIs. These attributes were used as feature vectors in the SVM-based method. Thirty PPIs known to be druggable were carefully selected from previous studies; these were used as positive instances. Our approach was applied to 1,295 human PPIs with tertiary structures of their protein complexes already solved. The best SVM model constructed discriminated the already-known target PPIs from others at an accuracy of 81% (sensitivity, 82%; specificity, 79%) in cross-validation. Among the attributes, the two with the greatest discriminative power in the best SVM model were the number of interacting proteins and the number of pathways. Using the model, we predicted several promising candidates for druggable PPIs, such as SMAD4/SKI. As more PPI data are accumulated in the near future, our method will have increased ability to accelerate the discovery of druggable PPIs.

Satellite antenna management system and method

NASA Technical Reports Server (NTRS)

Leath, Timothy T (Inventor); Azzolini, John D (Inventor)

1999-01-01

The antenna management system and method allow a satellite to communicate with a ground station either directly or by an intermediary of a second satellite, thus permitting communication even when the satellite is not within range of the ground station. The system and method employ five major software components, which are the control and initialization module, the command and telemetry handler module, the contact schedule processor module, the contact state machining module, and the telemetry state machine module. The control and initialization module initializes the system and operates the main control cycle, in which the other modules are called. The command and telemetry handler module handles communication to and from the ground station. The contact scheduler processor module handles the contact entry schedules to allow scheduling of contacts with the second satellite. The contact and telemetry state machine modules handle the various states of the satellite in beginning, maintaining and ending contact with the second satellite and in beginning, maintaining and ending communication with the satellite.

Single Molecule Cluster Analysis Identifies Signature Dynamic Conformations along the Splicing Pathway

PubMed Central

Blanco, Mario R.; Martin, Joshua S.; Kahlscheuer, Matthew L.; Krishnan, Ramya; Abelson, John; Laederach, Alain; Walter, Nils G.

2016-01-01

The spliceosome is the dynamic RNA-protein machine responsible for faithfully splicing introns from precursor messenger RNAs (pre-mRNAs). Many of the dynamic processes required for the proper assembly, catalytic activation, and disassembly of the spliceosome as it acts on its pre-mRNA substrate remain poorly understood, a challenge that persists for many biomolecular machines. Here, we developed a fluorescence-based Single Molecule Cluster Analysis (SiMCAn) tool to dissect the manifold conformational dynamics of a pre-mRNA through the splicing cycle. By clustering common dynamic behaviors derived from selectively blocked splicing reactions, SiMCAn was able to identify signature conformations and dynamic behaviors of multiple ATP-dependent intermediates. In addition, it identified a conformation adopted late in splicing by a 3′ splice site mutant, invoking a mechanism for substrate proofreading. SiMCAn presents a novel framework for interpreting complex single molecule behaviors that should prove widely useful for the comprehensive analysis of a plethora of dynamic cellular machines. PMID:26414013

Automated Data Assimilation and Flight Planning for Multi-Platform Observation Missions

NASA Technical Reports Server (NTRS)

Oza, Nikunj; Morris, Robert A.; Strawa, Anthony; Kurklu, Elif; Keely, Leslie

2008-01-01

This is a progress report on an effort in which our goal is to demonstrate the effectiveness of automated data mining and planning for the daily management of Earth Science missions. Currently, data mining and machine learning technologies are being used by scientists at research labs for validating Earth science models. However, few if any of these advanced techniques are currently being integrated into daily mission operations. Consequently, there are significant gaps in the knowledge that can be derived from the models and data that are used each day for guiding mission activities. The result can be sub-optimal observation plans, lack of useful data, and wasteful use of resources. Recent advances in data mining, machine learning, and planning make it feasible to migrate these technologies into the daily mission planning cycle. We describe the design of a closed loop system for data acquisition, processing, and flight planning that integrates the results of machine learning into the flight planning process.

Development of a remote-controlled fatigue test machine using a laser extensometer for investigation of irradiation effect on fatigue properties

NASA Astrophysics Data System (ADS)

Yonekawa, M.; Ishii, T.; Ohmi, M.; Takada, F.; Hoshiya, T.; Niimi, M.; Ioka, I.; Miwa, Y.; Tsuji, H.

2002-12-01

In order to investigate effects of neutron irradiation on fatigue properties of nuclear materials, a remote-controlled high temperature fatigue test machine was developed at the hot laboratory of the Japan Materials Testing Reactor (JMTR) in the Japan Atomic Energy Research Institute (JAERI). A small-sized fatigue specimen having double blades to measure strain with a laser extensometer was designed for this machine. A strain amplitude in fatigue tests of a completely reversed push-pull type using a triangular wave was controlled with an accuracy of ±3% of the total strain range during test. Low cycle fatigue tests of type 304 stainless steel irradiated in JMTR at 823 K up to a fast neutron fluence of 1×10 25 n/m 2 ( E>1 MeV) were performed in total strain ranges of 0.7-1.4% at 823 K using the designed small-sized specimens.

Development of a tandem-electrostatic-quadrupole accelerator facility for BNCT.

PubMed

Kreiner, A J; Thatar Vento, V; Levinas, P; Bergueiro, J; Di Paolo, H; Burlon, A A; Kesque, J M; Valda, A A; Debray, M E; Somacal, H R; Minsky, D M; Estrada, L; Hazarabedian, A; Johann, F; Suarez Sandin, J C; Castell, W; Davidson, J; Davidson, M; Giboudot, Y; Repetto, M; Obligado, M; Nery, J P; Huck, H; Igarzabal, M; Fernandez Salares, A

2009-07-01

In this work we describe the present status of an ongoing project to develop a tandem-electrostatic-quadrupole (TESQ) accelerator facility for accelerator-based (AB) BNCT at the Atomic Energy Commission of Argentina in Buenos Aires. The project final goal is a machine capable of delivering 30 mA of 2.4 MeV protons to be used in conjunction with a neutron production target based on the (7)Li(p,n)(7)Be reaction slightly beyond its resonance at 2.25 MeV. These are the specifications needed to produce sufficiently intense and clean epithermal neutron beams, based on the (7)Li(p,n)(7)Be reaction, to perform BNCT treatment for deep-seated tumors in less than an hour. An electrostatic machine is the technologically simplest and cheapest solution for optimized AB-BNCT. The machine being designed and constructed is a folded TESQ with a high-voltage terminal at 1.2 MV intended to work in air. Such a machine is conceptually shown to be capable of transporting and accelerating a 30 mA proton beam to 2.4 MeV. The general geometric layout, its associated electrostatic fields, and the acceleration tube are simulated using a 3D finite element procedure. The design and construction of the ESQ modules is discussed and their electrostatic fields are investigated. Beam transport calculations through the accelerator are briefly mentioned. Likewise, work related to neutron production targets, strippers, beam shaping assembly and patient treatment room is briefly described.

National Ignition Facility Control and Information System Operational Tools

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marshall, C D; Beeler, R G; Bowers, G A

The National Ignition Facility (NIF) in Livermore, California, is the world's highest-energy laser fusion system and one of the premier large scale scientific projects in the United States. The system is designed to setup and fire a laser shot to a fusion ignition or high energy density target at rates up to a shot every 4 hours. NIF has 192 laser beams delivering up to 1.8 MJ of energy to a {approx}2 mm target that is planned to produce >100 billion atm of pressure and temperatures of >100 million degrees centigrade. NIF is housed in a ten-story building footprint themore » size of three football fields as shown in Fig. 1. Commissioning was recently completed and NIF will be formally dedicated at Lawrence Livermore National Laboratory on May 29, 2009. The control system has 60,000 hardware controls points and employs 2 million lines of control system code. The control room has highly automated equipment setup prior to firing laser system shots. This automation has a data driven implementation that is conducive to dynamic modification and optimization depending on the shot goals defined by the end user experimenters. NIF has extensive facility machine history and infrastructure maintenance workflow tools both under development and deployed. An extensive operational tools suite has been developed to support facility operations including experimental shot setup, machine readiness, machine health and safety, and machine history. The following paragraphs discuss the current state and future upgrades to these four categories of operational tools.« less

WORMHOLE: Novel Least Diverged Ortholog Prediction through Machine Learning

PubMed Central

Sutphin, George L.; Mahoney, J. Matthew; Sheppard, Keith; Walton, David O.; Korstanje, Ron

2016-01-01

The rapid advancement of technology in genomics and targeted genetic manipulation has made comparative biology an increasingly prominent strategy to model human disease processes. Predicting orthology relationships between species is a vital component of comparative biology. Dozens of strategies for predicting orthologs have been developed using combinations of gene and protein sequence, phylogenetic history, and functional interaction with progressively increasing accuracy. A relatively new class of orthology prediction strategies combines aspects of multiple methods into meta-tools, resulting in improved prediction performance. Here we present WORMHOLE, a novel ortholog prediction meta-tool that applies machine learning to integrate 17 distinct ortholog prediction algorithms to identify novel least diverged orthologs (LDOs) between 6 eukaryotic species—humans, mice, zebrafish, fruit flies, nematodes, and budding yeast. Machine learning allows WORMHOLE to intelligently incorporate predictions from a wide-spectrum of strategies in order to form aggregate predictions of LDOs with high confidence. In this study we demonstrate the performance of WORMHOLE across each combination of query and target species. We show that WORMHOLE is particularly adept at improving LDO prediction performance between distantly related species, expanding the pool of LDOs while maintaining low evolutionary distance and a high level of functional relatedness between genes in LDO pairs. We present extensive validation, including cross-validated prediction of PANTHER LDOs and evaluation of evolutionary divergence and functional similarity, and discuss future applications of machine learning in ortholog prediction. A WORMHOLE web tool has been developed and is available at http://wormhole.jax.org/. PMID:27812085

WORMHOLE: Novel Least Diverged Ortholog Prediction through Machine Learning.

PubMed

Sutphin, George L; Mahoney, J Matthew; Sheppard, Keith; Walton, David O; Korstanje, Ron

2016-11-01

The rapid advancement of technology in genomics and targeted genetic manipulation has made comparative biology an increasingly prominent strategy to model human disease processes. Predicting orthology relationships between species is a vital component of comparative biology. Dozens of strategies for predicting orthologs have been developed using combinations of gene and protein sequence, phylogenetic history, and functional interaction with progressively increasing accuracy. A relatively new class of orthology prediction strategies combines aspects of multiple methods into meta-tools, resulting in improved prediction performance. Here we present WORMHOLE, a novel ortholog prediction meta-tool that applies machine learning to integrate 17 distinct ortholog prediction algorithms to identify novel least diverged orthologs (LDOs) between 6 eukaryotic species-humans, mice, zebrafish, fruit flies, nematodes, and budding yeast. Machine learning allows WORMHOLE to intelligently incorporate predictions from a wide-spectrum of strategies in order to form aggregate predictions of LDOs with high confidence. In this study we demonstrate the performance of WORMHOLE across each combination of query and target species. We show that WORMHOLE is particularly adept at improving LDO prediction performance between distantly related species, expanding the pool of LDOs while maintaining low evolutionary distance and a high level of functional relatedness between genes in LDO pairs. We present extensive validation, including cross-validated prediction of PANTHER LDOs and evaluation of evolutionary divergence and functional similarity, and discuss future applications of machine learning in ortholog prediction. A WORMHOLE web tool has been developed and is available at http://wormhole.jax.org/.

Intense X-ray machine for penetrating radiography

NASA Astrophysics Data System (ADS)

Lucht, Roy A.; Eckhouse, Shimon

Penetrating radiography has been used for many years in the nuclear weapons research programs. Infrequently penetrating radiography has been used in conventional weapons research programs. For example the Los Alamos PHERMEX machine was used to view uranium rods penetrating steel for the GAU-8 program, and the Ector machine was used to see low density regions in forming metal jets. The armor/anti-armor program at Los Alamos has created a need for an intense flash X-ray machine that can be dedicated to conventional weapons research. The Balanced Technology Initiative, through DARPA, has funded the design and construction of such a machine at Los Alamos. It will be an 8- to 10-MeV diode machine capable of delivering a dose of 500 R at 1 m with a spot size of less than 5 mm. The machine used an 87.5-stage low inductance Marx generator that charges up a 7.4-(Omega), 32-ns water line. The water line is discharged through a self-breakdown oil switch into a 12.4-(Omega) water line that rings up the voltage into the high impendance X-ray diode. A long (233-cm) vacuum drift tube is used to separate the large diameter oil-insulated diode region from the X-ray source area that may be exposed to high overpressures by the explosive experiments. The electron beam is selffocused at the target area using a low pressure background gas.

The emerging role and targetability of the TCA cycle in cancer metabolism.

PubMed

Anderson, Nicole M; Mucka, Patrick; Kern, Joseph G; Feng, Hui

2018-02-01

The tricarboxylic acid (TCA) cycle is a central route for oxidative phosphorylation in cells, and fulfills their bioenergetic, biosynthetic, and redox balance requirements. Despite early dogma that cancer cells bypass the TCA cycle and primarily utilize aerobic glycolysis, emerging evidence demonstrates that certain cancer cells, especially those with deregulated oncogene and tumor suppressor expression, rely heavily on the TCA cycle for energy production and macromolecule synthesis. As the field progresses, the importance of aberrant TCA cycle function in tumorigenesis and the potentials of applying small molecule inhibitors to perturb the enhanced cycle function for cancer treatment start to evolve. In this review, we summarize current knowledge about the fuels feeding the cycle, effects of oncogenes and tumor suppressors on fuel and cycle usage, common genetic alterations and deregulation of cycle enzymes, and potential therapeutic opportunities for targeting the TCA cycle in cancer cells. With the application of advanced technology and in vivo model organism studies, it is our hope that studies of this previously overlooked biochemical hub will provide fresh insights into cancer metabolism and tumorigenesis, subsequently revealing vulnerabilities for therapeutic interventions in various cancer types.

Development and Validation of a Slurry Model for Chemical Hydrogen Storage in Fuel Cell Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brooks, Kriston P.; Pires, Richard P.; Simmons, Kevin L.

2014-07-25

The US Department of Energy's (DOE) Hydrogen Storage Engineering Center of Excellence (HSECoE) is developing models for hydrogen storage systems for fuel cell-based light duty vehicle applications for a variety of promising materials. These transient models simulate the performance of the storage system for comparison to the DOE’s Technical Targets and a set of four drive cycles. The purpose of this research is to describe the models developed for slurry-based chemical hydrogen storage materials. The storage systems of both a representative exothermic system based on ammonia borane and endothermic system based on alane were developed and modeled in Simulink®. Oncemore » complete the reactor and radiator components of the model were validated with experimental data. The model was then run using a highway cycle, an aggressive cycle, cold-start cycle and hot drive cycle. The system design was adjusted to meet these drive cycles. A sensitivity analysis was then performed to identify the range of material properties where these DOE targets and drive cycles could be met. Materials with a heat of reaction greater than 11 kJ/mol H2 generated and a slurry hydrogen capacity of greater than 11.4% will meet the on-board efficiency and gravimetric capacity targets, respectively.« less

Emissions-critical charge cooling using an organic rankine cycle

DOEpatents

Ernst, Timothy C.; Nelson, Christopher R.

2014-07-15

The disclosure provides a system including a Rankine power cycle cooling subsystem providing emissions-critical charge cooling of an input charge flow. The system includes a boiler fluidly coupled to the input charge flow, an energy conversion device fluidly coupled to the boiler, a condenser fluidly coupled to the energy conversion device, a pump fluidly coupled to the condenser and the boiler, an adjuster that adjusts at least one parameter of the Rankine power cycle subsystem to change a temperature of the input charge exiting the boiler, and a sensor adapted to sense a temperature characteristic of the vaporized input charge. The system includes a controller that can determine a target temperature of the input charge sufficient to meet or exceed predetermined target emissions and cause the adjuster to adjust at least one parameter of the Rankine power cycle to achieve the predetermined target emissions.

Chk1 and Cds1: linchpins of the DNA damage and replication checkpoint pathways

PubMed Central

Rhind, Nicholas; Russell, Paul

2010-01-01

SUMMARY Recent work on the mechanisms of DNA damage and replication cell cycle checkpoints has revealed great similarity between the checkpoint pathways of organisms as diverse as yeasts, flies and humans. However, there are differences in the ways these organisms regulate their cell cycles. To connect the conserved checkpoint pathways with various cell cycle targets requires an adaptable link that can target different cell cycle components in different organisms. The Chk1 and Cds1 protein kinases, downstream effectors in the checkpoint pathways, seem to play just such roles. Perhaps more surprisingly, the two kinases not only have different targets in different organisms but also seem to respond to different signals in different organisms. So, whereas in fission yeast Chk1 is required for the DNA damage checkpoint and Cds1 is specifically involved in the replication checkpoint, their roles seem to be shuffled in metazoans. PMID:11058076

Therapies based on targeting EBV lytic replication for EBV-associated malignancies.

PubMed

Li, Hongde; Hu, Jianmin; Luo, Xiangjian; Bode, Ann M; Dong, Zigang; Cao, Ya

2018-05-11

In recent years, EBV lytic infection has been shown to significantly contribute to carcinogenesis. Thus, therapies aimed at targeting the EBV lytic cycle have been developed as novel strategies for treatment of EBV-associated diseases malignancies. In this review, focusing on the viral lytic proteins, we describe recent advances regarding the involvement of the EBV lytic cycle in carcinogenesis. Moreover, we further discuss two distinct EBV lytic cycle-targeted therapeutic strategies against EBV-induced malignancies: One of the strategies involves inhibition of the EBV lytic cycle by natural compounds known to have anti-EBV properties; another one is to intentionally induce EBV lytic replication in combination with nucleotide analogues. Recent advances in EBV lytic-based strategies are beginning to show promise in the treatment and/or prevention of EBV-related tumors. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

SU-F-SPS-10: The Dosimetric Comparison of GammaKnife and Cyberknife Treatment Plans for Brain SRS Treatment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sanli, E; Mabhouti, H; Cebe, M

Purpose: Brain stereotactic radiosurgery (SRS) involves the use of precisely directed, single session radiation to create a desired radiobiologic response within the brain target with acceptable minimal effects on surrounding structures or tissues. In this study, the dosimetric comparison of GammaKnife perfection and Cyberknife M6 treatment plans were made. Methods: Treatment plannings were done for GammaKnife perfection unit using Gammaplan treatment planning system (TPS) on the CT scan of head and neck randophantom simulating the treatment of sterotactic treatments for one brain metastasis. The dose distribution were calculated using TMR 10 algorithm. The treatment planning for the same target weremore » also done for Cyberknife M6 machine using Multiplan (TPS) with Monte Carlo algorithm. Using the same film batch, the net OD to dose calibration curve was obtained using both machine by delivering 0- 800 cGy. Films were scanned 48 hours after irradiation using an Epson 1000XL flatbed scanner. Dose distribution were measured using EBT3 film dosimeter. The measured and calculated doses were compared. Results: The dose distribution in the target and 2 cm beyond the target edge were calculated on TPSs and measured using EBT3 film. For cyberknife treatment plans, the gamma analysis passing rates between measured and calculated dose distributions were 99.2% and 96.7% for target and peripheral region of target respectively. For gammaknife treatment plans, the gamma analysis passing rates were 98.9% and 93.2% for target and peripheral region of target respectively. Conclusion: The study shows that dosimetrically comparable plans are achievable with Cyberknife and GammaKnife. Although TMR 10 algorithm predicts the target dose.« less

Speech Segregation based on Binary Classification

DTIC Science & Technology

2016-07-15

including the IBM, the target binary mask (TBM), the IRM, the short -time Fourier transform spectral magnitude (FFT-MAG) and its corresponding mask (FFT...complementary features and a fixed DNN as the discriminative learning machine. For evaluation metrics, besides SNR, we use the Short -Time Objective...target analysis is a recent successful intelligibility test conducted on both normal-hearing (NH) and hearing-impaired (HI) listeners. The speech

Program Synthesizes UML Sequence Diagrams

NASA Technical Reports Server (NTRS)

Barry, Matthew R.; Osborne, Richard N.

2006-01-01

A computer program called "Rational Sequence" generates Universal Modeling Language (UML) sequence diagrams of a target Java program running on a Java virtual machine (JVM). Rational Sequence thereby performs a reverse engineering function that aids in the design documentation of the target Java program. Whereas previously, the construction of sequence diagrams was a tedious manual process, Rational Sequence generates UML sequence diagrams automatically from the running Java code.

Sensory Feedback for Lower Extremity Prostheses Incorporating Targeted Muscle Reinnervation (TMR)

DTIC Science & Technology

2017-10-01

hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and...map and characterize the sensory capabilities of lower extremity Targeted Reinnervation (TR) sites under tactile stimulation , and (2) Measure the...descent machine; developed new tactile stimulators that we expect to use in later stages of this project; and completed baseline studies to calibrate

The Relationship Between the Learning Style Perceptual Preferences of Urban Fourth Grade Children and the Acquisition of Selected Physical Science Concepts Through Learning Cycle Instructional Methodology.

NASA Astrophysics Data System (ADS)

Adams, Kenneth Mark

The purpose of this research was to investigate the relationship between the learning style perceptual preferences of fourth grade urban students and the attainment of selected physical science concepts for three simple machines as taught using learning cycle methodology. The sample included all fourth grade children from one urban elementary school (N = 91). The research design followed a quasi-experimental format with a single group, equivalent teacher demonstration and student investigation materials, and identical learning cycle instructional treatment. All subjects completed the Understanding Simple Machines Test (USMT) prior to instructional treatment, and at the conclusion of treatment to measure student concept attainment related to the pendulum, the lever and fulcrum, and the inclined plane. USMT pre and post-test scores, California Achievement Test (CAT-5) percentile scores, and Learning Style Inventory (LSI) standard scores for four perceptual elements for each subject were held in a double blind until completion of the USMT post-test. The hypothesis tested in this study was: Learning style perceptual preferences of fourth grade students as measured by the Dunn, Dunn, and Price Learning Style Inventory (LSI) are significant predictors of success in the acquisition of physical science concepts taught through use of the learning cycle. Analysis of pre and post USMT scores, 18.18 and 30.20 respectively, yielded a significant mean gain of +12.02. A controlled stepwise regression was employed to identify significant predictors of success on the USMT post-test from among USMT pre-test, four CAT-5 percentile scores, and four LSI perceptual standard scores. The CAT -5 Total Math and Total Reading accounted for 64.06% of the variance in the USMT post-test score. The only perceptual element to act as a significant predictor was the Kinesthetic standard score, accounting for 1.72% of the variance. The study revealed that learning cycle instruction does not appear to be sensitive to different perceptual preferences. Students with different preferences for auditory, visual, and tactile modalities, when learning, seem to benefit equally from learning cycle exposure. Increased use of a double blind for future learning styles research was recommended.

Assessing the role of syringe dispensing machines and mobile van outlets in reaching hard-to-reach and high-risk groups of injecting drug users (IDUs): a review

PubMed Central

Islam, Md Mofizul; Conigrave, Katherine M

2007-01-01

Reaching hard-to-reach and high-risk injecting drug users (IDUs) is one of the most important challenges for contemporary needle syringe programs (NSPs). The aim of this review is to examine, based upon the available international experience, the effectiveness of syringe vending machines and mobile van/bus based NSPs in making services more accessible to these hard-to-reach and high-risk groups of IDUs. A literature search revealed 40 papers/reports, of which 18 were on dispensing machines (including vending and exchange machines) and 22 on mobile vans. The findings demonstrate that syringe dispensing machines and mobile vans are promising modalities of NSPs, which can make services more accessible to the target group and in particular to the harder-to-reach and higher-risk groups of IDUs. Their anonymous and confidential approaches make services attractive, accessible and acceptable to these groups. These two outlets were found to be complementary to each other and to other modes of NSPs. Services through dispensing machines and mobile vans in strategically important sites are crucial elements in continuing efforts in reducing the spread of HIV and other blood borne viruses among IDUs. PMID:17958894

Using machine learning algorithms to guide rehabilitation planning for home care clients.

PubMed

Zhu, Mu; Zhang, Zhanyang; Hirdes, John P; Stolee, Paul

2007-12-20

Targeting older clients for rehabilitation is a clinical challenge and a research priority. We investigate the potential of machine learning algorithms - Support Vector Machine (SVM) and K-Nearest Neighbors (KNN) - to guide rehabilitation planning for home care clients. This study is a secondary analysis of data on 24,724 longer-term clients from eight home care programs in Ontario. Data were collected with the RAI-HC assessment system, in which the Activities of Daily Living Clinical Assessment Protocol (ADLCAP) is used to identify clients with rehabilitation potential. For study purposes, a client is defined as having rehabilitation potential if there was: i) improvement in ADL functioning, or ii) discharge home. SVM and KNN results are compared with those obtained using the ADLCAP. For comparison, the machine learning algorithms use the same functional and health status indicators as the ADLCAP. The KNN and SVM algorithms achieved similar substantially improved performance over the ADLCAP, although false positive and false negative rates were still fairly high (FP > .18, FN > .34 versus FP > .29, FN. > .58 for ADLCAP). Results are used to suggest potential revisions to the ADLCAP. Machine learning algorithms achieved superior predictions than the current protocol. Machine learning results are less readily interpretable, but can also be used to guide development of improved clinical protocols.

Effect of microstructure on the breakage of tin bronze machining chips during pulverization via jet milling

NASA Astrophysics Data System (ADS)

Afshari, Elham; Ghambari, Mohammad; Farhangi, Hasan

2016-11-01

In this study, jet milling was used to recycle tin bronze machining chips into powder. The main purpose of this study was to assess the effect of the microstructure of tin bronze machining chips on their breakage behavior. An experimental target jet mill was used to pulverize machining chips of three different tin bronze alloys containing 7wt%, 10wt%, and 12wt% of tin. Optical and electron microscopy, as well as sieve analysis, were used to follow the trend of pulverization. Each alloy exhibited a distinct rate of size reduction, particle size distribution, and fracture surface appearance. The results showed that the degree of pulverization substantially increased with increasing tin content. This behavior was attributed to the higher number of machining cracks as well as the increased volume fraction of brittle δ phase in the alloys with higher tin contents. The δ phase was observed to strongly influence the creation of machining cracks as well as the nucleation and propagation of cracks during jet milling. In addition, a direct relationship was observed between the mean δ-phase spacing and the mean size of the jet-milled product; i.e., a decrease in the δ-phase spacing resulted in smaller particles.

Application of Machine Learning to Proteomics Data: Classification and Biomarker Identification in Postgenomics Biology

PubMed Central

Swan, Anna Louise; Mobasheri, Ali; Allaway, David; Liddell, Susan

2013-01-01

Abstract Mass spectrometry is an analytical technique for the characterization of biological samples and is increasingly used in omics studies because of its targeted, nontargeted, and high throughput abilities. However, due to the large datasets generated, it requires informatics approaches such as machine learning techniques to analyze and interpret relevant data. Machine learning can be applied to MS-derived proteomics data in two ways. First, directly to mass spectral peaks and second, to proteins identified by sequence database searching, although relative protein quantification is required for the latter. Machine learning has been applied to mass spectrometry data from different biological disciplines, particularly for various cancers. The aims of such investigations have been to identify biomarkers and to aid in diagnosis, prognosis, and treatment of specific diseases. This review describes how machine learning has been applied to proteomics tandem mass spectrometry data. This includes how it can be used to identify proteins suitable for use as biomarkers of disease and for classification of samples into disease or treatment groups, which may be applicable for diagnostics. It also includes the challenges faced by such investigations, such as prediction of proteins present, protein quantification, planning for the use of machine learning, and small sample sizes. PMID:24116388

PMLB: a large benchmark suite for machine learning evaluation and comparison.

PubMed

Olson, Randal S; La Cava, William; Orzechowski, Patryk; Urbanowicz, Ryan J; Moore, Jason H

2017-01-01

The selection, development, or comparison of machine learning methods in data mining can be a difficult task based on the target problem and goals of a particular study. Numerous publicly available real-world and simulated benchmark datasets have emerged from different sources, but their organization and adoption as standards have been inconsistent. As such, selecting and curating specific benchmarks remains an unnecessary burden on machine learning practitioners and data scientists. The present study introduces an accessible, curated, and developing public benchmark resource to facilitate identification of the strengths and weaknesses of different machine learning methodologies. We compare meta-features among the current set of benchmark datasets in this resource to characterize the diversity of available data. Finally, we apply a number of established machine learning methods to the entire benchmark suite and analyze how datasets and algorithms cluster in terms of performance. From this study, we find that existing benchmarks lack the diversity to properly benchmark machine learning algorithms, and there are several gaps in benchmarking problems that still need to be considered. This work represents another important step towards understanding the limitations of popular benchmarking suites and developing a resource that connects existing benchmarking standards to more diverse and efficient standards in the future.

Effects of Maintenance on Quality of Performance of Cryotherapy Devices for Treatment of Precancerous Cervical Lesions.

PubMed

Maza, Mauricio; Figueroa, Ruben; Laskow, Bari; Juárez, Alexa; Alfaro, Karla; Alonzo, Todd A; Felix, Juan C; Gage, Julia C; Cremer, Miriam

2018-01-01

The aim of the study was to evaluate the impact of maintenance on performance of cryosurgical equipment used in El Salvador primary health clinics. Nine gynecological cryotherapy devices used in El Salvador were bench tested against a new machine of the same make and model. The devices were run for five successive double-freeze cycles. The El Salvador machines then received maintenance by a specialized engineer and another double-freeze cycle was performed. Temperature at the device probe tip was recorded throughout each cycle and ballistic gelatin was used as the tissue analogue to measure freeze ball dimensions achieved by the devices. Outcome measures were mean lowest-sustained temperatures and freeze ball mean weight, depth, and diameter. Paired and unpaired t tests were used to compare results premaintenance versus postmaintenance and postmaintenance versus the reference, respectively. Premaintenance versus postmaintenance freeze ball dimensions were significantly different (mean differences in weight = 2.31 g, p = .01; depth = 2.29 mm, p = .03; diameter = 3.51 mm, p = .02). However, postmaintenance dimensions were not significantly different than those of the reference (weight = 7.44 g vs. 8.39 g, p = .07; depth = 10.71 vs. 11.24 mm, p = .1; diameter = 31.38 mm vs. 32.05 mm, p = .3). Postmaintenance, minimum, and lowest-sustained temperatures were within the recommended clinical range. Specialized maintenance was necessary for heavily used cryotherapy devices to perform adequately, highlighting the challenges of gas-based cryotherapy in low- and middle-income countries.

Seed Germination and Seedling Growth under Simulated Microgravity Causes Alterations in Plant Cell Proliferation and Ribosome Biogenesis

NASA Astrophysics Data System (ADS)

Matía, Isabel; van Loon, Jack W. A.; Carnero-Díaz, Eugénie; Marco, Roberto; Medina, Francisco Javier

2009-01-01

The study of the modifications induced by altered gravity in functions of plant cells is a valuable tool for the objective of the survival of terrestrial organisms in conditions different from those of the Earth. We have used the system "cell proliferation-ribosome biogenesis", two inter-related essential cellular processes, with the purpose of studying these modifications. Arabidopsis seedlings belonging to a transformed line containing the reporter gene GUS under the control of the promoter of the cyclin gene CYCB1, a cell cycle regulator, were grown in a Random Positioning Machine, a device known to accurately simulate microgravity. Samples were taken at 2, 4 and 8 days after germination and subjected to biometrical analysis and cellular morphometrical, ultrastructural and immunocytochemical studies in order to know the rates of cell proliferation and ribosome biogenesis, plus the estimation of the expression of the cyclin gene, as an indication of the state of cell cycle regulation. Our results show that cells divide more in simulated microgravity in a Random Positioning Machine than in control gravity, but the cell cycle appears significantly altered as early as 2 days after germination. Furthermore, higher proliferation is not accompanied by an increase in ribosome synthesis, as is the rule on Earth, but the functional markers of this process appear depleted in simulated microgravity-grown samples. Therefore, the alteration of the gravitational environmental conditions results in a considerable stress for plant cells, including those not specialized in gravity perception.

Method of Data storing, collection and aggregation for definition of life-cycle resources of electromechanical equipment

NASA Astrophysics Data System (ADS)

Zhukovskiy, Y.; Koteleva, N.

2017-10-01

Analysis of technical and technological conditions for the emergence of emergency situations during the operation of electromechanical equipment of enterprises of the mineral and raw materials complex shows that when developing the basis for ensuring safe operation, it is necessary to take into account not only the technical condition, but also the non-stationary operation of the operating conditions of equipment, and the nonstationarity of operational operating parameters of technological processes. Violations of the operation of individual parts of the machine, not detected in time, can lead to severe accidents at work, as well as to unplanned downtime and loss of profits. That is why, the issues of obtaining and processing Big data obtained during the life cycle of electromechanical equipment, for assessing the current state of the electromechanical equipment used, timely diagnostics of emergency and pre-emergency modes of its operation, estimating the residual resource, as well as prediction the technical state on the basis of machine learning are very important. This article is dedicated to developing the special method of data storing, collection and aggregation for definition of life-cycle resources of electromechanical equipment. This method can be used in working with big data and can allow extracting the knowledge from different data types: the plants’ historical data and the factory historical data. The data of the plants contains the information about electromechanical equipment operation and the data of the factory contains the information about a production of electromechanical equipment.

Deep kernel learning method for SAR image target recognition

NASA Astrophysics Data System (ADS)

Chen, Xiuyuan; Peng, Xiyuan; Duan, Ran; Li, Junbao

2017-10-01

With the development of deep learning, research on image target recognition has made great progress in recent years. Remote sensing detection urgently requires target recognition for military, geographic, and other scientific research. This paper aims to solve the synthetic aperture radar image target recognition problem by combining deep and kernel learning. The model, which has a multilayer multiple kernel structure, is optimized layer by layer with the parameters of Support Vector Machine and a gradient descent algorithm. This new deep kernel learning method improves accuracy and achieves competitive recognition results compared with other learning methods.

Lessons learned from the development and manufacture of ceramic reusable surface insulation materials for the space shuttle orbiters

NASA Technical Reports Server (NTRS)

Banas, R. P.; Elgin, D. R.; Cordia, E. R.; Nickel, K. N.; Gzowski, E. R.; Aguiler, L.

1983-01-01

Three ceramic, reusable surface insulation materials and two borosilicate glass coatings were used in the fabrication of tiles for the Space Shuttle orbiters. Approximately 77,000 tiles were made from these materials for the first three orbiters, Columbia, Challenger, and Discovery. Lessons learned in the development, scale up to production and manufacturing phases of these materials will benefit future production of ceramic reusable surface insulation materials. Processing of raw materials into tile blanks and coating slurries; programming and machining of tiles using numerical controlled milling machines; preparing and spraying tiles with the two coatings; and controlling material shrinkage during the high temperature (2100-2275 F) coating glazing cycles are among the topics discussed.

Cell Cycle Inhibition To Treat Sleeping Sickness.

PubMed

Epting, Conrad L; Emmer, Brian T; Du, Nga Y; Taylor, Joann M; Makanji, Ming Y; Olson, Cheryl L; Engman, David M

2017-09-19

African trypanosomiasis is caused by infection with the protozoan parasite Trypanosoma brucei During infection, this pathogen divides rapidly to high density in the bloodstream of its mammalian host in a manner similar to that of leukemia. Like all eukaryotes, T. brucei has a cell cycle involving the de novo synthesis of DNA regulated by ribonucleotide reductase (RNR), which catalyzes the conversion of ribonucleotides into their deoxy form. As an essential enzyme for the cell cycle, RNR is a common target for cancer chemotherapy. We hypothesized that inhibition of RNR by genetic or pharmacological means would impair parasite growth in vitro and prolong the survival of infected animals. Our results demonstrate that RNR inhibition is highly effective in suppressing parasite growth both in vitro and in vivo These results support drug discovery efforts targeting the cell cycle, not only for African trypanosomiasis but possibly also for other infections by eukaryotic pathogens. IMPORTANCE The development of drugs to treat infections with eukaryotic pathogens is challenging because many key virulence factors have closely related homologues in humans. Drug toxicity greatly limits these development efforts. For pathogens that replicate at a high rate, especially in the blood, an alternative approach is to target the cell cycle directly, much as is done to treat some hematologic malignancies. The results presented here indicate that targeting the cell cycle via inhibition of ribonucleotide reductase is effective at killing trypanosomes and prolonging the survival of infected animals. Copyright © 2017 Epting et al.

Spin-filtering at COSY

NASA Astrophysics Data System (ADS)

Weidemann, Christian; PAX Collaboration

2011-05-01

The Spin Filtering experiments at COSY and AD at CERN within the framework of the Polarized Antiproton EXperiments (PAX) are proposed to determine the spin-dependent cross sections in bar pp scattering by observation of the buildup of polarization of an initially unpolarized stored antiproton beam after multiple passage through an internal polarized gas target. In order to commission the experimental setup for the AD and to understand the relevant machine parameters spin-filtering will first be done with protons at COSY. A first major step toward this goal has been achieved with the installation of the required mini-β section in summer 2009 and it's commissioning in January 2010. The target chamber together with the atomic beam source and the so-called Breit-Rabi polarimeter have been installed and commissioned in summer 2010. In addition an openable storage cell has been used. It provides a target thickness of 5·1013 atoms/cm2. We report on the status of spin-filtering experiments at COSY and the outcome of a recent beam time including studies on beam lifetime limitations like intra-beam scattering and the electron-cooling performance as well as machine acceptance studies.

First experimental evidence of hydrodynamic tunneling of ultra–relativistic protons in extended solid copper target at the CERN HiRadMat facility

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schmidt, R.; Grenier, D.; Wollmann, D.

2014-08-15

A novel experiment has been performed at the CERN HiRadMat test facility to study the impact of the 440 GeV proton beam generated by the Super Proton Synchrotron on extended solid copper cylindrical targets. Substantial hydrodynamic tunneling of the protons in the target material has been observed that leads to significant lengthening of the projectile range, which confirms our previous theoretical predictions [N. A. Tahir et al., Phys. Rev. Spec. Top.-Accel. Beams 15, 051003 (2012)]. Simulation results show very good agreement with the experimental measurements. These results have very important implications on the machine protection design for powerful machines like themore » Large Hadron Collider (LHC), the future High Luminosity LHC, and the proposed huge 80 km circumference Future Circular Collider, which is currently being discussed at CERN. Another very interesting outcome of this work is that one may also study the field of High Energy Density Physics at this test facility.« less

Using Support Vector Machine Ensembles for Target Audience Classification on Twitter

PubMed Central

Lo, Siaw Ling; Chiong, Raymond; Cornforth, David

2015-01-01

The vast amount and diversity of the content shared on social media can pose a challenge for any business wanting to use it to identify potential customers. In this paper, our aim is to investigate the use of both unsupervised and supervised learning methods for target audience classification on Twitter with minimal annotation efforts. Topic domains were automatically discovered from contents shared by followers of an account owner using Twitter Latent Dirichlet Allocation (LDA). A Support Vector Machine (SVM) ensemble was then trained using contents from different account owners of the various topic domains identified by Twitter LDA. Experimental results show that the methods presented are able to successfully identify a target audience with high accuracy. In addition, we show that using a statistical inference approach such as bootstrapping in over-sampling, instead of using random sampling, to construct training datasets can achieve a better classifier in an SVM ensemble. We conclude that such an ensemble system can take advantage of data diversity, which enables real-world applications for differentiating prospective customers from the general audience, leading to business advantage in the crowded social media space. PMID:25874768

Using support vector machine ensembles for target audience classification on Twitter.

PubMed

Lo, Siaw Ling; Chiong, Raymond; Cornforth, David

2015-01-01

The vast amount and diversity of the content shared on social media can pose a challenge for any business wanting to use it to identify potential customers. In this paper, our aim is to investigate the use of both unsupervised and supervised learning methods for target audience classification on Twitter with minimal annotation efforts. Topic domains were automatically discovered from contents shared by followers of an account owner using Twitter Latent Dirichlet Allocation (LDA). A Support Vector Machine (SVM) ensemble was then trained using contents from different account owners of the various topic domains identified by Twitter LDA. Experimental results show that the methods presented are able to successfully identify a target audience with high accuracy. In addition, we show that using a statistical inference approach such as bootstrapping in over-sampling, instead of using random sampling, to construct training datasets can achieve a better classifier in an SVM ensemble. We conclude that such an ensemble system can take advantage of data diversity, which enables real-world applications for differentiating prospective customers from the general audience, leading to business advantage in the crowded social media space.

Advanced composites: Fabrication processes for selected resin matrix materials

NASA Technical Reports Server (NTRS)

Welhart, E. K.

1976-01-01

This design note is based on present state of the art for epoxy and polyimide matrix composite fabrication technology. Boron/epoxy and polyimide and graphite/epoxy and polyimide structural parts can be successfully fabricated. Fabrication cycles for polyimide matrix composites have been shortened to near epoxy cycle times. Nondestructive testing has proven useful in detecting defects and anomalies in composite structure elements. Fabrication methods and tooling materials are discussed along with the advantages and disadvantages of different tooling materials. Types of honeycomb core, material costs and fabrication methods are shown in table form for comparison. Fabrication limits based on tooling size, pressure capabilities and various machining operations are also discussed.

Mechatronics Education: From Paper Design to Product Prototype Using LEGO NXT Parts

NASA Astrophysics Data System (ADS)

Lofaro, Daniel M.; Le, Tony Truong Giang; Oh, Paul

The industrial design cycle starts with design then simulation, prototyping, and testing. When the tests do not match the design requirements the design process is started over again. It is important for students to experience this process before they leave their academic institution. The high cost of the prototype phase, due to CNC/Rapid Prototype machine costs, makes hands on study of this process expensive for students and the academic institutions. This document shows that the commercially available LEGO NXT Robot kit is a viable low cost surrogate to the expensive industrial CNC/Rapid Prototype portion of the industrial design cycle.

Malone-brayton cycle engine/heat pump

NASA Astrophysics Data System (ADS)

Gilmour, Thomas A.

1994-07-01

A machine, such as a heat pump, and having an all liquid heat exchange fluid, operates over a more nearly ideal thermodynamic cycle by adjustment of the proportionality of the volumetric capacities of a compressor and an expander to approximate the proportionality of the densities of the liquid heat exchange fluid at the chosen working pressures. Preferred forms of a unit including both the compressor and the expander on a common shaft employs difference in axial lengths of rotary pumps of the gear or vane type to achieve the adjustment of volumetric capacity. Adjustment of the heat pump system for differing heat sink conditions preferably employs variable compression ratio pumps.

A multi-armed bandit approach to superquantile selection

DTIC Science & Technology

2017-06-01

decision learning, machine learning, intelligence processing, intelligence cycle, quantitative finance. 15. NUMBER OF PAGES 73 16. PRICE CODE 17...fulfillment of the requirements for the degree of MASTER OF SCIENCE IN OPERATIONS RESEARCH from the NAVAL POSTGRADUATE SCHOOL June 2017 Approved by...Roberto S. Szechtman Thesis Advisor Michael P. Atkinson Second Reader Patricia A. Jacobs Chair, Operations Research Department iii THIS PAGE

Production and Costs of the Chambers Delimbinator in First Thinning of Pine Plantations

Treesearch

Scott T. Mooney; Kevin D. Boston; W. Dale Greene

2000-01-01

Production and quality measures were collected and analyzed for a new chain-flail delimbing machine, Chambers Delimbinator, on two operations in central and southwestern Georgia. The first operation, Logger A, used two skidders and one loader while the second operation, Logger B, used two skidder and two loaders. Lobber B with the lower cycle time and larger piece...

40 CFR 63.323 - Test methods and monitoring.

Code of Federal Regulations, 2011 CFR

2011-07-01

... air-perchloroethylene gas-vapor stream on the outlet side of the refrigerated condenser on a dry-to-dry machine, dryer, or reclaimer with a temperature sensor to determine if it is equal to or less than 7.2 °C (45 °F) before the end of the cool-down or drying cycle while the gas-vapor stream is flowing...

40 CFR 63.323 - Test methods and monitoring.

Code of Federal Regulations, 2010 CFR

2010-07-01

... air-perchloroethylene gas-vapor stream on the outlet side of the refrigerated condenser on a dry-to-dry machine, dryer, or reclaimer with a temperature sensor to determine if it is equal to or less than 7.2 °C (45 °F) before the end of the cool-down or drying cycle while the gas-vapor stream is flowing...

78 FR 11148 - Large Residential Washers From Mexico and the Republic of Korea: Antidumping Duty Orders

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-15

... contains payment system electronics; \\7\\ (b) it is configured with an externally mounted steel frame at... drying machines that are built on a unitary frame and share a common console that controls both the... selected wash cycle setting; and (d) the console containing the user interface is made of steel and is...

77 FR 46715 - Large Residential Washers From the Republic of Korea: Amendment to the Scope of the...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-06

... contains payment system electronics; \\12\\ (b) it is configured with an externally mounted steel frame at... distinct washing and drying machines that are built on a unitary frame and share a common console that... wash cycle setting; and (d) the console containing the user interface is made of steel and is assembled...

Evaluating Data Clustering Approach for Life-Cycle Facility Control

DTIC Science & Technology

2013-04-01

produce 90% matching accuracy with noise/variations up to 55%. KEYWORDS: Building Information Modelling ( BIM ), machine learning, pattern detection...reconciled to building information model elements and ultimately to an expected resource utilization schedule. The motivation for this integration is to...by interoperable data sources and building information models . Building performance modelling and simulation efforts such as those by Maile et al

Structural health monitoring of wind turbine blades

NASA Astrophysics Data System (ADS)

Rumsey, Mark A.; Paquette, Joshua A.

2008-03-01

As electric utility wind turbines increase in size, and correspondingly, increase in initial capital investment cost, there is an increasing need to monitor the health of the structure. Acquiring an early indication of structural or mechanical problems allows operators to better plan for maintenance, possibly operate the machine in a de-rated condition rather than taking the unit off-line, or in the case of an emergency, shut the machine down to avoid further damage. This paper describes several promising structural health monitoring (SHM) techniques that were recently exercised during a fatigue test of a 9 meter glass-epoxy and carbon-epoxy wind turbine blade. The SHM systems were implemented by teams from NASA Kennedy Space Center, Purdue University and Virginia Tech. A commercial off-the-shelf acoustic emission (AE) NDT system gathered blade AE data throughout the test. At a fatigue load cycle rate around 1.2 Hertz, and after more than 4,000,000 fatigue cycles, the blade was diagnostically and visibly failing at the out-board blade spar-cap termination point at 4.5 meters. For safety reasons, the test was stopped just before the blade completely failed. This paper provides an overview of the SHM and NDT system setups and some current test results.

Energy-saving compression valve of the rock drill

NASA Astrophysics Data System (ADS)

Glazov, A. N.; Efanov, A. A.; Aikina, T. Yu

2015-11-01

The relevance of the research is due to the necessity to create pneumatic rock drills with low air consumption. The article analyzes the reasons for low efficiency of percussive machines. The authors state that applying a single distribution body in the percussive mechanism does not allow carrying out a low-energy operating cycle of the mechanism. Using the studied device as an example, it is substantiated that applying a compression valve with two distribution bodies separately operating the working chambers makes it possible to significantly reduce the airflow. The authors describe the construction of a core drill percussive mechanism and the operation of a compression valve. It is shown that in the new percussive mechanism working chambers are cut off the circuit by the time when exhaust windows are opened by the piston and air is not supplied into the cylinder up to 20% of the cycle time. The air flow rate of the new mechanism was 3.8 m3/min. In comparison with the drill PK-75, the overall noise level of the new machine is lower by 8-10 dB, while the percussive mechanism efficiency is 2.3 times higher.

Advanced single permanent magnet axipolar ironless stator ac motor for electric passenger vehicles

NASA Technical Reports Server (NTRS)

Beauchamp, E. D.; Hadfield, J. R.; Wuertz, K. L.

1983-01-01

A program was conducted to design and develop an advanced-concept motor specifically created for propulsion of electric vehicles with increased range, reduced energy consumption, and reduced life-cycle costs in comparison with conventional systems. The motor developed is a brushless, dc, rare-earth cobalt, permanent magnet, axial air gap inductor machine that uses an ironless stator. Air cooling is inherent provided by the centrifugal-fan action of the rotor poles. An extensive design phase was conducted, which included analysis of the system performance versus the SAE J227a(D) driving cycle. A proof-of-principle model was developed and tested, and a functional model was developed and tested. Full generator-level testing was conducted on the functional model, recording electromagnetic, thermal, aerodynamic, and acoustic noise data. The machine demonstrated 20.3 kW output at 1466 rad/s and 160 dc. The novel ironless stator demonstated the capability to continuously operate at peak current. The projected system performance based on the use of a transistor inverter is 23.6 kW output power at 1466 rad/s and 83.3 percent efficiency. Design areas of concern regarding electric vehicle applications include the inherently high windage loss and rotor inertia.

Deceleration system for kinematic linkages of positioning

NASA Astrophysics Data System (ADS)

Stan, G.

2017-08-01

Flexible automation is used more and more in various production processes, so that both machining itself on CNC machine tools and workpiece handling means are performed through programming the needed working cycle. In order to obtain a successful precise positioning, each motion degree needs a certain deceleration before stopping at a programmed point. The increase of motion speed of moving elements within the manipulators structure depends directly on deceleration duty quality before the programmed stop. Proportional valves as well as servo-valves that can perform hydraulic decelerations are well known, but they feature several disadvantages, such as: high price, severe conditions for oil filtering and low reliability under industrial conditions. This work presents a new deceleration system that allows adjustment of deceleration slope according to actual conditions: inertial mass, speed etc. The new solution of hydraulic decelerator allows its integration to a position loop or its usage in case of positioning large elements that only perform fixed cycles. The results being obtained on the positioning accuracy of a linear axis using the new solution of the hydraulic decelerator are presented, too. The price of the new deceleration system is much lower compared to the price of proportional valves or servo-valves.

A novel magneto-DNA duplex probe for bacterial DNA detection based on exonuclease III-aided cycling amplification.

PubMed

Zeng, Yan; Wan, Yi; Zhang, Dun; Qi, Peng

2015-01-01

A novel magneto-DNA duplex probe for bacterial DNA detection based on exonuclease III (Exo-III) aided cycling amplification has been developed. This magneto-DNA duplex probe contains a partly hybrid fluorophore-modified capture probe and a fluorophore-modified signal probe with magnetic microparticle as carrier. In the presence of a perfectly matched target bacterial DNA, blunt 3'-terminus of the capture probe is formed, activating the Exo-III aided cycling amplification. Thus, Exo-III catalyzes the stepwise removal of mononucleotides from this terminus, releasing both fluorophore-modified signal probe, fluorescent dyes of the capture probe and target DNA. The released target DNA then starts a new cycle, while released fluorescent fragments are recovered with magnetic separation for fluorescence signal collection. This system exhibited sensitive detection of bacterial DNA, with a detection limit of 14 pM because of the unique cleavage function of Exo-III, high fluorescence intensity, and separating function of magneto-DNA duplex probes. Besides this sensitivity, this strategy exhibited excellent selectivity with mismatched bacterial DNA targets and other bacterial species targets and good applicability in real seawater samples, hence, this strategy could be potentially used for qualitative and quantitative analysis of bacteria. Copyright © 2014 Elsevier B.V. All rights reserved.

Model-Driven Engineering of Machine Executable Code

NASA Astrophysics Data System (ADS)

Eichberg, Michael; Monperrus, Martin; Kloppenburg, Sven; Mezini, Mira

Implementing static analyses of machine-level executable code is labor intensive and complex. We show how to leverage model-driven engineering to facilitate the design and implementation of programs doing static analyses. Further, we report on important lessons learned on the benefits and drawbacks while using the following technologies: using the Scala programming language as target of code generation, using XML-Schema to express a metamodel, and using XSLT to implement (a) transformations and (b) a lint like tool. Finally, we report on the use of Prolog for writing model transformations.